Automatic alignment of pre- and post-interventional liver CT images for assessment of radiofrequency ablation

NASA Astrophysics Data System (ADS)

Rieder, Christian; Wirtz, Stefan; Strehlow, Jan; Zidowitz, Stephan; Bruners, Philipp; Isfort, Peter; Mahnken, Andreas H.; Peitgen, Heinz-Otto

2012-02-01

Image-guided radiofrequency ablation (RFA) is becoming a standard procedure for minimally invasive tumor treatment in clinical practice. To verify the treatment success of the therapy, reliable post-interventional assessment of the ablation zone (coagulation) is essential. Typically, pre- and post-interventional CT images have to be aligned to compare the shape, size, and position of tumor and coagulation zone. In this work, we present an automatic workflow for masking liver tissue, enabling a rigid registration algorithm to perform at least as accurate as experienced medical experts. To minimize the effect of global liver deformations, the registration is computed in a local region of interest around the pre-interventional lesion and post-interventional coagulation necrosis. A registration mask excluding lesions and neighboring organs is calculated to prevent the registration algorithm from matching both lesion shapes instead of the surrounding liver anatomy. As an initial registration step, the centers of gravity from both lesions are aligned automatically. The subsequent rigid registration method is based on the Local Cross Correlation (LCC) similarity measure and Newton-type optimization. To assess the accuracy of our method, 41 RFA cases are registered and compared with the manually aligned cases from four medical experts. Furthermore, the registration results are compared with ground truth transformations based on averaged anatomical landmark pairs. In the evaluation, we show that our method allows to automatic alignment of the data sets with equal accuracy as medical experts, but requiring significancy less time consumption and variability.

Correction factor for ablation algorithms used in corneal refractive surgery with gaussian-profile beams

NASA Astrophysics Data System (ADS)

Jimenez, Jose Ramón; González Anera, Rosario; Jiménez del Barco, Luis; Hita, Enrique; Pérez-Ocón, Francisco

2005-01-01

We provide a correction factor to be added in ablation algorithms when a Gaussian beam is used in photorefractive laser surgery. This factor, which quantifies the effect of pulse overlapping, depends on beam radius and spot size. We also deduce the expected post-surgical corneal radius and asphericity when considering this factor. Data on 141 eyes operated on LASIK (laser in situ keratomileusis) with a Gaussian profile show that the discrepancy between experimental and expected data on corneal power is significantly lower when using the correction factor. For an effective improvement of post-surgical visual quality, this factor should be applied in ablation algorithms that do not consider the effects of pulse overlapping with a Gaussian beam.

RFA-cut: Semi-automatic segmentation of radiofrequency ablation zones with and without needles via optimal s-t-cuts.

PubMed

Egger, Jan; Busse, Harald; Brandmaier, Philipp; Seider, Daniel; Gawlitza, Matthias; Strocka, Steffen; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Kainz, Bernhard; Chen, Xiaojun; Hann, Alexander; Boechat, Pedro; Yu, Wei; Freisleben, Bernd; Alhonnoro, Tuomas; Pollari, Mika; Moche, Michael; Schmalstieg, Dieter

2015-01-01

In this contribution, we present a semi-automatic segmentation algorithm for radiofrequency ablation (RFA) zones via optimal s-t-cuts. Our interactive graph-based approach builds upon a polyhedron to construct the graph and was specifically designed for computed tomography (CT) acquisitions from patients that had RFA treatments of Hepatocellular Carcinomas (HCC). For evaluation, we used twelve post-interventional CT datasets from the clinical routine and as evaluation metric we utilized the Dice Similarity Coefficient (DSC), which is commonly accepted for judging computer aided medical segmentation tasks. Compared with pure manual slice-by-slice expert segmentations from interventional radiologists, we were able to achieve a DSC of about eighty percent, which is sufficient for our clinical needs. Moreover, our approach was able to handle images containing (DSC=75.9%) and not containing (78.1%) the RFA needles still in place. Additionally, we found no statistically significant difference (p<;0.423) between the segmentation results of the subgroups for a Mann-Whitney test. Finally, to the best of our knowledge, this is the first time a segmentation approach for CT scans including the RFA needles is reported and we show why another state-of-the-art segmentation method fails for these cases. Intraoperative scans including an RFA probe are very critical in the clinical practice and need a very careful segmentation and inspection to avoid under-treatment, which may result in tumor recurrence (up to 40%). If the decision can be made during the intervention, an additional ablation can be performed without removing the entire needle. This decreases the patient stress and associated risks and costs of a separate intervention at a later date. Ultimately, the segmented ablation zone containing the RFA needle can be used for a precise ablation simulation as the real needle position is known.

Development of an algorithm for corneal reshaping with a scanning laser beam

NASA Astrophysics Data System (ADS)

Shen, Jin-Hui; Söderberg, Per; Matsui, Takaaki; Manns, Fabrice; Parel, Jean-Marie

1995-07-01

The corneal-ablation rate, the beam-intensity distribution, and the initial and the desired corneal topographies are used to calculate a spatial distribution map of laser pulses. The optimal values of the parameters are determined with a computer model, for a system that produces 213-nm radiation with a Gaussian beam-intensity distribution and a peak radiant exposure of 400 mJ/cm2. The model shows that with a beam diameter of 0.5 mm, an overlap of 80%, and a 5-mm treatment zone, the roughness is less than 6% of the central ablation depth, the refractive error after correction is less than 0.1 D for corrections of myopia of 1, 3, and 6 D and less than 0.4 D for a correction of myopia of 10 D, and the number of pulses per diopter of

A diagnostic algorithm to optimize data collection and interpretation of Ripple Maps in atrial tachycardias.

PubMed

Koa-Wing, Michael; Nakagawa, Hiroshi; Luther, Vishal; Jamil-Copley, Shahnaz; Linton, Nick; Sandler, Belinda; Qureshi, Norman; Peters, Nicholas S; Davies, D Wyn; Francis, Darrel P; Jackman, Warren; Kanagaratnam, Prapa

2015-11-15

Ripple Mapping (RM) is designed to overcome the limitations of existing isochronal 3D mapping systems by representing the intracardiac electrogram as a dynamic bar on a surface bipolar voltage map that changes in height according to the electrogram voltage-time relationship, relative to a fiduciary point. We tested the hypothesis that standard approaches to atrial tachycardia CARTO™ activation maps were inadequate for RM creation and interpretation. From the results, we aimed to develop an algorithm to optimize RMs for future prospective testing on a clinical RM platform. CARTO-XP™ activation maps from atrial tachycardia ablations were reviewed by two blinded assessors on an off-line RM workstation. Ripple Maps were graded according to a diagnostic confidence scale (Grade I - high confidence with clear pattern of activation through to Grade IV - non-diagnostic). The RM-based diagnoses were corroborated against the clinical diagnoses. 43 RMs from 14 patients were classified as Grade I (5 [11.5%]); Grade II (17 [39.5%]); Grade III (9 [21%]) and Grade IV (12 [28%]). Causes of low gradings/errors included the following: insufficient chamber point density; window-of-interest<100% of cycle length (CL); <95% tachycardia CL mapped; variability of CL and/or unstable fiducial reference marker; and suboptimal bar height and scar settings. A data collection and map interpretation algorithm has been developed to optimize Ripple Maps in atrial tachycardias. This algorithm requires prospective testing on a real-time clinical platform. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Effective learning strategies for real-time image-guided adaptive control of multiple-source hyperthermia applicators.

PubMed

Cheng, Kung-Shan; Dewhirst, Mark W; Stauffer, Paul R; Das, Shiva

2010-03-01

This paper investigates overall theoretical requirements for reducing the times required for the iterative learning of a real-time image-guided adaptive control routine for multiple-source heat applicators, as used in hyperthermia and thermal ablative therapy for cancer. Methods for partial reconstruction of the physical system with and without model reduction to find solutions within a clinically practical timeframe were analyzed. A mathematical analysis based on the Fredholm alternative theorem (FAT) was used to compactly analyze the existence and uniqueness of the optimal heating vector under two fundamental situations: (1) noiseless partial reconstruction and (2) noisy partial reconstruction. These results were coupled with a method for further acceleration of the solution using virtual source (VS) model reduction. The matrix approximation theorem (MAT) was used to choose the optimal vectors spanning the reduced-order subspace to reduce the time for system reconstruction and to determine the associated approximation error. Numerical simulations of the adaptive control of hyperthermia using VS were also performed to test the predictions derived from the theoretical analysis. A thigh sarcoma patient model surrounded by a ten-antenna phased-array applicator was retained for this purpose. The impacts of the convective cooling from blood flow and the presence of sudden increase of perfusion in muscle and tumor were also simulated. By FAT, partial system reconstruction directly conducted in the full space of the physical variables such as phases and magnitudes of the heat sources cannot guarantee reconstructing the optimal system to determine the global optimal setting of the heat sources. A remedy for this limitation is to conduct the partial reconstruction within a reduced-order subspace spanned by the first few maximum eigenvectors of the true system matrix. By MAT, this VS subspace is the optimal one when the goal is to maximize the average tumor temperature. When more than 6 sources present, the steps required for a nonlinear learning scheme is theoretically fewer than that of a linear one, however, finite number of iterative corrections is necessary for a single learning step of a nonlinear algorithm. Thus, the actual computational workload for a nonlinear algorithm is not necessarily less than that required by a linear algorithm. Based on the analysis presented herein, obtaining a unique global optimal heating vector for a multiple-source applicator within the constraints of real-time clinical hyperthermia treatments and thermal ablative therapies appears attainable using partial reconstruction with minimum norm least-squares method with supplemental equations. One way to supplement equations is the inclusion of a method of model reduction.

Novel implications in the treatment of hepatocellular carcinoma

PubMed Central

Best, Jan; Schotten, Clemens; Theysohn, Jens M.; Wetter, Axel; Müller, Stefan; Radünz, Sonia; Schulze, Maren; Canbay, Ali; Dechêne, Alexander; Gerken, Guido

2017-01-01

Worldwide hepatocellular carcinoma remains one of the leading causes of cancer-related death, associated with a poor prognosis due to late diagnosis in the majority of cases. Physicians at care are frequently confronted with patients who are ineligible for curative treatment such as liver resection, transplantation or radiofrequency ablation. Besides established palliative locoregional therapies, such as ablation or chemoembolization, new treatment options, such as microwave ablation, drug-eluting bead transarterial chemoembolization or selective internal radiation therapy, are emerging; however, data from randomized controlled trials are still lacking. In order to achieve optimal tumor control, patients should receive tailored treatment concepts, considering their tumor burden, liver function and performance status, instead of strictly assigning patients to treatment modalities following algorithms that may be partly very restrictive. Palliative locoregional pretreatment might facilitate downstaging to ensure later curative resection or transplantation. In addition, the combined utilization of different locoregional treatment options or systemic co-treatment has been the subject of several trials. In cases where local tumor control cannot be achieved, or in the scenario of extrahepatic spread, sorafenib remains the only approved systemic therapy option. Alternative targeted therapies, such as immune checkpoint inhibitors have shown encouraging preliminary results, while data from phase III studies are pending. PMID:28042235

Optimization of gas-filled quartz capillary discharge waveguide for high-energy laser wakefield acceleration

NASA Astrophysics Data System (ADS)

Qin, Zhiyong; Li, Wentao; Liu, Jiansheng; Liu, Jiaqi; Yu, Changhai; Wang, Wentao; Qi, Rong; Zhang, Zhijun; Fang, Ming; Feng, Ke; Wu, Ying; Ke, Lintong; Chen, Yu; Wang, Cheng; Li, Ruxin; Xu, Zhizhan

2018-04-01

A hydrogen-filled capillary discharge waveguide made of quartz is presented for high-energy laser wakefield acceleration (LWFA). The experimental parameters (discharge current and gas pressure) were optimized to mitigate ablation by a quantitative analysis of the ablation plasma density inside the hydrogen-filled quartz capillary. The ablation plasma density was obtained by combining a spectroscopic measurement method with a calibrated gas transducer. In order to obtain a controllable plasma density and mitigate the ablation as much as possible, the range of suitable parameters was investigated. The experimental results demonstrated that the ablation in the quartz capillary could be mitigated by increasing the gas pressure to ˜7.5-14.7 Torr and decreasing the discharge current to ˜70-100 A. These optimized parameters are promising for future high-energy LWFA experiments based on the quartz capillary discharge waveguide.

Rear-side picosecond laser ablation of indium tin oxide micro-grooves

NASA Astrophysics Data System (ADS)

Liu, Peng; Wang, Wenjun; Mei, Xuesong; Liu, Bin; Zhao, Wanqin

2015-06-01

A comparative study of the fabrication of micro-grooves in indium tin oxide films by picosecond laser ablation for application in thin film solar cells is presented, evaluating the variation of different process parameters. Compared with traditional front-side ablation, rear-side ablation results in thinner grooves with varying laser power at a certain scan speed. In particular, and in contrast to front-side ablation, the width of the micro-grooves remains unchanged when the scan speed was changed. Thus, the micro-groove quality can be optimized by adjusting the scan speed while the groove width would not be affected. Furthermore, high-quality micro-grooves with ripple free surfaces and steep sidewalls could only be achieved when applying rear-side ablation. Finally, the formation mechanism of micro-cracks on the groove rims during rear-side ablation is analyzed and the cracks can be almost entirely eliminated by an optimization of the scan speed.

A Boundary Condition Relaxation Algorithm for Strongly Coupled, Ablating Flows Including Shape Change

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.; Johnston, Christopher O.

2011-01-01

Implementations of a model for equilibrium, steady-state ablation boundary conditions are tested for the purpose of providing strong coupling with a hypersonic flow solver. The objective is to remove correction factors or film cooling approximations that are usually applied in coupled implementations of the flow solver and the ablation response. Three test cases are considered - the IRV-2, the Galileo probe, and a notional slender, blunted cone launched at 10 km/s from the Earth's surface. A successive substitution is employed and the order of succession is varied as a function of surface temperature to obtain converged solutions. The implementation is tested on a specified trajectory for the IRV-2 to compute shape change under the approximation of steady-state ablation. Issues associated with stability of the shape change algorithm caused by explicit time step limits are also discussed.

Factors affecting optimal linear endovenous energy density for endovenous laser ablation in incompetent lower limb truncal veins - A review of the clinical evidence.

PubMed

Cowpland, Christine A; Cleese, Amy L; Whiteley, Mark S

2017-06-01

Objectives The objective is to identify the factors that affect the optimal linear endovenous energy density (LEED) to ablate incompetent truncal veins. Methods We performed a literature review of clinical studies, which reported truncal vein ablation rates and LEED. A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) flow diagram documents the search strategy. We analysed 13 clinical papers which fulfilled the criteria to be able to compare results of great saphenous vein occlusion as defined by venous duplex ultrasound, with the LEED used in the treatment. Results Evidence suggests that the optimal LEED for endovenous laser ablation of the great saphenous vein is >80 J/cm and <100 J/cm in terms of optimal closure rates with minimal side-effects and complications. Longer wavelengths targeting water might have a lower optimal LEED. A LEED <60 J/cm has reduced efficacy regardless of wavelength. The optimal LEED may vary with vein diameter and may be reduced by using specially shaped fibre tips. Laser delivery technique and type as well as the duration time of energy delivery appear to play a role in determining LEED. Conclusion The optimal LEED to ablate an incompetent great saphenous vein appears to be >80 J/cm and <95 J/cm based on current evidence for shorter wavelength lasers. There is evidence that longer wavelength lasers may be effective at LEEDs of <85 J/cm.

An integrated multidisciplinary algorithm for the management of spinal metastases: an International Spine Oncology Consortium report.

PubMed

Spratt, Daniel E; Beeler, Whitney H; de Moraes, Fabio Y; Rhines, Laurence D; Gemmete, Joseph J; Chaudhary, Neeraj; Shultz, David B; Smith, Sean R; Berlin, Alejandro; Dahele, Max; Slotman, Ben J; Younge, Kelly C; Bilsky, Mark; Park, Paul; Szerlip, Nicholas J

2017-12-01

Spinal metastases are becoming increasingly common because patients with metastatic disease are living longer. The close proximity of the spinal cord to the vertebral column limits many conventional therapeutic options that can otherwise be used to treat cancer. In response to this problem, an innovative multidisciplinary approach has been developed for the management of spinal metastases, leveraging the capabilities of image-guided stereotactic radiosurgery, separation surgery, vertebroplasty, and minimally invasive local ablative approaches. In this Review, we discuss the variables that should be considered during the management of these patients and review the role of each discipline and their respective management options to provide optimal care. This work is synthesised into a practical algorithm to aid clinicians in the management of patients with spinal metastasis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ion acceleration enhanced by target ablation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, S.; State Key Laboratory of Nuclear Physics and Technology, and Key Lab of HEDPS, CAPT, Peking University, Beijing 100871; Institute of Radiation, Helmholtz-Zentrum Dresden-Rossendorf, 01314 Dresden

2015-07-15

Laser proton acceleration can be enhanced by using target ablation, due to the energetic electrons generated in the ablation preplasma. When the ablation pulse matches main pulse, the enhancement gets optimized because the electrons' energy density is highest. A scaling law between the ablation pulse and main pulse is confirmed by the simulation, showing that for given CPA pulse and target, proton energy improvement can be achieved several times by adjusting the target ablation.

Intra-operative feedback and dynamic compensation for image-guided robotic focal ultrasound surgery.

PubMed

Chauhan, S; Amir, H; Chen, G; Hacker, A; Michel, M S; Koehrmann, K U

2008-11-01

This paper describes a non-invasive remote temperature measurement technique integrated with a biomechatronic surgery system devised in our laboratory and named FUSBOT (Focal Ultrasound Surgery RoBOT). FUSBOTs use High-Intensity Focused Ultrasound (HIFU) for ablation of cancers/tumors and targets accessible through various soft-tissue acoustic windows in the human body. The focused ultrasound beam parameters are chosen so that biologically significant temperature rises are achieved only within the focal volume. In this paper, FUSBOT(BS), a customized system for breast surgery, is taken as a representative example to demonstrate the implementation and the results of non-invasive feedback during ablation. An 8-axis PC-based controller controls various sub-sections of the system within a safe constrained work envelope. Temperature is a prime target parameter in ablative procedures, and it is of paramount importance that means should be devised for its measurement and control in order to design optimal dose protocols and judge the efficacy of FUS systems. A customized sensory interface is devised and integrated with FUSBOT(BS), and dedicated software algorithms are embedded for surgical planning based on real-time guidance and feedback. Variations in the physical parameters of the tissue interacting with the incident modality are used as surgical feedback. The use of real-time ultrasound imaging and data processed from various sensors to deduce lesion position and thermal feedback during surgery, as integrated with the robotic system for online surgical planning, is described. Dynamic registration algorithms are developed for compensation and re-registration of the robotic end-effector with respect to the target, and representative empirical outcomes for lesion tracking and online temperature estimation in various biological tissues are presented.

Two-year clinical follow-up after pulmonary vein isolation using high-intensity focused ultrasound (HIFU) and an esophageal temperature-guided safety algorithm.

PubMed

Neven, Kars; Metzner, Andreas; Schmidt, Boris; Ouyang, Feifan; Kuck, Karl-Heinz

2012-03-01

High-intensity frequency ultrasound (HIFU) can achieve pulmonary vein isolation (PVI), but severe complications have happened. An esophageal temperature (ET)-guided safety algorithm was implemented. We investigated medium-term outcome. After left atrial access, HIFU was applied until complete PVI. The safety algorithm was as follows: ≤3 complete ablations per pulmonary vein, early abortion when ET ≥40.0°C, use of Power Modulation at ET >39.0°C or when after 20 to 30 seconds no change in PV electrograms: to reduce the ablation temperature in the surrounding tissue, acoustic power is switched on and off with a frequency of 1 Hz; in all first ablations, use of Power Modulation after 50% of programmed time. Touch-up radiofrequency ablation when PVI failed. Follow-up included interviews and Holter electrocardiograms. Recurrence was defined as atrial fibrillation (AF) >30 seconds without a blanking period. A total of 28 symptomatic patients (18 males, age 63 years), with paroxysmal AF (n = 19) and persistent AF (n = 9) were included. After a median follow-up of 738 days, 22 of the 28 patients (79%) were free of AF without antiarrhythmic drugs. After 1 repeat procedure with radiofrequency ablation, 5 patients remained free of AF. The complications were as follows: 1 lethal atrial-to-esophageal fistula at day 31, 1 pericardial effusion at day 48, 1 unexplained death at day 49, and 2 persistent phrenic nerve palsies with full recovery within 12 months. Two-year follow-up after PVI using HIFU and an ET-guided safety algorithm shows success rates similar to those of radiofrequency-based procedures but with higher complication rates. Importantly, the ET-guided safety algorithm failed to prevent severe complications. HIFU does not meet safety standards required for the treatment of AF, and this led to a halt of its clinical use. Copyright © 2012 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Evaluation of laser ablation crater relief by white light micro interferometer

NASA Astrophysics Data System (ADS)

Gurov, Igor; Volkov, Mikhail; Zhukova, Ekaterina; Ivanov, Nikita; Margaryants, Nikita; Potemkin, Andrey; Samokhvalov, Andrey; Shelygina, Svetlana

2017-06-01

A multi-view scanning method is suggested to assess a complicated surface relief by white light interferometer. Peculiarities of the method are demonstrated on a special object in the form of quadrangular pyramid cavity, which is formed at measurement of micro-hardness of materials using a hardness gauge. An algorithm of the joint processing of multi-view scanning results is developed that allows recovering correct relief values. Laser ablation craters were studied experimentally, and their relief was recovered using the developed method. It is shown that the multi-view scanning reduces ambiguity when determining the local depth of the laser ablation craters micro relief. Results of experimental studies of the multi-view scanning method and data processing algorithm are presented.

Right atrium positioning for exposure of right pulmonary veins during off-pump atrial fibrillation ablation.

PubMed

Suwalski, Grzegorz; Emery, Robert; Mróz, Jakub; Kaczejko, Kamil; Gryszko, Leszek; Cwetsch, Andrzej; Skrobowski, Andrzej

2017-06-01

Concomitant surgical ablation of atrial fibrillation (AF) is recommended for patients undergoing off-pump coronary revascularization in the presence of this arrhythmia. Achievement of optimal visualization of pulmonary veins while maintaining stable haemodynamic conditions is crucial for proper completion of the ablation procedure. This study evaluates the safety and feasibility of right atrial positioning using a suction-based cardiac positioner as opposed to compressive manoeuvres for exposure during off-pump surgical ablation for AF. Thirty-four consecutive patients underwent pulmonary vein isolation, ganglionated plexi ablation and left atrial appendage occlusion during off-pump coronary artery bypass grafting. Right atrial suction positioning was used to visualize right pulmonary veins. Safety and feasibility end points were analysed intraoperatively and in the early postoperative course. In all patients, right atrial positioning created optimal conditions to complete transverse and oblique sinus blunt dissection, correct placement of a bipolar ablation probe, detection and ablation of ganglionated plexi and conduction block assessment. In all patients, this entire right-sided ablation procedure was completed with a single exposure manoeuvre. Feasibility end points were achieved in all study patients. This report documents the safety and feasibility of right atrial exposure using a suction-based cardiac positioner to complete ablation for AF concomitant with off-pump coronary revascularization. This technique may be widely adopted to create stable haemodynamic conditions and optimal visualization of the right pulmonary veins. © The Author 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

Ablative heat shield design for space shuttle

NASA Technical Reports Server (NTRS)

Seiferth, R. W.

1973-01-01

Ablator heat shield configuration optimization studies were conducted for the orbiter. Ablator and reusable surface insulation (RSI) trajectories for design studies were shaped to take advantage of the low conductance of ceramic RSI and high temperature capability of ablators. Comparative weights were established for the RSI system and for direct bond and mechanically attached ablator systems. Ablator system costs were determined for fabrication, installation and refurbishment. Cost penalties were assigned for payload weight penalties, if any. The direct bond ablator is lowest in weight and cost. A mechanically attached ablator using a magnesium subpanel is highly competitive for both weight and cost.

A cost-utility analysis of ablative therapy for Barrett’s esophagus

PubMed Central

Inadomi, John M.; Somsouk, Ma; Madanick, Ryan D.; Thomas, Jennifer P.; Shaheen, Nicholas J.

2009-01-01

Background & Aims Recommendations for patients with Barrett’s esophagus (BE) include endoscopic surveillance with esophagectomy for early-stage cancer, although new technologies to ablate dysplasia and metaplasia are available. This study compares the cost-utility of ablation with that of endoscopic surveillance strategies. Methods A decision analysis model was created to examine a population of patients with BE (mean age 50), with separate analyses for patients with no dysplasia, low-grade dysplasia (LGD), or high-grade dysplasia (HGD). Strategies compared were: no endoscopic surveillance; endoscopic surveillance with ablation for incident dysplasia; immediate ablation followed by endoscopic surveillance in all patients or limited to patients in whom metaplasia persisted, and esophagectomy. Ablation modalities modeled included radiofrequency, argon plasma coagulation, multipolar electrocoagulation and photodynamic therapy. Results Endoscopic ablation for patients with HGD could increase life expectancy by 3 quality-adjusted years at an incremental cost of < $6,000, compared with no intervention. Patients with LGD or no dysplasia can also be optimally managed with ablation, but continued surveillance after eradication of metaplasia is expensive. If ablation permanently eradicates at least 28% of LGD or 40% of non-dysplastic metaplasias, ablation would be preferred to surveillance. Conclusions Endoscopic ablation could be the preferred strategy for managing patients with BE with HGD. Ablation might also be preferred in subjects with LGD or no dysplasia, but the cost-effectiveness depends on the long-term effectiveness of ablation and whether surveillance endoscopy can be discontinued following successful ablation. As further post-ablation data become available, the optimal management strategy will be clarified. PMID:19272389

Measurement of thermally ablated lesions in sonoelastographic images using level set methods

NASA Astrophysics Data System (ADS)

Castaneda, Benjamin; Tamez-Pena, Jose Gerardo; Zhang, Man; Hoyt, Kenneth; Bylund, Kevin; Christensen, Jared; Saad, Wael; Strang, John; Rubens, Deborah J.; Parker, Kevin J.

2008-03-01

The capability of sonoelastography to detect lesions based on elasticity contrast can be applied to monitor the creation of thermally ablated lesion. Currently, segmentation of lesions depicted in sonoelastographic images is performed manually which can be a time consuming process and prone to significant intra- and inter-observer variability. This work presents a semi-automated segmentation algorithm for sonoelastographic data. The user starts by planting a seed in the perceived center of the lesion. Fast marching methods use this information to create an initial estimate of the lesion. Subsequently, level set methods refine its final shape by attaching the segmented contour to edges in the image while maintaining smoothness. The algorithm is applied to in vivo sonoelastographic images from twenty five thermal ablated lesions created in porcine livers. The estimated area is compared to results from manual segmentation and gross pathology images. Results show that the algorithm outperforms manual segmentation in accuracy, inter- and intra-observer variability. The processing time per image is significantly reduced.

Hybrid-drive implosion system for ICF targets

DOEpatents

Mark, James W.

1988-08-02

Hybrid-drive implosion systems (20,40) for ICF targets (10,22,42) are described which permit a significant increase in target gain at fixed total driver energy. The ICF target is compressed in two phases, an initial compression phase and a final peak power phase, with each phase driven by a separate, optimized driver. The targets comprise a hollow spherical ablator (12) surroundingly disposed around fusion fuel (14). The ablator is first compressed to higher density by a laser system (24), or by an ion beam system (44), that in each case is optimized for this initial phase of compression of the target. Then, following compression of the ablator, energy is directly delivered into the compressed ablator by an ion beam driver system (30,48) that is optimized for this second phase of operation of the target. The fusion fuel (14) is driven, at high gain, to conditions wherein fusion reactions occur. This phase separation allows hydrodynamic efficiency and energy deposition uniformity to be individually optimized, thereby securing significant advantages in energy gain. In additional embodiments, the same or separate drivers supply energy for ICF target implosion.

Hybrid-drive implosion system for ICF targets

DOEpatents

Mark, James W.

1988-01-01

Hybrid-drive implosion systems (20,40) for ICF targets (10,22,42) are described which permit a significant increase in target gain at fixed total driver energy. The ICF target is compressed in two phases, an initial compression phase and a final peak power phase, with each phase driven by a separate, optimized driver. The targets comprise a hollow spherical ablator (12) surroundingly disposed around fusion fuel (14). The ablator is first compressed to higher density by a laser system (24), or by an ion beam system (44), that in each case is optimized for this initial phase of compression of the target. Then, following compression of the ablator, energy is directly delivered into the compressed ablator by an ion beam driver system (30,48) that is optimized for this second phase of operation of the target. The fusion fuel (14) is driven, at high gain, to conditions wherein fusion reactions occur. This phase separation allows hydrodynamic efficiency and energy deposition uniformity to be individually optimized, thereby securing significant advantages in energy gain. In additional embodiments, the same or separate drivers supply energy for ICF target implosion.

Hybrid-drive implosion system for ICF targets

DOEpatents

Mark, J.W.K.

1987-10-14

Hybrid-drive implosion systems for ICF targets are described which permit a significant increase in target gain at fixed total driver energy. The ICF target is compressed in two phases, an initial compression phase and a final peak power phase, with each phase driven by a separate, optimized driver. The targets comprise a hollow spherical ablator surroundingly disposed around fusion fuel. The ablator is first compressed to higher density by a laser system, or by an ion beam system, that in each case is optimized for this initial phase of compression of the target. Then, following compression of the ablator, energy is directly delivered into the compressed ablator by an ion beam driver system that is optimized for this second phase of operation of the target. The fusion fuel is driven, at high gain, to conditions wherein fusion reactions occur. This phase separation allows hydrodynamic efficiency and energy deposition uniformity to be individually optimized, thereby securing significant advantages in energy gain. In additional embodiments, the same or separate drivers supply energy for ICF target implosion. 3 figs.

Enhancement After Myopic Small Incision Lenticule Extraction (SMILE) Using Surface Ablation.

PubMed

Siedlecki, Jakob; Luft, Nikolaus; Kook, Daniel; Wertheimer, Christian; Mayer, Wolfgang J; Bechmann, Martin; Wiltfang, Rainer; Priglinger, Siegfried G; Sekundo, Walter; Dirisamer, Martin

2017-08-01

To report the feasibility and outcomes of surface ablation after small incision lenticule extraction (SMILE). In this retrospective evaluation of 1,963 SMILE procedures, 43 eyes (2.2%) were re-treated at three separate clinics. Of these, 40 eyes of 28 patients with a follow-up of at least 3 months were included in the analysis. During surface ablation, mitomycin C was applied for haze prevention. Spherical equivalent was -6.35 ± 1.31 diopters (D) before SMILE and -0.86 ± 0.43 D before surface ablation. Surface ablation was performed after a mean of 9.82 ± 5.27 months and resulted in a spherical equivalent of 0.03 ± 0.57 D at 3 months (P < .0001). The number of patients within ±0.50 and ±1.00 D of target refraction increased from 22.5% to 80% and from 72.5% to 92.5%, respectively. Mean uncorrected distance visual acuity (UDVA) improved from 0.23 ± 0.20 to 0.08 ± 0.15 logMAR (P < .0001); 65% of patients gained at least one line. Corrected distance visual acuity (CDVA) remained unchanged with 0.01 ± 0.07 logMAR before versus -0.01 ± 0.05 logMAR after re-treatment (P = .99). Six eyes (15.0%) lost one line of CDVA, but final CDVA was 0.00 logMAR in four and 0.10 logMAR in two of these cases. The safety and efficacy indices were 1.06 and 0.90 at 3 months, respectively. Three of the four surface ablation profiles (Triple-A, tissue-saving algorithm, and topography-guided) resulted in equally good results, whereas enhancement with the aspherically optimized profile (ASA), used in two eyes, resulted in overcorrection (+1.38 and +1.75 D). Combined with the intraoperative application of mitomycin C, surface ablation seems to be a safe and effective method of secondary enhancement after SMILE. Due to the usually low residual myopia, the ASA profile is not recommended in these cases. [J Refract Surg. 2017;33(8):513-518.]. Copyright 2017, SLACK Incorporated.

Bipolar radiofrequency ablation with 2 × 2 electrodes as a building block for matrix radiofrequency ablation: Ex vivo liver experiments and finite element method modelling.

PubMed

Mulier, Stefaan; Jiang, Yansheng; Jamart, Jacques; Wang, Chong; Feng, Yuanbo; Marchal, Guy; Michel, Luc; Ni, Yicheng

2015-01-01

Size and geometry of the ablation zone obtained by currently available radiofrequency (RF) electrodes is highly variable. Reliability might be improved by matrix radiofrequency ablation (MRFA), in which the whole tumour volume is contained within a cage of x × y parallel electrodes. The aim of this study was to optimise the smallest building block for matrix radiofrequency ablation: a recently developed bipolar 2 × 2 electrode system. In ex vivo bovine liver, the parameters of the experimental set-up were changed one by one. In a second step, a finite element method (FEM) modelling of the experiment was performed to better understand the experimental findings. The optimal power to obtain complete ablation in the shortest time was 50-60 W. Performing an ablation until impedance rise was superior to ablation for a fixed duration. Increasing electrode diameter improved completeness of ablation due to lower temperature along the electrodes. A chessboard pattern of electrode polarity was inferior to a row pattern due to an electric field void in between the electrodes. Variability of ablation size was limited. The FEM correctly simulated and explained the findings in ex vivo liver. These experiments and FEM modelling allowed a better insight in the factors influencing the ablation zone in a bipolar 2 × 2 electrode RF system. With optimal parameters, complete ablation was obtained quickly and with limited variability. This knowledge will be useful to build a larger system with x × y electrodes for MRFA.

Automatic classification of scar tissue in late gadolinium enhancement cardiac MRI for the assessment of left-atrial wall injury after radiofrequency ablation

PubMed Central

Morris, Alan; Burgon, Nathan; McGann, Christopher; MacLeod, Robert; Cates, Joshua

2013-01-01

Radiofrequency ablation is a promising procedure for treating atrial fibrillation (AF) that relies on accurate lesion delivery in the left atrial (LA) wall for success. Late Gadolinium Enhancement MRI (LGE MRI) at three months post-ablation has proven effective for noninvasive assessment of the location and extent of scar formation, which are important factors for predicting patient outcome and planning of redo ablation procedures. We have developed an algorithm for automatic classification in LGE MRI of scar tissue in the LA wall and have evaluated accuracy and consistency compared to manual scar classifications by expert observers. Our approach clusters voxels based on normalized intensity and was chosen through a systematic comparison of the performance of multivariate clustering on many combinations of image texture. Algorithm performance was determined by overlap with ground truth, using multiple overlap measures, and the accuracy of the estimation of the total amount of scar in the LA. Ground truth was determined using the STAPLE algorithm, which produces a probabilistic estimate of the true scar classification from multiple expert manual segmentations. Evaluation of the ground truth data set was based on both inter- and intra-observer agreement, with variation among expert classifiers indicating the difficulty of scar classification for a given a dataset. Our proposed automatic scar classification algorithm performs well for both scar localization and estimation of scar volume: for ground truth datasets considered easy, variability from the ground truth was low; for those considered difficult, variability from ground truth was on par with the variability across experts. PMID:24236224

Automatic classification of scar tissue in late gadolinium enhancement cardiac MRI for the assessment of left-atrial wall injury after radiofrequency ablation

NASA Astrophysics Data System (ADS)

Perry, Daniel; Morris, Alan; Burgon, Nathan; McGann, Christopher; MacLeod, Robert; Cates, Joshua

2012-03-01

Radiofrequency ablation is a promising procedure for treating atrial fibrillation (AF) that relies on accurate lesion delivery in the left atrial (LA) wall for success. Late Gadolinium Enhancement MRI (LGE MRI) at three months post-ablation has proven effective for noninvasive assessment of the location and extent of scar formation, which are important factors for predicting patient outcome and planning of redo ablation procedures. We have developed an algorithm for automatic classification in LGE MRI of scar tissue in the LA wall and have evaluated accuracy and consistency compared to manual scar classifications by expert observers. Our approach clusters voxels based on normalized intensity and was chosen through a systematic comparison of the performance of multivariate clustering on many combinations of image texture. Algorithm performance was determined by overlap with ground truth, using multiple overlap measures, and the accuracy of the estimation of the total amount of scar in the LA. Ground truth was determined using the STAPLE algorithm, which produces a probabilistic estimate of the true scar classification from multiple expert manual segmentations. Evaluation of the ground truth data set was based on both inter- and intra-observer agreement, with variation among expert classifiers indicating the difficulty of scar classification for a given a dataset. Our proposed automatic scar classification algorithm performs well for both scar localization and estimation of scar volume: for ground truth datasets considered easy, variability from the ground truth was low; for those considered difficult, variability from ground truth was on par with the variability across experts.

Surface ablation with iris recognition and dynamic rotational eye tracking-based tissue saving treatment with the Technolas 217z excimer laser.

PubMed

Prakash, Gaurav; Agarwal, Amar; Kumar, Dhivya Ashok; Jacob, Soosan; Agarwal, Athiya; Maity, Amrita

2011-03-01

To evaluate the visual and refractive outcomes and expected benefits of Tissue Saving Treatment algorithm-guided surface ablation with iris recognition and dynamic rotational eye tracking. This prospective, interventional case series comprised 122 eyes (70 patients). Pre- and postoperative assessment included uncorrected distance visual acuity (UDVA), corrected distance visual acuity (CDVA), refraction, and higher order aberrations. All patients underwent Tissue Saving Treatment algorithm-guided surface ablation with iris recognition and dynamic rotational eye tracking using the Technolas 217z 100-Hz excimer platform (Technolas Perfect Vision GmbH). Follow-up was performed up to 6 months postoperatively. Theoretical benefit analysis was performed to evaluate the algorithm's outcomes compared to others. Preoperative spherocylindrical power was sphere -3.62 ± 1.60 diopters (D) (range: 0 to -6.75 D), cylinder -1.15 ± 1.00 D (range: 0 to -3.50 D), and spherical equivalent -4.19 ± 1.60 D (range: -7.75 to -2.00 D). At 6 months, 91% (111/122) of eyes were within ± 0.50 D of attempted correction. Postoperative UDVA was comparable to preoperative CDVA at 1 month (P=.47) and progressively improved at 6 months (P=.004). Two eyes lost one line of CDVA at 6 months. Theoretical benefit analysis revealed that of 101 eyes with astigmatism, 29 would have had cyclotorsion-induced astigmatism of ≥ 10% if iris recognition and dynamic rotational eye tracking were not used. Furthermore, the mean percentage decrease in maximum depth of ablation by using the Tissue Saving Treatment was 11.8 ± 2.9% over Aspheric, 17.8 ± 6.2% over Personalized, and 18.2 ± 2.8% over Planoscan algorithms. Tissue saving surface ablation with iris recognition and dynamic rotational eye tracking was safe and effective in this series of eyes. Copyright 2011, SLACK Incorporated.

C-plane Reconstructions from Sheaf Acquisition for Ultrasound Electrode Vibration Elastography.

PubMed

Ingle, Atul; Varghese, Tomy

2014-09-03

This paper presents a novel algorithm for reconstructing and visualizing ablated volumes using radiofrequency ultrasound echo data acquired with the electrode vibration elastography approach. The ablation needle is vibrated using an actuator to generate shear wave pulses that are tracked in the ultrasound image plane at different locations away from the needle. This data is used for reconstructing shear wave velocity maps for each imaging plane. A C-plane reconstruction algorithm is proposed which estimates shear wave velocity values on a collection of transverse planes that are perpendicular to the imaging planes. The algorithm utilizes shear wave velocity maps from different imaging planes that share a common axis of intersection. These C-planes can be used to generate a 3D visualization of the ablated region. Experimental validation of this approach was carried out using data from a tissue mimicking phantom. The shear wave velocity estimates were within 20% of those obtained from a clinical scanner, and a contrast of over 4 dB was obtained between the stiff and soft regions of the phantom.

Optimal approach for complete liver tumor ablation using radiofrequency ablation: a simulation study.

PubMed

Givehchi, Sogol; Wong, Yin How; Yeong, Chai Hong; Abdullah, Basri Johan Jeet

2018-04-01

To investigate the effect of radiofrequency ablation (RFA) electrode trajectory on complete tumor ablation using computational simulation. The RFA of a spherical tumor of 2.0 cm diameter along with 0.5 cm clinical safety margin was simulated using Finite Element Analysis software. A total of 86 points inside one-eighth of the tumor volume along the axial, sagittal and coronal planes were selected as the target sites for electrode-tip placement. The angle of the electrode insertion in both craniocaudal and orbital planes ranged from -90° to +90° with 30° increment. The RFA electrode was simulated to pass through the target site at different angles in combination of both craniocaudal and orbital planes before being advanced to the edge of the tumor. Complete tumor ablation was observed whenever the electrode-tip penetrated through the epicenter of the tumor regardless of the angles of electrode insertion in both craniocaudal and orbital planes. Complete tumor ablation can also be achieved by placing the electrode-tip at several optimal sites and angles. Identification of the tumor epicenter on the central slice of the axial images is essential to enhance the success rate of complete tumor ablation during RFA procedures.

Clinical Outcomes of an Optimized Prolate Ablation Procedure for Correcting Residual Refractive Errors Following Laser Surgery.

PubMed

Chung, Byunghoon; Lee, Hun; Choi, Bong Joon; Seo, Kyung Ryul; Kim, Eung Kwon; Kim, Dae Yune; Kim, Tae-Im

2017-02-01

The purpose of this study was to investigate the clinical efficacy of an optimized prolate ablation procedure for correcting residual refractive errors following laser surgery. We analyzed 24 eyes of 15 patients who underwent an optimized prolate ablation procedure for the correction of residual refractive errors following laser in situ keratomileusis, laser-assisted subepithelial keratectomy, or photorefractive keratectomy surgeries. Preoperative ophthalmic examinations were performed, and uncorrected distance visual acuity, corrected distance visual acuity, manifest refraction values (sphere, cylinder, and spherical equivalent), point spread function, modulation transfer function, corneal asphericity (Q value), ocular aberrations, and corneal haze measurements were obtained postoperatively at 1, 3, and 6 months. Uncorrected distance visual acuity improved and refractive errors decreased significantly at 1, 3, and 6 months postoperatively. Total coma aberration increased at 3 and 6 months postoperatively, while changes in all other aberrations were not statistically significant. Similarly, no significant changes in point spread function were detected, but modulation transfer function increased significantly at the postoperative time points measured. The optimized prolate ablation procedure was effective in terms of improving visual acuity and objective visual performance for the correction of persistent refractive errors following laser surgery.

Simulation of the impact of refractive surgery ablative laser pulses with a flying-spot laser beam on intrasurgery corneal temperature.

PubMed

Shraiki, Mario; Arba-Mosquera, Samuel

2011-06-01

To evaluate ablation algorithms and temperature changes in laser refractive surgery. The model (virtual laser system [VLS]) simulates different physical effects of an entire surgical process, simulating the shot-by-shot ablation process based on a modeled beam profile. The model is comprehensive and directly considers applied correction; corneal geometry, including astigmatism; laser beam characteristics; and ablative spot properties. Pulse lists collected from actual treatments were used to simulate the temperature increase during the ablation process. Ablation efficiency reduction in the periphery resulted in a lower peripheral temperature increase. Steep corneas had lesser temperature increases than flat ones. The maximum rise in temperature depends on the spatial density of the ablation pulses. For the same number of ablative pulses, myopic corrections showed the highest temperature increase, followed by myopic astigmatism, mixed astigmatism, phototherapeutic keratectomy (PTK), hyperopic astigmatism, and hyperopic treatments. The proposed model can be used, at relatively low cost, for calibration, verification, and validation of the laser systems used for ablation processes and would directly improve the quality of the results.

Analysis of laser surgery in non-melanoma skin cancer for optimal tissue removal

NASA Astrophysics Data System (ADS)

Fanjul-Vélez, Félix; Salas-García, Irene; Arce-Diego, José Luis

2015-02-01

Laser surgery is a commonly used technique for tissue ablation or the resection of malignant tumors. It presents advantages over conventional non-optical ablation techniques, like a scalpel or electrosurgery, such as the increased precision of the resected volume, minimization of scars and shorter recovery periods. Laser surgery is employed in medical branches such as ophthalmology or dermatology. The application of laser surgery requires the optimal adjustment of laser beam parameters, taking into account the particular patient and lesion. In this work we present a predictive tool for tissue resection in biological tissue after laser surgery, which allows an a priori knowledge of the tissue ablation volume, area and depth. The model employs a Monte Carlo 3D approach for optical propagation and a rate equation for plasma-induced ablation. The tool takes into account characteristics of the specific lesion to be ablated, mainly the geometric, optical and ablation properties. It also considers the parameters of the laser beam, such as the radius, spatial profile, pulse width, total delivered energy or wavelength. The predictive tool is applied to dermatology tumor resection, particularly to different types of non-melanoma skin cancer tumors: basocellular carcinoma, squamous cell carcinoma and infiltrative carcinoma. The ablation volume, area and depth are calculated for healthy skin and for each type of tumor as a function of the laser beam parameters. The tool could be used for laser surgery planning before the clinical application. The laser parameters could be adjusted for optimal resection volume, by personalizing the process to the particular patient and lesion.

Incessant ventricular tachycardia early after acute myocardial infarction: efficacy of radiofrequency catheter ablation but not of optimal coronary revascularization.

PubMed

Bonanno, C; Ometto, R; Finocchi, G; Rulfo, F; La Vecchia, L; Vincenzi, M

1999-12-01

Incessant ventricular tachycardia is an arrhythmia refractory to conventional antiarrhythmic treatment. We describe the case of 55-year-old man who presented incessant ventricular tachycardia in the early post-acute phase of myocardial infarction. Optimal coronary revascularization was not effective, but radiofrequency catheter ablation was able to eliminate the anatomic substrate and clinical arrhythmic recurrence.

Ablation of synovial pannus using microbubble-mediated ultrasonic cavitation in antigen-induced arthritis in rabbits.

PubMed

Qiu, Li; Jiang, Yong; Zhang, Lingyan; Wang, Lei; Luo, Yan

2012-12-01

To investigate the ablative effectiveness of microbubble-mediated ultrasonic cavitation for treating synovial pannus and to determine a potential mechanism using the antigen-induced arthritis model (AIA). Ultrasonic ablation was performed on the knee joints of AIA rabbits using optimal ultrasonic ablative parameters. Rabbits with antigen-induced arthritis were randomly assigned to 4 groups: (1) the ultrasound (US) + microbubble group; (2) the US only group; (3) the microbubble only group, and (4) the control group. At 1 h and 14 days after the first ablation, contrast-enhanced ultrasonography (CEUS) monitoring and pathology synovitis score were used to evaluate the therapeutic effects. Synovial necrosis and microvascular changes were also measured. After the ablation treatment, the thickness of synovium and parameters of time intensity curve including derived peak intensity and area under curve were measured using CEUS, and the pathology synovitis score in the ultrasound + microbubble group was significantly lower than that found in the remaining groups. No damage was observed in the surrounding normal tissues. The mechanism underlying the ultrasonic ablation was related to microthrombosis and microvascular rupture that resulted in synovial necrosis. The results suggest that microbubble-mediated ultrasonic cavitation should be applied as a non-invasive strategy for the treatment of synovial pannus in arthritis under optimal conditions.

Ablation algorithms and corneal asphericity in myopic correction with excimer lasers

NASA Astrophysics Data System (ADS)

Iroshnikov, Nikita G.; Larichev, Andrey V.; Yablokov, Michail G.

2007-06-01

The purpose of this work is studying a corneal asphericity change after a myopic refractive correction by mean of excimer lasers. As the ablation profile shape plays a key role in the post-op corneal asphericity, ablation profiles of recent lasers should be studied. The other task of this research was to analyze operation (LASIK) outcomes of one of the lasers with generic spherical ablation profile and to compare an asphericity change with theoretical predictions. The several correction methods, like custom generated aspherical profiles, may be utilized for mitigation of unwanted effects of asphericity change. Here we also present preliminary results of such correction for one of the excimer lasers.

Composite Configuration Interventional Therapy Robot for the Microwave Ablation of Liver Tumors

NASA Astrophysics Data System (ADS)

Cao, Ying-Yu; Xue, Long; Qi, Bo-Jin; Jiang, Li-Pei; Deng, Shuang-Cheng; Liang, Ping; Liu, Jia

2017-11-01

The existing interventional therapy robots for the microwave ablation of liver tumors have a poor clinical applicability with a large volume, low positioning speed and complex automatic navigation control. To solve above problems, a composite configuration interventional therapy robot with passive and active joints is developed. The design of composite configuration reduces the size of the robot under the premise of a wide range of movement, and the robot with composite configuration can realizes rapid positioning with operation safety. The cumulative error of positioning is eliminated and the control complexity is reduced by decoupling active parts. The navigation algorithms for the robot are proposed based on solution of the inverse kinematics and geometric analysis. A simulation clinical test method is designed for the robot, and the functions of the robot and the navigation algorithms are verified by the test method. The mean error of navigation is 1.488 mm and the maximum error is 2.056 mm, and the positioning time for the ablation needle is in 10 s. The experimental results show that the designed robot can meet the clinical requirements for the microwave ablation of liver tumors. The composite configuration is proposed in development of the interventional therapy robot for the microwave ablation of liver tumors, which provides a new idea for the structural design of medical robots.

Implementation of Radiation, Ablation, and Free Energy Minimization Modules for Coupled Simulations of Hypersonic Flow

NASA Technical Reports Server (NTRS)

Gnoffo, Peter A.; Johnston, Christopher O.; Thompson, Richard A.

2009-01-01

A description of models and boundary conditions required for coupling radiation and ablation physics to a hypersonic flow simulation is provided. Chemical equilibrium routines for varying elemental mass fraction are required in the flow solver to integrate with the equilibrium chemistry assumption employed in the ablation models. The capability also enables an equilibrium catalytic wall boundary condition in the non-ablating case. The paper focuses on numerical implementation issues using FIRE II, Mars return, and Apollo 4 applications to provide context for discussion. Variable relaxation factors applied to the Jacobian elements of partial equilibrium relations required for convergence are defined. Challenges of strong radiation coupling in a shock capturing algorithm are addressed. Results are presented to show how the current suite of models responds to a wide variety of conditions involving coupled radiation and ablation.

Local ablation therapy with contrast-enhanced ultrasonography for hepatocellular carcinoma: a practical review

PubMed Central

Kim, Tae Kyoung; Khalili, Korosh; Jang, Hyun-Jung

2015-01-01

A successful program for local ablation therapy for hepatocellular carcinoma (HCC) requires extensive imaging support for diagnosis and localization of HCC, imaging guidance for the ablation procedures, and post-treatment monitoring. Contrast-enhanced ultrasonography (CEUS) has several advantages over computed tomography/magnetic resonance imaging (CT/MRI), including real-time imaging capability, sensitive detection of arterial-phase hypervascularity and washout, no renal excretion, no ionizing radiation, repeatability, excellent patient compliance, and relatively low cost. CEUS is useful for image guidance for isoechoic lesions. While contrast-enhanced CT/MRI is the standard method for the diagnosis of HCC and post-ablation monitoring, CEUS is useful when CT/MRI findings are indeterminate or CT/MRI is contraindicated. This article provides a practical review of the role of CEUS in imaging algorithms for pre- and post-ablation therapy for HCC. PMID:26169081

Controlling dental enamel-cavity ablation depth with optimized stepping parameters along the focal plane normal using a three axis, numerically controlled picosecond laser.

PubMed

Yuan, Fusong; Lv, Peijun; Wang, Dangxiao; Wang, Lei; Sun, Yuchun; Wang, Yong

2015-02-01

The purpose of this study was to establish a depth-control method in enamel-cavity ablation by optimizing the timing of the focal-plane-normal stepping and the single-step size of a three axis, numerically controlled picosecond laser. Although it has been proposed that picosecond lasers may be used to ablate dental hard tissue, the viability of such a depth-control method in enamel-cavity ablation remains uncertain. Forty-two enamel slices with approximately level surfaces were prepared and subjected to two-dimensional ablation by a picosecond laser. The additive-pulse layer, n, was set to 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70. A three-dimensional microscope was then used to measure the ablation depth, d, to obtain a quantitative function relating n and d. Six enamel slices were then subjected to three dimensional ablation to produce 10 cavities, respectively, with additive-pulse layer and single-step size set to corresponding values. The difference between the theoretical and measured values was calculated for both the cavity depth and the ablation depth of a single step. These were used to determine minimum-difference values for both the additive-pulse layer (n) and single-step size (d). When the additive-pulse layer and the single-step size were set 5 and 45, respectively, the depth error had a minimum of 2.25 μm, and 450 μm deep enamel cavities were produced. When performing three-dimensional ablating of enamel with a picosecond laser, adjusting the timing of the focal-plane-normal stepping and the single-step size allows for the control of ablation-depth error to the order of micrometers.

Optimization of the generator settings for endobiliary radiofrequency ablation.

PubMed

Barret, Maximilien; Leblanc, Sarah; Vienne, Ariane; Rouquette, Alexandre; Beuvon, Frederic; Chaussade, Stanislas; Prat, Frederic

2015-11-10

To determine the optimal generator settings for endobiliary radiofrequency ablation. Endobiliary radiofrequency ablation was performed in live swine on the ampulla of Vater, the common bile duct and in the hepatic parenchyma. Radiofrequency ablation time, "effect", and power were allowed to vary. The animals were sacrificed two hours after the procedure. Histopathological assessment of the depth of the thermal lesions was performed. Twenty-five radiofrequency bursts were applied in three swine. In the ampulla of Vater (n = 3), necrosis of the duodenal wall was observed starting with an effect set at 8, power output set at 10 W, and a 30 s shot duration, whereas superficial mucosal damage of up to 350 μm in depth was recorded for an effect set at 8, power output set at 6 W and a 30 s shot duration. In the common bile duct (n = 4), a 1070 μm, safe and efficient ablation was obtained for an effect set at 8, a power output of 8 W, and an ablation time of 30 s. Within the hepatic parenchyma (n = 18), the depth of tissue damage varied from 1620 μm (effect = 8, power = 10 W, ablation time = 15 s) to 4480 μm (effect = 8, power = 8 W, ablation time = 90 s). The duration of the catheter application appeared to be the most important parameter influencing the depth of the thermal injury during endobiliary radiofrequency ablation. In healthy swine, the currently recommended settings of the generator may induce severe, supratherapeutic tissue damage in the biliary tree, especially in the high-risk area of the ampulla of Vater.

Creation of short microwave ablation zones: in vivo characterization of single and paired modified triaxial antennas.

PubMed

Lubner, Meghan G; Ziemlewicz, Tim J; Hinshaw, J Louis; Lee, Fred T; Sampson, Lisa A; Brace, Christopher L

2014-10-01

To characterize modified triaxial microwave antennas configured to produce short ablation zones. Fifty single-antenna and 27 paired-antenna hepatic ablations were performed in domestic swine (N = 11) with 17-gauge gas-cooled modified triaxial antennas powered at 65 W from a 2.45-GHz generator. Single-antenna ablations were performed at 2 (n = 16), 5 (n = 21), and 10 (n = 13) minutes. Paired-antenna ablations were performed at 1-cm and 2-cm spacing for 5 (n = 7 and n = 8, respectively) and 10 minutes (n = 7 and n = 5, respectively). Mean transverse width, length, and aspect ratio of sectioned ablation zones were measured and compared. For single antennas, mean ablation zone lengths were 2.9 cm ± 0.45, 3.5 cm ± 0.55, and 4.2 cm ± 0.40 at 2, 5, and 10 minutes, respectively. Mean widths were 1.8 cm ± 0.3, 2.0 cm ± 0.32, and 2.5 cm ± 0.25 at 2, 5, and 10 minutes, respectively. For paired antennas, mean length at 5 minutes with 1-cm and 2-cm spacing and 10 minutes with 1-cm and 2-cm spacing was 4.2 cm ± 0.9, 4.9 cm ± 1.0, 4.8 cm ± 0.5, and 4.8 cm ± 1.3, respectively. Mean width was 3.1 cm ± 1.0, 4.4 cm ± 0.7, 3.8 cm ± 0.4, and 4.5 cm ± 0.7, respectively. Paired-antenna ablations were more spherical (aspect ratios, 0.72-0.79 for 5-10 min) than single-antenna ablations (aspect ratios, 0.57-0.59). For paired-antenna ablations, 1-cm spacing appeared optimal, with improved circularity and decreased clefting compared with 2-cm spacing (circularity, 0.85 at 1 cm, 0.78 at 2 cm). Modified triaxial antennas can generate relatively short, spherical ablation zones. Paired-antenna ablations were rounder and larger in transverse dimension than single antenna ablations, with 1-cm spacing optimal for confluence of the ablation zone. Copyright © 2014 SIR. Published by Elsevier Inc. All rights reserved.

Creation of short microwave ablation zones: In Vivo Characterization of single and paired Modified Triaxial Antennas Laboratory Investigation

PubMed Central

Lubner, Meghan G.; Ziemlewicz, Tim J; Hinshaw, J. Louis; Lee, Fred T.; Sampson, Lisa J.; Brace, Chris L.

2014-01-01

Purpose To characterize modified triaxial microwave antennas configured to produce short ablation zones. Materials and Methods 50 single- and 27 paired-antenna hepatic ablations were performed in domestic swine (n=11) with 17-gauge, gas-cooled modified triaxial antennas powered at 65W from a 2.45 GHz generator. Single-antenna ablations were performed at 2 (n=16), 5 (n=21), and 10 (n=13) minutes. Paired-antenna ablations were performed at 1-cm and 2-cm spacing for 5 (n=7, n=8) and 10 minutes (n=7, n=5). Mean transverse width, length and aspect ratio of sectioned ablation zones were measured and compared. Results For single antennas, mean ablation zone length was 2.9±0.45, 3.5±0.55 and 4.2±0.40 cm at 2, 5, and 10 minutes respectively. Mean width was 1.8±0.3, 2.0±0.32, 2.5±0.25 cm at 2, 5, and 10 minutes. For paired antennas, mean length at 5 min 1 and 2 cm and 10 min 1 and 2 cm spacing was 4.2±0.9, 4.4±0.9, 4.8±0.5 and 4.3±0.9 cm respectively. Mean width was 3.1±1.0, 4.0±0.8 and 3.8±0.4, 4.2±0.6 cm respectively. Paired-antenna ablations were more spherical (aspect ratios 0.72-0.79 for 5-10 min) than single-antenna ablations (0.57-0.59). For paired-antenna ablations, 1 cm spacing appeared optimal, with improved circularity and decreased clefting compared to 2 cm spacing (circ 1 cm 0.85, 2 cm 0.78). Conclusion Modified triaxial antennas can generate relatively short, spherical ablation zones. Paired-antenna ablations were rounder and larger in transverse dimension compared to single antenna ablations, with 1 cm spacing optimal for confluence of the ablation zone. PMID:25156644

Therapy of Pancreatic Neuroendocrine Tumors: Fine Needle Intervention including Ethanol and Radiofrequency Ablation

PubMed Central

Lakhtakia, Sundeep

2017-01-01

Pancreatic neuroendocrine tumors (PNETs) are increasingly being detected, though usually as incidental findings. Majority of the PNETs are non-functional and surgical resection is the standard of care for most of them. However, in patients with small PNETs localized within the pancreas, who are unfit or unwilling for surgery, alternate methods of treatment are needed. Direct methods of ablation of PNETs, using either ethanol injection or radiofrequency ablation (RFA), are emerging as effective methods. The limited literature available as case reports or case series on endoscopic ultrasound (EUS)-guided local ablation using either ethanol or RFA has demonstrated safety and efficacy along with short- to medium-term sustained relief. Long-term benefits with these local ablative therapies are awaited. Comparative studies are needed to show which of these two competing technologies is superior. Finally, comparative trials of EUS-guided ablation with surgical resection in terms of efficacy and safety will ensure their place in the management algorithm. PMID:29207860

Nanosecond laser ablation of target Al in a gaseous medium: explosive boiling

NASA Astrophysics Data System (ADS)

Mazhukin, V. I.; Mazhukin, A. V.; Demin, M. M.; Shapranov, A. V.

2018-03-01

An approximate mathematical description of the processes of homogeneous nucleation and homogeneous evaporation (explosive boiling) of a metal target (Al) under the influence of ns laser radiation is proposed in the framework of the hydrodynamic model. Within the continuum approach, a multi-phase, multi-front hydrodynamic model and a computational algorithm are designed to simulate nanosecond laser ablation of the metal targets immersed in gaseous media. The proposed approach is intended for modeling and detailed analysis of the mechanisms of heterogeneous and homogeneous evaporation and their interaction with each other. It is shown that the proposed model and computational algorithm allow modeling of interrelated mechanisms of heterogeneous and homogeneous evaporation of metals, manifested in the form of pulsating explosive boiling. Modeling has shown that explosive evaporation in metals is due to the presence of a near-surface temperature maximum. It has been established that in nanosecond pulsed laser ablation, such exposure regimes can be implemented in which phase explosion is the main mechanism of material removal.

FAST SIMULATION OF SOLID TUMORS THERMAL ABLATION TREATMENTS WITH A 3D REACTION DIFFUSION MODEL *

PubMed Central

BERTACCINI, DANIELE; CALVETTI, DANIELA

2007-01-01

An efficient computational method for near real-time simulation of thermal ablation of tumors via radio frequencies is proposed. Model simulations of the temperature field in a 3D portion of tissue containing the tumoral mass for different patterns of source heating can be used to design the ablation procedure. The availability of a very efficient computational scheme makes it possible update the predicted outcome of the procedure in real time. In the algorithms proposed here a discretization in space of the governing equations is followed by an adaptive time integration based on implicit multistep formulas. A modification of the ode15s MATLAB function which uses Krylov space iterative methods for the solution of for the linear systems arising at each integration step makes it possible to perform the simulations on standard desktop for much finer grids than using the built-in ode15s. The proposed algorithm can be applied to a wide class of nonlinear parabolic differential equations. PMID:17173888

Non-Intrusive Sensor for In-Situ Measurement of Recession Rate of Ablative and Eroding Materials

NASA Technical Reports Server (NTRS)

Papadopoulos, George (Inventor); Tiliakos, Nicholas (Inventor); Thomson, Clint (Inventor); Benel, Gabriel (Inventor)

2014-01-01

A non-intrusive sensor for in-situ measurement of recession rate of heat shield ablatives. An ultrasonic wave source is carried in the housing. A microphone is also carried in the housing, for collecting the reflected ultrasonic waves from an interface surface of the ablative material. A time phasing control circuit is also included for time-phasing the ultrasonic wave source so that the waves reflected from the interface surface of the ablative material focus on the microphone, to maximize the acoustic pressure detected by the microphone and to mitigate acoustic velocity variation effects through the material through a de-coupling process that involves a software algorithm. A software circuit for computing the location off of which the ultrasonic waves scattered to focus back at the microphone is also included, so that the recession rate of the heat shield ablative may be monitored in real-time through the scan-focus approach.

Optimization of the generator settings for endobiliary radiofrequency ablation

PubMed Central

Barret, Maximilien; Leblanc, Sarah; Vienne, Ariane; Rouquette, Alexandre; Beuvon, Frederic; Chaussade, Stanislas; Prat, Frederic

2015-01-01

AIM: To determine the optimal generator settings for endobiliary radiofrequency ablation. METHODS: Endobiliary radiofrequency ablation was performed in live swine on the ampulla of Vater, the common bile duct and in the hepatic parenchyma. Radiofrequency ablation time, “effect”, and power were allowed to vary. The animals were sacrificed two hours after the procedure. Histopathological assessment of the depth of the thermal lesions was performed. RESULTS: Twenty-five radiofrequency bursts were applied in three swine. In the ampulla of Vater (n = 3), necrosis of the duodenal wall was observed starting with an effect set at 8, power output set at 10 W, and a 30 s shot duration, whereas superficial mucosal damage of up to 350 μm in depth was recorded for an effect set at 8, power output set at 6 W and a 30 s shot duration. In the common bile duct (n = 4), a 1070 μm, safe and efficient ablation was obtained for an effect set at 8, a power output of 8 W, and an ablation time of 30 s. Within the hepatic parenchyma (n = 18), the depth of tissue damage varied from 1620 μm (effect = 8, power = 10 W, ablation time = 15 s) to 4480 μm (effect = 8, power = 8 W, ablation time = 90 s). CONCLUSION: The duration of the catheter application appeared to be the most important parameter influencing the depth of the thermal injury during endobiliary radiofrequency ablation. In healthy swine, the currently recommended settings of the generator may induce severe, supratherapeutic tissue damage in the biliary tree, especially in the high-risk area of the ampulla of Vater. PMID:26566429

Optimization of direct current-enhanced radiofrequency ablation: an ex vivo study.

PubMed

Tanaka, Toshihiro; Isfort, Peter; Bruners, Philipp; Penzkofer, Tobias; Kichikawa, Kimihiko; Schmitz-Rode, Thomas; Mahnken, Andreas H

2010-10-01

The purpose of this study was to investigate the optimal setting for radiofrequency (RF) ablation combined with direct electrical current (DC) ablation in ex vivo bovine liver. An electrical circuit combining a commercially available RF ablation system with DC was developed. The negative electrode of a rectifier that provides DC was connected to a 3-cm multitined expandable RF probe. A 100-mH inductor was used to prevent electrical leakage from the RF generator. DC was applied for 15 min and followed by RF ablation in freshly excised bovine livers. Electric current was measured by an ammeter. Coagulation volume, ablation duration, and mean amperage were assessed for various DC voltages (no DC, 2.2, 4.5, and 9.0 V) and different RF ablation protocols (stepwise increase from 40 to 80 W, 40 W fixed, and 80 W fixed). Results were compared using Kruskal-Wallis and Mann-Whitney U test. Applying DC with 4.5 or 9.0 V, in combination with 40 W fixed or a stepwise increase of RF energy, resulted in significantly increased zone of ablation size compared with 2.2 V or no DC (P = 0.009). At 4.5 V DC, the stepwise increase of RF energy resulted in the same necrosis size as a 40 W fixed protocol (26.6 +/- 3.9 vs. 26.5 +/- 4.0 ml), but ablation duration was significantly decreased (296 +/- 85 s vs. 423 +/- 104 s; P = 0.028). Mean amperage was significantly lower at 4.5 V compared with 9.0 V (P = 0.028). Combining a stepwise increase of RF energy with a DC voltage of 4.5 V is most appropriate to increase coagulation volume and to minimize procedure time.

Optimization of Direct Current-Enhanced Radiofrequency Ablation: An Ex Vivo Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tanaka, Toshihiro, E-mail: toshihir@bf6.so-net.ne.jp; Isfort, Peter; Bruners, Philipp

2010-10-15

The purpose of this study was to investigate the optimal setting for radiofrequency (RF) ablation combined with direct electrical current (DC) ablation in ex vivo bovine liver. An electrical circuit combining a commercially available RF ablation system with DC was developed. The negative electrode of a rectifier that provides DC was connected to a 3-cm multitined expandable RF probe. A 100-mH inductor was used to prevent electrical leakage from the RF generator. DC was applied for 15 min and followed by RF ablation in freshly excised bovine livers. Electric current was measured by an ammeter. Coagulation volume, ablation duration, andmore » mean amperage were assessed for various DC voltages (no DC, 2.2, 4.5, and 9.0 V) and different RF ablation protocols (stepwise increase from 40 to 80 W, 40 W fixed, and 80 W fixed). Results were compared using Kruskal-Wallis and Mann-Whitney U test. Applying DC with 4.5 or 9.0 V, in combination with 40 W fixed or a stepwise increase of RF energy, resulted in significantly increased zone of ablation size compared with 2.2 V or no DC (P = 0.009). At 4.5 V DC, the stepwise increase of RF energy resulted in the same necrosis size as a 40 W fixed protocol (26.6 {+-} 3.9 vs. 26.5 {+-} 4.0 ml), but ablation duration was significantly decreased (296 {+-} 85 s vs. 423 {+-} 104 s; P = 0.028). Mean amperage was significantly lower at 4.5 V compared with 9.0 V (P = 0.028). Combining a stepwise increase of RF energy with a DC voltage of 4.5 V is most appropriate to increase coagulation volume and to minimize procedure time.« less

A study of the effect of selected material properties on the ablation performance of artificial graphite

NASA Technical Reports Server (NTRS)

Maahs, H. G.

1972-01-01

Eighteen material properties were measured on 45 different, commercially available, artificial graphites. Ablation performance of these same graphites were also measured in a Mach 2 airstream at a stagnation pressure of 5.6 atm. Correlations were developed, where possible, between pairs of the material properties. Multiple regression equations were then formulated relating ablation performance to the various material properties, thus identifying those material properties having the strongest effect on ablation performance. These regression equations reveal that ablation performance in the present test environment depends primarily on maximum grain size, density, ash content, thermal conductivity, and mean pore radius. For optimization of ablation performance, grain size should be small, ash content low, density and thermal conductivity high, and mean pore radius large.

Microwave Tissue Ablation: Biophysics, Technology and Applications

PubMed Central

2010-01-01

Microwave ablation is an emerging treatment option for many cancers, cardiac arrhythmias and other medical conditions. During treatment, microwaves are applied directly to tissues to produce rapid temperature elevations sufficient to produce immediate coagulative necrosis. The engineering design criteria for each application differ, with individual consideration for factors such as desired ablation zone size, treatment duration, and procedural invasiveness. Recent technological developments in applicator cooling, power control and system optimization for specific applications promise to increase the utilization of microwave ablation in the future. This article will review the basic biophysics of microwave tissue heating, provide an overview of the design and operation of current equipment, and outline areas for future research for microwave ablation. PMID:21175404

The Physics of Ultrabroadband Frequency Comb Generation and Optimized Combs for Measurements in Fundamental Physics

DTIC Science & Technology

2016-07-02

beams Superresolution machining Threshold effect of ablation means that structure diameter is less than the beam diameter fs pulses at 800 nm yield 200...Approved for public release: distribution unlimited. Applications of Bessel beams Superresolution machining Threshold effect of ablation means that... Superresolution machining Threshold effect of ablation means that structure diameter is less than the beam diameter fs pulses at 800 nm yield 200 nm

Family System of Advanced Charring Ablators for Planetary Exploration Missions

NASA Technical Reports Server (NTRS)

Congdon, William M.; Curry, Donald M.

2005-01-01

Advanced Ablators Program Objectives: 1) Flight-ready(TRL-6) ablative heat shields for deep-space missions; 2) Diversity of selection from family-system approach; 3) Minimum weight systems with high reliability; 4) Optimized formulations and processing; 5) Fully characterized properties; and 6) Low-cost manufacturing. Definition and integration of candidate lightweight structures. Test and analysis database to support flight-vehicle engineering. Results from production scale-up studies and production-cost analyses.

Temperature-controlled radiofrequency ablation of different tissues using two-compartment models.

PubMed

Singh, Sundeep; Repaka, Ramjee

2016-08-30

This study aims to analyse the efficacy of temperature-controlled radiofrequency ablation (RFA) in different tissues. A three-dimensional, 12 cm cubical model representing the healthy tissue has been studied in which spherical tumour of 2.5 cm has been embedded. Different body sites considered in the study are liver, kidney, lung and breast. The thermo-electric analysis has been performed to estimate the temperature distribution and ablation volume. A programmable temperature-controlled RFA has been employed by incorporating the closed-loop feedback PID controller. The model fidelity and integrity have been evaluated by comparing the numerical results with the experimental in vitro results obtained during RFA of polyacrylamide tissue-mimicking phantom gel. The results revealed that significant variations persist among the input voltage requirements and the temperature distributions within different tissues of interest. The highest ablation volume has been produced in hypovascular lungs whereas least ablation volume has been produced in kidney being a highly perfused tissue. The variation in optimal treatment time for complete necrosis of tumour along with quantification of damage to the surrounding healthy tissue has also been reported. The results show that the surrounding tissue environment significantly affects the ablation volume produced during RFA. The optimal treatment time for complete tumour ablation can play a critical role in minimising the damage to the surrounding healthy tissue and ensuring safe and risk free application of RFA. The obtained results emphasise the need for developing organ-specific clinical protocols and systems during RFA of tumour.

Time-of-flight measurement of ionic species generated during ablation for optimization of focusing condition at free-electron laser beamline

NASA Astrophysics Data System (ADS)

Senba, Y.; Nagasono, M.; Koyama, T.; Yumoto, H.; Ohashi, H.; Tono, K.; Togashi, T.; Inubushi, Y.; Sato, T.; Yabashi, M.; Ishikawa, T.

2013-03-01

Optimization of focusing conditions is important in free-electron laser applications. A time-of-flight mass analyzer has been designed and constructed for this purpose. The time-of-flight spectra of ionic species evolved from laser ablation of gold were measured. The yields of ionic species showed strong correlations with free-electron-laser intensity. This method conveniently allows for direct estimation of laser intensity on sample and determination of focusing position.

Radio Frequency Ablation Registration, Segmentation, and Fusion Tool

PubMed Central

McCreedy, Evan S.; Cheng, Ruida; Hemler, Paul F.; Viswanathan, Anand; Wood, Bradford J.; McAuliffe, Matthew J.

2008-01-01

The Radio Frequency Ablation Segmentation Tool (RFAST) is a software application developed using NIH's Medical Image Processing Analysis and Visualization (MIPAV) API for the specific purpose of assisting physicians in the planning of radio frequency ablation (RFA) procedures. The RFAST application sequentially leads the physician through the steps necessary to register, fuse, segment, visualize and plan the RFA treatment. Three-dimensional volume visualization of the CT dataset with segmented 3D surface models enables the physician to interactively position the ablation probe to simulate burns and to semi-manually simulate sphere packing in an attempt to optimize probe placement. PMID:16871716

Critical review on refractive surgical lasers

NASA Astrophysics Data System (ADS)

Lin, J. T.

1995-03-01

The current status of refractive surgical lasers (including excimer and nonexcimer lasers) is reviewed with an emphasis on photorefractive keratectomy (PRK). The correlation of engineering parameters and the clinical requirements with optimal conditions are presented. The fundamentals of corneal reshaping with formulas for ablation profiles and the advantages of the multizone method are discussed. Updated information on the Mini-Excimer PRK laser system, with an emphasis on the scanning delivery device, is presented. PMMA ablation profiles performed by standard diaphragm and scanning modes are compared for surface ablation quality. Scanning mode ablation patterns for myopia, hyperopia, and regular and irregular astigmatism are presented.

Numerical Simulation of Thermal Response and Ablation Behavior of a Hybrid Carbon/Carbon Composite

NASA Astrophysics Data System (ADS)

Zhang, Bai; Li, Xudong

2017-09-01

The thermal response and ablation behavior of a hybrid carbon/carbon (C/C) composite are studied herein by using a numerical model. This model is based on the energy- and mass-conservation principles as well as on the calculation of the thermophysical properties of materials. The thermal response and ablation behavior are simulated from the perspective of the matrix and fiber components of a hybrid C/C composite. The thermophysical properties during ablation are calculated, and a moving boundary is implemented to consider the recession of the ablation surface. The temperature distribution, thermophysical properties, char layer thickness, linear ablation rate, mass flow rate of the pyrolysis gases, and mass loss of the hybrid C/C composite are quantitatively predicted. This numerical study describing the thermal response and ablation behavior provides a fundamental understanding of the ablative mechanism of a hybrid C/C composite, serving as a reference and basis for further designs and optimizations of thermoprotective materials.

Numerical Simulation of Thermal Response and Ablation Behavior of a Hybrid Carbon/Carbon Composite

NASA Astrophysics Data System (ADS)

Zhang, Bai; Li, Xudong

2018-06-01

The thermal response and ablation behavior of a hybrid carbon/carbon (C/C) composite are studied herein by using a numerical model. This model is based on the energy- and mass-conservation principles as well as on the calculation of the thermophysical properties of materials. The thermal response and ablation behavior are simulated from the perspective of the matrix and fiber components of a hybrid C/C composite. The thermophysical properties during ablation are calculated, and a moving boundary is implemented to consider the recession of the ablation surface. The temperature distribution, thermophysical properties, char layer thickness, linear ablation rate, mass flow rate of the pyrolysis gases, and mass loss of the hybrid C/C composite are quantitatively predicted. This numerical study describing the thermal response and ablation behavior provides a fundamental understanding of the ablative mechanism of a hybrid C/C composite, serving as a reference and basis for further designs and optimizations of thermoprotective materials.

Shear wave velocity imaging using transient electrode perturbation: phantom and ex vivo validation.

PubMed

DeWall, Ryan J; Varghese, Tomy; Madsen, Ernest L

2011-03-01

This paper presents a new shear wave velocity imaging technique to monitor radio-frequency and microwave ablation procedures, coined electrode vibration elastography. A piezoelectric actuator attached to an ablation needle is transiently vibrated to generate shear waves that are tracked at high frame rates. The time-to-peak algorithm is used to reconstruct the shear wave velocity and thereby the shear modulus variations. The feasibility of electrode vibration elastography is demonstrated using finite element models and ultrasound simulations, tissue-mimicking phantoms simulating fully (phantom 1) and partially ablated (phantom 2) regions, and an ex vivo bovine liver ablation experiment. In phantom experiments, good boundary delineation was observed. Shear wave velocity estimates were within 7% of mechanical measurements in phantom 1 and within 17% in phantom 2. Good boundary delineation was also demonstrated in the ex vivo experiment. The shear wave velocity estimates inside the ablated region were higher than mechanical testing estimates, but estimates in the untreated tissue were within 20% of mechanical measurements. A comparison of electrode vibration elastography and electrode displacement elastography showed the complementary information that they can provide. Electrode vibration elastography shows promise as an imaging modality that provides ablation boundary delineation and quantitative information during ablation procedures.

Analysis of composite ablators using massively parallel computation

NASA Technical Reports Server (NTRS)

Shia, David

1995-01-01

In this work, the feasibility of using massively parallel computation to study the response of ablative materials is investigated. Explicit and implicit finite difference methods are used on a massively parallel computer, the Thinking Machines CM-5. The governing equations are a set of nonlinear partial differential equations. The governing equations are developed for three sample problems: (1) transpiration cooling, (2) ablative composite plate, and (3) restrained thermal growth testing. The transpiration cooling problem is solved using a solution scheme based solely on the explicit finite difference method. The results are compared with available analytical steady-state through-thickness temperature and pressure distributions and good agreement between the numerical and analytical solutions is found. It is also found that a solution scheme based on the explicit finite difference method has the following advantages: incorporates complex physics easily, results in a simple algorithm, and is easily parallelizable. However, a solution scheme of this kind needs very small time steps to maintain stability. A solution scheme based on the implicit finite difference method has the advantage that it does not require very small times steps to maintain stability. However, this kind of solution scheme has the disadvantages that complex physics cannot be easily incorporated into the algorithm and that the solution scheme is difficult to parallelize. A hybrid solution scheme is then developed to combine the strengths of the explicit and implicit finite difference methods and minimize their weaknesses. This is achieved by identifying the critical time scale associated with the governing equations and applying the appropriate finite difference method according to this critical time scale. The hybrid solution scheme is then applied to the ablative composite plate and restrained thermal growth problems. The gas storage term is included in the explicit pressure calculation of both problems. Results from ablative composite plate problems are compared with previous numerical results which did not include the gas storage term. It is found that the through-thickness temperature distribution is not affected much by the gas storage term. However, the through-thickness pressure and stress distributions, and the extent of chemical reactions are different from the previous numerical results. Two types of chemical reaction models are used in the restrained thermal growth testing problem: (1) pressure-independent Arrhenius type rate equations and (2) pressure-dependent Arrhenius type rate equations. The numerical results are compared to experimental results and the pressure-dependent model is able to capture the trend better than the pressure-independent one. Finally, a performance study is done on the hybrid algorithm using the ablative composite plate problem. It is found that there is a good speedup of performance on the CM-5. For 32 CPU's, the speedup of performance is 20. The efficiency of the algorithm is found to be a function of the size and execution time of a given problem and the effective parallelization of the algorithm. It also seems that there is an optimum number of CPU's to use for a given problem.

Radiofrequency Ablation of Benign Thyroid Nodules and Recurrent Thyroid Cancers: Consensus Statement and Recommendations

PubMed Central

Na, Dong Gyu; Lee, Jeong Hyun; Jung, So Lyung; Kim, Ji-hoon; Sung, Jin Yong; Shin, Jung Hee; Kim, Eun-Kyung; Lee, Joon Hyung; Kim, Dong Wook; Park, Jeong Seon; Kim, Kyu Sun; Baek, Seon Mi; Lee, Younghen; Chong, Semin; Sim, Jung Suk; Huh, Jung Yin; Bae, Jae-Ik; Kim, Kyung Tae; Han, Song Yee; Bae, Min Young; Kim, Yoon Suk

2012-01-01

Thermal ablation using radiofrequency is a new, minimally invasive modality employed as an alternative to surgery in patients with benign thyroid nodules and recurrent thyroid cancers. The Task Force Committee of the Korean Society of Thyroid Radiology has developed recommendations for the optimal use of radiofrequency ablation for thyroid nodules. These recommendations are based on a comprehensive analysis of the current literature, the results of multicenter studies, and expert consensus. PMID:22438678

Spacecraft formation flying for Earth-crossing object deflections using a power limited laser ablating

NASA Astrophysics Data System (ADS)

Yoo, Sung-Moon; Song, Young-Joo; Park, Sang-Young; Choi, Kyu-Hong

2009-06-01

A formation flying strategy with an Earth-crossing object (ECO) is proposed to avoid the Earth collision. Assuming that a future conceptual spacecraft equipped with a powerful laser ablation tool already rendezvoused with a fictitious Earth collision object, the optimal required laser operating duration and direction histories are accurately derived to miss the Earth. Based on these results, the concept of formation flying between the object and the spacecraft is applied and analyzed as to establish the spacecraft's orbital motion design strategy. A fictitious "Apophis"-like object is established to impact with the Earth and two major deflection scenarios are designed and analyzed. These scenarios include the cases for the both short and long laser operating duration to avoid the Earth impact. Also, requirement of onboard laser tool's for both cases are discussed. As a result, the optimal initial conditions for the spacecraft to maintain its relative trajectory to the object are discovered. Additionally, the discovered optimal initial conditions also satisfied the optimal required laser operating conditions with no additional spacecraft's own fuel expenditure to achieve the spacecraft formation flying with the ECO. The initial conditions founded in the current research can be used as a spacecraft's initial rendezvous points with the ECO when designing the future deflection missions with laser ablation tools. The results with proposed strategy are expected to make more advances in the fields of the conceptual studies, especially for the future deflection missions using powerful laser ablation tools.

Ablative skin resurfacing.

PubMed

Agrawal, Nidhi; Smith, Greg; Heffelfinger, Ryan

2014-02-01

Ablative laser resurfacing has evolved as a safe and effective treatment for skin rejuvenation. Although traditional lasers were associated with significant thermal damage and lengthy recovery, advances in laser technology have improved safety profiles and reduced social downtime. CO2 lasers remain the gold standard of treatment, and fractional ablative devices capable of achieving remarkable clinical improvement with fewer side effects and shorter recovery times have made it a more practical option for patients. Although ablative resurfacing has become safer, careful patient selection and choice of suitable laser parameters are essential to minimize complications and optimize outcomes. This article describes the current modalities used in ablative laser skin resurfacing and examines their efficacy, indications, and possible side effects. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Stress assisted selective ablation of ITO thin film by picosecond laser

NASA Astrophysics Data System (ADS)

Farid, Nazar; Chan, Helios; Milne, David; Brunton, Adam; M. O'Connor, Gerard

2018-01-01

Fast selective pattering with high precession on 175 nm ITO thin film with IR ps lasers is investigated. Ablation parameters are optimized with detailed studies on the scribed depth, topography, and particle generation using AFM and SEM. A comparison of 10 and 150 ps laser revealed that the shorter pulse (10 ps) laser is more appropriate in selective and partial ablation; up to 20 nm resolution for controlled depth with multipulses having energy below the damage threshold is demonstrated. The experimental results are interpreted to involve stress assisted ablation mechanism for the 10 ps laser while thermal ablation along with intense melting occurs for 150 ps laser. The transition between these regimes is estimated to occur at approximately 30 ps.

Observing laser ablation dynamics with sub-picosecond temporal resolution

NASA Astrophysics Data System (ADS)

Tani, Shuntaro; Kobayashi, Yohei

2017-04-01

Laser ablation is one of the most fundamental processes in laser processing, and the understanding of its dynamics is of key importance for controlling and manipulating the outcome. In this study, we propose a novel way of observing the dynamics in the time domain using an electro-optic sampling technique. We found that an electromagnetic field was emitted during the laser ablation process and that the amplitude of the emission was closely correlated with the ablated volume. From the temporal profile of the electromagnetic field, we analyzed the motion of charged particles with subpicosecond temporal resolution. The proposed method can provide new access to observing laser ablation dynamics and thus open a new way to optimize the laser processing.

In vitro parameter optimization for spatial control of focused ultrasound ablation when using low boiling point phase-change nanoemulsions.

PubMed

Puett, Connor; Phillips, Linsey C; Sheeran, Paul S; Dayton, Paul A

2013-01-01

Phase-shift nanoemulsions (PSNEs) provide cavitation sites when the perfluorocarbon (PFC) nanodroplets (ND) are vaporized to microbubbles by acoustic energy. Their presence lowers the power required to ablate tissue by high-intensity focused ultrasound (HIFU), potentially making it a safer option for a broader range of treatment sites. However, spatial control over the ablation region can be problematic when cavitation is used to enhance heating. This study explored relationships between vaporization, ablation, and the PSNE concentration in vitro to optimize the acoustic intensity and insonation time required for spatially controlled ablation enhancement using a PSNE that included a volatile PFC component. HIFU (continuous wave at 1 MHz; insonation times of 5, 10, 15, and 20 s; cool-down times of 2, 4, and 6 s; peak negative pressures of 2, 3, and 4 MPa) was applied to albumin-acrylamide gels containing PFC agents (1:1 mix of volatile decafluorobutane and more stable dodecafluoropentane at 10(5) to 10(8) PFC ND per milliliter) or agent-free controls. Vaporization fields (microbubble clouds) were imaged by conventional ultrasound, and ablation lesions were measured directly by calipers. Controlled ablation was defined as the production of 'cigar'-shaped lesions corresponding with the acoustic focal zone. This control was considered to be lost when ablation occurred in prefocal vaporization fields having a predominantly 'tadpole' or oblong shape. Changes in the vaporization field shape and location occurred on a continuum with increasing PSNE concentration and acoustic intensity. Working with the maximum concentration-intensity combinations resulting in controlled ablation demonstrated a dose-responsive relationship between insonation time and volumes of both the vaporization fields (approximately 20 to 240 mm(3)) and the ablation lesions (1 to 135 mm(3)) within them. HIFU ablation was enhanced by this PSNE and could be achieved using intensities ≤650 W/cm(2). Although the ablation lesions were located within much larger microbubble clouds, optimum insonation times and intensities could be selected to achieve an ablation lesion of desired size and location for a given PSNE concentration. This demonstration of controllable enhancement using a PSNE that contained a volatile PFC component is another step toward developing phase-shift nanotechnology as a potential clinical tool to improve HIFU.

Laser Ablation for Cancer: Past, Present and Future

PubMed Central

Schena, Emiliano; Saccomandi, Paola; Fong, Yuman

2017-01-01

Laser ablation (LA) is gaining acceptance for the treatment of tumors as an alternative to surgical resection. This paper reviews the use of lasers for ablative and surgical applications. Also reviewed are solutions aimed at improving LA outcomes: hyperthermal treatment planning tools and thermometric techniques during LA, used to guide the surgeon in the choice and adjustment of the optimal laser settings, and the potential use of nanoparticles to allow biologic selectivity of ablative treatments. Promising technical solutions and a better knowledge of laser-tissue interaction should allow LA to be used in a safe and effective manner as a cancer treatment. PMID:28613248

Techniques for Optimizing Surgical Scars, Part 2: Hypertrophic Scars and Keloids.

PubMed

Potter, Kathryn; Konda, Sailesh; Ren, Vicky Zhen; Wang, Apphia Lihan; Srinivasan, Aditya; Chilukuri, Suneel

2017-01-01

Surgical management of benign or malignant cutaneous tumors may result in noticeable scars that are of great concern to patients, regardless of sex, age, or ethnicity. Techniques to optimize surgical scars are discussed in this three-part review. Part 2 focuses on scar revision for hypertrophic and keloids scars. Scar revision options for hypertrophic and keloid scars include corticosteroids, bleomycin, fluorouracil, verapamil, avotermin, hydrogel scaffold, nonablative fractional lasers, ablative and fractional ablative lasers, pulsed dye laser (PDL), flurandrenolide tape, imiquimod, onion extract, silicone, and scar massage.

Three-dimensional mapping in the electrophysiological laboratory.

PubMed

Maury, Philippe; Monteil, Benjamin; Marty, Lilian; Duparc, Alexandre; Mondoly, Pierre; Rollin, Anne

2018-06-07

Investigation and catheter ablation of cardiac arrhythmias are currently still based on optimal knowledge of arrhythmia mechanisms in relation to the cardiac anatomy involved, in order to target their crucial components. Currently, most complex arrhythmias are investigated using three-dimensional electroanatomical navigation systems, because these are felt to optimally integrate both the anatomical and electrophysiological features of a given arrhythmia in a given patient. In this article, we review the technical background of available three-dimensional electroanatomical navigation systems, and their potential use in complex ablations. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Thermal response of a 4D carbon/carbon composite with volume ablation: a numerical simulation study

NASA Astrophysics Data System (ADS)

Zhang, Bai; Li, Xudong

2018-02-01

As carbon/carbon composites usually work at high temperature environments, material ablation inevitably occurs, which further affects the system stability and safety. In this paper, the thermal response of a thermoprotective four-directional carbon/carbon (4D C/C) composite is studied herein using a numerical model focusing on volume ablation. The model is based on energy- and mass-conservation principles as well as on the thermal decomposition equation of solid materials. The thermophysical properties of the C/C composite during the ablation process are calculated, and the thermal response during ablation, including temperature distribution, density, decomposition rate, char layer thickness, and mass loss, are quantitatively predicted. The present numerical study provides a fundamental understanding of the ablative mechanisms of a 4D C/C composite, serving as a reference and basis for further designs and optimizations of thermoprotective materials.

Automatic Tracking Algorithm in Coaxial Near-Infrared Laser Ablation Endoscope for Fetus Surgery

NASA Astrophysics Data System (ADS)

Hu, Yan; Yamanaka, Noriaki; Masamune, Ken

2014-07-01

This article reports a stable vessel object tracking method for the treatment of twin-to-twin transfusion syndrome based on our previous 2 DOF endoscope. During the treatment of laser coagulation, it is necessary to focus on the exact position of the target object, however it moves by the mother's respiratory motion and still remains a challenge to obtain and track the position precisely. In this article, an algorithm which uses features from accelerated segment test (FAST) to extract the features and optical flow as the object tracking method, is proposed to deal with above problem. Further, we experimentally simulate the movement due to the mother's respiration, and the results of position errors and similarity verify the effectiveness of the proposed tracking algorithm for laser ablation endoscopy in-vitro and under water considering two influential factors. At average, the errors are about 10 pixels and the similarity over 0.92 are obtained in the experiments.

Emerging needle ablation technology in urology.

PubMed

Leveillee, Raymond J; Pease, Karli; Salas, Nelson

2014-01-01

Thermal ablation of urologic tumors in the form of freezing (cryoablation) and heating (radiofrequency ablation) have been utilized successfully to treat and ablate soft tissue tumors for over 15 years. Multiple studies have demonstrated efficacy nearing that of extirpative surgery for certain urologic conditions. There are technical limitations to their speed and safety profile because of the physical limits of thermal diffusion. Recently, there has been a desire to investigate other forms of energy in an effort to circumvent the limitations of cryoblation and radiofrequency ablation. This review will focus on three relatively new energy applications as they pertain to tissue ablation: microwave, irreversible electroporation, and water vapor. High-intensity-focused ultrasound nor interstitial lasers are discussed, as there have been no recently published updates. Needle and probe-based ablative treatments will continue to play an important role. As three-dimensional imaging workstations move from the advanced radiologic interventional suite to the operating room, surgeons will likely still play a pivotal role in the +-application of these probe ablative devices. It is essential that the surgeon understands the fundamentals of these devices in order to optimize their application.

The effect of dopants on laser imprint mitigation

NASA Astrophysics Data System (ADS)

Phillips, Lee; Gardner, John H.; Bodner, Stephen E.; Colombant, Denis; Dahlburg, Jill

1999-11-01

An intact implosion of a pellet for direct-drive ICF requires that the perturbations imprinted by the laser be kept below some threshold. We report on simulations of targets that incorporate very small concentrations of a high-Z dopant in the ablator, to increase the electron density in the ablating plasma, causing the laser to be absorbed far enough from the solid ablator to achieve a substantial degree of thermal smoothing. These calculations were performed using NRL's FAST radiation hydrodynamics code(J.H. Gardner, A.J. Schmitt, et al., Phys. Plasmas) 5, 1935 (1998), incorporating the flux-corrected transport algorithm and opacities generated by an STA code, with non-LTE radiation transport based on the Busquet method.

Numerical Simulation of Doped Targets for ICF

NASA Astrophysics Data System (ADS)

Phillips, Lee; Gardner, John H.; Bodner, Stephen E.; Colombant, Denis; Klapisch, Marcel; Bar-Shalom, Avraham

1997-11-01

The ablative Rayleigh-Taylor (RT) instability can be reduced by preheating the ablator, thereby reducing the peak density and increasing the mass ablation velocity. The ablator can be preheated with radiation from higher Z dopants.(Gardner, J.H., Bodner, S.E., Dahlburg, J.P., Phys. Fluids 3), 1070 (1991) Dopants also reduce the density gradient at the ablator, which provides a second mechanism to reduce the RT growth rate. We have recently developed a more sophisticated and detailed radiation package that uses opacities generated by an STA code, with non-LTE radiation transport based on the Busquet method. This radiation package has been incorporated into NRL's FAST2D radiation hydrodynamics code, which has been used to evaluate and optimize the use of various dopants that can provide interesting levels of preheat for an ICF target.

Optimization of tissue physical parameters for accurate temperature estimation from finite-element simulation of radiofrequency ablation.

PubMed

Subramanian, Swetha; Mast, T Douglas

2015-10-07

Computational finite element models are commonly used for the simulation of radiofrequency ablation (RFA) treatments. However, the accuracy of these simulations is limited by the lack of precise knowledge of tissue parameters. In this technical note, an inverse solver based on the unscented Kalman filter (UKF) is proposed to optimize values for specific heat, thermal conductivity, and electrical conductivity resulting in accurately simulated temperature elevations. A total of 15 RFA treatments were performed on ex vivo bovine liver tissue. For each RFA treatment, 15 finite-element simulations were performed using a set of deterministically chosen tissue parameters to estimate the mean and variance of the resulting tissue ablation. The UKF was implemented as an inverse solver to recover the specific heat, thermal conductivity, and electrical conductivity corresponding to the measured area of the ablated tissue region, as determined from gross tissue histology. These tissue parameters were then employed in the finite element model to simulate the position- and time-dependent tissue temperature. Results show good agreement between simulated and measured temperature.

Shear Wave Velocity Imaging Using Transient Electrode Perturbation: Phantom and ex vivo Validation

PubMed Central

Varghese, Tomy; Madsen, Ernest L.

2011-01-01

This paper presents a new shear wave velocity imaging technique to monitor radio-frequency and microwave ablation procedures, coined electrode vibration elastography. A piezoelectric actuator attached to an ablation needle is transiently vibrated to generate shear waves that are tracked at high frame rates. The time-to-peak algorithm is used to reconstruct the shear wave velocity and thereby the shear modulus variations. The feasibility of electrode vibration elastography is demonstrated using finite element models and ultrasound simulations, tissue-mimicking phantoms simulating fully (phantom 1) and partially ablated (phantom 2) regions, and an ex vivo bovine liver ablation experiment. In phantom experiments, good boundary delineation was observed. Shear wave velocity estimates were within 7% of mechanical measurements in phantom 1 and within 17% in phantom 2. Good boundary delineation was also demonstrated in the ex vivo experiment. The shear wave velocity estimates inside the ablated region were higher than mechanical testing estimates, but estimates in the untreated tissue were within 20% of mechanical measurements. A comparison of electrode vibration elastography and electrode displacement elastography showed the complementary information that they can provide. Electrode vibration elastography shows promise as an imaging modality that provides ablation boundary delineation and quantitative information during ablation procedures. PMID:21075719

Noninvasive microwave ablation zone radii estimation using x-ray CT image analysis.

PubMed

Weiss, Noam; Goldberg, S Nahum; Nissenbaum, Yitzhak; Sosna, Jacob; Azhari, Haim

2016-08-01

The aims of this study were to noninvasively and automatically estimate both the radius of the ablated liver tissue and the radius encircling the treated zone, which also defines where the tissue is definitely untreated during a microwave (MW) thermal ablation procedure. Fourteen ex vivo bovine fresh liver specimens were ablated at 40 W using a 14 G microwave antenna, for durations of 3, 6, 8, and 10 min. The tissues were scanned every 5 s during the ablation using an x-ray CT scanner. In order to estimate the radius of the ablation zone, the acquired images were transformed into a polar presentation by displaying the Hounsfield units (HU) as a function of angle and radius. From this polar presentation, the average HU radial profile was analyzed at each time point and the ablation zone radius was estimated. In addition, textural analysis was applied to the original CT images. The proposed algorithm identified high entropy regions and estimated the treated zone radius per time. The estimated ablated zone radii as a function of treatment durations were compared, by means of correlation coefficient and root mean square error (RMSE) to gross pathology measurements taken immediately post-treatment from similarly ablated tissue. Both the estimated ablation radii and the treated zone radii demonstrated strong correlation with the measured gross pathology values (R(2) ≥ 0.89 and R(2) ≥ 0.86, respectively). The automated ablation radii estimation had an average discrepancy of less than 1 mm (RMSE = 0.65 mm) from the gross pathology measured values, while the treated zone radii showed a slight overestimation of approximately 1.5 mm (RMSE = 1.6 mm). Noninvasive monitoring of MW ablation using x-ray CT and image analysis is feasible. Automatic estimations of the ablation zone radius and the radius encompassing the treated zone that highly correlate with actual ablation measured values can be obtained. This technique can therefore potentially be used to obtain real time monitoring and improve the clinical outcome.

Fast and automatic depth control of iterative bone ablation based on optical coherence tomography data

NASA Astrophysics Data System (ADS)

Fuchs, Alexander; Pengel, Steffen; Bergmeier, Jan; Kahrs, Lüder A.; Ortmaier, Tobias

2015-07-01

Laser surgery is an established clinical procedure in dental applications, soft tissue ablation, and ophthalmology. The presented experimental set-up for closed-loop control of laser bone ablation addresses a feedback system and enables safe ablation towards anatomical structures that usually would have high risk of damage. This study is based on combined working volumes of optical coherence tomography (OCT) and Er:YAG cutting laser. High level of automation in fast image data processing and tissue treatment enables reproducible results and shortens the time in the operating room. For registration of the two coordinate systems a cross-like incision is ablated with the Er:YAG laser and segmented with OCT in three distances. The resulting Er:YAG coordinate system is reconstructed. A parameter list defines multiple sets of laser parameters including discrete and specific ablation rates as ablation model. The control algorithm uses this model to plan corrective laser paths for each set of laser parameters and dynamically adapts the distance of the laser focus. With this iterative control cycle consisting of image processing, path planning, ablation, and moistening of tissue the target geometry and desired depth are approximated until no further corrective laser paths can be set. The achieved depth stays within the tolerances of the parameter set with the smallest ablation rate. Specimen trials with fresh porcine bone have been conducted to prove the functionality of the developed concept. Flat bottom surfaces and sharp edges of the outline without visual signs of thermal damage verify the feasibility of automated, OCT controlled laser bone ablation with minimal process time.

An observation of ablation effect of soft biotissue by pulsed Er:YAG laser

NASA Astrophysics Data System (ADS)

Zhang, Xianzeng; Xie, Shusen; Ye, Qing; Zhan, Zhenlin

2007-02-01

Because of the unique properties with regard to the absorption in organic tissue, pulsed Er:YAG laser has found most interest for various application in medicine, such as dermatology, dentistry, and cosmetic surgery. However, consensus regarding the optimal parameters for clinical use of this tool has not been reached. In this paper, the laser ablation characteristics of soft tissue by Er:YAG laser irradiation was studied. Porcine skin tissue in vitro was used in the experiment. Laser fluences ranged from 25mJ/mm2 to 200mJ/mm2, repetition rates was 5Hz, spot sizes on the tissue surface was 2mm. The ablation effects were assessed by the means of optical microscope, ablation diameters and depths were measured with reading microscope. It was shown that the ablation of soft biotissue by pulsed Er:YAG laser was a threshold process. With appropriate choice of irradiation parameters, high quality ablation with clean, sharp cuts following closely the spatial contour of the incident beam can be achieved. The curves of ablation crater diameter and depth versus laser fluence were obtained, then the ablation threshold and ablation yield were calculated subsequently, and the influence of the number of pulses fired into a crater on ablation crater depth was also discussed.

Management of bone disease in women after breast cancer.

PubMed

Milat, F; Vincent, A J

2015-01-01

Breast cancer and osteoporosis are common conditions affecting women, particularly following menopause. With increasing breast cancer incidence, effects of therapies and decreasing mortality, issues relating to the preservation of bone health with breast cancer therapy have become a priority. Contributing factors to bone loss and fractures in women with breast cancer include tumor effects, estrogen deprivation secondary to breast cancer therapies (chemotherapy, ovarian ablation or aromatase inhibitors), natural menopause and secondary causes of bone loss, typically from concurrently prescribed medications. Management of osteoporosis and other survivorship care is complex, and a multi-disciplinary approach is recommended with assessment of risk factors for bone loss, optimization of bone health through lifestyle approaches and pharmacological interventions based on evidence-based algorithms. This review examines the pathophysiology of bone loss and gives guidelines for the management of bone disease in women with breast cancer.

Optimal configuration of power grid sources based on optimal particle swarm algorithm

NASA Astrophysics Data System (ADS)

Wen, Yuanhua

2018-04-01

In order to optimize the distribution problem of power grid sources, an optimized particle swarm optimization algorithm is proposed. First, the concept of multi-objective optimization and the Pareto solution set are enumerated. Then, the performance of the classical genetic algorithm, the classical particle swarm optimization algorithm and the improved particle swarm optimization algorithm are analyzed. The three algorithms are simulated respectively. Compared with the test results of each algorithm, the superiority of the algorithm in convergence and optimization performance is proved, which lays the foundation for subsequent micro-grid power optimization configuration solution.

Improved multimodality data fusion of late gadolinium enhancement MRI to left ventricular voltage maps in ventricular tachycardia ablation.

PubMed

Roujol, Sebastien; Basha, Tamer A; Tan, Alex; Khanna, Varun; Chan, Raymond H; Moghari, Mehdi H; Rayatzadeh, Hussein; Shaw, Jaime L; Josephson, Mark E; Nezafat, Reza

2013-05-01

Electroanatomical voltage mapping (EAVM) is commonly performed prior to catheter ablation of scar-related ventricular tachycardia (VT) to locate the arrhythmic substrate and to guide the ablation procedure. EAVM is used to locate the position of the ablation catheter and to provide a 3-D reconstruction of left-ventricular anatomy and scar. However, EAVM measurements only represent the endocardial scar with no transmural or epicardial information. Furthermore, EAVM is a time-consuming procedure, with a high operator dependence and has low sampling density, i.e., spatial resolution. Late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) allows noninvasive assessment of scar morphology that can depict 3-D scar architecture. Despite the potential use of LGE as a roadmap for VT ablation for identification of arrhythmogenic substrate, its utility has been very limited. To allow for identification of VT substrate, a correlation is needed between the substrates identified by EAVM as the gold standard and LGE-MRI scar characteristics. To do so, a system must be developed to fuse the datasets from these modalities. In this study, a registration pipeline for the fusion of LGE-MRI and EAVM data is presented. A novel surface registration algorithm is proposed, integrating the matching of global scar areas as an additional constraint in the registration process. A preparatory landmark registration is initially performed to expedite the convergence of the algorithm. Numerical simulations were performed to evaluate the accuracy of the registration in the presence of errors in identifying landmarks in EAVM or LGE-MRI datasets as well as additional errors due to respiratory or cardiac motion. Subsequently, the accuracy of the proposed fusion system was evaluated in a cohort of ten patients undergoing VT ablation where both EAVM and LGE-MRI data were available. Compared to landmark registration and surface registration, the presented method achieved significant improvement in registration error. The proposed data fusion system allows the fusion of EAVM and LGE-MRI data in VT ablation with registration errors less than 3.5  mm.

Impact of Tricuspid Regurgitation on the Success of Atrioventricular Node Ablation for Rate Control in Patients With Atrial Fibrillation: The Node Blast Study.

PubMed

Reddy, Yeruva Madhu; Gunda, Sampath; Vallakati, Ajay; Kanmanthareddy, Arun; Pillarisetti, Jayasree; Atkins, Donita; Bommana, Sudharani; Emert, Martin P; Pimentel, Rhea; Dendi, Raghuveer; Berenbom, Loren D; Lakkireddy, Dhanunjaya

2015-09-15

Atrioventricular node (AVN) ablation is an effective treatment for symptomatic patients with atrial arrhythmias who are refractory to rhythm and rate control strategies where optimal ventricular rate control is desired. There are limited data on the predictors of failure of AVN ablation. Our objective was to identify the predictors of failure of AVN ablation. This is an observational single-center study of consecutive patients who underwent AVN ablation in a large academic center. Baseline characteristics, procedural variables, and outcomes of AVN ablation were collected. AVN "ablation failure" was defined as resumption of AVN conduction resulting in recurrence of either rapid ventricular response or suboptimal biventricular pacing. A total of 247 patients drug refractory AF who underwent AVN ablation at our center with a mean age of 71 ± 12 years with 46% being males were included. Ablation failure was seen in 11 (4.5%) patients. There were no statistical differences between patients with "ablation failure" versus "ablation success" in any of the baseline clinical variables. Patients with moderate-to-severe tricuspid regurgitation (TR) were much more likely to have ablation failure than those with ablation success (8 [73%] vs 65 [27%]; p = 0.003). All 11 patients with ablation failure had a successful redo procedure, 9 with right and 2 with the left sided approach. On multivariate analysis, presence of moderate-to-severe TR was found to be the only predictor of failure of AVN ablation (odds ratio 9.1, confidence interval 1.99 to 42.22, p = 0.004). In conclusion, moderate-to-severe TR is a strong and independent predictor of failure of AVN ablation. Copyright © 2015 Elsevier Inc. All rights reserved.

Laser ablation in analytical chemistry - A review

DOE Office of Scientific and Technical Information (OSTI.GOV)

Russo, Richard E.; Mao, Xianglei; Liu, Haichen

Laser ablation is becoming a dominant technology for direct solid sampling in analytical chemistry. Laser ablation refers to the process in which an intense burst of energy delivered by a short laser pulse is used to sample (remove a portion of) a material. The advantages of laser ablation chemical analysis include direct characterization of solids, no chemical procedures for dissolution, reduced risk of contamination or sample loss, analysis of very small samples not separable for solution analysis, and determination of spatial distributions of elemental composition. This review describes recent research to understand and utilize laser ablation for direct solid sampling,more » with emphasis on sample introduction to an inductively coupled plasma (ICP). Current research related to contemporary experimental systems, calibration and optimization, and fractionation is discussed, with a summary of applications in several areas.« less

Robot-assisted radiofrequency ablation of a sacral S1-S2 aggressive hemangioma.

PubMed

Kaoudi, A; Capel, C; Chenin, L; Peltier, J; Lefranc, M

2018-05-16

Aggressive vertebral hemangiomas are rare tumors of the spine. The treatment management strategy usually consists of vertebroplasty, radiation therapy or in rare cases of surgical strategy. We present a case of a bulging sacral S1-S2 hemangioma in the spinal canal that could not be managed in the usual manner. Here, we demonstrate the usefulness of radiofrequency ablation technique as an alternative treatment as well as robotic assistance for optimal placement of the ablation probe within the lesion. Copyright © 2018. Published by Elsevier Inc.

How I do it-optimizing radiofrequency ablation in spinal metastases using iCT and navigation.

PubMed

Kavakebi, Pujan; Freyschlag, C F; Thomé, C

2017-10-01

Exact positioning of the radiofrequency ablation (RFA) probe for tumor treatment under fluoroscopic guidance can be difficult because of potentially small inaccessible lesions and the radiation dose to the medical staff in RFA. In addition, vertebroplasty (VP) can be significantly high. Description and workflow of RFA in spinal metastasis using iCT (intraoperative computed tomography) and 3D-navigation-based probe placement followed by VP. RFA and VP can be successfully combined with iCT-based navigation, which leads to a reduction of radiation to the staff and optimal probe positioning due to 3D navigation.

Cryo-balloon catheter localization in fluoroscopic images

NASA Astrophysics Data System (ADS)

Kurzendorfer, Tanja; Brost, Alexander; Jakob, Carolin; Mewes, Philip W.; Bourier, Felix; Koch, Martin; Kurzidim, Klaus; Hornegger, Joachim; Strobel, Norbert

2013-03-01

Minimally invasive catheter ablation has become the preferred treatment option for atrial fibrillation. Although the standard ablation procedure involves ablation points set by radio-frequency catheters, cryo-balloon catheters have even been reported to be more advantageous in certain cases. As electro-anatomical mapping systems do not support cryo-balloon ablation procedures, X-ray guidance is needed. However, current methods to provide support for cryo-balloon catheters in fluoroscopically guided ablation procedures rely heavily on manual user interaction. To improve this, we propose a first method for automatic cryo-balloon catheter localization in fluoroscopic images based on a blob detection algorithm. Our method is evaluated on 24 clinical images from 17 patients. The method successfully detected the cryoballoon in 22 out of 24 images, yielding a success rate of 91.6 %. The successful localization achieved an accuracy of 1.00 mm +/- 0.44 mm. Even though our methods currently fails in 8.4 % of the images available, it still offers a significant improvement over manual methods. Furthermore, detecting a landmark point along the cryo-balloon catheter can be a very important step for additional post-processing operations.

Performance of Er:YAG laser ablation of hard bone under different irrigation water cooling conditions

NASA Astrophysics Data System (ADS)

Beltrán Bernal, Lina M.; Shayeganrad, Gholamreza; Kosa, Gabor; Zelechowski, Marek; Rauter, Georg; Friederich, Niklaus; Cattin, Philippe C.; Zam, Azhar

2018-02-01

The biological applicability of the Erbium-doped Yttrium Aluminum Garnet (Er:YAG) laser in surgical processes is so far limited to hard dental tissues. Using the Er:YAG laser for bone ablation is being studied since it has shown good performance for ablating dental hard tissues at the wavelength 2.94 μm, which coincides with the absorption peak of water, one of the main components of hard tissue, like teeth and bone. To obtain a decent performance of the laser in the cutting process, we aim at examining the influence of sequenced water jet irrigation on both, the ablation rate and the prevention of carbonization while performing laser ablation of bone with fixed laser parameters. An Er:YAG laser at 2.94 μm wavelength, 940 mJ energy per pulse, 400 μs pulse width, and 10 Hz repetition rate is used for the ablation of a porcine femur bone under different pulsed water jet irrigation conditions. We used micro-computed tomography (micro-CT) scans to determine the geometry of the ablated areas. In addition, scanning electron microscopy (SEM) is used for qualitative observations for the presence of carbonization and micro-fractures on the ablated surfaces. We evaluate the performance of the laser ablation process for the different water jet conditions in terms of the ablation rate, quantified by the ablated volume per second and the ablation efficiency, calculated as the ablated volume per pulse energy. We provide an optimized system for laser ablation which delivers the appropriate amount of water to the bone and consequently, the bone is ablated in the most efficient way possible without carbonization.

Polarization image segmentation of radiofrequency ablated porcine myocardial tissue

PubMed Central

Ahmad, Iftikhar; Gribble, Adam; Murtza, Iqbal; Ikram, Masroor; Pop, Mihaela; Vitkin, Alex

2017-01-01

Optical polarimetry has previously imaged the spatial extent of a typical radiofrequency ablated (RFA) lesion in myocardial tissue, exhibiting significantly lower total depolarization at the necrotic core compared to healthy tissue, and intermediate values at the RFA rim region. Here, total depolarization in ablated myocardium was used to segment the total depolarization image into three (core, rim and healthy) zones. A local fuzzy thresholding algorithm was used for this multi-region segmentation, and then compared with a ground truth segmentation obtained from manual demarcation of RFA core and rim regions on the histopathology image. Quantitative comparison of the algorithm segmentation results was performed with evaluation metrics such as dice similarity coefficient (DSC = 0.78 ± 0.02 and 0.80 ± 0.02), sensitivity (Sn = 0.83 ± 0.10 and 0.91 ± 0.08), specificity (Sp = 0.76 ± 0.17 and 0.72 ± 0.17) and accuracy (Acc = 0.81 ± 0.09 and 0.71 ± 0.10) for RFA core and rim regions, respectively. This automatic segmentation of parametric depolarization images suggests a novel application of optical polarimetry, namely its use in objective RFA image quantification. PMID:28380013

Recommendations for dose calculations of lung cancer treatment plans treated with stereotactic ablative body radiotherapy (SABR)

NASA Astrophysics Data System (ADS)

Devpura, S.; Siddiqui, M. S.; Chen, D.; Liu, D.; Li, H.; Kumar, S.; Gordon, J.; Ajlouni, M.; Movsas, B.; Chetty, I. J.

2014-03-01

The purpose of this study was to systematically evaluate dose distributions computed with 5 different dose algorithms for patients with lung cancers treated using stereotactic ablative body radiotherapy (SABR). Treatment plans for 133 lung cancer patients, initially computed with a 1D-pencil beam (equivalent-path-length, EPL-1D) algorithm, were recalculated with 4 other algorithms commissioned for treatment planning, including 3-D pencil-beam (EPL-3D), anisotropic analytical algorithm (AAA), collapsed cone convolution superposition (CCC), and Monte Carlo (MC). The plan prescription dose was 48 Gy in 4 fractions normalized to the 95% isodose line. Tumors were classified according to location: peripheral tumors surrounded by lung (lung-island, N=39), peripheral tumors attached to the rib-cage or chest wall (lung-wall, N=44), and centrally-located tumors (lung-central, N=50). Relative to the EPL-1D algorithm, PTV D95 and mean dose values computed with the other 4 algorithms were lowest for "lung-island" tumors with smallest field sizes (3-5 cm). On the other hand, the smallest differences were noted for lung-central tumors treated with largest field widths (7-10 cm). Amongst all locations, dose distribution differences were most strongly correlated with tumor size for lung-island tumors. For most cases, convolution/superposition and MC algorithms were in good agreement. Mean lung dose (MLD) values computed with the EPL-1D algorithm were highly correlated with that of the other algorithms (correlation coefficient =0.99). The MLD values were found to be ~10% lower for small lung-island tumors with the model-based (conv/superposition and MC) vs. the correction-based (pencil-beam) algorithms with the model-based algorithms predicting greater low dose spread within the lungs. This study suggests that pencil beam algorithms should be avoided for lung SABR planning. For the most challenging cases, small tumors surrounded entirely by lung tissue (lung-island type), a Monte-Carlo-based algorithm may be warranted.

Design calculations for NIF convergent ablator experiments.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Callahan, Debra; Leeper, Ramon Joe; Spears, B. K.

2010-11-01

Design calculations for NIF convergent ablator experiments will be described. The convergent ablator experiments measure the implosion trajectory, velocity, and ablation rate of an x-ray driven capsule and are a important component of the U. S. National Ignition Campaign at NIF. The design calculations are post-processed to provide simulations of the key diagnostics: (1) Dante measurements of hohlraum x-ray flux and spectrum, (2) streaked radiographs of the imploding ablator shell, (3) wedge range filter measurements of D-He3 proton output spectra, and (4) GXD measurements of the imploded core. The simulated diagnostics will be compared to the experimental measurements to providemore » an assessment of the accuracy of the design code predictions of hohlraum radiation temperature, capsule ablation rate, implosion velocity, shock flash areal density, and x-ray bang time. Post-shot versions of the design calculations are used to enhance the understanding of the experimental measurements and will assist in choosing parameters for subsequent shots and the path towards optimal ignition capsule tuning.« less

Irreversible electroporation ablation area enhanced by synergistic high- and low-voltage pulses.

PubMed

Yao, Chenguo; Lv, Yanpeng; Dong, Shoulong; Zhao, Yajun; Liu, Hongmei

2017-01-01

Irreversible electroporation (IRE) produced by a pulsed electric field can ablate tissue. In this study, we achieved an enhancement in ablation area by using a combination of short high-voltage pulses (HVPs) to create a large electroporated area and long low-voltage pulses (LVPs) to ablate the electroporated area. The experiments were conducted in potato tuber slices. Slices were ablated with an array of four pairs of parallel steel electrodes using one of the following four electric pulse protocols: HVP, LVP, synergistic HVP+LVP (SHLVP) or LVP+HVP. Our results showed that the SHLVPs more effectively necrotized tissue than either the HVPs or LVPs, even when the SHLVP dose was the same as or lower than the HVP or LVP doses. The HVP and LVP order mattered and only HVPs+LVPs (SHLVPs) treatments increased the size of the ablation zone because the HVPs created a large electroporated area that was more susceptible to the subsequent LVPs. Real-time temperature change monitoring confirmed that the tissue was non-thermally ablated by the electric pulses. Theoretical calculations of the synergistic effects of the SHLVPs on tissue ablation were performed. Our proposed SHLVP protocol provides options for tissue ablation and may be applied to optimize the current clinical IRE protocols.

Irreversible electroporation ablation area enhanced by synergistic high- and low-voltage pulses

PubMed Central

2017-01-01

Irreversible electroporation (IRE) produced by a pulsed electric field can ablate tissue. In this study, we achieved an enhancement in ablation area by using a combination of short high-voltage pulses (HVPs) to create a large electroporated area and long low-voltage pulses (LVPs) to ablate the electroporated area. The experiments were conducted in potato tuber slices. Slices were ablated with an array of four pairs of parallel steel electrodes using one of the following four electric pulse protocols: HVP, LVP, synergistic HVP+LVP (SHLVP) or LVP+HVP. Our results showed that the SHLVPs more effectively necrotized tissue than either the HVPs or LVPs, even when the SHLVP dose was the same as or lower than the HVP or LVP doses. The HVP and LVP order mattered and only HVPs+LVPs (SHLVPs) treatments increased the size of the ablation zone because the HVPs created a large electroporated area that was more susceptible to the subsequent LVPs. Real-time temperature change monitoring confirmed that the tissue was non-thermally ablated by the electric pulses. Theoretical calculations of the synergistic effects of the SHLVPs on tissue ablation were performed. Our proposed SHLVP protocol provides options for tissue ablation and may be applied to optimize the current clinical IRE protocols. PMID:28253331

Is Cryoballoon Ablation Preferable to Radiofrequency Ablation for Treatment of Atrial Fibrillation by Pulmonary Vein Isolation? A Meta-Analysis

PubMed Central

Xu, Junxia; Huang, Yingqun; Cai, Hongbin; Qi, Yue; Jia, Nan; Shen, Weifeng; Lin, Jinxiu; Peng, Feng; Niu, Wenquan

2014-01-01

Objective Currently radiofrequency and cryoballoon ablations are the two standard ablation systems used for catheter ablation of atrial fibrillation; however, there is no universal consensus on which ablation is the optimal choice. We therefore sought to undertake a meta-analysis with special emphases on comparing the efficacy and safety between cryoballoon and radiofrequency ablations by synthesizing published clinical trials. Methods and Results Articles were identified by searching the MEDLINE and EMBASE databases before September 2013, by reviewing the bibliographies of eligible reports, and by consulting with experts in this field. Data were extracted independently and in duplicate. There were respectively 469 and 635 patients referred for cryoballoon and radiofrequency ablations from 14 qualified clinical trials. Overall analyses indicated that cryoballoon ablation significantly reduced fluoroscopic time and total procedure time by a weighted mean of 14.13 (95% confidence interval [95% CI]: 2.82 to 25.45; P = 0.014) minutes and 29.65 (95% CI: 8.54 to 50.77; P = 0.006) minutes compared with radiofrequency ablation, respectively, whereas ablation time in cryoballoon ablation was nonsignificantly elongated by a weighted mean of 11.66 (95% CI: −10.71 to 34.04; P = 0.307) minutes. Patients referred for cryoballoon ablation had a high yet nonsignificant success rate of catheter ablation compared with cryoballoon ablation (odds ratio; 95% CI; P: 1.34; 0.53 to 3.36; 0.538), and cryoballoon ablation was also found to be associated with the relatively low risk of having recurrent atrial fibrillation (0.75; 0.3 to 1.88; 0.538) and major complications (0.46; 0.11 to 1.83; 0.269). There was strong evidence of heterogeneity and low probability of publication bias. Conclusion Our findings demonstrate greater improvement in fluoroscopic time and total procedure duration for atrial fibrillation patients referred for cryoballoon ablation than those for radiofrequency ablation. PMID:24587324

Role of Contact Force Sensing in Catheter Ablation of Cardiac Arrhythmias: Evolution or History Repeating Itself?

PubMed

Ariyarathna, Nilshan; Kumar, Saurabh; Thomas, Stuart P; Stevenson, William G; Michaud, Gregory F

2018-06-01

Adequate catheter-tissue contact facilitates efficient heat energy transfer to target tissue. Tissue contact is thus critical to achieving lesion transmurality and success of radiofrequency (RF) ablation procedures, a fact recognized more than 2 decades ago. The availability of real-time contact force (CF)-sensing catheters has reinvigorated the field of ablation biophysics and optimized lesion formation. The ability to measure and display CF came with the promise of dramatic improvement in safety and efficacy; however, CF quality was noted to have just as important an influence on lesion formation as absolute CF quantity. Multiple other factors have emerged as key elements influencing effective lesion formation, including catheter stability, lesion contiguity and continuity, lesion density, contact homogeneity across a line of ablation, spatiotemporal dynamics of contact governed by cardiac and respiratory motion, contact directionality, and anatomic wall thickness, in addition to traditional ablation indices of power and RF duration. There is greater appreciation of surrogate markers as a guide to lesion formation, such as impedance fall, loss of pace capture, and change in unipolar electrogram morphology. In contrast, other surrogates such as tactile feedback, catheter motion, and electrogram amplitude are notably poor predictors of actual contact and lesion formation. This review aims to contextualize the role of CF sensing in lesion formation with respect of the fundamental principles of biophysics of RF ablation and summarize the state-of-the-art evidence behind the role of CF in optimizing lesion formation. Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

A prospective development study of software-guided radio-frequency ablation of primary and secondary liver tumors: Clinical intervention modelling, planning and proof for ablation cancer treatment (ClinicIMPPACT).

PubMed

Reinhardt, Martin; Brandmaier, Philipp; Seider, Daniel; Kolesnik, Marina; Jenniskens, Sjoerd; Sequeiros, Roberto Blanco; Eibisberger, Martin; Voglreiter, Philip; Flanagan, Ronan; Mariappan, Panchatcharam; Busse, Harald; Moche, Michael

2017-12-01

Radio-frequency ablation (RFA) is a promising minimal-invasive treatment option for early liver cancer, however monitoring or predicting the size of the resulting tissue necrosis during the RFA-procedure is a challenging task, potentially resulting in a significant rate of under- or over treatments. Currently there is no reliable lesion size prediction method commercially available. ClinicIMPPACT is designed as multicenter-, prospective-, non-randomized clinical trial to evaluate the accuracy and efficiency of innovative planning and simulation software. 60 patients with early liver cancer will be included at four European clinical institutions and treated with the same RFA system. The preinterventional imaging datasets will be used for computational planning of the RFA treatment. All ablations will be simulated simultaneously to the actual RFA procedure, using the software environment developed in this project. The primary outcome measure is the comparison of the simulated ablation zones with the true lesions shown in follow-up imaging after one month, to assess accuracy of the lesion prediction. This unique multicenter clinical trial aims at the clinical integration of a dedicated software solution to accurately predict lesion size and shape after radiofrequency ablation of liver tumors. Accelerated and optimized workflow integration, and real-time intraoperative image processing, as well as inclusion of patient specific information, e.g. organ perfusion and registration of the real RFA needle position might make the introduced software a powerful tool for interventional radiologists to optimize patient outcomes.

Wire ablation dynamics model and its application to imploding wire arrays of different geometries.

PubMed

Esaulov, A A; Kantsyrev, V L; Safronova, A S; Velikovich, A L; Shrestha, I K; Williamson, K M; Osborne, G C

2012-10-01

The paper presents an extended description of the amplified wire ablation dynamics model (WADM), which accounts in a single simulation for the processes of wire ablation and implosion of a wire array load of arbitrary geometry and wire material composition. To investigate the role of wire ablation effects, the implosions of cylindrical and planar wire array loads at the university based generators Cobra (Cornell University) and Zebra (University of Nevada, Reno) have been analyzed. The analysis of the experimental data shows that the wire mass ablation rate can be described as a function of the current through the wire and some coefficient defined by the wire material properties. The aluminum wires were found to ablate with the highest rate, while the copper ablation is the slowest one. The lower wire ablation rate results in a higher inward velocity of the ablated plasma, a higher rate of the energy coupling with the ablated plasma, and a more significant delay of implosion for a heavy load due to the ablation effects, which manifest the most in a cylindrical array configuration and almost vanish in a single-planar array configuration. The WADM is an efficient tool suited for wire array load design and optimization in wide parameter ranges, including the loads with specific properties needed for the inertial confinement fusion research and laboratory astrophysics experiments. The data output from the WADM simulation can be used to simplify the radiation magnetohydrodynamics modeling of the wire array plasma.

Three dimensional characterization of laser ablation craters using high resolution X-ray computed tomography

NASA Astrophysics Data System (ADS)

Galmed, A. H.; du Plessis, A.; le Roux, S. G.; Hartnick, E.; Von Bergmann, H.; Maaza, M.

2018-01-01

Laboratory X-ray computed tomography is an emerging technology for the 3D characterization and dimensional analysis of many types of materials. In this work we demonstrate the usefulness of this characterization method for the full three dimensional analysis of laser ablation craters, in the context of a laser induced breakdown spectroscopy setup. Laser induced breakdown spectroscopy relies on laser ablation for sampling the material of interest. We demonstrate here qualitatively (in images) and quantitatively (in terms of crater cone angles, depths, diameters and volume) laser ablation crater analysis in 3D for metal (aluminum) and rock (false gold ore). We show the effect of a Gaussian beam profile on the resulting crater geometry, as well as the first visual evidence of undercutting in the rock sample, most likely due to ejection of relatively large grains. The method holds promise for optimization of laser ablation setups especially for laser induced breakdown spectroscopy.

Hypertrichotic Becker's nevi treated with combination 1,550 nm non-ablative fractional photothermolysis and laser hair removal.

PubMed

Balaraman, Brundha; Friedman, Paul M

2016-04-01

The removal of Becker's nevi poses a significant challenge due to limited available therapeutic options and increased risk of adverse effects, including scarring and dyspigmentation. Herein, we present the use of the non-ablative fractional photothermolysis in combination with laser hair removal for the treatment of hypertrichotic Becker's nevi. Retrospective analysis of three patients with Becker's nevi revealed that two patients with hypertrichotic Becker's nevi had greater than 75% clearance with combination therapy, and one patient with atrichotic Becker's nevus had a similar result with monotherapy non-ablative fractional photothermolysis. This report demonstrates the utility and safety of combination non-ablative fractional resurfacing and laser hair removal for the treatment of hypertrichotic Becker's nevi, and monotherapy non-ablative fractional photothermolysis for atrichotic Becker's nevi. Further comparative studies are necessary to determine optimal laser parameters, treatment schedules, and response duration. © 2016 Wiley Periodicals, Inc.

Picosecond laser ablation of polyamide electrospun nanofibers

NASA Astrophysics Data System (ADS)

Götze, Marco; Krimig, Olaf; Kürbitz, Tobias; Henning, Sven; Heilmann, Andreas; Hillrichs, Georg

2017-02-01

Electrospun nanofibers mats have a great potential in tissue engineering and regenerative medicine. Their high porosity and enormous volume to surface ratio stimulate the growth and adhesion of mammalian cells and serve as a stable support structure. These suitable properties can be further optimized by structuring of the nanofibers. Ultrashort pulsed lasers can be used for modifying of the electrospun nanofibers without significant heat exposure. It seems also possible to generate very fine cuts from the fiber mats. In this study, polyamide electrospun nanofibers samples were processed with picosecond UV-laser irradiation (λ = 355 nm, τ = 15 ps). The samples were processed in dry, wet and immersed condition. To optimize cutting and structuring of nanofiber tissue flakes, the influence of different laser parameters on line widths, edge quality, heat-affected zone (HAZ) and the contamination of the fibers by ablated particles (debris) were examined. One additional aim was the minimization of the flake size. It was possible to generate nanofiber flakes in the sub-millimeter range. The quality of the nanofiber flakes could be improved by ablation near the ablation threshold of the material. For cutting under wet conditions shrinking of the flakes has to be taken into account.

Analysis of radiation parameters to control the effects of Nd:YAG laser surgery on gastric malignancies

NASA Astrophysics Data System (ADS)

Pelayo-Fernández, M. L.; Fanjul-Vélez, F.; Salas-García, I.; Hernández-González, A.; Arce-Diego, J. L.

2015-07-01

Endoscopic laser surgery provides an advantageous alternative to Argon Plasma Coagulation, endoscopic tweezers or electro-ablation in gastroenterology that facilitates a selective ablation of stomach tumors with an additional hemostatic effect in the surrounding tissue. This coagulation effect can also be employed for the treatment of gastric ulcers. It is mandatory to control the laser parameters regardless of the desired effect, either cancerous tissue ablation or coagulation to prevent ulcerous bleeding, in order to avoid stomach wall perforation or an insufficient therapeutic outcome. Dosimetric models constitute an attractive tool to determine the proper light dose in order to offer a customized therapy planning that optimizes the treatment results. In this work, a model for Nd:YAG laser surgery is applied to predict both the coagulation zone in gastric ulcers and the removal in adenocarcinomas under different laser setups. Results show clear differences in the effective zone of the gastric malignancy affected by both coagulation and ablation. Therefore the current model could be employed in the clinical practice to plan the optimal laser beam parameters to treat a certain type of pathologic stomach tissue with variable morphology and without risk of perforation or undertreated parts.

Management algorithms for cervical cancer screening and precancer treatment for resource-limited settings.

PubMed

Basu, Partha; Meheus, Filip; Chami, Youssef; Hariprasad, Roopa; Zhao, Fanghui; Sankaranarayanan, Rengaswamy

2017-07-01

Management algorithms for screen-positive women in cervical cancer prevention programs have undergone substantial changes in recent years. The WHO strongly recommends human papillomavirus (HPV) testing for primary screening, if affordable, or if not, then visual inspection with acetic acid (VIA), and promotes treatment directly following screening through the screen-and-treat approach (one or two clinic visits). While VIA-positive women can be offered immediate ablative treatment based on certain eligibility criteria, HPV-positive women need to undergo subsequent VIA to determine their eligibility. Simpler ablative methods of treatment such as cryotherapy and thermal coagulation have been demonstrated to be effective and to have excellent safety profiles, and these have become integral parts of new management algorithms. The challenges faced by low-resource countries are many and include, from the management perspective, identifying an affordable point-of-care HPV detection test, minimizing over-treatment, and installing an effective information system to ensure high compliance to treatment and follow-up. © 2017 The Authors. International Journal of Gynecology & Obstetrics published by John Wiley & Sons Ltd on behalf of International Federation of Gynecology and Obstetrics.

SU-E-T-91: Accuracy of Dose Calculation Algorithms for Patients Undergoing Stereotactic Ablative Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tajaldeen, A; Ramachandran, P; Geso, M

2015-06-15

Purpose: The purpose of this study was to investigate and quantify the variation in dose distributions in small field lung cancer radiotherapy using seven different dose calculation algorithms. Methods: The study was performed in 21 lung cancer patients who underwent Stereotactic Ablative Body Radiotherapy (SABR). Two different methods (i) Same dose coverage to the target volume (named as same dose method) (ii) Same monitor units in all algorithms (named as same monitor units) were used for studying the performance of seven different dose calculation algorithms in XiO and Eclipse treatment planning systems. The seven dose calculation algorithms include Superposition, Fastmore » superposition, Fast Fourier Transform ( FFT) Convolution, Clarkson, Anisotropic Analytic Algorithm (AAA), Acurous XB and pencil beam (PB) algorithms. Prior to this, a phantom study was performed to assess the accuracy of these algorithms. Superposition algorithm was used as a reference algorithm in this study. The treatment plans were compared using different dosimetric parameters including conformity, heterogeneity and dose fall off index. In addition to this, the dose to critical structures like lungs, heart, oesophagus and spinal cord were also studied. Statistical analysis was performed using Prism software. Results: The mean±stdev with conformity index for Superposition, Fast superposition, Clarkson and FFT convolution algorithms were 1.29±0.13, 1.31±0.16, 2.2±0.7 and 2.17±0.59 respectively whereas for AAA, pencil beam and Acurous XB were 1.4±0.27, 1.66±0.27 and 1.35±0.24 respectively. Conclusion: Our study showed significant variations among the seven different algorithms. Superposition and AcurosXB algorithms showed similar values for most of the dosimetric parameters. Clarkson, FFT convolution and pencil beam algorithms showed large differences as compared to superposition algorithms. Based on our study, we recommend Superposition and AcurosXB algorithms as the first choice of algorithms in lung cancer radiotherapy involving small fields. However, further investigation by Monte Carlo simulation is required to confirm our results.« less

Investigation of factors affecting the synthesis of nano-cadmium sulfide by pulsed laser ablation in liquid environment

NASA Astrophysics Data System (ADS)

Darwish, Ayman M.; Eisa, Wael H.; Shabaka, Ali A.; Talaat, Mohamed H.

2016-01-01

Pulsed laser ablation in a liquid medium is a promising technique as compared to the other synthetic methods to synthesize different materials in nanoscale form. The laser parameters (e.g., wavelength, pulse width, fluence, and repetition frequency) and liquid medium (e.g., aqueous/nonaqueous liquid or solution with surfactant) were tightly controlled during and after the ablation process. By optimizing these parameters, the particle size and distribution of materials can be adjusted. The UV-vis absorption spectra and weight changes of targets were used for the characterization and comparison of products.

Thyroid Radiofrequency Ablation: Updates on Innovative Devices and Techniques

PubMed Central

Park, Hye Sun; Park, Auh Whan; Chung, Sae Rom; Choi, Young Jun; Lee, Jeong Hyun

2017-01-01

Radiofrequency ablation (RFA) is a well-known, effective, and safe method for treating benign thyroid nodules and recurrent thyroid cancers. Thyroid-dedicated devices and basic techniques for thyroid RFA were introduced by the Korean Society of Thyroid Radiology (KSThR) in 2012. Thyroid RFA has now been adopted worldwide, with subsequent advances in devices and techniques. To optimize the treatment efficacy and patient safety, understanding the basic and advanced RFA techniques and selecting the optimal treatment strategy are critical. The goal of this review is to therefore provide updates and analysis of current devices and advanced techniques for RFA treatment of benign thyroid nodules and recurrent thyroid cancers. PMID:28670156

Mass balance model parameter transferability on a tropical glacier

NASA Astrophysics Data System (ADS)

Gurgiser, Wolfgang; Mölg, Thomas; Nicholson, Lindsey; Kaser, Georg

2013-04-01

The mass balance and melt water production of glaciers is of particular interest in the Peruvian Andes where glacier melt water has markedly increased water supply during the pronounced dry seasons in recent decades. However, the melt water contribution from glaciers is projected to decrease with appreciable negative impacts on the local society within the coming decades. Understanding mass balance processes on tropical glaciers is a prerequisite for modeling present and future glacier runoff. As a first step towards this aim we applied a process-based surface mass balance model in order to calculate observed ablation at two stakes in the ablation zone of Shallap Glacier (4800 m a.s.l., 9°S) in the Cordillera Blanca, Peru. Under the tropical climate, the snow line migrates very frequently across most of the ablation zone all year round causing large temporal and spatial variations of glacier surface conditions and related ablation. Consequently, pronounced differences between the two chosen stakes and the two years were observed. Hourly records of temperature, humidity, wind speed, short wave incoming radiation, and precipitation are available from an automatic weather station (AWS) on the moraine near the glacier for the hydrological years 2006/07 and 2007/08 while stake readings are available at intervals of between 14 to 64 days. To optimize model parameters, we used 1000 model simulations in which the most sensitive model parameters were varied randomly within their physically meaningful ranges. The modeled surface height change was evaluated against the two stake locations in the lower ablation zone (SH11, 4760m) and in the upper ablation zone (SH22, 4816m), respectively. The optimal parameter set for each point achieved good model skill but if we transfer the best parameter combination from one stake site to the other stake site model errors increases significantly. The same happens if we optimize the model parameters for each year individually and transfer these combinations to the other year. We show that multi-site and multi-year analyses are crucial before extrapolating ablation modeling to larger glacier areas. So far tested surface albedo schemes and respective parameterizations can obviously not satisfyingly reproduce the dynamics of glacier surface conditions at our study site and new solutions to the problem have to be explored.

Radiofrequency electrode vibration-induced shear wave imaging for tissue modulus estimation: a simulation study.

PubMed

Bharat, Shyam; Varghese, Tomy

2010-10-01

Quasi-static electrode displacement elastography, used for in-vivo imaging of radiofrequency ablation-induced lesions in abdominal organs such as the liver and kidney, is extended in this paper to dynamic vibrational perturbations of the ablation electrode. Propagation of the resulting shear waves into adjoining regions of tissue can be tracked and the shear wave velocity used to quantify the shear (and thereby Young's) modulus of tissue. The algorithm used utilizes the time-to-peak displacement data (obtained from finite element analyses) to calculate the speed of shear wave propagation in the material. The simulation results presented illustrate the feasibility of estimating the Young's modulus of tissue and is promising for characterizing the stiffness of radiofrequency-ablated thermal lesions and surrounding normal tissue.

Brain Emboli After Left Ventricular Endocardial Ablation.

PubMed

Whitman, Isaac R; Gladstone, Rachel A; Badhwar, Nitish; Hsia, Henry H; Lee, Byron K; Josephson, S Andrew; Meisel, Karl M; Dillon, William P; Hess, Christopher P; Gerstenfeld, Edward P; Marcus, Gregory M

2017-02-28

Catheter ablation for ventricular tachycardia and premature ventricular complexes (PVCs) is common. Catheter ablation of atrial fibrillation is associated with a risk of cerebral emboli attributed to cardioversions and numerous ablation lesions in the low-flow left atrium, but cerebral embolic risk in ventricular ablation has not been evaluated. We enrolled 18 consecutive patients meeting study criteria scheduled for ventricular tachycardia or PVC ablation over a 9-month period. Patients undergoing left ventricular (LV) ablation were compared with a control group of those undergoing right ventricular ablation only. Patients were excluded if they had implantable cardioverter defibrillators or permanent pacemakers. Radiofrequency energy was used for ablation in all cases and heparin was administered with goal-activated clotting times of 300 to 400 seconds for all LV procedures. Pre- and postprocedural brain MRI was performed on each patient within a week of the ablation procedure. Embolic infarcts were defined as new foci of reduced diffusion and high signal intensity on fluid-attenuated inversion recovery brain MRI within a vascular distribution. The mean age was 58 years, half of the patients were men, half had a history of hypertension, and the majority had no known vascular disease or heart failure. LV ablation was performed in 12 patients (ventricular tachycardia, n=2; PVC, n=10) and right ventricular ablation was performed exclusively in 6 patients (ventricular tachycardia, n=1; PVC, n=5). Seven patients (58%) undergoing LV ablation experienced a total of 16 cerebral emboli, in comparison with zero patients undergoing right ventricular ablation ( P =0.04). Seven of 11 patients (63%) undergoing a retrograde approach to the LV developed at least 1 new brain lesion. More than half of patients undergoing routine LV ablation procedures (predominately PVC ablations) experienced new brain emboli after the procedure. Future research is critical to understanding the long-term consequences of these lesions and to determining optimal strategies to avoid them. © 2017 American Heart Association, Inc.

Multiple-electrode radiofrequency ablation: simultaneous production of separate zones of coagulation in an in vivo porcine liver model.

PubMed

Laeseke, Paul F; Sampson, Lisa A; Haemmerich, Dieter; Brace, Chris L; Fine, Jason P; Frey, Tina M; Winter, Thomas C; Lee, Fred T

2005-12-01

A multiple-electrode radiofrequency (RF) system was developed based on switching between electrodes that allows for the simultaneous use of as many as three electrically independent electrodes. The purpose of this study was to determine if each multiple-electrode ablation zone is identical to an ablation zone created with conventional single-electrode mode. Nine female domestic pigs (mean weight, 90 kg) were used for this study. A prototype monopolar multiple-electrode RF ablation system was created with use of an RF generator and an electronic switching algorithm. A maximum of three electrodes can be used simultaneously by switching between electrodes at each impedance spike (30 omega greater than baseline levels). A total of 39 zones of ablation were created at open laparotomy in pig livers with use of a conventional single electrode (n = 9), two single electrodes simultaneously (n = 6 ablations; 12 ablation zones), or three single electrodes simultaneously (n = 6 ablations; 18 ablation zones). RF electrodes were spaced in separate lobes of the liver when multiple zones of coagulation were created simultaneously. Animals were euthanized after RF ablation, livers were removed, and ablation zones were sectioned and measured. Zones of coagulation created simultaneously with two or three electrodes were equivalent to ablation zones created with use of conventional single-electrode ablation. No significant differences were observed among control animals treated with a single electrode, those with two separate zones of ablation created simultaneously, and those with three simultaneously created ablation zones in terms of mean (+/-SD) minimum diameter (1.6 cm +/- 0.6, 1.6 cm +/- 0.5, and 1.7 cm +/- 0.4, respectively), maximum diameter (2.0 cm +/- 0.5, 2.3 cm +/- 0.5, 2.2 cm +/- 0.5, respectively), and volume (6.7 cm3 +/- 3.7, 7.4 cm3 +/- 3.8, and 7.8 cm3 +/- 3.9; P > .30, analysis of variance, pairwise t-test comparisons). A rapid-switching multiple-electrode RF system was able to simultaneously create as many as three separate ablation zones of equivalent size compared with single-electrode controls. This system would allow physicians to simultaneously treat multiple tumors, substantially reducing procedure time and anesthesia risk.

An efficient algorithm for function optimization: modified stem cells algorithm

NASA Astrophysics Data System (ADS)

Taherdangkoo, Mohammad; Paziresh, Mahsa; Yazdi, Mehran; Bagheri, Mohammad Hadi

2013-03-01

In this paper, we propose an optimization algorithm based on the intelligent behavior of stem cell swarms in reproduction and self-organization. Optimization algorithms, such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm and Artificial Bee Colony (ABC) algorithm, can give solutions to linear and non-linear problems near to the optimum for many applications; however, in some case, they can suffer from becoming trapped in local optima. The Stem Cells Algorithm (SCA) is an optimization algorithm inspired by the natural behavior of stem cells in evolving themselves into new and improved cells. The SCA avoids the local optima problem successfully. In this paper, we have made small changes in the implementation of this algorithm to obtain improved performance over previous versions. Using a series of benchmark functions, we assess the performance of the proposed algorithm and compare it with that of the other aforementioned optimization algorithms. The obtained results prove the superiority of the Modified Stem Cells Algorithm (MSCA).

Robotic navigation and ablation.

PubMed

Malcolme-Lawes, L; Kanagaratnam, P

2010-12-01

Robotic technologies have been developed to allow optimal catheter stability and reproducible catheter movements with the aim of achieving contiguous and transmural lesion delivery. Two systems for remote navigation of catheters within the heart have been developed; the first is based on a magnetic navigation system (MNS) Niobe, Stereotaxis, Saint-Louis, Missouri, USA, the second is based on a steerable sheath system (Sensei, Hansen Medical, Mountain View, CA, USA). Both robotic and magnetic navigation systems have proven to be feasible for performing ablation of both simple and complex arrhythmias, particularly atrial fibrillation. Studies to date have shown similar success rates for AF ablation compared to that of manual ablation, with many groups finding a reduction in fluoroscopy times. However, the early learning curve of cases demonstrated longer procedure times, mainly due to additional setup times. With centres performing increasing numbers of robotic ablations and the introduction of a pressure monitoring system, lower power settings and instinctive driving software, complication rates are reducing, and fluoroscopy times have been lower than manual ablation in many studies. As the demand for catheter ablation for arrhythmias such as atrial fibrillation increases and the number of centres performing these ablations increases, the demand for systems which reduce the hand skill requirement and improve the comfort of the operator will also increase.

Treatment of Recurrent Nonparoxysmal Atrial Fibrillation Using Focal Impulse and Rotor Mapping (FIRM)-Guided Rotor Ablation: Early Recurrence and Long-Term Outcomes.

PubMed

Spitzer, Stefan Georg; Károlyi, László; Rämmler, Carola; Scharfe, Frank; Weinmann, Thomas; Zieschank, Mirko; Langbein, Anke

2017-01-01

A patient-tailored ablation approach focused on the elimination of both pulmonary vein triggers as well as substrate drivers may result in favorable outcomes in recurrent persistent AF patients. We evaluated the long-term outcomes of rotor ablation combined with conventional pulmonary vein isolation (PVI) in patients with recurrent nonparoxysmal AF. Fifty-eight consecutive patients underwent FIRM-guided rotor ablation followed by conventional PVI for the treatment of recurrent nonparoxysmal AF. A software algorithm was used to display rotational activity at rotor sites by creating propagation maps from unipolar electrograms recorded using a 64-electrode basket catheter. These rotor sites were targeted for ablation, followed by conventional PVI. All patients had nonparoxysmal AF (83% longstanding persistent) and a previously failed conventional ablation procedure. Stable rotors were identified in all patients (mean of 3.0 ± 1.6 per patient), with 55.2% having right atrial rotors and 96.6% left atrial rotors, respectively. Complications occurred in 5.2% of patients, none related to the FIRM procedure. The median follow-up was 12 months. At 6 and 12 months of follow-up, 73.2% and 76.9% of patients remained free from AF/AT, respectively. Excluding 2 patients who underwent a successful redo ablation procedure/electrical cardioversion, at 12 months of follow-up, 69.2% were free from any AF/AT and 73.1% were free from AF after a single FIRM-guided ablation procedure. A high degree of success was observed in this cohort of primarily longstanding persistent AF patients treated for recurrent AF with FIRM-guided rotor ablation. Prospective randomized controlled trials are needed. © 2016 Wiley Periodicals, Inc.

Surgical therapy of vulvar cancer: how to choose the correct reconstruction?

PubMed Central

2016-01-01

Objective To create a comprehensive algorithmic approach to reconstruction after vulvar cancer ablative surgery, which includes both traditional and perforator flaps, evaluating anatomical subunits and shape of the defect. Methods We retrospectively reviewed 80 cases of reconstruction after vulvar cancer ablative surgery, performed between June 2006 and January 2016, transferring 101 flaps. We registered the possibility to achieve the complete wound closure, even in presence of very complex defects, and the postoperative complications. On the basis of these experience, analyzing the choices made and considering the complications, we developed an algorithm to help with the selection of the flap in vulvoperineal reconstruction after oncologic ablative surgery for vulvar cancer. Results We employed eight types of different flaps, including 54 traditional fasciocutaneous V-Y flaps, 23 rectus abdominis myocutaneous flaps, 11 anterolateral thigh flaps, three V-Y gracilis myocutaneous flaps, three free style perforators V-Y flaps from the inner thigh, two Limberg flaps, two lotus flaps, two deep inferior epigastric artery perforator flap, and one superficial circumflex iliac artery perforator flap. The structures most frequently involved in resection were vulva, perineum, mons pubis, groins, vagina, urethra and, more rarely, rectum, bladder, and lower abdominal wall. Conclusion The algorithm we implemented can be a useful tool to help flap selection. The key points in the decision-making process are: anatomical subunits to be covered, overall shape and symmetry of the defect and some patient features such as skin laxity or previous radiotherapy. Perforator flaps, when feasible, must be considered standard in vulvoperineal reconstruction, although in some cases traditional flaps remain the best choice. PMID:27550406

Use of New Imaging CARTO® Segmentation Module Software to Facilitate Ablation of Ventricular Arrhythmias.

PubMed

Tovia-Brodie, Oholi; Belhassen, Bernard; Glick, Aharon; Shmilovich, Haim; Aviram, Galit; Rosso, Raphael; Michowitz, Yoav

2017-02-01

A new imaging software (CARTO® Segmentation Module, Biosense Webster) allows preprocedural 3-D reconstruction of all heart chambers based on cardiac CT. We describe our initial experience with the new module during ablation of ventricular arrhythmias. Eighteen consecutive patients with idiopathic ventricular arrhythmias or ischemic ventricular tachycardia (VT) were studied. In the latter group, a combined endocardial and epicardial ablation was performed. Of the 14 patients with idiopathic arrhythmias, 12 were ablated in the outflow tract (OT), 1 in the midseptal left ventricle, and 1 at the left posterior fascicular area; acute successful ablation was achieved in 11 (78.6%) patients. The procedure was discontinued due to close proximity of the arrhythmia origin to the coronary arteries (CA) in 2 patients. Acute successful uncomplicated ablation was achieved in all 4 patients with ischemic VT. During ablation in the coronary cusps commissures, the CARTO® Segmentation Module accurately defined the cusps anatomy. The precise anatomic location provided by the module assisted in successfully ablating when information from activation mapping was not optimal, by ablating at the opposite side of the cusps. In addition, by demonstrating the precise location of the CA, it allowed safe ablation of arrhythmias that originated in close proximity to the CA both in the OT area and the epicardium, eliminating the need for repeat angiography. The CARTO® Segmentation Module is useful for accurate definition of the exact anatomic location of ventricular arrhythmias and for safely ablating them especially in close proximity to the CA. © 2016 Wiley Periodicals, Inc.

Prediction of Ablation Rates from Solid Surfaces Exposed to High Temperature Gas Flow

NASA Technical Reports Server (NTRS)

Akyuzlu, Kazim M.; Coote, David

2013-01-01

A mathematical model and a solution algorithm is developed to study the physics of high temperature heat transfer and material ablation and identify the problems associated with the flow of hydrogen gas at very high temperatures and velocities through pipes and various components of Nuclear Thermal Rocket (NTR) motors. Ablation and melting can be experienced when the inner solid surface of the cooling channels and the diverging-converging nozzle of a Nuclear Thermal Rocket (NTR) motor is exposed to hydrogen gas flow at temperatures around 2500 degrees Kelvin and pressures around 3.4 MPa. In the experiments conducted on typical NTR motors developed in 1960s, degradation of the cooling channel material (cracking in the nuclear fuel element cladding) and in some instances melting of the core was observed. This paper presents the results of a preliminary study based on two types of physics based mathematical models that were developed to simulate the thermal-hydrodynamic conditions that lead to ablation of the solid surface of a stainless steel pipe exposed to high temperature hydrogen gas near sonic velocities. One of the proposed models is one-dimensional and assumes the gas flow to be unsteady, compressible and viscous. An in-house computer code was developed to solve the conservations equations of this model using a second-order accurate finite-difference technique. The second model assumes the flow to be three-dimensional, unsteady, compressible and viscous. A commercial CFD code (Fluent) was used to solve the later model equations. Both models assume the thermodynamic and transport properties of the hydrogen gas to be temperature dependent. In the solution algorithm developed for this study, the unsteady temperature of the pipe is determined from the heat equation for the solid. The solid-gas interface temperature is determined from an energy balance at the interface which includes heat transfer from or to the interface by conduction, convection, radiation, and ablation. Two different ablation models are proposed to determine the heat loss from the solid surface due to the ablation of the solid material. Both of them are physics based. Various numerical simulations were carried out using both models to predict the temperature distribution in the solid and in the gas flow, and then predict the ablation rates at a typical NTR motor hydrogen gas temperature and pressure. Solid mass loss rate per foot of a pipe was also calculated from these predictions. The results are presented for fully developed turbulent flow conditions in a sample SS pipe with a 6 inch diameter.

Visual servoing of a laser ablation based cochleostomy

NASA Astrophysics Data System (ADS)

Kahrs, Lüder A.; Raczkowsky, Jörg; Werner, Martin; Knapp, Felix B.; Mehrwald, Markus; Hering, Peter; Schipper, Jörg; Klenzner, Thomas; Wörn, Heinz

2008-03-01

The aim of this study is a defined, visually based and camera controlled bone removal by a navigated CO II laser on the promontory of the inner ear. A precise and minimally traumatic opening procedure of the cochlea for the implantation of a cochlear implant electrode (so-called cochleostomy) is intended. Harming the membrane linings of the inner ear can result in damage of remaining organ functions (e.g. complete deafness or vertigo). A precise tissue removal by a laser-based bone ablation system is investigated. Inside the borehole the pulsed laser beam is guided automatically over the bone by using a two mirror galvanometric scanner. The ablation process is controlled by visual servoing. For the detection of the boundary layers of the inner ear the ablation area is monitored by a color camera. The acquired pictures are analyzed by image processing. The results of this analysis are used to control the process of laser ablation. This publication describes the complete system including image processing algorithms and the concept for the resulting distribution of single laser pulses. The system has been tested on human cochleae in ex-vivo studies. Further developments could lead to safe intraoperative openings of the cochlea by a robot based surgical laser instrument.

Synthesis by picosecond laser ablation of ligand-free Ag and Au nanoparticles for SERS applications

NASA Astrophysics Data System (ADS)

Fazio, Enza; Spadaro, Salvatore; Santoro, Marco; Trusso, Sebastiano; Lucotti, Andrea.; Tommasini, Matteo.; Neri, Fortunato; Maria Ossi, Paolo

2018-01-01

The morphological and optical properties of noble metal nanoparticles prepared by picosecond laser generated plasmas in water were investigated. First, the ablation efficiency was maximized searching the optimal focusing conditions. The nanoparticle size, measured by Scanning Transmission Electron Microscopy, strongly depends on the laser fluence, keeping fixed the other deposition parameters such as the target to scanner objective distance and laser repetition frequency. STEM images indicate narrow gradients of NP sizes. Hence the optimization of ablation parameters favours a fine tuning of nanoparticles. UV-Visible spectroscopy helped to determine the appropriate laser wavelength to resonantly excite the localized surface plasmon to carry out Surface Enhanced Raman Scattering (SERS) measurements. The SERS activity of Ag and Au substrates, obtained spraying the colloids synthesized in water, was tested using crystal violet as a probe molecule. The good SERS performance, observed at excitation wavelength 785 nm, is attributed to aggregation phenomena of nanoparticles sprayed on the support.

The Influence of the Aspheric Profiles for Transition Zone on Optical Performance of Human Eye After Conventional Ablation

NASA Astrophysics Data System (ADS)

Fang, L.

2014-12-01

The analysis in the impact of transition zone on the optical performance of human eye after laser refractive surgery is important for improving visual correction technology. By designing the ablation profiles of aspheric transition zone and creating the ablation profile for conventional refractive surgery in optical zone, the influence of aspheric transition zone on residual aberrations was studied. The results indicated that the ablation profiles of transition zone had a significant influence on the residual wavefront aberrations. For a hyperopia correction, the profile #9 shows a larger induced coma and spherical aberration when the translation of the centre of pupil remains constant. However, for a myopia astigmatism correction, the induced coma and spherical aberration in profile #1 shows relatively larger RMS values than those in other profiles. Therefore, the residual higher order aberrations may be decreased by optimizing ablation profiles of transition zone, but they cannot be eliminated. In order to achieve the best visual performance, the design of ablation pattern of transition zone played a crucial role.

Luminal esophageal temperature monitoring with a deflectable esophageal temperature probe and intracardiac echocardiography may reduce esophageal injury during atrial fibrillation ablation procedures: results of a pilot study.

PubMed

Leite, Luiz R; Santos, Simone N; Maia, Henrique; Henz, Benhur D; Giuseppin, Fábio; Oliverira, Anderson; Zanatta, André R; Peres, Ayrton K; Novakoski, Clarissa; Barreto, Jose R; Vassalo, Fabrício; d'Avila, Andre; Singh, Sheldon M

2011-04-01

Luminal esophageal temperature (LET) monitoring is one strategy to minimize esophageal injury during atrial fibrillation ablation procedures. However, esophageal ulceration and fistulas have been reported despite adequate LET monitoring. The objective of this study was to assess a novel approach to LET monitoring with a deflectable LET probe on the rate of esophageal injury in patients undergoing atrial fibrillation ablation. Forty-five consecutive patients undergoing an atrial fibrillation ablation procedure followed by esophageal endoscopy were included in this prospective observational pilot study. LET monitoring was performed with a 7F deflectable ablation catheter that was positioned as close as possible to the site of left atrial ablation using the deflectable component of the catheter guided by visualization of its position on intracardiac echocardiography. Ablation in the posterior left atrial was limited to 25 W and terminated when the LET increased 2°C from baseline. Endoscopy was performed 1 to 2 days after the procedure. All patients had at least 1 LET elevation >2°C necessitating cessation of ablation. Deflection of the LET probe was needed to accurately measure LET in 5% of patients when ablating near the left pulmonary veins, whereas deflection of the LET probe was necessary in 88% of patients when ablating near the right pulmonary veins. The average maximum increase in LET was 2.5±1.5°C. No patients had esophageal thermal injury on follow-up endoscopy. A strategy of optimal LET probe placement using a deflectable LET probe and intracardiac echocardiography guidance, combined with cessation of radiofrequency ablation with a 2°C rise in LET, may reduce esophageal thermal injury during left atrial ablation procedures.

Orbit Modification of Earth-Crossing Asteroids/Comets Using Rendezvous Spacecraft and Laser Ablation

NASA Technical Reports Server (NTRS)

Park, Sang-Young; Mazanek, Daniel D.

2005-01-01

This report describes the approach and results of an end-to-end simulation to deflect a long-period comet (LPC) by using a rapid rendezvous spacecraft and laser ablation system. The laser energy required for providing sufficient deflection DELTA V and an analysis of possible intercept/rendezvous spacecraft trajectories are studied in this analysis. These problems minimize a weighted sum of the flight time and required propellant by using an advanced propulsion system. The optimal thrust-vector history and propellant mass to use are found in order to transfer a spacecraft from the Earth to a targeted celestial object. One goal of this analysis is to formulate an optimization problem for intercept/rendezvous spacecraft trajectories. One approach to alter the trajectory of the object in a highly controlled manner is to use pulsed laser ablative propulsion. A sufficiently intense laser pulse ablates the surface of a near-Earth object (NEO) by causing plasma blowoff. The momentum change from a single laser pulse is very small. However, the cumulative effect is very effective because the laser can interact with the object over long periods of time. The laser ablation technique can overcome the mass penalties associated with other nondisruptive approaches because no propellant is required to generate the DELTA V (the material of the celestial object is the propellant source). Additionally, laser ablation is effective against a wide range of surface materials and does not require any landing or physical attachment to the object. For diverting distant asteroids and comets, the power and optical requirements of a laser ablation system on or near the Earth may be too extreme to contemplate in the next few decades. A hybrid solution would be for a spacecraft to carry a laser as a payload to a particular celestial body. The spacecraft would require an advanced propulsion system capable of rapid rendezvous with the object and an extremely powerful electrical generator, which is likely needed for the propulsion system as well. The spacecraft would station-keep with the object at a small standoff distance while the laser ablation is performed.

A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

DOE PAGES

Molzahn, Daniel K.; Dorfler, Florian K.; Sandberg, Henrik; ...

2017-07-25

Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. Here, this paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.

A Survey of Distributed Optimization and Control Algorithms for Electric Power Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Molzahn, Daniel K.; Dorfler, Florian K.; Sandberg, Henrik

Historically, centrally computed algorithms have been the primary means of power system optimization and control. With increasing penetrations of distributed energy resources requiring optimization and control of power systems with many controllable devices, distributed algorithms have been the subject of significant research interest. Here, this paper surveys the literature of distributed algorithms with applications to optimization and control of power systems. In particular, this paper reviews distributed algorithms for offline solution of optimal power flow (OPF) problems as well as online algorithms for real-time solution of OPF, optimal frequency control, optimal voltage control, and optimal wide-area control problems.

Automatic control of finite element models for temperature-controlled radiofrequency ablation.

PubMed

Haemmerich, Dieter; Webster, John G

2005-07-14

The finite element method (FEM) has been used to simulate cardiac and hepatic radiofrequency (RF) ablation. The FEM allows modeling of complex geometries that cannot be solved by analytical methods or finite difference models. In both hepatic and cardiac RF ablation a common control mode is temperature-controlled mode. Commercial FEM packages don't support automating temperature control. Most researchers manually control the applied power by trial and error to keep the tip temperature of the electrodes constant. We implemented a PI controller in a control program written in C++. The program checks the tip temperature after each step and controls the applied voltage to keep temperature constant. We created a closed loop system consisting of a FEM model and the software controlling the applied voltage. The control parameters for the controller were optimized using a closed loop system simulation. We present results of a temperature controlled 3-D FEM model of a RITA model 30 electrode. The control software effectively controlled applied voltage in the FEM model to obtain, and keep electrodes at target temperature of 100 degrees C. The closed loop system simulation output closely correlated with the FEM model, and allowed us to optimize control parameters. The closed loop control of the FEM model allowed us to implement temperature controlled RF ablation with minimal user input.

Optimization of a novel Tm fiber laser lithotripter in terms of stone ablation efficiency and retropulsion reduction

NASA Astrophysics Data System (ADS)

Yaroslavsky, Ilya; Vinnichenko, Victoria; McNeill, Tyler; Novoseltseva, Anna; Perchuk, Igor; Vybornov, Alexander; Altshuler, Gregory; Gapontsev, Valentin

2018-02-01

Recently, a Thulium (Tm) fiber laser operating at a wavelength of 1940 nm and peak power up to 500 W has been introduced as a promising energy source for laser lithotripsy. Direct comparative studies have demonstrated considerable advantages of Tm fiber laser over the current industry-standard 2100 nm Holmium:YAG (Ho:YAG) device in terms of ablation rate and retropulsion effects. In this work, we investigated avenues of further improving stone ablation efficiency and reducing retropulsion. Specifically, the roles of temporal pulse structure and fiber tip preparation were studied in detail. Experiments were conducted on Bego stone phantoms in an aqueous environment using a computerized 2D stage for controlled scanning of the fiber over the stone surface. High-resolution 3D-enabled optical microscopy was employed to assess both fiber tip damage and stone ablation rate. Retropulsion effects were quantified using a high-speed video camera. Fiber burn back was evaluated as well. Fiber performance could be preserved during prolonged (up to 15 min) procedures when the fiber tip was adequately prepared. Furthermore, the results were compared with available literature for similar experiments performed with the Ho:YAG laser. The data obtained provide an important foundation for optimizing clinical performance of Tm fiber systems for lithotripsy.

Warehouse stocking optimization based on dynamic ant colony genetic algorithm

NASA Astrophysics Data System (ADS)

Xiao, Xiaoxu

2018-04-01

In view of the various orders of FAW (First Automotive Works) International Logistics Co., Ltd., the SLP method is used to optimize the layout of the warehousing units in the enterprise, thus the warehouse logistics is optimized and the external processing speed of the order is improved. In addition, the relevant intelligent algorithms for optimizing the stocking route problem are analyzed. The ant colony algorithm and genetic algorithm which have good applicability are emphatically studied. The parameters of ant colony algorithm are optimized by genetic algorithm, which improves the performance of ant colony algorithm. A typical path optimization problem model is taken as an example to prove the effectiveness of parameter optimization.

An improved marriage in honey bees optimization algorithm for single objective unconstrained optimization.

PubMed

Celik, Yuksel; Ulker, Erkan

2013-01-01

Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms.

Role of Rotors in the Ablative Therapy of Persistent Atrial Fibrillation

PubMed Central

Schricker, Amir A; Zaman, Junaid; Narayan, Sanjiv M

2015-01-01

Atrial fibrillation (AF) ablation is increasingly used to maintain sinus rhythm yet its results are sub-optimal, especially in patients with persistent AF or prior unsuccessful procedures. Attempts at improvement have often targeted substrates that sustain AF after it is triggered, yet those mechanisms are debated. Many studies now challenge the concept that AF is driven by self-sustaining disordered wavelets, showing instead that localised drivers (rotors) may drive disorder via a process known as fibrillatory conduction. Novel mapping using wide-area recordings, physiological filtering and phase analysis demonstrates rotors in human AF. Contact mapping with focal impulse and rotor modulation (FIRM) shows that localised ablation at sources can improve procedural success in many populations on long-term follow up and some newer approaches to rotor mapping are qualitatively similar. This review critically evaluates the data on rotor mapping and ablation, which advances our conceptual understanding of AF and holds the promise of substantially improving ablative outcomes in patients with persistent AF. PMID:26835100

An ex-vivo experimental study on optimization of bipolar radiofrequency liver ablation using perfusion-cooled electrodes.

PubMed

Lee, J M; Han, J K; Kim, S H; Lee, J Y; Shin, K S; Choi, B I

2005-08-01

To determine optimal parameters for bipolar radiofrequency ablation (RFA) using perfusion-cooled electrodes to create a large ablation volume in ex vivo bovine liver. Three sets of RF experiments were performed using a 200-Watt generator and two 15-gauge perfusion-cooled or internally cooled electrodes in ex vivo bovine livers. In the first set of experiments, to find the ideal inter-electrode distance for creating large coagulation necrosis, 30 ablation lesions were created by bipolar RFAs at inter-electrode spacings of 3 cm, 4 cm, and 5 cm. In the second set of experiments, to explore the ideal duration of RF application, bipolar RFAs were performed for 10 min and 20 min. In the first and second experiments, 10 lesions were made for each condition with infusion of 6% hypertonic saline (HS) at 2 ml/min. In the third set of experiments, 10 ablation lesions were created by bipolar RFAs using internally cooled electrodes without HS infusion. The mean volume of those ablation lesions was then compared to that of the lesions created by bipolar RFA using perfusion-cooled electrodes in the second experiments. Tissue impedance, dimension, and shape of the ablated areas were compared in each condition. In the first set of experiments, bipolar RFA created a homogeneous oval or spherical-shaped ablation area between the electrodes at 3-5 cm spacing, but showed a more spherical-shaped lesion at 3 cm inter-electrode spacing than at 4 cm and 5 cm spacing. In the second set of experiments, RF energy delivered for 20 min created a larger dimension of coagulation necrosis than energy delivered for 10 min: 107.6 +/- 34 cm3 versus 59.5 +/- 27 cm3 (P<0.05). In addition, the mean volume of ablation regions obtained with bipolar RFA using the internally cooled electrode was 47.5+/- 17 cm3, which was significantly less than that with bipolar RFA using perfusion-cooled electrodes (P <0.05). Bipolar RFA using perfusion-cooled electrodes achieves homogeneous areas of coagulation necrosis between two electrodes, preferably at 3 or 4 cm inter-electrode distance for 20 min, and is better in creating large coagulation necrosis than bipolar RFA using internally cooled electrodes.

Synchronization of skin ablation and microjet injection for an effective transdermal drug delivery

NASA Astrophysics Data System (ADS)

Jang, Hun-jae; Yeo, Seonggu; Yoh, Jack J.

2016-04-01

An Er:YAG laser with 2940-nm wavelength and 150-µs pulse duration was built for the purpose of combined ablation and microjet injection. A shorter pulse duration compared to common erbium lasers in dentistry is desirable for a synchronization of skin ablation and subsequent microjet injection into target skin for transdermal injection of liquid dose. A single laser beam is split into two for an optimal energy of pre-ablation of skin and the residual energy allocated to a microjet ejection. A newly designed injector consists of an L-shaped chamber and a parabolic mirror in a single unit, and the handheld laser is a part of an integrated system requiring no optical fiber. Through various injection tests using the porcine skin, the effectiveness of the new delivery system is herein evaluated.

Data Fitting to Study Ablated Hard Dental Tissues by Nanosecond Laser Irradiation.

PubMed

Al-Hadeethi, Y; Al-Jedani, S; Razvi, M A N; Saeed, A; Abdel-Daiem, A M; Ansari, M Shahnawaze; Babkair, Saeed S; Salah, Numan A; Al-Mujtaba, A

2016-01-01

Laser ablation of dental hard tissues is one of the most important laser applications in dentistry. Many works have reported the interaction of laser radiations with tooth material to optimize laser parameters such as wavelength, energy density, etc. This work has focused on determining the relationship between energy density and ablation thresholds using pulsed, 5 nanosecond, neodymium-doped yttrium aluminum garnet; Nd:Y3Al5O12 (Nd:YAG) laser at 1064 nanometer. For enamel and dentin tissues, the ablations have been performed using laser-induced breakdown spectroscopy (LIBS) technique. The ablation thresholds and relationship between energy densities and peak areas of calcium lines, which appeared in LIBS, were determined using data fitting. Furthermore, the morphological changes were studied using Scanning Electron Microscope (SEM). Moreover, the chemical stability of the tooth material after ablation has been studied using Energy-Dispersive X-Ray Spectroscopy (EDX). The differences between carbon atomic % of non-irradiated and irradiated samples were tested using statistical t-test. Results revealed that the best fitting between energy densities and peak areas of calcium lines were exponential and linear for enamel and dentin, respectively. In addition, the ablation threshold of Nd:YAG lasers in enamel was higher than that of dentin. The morphology of the surrounded ablated region of enamel showed thermal damages. For enamel, the EDX quantitative analysis showed that the atomic % of carbon increased significantly when laser energy density increased.

Multimodal optimization by using hybrid of artificial bee colony algorithm and BFGS algorithm

NASA Astrophysics Data System (ADS)

Anam, S.

2017-10-01

Optimization has become one of the important fields in Mathematics. Many problems in engineering and science can be formulated into optimization problems. They maybe have many local optima. The optimization problem with many local optima, known as multimodal optimization problem, is how to find the global solution. Several metaheuristic methods have been proposed to solve multimodal optimization problems such as Particle Swarm Optimization (PSO), Genetics Algorithm (GA), Artificial Bee Colony (ABC) algorithm, etc. The performance of the ABC algorithm is better than or similar to those of other population-based algorithms with the advantage of employing a fewer control parameters. The ABC algorithm also has the advantages of strong robustness, fast convergence and high flexibility. However, it has the disadvantages premature convergence in the later search period. The accuracy of the optimal value cannot meet the requirements sometimes. Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is a good iterative method for finding a local optimum. Compared with other local optimization methods, the BFGS algorithm is better. Based on the advantages of the ABC algorithm and the BFGS algorithm, this paper proposes a hybrid of the artificial bee colony algorithm and the BFGS algorithm to solve the multimodal optimization problem. The first step is that the ABC algorithm is run to find a point. In the second step is that the point obtained by the first step is used as an initial point of BFGS algorithm. The results show that the hybrid method can overcome from the basic ABC algorithm problems for almost all test function. However, if the shape of function is flat, the proposed method cannot work well.

Laser effects based optimal laser parameter identifications for paint removal from metal substrate at 1064 nm: a multi-pulse model

NASA Astrophysics Data System (ADS)

Han, Jinghua; Cui, Xudong; Wang, Sha; Feng, Guoying; Deng, Guoliang; Hu, Ruifeng

2017-10-01

Paint removal by laser ablation is favoured among cleaning techniques due to its high efficiency. How to predict the optimal laser parameters without producing damage to substrate still remains challenging for accurate paint stripping. On the basis of ablation morphologies and combining experiments with numerical modelling, the underlying mechanisms and the optimal conditions for paint removal by laser ablation are thoroughly investigated. Our studies suggest that laser paint removal is dominated by the laser vaporization effect, thermal stress effect and laser plasma effect, in which thermal stress effect is the most favoured while laser plasma effect should be avoided during removal operations. Based on the thermodynamic equations, we numerically evaluated the spatial distribution of the temperature as well as thermal stress in the paint and substrate under the irradiation of laser pulse at 1064 nm. The obtained curves of the paint thickness vs. threshold fluences can provide the reference standard of laser parameter selection in view of the paint layer with different thickness. A multi-pulse model is proposed and validated under a constant laser fluence to perfectly remove a thicker paint layer. The investigations and the methods proposed here might give hints to the efficient operations on the paint removal and lowering the risk of substrate damages.

Interior search algorithm (ISA): a novel approach for global optimization.

PubMed

Gandomi, Amir H

2014-07-01

This paper presents the interior search algorithm (ISA) as a novel method for solving optimization tasks. The proposed ISA is inspired by interior design and decoration. The algorithm is different from other metaheuristic algorithms and provides new insight for global optimization. The proposed method is verified using some benchmark mathematical and engineering problems commonly used in the area of optimization. ISA results are further compared with well-known optimization algorithms. The results show that the ISA is efficiently capable of solving optimization problems. The proposed algorithm can outperform the other well-known algorithms. Further, the proposed algorithm is very simple and it only has one parameter to tune. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

An Improved Marriage in Honey Bees Optimization Algorithm for Single Objective Unconstrained Optimization

PubMed Central

Celik, Yuksel; Ulker, Erkan

2013-01-01

Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms. PMID:23935416

Laser-drilled micro-hole arrays on polyurethane synthetic leather for improvement of water vapor permeability

NASA Astrophysics Data System (ADS)

Wu, Y.; Wang, A. H.; Zheng, R. R.; Tang, H. Q.; Qi, X. Y.; Ye, B.

2014-06-01

Three kinds of lasers at 1064, 532 and 355 nm wavelengths respectively were adopted to construct micro-hole arrays on polyurethane (PU) synthetic leather with an aim to improve water vapor permeability (WVP) of PU synthetic leather. The morphology of the laser-drilled micro-holes was observed to optimize laser parameters. The WVP and slit tear resistance of the laser-drilled leather were measured. Results show that the optimized pulse energy for the 1064, 532 and 355 nm lasers are 0.8, 1.1 and 0.26 mJ, respectively. The diameters of the micro-holes drilled with the optimized laser pulse energy were about 20, 15 and 10 μm, respectively. The depths of the micro-holes drilled with the optimized pulse energy were about 21, 60 and 69 μm, respectively. Compared with the untreated samples, the highest WVP growth ratio was 38.4%, 46.8% and 53.5% achieved by the 1064, 532 and 355 nm lasers, respectively. And the highest decreasing ratio of slit tear resistance was 11.1%, 14.8%, and 22.5% treated by the 1064, 532 and 355 nm lasers, respectively. Analysis of the interaction mechanism between laser beams at three kinds of laser wavelengths and the PU synthetic leather revealed that laser micro-drilling at 355 nm wavelength displayed both photochemical ablation and photothermal ablation, while laser micro-drilling at 1064 and 532 nm wavelengths leaded to photothermal ablation only.

Performance comparison of genetic algorithms and particle swarm optimization for model integer programming bus timetabling problem

NASA Astrophysics Data System (ADS)

Wihartiko, F. D.; Wijayanti, H.; Virgantari, F.

2018-03-01

Genetic Algorithm (GA) is a common algorithm used to solve optimization problems with artificial intelligence approach. Similarly, the Particle Swarm Optimization (PSO) algorithm. Both algorithms have different advantages and disadvantages when applied to the case of optimization of the Model Integer Programming for Bus Timetabling Problem (MIPBTP), where in the case of MIPBTP will be found the optimal number of trips confronted with various constraints. The comparison results show that the PSO algorithm is superior in terms of complexity, accuracy, iteration and program simplicity in finding the optimal solution.

Evaluation of focused ultrasound algorithms: Issues for reducing pre-focal heating and treatment time.

PubMed

Yiannakou, Marinos; Trimikliniotis, Michael; Yiallouras, Christos; Damianou, Christakis

2016-02-01

Due to the heating in the pre-focal field the delay between successive movements in high intensity focused ultrasound (HIFU) are sometimes as long as 60s, resulting to treatment time in the order of 2-3h. Because there is generally a requirement to reduce treatment time, we were motivated to explore alternative transducer motion algorithms in order to reduce pre-focal heating and treatment time. A 1 MHz single element transducer with 4 cm diameter and 10 cm focal length was used. A simulation model was developed that estimates the temperature, thermal dose and lesion development in the pre-focal field. The simulated temperature history that was combined with the motion algorithms produced thermal maps in the pre-focal region. Polyacrylimde gel phantom was used to evaluate the induced pre-focal heating for each motion algorithm used, and also was used to assess the accuracy of the simulation model. Three out of the six algorithms having successive steps close to each other, exhibited severe heating in the pre-focal field. Minimal heating was produced with the algorithms having successive steps apart from each other (square, square spiral and random). The last three algorithms were improved further (with small cost in time), thus eliminating completely the pre-focal heating and reducing substantially the treatment time as compared to traditional algorithms. Out of the six algorithms, 3 were successful in eliminating the pre-focal heating completely. Because these 3 algorithms required no delay between successive movements (except in the last part of the motion), the treatment time was reduced by 93%. Therefore, it will be possible in the future, to achieve treatment time of focused ultrasound therapies shorter than 30 min. The rate of ablated volume achieved with one of the proposed algorithms was 71 cm(3)/h. The intention of this pilot study was to demonstrate that the navigation algorithms play the most important role in reducing pre-focal heating. By evaluating in the future, all commercially available geometries, it will be possible to reduce the treatment time, for thermal ablation protocols intended for oncological targets. Copyright © 2015 Elsevier B.V. All rights reserved.

Efficient bone cutting with the novel diode pumped Er:YAG laser system: in vitro investigation and optimization of the treatment parameters

NASA Astrophysics Data System (ADS)

Stock, Karl; Diebolder, Rolf; Hausladen, Florian; Hibst, Raimund

2014-03-01

It is well known that flashlamp pumped Er:YAG lasers allow efficient bone ablation due to strong absorption at 3μm by water. Preliminary experiments revealed also a newly developed diode pumped Er:YAG laser system (Pantec Engineering AG) to be an efficient tool for use for bone surgery. The aim of the present in vitro study is the investigation of a new power increased version of the laser system with higher pulse energy and optimization of the treatment set-up to get high cutting quality, efficiency, and ablation depth. Optical simulations were performed to achieve various focus diameters and homogeneous beam profile. An appropriate experimental set-up with two different focusing units, a computer controlled linear stage with sample holder, and a shutter unit was realized. By this we are able to move the sample (slices of pig bone) with a defined velocity during the irradiation. Cutting was performed under appropriate water spray by moving the sample back and forth. After each path the ablation depth was measured and the focal plane was tracked to the actual bottom of the groove. Finally, the cuts were analyzed by light microcopy regarding the ablation quality and geometry, and thermal effects. In summary, the results show that with carefully adapted irradiation parameters narrow and deep cuts (ablation depth > 6mm, aspect ratio approx. 20) are possible without carbonization. In conclusion, these in vitro investigations demonstrate that high efficient bone cutting is possible with the diode pumped Er:YAG laser system using appropriate treatment set-up and parameters.

Optimization Of Feature Weight TheVoting Feature Intervals 5 Algorithm Using Partical Swarm Optimization Algorithm

NASA Astrophysics Data System (ADS)

Hayana Hasibuan, Eka; Mawengkang, Herman; Efendi, Syahril

2017-12-01

The use of Partical Swarm Optimization Algorithm in this research is to optimize the feature weights on the Voting Feature Interval 5 algorithm so that we can find the model of using PSO algorithm with VFI 5. Optimization of feature weight on Diabetes or Dyspesia data is considered important because it is very closely related to the livelihood of many people, so if there is any inaccuracy in determining the most dominant feature weight in the data will cause death. Increased accuracy by using PSO Algorithm ie fold 1 from 92.31% to 96.15% increase accuracy of 3.8%, accuracy of fold 2 on Algorithm VFI5 of 92.52% as well as generated on PSO Algorithm means accuracy fixed, then in fold 3 increase accuracy of 85.19% Increased to 96.29% Accuracy increased by 11%. The total accuracy of all three trials increased by 14%. In general the Partical Swarm Optimization algorithm has succeeded in increasing the accuracy to several fold, therefore it can be concluded the PSO algorithm is well used in optimizing the VFI5 Classification Algorithm.

Changes in optical properties during heating of ex vivo liver tissues

NASA Astrophysics Data System (ADS)

Nagarajan, Vivek Krishna; Gogineni, Venkateshwara R.; White, Sarah B.; Yu, Bing

2017-02-01

Thermal ablation is the use of heat to induce cell death through coagulative necrosis. Ideally, complete ablation of tumor cells with no damage to surrounding critical structures such as blood vessels, nerves or even organs is desired. Ablation monitoring techniques are often employed to ensure optimal tumor ablation. In thermal tissue ablation, tissue damage is known to be dependent on the temperature and time of exposure. Aptly, current methods for monitoring ablation rely profoundly on local tissue temperature and duration of heating to predict the degree of tissue damage. However, such methods do not take into account the microstructural and physiological changes in tissues as a result of thermocoagulation. Light propagation within biological tissues is known to be dependent on the tissue microstructure and physiology. During tissue denaturation, changes in tissue structure alter light propagations in tissue which could be used to directly assess the extent of thermal tissue damage. We report the use of a spectroscopic system for monitoring the tissue optical properties during heating of ex vivo liver tissues. We observed that during tissue denaturation, continuous changes in wavelength-averaged μa(λ) and μ's(λ) followed a sigmoidal trend and are correlated with damage predicted by Arrhenius model.

Investigations of morphological features of picosecond dual-wavelength laser ablation of stainless steel

NASA Astrophysics Data System (ADS)

Zhao, Wanqin; Wang, Wenjun; Mei, Xuesong; Jiang, Gedong; Liu, Bin

2014-06-01

Investigations on the morphological features of holes and grooves ablated on the surface of stainless steel using the picosecond dual-wavelength laser system with different powers combinations are presented based on the scarce researches on morphology of dual-wavelength laser ablation. The experimental results show the profiles of holes ablated by the visible beam appear V-shaped while those for the near-infrared have large openings and display U-shaped, which are independent of the ablation mechanism of ultrafast laser. For the dual-wavelength beam (a combination of visible beam and near-infrared), the holes resemble sunflower-like structures and have smoother ring patterns on the bottom. In general, the holes ablated by the dual-wavelength beam appear to have much flatter bottoms, linearly sloped side-walls and spinodal structures between the bottoms of the holes and the side-walls. Furthermore, through judiciously combining the powers of the dual-wavelength beam, high-quality grooves could be obtained with a flat worm-like structure at the bottom surface and less resolidified melt ejection edges. This study provides insight into optimizing ultrafast laser micromachining in order to obtain desired morphology.

Planarization of Isolated Defects on ICF Target Capsule Surfaces by Pulsed Laser Ablation

DOE PAGES

Alfonso, Noel; Carlson, Lane C.; Bunn, Thomas L.

2016-08-09

Demanding surface quality requirements for inertial confinement fusion (ICF) capsules motivated the development of a pulsed laser ablation method to reduce or eliminate undesirable surface defects. The pulsed laser ablation technique takes advantage of a full surface (4π) capsule manipulation system working in combination with an optical profiling (confocal) microscope. Based on the defect topography, the material removal rate, the laser pulse energy and its beam profile, a customized laser raster pattern is derived to remove the defect. The pattern is a table of coordinates and number of pulses that dictate how the defect will be vaporized until its heightmore » is level with the capsule surface. This paper explains how the raster patterns are optimized to minimize surface roughness and how surface roughness after laser ablation is simulated. The simulated surfaces are compared with actual ablated surfaces. Large defects are reduced to a size regime where a tumble finishing process produces very high quality surfaces devoid of high mode defects. The combined polishing processes of laser ablation and tumble finishing have become routine fabrication steps for National Ignition Facility capsule production.« less

Long-wave plasma radiofrequency ablation for treatment of xanthelasma palpebrarum.

PubMed

Baroni, Adone

2018-03-01

Xanthelasma palpebrarum is the most common type of xanthoma affecting the eyelids. It is characterized by asymptomatic soft yellowish macules, papules, or plaques over the upper and lower eyelids. Many treatments are available for management of xanthelasma palpebrarum, the most commonly used include surgical excision, ablative CO 2 or erbium lasers, nonablative Q-switched Nd:YAG laser, trichloroacetic acid peeling, and radiofrequency ablation. This study aims to evaluate the effectiveness of RF ablation in the treatment of xanthelasma palpebrarum, with D.A.S. Medical portable device (Technolux, Italia), a radiofrequency tool working with long-wave plasma energy and without anesthesia. Twenty patients, 15 female and 5 male, affected by xanthelasma palpebrarum, were enrolled for long-wave plasma radiofrequency ablation treatment. The treatment consisted of 3/4 sessions that were carried out at intervals of 30 days. Treatments were well tolerated by all patients with no adverse effects and optimal aesthetic results. The procedure is very fast and can be performed without anesthesia because of the low and tolerable pain stimulation. Long-wave plasma radiofrequency ablation is an effective option for treatment of xanthelasma palpebrarum and adds an additional tool to the increasing list of medical devices for aesthetic treatments. © 2018 Wiley Periodicals, Inc.

Adaptive cockroach swarm algorithm

NASA Astrophysics Data System (ADS)

Obagbuwa, Ibidun C.; Abidoye, Ademola P.

2017-07-01

An adaptive cockroach swarm optimization (ACSO) algorithm is proposed in this paper to strengthen the existing cockroach swarm optimization (CSO) algorithm. The ruthless component of CSO algorithm is modified by the employment of blend crossover predator-prey evolution method which helps algorithm prevent any possible population collapse, maintain population diversity and create adaptive search in each iteration. The performance of the proposed algorithm on 16 global optimization benchmark function problems was evaluated and compared with the existing CSO, cuckoo search, differential evolution, particle swarm optimization and artificial bee colony algorithms.

A chaos wolf optimization algorithm with self-adaptive variable step-size

NASA Astrophysics Data System (ADS)

Zhu, Yong; Jiang, Wanlu; Kong, Xiangdong; Quan, Lingxiao; Zhang, Yongshun

2017-10-01

To explore the problem of parameter optimization for complex nonlinear function, a chaos wolf optimization algorithm (CWOA) with self-adaptive variable step-size was proposed. The algorithm was based on the swarm intelligence of wolf pack, which fully simulated the predation behavior and prey distribution way of wolves. It possessed three intelligent behaviors such as migration, summons and siege. And the competition rule as "winner-take-all" and the update mechanism as "survival of the fittest" were also the characteristics of the algorithm. Moreover, it combined the strategies of self-adaptive variable step-size search and chaos optimization. The CWOA was utilized in parameter optimization of twelve typical and complex nonlinear functions. And the obtained results were compared with many existing algorithms, including the classical genetic algorithm, the particle swarm optimization algorithm and the leader wolf pack search algorithm. The investigation results indicate that CWOA possess preferable optimization ability. There are advantages in optimization accuracy and convergence rate. Furthermore, it demonstrates high robustness and global searching ability.

Towards multispectral endoscopic imaging of cardiac lesion assessment and classification for cardiac ablation therapy

NASA Astrophysics Data System (ADS)

Park, Soo Young; Singh-Moon, Rajinder P.; Hendon, Christine P.

2018-02-01

Pulmonary vein (PV) isolation is a critical procedure for the treatment and termination of atrial fibrillation (AF). The success of such treatment depends on the extent of tissue damage, where partial lesions can allow abnormal electrical conduction and risk relapse of AF. Proper evaluation of lesion delivery and ablation line continuity remains challenging with current techniques and in part limit procedural efficacy. A tool for direct visualization of endo-myocardial lesions in vivo could potentially reduce ambiguity in treatment location and extent and improve the overall fidelity of lesion sets. In this work, we introduce a method for wide-field visualization of myocardial tissue including the discernment of ablated and non-ablated regions using an endoscopic multispectral imaging system (EMIS). The system was designed to fit the working channel of most commercial sheathes (<4 Fr) and supported quadruple-wavelength reflectance imaging through a flexible fiber-bundle. A total of 50 endocardial lesions were created and imaged on nine swine hearts, ex vivo in addition to 15 lesions on human LA samples near PV regions. A pixel-wise linear discriminant analysis algorithm was developed to classify regions of ablation treatment based on calibrated EMI maps. Results show good agreement of treatment severity and spatial extent compared to post-hoc tissue vital staining.

New knowledge-based genetic algorithm for excavator boom structural optimization

NASA Astrophysics Data System (ADS)

Hua, Haiyan; Lin, Shuwen

2014-03-01

Due to the insufficiency of utilizing knowledge to guide the complex optimal searching, existing genetic algorithms fail to effectively solve excavator boom structural optimization problem. To improve the optimization efficiency and quality, a new knowledge-based real-coded genetic algorithm is proposed. A dual evolution mechanism combining knowledge evolution with genetic algorithm is established to extract, handle and utilize the shallow and deep implicit constraint knowledge to guide the optimal searching of genetic algorithm circularly. Based on this dual evolution mechanism, knowledge evolution and population evolution can be connected by knowledge influence operators to improve the configurability of knowledge and genetic operators. Then, the new knowledge-based selection operator, crossover operator and mutation operator are proposed to integrate the optimal process knowledge and domain culture to guide the excavator boom structural optimization. Eight kinds of testing algorithms, which include different genetic operators, are taken as examples to solve the structural optimization of a medium-sized excavator boom. By comparing the results of optimization, it is shown that the algorithm including all the new knowledge-based genetic operators can more remarkably improve the evolutionary rate and searching ability than other testing algorithms, which demonstrates the effectiveness of knowledge for guiding optimal searching. The proposed knowledge-based genetic algorithm by combining multi-level knowledge evolution with numerical optimization provides a new effective method for solving the complex engineering optimization problem.

Fireworks algorithm for mean-VaR/CVaR models

NASA Astrophysics Data System (ADS)

Zhang, Tingting; Liu, Zhifeng

2017-10-01

Intelligent algorithms have been widely applied to portfolio optimization problems. In this paper, we introduce a novel intelligent algorithm, named fireworks algorithm, to solve the mean-VaR/CVaR model for the first time. The results show that, compared with the classical genetic algorithm, fireworks algorithm not only improves the optimization accuracy and the optimization speed, but also makes the optimal solution more stable. We repeat our experiments at different confidence levels and different degrees of risk aversion, and the results are robust. It suggests that fireworks algorithm has more advantages than genetic algorithm in solving the portfolio optimization problem, and it is feasible and promising to apply it into this field.

Using FT-IR Spectroscopy to Elucidate the Structures of Ablative Polymers

NASA Technical Reports Server (NTRS)

Fan, Wendy

2011-01-01

The composition and structure of an ablative polymer has a multifaceted influence on its thermal, mechanical and ablative properties. Understanding the molecular level information is critical to the optimization of material performance because it helps to establish correlations with the macroscopic properties of the material, the so-called structure-property relationship. Moreover, accurate information of molecular structures is also essential to predict the thermal decomposition pathways as well as to identify decomposition species that are fundamentally important to modeling work. In this presentation, I will describe the use of infrared transmission spectroscopy (FT-IR) as a convenient tool to aid the discovery and development of thermal protection system materials.

Optimized LWIR enhancement of nanosecond and femtosecond LIBS uranium emission

NASA Astrophysics Data System (ADS)

Akpovo, Codjo A.; Ford, Alan; Johnson, Lewis

2016-05-01

A carbon dioxide (CO2) transverse electrical breakdown in atmosphere (TEA), pulsed laser was used to enhance the laser-induced breakdown spectroscopy (LIBS) spectral signatures of uranium under nanosecond (ns) and femtosecond (fs) ablation. The peak areas of both ionic and neutral species increased by one order of magnitude for ns-ablation and two orders of magnitude for fs-ablation over LIBS when the CO2 TEA laser was used with samples of dried solutions of uranyl nitrate hexahydrate (UO2(NO3)2·6H2O) on silicon wafers. Electron temperature and density measurements show that the spectral emission improvement from using the TEA laser comes from plasma reheating.

3D ultrasound image guidance system used in RF uterine adenoma and uterine bleeding ablation system

NASA Astrophysics Data System (ADS)

Ding, Mingyue; Luo, Xiaoan; Cai, Chao; Zhou, Chengping; Fenster, Aaron

2006-03-01

Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese women. Many women lose their fertility from these diseases. Currently, a minimally invasive ablation system using an RF button electrode is being used in Chinese hospitals to destroy tumor cells or stop bleeding. In this paper, we report on a 3D US guidance system developed to avoid accidents or death of the patient by inaccurate localization of the tumor position during treatment. A 3D US imaging system using a rotational scanning approach of an abdominal probe was built. In order to reduce the distortion produced when the rotational axis is not collinear with the central beam of the probe, a new 3D reconstruction algorithm is used. Then, a fast 3D needle segmentation algorithm is used to find the electrode. Finally, the tip of electrode is determined along the segmented 3D needle and the whole electrode is displayed. Experiments with a water phantom demonstrated the feasibility of our approach.

Serial removal of caries lesions from tooth occlusal surfaces using near-IR image-guided IR laser ablation

NASA Astrophysics Data System (ADS)

Chan, Kenneth H.; Tom, Henry; Darling, Cynthia L.; Fried, Daniel

2015-02-01

Previous studies have established that caries lesions can be imaged with high contrast without the interference of stains at near-IR wavelengths greater than 1300-nm. It has been demonstrated that computer controlled laser scanning systems utilizing IR lasers operating at high pulse repetition rates can be used for serial imaging and selective removal of caries lesions. In this study, we report our progress towards the development of algorithms for generating rasterized ablation maps from near-IR reflectance images for the removal of natural lesions from tooth occlusal surfaces. An InGaAs camera and a filtered tungsten-halogen lamp producing near-IR light in the range of 1500-1700-nm were used to collect crosspolarization reflectance images of tooth occlusal surfaces. A CO2 laser operating at a wavelength of 9.3- μm with a pulse duration of 10-15-μs was used for image-guided ablation.

Excimer laser decontamination

NASA Astrophysics Data System (ADS)

Sentis, Marc L.; Delaporte, Philippe C.; Marine, Wladimir; Uteza, Olivier P.

2000-04-01

The application of excimer laser ablation process to the decontamination of radioactive surfaces is discussed. This technology is very attractive because it allows to efficiently remove the contaminated particles without secondary waste production. To demonstrate the capability of such technology to efficiently decontaminate large area, we studied and developed a prototype which include a XeCl laser, an optical fiber delivery system and an ablated particles collection cell. The main physical processes taking place during UV laser ablation will be explained. The influence of laser wavelength, pulse duration and absorption coefficient of material will be discussed. Special studies have been performed to understand the processes which limit the transmission of high average power excimer laser through optical fiber, and to determine the laser conditions to optimize the value of this transmission. An in-situ spectroscopic analysis of laser ablation plasma allows the real time control of the decontamination. The results obtained for painting or metallic oxides removal from stainless steel surfaces will be presented.

Nanoparticle mediated ablation of breast cancer cells using a nanosecond pulsed electric field

NASA Astrophysics Data System (ADS)

Burford, Christopher

In the past, both nanomaterials and various heating modalities have been researched as means for treating cancers. However, many of the current methodologies have the flaws of inconsistent tumor ablation and significant destruction of healthy cells. Based on research performed using constant radiofrequency electric fields and metallic nanoparticles (where cell necrosis is induced by the heating of these nanoparticles) we have developed a modality that simlarly uses functionalized metallic nanoparticles, specific for the T47D breast cancer cell line, and nanosecond pulsed electric fields as the hyperthermic inducer. Using both iron oxide and gold nanoparticles the results of our pilot studies indicated that up to 90% of the cancer cells were ablated given the optimal treatment parameters. These quantities of ablated cells were achieved using a cumulative exposure time 6 orders of magnitude less than most in vitro radiofrequency electric field studies.

Laser ablation of iron-rich black films from exposed granite surfaces

NASA Astrophysics Data System (ADS)

Delgado Rodrigues, J.; Costa, D.; Mascalchi, M.; Osticioli, I.; Siano, S.

2014-10-01

Here, we investigated the potential of laser removal of iron-rich dark films from weathered granite substrates, which represents a very difficult conservation problem because of the polymineralic nature of the stone and of its complex deterioration mechanisms. As often occurs, biotite was the most critical component because of its high optical absorption, low melting temperature, and pronounced cleavage, which required a careful control of the photothermal and photomechanical effects to optimize the selective ablation of the mentioned unwanted dark film. Different pulse durations and wavelengths Nd:YAG lasers were tested and optimal irradiation conditions were determined through thorough analytical characterisations. Besides addressing a specific conservation problem, the present work provides information of general valence in laser uncovering of encrusted granite.

A tabu search evalutionary algorithm for multiobjective optimization: Application to a bi-criterion aircraft structural reliability problem

NASA Astrophysics Data System (ADS)

Long, Kim Chenming

Real-world engineering optimization problems often require the consideration of multiple conflicting and noncommensurate objectives, subject to nonconvex constraint regions in a high-dimensional decision space. Further challenges occur for combinatorial multiobjective problems in which the decision variables are not continuous. Traditional multiobjective optimization methods of operations research, such as weighting and epsilon constraint methods, are ill-suited to solving these complex, multiobjective problems. This has given rise to the application of a wide range of metaheuristic optimization algorithms, such as evolutionary, particle swarm, simulated annealing, and ant colony methods, to multiobjective optimization. Several multiobjective evolutionary algorithms have been developed, including the strength Pareto evolutionary algorithm (SPEA) and the non-dominated sorting genetic algorithm (NSGA), for determining the Pareto-optimal set of non-dominated solutions. Although numerous researchers have developed a wide range of multiobjective optimization algorithms, there is a continuing need to construct computationally efficient algorithms with an improved ability to converge to globally non-dominated solutions along the Pareto-optimal front for complex, large-scale, multiobjective engineering optimization problems. This is particularly important when the multiple objective functions and constraints of the real-world system cannot be expressed in explicit mathematical representations. This research presents a novel metaheuristic evolutionary algorithm for complex multiobjective optimization problems, which combines the metaheuristic tabu search algorithm with the evolutionary algorithm (TSEA), as embodied in genetic algorithms. TSEA is successfully applied to bicriteria (i.e., structural reliability and retrofit cost) optimization of the aircraft tail structure fatigue life, which increases its reliability by prolonging fatigue life. A comparison for this application of the proposed algorithm, TSEA, with several state-of-the-art multiobjective optimization algorithms reveals that TSEA outperforms these algorithms by providing retrofit solutions with greater reliability for the same costs (i.e., closer to the Pareto-optimal front) after the algorithms are executed for the same number of generations. This research also demonstrates that TSEA competes with and, in some situations, outperforms state-of-the-art multiobjective optimization algorithms such as NSGA II and SPEA 2 when applied to classic bicriteria test problems in the technical literature and other complex, sizable real-world applications. The successful implementation of TSEA contributes to the safety of aeronautical structures by providing a systematic way to guide aircraft structural retrofitting efforts, as well as a potentially useful algorithm for a wide range of multiobjective optimization problems in engineering and other fields.

An Orthogonal Evolutionary Algorithm With Learning Automata for Multiobjective Optimization.

PubMed

Dai, Cai; Wang, Yuping; Ye, Miao; Xue, Xingsi; Liu, Hailin

2016-12-01

Research on multiobjective optimization problems becomes one of the hottest topics of intelligent computation. In order to improve the search efficiency of an evolutionary algorithm and maintain the diversity of solutions, in this paper, the learning automata (LA) is first used for quantization orthogonal crossover (QOX), and a new fitness function based on decomposition is proposed to achieve these two purposes. Based on these, an orthogonal evolutionary algorithm with LA for complex multiobjective optimization problems with continuous variables is proposed. The experimental results show that in continuous states, the proposed algorithm is able to achieve accurate Pareto-optimal sets and wide Pareto-optimal fronts efficiently. Moreover, the comparison with the several existing well-known algorithms: nondominated sorting genetic algorithm II, decomposition-based multiobjective evolutionary algorithm, decomposition-based multiobjective evolutionary algorithm with an ensemble of neighborhood sizes, multiobjective optimization by LA, and multiobjective immune algorithm with nondominated neighbor-based selection, on 15 multiobjective benchmark problems, shows that the proposed algorithm is able to find more accurate and evenly distributed Pareto-optimal fronts than the compared ones.

Method for evaluation of predictive models of microwave ablation via post-procedural clinical imaging

NASA Astrophysics Data System (ADS)

Collins, Jarrod A.; Brown, Daniel; Kingham, T. Peter; Jarnagin, William R.; Miga, Michael I.; Clements, Logan W.

2015-03-01

Development of a clinically accurate predictive model of microwave ablation (MWA) procedures would represent a significant advancement and facilitate an implementation of patient-specific treatment planning to achieve optimal probe placement and ablation outcomes. While studies have been performed to evaluate predictive models of MWA, the ability to quantify the performance of predictive models via clinical data has been limited to comparing geometric measurements of the predicted and actual ablation zones. The accuracy of placement, as determined by the degree of spatial overlap between ablation zones, has not been achieved. In order to overcome this limitation, a method of evaluation is proposed where the actual location of the MWA antenna is tracked and recorded during the procedure via a surgical navigation system. Predictive models of the MWA are then computed using the known position of the antenna within the preoperative image space. Two different predictive MWA models were used for the preliminary evaluation of the proposed method: (1) a geometric model based on the labeling associated with the ablation antenna and (2) a 3-D finite element method based computational model of MWA using COMSOL. Given the follow-up tomographic images that are acquired at approximately 30 days after the procedure, a 3-D surface model of the necrotic zone was generated to represent the true ablation zone. A quantification of the overlap between the predicted ablation zones and the true ablation zone was performed after a rigid registration was computed between the pre- and post-procedural tomograms. While both model show significant overlap with the true ablation zone, these preliminary results suggest a slightly higher degree of overlap with the geometric model.

Physical mechanisms of SiN{sub x} layer structuring with ultrafast lasers by direct and confined laser ablation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rapp, S., E-mail: rapp@hm.edu; Erlangen Graduate School in Advanced Optical Technologies; Heinrich, G.

2015-03-14

In the production process of silicon microelectronic devices and high efficiency silicon solar cells, local contact openings in thin dielectric layers are required. Instead of photolithography, these openings can be selectively structured with ultra-short laser pulses by confined laser ablation in a fast and efficient lift off production step. Thereby, the ultrafast laser pulse is transmitted by the dielectric layer and absorbed at the substrate surface leading to a selective layer removal in the nanosecond time domain. Thermal damage in the substrate due to absorption is an unwanted side effect. The aim of this work is to obtain a deepermore » understanding of the physical laser-material interaction with the goal of finding a damage-free ablation mechanism. For this, thin silicon nitride (SiN{sub x}) layers on planar silicon (Si) wafers are processed with infrared fs-laser pulses. Two ablation types can be distinguished: The known confined ablation at fluences below 300 mJ/cm{sup 2} and a combined partial confined and partial direct ablation at higher fluences. The partial direct ablation process is caused by nonlinear absorption in the SiN{sub x} layer in the center of the applied Gaussian shaped laser pulses. Pump-probe investigations of the central area show ultra-fast reflectivity changes typical for direct laser ablation. Transmission electron microscopy results demonstrate that the Si surface under the remaining SiN{sub x} island is not damaged by the laser ablation process. At optimized process parameters, the method of direct laser ablation could be a good candidate for damage-free selective structuring of dielectric layers on absorbing substrates.« less

Honey Bees Inspired Optimization Method: The Bees Algorithm.

PubMed

Yuce, Baris; Packianather, Michael S; Mastrocinque, Ernesto; Pham, Duc Truong; Lambiase, Alfredo

2013-11-06

Optimization algorithms are search methods where the goal is to find an optimal solution to a problem, in order to satisfy one or more objective functions, possibly subject to a set of constraints. Studies of social animals and social insects have resulted in a number of computational models of swarm intelligence. Within these swarms their collective behavior is usually very complex. The collective behavior of a swarm of social organisms emerges from the behaviors of the individuals of that swarm. Researchers have developed computational optimization methods based on biology such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony. The aim of this paper is to describe an optimization algorithm called the Bees Algorithm, inspired from the natural foraging behavior of honey bees, to find the optimal solution. The algorithm performs both an exploitative neighborhood search combined with random explorative search. In this paper, after an explanation of the natural foraging behavior of honey bees, the basic Bees Algorithm and its improved versions are described and are implemented in order to optimize several benchmark functions, and the results are compared with those obtained with different optimization algorithms. The results show that the Bees Algorithm offering some advantage over other optimization methods according to the nature of the problem.

Teaching-learning-based Optimization Algorithm for Parameter Identification in the Design of IIR Filters

NASA Astrophysics Data System (ADS)

Singh, R.; Verma, H. K.

2013-12-01

This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.

Interventional Pain Management for Sacroiliac Tumors in the Oncologic Population: A Case Series and Paradigm Approach.

PubMed

Hutson, Nathan; Hung, Joseph C; Puttanniah, Vinay; Lis, Eric; Laufer, Ilya; Gulati, Amitabh

2017-05-01

Tumors invading the sacrum and/or ilium often represent incurable metastatic disease, and treatment is targeted toward palliation of symptoms and control of pain. As systemic opioid therapy is frequently inadequate and limited by side effects, a variety of interventional techniques are available to better optimize analgesia. Using six patients as a paradigm for interventional approaches to pain relief, we present a therapeutic algorithm for treating sacroiliac tumor-related pain in the oncologic population. We describe the use of ultrasound-guided proximal sacroiliac joint corticosteroid injection, sacroiliac lateral branch radiofrequency ablation, percutaneous sacroplasty, and implantable neuraxial drug delivery devices to treat malignant sacroiliac pain in six patients. Pre- and postprocedure numerical rating scale (NRS) pain scores, duration of pain relief, and postprocedure pain medication requirements were studied for each patient. Each patient had marked improvement in their pain based on an average postprocedure NRS difference of six points. The average duration of pain relief was eight months. In all cases, opioid requirements decreased after the intervention. Depending on tumor location, burden of disease, and patient preference, patients suffering from metastatic disease to the sacrum may find benefit from use of ultrasound-guided proximal sacroiliac joint corticosteroid injection, sacroiliac lateral branch radiofrequency ablation, percutaneous sacroplasty, dorsal column stimulator leads, and/or implantable neuraxial drug delivery devices. We provide a paradigm for treatment in this patient population. © 2016 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Queue and stack sorting algorithm optimization and performance analysis

NASA Astrophysics Data System (ADS)

Qian, Mingzhu; Wang, Xiaobao

2018-04-01

Sorting algorithm is one of the basic operation of a variety of software development, in data structures course specializes in all kinds of sort algorithm. The performance of the sorting algorithm is directly related to the efficiency of the software. A lot of excellent scientific research queue is constantly optimizing algorithm, algorithm efficiency better as far as possible, the author here further research queue combined with stacks of sorting algorithms, the algorithm is mainly used for alternating operation queue and stack storage properties, Thus avoiding the need for a large number of exchange or mobile operations in the traditional sort. Before the existing basis to continue research, improvement and optimization, the focus on the optimization of the time complexity of the proposed optimization and improvement, The experimental results show that the improved effectively, at the same time and the time complexity and space complexity of the algorithm, the stability study corresponding research. The improvement and optimization algorithm, improves the practicability.

Automatic control of finite element models for temperature-controlled radiofrequency ablation

PubMed Central

Haemmerich, Dieter; Webster, John G

2005-01-01

Background The finite element method (FEM) has been used to simulate cardiac and hepatic radiofrequency (RF) ablation. The FEM allows modeling of complex geometries that cannot be solved by analytical methods or finite difference models. In both hepatic and cardiac RF ablation a common control mode is temperature-controlled mode. Commercial FEM packages don't support automating temperature control. Most researchers manually control the applied power by trial and error to keep the tip temperature of the electrodes constant. Methods We implemented a PI controller in a control program written in C++. The program checks the tip temperature after each step and controls the applied voltage to keep temperature constant. We created a closed loop system consisting of a FEM model and the software controlling the applied voltage. The control parameters for the controller were optimized using a closed loop system simulation. Results We present results of a temperature controlled 3-D FEM model of a RITA model 30 electrode. The control software effectively controlled applied voltage in the FEM model to obtain, and keep electrodes at target temperature of 100°C. The closed loop system simulation output closely correlated with the FEM model, and allowed us to optimize control parameters. Discussion The closed loop control of the FEM model allowed us to implement temperature controlled RF ablation with minimal user input. PMID:16018811

Data Fitting to Study Ablated Hard Dental Tissues by Nanosecond Laser Irradiation

PubMed Central

Abdel-Daiem, A. M.; Ansari, M. Shahnawaze; Babkair, Saeed S.; Salah, Numan A.; Al-Mujtaba, A.

2016-01-01

Laser ablation of dental hard tissues is one of the most important laser applications in dentistry. Many works have reported the interaction of laser radiations with tooth material to optimize laser parameters such as wavelength, energy density, etc. This work has focused on determining the relationship between energy density and ablation thresholds using pulsed, 5 nanosecond, neodymium-doped yttrium aluminum garnet; Nd:Y3Al5O12 (Nd:YAG) laser at 1064 nanometer. For enamel and dentin tissues, the ablations have been performed using laser-induced breakdown spectroscopy (LIBS) technique. The ablation thresholds and relationship between energy densities and peak areas of calcium lines, which appeared in LIBS, were determined using data fitting. Furthermore, the morphological changes were studied using Scanning Electron Microscope (SEM). Moreover, the chemical stability of the tooth material after ablation has been studied using Energy-Dispersive X-Ray Spectroscopy (EDX). The differences between carbon atomic % of non-irradiated and irradiated samples were tested using statistical t-test. Results revealed that the best fitting between energy densities and peak areas of calcium lines were exponential and linear for enamel and dentin, respectively. In addition, the ablation threshold of Nd:YAG lasers in enamel was higher than that of dentin. The morphology of the surrounded ablated region of enamel showed thermal damages. For enamel, the EDX quantitative analysis showed that the atomic % of carbon increased significantly when laser energy density increased. PMID:27228169

Dynamic Changes of QRS Morphology of Premature Ventricular Contractions During Ablation in the Right Ventricular Outflow Tract: A Case Report.

PubMed

Yue-Chun, Li; Jia-Feng, Lin; Jia-Xuan, Lin

2015-10-01

Electrocardiographic characteristics can be useful in differentiating between right ventricular outflow tract (RVOT) and aortic sinus cusp (ASC) ventricular arrhythmias. Ventricular arrhythmias originating from ASC, however, show preferential conduction to RVOT that may render the algorithms of electrocardiographic characteristics less reliable. Even though there are few reports describing ventricular arrhythmias with ASC origins and endocardial breakout sites of RVOT, progressive dynamic changes in QRS morphology of the ventricular arrhythmias during ablation obtained were rare.This case report describes a patient with symptomatic premature ventricular contractions of left ASC origin presenting an electrocardiogram (ECG) characteristic of right ventricular outflow tract before ablation. Pacing at right ventricular outflow tract reproduced an excellent pace map. When radiofrequency catheter ablation was applied to the right ventricular outflow tract, the QRS morphology of premature ventricular contractions progressively changed from ECG characteristics of right ventricular outflow tract origin to ECG characteristics of left ASC origin.Successful radiofrequency catheter ablation was achieved at the site of the earliest ventricular activation in the left ASC. The distance between the successful ablation site of the left ASC and the site with an excellent pace map of the RVOT was 20 mm.The ndings could be strong evidence for a preferential conduction via the myocardial bers from the ASC origin to the breakout site in the right ventricular outflow tract. This case demonstrates that ventricular arrhythmias with a single origin and exit shift may exhibit QRS morphology changes.

Research on particle swarm optimization algorithm based on optimal movement probability

NASA Astrophysics Data System (ADS)

Ma, Jianhong; Zhang, Han; He, Baofeng

2017-01-01

The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.

Trajectory optimization of spacecraft high-thrust orbit transfer using a modified evolutionary algorithm

NASA Astrophysics Data System (ADS)

Shirazi, Abolfazl

2016-10-01

This article introduces a new method to optimize finite-burn orbital manoeuvres based on a modified evolutionary algorithm. Optimization is carried out based on conversion of the orbital manoeuvre into a parameter optimization problem by assigning inverse tangential functions to the changes in direction angles of the thrust vector. The problem is analysed using boundary delimitation in a common optimization algorithm. A method is introduced to achieve acceptable values for optimization variables using nonlinear simulation, which results in an enlarged convergence domain. The presented algorithm benefits from high optimality and fast convergence time. A numerical example of a three-dimensional optimal orbital transfer is presented and the accuracy of the proposed algorithm is shown.

Blood Pressure Response to Main Renal Artery and Combined Main Renal Artery Plus Branch Renal Denervation in Patients With Resistant Hypertension.

PubMed

Fengler, Karl; Ewen, Sebastian; Höllriegel, Robert; Rommel, Karl-Philipp; Kulenthiran, Saaraaken; Lauder, Lucas; Cremers, Bodo; Schuler, Gerhard; Linke, Axel; Böhm, Michael; Mahfoud, Felix; Lurz, Philipp

2017-08-10

Single-electrode ablation of the main renal artery for renal sympathetic denervation showed mixed blood pressure (BP)-lowering effects. Further improvement of the technique seems crucial to optimize effectiveness of the procedure. Because sympathetic nerve fibers are closer to the lumen in the distal part of the renal artery, treatment of the distal main artery and its branches has been shown to reduce variability in treatment effects in preclinical studies and a recent randomized trial. Whether this optimized technique improves clinical outcomes remains uncertain. We report a 2-center experience of main renal artery and combined main renal artery plus branches renal denervation in patients with resistant hypertension using a multielectrode catheter. Twenty-five patients with therapy-resistant hypertension underwent renal sympathetic denervation with combined main renal artery and renal branch ablation and were compared to matched controls undergoing an ablation of the main renal artery only. BP change was assessed by ambulatory measurement at baseline and after 3 months. At baseline, BP was balanced between the groups. After 3 months, BP changed significantly in the combined ablation group (systolic/diastolic 24-hour mean and daytime mean BP -8.5±9.8/-7.0±10.7 and -9.4±9.8/-7.1±13.5 mm Hg, P <0.001/0.003 and <0.001/0.016, respectively), but not in patients with main artery treatment (-3.5±11.1/-2.0±7.6 and -2.8±10.9/-1.8±7.7 mm Hg, P =0.19/0.20 and 0.19/0.24, respectively). Systolic daytime BP was significantly more reduced in patients with combined ablation than in patients with main artery ablation ( P =0.033). Combined ablation of the main renal artery and branches appears to improve BP-lowering efficacy and should be further investigated. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

A Modified Particle Swarm Optimization Technique for Finding Optimal Designs for Mixture Models

PubMed Central

Wong, Weng Kee; Chen, Ray-Bing; Huang, Chien-Chih; Wang, Weichung

2015-01-01

Particle Swarm Optimization (PSO) is a meta-heuristic algorithm that has been shown to be successful in solving a wide variety of real and complicated optimization problems in engineering and computer science. This paper introduces a projection based PSO technique, named ProjPSO, to efficiently find different types of optimal designs, or nearly optimal designs, for mixture models with and without constraints on the components, and also for related models, like the log contrast models. We also compare the modified PSO performance with Fedorov's algorithm, a popular algorithm used to generate optimal designs, Cocktail algorithm, and the recent algorithm proposed by [1]. PMID:26091237

Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle-Pock algorithm

PubMed Central

Sidky, Emil Y.; Jørgensen, Jakob H.; Pan, Xiaochuan

2012-01-01

The primal-dual optimization algorithm developed in Chambolle and Pock (CP), 2011 is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems for the purpose of designing iterative image reconstruction algorithms for CT. The primal-dual algorithm is briefly summarized in the article, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application modeling breast CT with low-intensity X-ray illumination is presented. PMID:22538474

Production scheduling with ant colony optimization

NASA Astrophysics Data System (ADS)

Chernigovskiy, A. S.; Kapulin, D. V.; Noskova, E. E.; Yamskikh, T. N.; Tsarev, R. Yu

2017-10-01

The optimum solution of the production scheduling problem for manufacturing processes at an enterprise is crucial as it allows one to obtain the required amount of production within a specified time frame. Optimum production schedule can be found using a variety of optimization algorithms or scheduling algorithms. Ant colony optimization is one of well-known techniques to solve the global multi-objective optimization problem. In the article, the authors present a solution of the production scheduling problem by means of an ant colony optimization algorithm. A case study of the algorithm efficiency estimated against some others production scheduling algorithms is presented. Advantages of the ant colony optimization algorithm and its beneficial effect on the manufacturing process are provided.

Utilization of selected laser-ablation-based diagnostic methods for study of elemental distribution in various solid samples

NASA Astrophysics Data System (ADS)

Kaiser, J.; Novotný, K.; Hrdlička, A.; Malina, R.; Novotný, J.; Prochazka, D.; Petrilak, M.; Krajcarová, L.; Vítková, G.; Kučerová, P.

2010-12-01

Here we report on the recent developments and upgrades of our Laser-Induced Breakdown Spectroscopy setups and their different modification for high-resolution mapping. Mapping capabilities of Laser-Induced Breakdown Spectroscopy (LIBS) and Laser Ablation Inductively Coupled Plasma Mass Spectrometry are compared. The applied improvements as an autofocus algorithm, together with the realization of double-pulse LIBS or combination of LIBS by Laser-Induced Fluorescence Spectroscopy (LIFS) with technique are detailed. The signal enhancement obtained by double-pulse approach is demonstrated. The state of the art on development of portable remote LIBS apparatus is also presented.

SPECIAL ISSUE DEVOTED TO THE 25th ANNIVERSARY OF THE A.M. PROKHOROV GENERAL PHYSICS INSTITUTE: High-speed ablation of ultradeep channels by a phase-conjugate dynamically controlled passively Q-switched Nd:YAG laser

NASA Astrophysics Data System (ADS)

Basiev, T. T.; Garnov, S. V.; Klimentov, S. M.; Pivovarov, P. A.; Gavrilov, A. V.; Smetanin, S. N.; Solokhin, S. A.; Fedin, A. V.

2007-10-01

Parameters of high-speed ablation of ultradeep channels by controlled pulse trains from a single-mode phase-conjugate dynamic cavity Nd:YAG laser emitting 20-200-ns, 70-250-mJ pulses at a pulse repetition rate in a train of 40-250 kHz are studied. The optimal parameters of ablation are found, for which a long-lived region of a hot rarefied gas was maintained in the ultradeep channel, which suppressed the shielding action of the surface plasma. The control of the lasing process during ablation optimises not only the heating and plasma formation, but also the removal of the processed material in the pause between laser pulses. Adaptive regulation of lasing parameters during ablation made it possible to obtain ultradeep channels of length 8-27 mm and diameters 80-300 μm of the input and output holes in metals (aluminium, steel and Inconel 718 nickel superalloy) and ultrahard ceramics (Al2O3, AlN, SiC).

Optimization of Straight Cylindrical Turning Using Artificial Bee Colony (ABC) Algorithm

NASA Astrophysics Data System (ADS)

Prasanth, Rajanampalli Seshasai Srinivasa; Hans Raj, Kandikonda

2017-04-01

Artificial bee colony (ABC) algorithm, that mimics the intelligent foraging behavior of honey bees, is increasingly gaining acceptance in the field of process optimization, as it is capable of handling nonlinearity, complexity and uncertainty. Straight cylindrical turning is a complex and nonlinear machining process which involves the selection of appropriate cutting parameters that affect the quality of the workpiece. This paper presents the estimation of optimal cutting parameters of the straight cylindrical turning process using the ABC algorithm. The ABC algorithm is first tested on four benchmark problems of numerical optimization and its performance is compared with genetic algorithm (GA) and ant colony optimization (ACO) algorithm. Results indicate that, the rate of convergence of ABC algorithm is better than GA and ACO. Then, the ABC algorithm is used to predict optimal cutting parameters such as cutting speed, feed rate, depth of cut and tool nose radius to achieve good surface finish. Results indicate that, the ABC algorithm estimated a comparable surface finish when compared with real coded genetic algorithm and differential evolution algorithm.

Firefly Algorithm, Lévy Flights and Global Optimization

NASA Astrophysics Data System (ADS)

Yang, Xin-She

Nature-inspired algorithms such as Particle Swarm Optimization and Firefly Algorithm are among the most powerful algorithms for optimization. In this paper, we intend to formulate a new metaheuristic algorithm by combining Lévy flights with the search strategy via the Firefly Algorithm. Numerical studies and results suggest that the proposed Lévy-flight firefly algorithm is superior to existing metaheuristic algorithms. Finally implications for further research and wider applications will be discussed.

A new hybrid meta-heuristic algorithm for optimal design of large-scale dome structures

NASA Astrophysics Data System (ADS)

Kaveh, A.; Ilchi Ghazaan, M.

2018-02-01

In this article a hybrid algorithm based on a vibrating particles system (VPS) algorithm, multi-design variable configuration (Multi-DVC) cascade optimization, and an upper bound strategy (UBS) is presented for global optimization of large-scale dome truss structures. The new algorithm is called MDVC-UVPS in which the VPS algorithm acts as the main engine of the algorithm. The VPS algorithm is one of the most recent multi-agent meta-heuristic algorithms mimicking the mechanisms of damped free vibration of single degree of freedom systems. In order to handle a large number of variables, cascade sizing optimization utilizing a series of DVCs is used. Moreover, the UBS is utilized to reduce the computational time. Various dome truss examples are studied to demonstrate the effectiveness and robustness of the proposed method, as compared to some existing structural optimization techniques. The results indicate that the MDVC-UVPS technique is a powerful search and optimization method for optimizing structural engineering problems.

Machining Parameters Optimization using Hybrid Firefly Algorithm and Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Farahlina Johari, Nur; Zain, Azlan Mohd; Haszlinna Mustaffa, Noorfa; Udin, Amirmudin

2017-09-01

Firefly Algorithm (FA) is a metaheuristic algorithm that is inspired by the flashing behavior of fireflies and the phenomenon of bioluminescent communication and the algorithm is used to optimize the machining parameters (feed rate, depth of cut, and spindle speed) in this research. The algorithm is hybridized with Particle Swarm Optimization (PSO) to discover better solution in exploring the search space. Objective function of previous research is used to optimize the machining parameters in turning operation. The optimal machining cutting parameters estimated by FA that lead to a minimum surface roughness are validated using ANOVA test.

The coral reefs optimization algorithm: a novel metaheuristic for efficiently solving optimization problems.

PubMed

Salcedo-Sanz, S; Del Ser, J; Landa-Torres, I; Gil-López, S; Portilla-Figueras, J A

2014-01-01

This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems.

Guided particle swarm optimization method to solve general nonlinear optimization problems

NASA Astrophysics Data System (ADS)

Abdelhalim, Alyaa; Nakata, Kazuhide; El-Alem, Mahmoud; Eltawil, Amr

2018-04-01

The development of hybrid algorithms is becoming an important topic in the global optimization research area. This article proposes a new technique in hybridizing the particle swarm optimization (PSO) algorithm and the Nelder-Mead (NM) simplex search algorithm to solve general nonlinear unconstrained optimization problems. Unlike traditional hybrid methods, the proposed method hybridizes the NM algorithm inside the PSO to improve the velocities and positions of the particles iteratively. The new hybridization considers the PSO algorithm and NM algorithm as one heuristic, not in a sequential or hierarchical manner. The NM algorithm is applied to improve the initial random solution of the PSO algorithm and iteratively in every step to improve the overall performance of the method. The performance of the proposed method was tested over 20 optimization test functions with varying dimensions. Comprehensive comparisons with other methods in the literature indicate that the proposed solution method is promising and competitive.

The Coral Reefs Optimization Algorithm: A Novel Metaheuristic for Efficiently Solving Optimization Problems

PubMed Central

Salcedo-Sanz, S.; Del Ser, J.; Landa-Torres, I.; Gil-López, S.; Portilla-Figueras, J. A.

2014-01-01

This paper presents a novel bioinspired algorithm to tackle complex optimization problems: the coral reefs optimization (CRO) algorithm. The CRO algorithm artificially simulates a coral reef, where different corals (namely, solutions to the optimization problem considered) grow and reproduce in coral colonies, fighting by choking out other corals for space in the reef. This fight for space, along with the specific characteristics of the corals' reproduction, produces a robust metaheuristic algorithm shown to be powerful for solving hard optimization problems. In this research the CRO algorithm is tested in several continuous and discrete benchmark problems, as well as in practical application scenarios (i.e., optimum mobile network deployment and off-shore wind farm design). The obtained results confirm the excellent performance of the proposed algorithm and open line of research for further application of the algorithm to real-world problems. PMID:25147860

A Comparative Study of Optimization Algorithms for Engineering Synthesis.

DTIC Science & Technology

1983-03-01

the ADS program demonstrates the flexibility a design engineer would have in selecting an optimization algorithm best suited to solve a particular...demonstrates the flexibility a design engineer would have in selecting an optimization algorithm best suited to solve a particular problem. 4 TABLE OF...algorithm to suit a particular problem. The ADS library of design optimization algorithms was . developed by Vanderplaats in response to the first

Particle Swarm Optimization Toolbox

NASA Technical Reports Server (NTRS)

Grant, Michael J.

2010-01-01

The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry trajectory and guidance design for the Mars Science Laboratory mission but may be applied to any optimization problem.

Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Xiaobiao; Safranek, James

2014-09-01

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

A fast optimization algorithm for multicriteria intensity modulated proton therapy planning.

PubMed

Chen, Wei; Craft, David; Madden, Thomas M; Zhang, Kewu; Kooy, Hanne M; Herman, Gabor T

2010-09-01

To describe a fast projection algorithm for optimizing intensity modulated proton therapy (IMPT) plans and to describe and demonstrate the use of this algorithm in multicriteria IMPT planning. The authors develop a projection-based solver for a class of convex optimization problems and apply it to IMPT treatment planning. The speed of the solver permits its use in multicriteria optimization, where several optimizations are performed which span the space of possible treatment plans. The authors describe a plan database generation procedure which is customized to the requirements of the solver. The optimality precision of the solver can be specified by the user. The authors apply the algorithm to three clinical cases: A pancreas case, an esophagus case, and a tumor along the rib cage case. Detailed analysis of the pancreas case shows that the algorithm is orders of magnitude faster than industry-standard general purpose algorithms (MOSEK'S interior point optimizer, primal simplex optimizer, and dual simplex optimizer). Additionally, the projection solver has almost no memory overhead. The speed and guaranteed accuracy of the algorithm make it suitable for use in multicriteria treatment planning, which requires the computation of several diverse treatment plans. Additionally, given the low memory overhead of the algorithm, the method can be extended to include multiple geometric instances and proton range possibilities, for robust optimization.

Harmonic Motion Imaging for Abdominal Tumor Detection and High-intensity Focused Ultrasound Ablation Monitoring: A Feasibility Study in a Transgenic Mouse Model of Pancreatic Cancer

PubMed Central

Chen, Hong; Hou, Gary Y.; Han, Yang; Payen, Thomas; Palermo, Carmine F.; Olive, Kenneth P.; Konofagou, Elisa E.

2015-01-01

Harmonic motion imaging (HMI) is a radiation force-based elasticity imaging technique that tracks oscillatory tissue displacements induced by sinusoidal ultrasonic radiation force to assess relative tissue stiffness. The objective of this study was to evaluate the feasibility of HMI in pancreatic tumor detection and high-intensity focused ultrasound (HIFU) treatment monitoring. The HMI system consisted of a focused ultrasound transducer, which generated sinusoidal radiation force to induce oscillatory tissue motion at 50 Hz, and a diagnostic ultrasound transducer, which detected the axial tissue displacements based on acquired radiofrequency signals using a 1D cross-correlation algorithm. For pancreatic tumor detection, HMI images were generated for pancreatic tumors in transgenic mice and normal pancreases in wild-type mice. The obtained HMI images showed a high contrast between normal and malignant pancreases with an average peak-to-peak HMI displacement ratio of 3.2. Histological analysis showed that no tissue damage was associated with HMI when it was used for the sole purpose of elasticity imaging. For pancreatic tumor ablation monitoring, the focused ultrasound transducer was operated with a higher acoustic power and longer pulse length than that used in tumor detection to simultaneously induce HIFU thermal ablation and oscillatory tissue displacements, allowing HMI monitoring without interrupting tumor ablation. HMI monitoring of HIFU ablation found significant decreases in the peak-to-peak HMI displacements before and after HIFU ablation with a reduction rate ranging from 15.8% to 57.0%. The formation of thermal lesions after HIFU exposure was confirmed by histological analysis. This study demonstrated the feasibility of HMI in abdominal tumor detection and HIFU ablation monitoring. PMID:26415128

Harmonic motion imaging for abdominal tumor detection and high-intensity focused ultrasound ablation monitoring: an in vivo feasibility study in a transgenic mouse model of pancreatic cancer.

PubMed

Chen, Hong; Hou, Gary Y; Han, Yang; Payen, Thomas; Palermo, Carmine F; Olive, Kenneth P; Konofagou, Elisa E

2015-09-01

Harmonic motion imaging (HMI) is a radiationforce- based elasticity imaging technique that tracks oscillatory tissue displacements induced by sinusoidal ultrasonic radiation force to assess the resulting oscillatory displacement denoting the underlying tissue stiffness. The objective of this study was to evaluate the feasibility of HMI in pancreatic tumor detection and high-intensity focused ultrasound (HIFU) treatment monitoring. The HMI system consisted of a focused ultrasound transducer, which generated sinusoidal radiation force to induce oscillatory tissue motion at 50 Hz, and a diagnostic ultrasound transducer, which detected the axial tissue displacements based on acquired radio-frequency signals using a 1-D cross-correlation algorithm. For pancreatic tumor detection, HMI images were generated for pancreatic tumors in transgenic mice and normal pancreases in wild-type mice. The obtained HMI images showed a high contrast between normal and malignant pancreases with an average peak-to-peak HMI displacement ratio of 3.2. Histological analysis showed that no tissue damage was associated with HMI when it was used for the sole purpose of elasticity imaging. For pancreatic tumor ablation monitoring, the focused ultrasound transducer was operated at a higher acoustic power and longer pulse length than that used in tumor detection to simultaneously induce HIFU thermal ablation and oscillatory tissue displacements, allowing HMI monitoring without interrupting tumor ablation. HMI monitoring of HIFU ablation found significant decreases in the peak-to-peak HMI displacements before and after HIFU ablation with a reduction rate ranging from 15.8% to 57.0%. The formation of thermal lesions after HIFU exposure was confirmed by histological analysis. This study demonstrated the feasibility of HMI in abdominal tumor detection and HIFU ablation monitoring.

Multidisciplinary Optimization of a Transport Aircraft Wing using Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Sobieszczanski-Sobieski, Jaroslaw; Venter, Gerhard

2002-01-01

The purpose of this paper is to demonstrate the application of particle swarm optimization to a realistic multidisciplinary optimization test problem. The paper's new contributions to multidisciplinary optimization is the application of a new algorithm for dealing with the unique challenges associated with multidisciplinary optimization problems, and recommendations as to the utility of the algorithm in future multidisciplinary optimization applications. The selected example is a bi-level optimization problem that demonstrates severe numerical noise and has a combination of continuous and truly discrete design variables. The use of traditional gradient-based optimization algorithms is thus not practical. The numerical results presented indicate that the particle swarm optimization algorithm is able to reliably find the optimum design for the problem presented here. The algorithm is capable of dealing with the unique challenges posed by multidisciplinary optimization as well as the numerical noise and truly discrete variables present in the current example problem.

Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming.

PubMed

Wang, Haizhou; Song, Mingzhou

2011-12-01

The heuristic k -means algorithm, widely used for cluster analysis, does not guarantee optimality. We developed a dynamic programming algorithm for optimal one-dimensional clustering. The algorithm is implemented as an R package called Ckmeans.1d.dp . We demonstrate its advantage in optimality and runtime over the standard iterative k -means algorithm.

Flight plan optimization

NASA Astrophysics Data System (ADS)

Dharmaseelan, Anoop; Adistambha, Keyne D.

2015-05-01

Fuel cost accounts for 40 percent of the operating cost of an airline. Fuel cost can be minimized by planning a flight on optimized routes. The routes can be optimized by searching best connections based on the cost function defined by the airline. The most common algorithm that used to optimize route search is Dijkstra's. Dijkstra's algorithm produces a static result and the time taken for the search is relatively long. This paper experiments a new algorithm to optimize route search which combines the principle of simulated annealing and genetic algorithm. The experimental results of route search, presented are shown to be computationally fast and accurate compared with timings from generic algorithm. The new algorithm is optimal for random routing feature that is highly sought by many regional operators.

Epileptogenicity and pathology - Under consideration of ablative approaches.

PubMed

Stefan, H; Schmitt, F C

2018-05-01

Besides resective epilepsy surgery, minimally invasive ablation using new diagnostic and therapeutic techniques recently became available. Optimal diagnostic approaches for these treatment options are discussed. The pathophysiology of epileptogenic networks differs depending on the lesion-types and location, requiring a differential use of non-invasive or invasive functional studies. In addition to the definition of epileptogenic zones, a challenge for pre-surgical investigation is the determination of three-dimensional epileptic networks to be removed. Copyright © 2018. Published by Elsevier B.V.

Randomised clinical trial of cryoballoon versus irrigated radio frequency catheter ablation for atrial fibrillation-the effect of double short versus standard exposure cryoablation duration during pulmonary vein isolation (CIRCA-DOSE): methods and rationale.

PubMed

Andrade, Jason G; Deyell, Marc W; Badra, Mariano; Champagne, Jean; Dubuc, Marc; Leong-Sit, Peter; Macle, Laurent; Novak, Paul; Roux, Jean-Francois; Sapp, John; Tang, Anthony; Verma, Atul; Wells, George A; Khairy, Paul

2017-10-05

Pulmonary vein isolation (PVI) is an effective therapy for paroxysmal atrial fibrillation (AF), but it has limitations. The two most significant recent advances have centred on the integration of real-time quantitative assessment of catheter contact force into focal radio frequency (RF) ablation catheters and the development of dedicated ablation tools capable of achieving PVI with a single ablation lesion (Arctic Front cryoballoon, Medtronic, Minneapolis, MN, USA). Although each of these holds promise for improving the clinical success of catheter ablation of AF, there has not been a rigorous comparison of these advanced ablation technologies. Moreover, the optimal duration of cryoablation (freezing time) has not been determined. Patients undergoing an initial PVI procedure for paroxysmal AF will be recruited. Patients will be randomised 1:1:1 between contact-force irrigated RF ablation, short duration cryoballoon ablation (2 min applications) and standard duration cryoballoon ablation (4 min applications). The primary outcome is time to first documented AF recurrence on implantable loop recorder. With a sample size of 111 per group and a two-sided 0.025 significance level (to account for the two main comparisons), the study will have 80% power (using a log-rank test) to detect a difference of 20% between contact force RF catheter ablation and either of the two cryoballoon ablation groups. Factoring in a 4% loss to follow-up, 116 patients per group should be randomised and followed for a year (total study population of 348). The study was approved by the University of British Columbia Office of Research (Services) Ethics Clinical Research Ethics Board. Results of the study will be submitted for publication in a peer-reviewed journal. NCT01913522; Pre-results. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Electrophysiology testing and catheter ablation are helpful when evaluating asymptomatic patients with Wolff-Parkinson-White pattern: the pro perspective.

PubMed

Pappone, Carlo; Santinelli, Vincenzo

2015-09-01

Important advances in the natural history and diagnosis of, and therapy for, asymptomatic Wolff-Parkinson-White (WPW) syndrome have been made in the last decade by our group. These data have necessitated revisiting current practice guidelines to decide on the optimal management of the asymptomatic WPW population. There has also been an emphasis on identifying initially asymptomatic individuals who are at risk by nationwide screening programs using the electrocardiogram for prophylactic catheter ablation to prevent the lifetime risk of sudden cardiac death, particularly in young asymptomatic people, because only a subgroup of them is at high risk, requiring early catheter ablation. Copyright © 2015 Elsevier Inc. All rights reserved.

Optical emission and nanoparticle generation in Al plasmas using ultrashort laser pulses temporally optimized by real-time spectroscopic feedback

DOE Office of Scientific and Technical Information (OSTI.GOV)

Guillermin, M.; Colombier, J. P.; Audouard, E.

2010-07-15

With an interest in pulsed laser deposition and remote spectroscopy techniques, we explore here the potential of laser pulses temporally tailored on ultrafast time scales to control the expansion and the excitation degree of various ablation products including atomic species and nanoparticulates. Taking advantage of automated pulse-shaping techniques, an adaptive procedure based on spectroscopic feedback is applied to regulate the irradiance and enhance the optical emission of monocharged aluminum ions with respect to the neutral signal. This leads to optimized pulses usually consisting in a series of femtosecond peaks distributed on a longer picosecond sequence. The ablation features induced bymore » the optimized pulse are compared with those determined by picosecond pulses generated by imposed second-order dispersion or by double pulse sequences with adjustable picosecond separation. This allows to analyze the influence of fast- and slow-varying envelope features on the material heating and the resulting plasma excitation degree. Using various optimal pulse forms including designed asymmetric shapes, we analyze the establishment of surface pre-excitation that enables conditions of enhanced radiation coupling. Thin films elaborated by unshaped femtosecond laser pulses and by optimized, stretched, or double pulse sequences are compared, indicating that the nanoparticles generation efficiency is strongly influenced by the temporal shaping of the laser irradiation. A thermodynamic scenario involving supercritical heating is proposed to explain enhanced ionization rates and lower particulates density for optimal pulses. Numerical one-dimensional hydrodynamic simulations for the excited matter support the interpretation of the experimental results in terms of relative efficiency of various relaxation paths for excited matter above or below the thermodynamic stability limits. The calculation results underline the role of the temperature and density gradients along the ablated plasma plume which lead to the spatial distinct locations of excited species. Moreover, the nanoparticles sizes are computed based on liquid layer ejection followed by a Rayleigh and Taylor instability decomposition, in good agreement with the experimental findings.« less

Cuckoo Search Algorithm Based on Repeat-Cycle Asymptotic Self-Learning and Self-Evolving Disturbance for Function Optimization

PubMed Central

Wang, Jie-sheng; Li, Shu-xia; Song, Jiang-di

2015-01-01

In order to improve convergence velocity and optimization accuracy of the cuckoo search (CS) algorithm for solving the function optimization problems, a new improved cuckoo search algorithm based on the repeat-cycle asymptotic self-learning and self-evolving disturbance (RC-SSCS) is proposed. A disturbance operation is added into the algorithm by constructing a disturbance factor to make a more careful and thorough search near the bird's nests location. In order to select a reasonable repeat-cycled disturbance number, a further study on the choice of disturbance times is made. Finally, six typical test functions are adopted to carry out simulation experiments, meanwhile, compare algorithms of this paper with two typical swarm intelligence algorithms particle swarm optimization (PSO) algorithm and artificial bee colony (ABC) algorithm. The results show that the improved cuckoo search algorithm has better convergence velocity and optimization accuracy. PMID:26366164

Modified artificial bee colony algorithm for reactive power optimization

NASA Astrophysics Data System (ADS)

Sulaiman, Noorazliza; Mohamad-Saleh, Junita; Abro, Abdul Ghani

2015-05-01

Bio-inspired algorithms (BIAs) implemented to solve various optimization problems have shown promising results which are very important in this severely complex real-world. Artificial Bee Colony (ABC) algorithm, a kind of BIAs has demonstrated tremendous results as compared to other optimization algorithms. This paper presents a new modified ABC algorithm referred to as JA-ABC3 with the aim to enhance convergence speed and avoid premature convergence. The proposed algorithm has been simulated on ten commonly used benchmarks functions. Its performance has also been compared with other existing ABC variants. To justify its robust applicability, the proposed algorithm has been tested to solve Reactive Power Optimization problem. The results have shown that the proposed algorithm has superior performance to other existing ABC variants e.g. GABC, BABC1, BABC2, BsfABC dan IABC in terms of convergence speed. Furthermore, the proposed algorithm has also demonstrated excellence performance in solving Reactive Power Optimization problem.

MR-guided high-intensity focused ultrasound ablation of breast cancer with a dedicated breast platform.

PubMed

Merckel, Laura G; Bartels, Lambertus W; Köhler, Max O; van den Bongard, H J G Desirée; Deckers, Roel; Mali, Willem P Th M; Binkert, Christoph A; Moonen, Chrit T; Gilhuijs, Kenneth G A; van den Bosch, Maurice A A J

2013-04-01

Optimizing the treatment of breast cancer remains a major topic of interest. In current clinical practice, breast-conserving therapy is the standard of care for patients with localized breast cancer. Technological developments have fueled interest in less invasive breast cancer treatment. Magnetic resonance-guided high-intensity focused ultrasound (MR-HIFU) is a completely noninvasive ablation technique. Focused beams of ultrasound are used for ablation of the target lesion without disrupting the skin and subcutaneous tissues in the beam path. MRI is an excellent imaging method for tumor targeting, treatment monitoring, and evaluation of treatment results. The combination of HIFU and MR imaging offers an opportunity for image-guided ablation of breast cancer. Previous studies of MR-HIFU in breast cancer patients reported a limited efficacy, which hampered the clinical translation of this technique. These prior studies were performed without an MR-HIFU system specifically developed for breast cancer treatment. In this article, a novel and dedicated MR-HIFU breast platform is presented. This system has been designed for safe and effective MR-HIFU ablation of breast cancer. Furthermore, both clinical and technical challenges are discussed, which have to be solved before MR-HIFU ablation of breast cancer can be implemented in routine clinical practice.

Modeling of Laser Material Interactions

NASA Astrophysics Data System (ADS)

Garrison, Barbara

2009-03-01

Irradiation of a substrate by laser light initiates the complex chemical and physical process of ablation where large amounts of material are removed. Ablation has been successfully used in techniques such as nanolithography and LASIK surgery, however a fundamental understanding of the process is necessary in order to further optimize and develop applications. To accurately describe the ablation phenomenon, a model must take into account the multitude of events which occur when a laser irradiates a target including electronic excitation, bond cleavage, desorption of small molecules, ongoing chemical reactions, propagation of stress waves, and bulk ejection of material. A coarse grained molecular dynamics (MD) protocol with an embedded Monte Carlo (MC) scheme has been developed which effectively addresses each of these events during the simulation. Using the simulation technique, thermal and chemical excitation channels are separately studied with a model polymethyl methacrylate system. The effects of the irradiation parameters and reaction pathways on the process dynamics are investigated. The mechanism of ablation for thermal processes is governed by a critical number of bond breaks following the deposition of energy. For the case where an absorbed photon directly causes a bond scission, ablation occurs following the rapid chemical decomposition of material. The study provides insight into the influence of thermal and chemical processes in polymethyl methacrylate and facilitates greater understanding of the complex nature of polymer ablation.

Evolution of Force Sensing Technologies.

PubMed

Shah, Dipen

2017-06-01

In order to Improve the procedural success and long-term outcomes of catheter ablation techniques for atrial fibrillation (AF), an Important unfulfilled requirement is to create durable electrophysiologically complete lesions. Measurement of contact force (CF) between the catheter tip and the target tissue can guide physicians to optimise both mapping and ablation procedures. Contact force can affect lesion size and clinical outcomes following catheter ablation of AF. Force sensing technologies have matured since their advent several years ago, and now allow the direct measurement of CF between the catheter tip and the target myocardium in real time. In order to obtain complete durable lesions, catheter tip spatial stability and stable contact force are important. Suboptimal energy delivery, lesion density/contiguity and/or excessive wall thickness of the pulmonary vein-left atrial (PV-LA) junction may result in conduction recovery at these sites. Lesion assessment tools may help predict and localise electrical weak points resulting in conduction recovery during and after ablation. There is increasing clinical evidence to show that optimal use of CF sensing during ablation can reduce acute PV re-conduction, although prospective randomised studies are desirable to confirm long-term favourable clinical outcomes. In combination with optimised lesion assessment tools, contact force sensing technology has the potential to become the standard of care for all patients undergoing AF catheter ablation.

Residual heat deposition in dental enamel during IR laser ablation at 2.79, 2.94, 9.6, and 10.6 microm.

PubMed

Fried, D; Ragadio, J; Champion, A

2001-01-01

The principal factor limiting the rate of laser ablation of dental hard tissue is the risk of excessive heat accumulation in the tooth. Excessive heat deposition or accumulation may result in unacceptable damage to the pulp. The objective of this study was to measure the residual heat deposition during the laser ablation of dental enamel at those IR laser wavelengths well suited for the removal of dental caries. Optimal laser ablation systems minimize the residual heat deposition in the tooth by efficiently transferring the deposited laser energy to kinetic and internal energy of ejected tissue components. The residual heat deposition in dental enamel was measured at laser wavelengths of 2.79, 2.94, 9.6, and 10.6 microm and pulse widths of 150 nsec -150 microsec using bovine block "calorimeters." Water droplets were applied to the surface before ablation with 150 microsec Er:YAG laser pulses to determine the influence of an optically thick water layer on reducing heat deposition. The residual heat was at a minimum for fluences well above the ablation threshold where measured values ranged from 25-70% depending on pulse duration and wavelength for the systems investigated. The lowest values of the residual heat were measured for short (< 20 micros) CO(2) laser pulses at 9.6 microm and for Q-switched erbium laser pulses at 2.79 and 2.94 microm. Droplets of water applied to the surface before ablation significantly reduced the residual heat deposition during ablation with 150 microsec Er:YAG laser pulses. Residual heat deposition can be markedly reduced by using CO(2) laser pulses of less than 20 microsec duration and shorter Q-switched Er:YAG and Er:YSGG laser pulses for enamel ablation. Copyright 2001 Wiley-Liss, Inc.

Thermal ablation of pancreatic cyst with a prototype endoscopic ultrasound capable radiofrequency needle device: A pilot feasibility study

PubMed Central

Moris, Maria; Atar, Mustafa; Kadayifci, Abdurrahman; Krishna, Murli; Librero, Ariston; Richie, Eugene; Brugge, William; Wallace, Michael B.

2017-01-01

Background and Objectives: Pancreatic cysts are evaluated by endoscopic ultrasound and fine needle aspiration (EUS). The only accepted treatment is pancreatectomy, which is associated with morbidity and mortality. This study evaluated the optimal thermal dosimetry of a novel radiofrequency ablation device using a standard electrosurgical unit in ex vivo cyst models. Methods: A modified EUS 22-gauge monopolar needle prototype with a tip electrode connected to a standard electrosurgical unit (Erbe USA, Marietta, GA, USA) was used to induce a subboiling point temperature. A cyst model was created using 2-cm sections of porcine small intestine ligated and filled with saline. After ablation, the cyst models were prepared for pathological evaluation. The epithelial layers were measured in at least two different sites with a micrometer and compared with the corresponding control sample. Results: Thirty-two cyst models were ablated with maximum temperatures of 50°C, 60°C, 90°C, and 97°C in 8, 11, 11, and 2 cysts, respectively. Longer ablation times were required to induce higher temperatures. A trend in the reduction in thickness of the measured layers was observed after exposure to higher temperatures. A temperature over 50°C was required for the ablation of the muscularis, submucosa, and villi, and over 60°C was required to ablate the mucosal crypts. Conclusions: In a preclinical model, a novel radiofrequency EUS-capable needle connected to a standard electrosurgical unit using standard low-voltage coagulation provided ablation in a temperature-dependent fashion with a threshold of at least 60°C and a safe cyst margin below 97°C. This potentially will allow low-cost, convenient cyst ablation. PMID:28440238

Optimal contact forces to minimize cardiac perforations before, during, and/or after radiofrequency or cryothermal ablations.

PubMed

Quallich, Stephen G; Van Heel, Michael; Iaizzo, Paul A

2015-02-01

Catheter perforations remain a major clinical concern during ablation procedures for treatment of atrial arrhythmias and may lead to life-threatening cardiac tamponade. Radiofrequency (RF) ablation alters the biomechanical properties of cardiac tissue, ultimately allowing for perforation to occur more readily. Studies on the effects of cryoablation on perforation force as well as studies defining the perforation force of human tissue are limited. The purpose of this study was to investigate the required force to elicit perforation of cardiac atrial tissue after or during ablation procedures. Effects of RF or cryothermal ablations on catheter perforation forces for both swine (n = 83 animals, 530 treatments) and human (n = 8 specimens, 136 treatments) cardiac tissue were investigated. Overall average forces resulting in perforation of healthy unablated tissue were 406g ± 170g for swine and 591g ± 240g for humans. Post-RF ablation applications considerably reduced these forces to 246g ± 118g for swine and 362 ± 185g for humans (P <.001). Treatments with cryoablation did not significantly alter forces required to induce perforations. Decreasing catheter sizes resulted in a reduction in forces required to perforate the atrial wall (P <.001). Catheter perforations occurred over an array of contact forces with a minimum of 38g being observed. The swine model likely underestimates the required perforation forces relative to those of human tissues. We provide novel insights related to the comparative effects of RF and cryothermal ablations on the potential for inducing undesired punctures, with RF ablation reducing perforation force significantly. These data are insightful for physicians performing ablation procedures as well as for medical device designers. Copyright © 2015 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

Improving the ablation efficiency of excimer laser systems with higher repetition rates through enhanced debris removal and optimized spot pattern.

PubMed

Arba-Mosquera, Samuel; Klinner, Thomas

2014-03-01

To evaluate the reasons for the required increased radiant exposure for higher-repetition-rate excimer lasers and determine experimentally possible compensations to achieve equivalent ablation profiles maintaining the same single-pulse energies and radiant exposures for laser repetition rates ranging from 430 to 1000 Hz. Schwind eye-tech-solutions GmbH and Co. KG, Kleinostheim, Germany. Experimental study. Poly(methyl methacrylate) (PMMA) plates were photoablated. The pulse laser energy was maintained during all experiments; the effects of the flow of the debris removal, the shot pattern for the correction, and precooling the PMMA plates were evaluated in terms of achieved ablation versus repetition rate. The mean ablation performance ranged from 88% to 100%; the variability between the profile measurements ranged from 1.4% to 6.2%. Increasing the laser repetition rate from 430 Hz to 1000 Hz reduced the mean ablation performance from 98% to 91% and worsened the variability from 1.9% to 4.3%. Increasing the flow of the debris removal, precooling the PMMA plates to -18°C, and adapting the shot pattern for the thermal response of PMMA to excimer ablation helped stabilize the variability. Only adapting the shot pattern for the thermal response of PMMA to excimer ablation helped stabilize the mean ablation performance. The ablation performance of higher-repetition-rate excimer lasers on PMMA improved with improvements in the debris removal systems and shot pattern. More powerful debris removal systems and smart shot patterns in terms of thermal response improved the performance of these excimer lasers. Copyright © 2014 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

A new optimized GA-RBF neural network algorithm.

PubMed

Jia, Weikuan; Zhao, Dean; Shen, Tian; Su, Chunyang; Hu, Chanli; Zhao, Yuyan

2014-01-01

When confronting the complex problems, radial basis function (RBF) neural network has the advantages of adaptive and self-learning ability, but it is difficult to determine the number of hidden layer neurons, and the weights learning ability from hidden layer to the output layer is low; these deficiencies easily lead to decreasing learning ability and recognition precision. Aiming at this problem, we propose a new optimized RBF neural network algorithm based on genetic algorithm (GA-RBF algorithm), which uses genetic algorithm to optimize the weights and structure of RBF neural network; it chooses new ways of hybrid encoding and optimizing simultaneously. Using the binary encoding encodes the number of the hidden layer's neurons and using real encoding encodes the connection weights. Hidden layer neurons number and connection weights are optimized simultaneously in the new algorithm. However, the connection weights optimization is not complete; we need to use least mean square (LMS) algorithm for further leaning, and finally get a new algorithm model. Using two UCI standard data sets to test the new algorithm, the results show that the new algorithm improves the operating efficiency in dealing with complex problems and also improves the recognition precision, which proves that the new algorithm is valid.

Metaheuristic Optimization and its Applications in Earth Sciences

NASA Astrophysics Data System (ADS)

Yang, Xin-She

2010-05-01

A common but challenging task in modelling geophysical and geological processes is to handle massive data and to minimize certain objectives. This can essentially be considered as an optimization problem, and thus many new efficient metaheuristic optimization algorithms can be used. In this paper, we will introduce some modern metaheuristic optimization algorithms such as genetic algorithms, harmony search, firefly algorithm, particle swarm optimization and simulated annealing. We will also discuss how these algorithms can be applied to various applications in earth sciences, including nonlinear least-squares, support vector machine, Kriging, inverse finite element analysis, and data-mining. We will present a few examples to show how different problems can be reformulated as optimization. Finally, we will make some recommendations for choosing various algorithms to suit various problems. References 1) D. H. Wolpert and W. G. Macready, No free lunch theorems for optimization, IEEE Trans. Evolutionary Computation, Vol. 1, 67-82 (1997). 2) X. S. Yang, Nature-Inspired Metaheuristic Algorithms, Luniver Press, (2008). 3) X. S. Yang, Mathematical Modelling for Earth Sciences, Dunedin Academic Press, (2008).

VDLLA: A virtual daddy-long legs optimization

NASA Astrophysics Data System (ADS)

Yaakub, Abdul Razak; Ghathwan, Khalil I.

2016-08-01

Swarm intelligence is a strong optimization algorithm based on a biological behavior of insects or animals. The success of any optimization algorithm is depending on the balance between exploration and exploitation. In this paper, we present a new swarm intelligence algorithm, which is based on daddy long legs spider (VDLLA) as a new optimization algorithm with virtual behavior. In VDLLA, each agent (spider) has nine positions which represent the legs of spider and each position represent one solution. The proposed VDLLA is tested on four standard functions using average fitness, Medium fitness and standard deviation. The results of proposed VDLLA have been compared against Particle Swarm Optimization (PSO), Differential Evolution (DE) and Bat Inspired Algorithm (BA). Additionally, the T-Test has been conducted to show the significant deference between our proposed and other algorithms. VDLLA showed very promising results on benchmark test functions for unconstrained optimization problems and also significantly improved the original swarm algorithms.

Use of shear waves for diagnosis and ablation monitoring of prostate cancer: a feasibility study

NASA Astrophysics Data System (ADS)

Gomez, A.; Rus, G.; Saffari, N.

2016-01-01

Prostate cancer remains as a major healthcare issue. Limitations in current diagnosis and treatment monitoring techniques imply that there is still a need for improvements. The efficacy of prostate cancer diagnosis is still low, generating under and over diagnoses. High intensity focused ultrasound ablation is an emerging treatment modality, which enables the noninvasive ablation of pathogenic tissue. Clinical trials are being carried out to evaluate its longterm efficacy as a focal treatment for prostate cancer. Successful treatment of prostate cancer using non-invasive modalities is critically dependent on accurate diagnostic means and is greatly benefited by a real-time monitoring system. While magnetic resonance imaging remains the gold standard for prostate imaging, its wider implementation for prostate cancer diagnosis remains prohibitively expensive. Conventional ultrasound is currently limited to guiding biopsy. Elastography techniques are emerging as a promising real-time imaging method, as cancer nodules are usually stiffer than adjacent healthy prostatic tissue. In this paper, a new transurethral approach is proposed, using shear waves for diagnosis and ablation monitoring of prostate cancer. A finite-difference time domain model is developed for studying the feasibility of the method, and an inverse problem technique based on genetic algorithms is proposed for reconstructing the location, size and stiffness parameters of the tumour. Preliminary results indicate that the use of shear waves for diagnosis and monitoring ablation of prostate cancer is feasible.

Interactive Volumetry Of Liver Ablation Zones.

PubMed

Egger, Jan; Busse, Harald; Brandmaier, Philipp; Seider, Daniel; Gawlitza, Matthias; Strocka, Steffen; Voglreiter, Philip; Dokter, Mark; Hofmann, Michael; Kainz, Bernhard; Hann, Alexander; Chen, Xiaojun; Alhonnoro, Tuomas; Pollari, Mika; Schmalstieg, Dieter; Moche, Michael

2015-10-20

Percutaneous radiofrequency ablation (RFA) is a minimally invasive technique that destroys cancer cells by heat. The heat results from focusing energy in the radiofrequency spectrum through a needle. Amongst others, this can enable the treatment of patients who are not eligible for an open surgery. However, the possibility of recurrent liver cancer due to incomplete ablation of the tumor makes post-interventional monitoring via regular follow-up scans mandatory. These scans have to be carefully inspected for any conspicuousness. Within this study, the RF ablation zones from twelve post-interventional CT acquisitions have been segmented semi-automatically to support the visual inspection. An interactive, graph-based contouring approach, which prefers spherically shaped regions, has been applied. For the quantitative and qualitative analysis of the algorithm's results, manual slice-by-slice segmentations produced by clinical experts have been used as the gold standard (which have also been compared among each other). As evaluation metric for the statistical validation, the Dice Similarity Coefficient (DSC) has been calculated. The results show that the proposed tool provides lesion segmentation with sufficient accuracy much faster than manual segmentation. The visual feedback and interactivity make the proposed tool well suitable for the clinical workflow.

Optimal Parameters for Intervertebral Disk Resection Using Aqua-Plasma Beams.

PubMed

Yoon, Sung-Young; Kim, Gon-Ho; Kim, Yushin; Kim, Nack Hwan; Lee, Sangheon; Kawai, Christina; Hong, Youngki

2018-06-14

 A minimally invasive procedure for intervertebral disk resection using plasma beams has been developed. Conventional parameters for the plasma procedure such as voltage and tip speed mainly rely on the surgeon's personal experience, without adequate evidence from experiments. Our objective was to determine the optimal parameters for plasma disk resection.  Rate of ablation was measured at different procedural tip speeds and voltages using porcine nucleus pulposi. The amount of heat formation during experimental conditions was also measured to evaluate the thermal safety of the plasma procedure.  The ablation rate increased at slower procedural speeds and higher voltages. However, for thermal safety, the optimal parameters for plasma procedures with minimal tissue damage were an electrical output of 280 volts root-mean-square (V rms ) and a procedural tip speed of 2.5 mm/s.  Our findings provide useful information for an effective and safe plasma procedure for disk resection in a clinical setting. Georg Thieme Verlag KG Stuttgart · New York.

A Novel Particle Swarm Optimization Algorithm for Global Optimization

PubMed Central

Wang, Chun-Feng; Liu, Kui

2016-01-01

Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire population in the current iteration is considered. Meanwhile, to avoid premature, an abandoned mechanism is used. Furthermore, for improving the global convergence speed of our algorithm, a chaotic search is adopted in the best solution of the current iteration. To verify the performance of our algorithm, standard test functions have been employed. The experimental results show that the algorithm is much more robust and efficient than some existing Particle Swarm Optimization algorithms. PMID:26955387

Analysis of parameter estimation and optimization application of ant colony algorithm in vehicle routing problem

NASA Astrophysics Data System (ADS)

Xu, Quan-Li; Cao, Yu-Wei; Yang, Kun

2018-03-01

Ant Colony Optimization (ACO) is the most widely used artificial intelligence algorithm at present. This study introduced the principle and mathematical model of ACO algorithm in solving Vehicle Routing Problem (VRP), and designed a vehicle routing optimization model based on ACO, then the vehicle routing optimization simulation system was developed by using c ++ programming language, and the sensitivity analyses, estimations and improvements of the three key parameters of ACO were carried out. The results indicated that the ACO algorithm designed in this paper can efficiently solve rational planning and optimization of VRP, and the different values of the key parameters have significant influence on the performance and optimization effects of the algorithm, and the improved algorithm is not easy to locally converge prematurely and has good robustness.

Optimization of High-Dimensional Functions through Hypercube Evaluation

PubMed Central

Abiyev, Rahib H.; Tunay, Mustafa

2015-01-01

A novel learning algorithm for solving global numerical optimization problems is proposed. The proposed learning algorithm is intense stochastic search method which is based on evaluation and optimization of a hypercube and is called the hypercube optimization (HO) algorithm. The HO algorithm comprises the initialization and evaluation process, displacement-shrink process, and searching space process. The initialization and evaluation process initializes initial solution and evaluates the solutions in given hypercube. The displacement-shrink process determines displacement and evaluates objective functions using new points, and the search area process determines next hypercube using certain rules and evaluates the new solutions. The algorithms for these processes have been designed and presented in the paper. The designed HO algorithm is tested on specific benchmark functions. The simulations of HO algorithm have been performed for optimization of functions of 1000-, 5000-, or even 10000 dimensions. The comparative simulation results with other approaches demonstrate that the proposed algorithm is a potential candidate for optimization of both low and high dimensional functions. PMID:26339237

Towards enhancement of performance of K-means clustering using nature-inspired optimization algorithms.

PubMed

Fong, Simon; Deb, Suash; Yang, Xin-She; Zhuang, Yan

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario.

Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms

PubMed Central

Deb, Suash; Yang, Xin-She

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario. PMID:25202730

Optimal Battery Sizing in Photovoltaic Based Distributed Generation Using Enhanced Opposition-Based Firefly Algorithm for Voltage Rise Mitigation

PubMed Central

Wong, Ling Ai; Shareef, Hussain; Mohamed, Azah; Ibrahim, Ahmad Asrul

2014-01-01

This paper presents the application of enhanced opposition-based firefly algorithm in obtaining the optimal battery energy storage systems (BESS) sizing in photovoltaic generation integrated radial distribution network in order to mitigate the voltage rise problem. Initially, the performance of the original firefly algorithm is enhanced by utilizing the opposition-based learning and introducing inertia weight. After evaluating the performance of the enhanced opposition-based firefly algorithm (EOFA) with fifteen benchmark functions, it is then adopted to determine the optimal size for BESS. Two optimization processes are conducted where the first optimization aims to obtain the optimal battery output power on hourly basis and the second optimization aims to obtain the optimal BESS capacity by considering the state of charge constraint of BESS. The effectiveness of the proposed method is validated by applying the algorithm to the 69-bus distribution system and by comparing the performance of EOFA with conventional firefly algorithm and gravitational search algorithm. Results show that EOFA has the best performance comparatively in terms of mitigating the voltage rise problem. PMID:25054184

Optimal battery sizing in photovoltaic based distributed generation using enhanced opposition-based firefly algorithm for voltage rise mitigation.

PubMed

Wong, Ling Ai; Shareef, Hussain; Mohamed, Azah; Ibrahim, Ahmad Asrul

2014-01-01

This paper presents the application of enhanced opposition-based firefly algorithm in obtaining the optimal battery energy storage systems (BESS) sizing in photovoltaic generation integrated radial distribution network in order to mitigate the voltage rise problem. Initially, the performance of the original firefly algorithm is enhanced by utilizing the opposition-based learning and introducing inertia weight. After evaluating the performance of the enhanced opposition-based firefly algorithm (EOFA) with fifteen benchmark functions, it is then adopted to determine the optimal size for BESS. Two optimization processes are conducted where the first optimization aims to obtain the optimal battery output power on hourly basis and the second optimization aims to obtain the optimal BESS capacity by considering the state of charge constraint of BESS. The effectiveness of the proposed method is validated by applying the algorithm to the 69-bus distribution system and by comparing the performance of EOFA with conventional firefly algorithm and gravitational search algorithm. Results show that EOFA has the best performance comparatively in terms of mitigating the voltage rise problem.

Conformal needle-based ultrasound ablation using EM-tracked conebeam CT image guidance

NASA Astrophysics Data System (ADS)

Burdette, E. Clif; Banovac, Filip; Diederich, Chris J.; Cheng, Patrick; Wilson, Emmanuel; Cleary, Kevin R.

2011-03-01

Numerous studies have demonstrated the efficacy of interstitial ablative approaches for the treatment of renal and hepatic tumors. Despite these promising results, current systems remain highly dependent on operator skill, and cannot treat many tumors because there is little control of the size and shape of the zone of necrosis, and no control over ablator trajectory within tissue once insertion has taken place. Additionally, tissue deformation and target motion make it extremely difficult to accurately place the ablator device into the target. Irregularly shaped target volumes typically require multiple insertions and several sequential thermal ablation procedures. This study demonstrated feasibility of spatially tracked image-guided conformal ultrasound (US) ablation for percutaneous directional ablation of diseased tissue. Tissue was prepared by suturing the liver within a pig belly and 1mm BBs placed to serve as needle targets. The image guided system used integrated electromagnetic tracking and cone-beam CT (CBCT) with conformable needlebased high-intensity US ablation in the interventional suite. Tomographic images from cone beam CT were transferred electronically to the image-guided tracking system (IGSTK). Paired-point registration was used to register the target specimen to CT images and enable navigation. Path planning is done by selecting the target BB on the GUI of the realtime tracking system and determining skin entry location until an optimal path is selected. Power was applied to create the desired ablation extent within 7-10 minutes at a thermal dose (>300eqm43). The system was successfully used to place the US ablator in planned target locations within ex-vivo kidney and liver through percutaneous access. Targeting accuracy was 3-4 mm. Sectioned specimens demonstrated uniform ablation within the planned target zone. Subsequent experiments were conducted for multiple ablator positions based upon treatment planning simulations. Ablation zones in liver were 73cc, 84cc, and 140cc for 3, 4, and 5 placements, respectively. These experiments demonstrate the feasibility of combining real-time spatially tracked image guidance with directional interstitial ultrasound ablation. Interstitial ultrasound ablation delivered on multiple needles permit the size and shape of the ablation zone to be "sculpted" by modifying the angle and intensity of the active US elements in the array. This paper summarizes the design and development of the first system incorporating thermal treatment planning and integration of a novel interstitial acoustic ablation device with integrated 3D electromagnetic tracking and guidance strategy.

Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm.

PubMed

Rani, R Ranjani; Ramyachitra, D

2016-12-01

Multiple sequence alignment (MSA) is a widespread approach in computational biology and bioinformatics. MSA deals with how the sequences of nucleotides and amino acids are sequenced with possible alignment and minimum number of gaps between them, which directs to the functional, evolutionary and structural relationships among the sequences. Still the computation of MSA is a challenging task to provide an efficient accuracy and statistically significant results of alignments. In this work, the Bacterial Foraging Optimization Algorithm was employed to align the biological sequences which resulted in a non-dominated optimal solution. It employs Multi-objective, such as: Maximization of Similarity, Non-gap percentage, Conserved blocks and Minimization of gap penalty. BAliBASE 3.0 benchmark database was utilized to examine the proposed algorithm against other methods In this paper, two algorithms have been proposed: Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC) and Bacterial Foraging Optimization Algorithm. It was found that Hybrid Genetic Algorithm with Artificial Bee Colony performed better than the existing optimization algorithms. But still the conserved blocks were not obtained using GA-ABC. Then BFO was used for the alignment and the conserved blocks were obtained. The proposed Multi-Objective Bacterial Foraging Optimization Algorithm (MO-BFO) was compared with widely used MSA methods Clustal Omega, Kalign, MUSCLE, MAFFT, Genetic Algorithm (GA), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO) and Hybrid Genetic Algorithm with Artificial Bee Colony (GA-ABC). The final results show that the proposed MO-BFO algorithm yields better alignment than most widely used methods. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Use of the Hotelling observer to optimize image reconstruction in digital breast tomosynthesis

PubMed Central

Sánchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan

2015-01-01

Abstract. We propose an implementation of the Hotelling observer that can be applied to the optimization of linear image reconstruction algorithms in digital breast tomosynthesis. The method is based on considering information within a specific region of interest, and it is applied to the optimization of algorithms for detectability of microcalcifications. Several linear algorithms are considered: simple back-projection, filtered back-projection, back-projection filtration, and Λ-tomography. The optimized algorithms are then evaluated through the reconstruction of phantom data. The method appears robust across algorithms and parameters and leads to the generation of algorithm implementations which subjectively appear optimized for the task of interest. PMID:26702408

Portfolio optimization by using linear programing models based on genetic algorithm

NASA Astrophysics Data System (ADS)

Sukono; Hidayat, Y.; Lesmana, E.; Putra, A. S.; Napitupulu, H.; Supian, S.

2018-01-01

In this paper, we discussed the investment portfolio optimization using linear programming model based on genetic algorithms. It is assumed that the portfolio risk is measured by absolute standard deviation, and each investor has a risk tolerance on the investment portfolio. To complete the investment portfolio optimization problem, the issue is arranged into a linear programming model. Furthermore, determination of the optimum solution for linear programming is done by using a genetic algorithm. As a numerical illustration, we analyze some of the stocks traded on the capital market in Indonesia. Based on the analysis, it is shown that the portfolio optimization performed by genetic algorithm approach produces more optimal efficient portfolio, compared to the portfolio optimization performed by a linear programming algorithm approach. Therefore, genetic algorithms can be considered as an alternative on determining the investment portfolio optimization, particularly using linear programming models.

In-Situ Apatite Laser Ablation U-Th-Sm/He Dating, Methods and Challenges

NASA Astrophysics Data System (ADS)

Pickering, J. E.; Matthews, W.; Guest, B.; Hamilton, B.; Sykes, C.

2015-12-01

In-situ, laser ablation U-Th-Sm/He dating is an emerging technique in thermochronology that has been proven as a means to date zircon and monzonite1-5. In-situ U-Th-Sm/He thermochronology eliminates many of the problems and inconveniences associated with traditional, whole grain methods, including; reducing bias in grain selection based on size, shape and clarity; allowing for the use of broken grains and grains with inclusions; avoiding bad neighbour effects; and eliminating safety hazards associated with dissolution. In-situ apatite laser ablation is challenging due to low concentrations of U and Th and thus a low abundance of radiogenic He. For apatite laser ablation to be effective the ultra-high-vacuum (UHV) line must have very low and consistent background levels of He. To reduce He background, samples are mounted in a UHV stable medium. Our mounting process uses a MicroHePP (Microscope Mounted Heated Platen Press) to press samples into FEP (fluorinated ethylene propylene) bonded to an aluminum backing plate. Samples are ablated using a Resonetics 193 nm excimer laser and liberated He is measured using a quadrupole mass spectrometer on the ASI Alphachron noble gas line; collectively this system is known as the Resochron. The ablated sites are imaged using a Zygo Zescope optical profilometer and ablated pit volume measured using PitVol, a custom MatLab algorithm developed to enable precise and unbiased measurement of the ablated pit geometry. We use the well-characterized Durango apatite to demonstrate the accuracy and precision of the method. He liberated from forty-two pits, having volumes between 1700 and 9000 um3, were measured using the Resochron. The ablated sites were imaged using a Zygo Zescope optical profilometer and ablated pit volume measured using PitVol. U, Th and Sm concentrations were measured by laser ablation and the U-Th-Sm/He age calculated by standard age equation. An age of 33.8±0.31 Ma was determined and compares well with conventional U-Th/He methods, whole grain degassing and dissolution, that produced an age of 32.73±0.47 Ma for chips of the same Durango crystal. Further dating of other well characterized apatite crystals will be used to test the robustness of the method.

A Comprehensive Review of Swarm Optimization Algorithms

PubMed Central

2015-01-01

Many swarm optimization algorithms have been introduced since the early 60’s, Evolutionary Programming to the most recent, Grey Wolf Optimization. All of these algorithms have demonstrated their potential to solve many optimization problems. This paper provides an in-depth survey of well-known optimization algorithms. Selected algorithms are briefly explained and compared with each other comprehensively through experiments conducted using thirty well-known benchmark functions. Their advantages and disadvantages are also discussed. A number of statistical tests are then carried out to determine the significant performances. The results indicate the overall advantage of Differential Evolution (DE) and is closely followed by Particle Swarm Optimization (PSO), compared with other considered approaches. PMID:25992655

Skin pre-ablation and laser assisted microjet injection for deep tissue penetration.

PubMed

Jang, Hun-Jae; Yeo, Seonggu; Yoh, Jack J

2017-04-01

For conventional needless injection, there still remain many unresolved issues such as the potential for cross-contamination, poor reliability of targeted delivery dose, and significantly painstaking procedures. As an alternative, the use of microjets generated with Er:YAG laser for delivering small doses with controlled penetration depths has been reported. In this study, a new system with two stages is evaluated for effective transdermal drug delivery. First, the skin is pre-ablated to eliminate the hard outer layer and second, laser-driven microjet penetrates the relatively weaker and freshly exposed epidermis. Each stage of operation shares a single Er:YAG laser that is suitable for skin ablation as well as for the generation of a microjet. In this study, pig skin is selected for quantification of the injection depth based on the two-stage procedure, namely pre-ablation and microjet injection. The three types of pre-ablation devised here consists of bulk ablation, fractional ablation, and fractional-rotational ablation. The number of laser pulses are 12, 18, and 24 for each ablation type. For fractional-rotational ablation, the fractional beams are rotated by 11.25° at each pulse. The drug permeation in the skin is evaluated using tissue marking dyes. The depth of penetration is quantified by a cross sectional view of the single spot injections. Multi-spot injections are also carried out to control the dose and spread of the drug. The benefits of a pre-ablation procedure prior to the actual microjet injection to the penetration is verified. The four possible combinations of injection are (a) microjet only; (b) bulk ablation and microjet injection; (c) fractional ablation and microjet injection; and (d) fractional-rotational ablation and microjet injection. Accordingly, the total depth increases with injection time for all cases. In particular, the total depth of penetration attained via fractional pre-ablation increased by 8 ∼ 11% and that of fractional-rotational pre-ablation increased by 13 ∼ 33%, when compared with the no pre-ablation or microjet only cases. A noticeable point is that the fraction-rotational pre-ablation and microjet result is comparable to the bulk ablation and microjet result of 11 ∼ 42%. The penetration depth underneath ablated stratum corneum (SC) is also measured in order to verify the pre-ablation effect. The penetration depths for each case are (a) 443 ± 104 µm; (b) 625 ± 98 µm; (c) 523 ± 95 µm; and (d) 595 ± 141 µm for microjet only, bulk ablation and microjet, fractional ablation and microjet, and fractional-rotational ablation and microjet, respectively. This is quite beneficial since any healing time associated with ablation is significantly reduced by avoiding hard-core bulk ablation. Thus the bulk pre-ablation and microjet may well be superseded by the less invasive fractiona-rotational ablation followed by the microjet injection. The density of micro-holes is 1.27 number/mm 2 for fractional ablation and 4.84 number/mm 2 for fractional-rotational ablation. The penetration depths measured underneath the ablated SC are 581 µm (fractional ablation and microjet) and 691 µm (fractional-rotational ablation and microjet). Fractional-rotational ablation increases number of micro-holes in a unit area, enabling fast reepithelialization and high drug delivery efficiency. Optimization of system parameters such as ablation time, number of ablations, and injection time will eventually ensure a macromolecule delivery technique with the potential to include vaccines, insulins, and growth hormones, all of which require deeper penetration into the skin. Lasers Surg. Med. 49:387-394, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Privacy Preservation in Distributed Subgradient Optimization Algorithms.

PubMed

Lou, Youcheng; Yu, Lean; Wang, Shouyang; Yi, Peng

2017-07-31

In this paper, some privacy-preserving features for distributed subgradient optimization algorithms are considered. Most of the existing distributed algorithms focus mainly on the algorithm design and convergence analysis, but not the protection of agents' privacy. Privacy is becoming an increasingly important issue in applications involving sensitive information. In this paper, we first show that the distributed subgradient synchronous homogeneous-stepsize algorithm is not privacy preserving in the sense that the malicious agent can asymptotically discover other agents' subgradients by transmitting untrue estimates to its neighbors. Then a distributed subgradient asynchronous heterogeneous-stepsize projection algorithm is proposed and accordingly its convergence and optimality is established. In contrast to the synchronous homogeneous-stepsize algorithm, in the new algorithm agents make their optimization updates asynchronously with heterogeneous stepsizes. The introduced two mechanisms of projection operation and asynchronous heterogeneous-stepsize optimization can guarantee that agents' privacy can be effectively protected.

Performance of an ablator for Space Shuttle inorbit repair in an arc-plasma airstream

NASA Technical Reports Server (NTRS)

Stewart, D. A.; Cuellar, M.; Flowers, O.

1983-01-01

An ablator patch material performed well in an arc plasma environment simulating nominal Earth entry conditions for the Space Shuttle. Ablation tests using vacuum molded cones provided data to optimize the formulation of a two part polymer system for application under space conditions. The blunt cones were made using a Teflon mold and a state of the art caulking gun. Char stability of formulations with various amounts of catalyst and diluent were investigated. The char was found to be unstable in formulations with low amounts of catalyst and high amounts of diluent. The best polymer system determined by these tests was evaluated using a half tile patch in a multiple High Temperature Reusable surface Insulation tile model. It was demonstrated that this ablator could be applied in a space environment using a state of the art caulking gun, would maintain the outer mold line of the thermal protection system during entry, and would keep the bond line temperature at the aluminum tile interface below the design limit.

Rapid fabrication of poly(dimethylsiloxane)-based microchip capillary electrophoresis devices using CO2 laser ablation.

PubMed

Fogarty, Barbara A; Heppert, Kathleen E; Cory, Theodore J; Hulbutta, Kalonie R; Martin, R Scott; Lunte, Susan M

2005-06-01

The use of CO(2) laser ablation for the patterning of capillary electrophoresis (CE) microchannels in poly(dimethylsiloxane)(PDMS) is described. Low-cost polymer devices were produced using a relatively inexpensive CO(2) laser system that facilitated rapid patterning and ablation of microchannels. Device designs were created using a commercially available software package. The effects of PDMS thickness, laser focusing, power, and speed on the resulting channel dimensions were investigated. Using optimized settings, the smallest channels that could be produced averaged 33 microm in depth (11.1% RSD, N= 6) and 110 microm in width (5.7% RSD, N= 6). The use of a PDMS substrate allowed reversible sealing of microchip components at room temperature without the need for cleanroom facilities. Using a layer of pre-cured polymer, devices were designed, ablated, and assembled within minutes. The final devices were used for microchip CE separation and detection of the fluorescently labeled neurotransmitters aspartate and glutamate.

Profiling of patterned metal layers by laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS)

NASA Astrophysics Data System (ADS)

Bi, Melody; Ruiz, Antonio M.; Gornushkin, Igor; Smith, Ben W.; Winefordner, James D.

2000-02-01

Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) was used for profiling patterned thin metal layers on a polymer/silicon substrate. The parameters of the laser and ICP-MS operating conditions have been studied and optimized for this purpose. A new laser ablation chamber was designed and built to achieve the best spatial resolution. The results of the profiling by LA-ICP-MS were compared to those obtained from a laser ablation optical emission spectrometry (LA-OES) instrument, which measured the emission of the plasma at the sample surface, and thus, eliminated the time delay caused by the sample transport into the ICP-MS system. Emission spectra gave better spatial resolution than mass spectra. However, LA-ICP-MS provided much better sensitivity and was able to profile thin metal layers (on the order of a few nanometers) on the silicon surface. A lateral spatial resolution of 45 μm was achieved.

Morphologies of femtosecond laser ablation of ITO thin films using gaussian or quasi-flat top beams for OLED repair

NASA Astrophysics Data System (ADS)

Kim, Hoon-Young; Choi, Won-Suk; Ji, Suk-Young; Shin, Young-Gwan; Jeon, Jin-Woo; Ahn, Sanghoon; Cho, Sung-Hak

2018-02-01

This study compares the ablation morphologies obtained with a femtosecond laser of both Gaussian and quasi-flat top beam profiles when applied to indium tin oxide (ITO) thin films for the purpose of OLED repair. A femtosecond laser system with a wavelength of 1030 nm and pulse duration of 190 fs is used to pattern an ITO thin film. The laser fluence is optimized for patterning at 1.38 J/cm2. The patterned ITO thin film is then evaluated through both optical microscope and atomic force microscope. Ablations with a square quasi-flat top beam are demonstrated using slits with varying x- y axes. With the Gaussian beam, the pattern width of the ablated area is shown to range from 9.17 to 9.99 μm when the number of irradiation pulse increases from one to six. In contrast, when slit control is used to obtain a quasi-flat top beam, the ablated pattern width remains constant at 10 μm, despite the increase in the number of pulse. The improved surface roughness is correlated with the quasi-flat top beam through measured Ra values. Furthermore, when using the Gaussian beam, the minimum resolution of the controllable ablation depth on the ITO thin film is found to be 60 nm. In contrast, when the quasi-flat top beam is used, the minimum ablation depth decreases to 40 nm.

Particle swarm optimization: an alternative in marine propeller optimization?

NASA Astrophysics Data System (ADS)

Vesting, F.; Bensow, R. E.

2018-01-01

This article deals with improving and evaluating the performance of two evolutionary algorithm approaches for automated engineering design optimization. Here a marine propeller design with constraints on cavitation nuisance is the intended application. For this purpose, the particle swarm optimization (PSO) algorithm is adapted for multi-objective optimization and constraint handling for use in propeller design. Three PSO algorithms are developed and tested for the optimization of four commercial propeller designs for different ship types. The results are evaluated by interrogating the generation medians and the Pareto front development. The same propellers are also optimized utilizing the well established NSGA-II genetic algorithm to provide benchmark results. The authors' PSO algorithms deliver comparable results to NSGA-II, but converge earlier and enhance the solution in terms of constraints violation.

Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm.

PubMed

Yang, Zhang; Shufan, Ye; Li, Guo; Weifeng, Ding

2016-01-01

The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method.

Segmentation of MRI Brain Images with an Improved Harmony Searching Algorithm

PubMed Central

Yang, Zhang; Li, Guo; Weifeng, Ding

2016-01-01

The harmony searching (HS) algorithm is a kind of optimization search algorithm currently applied in many practical problems. The HS algorithm constantly revises variables in the harmony database and the probability of different values that can be used to complete iteration convergence to achieve the optimal effect. Accordingly, this study proposed a modified algorithm to improve the efficiency of the algorithm. First, a rough set algorithm was employed to improve the convergence and accuracy of the HS algorithm. Then, the optimal value was obtained using the improved HS algorithm. The optimal value of convergence was employed as the initial value of the fuzzy clustering algorithm for segmenting magnetic resonance imaging (MRI) brain images. Experimental results showed that the improved HS algorithm attained better convergence and more accurate results than those of the original HS algorithm. In our study, the MRI image segmentation effect of the improved algorithm was superior to that of the original fuzzy clustering method. PMID:27403428

Optimal design of low-density SNP arrays for genomic prediction: algorithm and applications

USDA-ARS?s Scientific Manuscript database

Low-density (LD) single nucleotide polymorphism (SNP) arrays provide a cost-effective solution for genomic prediction and selection, but algorithms and computational tools are needed for their optimal design. A multiple-objective, local optimization (MOLO) algorithm was developed for design of optim...

Selecting Random Distributed Elements for HIFU using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Zhou, Yufeng

2011-09-01

As an effective and noninvasive therapeutic modality for tumor treatment, high-intensity focused ultrasound (HIFU) has attracted attention from both physicians and patients. New generations of HIFU systems with the ability to electrically steer the HIFU focus using phased array transducers have been under development. The presence of side and grating lobes may cause undesired thermal accumulation at the interface of the coupling medium (i.e. water) and skin, or in the intervening tissue. Although sparse randomly distributed piston elements could reduce the amplitude of grating lobes, there are theoretically no grating lobes with the use of concave elements in the new phased array HIFU. A new HIFU transmission strategy is proposed in this study, firing a number of but not all elements for a certain period and then changing to another group for the next firing sequence. The advantages are: 1) the asymmetric position of active elements may reduce the side lobes, and 2) each element has some resting time during the entire HIFU ablation (up to several hours for some clinical applications) so that the decreasing efficiency of the transducer due to thermal accumulation is minimized. Genetic algorithm was used for selecting randomly distributed elements in a HIFU array. Amplitudes of the first side lobes at the focal plane were used as the fitness value in the optimization. Overall, it is suggested that the proposed new strategy could reduce the side lobe and the consequent side-effects, and the genetic algorithm is effective in selecting those randomly distributed elements in a HIFU array.

Skull removal in MR images using a modified artificial bee colony optimization algorithm.

PubMed

Taherdangkoo, Mohammad

2014-01-01

Removal of the skull from brain Magnetic Resonance (MR) images is an important preprocessing step required for other image analysis techniques such as brain tissue segmentation. In this paper, we propose a new algorithm based on the Artificial Bee Colony (ABC) optimization algorithm to remove the skull region from brain MR images. We modify the ABC algorithm using a different strategy for initializing the coordinates of scout bees and their direction of search. Moreover, we impose an additional constraint to the ABC algorithm to avoid the creation of discontinuous regions. We found that our algorithm successfully removed all bony skull from a sample of de-identified MR brain images acquired from different model scanners. The obtained results of the proposed algorithm compared with those of previously introduced well known optimization algorithms such as Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) demonstrate the superior results and computational performance of our algorithm, suggesting its potential for clinical applications.

Perivascular radiofrequency renal denervation lowers blood pressure and ameliorates cardiorenal fibrosis in spontaneously hypertensive rats

PubMed Central

Zhang, Yan; Su, Linan; Zhang, Yunrong; Wang, Qiang; Yang, Dachun; Li, De; Yang, Yongjian; Ma, Shuangtao

2017-01-01

Background Catheter-based renal denervation (RDN) is a promising approach to treat hypertension, but innervation patterns limit the response to endovascular RDN and the post-procedural renal artery narrowing or stenosis questions the endovascular ablation strategy. This study was performed to investigate the anti-hypertensive and target organ protective effects of perivascular RDN in spontaneously hypertensive rats (SHR). Methods SHR and normotensive Wistar-Kyoto (WKY) rats were divided into sham group (n = 10), radiofrequency ablation group (n = 20) in which rats received bilateral perivascular ablation with radiofrequency energy (2 watts), and chemical (10% phenol in 95% ethanol) ablation group (n = 12). The tail-cuff blood pressure was measured before the ablation and on day 14 and day 28 after the procedure. The plasma levels of creatinine, urea nitrogen, and catecholamines, urinary excretion of electrolytes and protein, and myocardial and glomerular fibrosis were analyzed and compared among the groups on day 28 after the procedure. Results We identified that 2-watt is the optimal radiofrequency power for perivascular RDN in rats. Perivascular radiofrequency and chemical ablation achieved roughly comparable blood pressure reduction in SHR but not in WKY on day 14 and day 28 following the procedure. Radiofrequency-mediated ablation substantially destroyed the renal nerves surrounding the renal arteries of both SHR and WKY without damaging the renal arteries and diminished the expression of tyrosine hydroxylase, the enzyme marker for postganglionic sympathetic nerves. Additionally, perivascular radiofrequency ablation also decreased the plasma catecholamines of SHR. Interestingly, both radiofrequency and chemical ablation decreased the myocardial and glomerular fibrosis of SHR, while neither increased the plasma creatinine and blood urea nitrogen nor affected the urinary excretion of electrolytes and protein when compared to sham group. Conclusions Radiofrequency-mediated perivascular RDN may become a feasible procedure against hypertension, and provide similar anti-hypertensive and target organ protective effects as does the chemical ablation. PMID:28453557

Fiber-delivered mid-infrared (6-7) laser ablation of retinal tissue under perfluorodecalin

NASA Astrophysics Data System (ADS)

Mackanos, Mark A.; Joos, Karen M.; Jansen, E. Duco

2003-07-01

The Er:YAG laser (l=2.94mm) is an effective tool in vitreo-retinal surgery. Pulsed mid-infrared (l=6.45 mm) radiation from the Free Electron Laser has been touted as a potentially superior cutting tool. To date, use of this laser has been limited to applications in an air environment. The goal of this study was: 1) determine feasibility of fiberoptic delivery of 6.45mm using silverhalide fibers (d=700mm); 2) use infrared transparent vitreous substitute (perfluorodecalin) to allow non-contact ablation of the retina at 6.45mm. Fiber damage threshold=7.8J/cm2 (0.54GW/cm2) while transmission loss=0.54dB/m, allowing supra-ablative radiant exposures to the target. FTIR measurements of perfluorodecalin at 6.45mm yielded ma=3mm-1. Pump-probe imaging of ablation of a tissue-phantom through perfluorodecalin showed feasibility of non-contact ablation at l=6.45mm. Ablation of the retinal membranes of enucleated pig eyes was carried out under perfluorodecalin (5 Hz, 1.3 J/cm2). Each eye was cut along its equator to expose the retina. Vitreous was replaced by perfluorodecalin and laser radiation was delivered to the retina via the silverhalide fiber. The eye was rotated (at 2 rpm) using a stepper motor (0.9o/step) to create an ablation circle around the central axis of the retina (50% spot-to-spot overlap). Histological analysis of ablation yield and collateral damage will be presented. We have shown that using l=6.45mm delivered via silver halide fibers through perfluorodecalin allowed non-contact laser ablation. Remote structures are shielded, as the radiant exposure falls below the ablation threshold owing non-negligible absorption of perfluorodecalin at 6.45mm. This may optimize efficacy and safety of laser-based vitreoretinal surgery.

Perivascular radiofrequency renal denervation lowers blood pressure and ameliorates cardiorenal fibrosis in spontaneously hypertensive rats.

PubMed

Wei, Shujie; Li, Dan; Zhang, Yan; Su, Linan; Zhang, Yunrong; Wang, Qiang; Yang, Dachun; Li, De; Yang, Yongjian; Ma, Shuangtao

2017-01-01

Catheter-based renal denervation (RDN) is a promising approach to treat hypertension, but innervation patterns limit the response to endovascular RDN and the post-procedural renal artery narrowing or stenosis questions the endovascular ablation strategy. This study was performed to investigate the anti-hypertensive and target organ protective effects of perivascular RDN in spontaneously hypertensive rats (SHR). SHR and normotensive Wistar-Kyoto (WKY) rats were divided into sham group (n = 10), radiofrequency ablation group (n = 20) in which rats received bilateral perivascular ablation with radiofrequency energy (2 watts), and chemical (10% phenol in 95% ethanol) ablation group (n = 12). The tail-cuff blood pressure was measured before the ablation and on day 14 and day 28 after the procedure. The plasma levels of creatinine, urea nitrogen, and catecholamines, urinary excretion of electrolytes and protein, and myocardial and glomerular fibrosis were analyzed and compared among the groups on day 28 after the procedure. We identified that 2-watt is the optimal radiofrequency power for perivascular RDN in rats. Perivascular radiofrequency and chemical ablation achieved roughly comparable blood pressure reduction in SHR but not in WKY on day 14 and day 28 following the procedure. Radiofrequency-mediated ablation substantially destroyed the renal nerves surrounding the renal arteries of both SHR and WKY without damaging the renal arteries and diminished the expression of tyrosine hydroxylase, the enzyme marker for postganglionic sympathetic nerves. Additionally, perivascular radiofrequency ablation also decreased the plasma catecholamines of SHR. Interestingly, both radiofrequency and chemical ablation decreased the myocardial and glomerular fibrosis of SHR, while neither increased the plasma creatinine and blood urea nitrogen nor affected the urinary excretion of electrolytes and protein when compared to sham group. Radiofrequency-mediated perivascular RDN may become a feasible procedure against hypertension, and provide similar anti-hypertensive and target organ protective effects as does the chemical ablation.

Hybrid algorithms for fuzzy reverse supply chain network design.

PubMed

Che, Z H; Chiang, Tzu-An; Kuo, Y C; Cui, Zhihua

2014-01-01

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods.

Hybrid Algorithms for Fuzzy Reverse Supply Chain Network Design

PubMed Central

Che, Z. H.; Chiang, Tzu-An; Kuo, Y. C.

2014-01-01

In consideration of capacity constraints, fuzzy defect ratio, and fuzzy transport loss ratio, this paper attempted to establish an optimized decision model for production planning and distribution of a multiphase, multiproduct reverse supply chain, which addresses defects returned to original manufacturers, and in addition, develops hybrid algorithms such as Particle Swarm Optimization-Genetic Algorithm (PSO-GA), Genetic Algorithm-Simulated Annealing (GA-SA), and Particle Swarm Optimization-Simulated Annealing (PSO-SA) for solving the optimized model. During a case study of a multi-phase, multi-product reverse supply chain network, this paper explained the suitability of the optimized decision model and the applicability of the algorithms. Finally, the hybrid algorithms showed excellent solving capability when compared with original GA and PSO methods. PMID:24892057

Hybrid cryptosystem RSA - CRT optimization and VMPC

NASA Astrophysics Data System (ADS)

Rahmadani, R.; Mawengkang, H.; Sutarman

2018-03-01

Hybrid cryptosystem combines symmetric algorithms and asymmetric algorithms. This combination utilizes speeds on encryption/decryption processes of symmetric algorithms and asymmetric algorithms to secure symmetric keys. In this paper we propose hybrid cryptosystem that combine symmetric algorithms VMPC and asymmetric algorithms RSA - CRT optimization. RSA - CRT optimization speeds up the decryption process by obtaining plaintext with dp and p key only, so there is no need to perform CRT processes. The VMPC algorithm is more efficient in software implementation and reduces known weaknesses in RC4 key generation. The results show hybrid cryptosystem RSA - CRT optimization and VMPC is faster than hybrid cryptosystem RSA - VMPC and hybrid cryptosystem RSA - CRT - VMPC. Keyword : Cryptography, RSA, RSA - CRT, VMPC, Hybrid Cryptosystem.

Evaluation of hybrid inverse planning and optimization (HIPO) algorithm for optimization in real-time, high-dose-rate (HDR) brachytherapy for prostate.

PubMed

Pokharel, Shyam; Rana, Suresh; Blikenstaff, Joseph; Sadeghi, Amir; Prestidge, Bradley

2013-07-08

The purpose of this study is to investigate the effectiveness of the HIPO planning and optimization algorithm for real-time prostate HDR brachytherapy. This study consists of 20 patients who underwent ultrasound-based real-time HDR brachytherapy of the prostate using the treatment planning system called Oncentra Prostate (SWIFT version 3.0). The treatment plans for all patients were optimized using inverse dose-volume histogram-based optimization followed by graphical optimization (GRO) in real time. The GRO is manual manipulation of isodose lines slice by slice. The quality of the plan heavily depends on planner expertise and experience. The data for all patients were retrieved later, and treatment plans were created and optimized using HIPO algorithm with the same set of dose constraints, number of catheters, and set of contours as in the real-time optimization algorithm. The HIPO algorithm is a hybrid because it combines both stochastic and deterministic algorithms. The stochastic algorithm, called simulated annealing, searches the optimal catheter distributions for a given set of dose objectives. The deterministic algorithm, called dose-volume histogram-based optimization (DVHO), optimizes three-dimensional dose distribution quickly by moving straight downhill once it is in the advantageous region of the search space given by the stochastic algorithm. The PTV receiving 100% of the prescription dose (V100) was 97.56% and 95.38% with GRO and HIPO, respectively. The mean dose (D(mean)) and minimum dose to 10% volume (D10) for the urethra, rectum, and bladder were all statistically lower with HIPO compared to GRO using the student pair t-test at 5% significance level. HIPO can provide treatment plans with comparable target coverage to that of GRO with a reduction in dose to the critical structures.

Improved hybrid optimization algorithm for 3D protein structure prediction.

PubMed

Zhou, Changjun; Hou, Caixia; Wei, Xiaopeng; Zhang, Qiang

2014-07-01

A new improved hybrid optimization algorithm - PGATS algorithm, which is based on toy off-lattice model, is presented for dealing with three-dimensional protein structure prediction problems. The algorithm combines the particle swarm optimization (PSO), genetic algorithm (GA), and tabu search (TS) algorithms. Otherwise, we also take some different improved strategies. The factor of stochastic disturbance is joined in the particle swarm optimization to improve the search ability; the operations of crossover and mutation that are in the genetic algorithm are changed to a kind of random liner method; at last tabu search algorithm is improved by appending a mutation operator. Through the combination of a variety of strategies and algorithms, the protein structure prediction (PSP) in a 3D off-lattice model is achieved. The PSP problem is an NP-hard problem, but the problem can be attributed to a global optimization problem of multi-extremum and multi-parameters. This is the theoretical principle of the hybrid optimization algorithm that is proposed in this paper. The algorithm combines local search and global search, which overcomes the shortcoming of a single algorithm, giving full play to the advantage of each algorithm. In the current universal standard sequences, Fibonacci sequences and real protein sequences are certified. Experiments show that the proposed new method outperforms single algorithms on the accuracy of calculating the protein sequence energy value, which is proved to be an effective way to predict the structure of proteins.

Optimal Golomb Ruler Sequences Generation for Optical WDM Systems: A Novel Parallel Hybrid Multi-objective Bat Algorithm

NASA Astrophysics Data System (ADS)

Bansal, Shonak; Singh, Arun Kumar; Gupta, Neena

2017-02-01

In real-life, multi-objective engineering design problems are very tough and time consuming optimization problems due to their high degree of nonlinearities, complexities and inhomogeneity. Nature-inspired based multi-objective optimization algorithms are now becoming popular for solving multi-objective engineering design problems. This paper proposes original multi-objective Bat algorithm (MOBA) and its extended form, namely, novel parallel hybrid multi-objective Bat algorithm (PHMOBA) to generate shortest length Golomb ruler called optimal Golomb ruler (OGR) sequences at a reasonable computation time. The OGRs found their application in optical wavelength division multiplexing (WDM) systems as channel-allocation algorithm to reduce the four-wave mixing (FWM) crosstalk. The performances of both the proposed algorithms to generate OGRs as optical WDM channel-allocation is compared with other existing classical computing and nature-inspired algorithms, including extended quadratic congruence (EQC), search algorithm (SA), genetic algorithms (GAs), biogeography based optimization (BBO) and big bang-big crunch (BB-BC) optimization algorithms. Simulations conclude that the proposed parallel hybrid multi-objective Bat algorithm works efficiently as compared to original multi-objective Bat algorithm and other existing algorithms to generate OGRs for optical WDM systems. The algorithm PHMOBA to generate OGRs, has higher convergence and success rate than original MOBA. The efficiency improvement of proposed PHMOBA to generate OGRs up to 20-marks, in terms of ruler length and total optical channel bandwidth (TBW) is 100 %, whereas for original MOBA is 85 %. Finally the implications for further research are also discussed.

Multiobjective optimization of temporal processes.

PubMed

Song, Zhe; Kusiak, Andrew

2010-06-01

This paper presents a dynamic predictive-optimization framework of a nonlinear temporal process. Data-mining (DM) and evolutionary strategy algorithms are integrated in the framework for solving the optimization model. DM algorithms learn dynamic equations from the process data. An evolutionary strategy algorithm is then applied to solve the optimization problem guided by the knowledge extracted by the DM algorithm. The concept presented in this paper is illustrated with the data from a power plant, where the goal is to maximize the boiler efficiency and minimize the limestone consumption. This multiobjective optimization problem can be either transformed into a single-objective optimization problem through preference aggregation approaches or into a Pareto-optimal optimization problem. The computational results have shown the effectiveness of the proposed optimization framework.

Femtosecond laser ablation of gold interdigitated electrodes for electronic tongues

NASA Astrophysics Data System (ADS)

Manzoli, Alexandra; de Almeida, Gustavo F. B.; Filho, José A.; Mattoso, Luiz H. C.; Riul, Antonio; Mendonca, Cleber R.; Correa, Daniel S.

2015-06-01

Electronic tongue (e-tongue) sensors based on impedance spectroscopy have emerged as a potential technology to evaluate the quality and chemical composition of food, beverages, and pharmaceuticals. E-tongues usually employ transducers based on metal interdigitated electrodes (IDEs) coated with a thin layer of an active material, which is capable of interacting chemically with several types of analytes. IDEs are usually produced by photolithographic methods, which are time-consuming and costly, therefore, new fabrication technologies are required to make it more affordable. Here, we employed femtosecond laser ablation with pulse duration of 50 fs to microfabricate gold IDEs having finger width from 2.3 μm up to 3.2 μm. The parameters used in the laser ablation technique, such as light intensity, scan speed and beam spot size have been optimized to achieve uniform IDEs, which were characterized by optical and scanning electron microscopy. The electrical properties of gold IDEs fabricated by laser ablation were evaluated by impedance spectroscopy, and compared to those produced by conventional photolithography. The results show that femtosecond laser ablation is a promising alternative to conventional photolithography for fabricating metal IDEs for e-tongue systems.

Automated geometric optimization for robotic HIFU treatment of liver tumors.

PubMed

Williamson, Tom; Everitt, Scott; Chauhan, Sunita

2018-05-01

High intensity focused ultrasound (HIFU) represents a non-invasive method for the destruction of cancerous tissue within the body. Heating of targeted tissue by focused ultrasound transducers results in the creation of ellipsoidal lesions at the target site, the locations of which can have a significant impact on treatment outcomes. Towards this end, this work describes a method for the optimization of lesion positions within arbitrary tumors, with specific anatomical constraints. A force-based optimization framework was extended to the case of arbitrary tumor position and constrained orientation. Analysis of the approximate reachable treatment volume for the specific case of treatment of liver tumors was performed based on four transducer configurations and constraint conditions derived. Evaluation was completed utilizing simplified spherical and ellipsoidal tumor models and randomly generated tumor volumes. The total volume treated, lesion overlap and healthy tissue ablated was evaluated. Two evaluation scenarios were defined and optimized treatment plans assessed. The optimization framework resulted in improvements of up to 10% in tumor volume treated, and reductions of up to 20% in healthy tissue ablated as compared to the standard lesion rastering approach. Generation of optimized plans proved feasible for both sub- and intercostally located tumors. This work describes an optimized method for the planning of lesion positions during HIFU treatment of liver tumors. The approach allows the determination of optimal lesion locations and orientations, and can be applied to arbitrary tumor shapes and sizes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter.

PubMed

Fu, Xingang; Li, Shuhui; Fairbank, Michael; Wunsch, Donald C; Alonso, Eduardo

2015-09-01

This paper investigates how to train a recurrent neural network (RNN) using the Levenberg-Marquardt (LM) algorithm as well as how to implement optimal control of a grid-connected converter (GCC) using an RNN. To successfully and efficiently train an RNN using the LM algorithm, a new forward accumulation through time (FATT) algorithm is proposed to calculate the Jacobian matrix required by the LM algorithm. This paper explores how to incorporate FATT into the LM algorithm. The results show that the combination of the LM and FATT algorithms trains RNNs better than the conventional backpropagation through time algorithm. This paper presents an analytical study on the optimal control of GCCs, including theoretically ideal optimal and suboptimal controllers. To overcome the inapplicability of the optimal GCC controller under practical conditions, a new RNN controller with an improved input structure is proposed to approximate the ideal optimal controller. The performance of an ideal optimal controller and a well-trained RNN controller was compared in close to real-life power converter switching environments, demonstrating that the proposed RNN controller can achieve close to ideal optimal control performance even under low sampling rate conditions. The excellent performance of the proposed RNN controller under challenging and distorted system conditions further indicates the feasibility of using an RNN to approximate optimal control in practical applications.

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT

PubMed Central

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of “premature convergence,” that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment. PMID:29181020

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT.

PubMed

Nie, Xiaohua; Wang, Wei; Nie, Haoyao

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of "premature convergence," that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment.

Ablative thermal management structural material on the hypersonic vehicles

NASA Astrophysics Data System (ADS)

Shortland, H.; Tsai, C.

A hypersonic vehicle is designed to fly at high Mach number in the earth's atmosphere that will result in higher aerodynamic heating loads on specific areas of the vehicle. A thermal protection system is required for these areas that may exceed the operating temperature limit of structural materials. This paper delineates the application of ablative material as the passive type of thermal protection system for the nose or wing leading edges. A simplified quasi-steady-state one-dimensional computer model was developed to evaluate the performance and thermal design of a leading edge. The detailed description of the governing mathematical equations and results are presented. This model provides a quantitative information to support the design estimate, performance optimization, and assess preliminary feasibility of using ablation as a design approach.

Core/shell structured Zn/ZnO nanoparticles synthesized by gaseous laser ablation with enhanced photocatalysis efficiency

NASA Astrophysics Data System (ADS)

Song, Lu; Wang, Yafei; Ma, Jing; Zhang, Qinghua; Shen, Zhijian

2018-06-01

Zinc oxide (ZnO) is a competitive candidate in semiconductor photocatalysts, only if the efficiency could be fully optimized especially by tailored nanostructures. Here we report a kind of core/shell structured Zn/ZnO nanoparticles with enhanced photocatalysis efficiency, which were synthesized by a highly-productive gaseous laser ablation method. The nanodroplets generated by laser ablation would be reduced to zinc in the protective atmosphere, and further be oxidized at surface to form a specific core/shell structured Zn/ZnO nanoparticles within seconds. Thanks to the formation of this Zn-ZnO Schottky junction, the photocatalysis degradation efficiency of such core/shell Zn/ZnO nanostructure is significantly improved owing to the enhanced visible light absorption and inhibited carrier recombination by introducing the metallic zinc.

Computer simulation of photorefractive keratectomy for the correction of myopia and hyperopia

NASA Astrophysics Data System (ADS)

Pinault, Pascal; 'Huillier, J. P.

1996-01-01

Photorefractive keratectomy (PRK) performed by means of the 193 nm excimer laser has stimulated considerable interest in the ophthalmic community because this new procedure has the potential to correct myopia, hyperopia, and astigmatism. The use of a laser beam to remove a controlled amount of tissue from the cornea implies that both the energy density of the laser beam and the target removed rate are accurately known. In addition, the required tissue ablation profile to achieve refractive correction must be predicted by optical calculations. This paper investigates: (1) Optical computations based on raytracing model to determine what anterior profile of cornea is needed postoperatively for ametropia. (2) Maximal depth of the removed corneal tissue against the ablation zone treated. And (3) the thickness of ablated corneal lenticule at any distance from the optical axis. Relationships between these data are well fitted by polynomial regressive curves in order to be useful as an algorithm in the computer-controlled delivery of the ArF laser beam.

Excimer laser correction of hyperopia, hyperopic and mixed astigmatism: past, present, and future.

PubMed

Lukenda, Adrian; Martinović, Zeljka Karaman; Kalauz, Miro

2012-06-01

The broad acceptance of "spot scanning" or "flying spot" excimer lasers in the last decade has enabled the domination of corneal ablative laser surgery over other refractive surgical procedures for the correction of hyperopia, hyperopic and mixed astigmatism. This review outlines the most important reasons why the ablative laser correction of hyperopia, hyperopic and mixed astigmatism for many years lagged behind that of myopia. Most of today's scanning laser systems, used in the LASIK and PRK procedures, can safely and effectively perform low, moderate and high hyperopic and hyperopic astigmatic corrections. The introduction of these laser platforms has also significantly improved the long term refractive stability of hyperopic treatments. In the future, further improvements in femtosecond and nanosecond technology, eye-tracker systems, and the development of new customized algorithms, such as the ray-tracing method, could additionally increase the upper limit for the safe and predictable corneal ablative laser correction ofhyperopia, hyperopic and mixed astigmatism.

New Dandelion Algorithm Optimizes Extreme Learning Machine for Biomedical Classification Problems

PubMed Central

Li, Xiguang; Zhao, Liang; Gong, Changqing; Liu, Xiaojing

2017-01-01

Inspired by the behavior of dandelion sowing, a new novel swarm intelligence algorithm, namely, dandelion algorithm (DA), is proposed for global optimization of complex functions in this paper. In DA, the dandelion population will be divided into two subpopulations, and different subpopulations will undergo different sowing behaviors. Moreover, another sowing method is designed to jump out of local optimum. In order to demonstrate the validation of DA, we compare the proposed algorithm with other existing algorithms, including bat algorithm, particle swarm optimization, and enhanced fireworks algorithm. Simulations show that the proposed algorithm seems much superior to other algorithms. At the same time, the proposed algorithm can be applied to optimize extreme learning machine (ELM) for biomedical classification problems, and the effect is considerable. At last, we use different fusion methods to form different fusion classifiers, and the fusion classifiers can achieve higher accuracy and better stability to some extent. PMID:29085425

Improved mine blast algorithm for optimal cost design of water distribution systems

NASA Astrophysics Data System (ADS)

Sadollah, Ali; Guen Yoo, Do; Kim, Joong Hoon

2015-12-01

The design of water distribution systems is a large class of combinatorial, nonlinear optimization problems with complex constraints such as conservation of mass and energy equations. Since feasible solutions are often extremely complex, traditional optimization techniques are insufficient. Recently, metaheuristic algorithms have been applied to this class of problems because they are highly efficient. In this article, a recently developed optimizer called the mine blast algorithm (MBA) is considered. The MBA is improved and coupled with the hydraulic simulator EPANET to find the optimal cost design for water distribution systems. The performance of the improved mine blast algorithm (IMBA) is demonstrated using the well-known Hanoi, New York tunnels and Balerma benchmark networks. Optimization results obtained using IMBA are compared to those using MBA and other optimizers in terms of their minimum construction costs and convergence rates. For the complex Balerma network, IMBA offers the cheapest network design compared to other optimization algorithms.

Linear antenna array optimization using flower pollination algorithm.

PubMed

Saxena, Prerna; Kothari, Ashwin

2016-01-01

Flower pollination algorithm (FPA) is a new nature-inspired evolutionary algorithm used to solve multi-objective optimization problems. The aim of this paper is to introduce FPA to the electromagnetics and antenna community for the optimization of linear antenna arrays. FPA is applied for the first time to linear array so as to obtain optimized antenna positions in order to achieve an array pattern with minimum side lobe level along with placement of deep nulls in desired directions. Various design examples are presented that illustrate the use of FPA for linear antenna array optimization, and subsequently the results are validated by benchmarking along with results obtained using other state-of-the-art, nature-inspired evolutionary algorithms such as particle swarm optimization, ant colony optimization and cat swarm optimization. The results suggest that in most cases, FPA outperforms the other evolutionary algorithms and at times it yields a similar performance.

A new chaotic multi-verse optimization algorithm for solving engineering optimization problems

NASA Astrophysics Data System (ADS)

Sayed, Gehad Ismail; Darwish, Ashraf; Hassanien, Aboul Ella

2018-03-01

Multi-verse optimization algorithm (MVO) is one of the recent meta-heuristic optimization algorithms. The main inspiration of this algorithm came from multi-verse theory in physics. However, MVO like most optimization algorithms suffers from low convergence rate and entrapment in local optima. In this paper, a new chaotic multi-verse optimization algorithm (CMVO) is proposed to overcome these problems. The proposed CMVO is applied on 13 benchmark functions and 7 well-known design problems in the engineering and mechanical field; namely, three-bar trust, speed reduce design, pressure vessel problem, spring design, welded beam, rolling element-bearing and multiple disc clutch brake. In the current study, a modified feasible-based mechanism is employed to handle constraints. In this mechanism, four rules were used to handle the specific constraint problem through maintaining a balance between feasible and infeasible solutions. Moreover, 10 well-known chaotic maps are used to improve the performance of MVO. The experimental results showed that CMVO outperforms other meta-heuristic optimization algorithms on most of the optimization problems. Also, the results reveal that sine chaotic map is the most appropriate map to significantly boost MVO's performance.

Speed and convergence properties of gradient algorithms for optimization of IMRT.

PubMed

Zhang, Xiaodong; Liu, Helen; Wang, Xiaochun; Dong, Lei; Wu, Qiuwen; Mohan, Radhe

2004-05-01

Gradient algorithms are the most commonly employed search methods in the routine optimization of IMRT plans. It is well known that local minima can exist for dose-volume-based and biology-based objective functions. The purpose of this paper is to compare the relative speed of different gradient algorithms, to investigate the strategies for accelerating the optimization process, to assess the validity of these strategies, and to study the convergence properties of these algorithms for dose-volume and biological objective functions. With these aims in mind, we implemented Newton's, conjugate gradient (CG), and the steepest decent (SD) algorithms for dose-volume- and EUD-based objective functions. Our implementation of Newton's algorithm approximates the second derivative matrix (Hessian) by its diagonal. The standard SD algorithm and the CG algorithm with "line minimization" were also implemented. In addition, we investigated the use of a variation of the CG algorithm, called the "scaled conjugate gradient" (SCG) algorithm. To accelerate the optimization process, we investigated the validity of the use of a "hybrid optimization" strategy, in which approximations to calculated dose distributions are used during most of the iterations. Published studies have indicated that getting trapped in local minima is not a significant problem. To investigate this issue further, we first obtained, by trial and error, and starting with uniform intensity distributions, the parameters of the dose-volume- or EUD-based objective functions which produced IMRT plans that satisfied the clinical requirements. Using the resulting optimized intensity distributions as the initial guess, we investigated the possibility of getting trapped in a local minimum. For most of the results presented, we used a lung cancer case. To illustrate the generality of our methods, the results for a prostate case are also presented. For both dose-volume and EUD based objective functions, Newton's method far outperforms other algorithms in terms of speed. The SCG algorithm, which avoids expensive "line minimization," can speed up the standard CG algorithm by at least a factor of 2. For the same initial conditions, all algorithms converge essentially to the same plan. However, we demonstrate that for any of the algorithms studied, starting with previously optimized intensity distributions as the initial guess but for different objective function parameters, the solution frequently gets trapped in local minima. We found that the initial intensity distribution obtained from IMRT optimization utilizing objective function parameters, which favor a specific anatomic structure, would lead to a local minimum corresponding to that structure. Our results indicate that from among the gradient algorithms tested, Newton's method appears to be the fastest by far. Different gradient algorithms have the same convergence properties for dose-volume- and EUD-based objective functions. The hybrid dose calculation strategy is valid and can significantly accelerate the optimization process. The degree of acceleration achieved depends on the type of optimization problem being addressed (e.g., IMRT optimization, intensity modulated beam configuration optimization, or objective function parameter optimization). Under special conditions, gradient algorithms will get trapped in local minima, and reoptimization, starting with the results of previous optimization, will lead to solutions that are generally not significantly different from the local minimum.

Role of contact force in ischemic scar-related ventricular tachycardia ablation; optimal force required and impact of left ventricular access route.

PubMed

Elsokkari, Ihab; Sapp, John L; Doucette, Steve; Parkash, Ratika; Gray, Christopher J; Gardner, Martin J; Macintyre, Ciorsti; AbdelWahab, Amir M

2018-06-26

Contact force-sensing technology has become a widely used addition to catheter ablation procedures. Neither the optimal contact force required to achieve adequate lesion formation in the ventricle, nor the impact of left ventricular access route on contact force has been fully clarified. Consecutive patients (n = 24) with ischemic cardiomyopathy who underwent ablation for scar-related ventricular tachycardia were included in the study. All ablations (n = 25) were performed using irrigated contact force-sensing catheters (Smart Touch, Biosense Webster). Effective lesion formation was defined as electrical unexcitability post ablation at sites which were electrically excitable prior to ablation (unipolar pacing at 10 mA, 2 ms pulse width). We explored the contact force which achieved effective lesion formation and the impact of left ventricular access route (retrograde aortic or transseptal) on the contact force achieved in various segments of the left ventricle. Scar zone was defined as bipolar signal amplitude < 0.5 mV. Among 427 ablation points, effective lesion formation was achieved at 201 points (47.1%). Contact force did not predict effective lesion formation in the overall group. However, within the scar zone, mean contact force ≥ 10 g was significantly associated with effective lesion formation [OR 3.21 (1.43, 7.19) P = 0.005]. In the 12-segment model of the left ventricle, the retrograde approach was associated with higher median contact force in the apical anterior segment (31 vs 19 g; P = 0.045) while transseptal approach had higher median force in the basal inferior segment (25 vs 15 g; P = 0.021). In the 4-segment model, the retrograde approach had higher force in the anterior wall (28 vs 16 g; P = 0.004) while the transseptal approach had higher force in the lateral wall (21 vs 18 g; P = 0.032). There was a trend towards higher force in the inferior wall with the transseptal approach, but this was not statistically significant (20 vs 15 g; P = 0.063). In patients with ischemic cardiomyopathy, a mean contact force of 10 g or more within the scar zone had the best correlation with electrical unexcitability post ablation in our study. The retrograde aortic approach was associated with better contact force over the anterior wall while use of a transseptal approach had better contact force over the lateral wall.

A Library of Optimization Algorithms for Organizational Design

DTIC Science & Technology

2005-01-01

N00014-98-1-0465 and #N00014-00-1-0101 A Library of Optimization Algorithms for Organizational Design Georgiy M. Levchuk Yuri N. Levchuk Jie Luo...E-mail: Krishna@engr.uconn.edu Abstract This paper presents a library of algorithms to solve a broad range of optimization problems arising in the...normative design of organizations to execute a specific mission. The use of specific optimization algorithms for different phases of the design process

Genetic Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.

2004-01-01

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved.

Designing multifocal corneal models to correct presbyopia by laser ablation

NASA Astrophysics Data System (ADS)

Alarcón, Aixa; Anera, Rosario G.; Del Barco, Luis Jiménez; Jiménez, José R.

2012-01-01

Two multifocal corneal models and an aspheric model designed to correct presbyopia by corneal photoablation were evaluated. The design of each model was optimized to achieve the best visual quality possible for both near and distance vision. In addition, we evaluated the effect of myosis and pupil decentration on visual quality. The corrected model with the central zone for near vision provides better results since it requires less ablated corneal surface area, permits higher addition values, presents stabler visual quality with pupil-size variations and lower high-order aberrations.

Toward realistic radiofrequency ablation of hepatic tumors 3D simulation and planning

NASA Astrophysics Data System (ADS)

Villard, Caroline; Soler, Luc; Gangi, Afshin; Mutter, Didier; Marescaux, Jacques

2004-05-01

Radiofrequency ablation (RFA) has become an increasingly used technique in the treatment of patients with unresectable hepatic tumors. Evaluation of vascular architecture, post-RFA tissue necrosis prediction, and the choice of a suitable needle placement strategy using conventional radiological techniques remain difficult. In an attempt to enhance the safety of RFA, a 3D simulator and treatment planning tool, that simulates the necrosis of the treated area, and proposes an optimal placement for the needle, has been developed. From enhanced spiral CT scans with 2 mm cuts, 3D reconstructions of patients with liver metastases are automatically generated. Virtual needles can be added to the 3D scene, together with their corresponding zones of necrosis that are displayed as a meshed spheroids representing the 60° C isosurface. The simulator takes into account the cooling effect of local vessels greater than 3mm in diameter, making necrosis shapes more realistic. Using a voxel-based algorithm, RFA spheroids are deformed following the shape of the vessels, extended by an additional cooled area. This operation is performed in real-time, allowing updates while needle is adjusted. This allows to observe whether the considered needle placement strategy would burn the whole cancerous zone or not. Planned needle positioning can also be automatically generated by the software to produce complete destruction of the tumor with a 1 cm margin, with maximum respect of the healthy liver and of all major extrahepatic and intrahepatic structures to avoid. If he wishes, the radiologist can select on the skin an insertion window for the needle, focusing the research of the trajectory.

Comparison of clinical outcomes in PRK with a standard and aspherical optimized profile: a full case analysis of 100 eyes with 1-year follow-up.

PubMed

Dausch, Dieter; Dausch, Burglinde; Wottke, Matthias; Sluyterman van Langeweyde, Georg

2014-01-01

One hundred eyes from 55 adult patients with myopia were retrospectively studied to determine the comparative safety, efficacy, and predictability of aberration smart ablation (ASA) and a new advanced ablation algorithm (Triple-A) using the MEL(®) 80 excimer laser. Fifty myopic eyes with a manifest refraction spherical equivalent (MRSE) between -1.0 diopters (D) and -9.75 D were consecutively treated with photorefractive keratec-tomy ASA, and 50 myopic eyes with an MRSE between -1.38 D and -11.0 D with photorefractive keratectomy Triple-A. Uncorrected distance visual acuity, MRSE, the absolute value of the cylinder, corrected distance visual acuity, and postoperative complications at 1 month, 3 months, 6 months, and 12 months (1 year) were descriptively analyzed and compared at 1 year. After 12 months, the MRSE variance was statistically significantly better in patients triaged to receive Triple-A compared with patients receiving ASA (ASA, ±0.7 D; Triple-A, ±0.15 D; P<0.001). Furthermore, no patient in the Triple-A group had any cylinder postoperatively. Patients in the Triple-A treatment arm achieved a superior result. No statistically significant difference in the two treatment arms was noted for the analysis of the mean MRSE at 12 months (P=0.78). Triple-A was more effective than standard aspherical surgical intervention in a number of treatment outcome parameters (eg, MRSE, astigmatism, efficacy index). The two surgical procedures were equivalent in terms of safety.

A methodology for constraining power in finite element modeling of radiofrequency ablation.

PubMed

Jiang, Yansheng; Possebon, Ricardo; Mulier, Stefaan; Wang, Chong; Chen, Feng; Feng, Yuanbo; Xia, Qian; Liu, Yewei; Yin, Ting; Oyen, Raymond; Ni, Yicheng

2017-07-01

Radiofrequency ablation (RFA) is a minimally invasive thermal therapy for the treatment of cancer, hyperopia, and cardiac tachyarrhythmia. In RFA, the power delivered to the tissue is a key parameter. The objective of this study was to establish a methodology for the finite element modeling of RFA with constant power. Because of changes in the electric conductivity of tissue with temperature, a nonconventional boundary value problem arises in the mathematic modeling of RFA: neither the voltage (Dirichlet condition) nor the current (Neumann condition), but the power, that is, the product of voltage and current was prescribed on part of boundary. We solved the problem using Lagrange multiplier: the product of the voltage and current on the electrode surface is constrained to be equal to the Joule heating. We theoretically proved the equality between the product of the voltage and current on the surface of the electrode and the Joule heating in the domain. We also proved the well-posedness of the problem of solving the Laplace equation for the electric potential under a constant power constraint prescribed on the electrode surface. The Pennes bioheat transfer equation and the Laplace equation for electric potential augmented with the constraint of constant power were solved simultaneously using the Newton-Raphson algorithm. Three problems for validation were solved. Numerical results were compared either with an analytical solution deduced in this study or with results obtained by ANSYS or experiments. This work provides the finite element modeling of constant power RFA with a firm mathematical basis and opens pathway for achieving the optimal RFA power. Copyright © 2016 John Wiley & Sons, Ltd.

Radiofrequency catheter ablation of atrial fibrillation: Electrical modification suggesting transmurality is faster achieved with remote magnetic catheter in comparison with contact force use.

PubMed

Bun, Sok-Sithikun; Ayari, Anis; Latcu, Decebal Gabriel; Errahmouni, Abdelkarim; Saoudi, Nadir

2017-07-01

Remote magnetic navigation (RMN) and contact force (CF) sensing catheters are available technologies for radiofrequency (RF) catheter ablation of atrial fibrillation (AF). Our purpose was to compare time to electrogram (EGM) modification suggesting transmural lesions between RMN and CF-guided AF ablation. A total of 1,008 RF applications were analyzed in 21 patients undergoing RMN (n = 11) or CF-guided ablation (n = 10) for paroxysmal AF. All procedures were performed in sinus rhythm during general anesthesia. Time to EGM modification was measured until transmurality criteria were fulfilled: (1) complete disappearance of R if initial QR morphology; (2) diminution > 75% of R if initial QRS morphology; (3) complete disappearance of R' of initial RSR' morphology. Impedance drop as well as force time integral (FTI) were also assessed for each application. Mean CF at the beginning of each RF application in the CF group was 11 ± 2 g and mean FTI per application was 488 ± 163 gs. Time to EGM modification was significantly shorter in the RMN group (4.52 ± 0.1 seconds vs. 5.6 ± 0.09 seconds; P < 0.00001). There was no significant difference between other procedural parameters. Remote magnetic AF ablation is associated with faster EGM modification suggesting transmurality than optimized CF and FTI-guided catheter ablation. © 2017 Wiley Periodicals, Inc.

Similarities and differences in ablative and non-ablative iron oxide nanoparticle hyperthermia cancer treatment

NASA Astrophysics Data System (ADS)

Petryk, Alicia A.; Misra, Adwiteeya; Kastner, Elliot J.; Mazur, Courtney M.; Petryk, James D.; Hoopes, P. Jack

2015-03-01

The use of hyperthermia to treat cancer is well studied and has utilized numerous delivery techniques, including microwaves, radio frequency, focused ultrasound, induction heating, infrared radiation, warmed perfusion liquids (combined with chemotherapy), and recently, metallic nanoparticles (NP) activated by near infrared radiation (NIR) and alternating magnetic field (AMF) based platforms. It has been demonstrated by many research groups that ablative temperatures and cytotoxicity can be produced with locally NP-based hyperthermia. Such ablative NP techniques have demonstrated the potential for success. Much attention has also been given to the fact that NP may be administered systemically, resulting in a broader cancer therapy approach, a lower level of tumor NP content and a different type of NP cancer therapy (most likely in the adjuvant setting). To use NP based hyperthermia successfully as a cancer treatment, the technique and its goal must be understood and utilized in the appropriate clinical context. The parameters include, but are not limited to, NP access to the tumor (large vs. small quantity), cancer cell-specific targeting, drug carrying capacity, potential as an ionizing radiation sensitizer, and the material properties (magnetic characteristics, size and charge). In addition to their potential for cytotoxicity, the material properties of the NP must also be optimized for imaging, detection and direction. In this paper we will discuss the differences between, and potential applications for, ablative and non-ablative magnetic nanoparticle hyperthermia.

Numerical Response Surfaces of Volume of Ablation and Retropulsion Amplitude by Settings of Ho:YAG Laser Lithotripter

PubMed Central

Rutherford, Jonathan; Solomon, Metasebya; Cheng, Brian; Xuan, Jason R.; Gong, Jason; Yu, Honggang; Xia, Michael L. D.; Yang, Xirong; Hasenberg, Thomas; Curran, Sean

2018-01-01

Objectives Although laser lithotripsy is now the preferred treatment option for urolithiasis due to shorter operation time and a better stone-free rate, the optimal laser settings for URS (ureteroscopic lithotripsy) for less operation time remain unclear. The aim of this study was to look for quantitative responses of calculus ablation and retropulsion by performing operator-independent experiments to determine the best fit versus the pulse energy, pulse width, and the number of pulses. Methods A lab-built Ho:YAG laser was used as the laser pulse source, with a pulse energy from 0.2 J up to 3.0 J and a pulse width of 150 μs up to 1000 μs. The retropulsion was monitored using a high-speed camera, and the laser-induced craters were evaluated with a 3-D digital microscope. The best fit to the experimental data is done by a design of experiment software. Results The numerical formulas for the response surfaces of ablation speed and retropulsion amplitude are generated. Conclusions The longer the pulse, the less the ablation or retropulsion, while the longer pulse makes the ablation decrease faster than the retropulsion. The best quadratic fit of the response surface for the volume of ablation varied nonlinearly with pulse duration and pulse number. PMID:29707187

Isolating and quantifying cross-beam energy transfer in direct-drive implosions on OMEGA and the National Ignition Facility

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, A. K.; Cao, D.; Michel, D. T.

The angularly-resolved mass ablation rates and ablation front trajectories for Si-coated CH targets were measured in direct-drive inertial confinement fusion experiments to quantify crossbeam energy transfer (CBET) while constraining the hydrodynamic coupling. A polar-direct-drive laser configuration was used, where the equatorial laser beams were dropped from a symmetric direct-drive configuration to suppress CBET at the pole, while allowing it to persist at the equator. The combination of low- and high-CBET conditions in the same implosion allowed the effects of CBET on the ablation rate and ablation pressure to be decoupled from the other physics effects that influence laser-coupling. Hydrodynamic simulationsmore » performed without CBET reproduced the measured ablation rate and ablation front trajectory at the pole of the target, verifying that the other laser-coupling physics effects are well-modeled when CBET effects are negligible. The simulated mass ablation rates and ablation front trajectories were in excellent agreement with the measurements at all angles when a CBET model based on Randall’s equations [C. J. Randall et al., Phys. Fluids 24, 1474 (1981)] was included into the simulations with an optimized multiplier on the CBET gain factor. These measurements were performed on both OMEGA and the National Ignition Facility to access a wide range of plasma conditions, laser intensities, and laser beam geometries. Furthermore, the presence of the CBET gain multiplier required to match the data in all of the configurations tested suggests that additional physics effects, such as intensity variations due to diffraction, shortcomings of extending the 1-D Randall model to 3-D, or polarization effects, should be explored to explain the differences in observed and predicted drive.« less

Isolating and quantifying cross-beam energy transfer in direct-drive implosions on OMEGA and the National Ignition Facility

DOE PAGES

Davis, A. K.; Cao, D.; Michel, D. T.; ...

2016-04-20

The angularly-resolved mass ablation rates and ablation front trajectories for Si-coated CH targets were measured in direct-drive inertial confinement fusion experiments to quantify crossbeam energy transfer (CBET) while constraining the hydrodynamic coupling. A polar-direct-drive laser configuration was used, where the equatorial laser beams were dropped from a symmetric direct-drive configuration to suppress CBET at the pole, while allowing it to persist at the equator. The combination of low- and high-CBET conditions in the same implosion allowed the effects of CBET on the ablation rate and ablation pressure to be decoupled from the other physics effects that influence laser-coupling. Hydrodynamic simulationsmore » performed without CBET reproduced the measured ablation rate and ablation front trajectory at the pole of the target, verifying that the other laser-coupling physics effects are well-modeled when CBET effects are negligible. The simulated mass ablation rates and ablation front trajectories were in excellent agreement with the measurements at all angles when a CBET model based on Randall’s equations [C. J. Randall et al., Phys. Fluids 24, 1474 (1981)] was included into the simulations with an optimized multiplier on the CBET gain factor. These measurements were performed on both OMEGA and the National Ignition Facility to access a wide range of plasma conditions, laser intensities, and laser beam geometries. Furthermore, the presence of the CBET gain multiplier required to match the data in all of the configurations tested suggests that additional physics effects, such as intensity variations due to diffraction, shortcomings of extending the 1-D Randall model to 3-D, or polarization effects, should be explored to explain the differences in observed and predicted drive.« less

In vivo evaluation of virtual electrode mapping and ablation utilizing a direct endocardial visualization ablation catheter.

PubMed

Chik, William W B; Barry, M A; Malchano, Zach; Wylie, Bryan; Pouliopoulos, Jim; Huang, Kaimin; Lu, Juntang; Thavapalachandran, Sujitha; Robinson, David; Saadat, Vahid; Thomas, Stuart P; Ross, David L; Kovoor, Pramesh; Thiagalingam, Aravinda

2012-01-01

Radiofrequency (RF) ablation utilizing direct endocardial visualization (DEV) requires a "virtual electrode" to deliver RF energy while preserving visualization. This study aimed to: (1) examine the virtual electrode RF ablation efficacy; (2) determine the optimal power and duration settings; and (3) evaluate the utility of virtual electrode unipolar electrograms. The DEV catheter lesions were compared to lesions formed using a 3.5 mm open irrigated tip catheter within the right atria of 12 sheep. Generator power settings for DEV were titrated from 12W, 14W and 16W for 20, 30 and 40 seconds duration with 25 mL/min saline irrigation. Standard irrigated tip catheter settings of 30W, 50°C for 30 seconds and 30 mL/min were used. The DEV lesions were significantly greater in surface area and both major and minor axes compared to irrigated tip lesions (surface area 19.43 ± 9.09 vs 10.88 ± 4.72 mm, P<0.01) with no difference in transmurality (93/94 vs 46/47) or depth (1.86 ± 0.75 vs 1.85 ± 0.57 mm). Absolute electrogram amplitude reduction was greater for DEV lesions (1.89 ± 1.31 vs 1.49 ± 0.78 mV, P = 0.04), but no difference in percentage reduction. Pre-ablation pacing thresholds were not different between DEV (0.79 ± 0.36 mA) and irrigated tip (0.73 ± 0.25 mA) lesions. There were no complications noted during ablation with either catheter. Virtual electrode ablation consistently created wider lesions at lower power compared to irrigated tip ablation. Virtual electrode electrograms showed a comparable pacing and sensing efficacy in detecting local myocardial electrophysiological changes. © 2011 Wiley Periodicals, Inc.

First-order convex feasibility algorithms for x-ray CT

PubMed Central

Sidky, Emil Y.; Jørgensen, Jakob S.; Pan, Xiaochuan

2013-01-01

Purpose: Iterative image reconstruction (IIR) algorithms in computed tomography (CT) are based on algorithms for solving a particular optimization problem. Design of the IIR algorithm, therefore, is aided by knowledge of the solution to the optimization problem on which it is based. Often times, however, it is impractical to achieve accurate solution to the optimization of interest, which complicates design of IIR algorithms. This issue is particularly acute for CT with a limited angular-range scan, which leads to poorly conditioned system matrices and difficult to solve optimization problems. In this paper, we develop IIR algorithms which solve a certain type of optimization called convex feasibility. The convex feasibility approach can provide alternatives to unconstrained optimization approaches and at the same time allow for rapidly convergent algorithms for their solution—thereby facilitating the IIR algorithm design process. Methods: An accelerated version of the Chambolle−Pock (CP) algorithm is adapted to various convex feasibility problems of potential interest to IIR in CT. One of the proposed problems is seen to be equivalent to least-squares minimization, and two other problems provide alternatives to penalized, least-squares minimization. Results: The accelerated CP algorithms are demonstrated on a simulation of circular fan-beam CT with a limited scanning arc of 144°. The CP algorithms are seen in the empirical results to converge to the solution of their respective convex feasibility problems. Conclusions: Formulation of convex feasibility problems can provide a useful alternative to unconstrained optimization when designing IIR algorithms for CT. The approach is amenable to recent methods for accelerating first-order algorithms which may be particularly useful for CT with limited angular-range scanning. The present paper demonstrates the methodology, and future work will illustrate its utility in actual CT application. PMID:23464295

A hybrid Jaya algorithm for reliability-redundancy allocation problems

NASA Astrophysics Data System (ADS)

Ghavidel, Sahand; Azizivahed, Ali; Li, Li

2018-04-01

This article proposes an efficient improved hybrid Jaya algorithm based on time-varying acceleration coefficients (TVACs) and the learning phase introduced in teaching-learning-based optimization (TLBO), named the LJaya-TVAC algorithm, for solving various types of nonlinear mixed-integer reliability-redundancy allocation problems (RRAPs) and standard real-parameter test functions. RRAPs include series, series-parallel, complex (bridge) and overspeed protection systems. The search power of the proposed LJaya-TVAC algorithm for finding the optimal solutions is first tested on the standard real-parameter unimodal and multi-modal functions with dimensions of 30-100, and then tested on various types of nonlinear mixed-integer RRAPs. The results are compared with the original Jaya algorithm and the best results reported in the recent literature. The optimal results obtained with the proposed LJaya-TVAC algorithm provide evidence for its better and acceptable optimization performance compared to the original Jaya algorithm and other reported optimal results.

New human-centered linear and nonlinear motion cueing algorithms for control of simulator motion systems

NASA Astrophysics Data System (ADS)

Telban, Robert J.

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. To address this, new human-centered motion cueing algorithms were developed. A revised "optimal algorithm" uses time-invariant filters developed by optimal control, incorporating human vestibular system models. The "nonlinear algorithm" is a novel approach that is also formulated by optimal control, but can also be updated in real time. It incorporates a new integrated visual-vestibular perception model that includes both visual and vestibular sensation and the interaction between the stimuli. A time-varying control law requires the matrix Riccati equation to be solved in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. As a result of unsatisfactory sensation, an augmented turbulence cue was added to the vertical mode for both the optimal and nonlinear algorithms. The relative effectiveness of the algorithms, in simulating aircraft maneuvers, was assessed with an eleven-subject piloted performance test conducted on the NASA Langley Visual Motion Simulator (VMS). Two methods, the quasi-objective NASA Task Load Index (TLX), and power spectral density analysis of pilot control, were used to assess pilot workload. TLX analysis reveals, in most cases, less workload and variation among pilots with the nonlinear algorithm. Control input analysis shows pilot-induced oscillations on a straight-in approach are less prevalent compared to the optimal algorithm. The augmented turbulence cues increased workload on an offset approach that the pilots deemed more realistic compared to the NASA adaptive algorithm. The takeoff with engine failure showed the least roll activity for the nonlinear algorithm, with the least rudder pedal activity for the optimal algorithm.

Using Animal Instincts to Design Efficient Biomedical Studies via Particle Swarm Optimization.

PubMed

Qiu, Jiaheng; Chen, Ray-Bing; Wang, Weichung; Wong, Weng Kee

2014-10-01

Particle swarm optimization (PSO) is an increasingly popular metaheuristic algorithm for solving complex optimization problems. Its popularity is due to its repeated successes in finding an optimum or a near optimal solution for problems in many applied disciplines. The algorithm makes no assumption of the function to be optimized and for biomedical experiments like those presented here, PSO typically finds the optimal solutions in a few seconds of CPU time on a garden-variety laptop. We apply PSO to find various types of optimal designs for several problems in the biological sciences and compare PSO performance relative to the differential evolution algorithm, another popular metaheuristic algorithm in the engineering literature.

A global optimization algorithm inspired in the behavior of selfish herds.

PubMed

Fausto, Fernando; Cuevas, Erik; Valdivia, Arturo; González, Adrián

2017-10-01

In this paper, a novel swarm optimization algorithm called the Selfish Herd Optimizer (SHO) is proposed for solving global optimization problems. SHO is based on the simulation of the widely observed selfish herd behavior manifested by individuals within a herd of animals subjected to some form of predation risk. In SHO, individuals emulate the predatory interactions between groups of prey and predators by two types of search agents: the members of a selfish herd (the prey) and a pack of hungry predators. Depending on their classification as either a prey or a predator, each individual is conducted by a set of unique evolutionary operators inspired by such prey-predator relationship. These unique traits allow SHO to improve the balance between exploration and exploitation without altering the population size. To illustrate the proficiency and robustness of the proposed method, it is compared to other well-known evolutionary optimization approaches such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Firefly Algorithm (FA), Differential Evolution (DE), Genetic Algorithms (GA), Crow Search Algorithm (CSA), Dragonfly Algorithm (DA), Moth-flame Optimization Algorithm (MOA) and Sine Cosine Algorithm (SCA). The comparison examines several standard benchmark functions, commonly considered within the literature of evolutionary algorithms. The experimental results show the remarkable performance of our proposed approach against those of the other compared methods, and as such SHO is proven to be an excellent alternative to solve global optimization problems. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimal Budget Allocation for Sample Average Approximation

DTIC Science & Technology

2011-06-01

an optimization algorithm applied to the sample average problem. We examine the convergence rate of the estimator as the computing budget tends to...regime for the optimization algorithm . 1 Introduction Sample average approximation (SAA) is a frequently used approach to solving stochastic programs...appealing due to its simplicity and the fact that a large number of standard optimization algorithms are often available to optimize the resulting sample

High-intensity focused ultrasound ablation of thyroid nodules: first human feasibility study.

PubMed

Esnault, Olivier; Franc, Brigitte; Ménégaux, Fabrice; Rouxel, Agnès; De Kerviler, Eric; Bourrier, Pierre; Lacoste, François; Chapelon, Jean-Yves; Leenhardt, Laurence

2011-09-01

Thyroid surgery is common, but complications may occur. High-intensity focused ultrasound (HIFU) is a minimally invasive alternative to surgery. We hypothesized that an optimized HIFU device could be safe and effective for ablating benign thyroid nodules without affecting neighboring structures. In this open, single-center feasibility study, 25 patients were treated with HIFU with real-time ultrasound imaging 2 weeks before a scheduled thyroidectomy for multinodular goiter. Thyroid ultrasonography imaging, thyroid function, were evaluated before and after treatment. Adverse events were carefully recorded. Each patient received HIFU for one thyroid nodule, solid or mixed, with mean diameter ≥8 mm, and no suspicion of malignancy. The HIFU device was progressively adjusted with stepwise testing. The energy level for ablation ranged from 35 to 94 J/pulse for different groups of patients. One pathologist examined all removed thyroids. Three patients discontinued treatment due to pain or skin microblister. Among the remaining 22 patients, 16 showed significant changes by ultrasound. Macroscopic and histological examinations showed that all lesions were confined to the targeted nodule without affecting neighboring structures. At pathological analysis, the extent of nodule destruction ranged from 2% to 80%. Five out of 22 patients had over 20% pathological lesions unmistakably attributed to HIFU. Seventeen cases had putative lesions including nonspecific necrosis, hemorrhage, nodule detachment, cavitations, and cysts. Among these 17 cases, 12 had both ultrasound changes and cavitation at histology that may be expected for an HIFU effect. In the last three patients ablated at the highest energy level, significant ultrasound changes and complete coagulative necrosis were observed in 80%, 78%, and 58% of the targeted area, respectively. There were no major complications of ablation. This study showed the potential efficacy of HIFU for human thyroid nodule ablation. Lesions were clearly visible by histology and ultrasound after high energy treatments, and safety and tolerability were good. We identified a power threshold for optimal necrosis of the target thyroid tissue. Further studies are ongoing to assess nodule changes at longer follow-up times.

Techniques for shuttle trajectory optimization

NASA Technical Reports Server (NTRS)

Edge, E. R.; Shieh, C. J.; Powers, W. F.

1973-01-01

The application of recently developed function-space Davidon-type techniques to the shuttle ascent trajectory optimization problem is discussed along with an investigation of the recently developed PRAXIS algorithm for parameter optimization. At the outset of this analysis, the major deficiency of the function-space algorithms was their potential storage problems. Since most previous analyses of the methods were with relatively low-dimension problems, no storage problems were encountered. However, in shuttle trajectory optimization, storage is a problem, and this problem was handled efficiently. Topics discussed include: the shuttle ascent model and the development of the particular optimization equations; the function-space algorithms; the operation of the algorithm and typical simulations; variable final-time problem considerations; and a modification of Powell's algorithm.

Optimal design of the rotor geometry of line-start permanent magnet synchronous motor using the bat algorithm

NASA Astrophysics Data System (ADS)

Knypiński, Łukasz

2017-12-01

In this paper an algorithm for the optimization of excitation system of line-start permanent magnet synchronous motors will be presented. For the basis of this algorithm, software was developed in the Borland Delphi environment. The software consists of two independent modules: an optimization solver, and a module including the mathematical model of a synchronous motor with a self-start ability. The optimization module contains the bat algorithm procedure. The mathematical model of the motor has been developed in an Ansys Maxwell environment. In order to determine the functional parameters of the motor, additional scripts in Visual Basic language were developed. Selected results of the optimization calculation are presented and compared with results for the particle swarm optimization algorithm.

Developing a Shuffled Complex-Self Adaptive Hybrid Evolution (SC-SAHEL) Framework for Water Resources Management and Water-Energy System Optimization

NASA Astrophysics Data System (ADS)

Rahnamay Naeini, M.; Sadegh, M.; AghaKouchak, A.; Hsu, K. L.; Sorooshian, S.; Yang, T.

2017-12-01

Meta-Heuristic optimization algorithms have gained a great deal of attention in a wide variety of fields. Simplicity and flexibility of these algorithms, along with their robustness, make them attractive tools for solving optimization problems. Different optimization methods, however, hold algorithm-specific strengths and limitations. Performance of each individual algorithm obeys the "No-Free-Lunch" theorem, which means a single algorithm cannot consistently outperform all possible optimization problems over a variety of problems. From users' perspective, it is a tedious process to compare, validate, and select the best-performing algorithm for a specific problem or a set of test cases. In this study, we introduce a new hybrid optimization framework, entitled Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL), which combines the strengths of different evolutionary algorithms (EAs) in a parallel computing scheme, and allows users to select the most suitable algorithm tailored to the problem at hand. The concept of SC-SAHEL is to execute different EAs as separate parallel search cores, and let all participating EAs to compete during the course of the search. The newly developed SC-SAHEL algorithm is designed to automatically select, the best performing algorithm for the given optimization problem. This algorithm is rigorously effective in finding the global optimum for several strenuous benchmark test functions, and computationally efficient as compared to individual EAs. We benchmark the proposed SC-SAHEL algorithm over 29 conceptual test functions, and two real-world case studies - one hydropower reservoir model and one hydrological model (SAC-SMA). Results show that the proposed framework outperforms individual EAs in an absolute majority of the test problems, and can provide competitive results to the fittest EA algorithm with more comprehensive information during the search. The proposed framework is also flexible for merging additional EAs, boundary-handling techniques, and sampling schemes, and has good potential to be used in Water-Energy system optimal operation and management.

Load Frequency Control of AC Microgrid Interconnected Thermal Power System

NASA Astrophysics Data System (ADS)

Lal, Deepak Kumar; Barisal, Ajit Kumar

2017-08-01

In this paper, a microgrid (MG) power generation system is interconnected with a single area reheat thermal power system for load frequency control study. A new meta-heuristic optimization algorithm i.e. Moth-Flame Optimization (MFO) algorithm is applied to evaluate optimal gains of the fuzzy based proportional, integral and derivative (PID) controllers. The system dynamic performance is studied by comparing the results with MFO optimized classical PI/PID controllers. Also the system performance is investigated with fuzzy PID controller optimized by recently developed grey wolf optimizer (GWO) algorithm, which has proven its superiority over other previously developed algorithm in many interconnected power systems.

Direct adaptive performance optimization of subsonic transports: A periodic perturbation technique

NASA Technical Reports Server (NTRS)

Espana, Martin D.; Gilyard, Glenn

1995-01-01

Aircraft performance can be optimized at the flight condition by using available redundancy among actuators. Effective use of this potential allows improved performance beyond limits imposed by design compromises. Optimization based on nominal models does not result in the best performance of the actual aircraft at the actual flight condition. An adaptive algorithm for optimizing performance parameters, such as speed or fuel flow, in flight based exclusively on flight data is proposed. The algorithm is inherently insensitive to model inaccuracies and measurement noise and biases and can optimize several decision variables at the same time. An adaptive constraint controller integrated into the algorithm regulates the optimization constraints, such as altitude or speed, without requiring and prior knowledge of the autopilot design. The algorithm has a modular structure which allows easy incorporation (or removal) of optimization constraints or decision variables to the optimization problem. An important part of the contribution is the development of analytical tools enabling convergence analysis of the algorithm and the establishment of simple design rules. The fuel-flow minimization and velocity maximization modes of the algorithm are demonstrated on the NASA Dryden B-720 nonlinear flight simulator for the single- and multi-effector optimization cases.

Automatic segmentation for detecting uterine fibroid regions treated with MR-guided high intensity focused ultrasound (MR-HIFU).

PubMed

Antila, Kari; Nieminen, Heikki J; Sequeiros, Roberto Blanco; Ehnholm, Gösta

2014-07-01

Up to 25% of women suffer from uterine fibroids (UF) that cause infertility, pain, and discomfort. MR-guided high intensity focused ultrasound (MR-HIFU) is an emerging technique for noninvasive, computer-guided thermal ablation of UFs. The volume of induced necrosis is a predictor of the success of the treatment. However, accurate volume assessment by hand can be time consuming, and quick tools produce biased results. Therefore, fast and reliable tools are required in order to estimate the technical treatment outcome during the therapy event so as to predict symptom relief. A novel technique has been developed for the segmentation and volume assessment of the treated region. Conventional algorithms typically require user interaction ora priori knowledge of the target. The developed algorithm exploits the treatment plan, the coordinates of the intended ablation, for fully automatic segmentation with no user input. A good similarity to an expert-segmented manual reference was achieved (Dice similarity coefficient = 0.880 ± 0.074). The average automatic segmentation time was 1.6 ± 0.7 min per patient against an order of tens of minutes when done manually. The results suggest that the segmentation algorithm developed, requiring no user-input, provides a feasible and practical approach for the automatic evaluation of the boundary and volume of the HIFU-treated region.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization.

PubMed

Jiang, Ailian; Zheng, Lihong

2018-03-29

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.

An Effective Hybrid Routing Algorithm in WSN: Ant Colony Optimization in combination with Hop Count Minimization

PubMed Central

2018-01-01

Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs). This paper investigates the existing ant colony optimization (ACO)-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime. PMID:29596336

An Improved DINEOF Algorithm for Filling Missing Values in Spatio-Temporal Sea Surface Temperature Data.

PubMed

Ping, Bo; Su, Fenzhen; Meng, Yunshan

2016-01-01

In this study, an improved Data INterpolating Empirical Orthogonal Functions (DINEOF) algorithm for determination of missing values in a spatio-temporal dataset is presented. Compared with the ordinary DINEOF algorithm, the iterative reconstruction procedure until convergence based on every fixed EOF to determine the optimal EOF mode is not necessary and the convergence criterion is only reached once in the improved DINEOF algorithm. Moreover, in the ordinary DINEOF algorithm, after optimal EOF mode determination, the initial matrix with missing data will be iteratively reconstructed based on the optimal EOF mode until the reconstruction is convergent. However, the optimal EOF mode may be not the best EOF for some reconstructed matrices generated in the intermediate steps. Hence, instead of using asingle EOF to fill in the missing data, in the improved algorithm, the optimal EOFs for reconstruction are variable (because the optimal EOFs are variable, the improved algorithm is called VE-DINEOF algorithm in this study). To validate the accuracy of the VE-DINEOF algorithm, a sea surface temperature (SST) data set is reconstructed by using the DINEOF, I-DINEOF (proposed in 2015) and VE-DINEOF algorithms. Four parameters (Pearson correlation coefficient, signal-to-noise ratio, root-mean-square error, and mean absolute difference) are used as a measure of reconstructed accuracy. Compared with the DINEOF and I-DINEOF algorithms, the VE-DINEOF algorithm can significantly enhance the accuracy of reconstruction and shorten the computational time.

From Determinism and Probability to Chaos: Chaotic Evolution towards Philosophy and Methodology of Chaotic Optimization

PubMed Central

2015-01-01

We present and discuss philosophy and methodology of chaotic evolution that is theoretically supported by chaos theory. We introduce four chaotic systems, that is, logistic map, tent map, Gaussian map, and Hénon map, in a well-designed chaotic evolution algorithm framework to implement several chaotic evolution (CE) algorithms. By comparing our previous proposed CE algorithm with logistic map and two canonical differential evolution (DE) algorithms, we analyse and discuss optimization performance of CE algorithm. An investigation on the relationship between optimization capability of CE algorithm and distribution characteristic of chaotic system is conducted and analysed. From evaluation result, we find that distribution of chaotic system is an essential factor to influence optimization performance of CE algorithm. We propose a new interactive EC (IEC) algorithm, interactive chaotic evolution (ICE) that replaces fitness function with a real human in CE algorithm framework. There is a paired comparison-based mechanism behind CE search scheme in nature. A simulation experimental evaluation is conducted with a pseudo-IEC user to evaluate our proposed ICE algorithm. The evaluation result indicates that ICE algorithm can obtain a significant better performance than or the same performance as interactive DE. Some open topics on CE, ICE, fusion of these optimization techniques, algorithmic notation, and others are presented and discussed. PMID:25879067

From determinism and probability to chaos: chaotic evolution towards philosophy and methodology of chaotic optimization.

PubMed

Pei, Yan

2015-01-01

We present and discuss philosophy and methodology of chaotic evolution that is theoretically supported by chaos theory. We introduce four chaotic systems, that is, logistic map, tent map, Gaussian map, and Hénon map, in a well-designed chaotic evolution algorithm framework to implement several chaotic evolution (CE) algorithms. By comparing our previous proposed CE algorithm with logistic map and two canonical differential evolution (DE) algorithms, we analyse and discuss optimization performance of CE algorithm. An investigation on the relationship between optimization capability of CE algorithm and distribution characteristic of chaotic system is conducted and analysed. From evaluation result, we find that distribution of chaotic system is an essential factor to influence optimization performance of CE algorithm. We propose a new interactive EC (IEC) algorithm, interactive chaotic evolution (ICE) that replaces fitness function with a real human in CE algorithm framework. There is a paired comparison-based mechanism behind CE search scheme in nature. A simulation experimental evaluation is conducted with a pseudo-IEC user to evaluate our proposed ICE algorithm. The evaluation result indicates that ICE algorithm can obtain a significant better performance than or the same performance as interactive DE. Some open topics on CE, ICE, fusion of these optimization techniques, algorithmic notation, and others are presented and discussed.

Workflow oriented software support for image guided radiofrequency ablation of focal liver malignancies

NASA Astrophysics Data System (ADS)

Weihusen, Andreas; Ritter, Felix; Kröger, Tim; Preusser, Tobias; Zidowitz, Stephan; Peitgen, Heinz-Otto

2007-03-01

Image guided radiofrequency (RF) ablation has taken a significant part in the clinical routine as a minimally invasive method for the treatment of focal liver malignancies. Medical imaging is used in all parts of the clinical workflow of an RF ablation, incorporating treatment planning, interventional targeting and result assessment. This paper describes a software application, which has been designed to support the RF ablation workflow under consideration of the requirements of clinical routine, such as easy user interaction and a high degree of robust and fast automatic procedures, in order to keep the physician from spending too much time at the computer. The application therefore provides a collection of specialized image processing and visualization methods for treatment planning and result assessment. The algorithms are adapted to CT as well as to MR imaging. The planning support contains semi-automatic methods for the segmentation of liver tumors and the surrounding vascular system as well as an interactive virtual positioning of RF applicators and a concluding numerical estimation of the achievable heat distribution. The assessment of the ablation result is supported by the segmentation of the coagulative necrosis and an interactive registration of pre- and post-interventional image data for the comparison of tumor and necrosis segmentation masks. An automatic quantification of surface distances is performed to verify the embedding of the tumor area into the thermal lesion area. The visualization methods support representations in the commonly used orthogonal 2D view as well as in 3D scenes.

Depth profiling of galvanoaluminium-nickel coatings on steel by UV- and VIS-LIBS

NASA Astrophysics Data System (ADS)

Nagy, T. O.; Pacher, U.; Giesriegl, A.; Weimerskirch, M. J. J.; Kautek, W.

2017-10-01

Laser-induced depth profiling was applied to the investigation of galvanised steel sheets as a typical modern multi-layer coating system for environmental corrosion protection. The samples were ablated stepwise by the use of two different wavelengths of a frequency-converted Nd:YAG-laser, 266 nm and 532 nm, with a pulse duration of τ = 4 ns at fluences ranging from F = 50 to 250 J cm-2. The emission light of the resulting plasma was analysed as a function of both penetration depth and elemental spectrum in terms of linear correlation analysis. Elemental depth profiles were calculated and compared to EDX-cross sections of the cut sample. A proven mathematical algorithm designed for the reconstruction of layer structures from distorted emission traces caused by the Gaussian ablation profile can even resolve thin intermediate layers in terms of depth and thickness. The obtained results were compared to a purely thermally controlled ablation model. Thereby light-plasma coupling is suggested to be a possible cause of deviations in the ablation behaviour of Al. The average ablation rate h as a function of fluence F for Ni ranges from 1 to 3.5 μm/pulse for λ = 266 nm as well as for λ = 532 nm. In contrast, the range of h for Al differs from 2 to 4 μm/pulse for λ = 532 nm and 4 to 8 μm/pulse for λ = 266 nm in the exact same fluence range on the exact same sample.

Optimizing the Shunting Schedule of Electric Multiple Units Depot Using an Enhanced Particle Swarm Optimization Algorithm

PubMed Central

Jin, Junchen

2016-01-01

The shunting schedule of electric multiple units depot (SSED) is one of the essential plans for high-speed train maintenance activities. This paper presents a 0-1 programming model to address the problem of determining an optimal SSED through automatic computing. The objective of the model is to minimize the number of shunting movements and the constraints include track occupation conflicts, shunting routes conflicts, time durations of maintenance processes, and shunting running time. An enhanced particle swarm optimization (EPSO) algorithm is proposed to solve the optimization problem. Finally, an empirical study from Shanghai South EMU Depot is carried out to illustrate the model and EPSO algorithm. The optimization results indicate that the proposed method is valid for the SSED problem and that the EPSO algorithm outperforms the traditional PSO algorithm on the aspect of optimality. PMID:27436998

Investigations of quantum heuristics for optimization

NASA Astrophysics Data System (ADS)

Rieffel, Eleanor; Hadfield, Stuart; Jiang, Zhang; Mandra, Salvatore; Venturelli, Davide; Wang, Zhihui

We explore the design of quantum heuristics for optimization, focusing on the quantum approximate optimization algorithm, a metaheuristic developed by Farhi, Goldstone, and Gutmann. We develop specific instantiations of the of quantum approximate optimization algorithm for a variety of challenging combinatorial optimization problems. Through theoretical analyses and numeric investigations of select problems, we provide insight into parameter setting and Hamiltonian design for quantum approximate optimization algorithms and related quantum heuristics, and into their implementation on hardware realizable in the near term.

Optimization of multi-objective micro-grid based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Zhang, Jian; Gan, Yang

2018-04-01

The paper presents a multi-objective optimal configuration model for independent micro-grid with the aim of economy and environmental protection. The Pareto solution set can be obtained by solving the multi-objective optimization configuration model of micro-grid with the improved particle swarm algorithm. The feasibility of the improved particle swarm optimization algorithm for multi-objective model is verified, which provides an important reference for multi-objective optimization of independent micro-grid.

Impact of radiofrequency ablation geometry on electrical conduction

NASA Astrophysics Data System (ADS)

Rivas, Rhiana N.; Lye, Theresa H.; Hendon, Christine P.

2018-02-01

The gold standard of current treatment for atrial fibrillation is radiofrequency ablation (RFA). Single RFA procedures have low long-term, single-procedure success rates, which can be attributed to factors including inability to measure and visualize lesion depth in real time and incomplete knowledge of how atrial fibrillation manifests and persists. One way to address this problem is to develop a heart model that accurately fits lesion dimensions and depth using OCT to extract structural information. Twenty-three lesions of varying transmurality in left and right swine atrial tissue have been imaged with a Thorlabs OCT system with 6.5-micron axial resolution and a custom Ultra High Resolution system with 2.5-micron axial resolution. The boundaries of the ablation lesions were identified by the appearance of the birefringence artifact to identify areas of un-ablated tissue, as well as by changes to depth penetration and structural features, including decreased contrast between the endocardium and myocardium and disappearance of collagen fibers within the ablation lesion. Using these features, the lateral positions of the lesion boundaries were identified. An algorithm that fit ellipses to the lesion contours modeled the ablation geometry in depth. Lesion dimensions and shape were confirmed by comparison with trichrome histological processing. Finite-element models were fitted with these parameters and electrophysiological simulations were run with the Continuity 6 package. Next steps include correlating lesion geometry to conduction velocity, and including further tissue complexity such as varying tissue composition and fiber orientation. Additional models of linear lesions with gaps and adjacent lesions created with non-perpendicular contact will be created. This work will provide insight into how lesion geometry, tissue composition, and fiber organization impact electrophysiological propagation.

Multiobjective Optimization Using a Pareto Differential Evolution Approach

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.; Biegel, Bryan A. (Technical Monitor)

2002-01-01

Differential Evolution is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. In this paper, the Differential Evolution algorithm is extended to multiobjective optimization problems by using a Pareto-based approach. The algorithm performs well when applied to several test optimization problems from the literature.

Enhanced Particle Swarm Optimization Algorithm: Efficient Training of ReaxFF Reactive Force Fields.

PubMed

Furman, David; Carmeli, Benny; Zeiri, Yehuda; Kosloff, Ronnie

2018-06-12

Particle swarm optimization (PSO) is a powerful metaheuristic population-based global optimization algorithm. However, when it is applied to nonseparable objective functions, its performance on multimodal landscapes is significantly degraded. Here we show that a significant improvement in the search quality and efficiency on multimodal functions can be achieved by enhancing the basic rotation-invariant PSO algorithm with isotropic Gaussian mutation operators. The new algorithm demonstrates superior performance across several nonlinear, multimodal benchmark functions compared with the rotation-invariant PSO algorithm and the well-established simulated annealing and sequential one-parameter parabolic interpolation methods. A search for the optimal set of parameters for the dispersion interaction model in the ReaxFF- lg reactive force field was carried out with respect to accurate DFT-TS calculations. The resulting optimized force field accurately describes the equations of state of several high-energy molecular crystals where such interactions are of crucial importance. The improved algorithm also presents better performance compared to a genetic algorithm optimization method in the optimization of the parameters of a ReaxFF- lg correction model. The computational framework is implemented in a stand-alone C++ code that allows the straightforward development of ReaxFF reactive force fields.

Planning Target Volume D95 and Mean Dose Should Be Considered for Optimal Local Control for Stereotactic Ablative Radiation Therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Lina; Zhou, Shouhao; Balter, Peter

Purpose: To identify the optimal dose parameters predictive for local/lobar control after stereotactic ablative radiation therapy (SABR) in early-stage non-small cell lung cancer (NSCLC). Methods and Materials: This study encompassed a total of 1092 patients (1200 lesions) with NSCLC of clinical stage T1-T2 N0M0 who were treated with SABR of 50 Gy in 4 fractions or 70 Gy in 10 fractions, depending on tumor location/size, using computed tomography-based heterogeneity corrections and a convolution superposition calculation algorithm. Patients were monitored by chest CT or positron emission tomography/CT and/or biopsy after SABR. Factors predicting local/lobar recurrence (LR) were determined by competing risk multivariate analysis.more » Continuous variables were divided into 2 subgroups at cutoff values identified by receiver operating characteristic curves. Results: At a median follow-up time of 31.7 months (interquartile range, 14.8-51.3 months), the 5-year time to local recurrence within the same lobe and overall survival rates were 93.8% and 44.8%, respectively. Total cumulative number of patients experiencing LR was 40 (3.7%), occurring at a median time of 14.4 months (range, 4.8-46 months). Using multivariate competing risk analysis, independent predictive factors for LR after SABR were minimum biologically effective dose (BED{sub 10}) to 95% of planning target volume (PTVD95 BED{sub 10}) ≤86 Gy (corresponding to PTV D95 physics dose of 42 Gy in 4 fractions or 55 Gy in 10 fractions) and gross tumor volume ≥8.3 cm{sup 3}. The PTVmean BED{sub 10} was highly correlated with PTVD95 BED{sub 10.} In univariate analysis, a cutoff of 130 Gy for PTVmean BED{sub 10} (corresponding to PTVmean physics dose of 55 Gy in 4 fractions or 75 Gy in 10 fractions) was also significantly associated with LR. Conclusions: In addition to gross tumor volume, higher radiation dose delivered to the PTV predicts for better local/lobar control. We recommend that both PTVD95 BED{sub 10} >86 Gy and PTVmean BED{sub 10} >130 Gy should be considered for SABR plan optimization.« less

Microwave ablation of hepatocellular carcinoma

PubMed Central

Poggi, Guido; Tosoratti, Nevio; Montagna, Benedetta; Picchi, Chiara

2015-01-01

Although surgical resection is still the optimal treatment option for early-stage hepatocellular carcinoma (HCC) in patients with well compensated cirrhosis, thermal ablation techniques provide a valid non-surgical treatment alternative, thanks to their minimal invasiveness, excellent tolerability and safety profile, proven efficacy in local disease control, virtually unlimited repeatability and cost-effectiveness. Different energy sources are currently employed in clinics as physical agents for percutaneous or intra-surgical thermal ablation of HCC nodules. Among them, radiofrequency (RF) currents are the most used, while microwave ablations (MWA) are becoming increasingly popular. Starting from the 90s’, RF ablation (RFA) rapidly became the standard of care in ablation, especially in the treatment of small HCC nodules; however, RFA exhibits substantial performance limitations in the treatment of large lesions and/or tumors located near major heat sinks. MWA, first introduced in the Far Eastern clinical practice in the 80s’, showing promising results but also severe limitations in the controllability of the emitted field and in the high amount of power employed for the ablation of large tumors, resulting in a poor coagulative performance and a relatively high complication rate, nowadays shows better results both in terms of treatment controllability and of overall coagulative performance, thanks to the improvement of technology. In this review we provide an extensive and detailed overview of the key physical and technical aspects of MWA and of the currently available systems, and we want to discuss the most relevant published data on MWA treatments of HCC nodules in regard to clinical results and to the type and rate of complications, both in absolute terms and in comparison with RFA. PMID:26557950

Optimal Doppler centroid estimation for SAR data from a quasi-homogeneous source

NASA Technical Reports Server (NTRS)

Jin, M. Y.

1986-01-01

This correspondence briefly describes two Doppler centroid estimation (DCE) algorithms, provides a performance summary for these algorithms, and presents the experimental results. These algorithms include that of Li et al. (1985) and a newly developed one that is optimized for quasi-homogeneous sources. The performance enhancement achieved by the optimal DCE algorithm is clearly demonstrated by the experimental results.

Hybrid Nested Partitions and Math Programming Framework for Large-scale Combinatorial Optimization

DTIC Science & Technology

2010-03-31

optimization problems: 1) exact algorithms and 2) metaheuristic algorithms . This project will integrate concepts from these two technologies to develop...optimal solutions within an acceptable amount of computation time, and 2) metaheuristic algorithms such as genetic algorithms , tabu search, and the...integer programming decomposition approaches, such as Dantzig Wolfe decomposition and Lagrangian relaxation, and metaheuristics such as the Nested

Hull Form Design and Optimization Tool Development

DTIC Science & Technology

2012-07-01

global minimum. The algorithm accomplishes this by using a method known as metaheuristics which allows the algorithm to examine a large area by...further development of these tools including the implementation and testing of a new optimization algorithm , the improvement of a rapid hull form...under the 2012 Naval Research Enterprise Intern Program. 15. SUBJECT TERMS hydrodynamic, hull form, generation, optimization, algorithm

Impact of Chaos Functions on Modern Swarm Optimizers.

PubMed

Emary, E; Zawbaa, Hossam M

2016-01-01

Exploration and exploitation are two essential components for any optimization algorithm. Much exploration leads to oscillation and premature convergence while too much exploitation slows down the optimization algorithm and the optimizer may be stuck in local minima. Therefore, balancing the rates of exploration and exploitation at the optimization lifetime is a challenge. This study evaluates the impact of using chaos-based control of exploration/exploitation rates against using the systematic native control. Three modern algorithms were used in the study namely grey wolf optimizer (GWO), antlion optimizer (ALO) and moth-flame optimizer (MFO) in the domain of machine learning for feature selection. Results on a set of standard machine learning data using a set of assessment indicators prove advance in optimization algorithm performance when using variational repeated periods of declined exploration rates over using systematically decreased exploration rates.

PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization

PubMed Central

Chen, Shuangqing; Wei, Lixin; Guan, Bing

2018-01-01

Particle swarm optimization (PSO) and fireworks algorithm (FWA) are two recently developed optimization methods which have been applied in various areas due to their simplicity and efficiency. However, when being applied to high-dimensional optimization problems, PSO algorithm may be trapped in the local optima owing to the lack of powerful global exploration capability, and fireworks algorithm is difficult to converge in some cases because of its relatively low local exploitation efficiency for noncore fireworks. In this paper, a hybrid algorithm called PS-FW is presented, in which the modified operators of FWA are embedded into the solving process of PSO. In the iteration process, the abandonment and supplement mechanism is adopted to balance the exploration and exploitation ability of PS-FW, and the modified explosion operator and the novel mutation operator are proposed to speed up the global convergence and to avoid prematurity. To verify the performance of the proposed PS-FW algorithm, 22 high-dimensional benchmark functions have been employed, and it is compared with PSO, FWA, stdPSO, CPSO, CLPSO, FIPS, Frankenstein, and ALWPSO algorithms. Results show that the PS-FW algorithm is an efficient, robust, and fast converging optimization method for solving global optimization problems. PMID:29675036

An algorithmic framework for multiobjective optimization.

PubMed

Ganesan, T; Elamvazuthi, I; Shaari, Ku Zilati Ku; Vasant, P

2013-01-01

Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization.

An Algorithmic Framework for Multiobjective Optimization

PubMed Central

Ganesan, T.; Elamvazuthi, I.; Shaari, Ku Zilati Ku; Vasant, P.

2013-01-01

Multiobjective (MO) optimization is an emerging field which is increasingly being encountered in many fields globally. Various metaheuristic techniques such as differential evolution (DE), genetic algorithm (GA), gravitational search algorithm (GSA), and particle swarm optimization (PSO) have been used in conjunction with scalarization techniques such as weighted sum approach and the normal-boundary intersection (NBI) method to solve MO problems. Nevertheless, many challenges still arise especially when dealing with problems with multiple objectives (especially in cases more than two). In addition, problems with extensive computational overhead emerge when dealing with hybrid algorithms. This paper discusses these issues by proposing an alternative framework that utilizes algorithmic concepts related to the problem structure for generating efficient and effective algorithms. This paper proposes a framework to generate new high-performance algorithms with minimal computational overhead for MO optimization. PMID:24470795

Time-optimal trajectory planning for underactuated spacecraft using a hybrid particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Zhuang, Yufei; Huang, Haibin

2014-02-01

A hybrid algorithm combining particle swarm optimization (PSO) algorithm with the Legendre pseudospectral method (LPM) is proposed for solving time-optimal trajectory planning problem of underactuated spacecrafts. At the beginning phase of the searching process, an initialization generator is constructed by the PSO algorithm due to its strong global searching ability and robustness to random initial values, however, PSO algorithm has a disadvantage that its convergence rate around the global optimum is slow. Then, when the change in fitness function is smaller than a predefined value, the searching algorithm is switched to the LPM to accelerate the searching process. Thus, with the obtained solutions by the PSO algorithm as a set of proper initial guesses, the hybrid algorithm can find a global optimum more quickly and accurately. 200 Monte Carlo simulations results demonstrate that the proposed hybrid PSO-LPM algorithm has greater advantages in terms of global searching capability and convergence rate than both single PSO algorithm and LPM algorithm. Moreover, the PSO-LPM algorithm is also robust to random initial values.

A hybrid artificial bee colony algorithm for numerical function optimization

NASA Astrophysics Data System (ADS)

Alqattan, Zakaria N.; Abdullah, Rosni

2015-02-01

Artificial Bee Colony (ABC) algorithm is one of the swarm intelligence algorithms; it has been introduced by Karaboga in 2005. It is a meta-heuristic optimization search algorithm inspired from the intelligent foraging behavior of the honey bees in nature. Its unique search process made it as one of the most competitive algorithm with some other search algorithms in the area of optimization, such as Genetic algorithm (GA) and Particle Swarm Optimization (PSO). However, the ABC performance of the local search process and the bee movement or the solution improvement equation still has some weaknesses. The ABC is good in avoiding trapping at the local optimum but it spends its time searching around unpromising random selected solutions. Inspired by the PSO, we propose a Hybrid Particle-movement ABC algorithm called HPABC, which adapts the particle movement process to improve the exploration of the original ABC algorithm. Numerical benchmark functions were used in order to experimentally test the HPABC algorithm. The results illustrate that the HPABC algorithm can outperform the ABC algorithm in most of the experiments (75% better in accuracy and over 3 times faster).

Seven-spot ladybird optimization: a novel and efficient metaheuristic algorithm for numerical optimization.

PubMed

Wang, Peng; Zhu, Zhouquan; Huang, Shuai

2013-01-01

This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical benchmark functions with multimodality. The results show that SLO has the ability to find the best solution with a comparatively small population size and is suitable for solving optimization problems with lower dimensions.

Seven-Spot Ladybird Optimization: A Novel and Efficient Metaheuristic Algorithm for Numerical Optimization

PubMed Central

Zhu, Zhouquan

2013-01-01

This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical benchmark functions with multimodality. The results show that SLO has the ability to find the best solution with a comparatively small population size and is suitable for solving optimization problems with lower dimensions. PMID:24385879

Optimal cost design of water distribution networks using a decomposition approach

NASA Astrophysics Data System (ADS)

Lee, Ho Min; Yoo, Do Guen; Sadollah, Ali; Kim, Joong Hoon

2016-12-01

Water distribution network decomposition, which is an engineering approach, is adopted to increase the efficiency of obtaining the optimal cost design of a water distribution network using an optimization algorithm. This study applied the source tracing tool in EPANET, which is a hydraulic and water quality analysis model, to the decomposition of a network to improve the efficiency of the optimal design process. The proposed approach was tested by carrying out the optimal cost design of two water distribution networks, and the results were compared with other optimal cost designs derived from previously proposed optimization algorithms. The proposed decomposition approach using the source tracing technique enables the efficient decomposition of an actual large-scale network, and the results can be combined with the optimal cost design process using an optimization algorithm. This proves that the final design in this study is better than those obtained with other previously proposed optimization algorithms.

Analysis of an Optimized MLOS Tomographic Reconstruction Algorithm and Comparison to the MART Reconstruction Algorithm

NASA Astrophysics Data System (ADS)

La Foy, Roderick; Vlachos, Pavlos

2011-11-01

An optimally designed MLOS tomographic reconstruction algorithm for use in 3D PIV and PTV applications is analyzed. Using a set of optimized reconstruction parameters, the reconstructions produced by the MLOS algorithm are shown to be comparable to reconstructions produced by the MART algorithm for a range of camera geometries, camera numbers, and particle seeding densities. The resultant velocity field error calculated using PIV and PTV algorithms is further minimized by applying both pre and post processing to the reconstructed data sets.

Application of Improved APO Algorithm in Vulnerability Assessment and Reconstruction of Microgrid

NASA Astrophysics Data System (ADS)

Xie, Jili; Ma, Hailing

2018-01-01

Artificial Physics Optimization (APO) has good global search ability and can avoid the premature convergence phenomenon in PSO algorithm, which has good stability of fast convergence and robustness. On the basis of APO of the vector model, a reactive power optimization algorithm based on improved APO algorithm is proposed for the static structure and dynamic operation characteristics of microgrid. The simulation test is carried out through the IEEE 30-bus system and the result shows that the algorithm has better efficiency and accuracy compared with other optimization algorithms.

Focusing light through random photonic layers by four-element division algorithm

NASA Astrophysics Data System (ADS)

Fang, Longjie; Zhang, Xicheng; Zuo, Haoyi; Pang, Lin

2018-02-01

The propagation of waves in turbid media is a fundamental problem of optics with vast applications. Optical phase optimization approaches for focusing light through turbid media using phase control algorithm have been widely studied in recent years due to the rapid development of spatial light modulator. The existing approaches include element-based algorithms - stepwise sequential algorithm, continuous sequential algorithm and whole element optimization approaches - partitioning algorithm, transmission matrix approach and genetic algorithm. The advantage of element-based approaches is that the phase contribution of each element is very clear; however, because the intensity contribution of each element to the focal point is small especially for the case of large number of elements, the determination of the optimal phase for a single element would be difficult. In other words, the signal to noise ratio of the measurement is weak, leading to possibly local maximal during the optimization. As for whole element optimization approaches, all elements are employed for the optimization. Of course, signal to noise ratio during the optimization is improved. However, because more random processings are introduced into the processing, optimizations take more time to converge than the single element based approaches. Based on the advantages of both single element based approaches and whole element optimization approaches, we propose FEDA approach. Comparisons with the existing approaches show that FEDA only takes one third of measurement time to reach the optimization, which means that FEDA is promising in practical application such as for deep tissue imaging.

GlobiPack v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bartlett, Roscoe

2010-03-31

GlobiPack contains a small collection of optimization globalization algorithms. These algorithms are used by optimization and various nonlinear equation solver algorithms.Used as the line-search procedure with Newton and Quasi-Newton optimization and nonlinear equation solver methods. These are standard published 1-D line search algorithms such as are described in the book Nocedal and Wright Numerical Optimization: 2nd edition, 2006. One set of algorithms were copied and refactored from the existing open-source Trilinos package MOOCHO where the linear search code is used to globalize SQP methods. This software is generic to any mathematical optimization problem where smooth derivatives exist. There is nomore » specific connection or mention whatsoever to any specific application, period. You cannot find more general mathematical software.« less

Direct position determination for digital modulation signals based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Yu, Wan-Ting; Yu, Hong-yi; Du, Jian-Ping; Wang, Ding

2018-04-01

The Direct Position Determination (DPD) algorithm has been demonstrated to achieve a better accuracy with known signal waveforms. However, the signal waveform is difficult to be completely known in the actual positioning process. To solve the problem, we proposed a DPD method for digital modulation signals based on improved particle swarm optimization algorithm. First, a DPD model is established for known modulation signals and a cost function is obtained on symbol estimation. Second, as the optimization of the cost function is a nonlinear integer optimization problem, an improved Particle Swarm Optimization (PSO) algorithm is considered for the optimal symbol search. Simulations are carried out to show the higher position accuracy of the proposed DPD method and the convergence of the fitness function under different inertia weight and population size. On the one hand, the proposed algorithm can take full advantage of the signal feature to improve the positioning accuracy. On the other hand, the improved PSO algorithm can improve the efficiency of symbol search by nearly one hundred times to achieve a global optimal solution.

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA Technical Reports Server (NTRS)

Rash, James L.

2010-01-01

NASA's space data-communications infrastructure, the Space Network and the Ground Network, provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft via orbiting relay satellites and ground stations. An implementation of the methods and algorithms disclosed herein will be a system that produces globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary search, a class of probabilistic strategies for searching large solution spaces, constitutes the essential technology in this disclosure. Also disclosed are methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithm itself. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally, with applicability to a very broad class of combinatorial optimization problems.

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment

PubMed Central

Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution. PMID:29186166

Multi-AUV autonomous task planning based on the scroll time domain quantum bee colony optimization algorithm in uncertain environment.

PubMed

Li, Jianjun; Zhang, Rubo; Yang, Yu

2017-01-01

Research on distributed task planning model for multi-autonomous underwater vehicle (MAUV). A scroll time domain quantum artificial bee colony (STDQABC) optimization algorithm is proposed to solve the multi-AUV optimal task planning scheme. In the uncertain marine environment, the rolling time domain control technique is used to realize a numerical optimization in a narrowed time range. Rolling time domain control is one of the better task planning techniques, which can greatly reduce the computational workload and realize the tradeoff between AUV dynamics, environment and cost. Finally, a simulation experiment was performed to evaluate the distributed task planning performance of the scroll time domain quantum bee colony optimization algorithm. The simulation results demonstrate that the STDQABC algorithm converges faster than the QABC and ABC algorithms in terms of both iterations and running time. The STDQABC algorithm can effectively improve MAUV distributed tasking planning performance, complete the task goal and get the approximate optimal solution.

Evaluation of Genetic Algorithm Concepts Using Model Problems. Part 2; Multi-Objective Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2003-01-01

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of simple model problems. Several new features including a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. Results indicate that the genetic algorithm optimization approach is flexible in application and extremely reliable, providing optimal results for all optimization problems attempted. The binning algorithm generally provides pareto front quality enhancements and moderate convergence efficiency improvements for most of the model problems. The gene-space transformation procedure provides a large convergence efficiency enhancement for problems with non-convoluted pareto fronts and a degradation in efficiency for problems with convoluted pareto fronts. The most difficult problems --multi-mode search spaces with a large number of genes and convoluted pareto fronts-- require a large number of function evaluations for GA convergence, but always converge.

A new improved artificial bee colony algorithm for ship hull form optimization

NASA Astrophysics Data System (ADS)

Huang, Fuxin; Wang, Lijue; Yang, Chi

2016-04-01

The artificial bee colony (ABC) algorithm is a relatively new swarm intelligence-based optimization algorithm. Its simplicity of implementation, relatively few parameter settings and promising optimization capability make it widely used in different fields. However, it has problems of slow convergence due to its solution search equation. Here, a new solution search equation based on a combination of the elite solution pool and the block perturbation scheme is proposed to improve the performance of the algorithm. In addition, two different solution search equations are used by employed bees and onlooker bees to balance the exploration and exploitation of the algorithm. The developed algorithm is validated by a set of well-known numerical benchmark functions. It is then applied to optimize two ship hull forms with minimum resistance. The tested results show that the proposed new improved ABC algorithm can outperform the ABC algorithm in most of the tested problems.

MINIVER: Miniature version of real/ideal gas aero-heating and ablation computer program

NASA Technical Reports Server (NTRS)

Hendler, D. R.

1976-01-01

Computer code is used to determine heat transfer multiplication factors, special flow field simulation techniques, different heat transfer methods, different transition criteria, crossflow simulation, and more efficient thin skin thickness optimization procedure.

Modeling of endoluminal and interstitial ultrasound hyperthermia and thermal ablation: applications to device design, feedback control, and treatment planning

PubMed Central

Prakash, Punit; Salgaonkar, Vasant A.; Diederich, Chris J.

2014-01-01

Endoluminal and catheter-based ultrasound applicators are currently under development and are in clinical use for minimally invasive hyperthermia and thermal ablation of various tissue targets. Computational models play a critical role in in device design and optimization, assessment of therapeutic feasibility and safety, devising treatment monitoring and feedback control strategies, and performing patient-specific treatment planning with this technology. The critical aspects of theoretical modeling, applied specifically to endoluminal and interstitial ultrasound thermotherapy, are reviewed. Principles and practical techniques for modeling acoustic energy deposition, bioheat transfer, thermal tissue damage, and dynamic changes in the physical and physiological state of tissue are reviewed. The integration of these models and applications of simulation techniques in identification of device design parameters, development of real time feedback-control platforms, assessing the quality and safety of treatment delivery strategies, and optimization of inverse treatment plans are presented. PMID:23738697

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

PubMed

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-03-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

PubMed Central

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-01-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060

Using ultrasound CBE imaging without echo shift compensation for temperature estimation.

PubMed

Tsui, Po-Hsiang; Chien, Yu-Ting; Liu, Hao-Li; Shu, Yu-Chen; Chen, Wen-Shiang

2012-09-01

Clinical trials have demonstrated that hyperthermia improves cancer treatments. Previous studies developed ultrasound temperature imaging methods, based on the changes in backscattered energy (CBE), to monitor temperature variations during hyperthermia. Echo shift, induced by increasing temperature, contaminates the CBE image, and its tracking and compensation should normally ensure that estimations of CBE at each pixel are correct. To obtain a simplified algorithm that would allow real-time computation of CBE images, this study evaluated the usefulness of CBE imaging without echo shift compensation in detecting distributions in temperature. Experiments on phantoms, using different scatterer concentrations, and porcine livers were conducted to acquire raw backscattered data at temperatures ranging from 37°C to 45°C. Tissue samples of pork tenderloin were ablated in vitro by microwave irradiation to evaluate the feasibility of using the CBE image without compensation to monitor tissue ablation. CBE image construction was based on a ratio map obtained from the envelope image divided by the reference envelope image at 37°C. The experimental results demonstrated that the CBE image obtained without echo shift compensation has the ability to estimate temperature variations induced during uniform heating or tissue ablation. The magnitude of the CBE as a function of temperature obtained without compensation is stronger than that with compensation, implying that the CBE image without compensation has a better sensitivity to detect temperature. These findings suggest that echo shift tracking and compensation may be unnecessary in practice, thus simplifying the algorithm required to implement real-time CBE imaging. Copyright © 2012 Elsevier B.V. All rights reserved.

Classification of Medical Datasets Using SVMs with Hybrid Evolutionary Algorithms Based on Endocrine-Based Particle Swarm Optimization and Artificial Bee Colony Algorithms.

PubMed

Lin, Kuan-Cheng; Hsieh, Yi-Hsiu

2015-10-01

The classification and analysis of data is an important issue in today's research. Selecting a suitable set of features makes it possible to classify an enormous quantity of data quickly and efficiently. Feature selection is generally viewed as a problem of feature subset selection, such as combination optimization problems. Evolutionary algorithms using random search methods have proven highly effective in obtaining solutions to problems of optimization in a diversity of applications. In this study, we developed a hybrid evolutionary algorithm based on endocrine-based particle swarm optimization (EPSO) and artificial bee colony (ABC) algorithms in conjunction with a support vector machine (SVM) for the selection of optimal feature subsets for the classification of datasets. The results of experiments using specific UCI medical datasets demonstrate that the accuracy of the proposed hybrid evolutionary algorithm is superior to that of basic PSO, EPSO and ABC algorithms, with regard to classification accuracy using subsets with a reduced number of features.

A Swarm Optimization Genetic Algorithm Based on Quantum-Behaved Particle Swarm Optimization.

PubMed

Sun, Tao; Xu, Ming-Hai

2017-01-01

Quantum-behaved particle swarm optimization (QPSO) algorithm is a variant of the traditional particle swarm optimization (PSO). The QPSO that was originally developed for continuous search spaces outperforms the traditional PSO in search ability. This paper analyzes the main factors that impact the search ability of QPSO and converts the particle movement formula to the mutation condition by introducing the rejection region, thus proposing a new binary algorithm, named swarm optimization genetic algorithm (SOGA), because it is more like genetic algorithm (GA) than PSO in form. SOGA has crossover and mutation operator as GA but does not need to set the crossover and mutation probability, so it has fewer parameters to control. The proposed algorithm was tested with several nonlinear high-dimension functions in the binary search space, and the results were compared with those from BPSO, BQPSO, and GA. The experimental results show that SOGA is distinctly superior to the other three algorithms in terms of solution accuracy and convergence.

An improved grey wolf optimizer algorithm for the inversion of geoelectrical data

NASA Astrophysics Data System (ADS)

Li, Si-Yu; Wang, Shu-Ming; Wang, Peng-Fei; Su, Xiao-Lu; Zhang, Xin-Song; Dong, Zhi-Hui

2018-05-01

The grey wolf optimizer (GWO) is a novel bionics algorithm inspired by the social rank and prey-seeking behaviors of grey wolves. The GWO algorithm is easy to implement because of its basic concept, simple formula, and small number of parameters. This paper develops a GWO algorithm with a nonlinear convergence factor and an adaptive location updating strategy and applies this improved grey wolf optimizer (improved grey wolf optimizer, IGWO) algorithm to geophysical inversion problems using magnetotelluric (MT), DC resistivity and induced polarization (IP) methods. Numerical tests in MATLAB 2010b for the forward modeling data and the observed data show that the IGWO algorithm can find the global minimum and rarely sinks to the local minima. For further study, inverted results using the IGWO are contrasted with particle swarm optimization (PSO) and the simulated annealing (SA) algorithm. The outcomes of the comparison reveal that the IGWO and PSO similarly perform better in counterpoising exploration and exploitation with a given number of iterations than the SA.

Transonic Wing Shape Optimization Using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.; Kwak, Dochan (Technical Monitor)

2002-01-01

A method for aerodynamic shape optimization based on a genetic algorithm approach is demonstrated. The algorithm is coupled with a transonic full potential flow solver and is used to optimize the flow about transonic wings including multi-objective solutions that lead to the generation of pareto fronts. The results indicate that the genetic algorithm is easy to implement, flexible in application and extremely reliable.

Solving TSP problem with improved genetic algorithm

NASA Astrophysics Data System (ADS)

Fu, Chunhua; Zhang, Lijun; Wang, Xiaojing; Qiao, Liying

2018-05-01

The TSP is a typical NP problem. The optimization of vehicle routing problem (VRP) and city pipeline optimization can use TSP to solve; therefore it is very important to the optimization for solving TSP problem. The genetic algorithm (GA) is one of ideal methods in solving it. The standard genetic algorithm has some limitations. Improving the selection operator of genetic algorithm, and importing elite retention strategy can ensure the select operation of quality, In mutation operation, using the adaptive algorithm selection can improve the quality of search results and variation, after the chromosome evolved one-way evolution reverse operation is added which can make the offspring inherit gene of parental quality improvement opportunities, and improve the ability of searching the optimal solution algorithm.

System Design under Uncertainty: Evolutionary Optimization of the Gravity Probe-B Spacecraft

NASA Technical Reports Server (NTRS)

Pullen, Samuel P.; Parkinson, Bradford W.

1994-01-01

This paper discusses the application of evolutionary random-search algorithms (Simulated Annealing and Genetic Algorithms) to the problem of spacecraft design under performance uncertainty. Traditionally, spacecraft performance uncertainty has been measured by reliability. Published algorithms for reliability optimization are seldom used in practice because they oversimplify reality. The algorithm developed here uses random-search optimization to allow us to model the problem more realistically. Monte Carlo simulations are used to evaluate the objective function for each trial design solution. These methods have been applied to the Gravity Probe-B (GP-B) spacecraft being developed at Stanford University for launch in 1999, Results of the algorithm developed here for GP-13 are shown, and their implications for design optimization by evolutionary algorithms are discussed.

An Improved Cuckoo Search Optimization Algorithm for the Problem of Chaotic Systems Parameter Estimation

PubMed Central

Wang, Jun; Zhou, Bihua; Zhou, Shudao

2016-01-01

This paper proposes an improved cuckoo search (ICS) algorithm to establish the parameters of chaotic systems. In order to improve the optimization capability of the basic cuckoo search (CS) algorithm, the orthogonal design and simulated annealing operation are incorporated in the CS algorithm to enhance the exploitation search ability. Then the proposed algorithm is used to establish parameters of the Lorenz chaotic system and Chen chaotic system under the noiseless and noise condition, respectively. The numerical results demonstrate that the algorithm can estimate parameters with high accuracy and reliability. Finally, the results are compared with the CS algorithm, genetic algorithm, and particle swarm optimization algorithm, and the compared results demonstrate the method is energy-efficient and superior. PMID:26880874

Optimal design of minimum mean-square error noise reduction algorithms using the simulated annealing technique.

PubMed

Bai, Mingsian R; Hsieh, Ping-Ju; Hur, Kur-Nan

2009-02-01

The performance of the minimum mean-square error noise reduction (MMSE-NR) algorithm in conjunction with time-recursive averaging (TRA) for noise estimation is found to be very sensitive to the choice of two recursion parameters. To address this problem in a more systematic manner, this paper proposes an optimization method to efficiently search the optimal parameters of the MMSE-TRA-NR algorithms. The objective function is based on a regression model, whereas the optimization process is carried out with the simulated annealing algorithm that is well suited for problems with many local optima. Another NR algorithm proposed in the paper employs linear prediction coding as a preprocessor for extracting the correlated portion of human speech. Objective and subjective tests were undertaken to compare the optimized MMSE-TRA-NR algorithm with several conventional NR algorithms. The results of subjective tests were processed by using analysis of variance to justify the statistic significance. A post hoc test, Tukey's Honestly Significant Difference, was conducted to further assess the pairwise difference between the NR algorithms.

Evolutionary Beamforming Optimization for Radio Frequency Charging in Wireless Rechargeable Sensor Networks.

PubMed

Yao, Ke-Han; Jiang, Jehn-Ruey; Tsai, Chung-Hsien; Wu, Zong-Syun

2017-08-20

This paper investigates how to efficiently charge sensor nodes in a wireless rechargeable sensor network (WRSN) with radio frequency (RF) chargers to make the network sustainable. An RF charger is assumed to be equipped with a uniform circular array (UCA) of 12 antennas with the radius λ , where λ is the RF wavelength. The UCA can steer most RF energy in a target direction to charge a specific WRSN node by the beamforming technology. Two evolutionary algorithms (EAs) using the evolution strategy (ES), namely the Evolutionary Beamforming Optimization (EBO) algorithm and the Evolutionary Beamforming Optimization Reseeding (EBO-R) algorithm, are proposed to nearly optimize the power ratio of the UCA beamforming peak side lobe (PSL) and the main lobe (ML) aimed at the given target direction. The proposed algorithms are simulated for performance evaluation and are compared with a related algorithm, called Particle Swarm Optimization Gravitational Search Algorithm-Explore (PSOGSA-Explore), to show their superiority.

Feed-Forward Neural Network Soft-Sensor Modeling of Flotation Process Based on Particle Swarm Optimization and Gravitational Search Algorithm

PubMed Central

Wang, Jie-Sheng; Han, Shuang

2015-01-01

For predicting the key technology indicators (concentrate grade and tailings recovery rate) of flotation process, a feed-forward neural network (FNN) based soft-sensor model optimized by the hybrid algorithm combining particle swarm optimization (PSO) algorithm and gravitational search algorithm (GSA) is proposed. Although GSA has better optimization capability, it has slow convergence velocity and is easy to fall into local optimum. So in this paper, the velocity vector and position vector of GSA are adjusted by PSO algorithm in order to improve its convergence speed and prediction accuracy. Finally, the proposed hybrid algorithm is adopted to optimize the parameters of FNN soft-sensor model. Simulation results show that the model has better generalization and prediction accuracy for the concentrate grade and tailings recovery rate to meet the online soft-sensor requirements of the real-time control in the flotation process. PMID:26583034

Genetic Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization

NASA Technical Reports Server (NTRS)

Holst, Terry L.

2005-01-01

A genetic algorithm approach suitable for solving multi-objective problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding Pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the Pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide Pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved.

Corneal tissue ablation using 6.1 μm quantum cascade laser

NASA Astrophysics Data System (ADS)

Huang, Yong; Kang, Jin U.

2012-03-01

High absorption property of tissues in the IR range (λ> 2 μm) results in effective tissue ablation, especially near 3 μm. In the mid-infrared range, wavelengths of 6.1 μm and 6.45 μm fall into the absorption bands of the amide protein groups Amide-I and Amide-II, respectively. They also coincide with the deformation mode of water, which has an absorption peak at 6.1 μm. This coincidence makes 6.1 μm laser a better ablation tool that has promising effectiveness and minimum collateral damages than 3 μm lasers. In this work, we performed bovine corneal ablation test in-vitro using high-power 6.1μm quantum cascade laser (QCL) operated at pulse mode. Quantum cascade laser has the advantages of low cost, compact size and tunable wavelength, which makes it great alternative Mid-IR light source to conventional tunable free-electron lasers (FEL) for medical applications. Preliminary results show that effective corneal stroma craters were achieved with much less collateral damage in corneal tissue that contains less water. Future study will focus on optimizing the control parameters of QCL to attain neat and precise ablation of corneal tissue and development of high peak power QCL.

Residual energy deposition in dental enamel during IR laser ablation at 2.79, 2.94, 9.6, and 10.6 μm

NASA Astrophysics Data System (ADS)

Ragadio, Jerome N.; Lee, Christian K.; Fried, Daniel

2000-03-01

The objective of this study was to measure the residual heat deposition during laser ablation at those IR laser wavelengths best suited for the removal of dental caries. The principal factor limiting the rate of laser ablation of dental hard tissue is the risk of excessive heat accumulation in the tooth, which has the potential for causing damage to the pulp. Optimal laser ablation systems minimize the residual energy deposition in the tooth by transferring deposited laser energy to kinetic and internal energy of ejected tissue components. The residual heat deposition in the tooth was measured at laser wavelengths of 2.79, 2.94, 9.6 and 10.6 micrometer and pulse widths of 150 ns - 150 microsecond(s) . The residual energy was at a minimum for fluences well above the ablation threshold where it saturates at values from 25 - 70% depending on pulse duration and wavelength for the systems investigated. The lowest values of the residual energy were measured for short (less than 20 microseconds) CO2 laser pulses at 9.6 micrometer and for Q-switched erbium laser pulses. This work was supported by NIH/NIDCR R29DE12091 and the Center for Laser Applications in Medicine, DOE DEFG0398ER62576.

Reflectance confocal microscopy-guided laser ablation of basal cell carcinomas: initial in vivo results

NASA Astrophysics Data System (ADS)

Sierra, Heidy; Cordova, Miguel; Yelamos, Oriol; Chen, Chih-Shan Jason; Rajadhyaksha, Milind

2017-02-01

Laser ablation offers a procedure for precise, fast and minimally invasive removal of superficial and early nodular basal cell carcinomas (BCCs). However, the lack of histopathological confirmation has been a limitation toward widespread use in the clinic. A reflectance confocal microscopy (RCM) imaging-guided laser ablation approach offers cellular-level histopathology-like feedback directly on the patient, which may guide and help improve the efficacy of this procedure. We performed an initial study on 44 BCCs on 21 patients in vivo (based in an ex vivo bench-top study reported in our earlier papers), using a pulsed erbium: ytterbium aluminum garnet laser and a contrast agent (aluminum chloride). Initial 10 lesions, the RCM imaging-guided detection of either presence of residual tumor or complete clearance was immediately confirmed with histopathology. Additionally, 34 BCCs on 15 patients were treated with RCM imaging-guided laser ablation, and the clearance of tumor is currently being monitored with follow-up imaging (i. e., no histopathology) at 3, 6 and 18 months. Thus far, the imaging resolution appears to be sufficient and consistent for monitoring efficacy in the wound, both immediately post-ablation and subsequently during recovery. The efficacy appears to be promising. However, further investigation and optimization to image over the entire wound (without missing any areas) need to be investigated.

Study on mechanical and ablative properties of EPDM/OMMT thermal insulating nanocomposites.

PubMed

Gao, Guoxin; Zhang, Zhicheng; Li, Xuefei; Meng, Qingjie; Zheng, Yuansuo; Jin, Zhihao

2010-11-01

In order to enhance the elongation at break, the ablation resistant properties as well as the tensile strength of the thermal insulating materials, organo-montmorillonite (OMMT) was introduced into the short aramid fibers reinforced Ethylene-Propylene-Diene Monomer (EPDM) based nanocomposites. The effects of OMMT content on the mechanical and ablative properties of the nanocomposites were investigated systematically. X-ray diffraction (XRD) and transmission electron microscopy (TEM) confirm that EPDM-matrix has been intercalated into OMMT interlayers after a mixing process on a two-roll mill. The brittle fracture of nanocomposites also indicates that OMMT can lubricate aramid fiber to weaken the interfacial adhesive strength between the fibers and the matrix. As a result, the tensile strength and elongation at break are both improved sharply with OMMT content increasing from 1 phr to 7 phr. However, thanks to the inevitable agglomeration of OMMT with high loading inside the nanocomposites, the tensile strength and elongation at break reduce gently once OMMT is over 7 phr. Furthermore, the ablation resistant properties are improved greatly by increasing OMMT from 1 phr to 11 phr. Therefore, the optimal content of OMMT is 7-11 phr for the thermal insulating nanocomposites with big elongation and excellent ablation resistant properties.

A Modified Mean Gray Wolf Optimization Approach for Benchmark and Biomedical Problems.

PubMed

Singh, Narinder; Singh, S B

2017-01-01

A modified variant of gray wolf optimization algorithm, namely, mean gray wolf optimization algorithm has been developed by modifying the position update (encircling behavior) equations of gray wolf optimization algorithm. The proposed variant has been tested on 23 standard benchmark well-known test functions (unimodal, multimodal, and fixed-dimension multimodal), and the performance of modified variant has been compared with particle swarm optimization and gray wolf optimization. Proposed algorithm has also been applied to the classification of 5 data sets to check feasibility of the modified variant. The results obtained are compared with many other meta-heuristic approaches, ie, gray wolf optimization, particle swarm optimization, population-based incremental learning, ant colony optimization, etc. The results show that the performance of modified variant is able to find best solutions in terms of high level of accuracy in classification and improved local optima avoidance.

Radiofrequency ablation of retained placenta accreta after conservative management: preliminary evaluation in the pregnant ewe and in normal human placenta in vitro.

PubMed

Morel, O; Monceau, E; Tran, N; Malartic, C; Morel, F; Barranger, E; Côté, J F; Gayat, E; Chavatte-Palmer, P; Cabrol, D; Tsatsaris, V

2009-06-01

To evaluate radiofrequency (RF) efficiency and safety for the ablation of retained placenta in humans, using a pregnant sheep model. Experimental study. Laboratory of Surgery School, Nancy, France. Three pregnant ewes/ten human placentas. Various RF procedures were tested in pregnant ewes on 50 placentomes (individual placental units). Reproducibility of the best procedure was then evaluated in a further 20 placentomes and on ten human term placentas in vitro after delivery. Placental tissues destruction, lesions' size, myometrial lesions. Low power (100 W) and low target temperatures (60 degrees C) lead to homogenous tissue destruction, without myometrial lesion. No significant difference was observed in terms of lesion size and procedure duration for in the placentomes of pregnant ewe in vivo and in human placentas in vitro. The diameter of the ablation could be correlated with the tines deployment. The placental tissue structure is very permissive to RF energy, which suggests that RF could be used for the ablation of retained placenta, providing optimal control of tissue destruction. These results call for further experimental evaluations.

Surface Modification of ICF Target Capsules by Pulsed Laser Ablation

DOE PAGES

Carlson, Lane C.; Johnson, Michael A.; Bunn, Thomas L.

2016-06-30

Topographical modifications of spherical surfaces are imprinted on National Ignition Facility (NIF) target capsules by extending the capabilities of a recently developed full surface (4π) laser ablation and mapping apparatus. The laser ablation method combines the precision, energy density and long reach of a focused laser beam to pre-impose sinusoidal modulations on the outside surface of High Density Carbon (HDC) capsules and the inside surface of Glow Discharge Polymer (GDP) capsules. Sinusoidal modulations described in this paper have sub-micron to 10’s of microns vertical scale and wavelengths as small as 30 μm and as large as 200 μm. The modulatedmore » patterns are created by rastering a focused laser fired at discrete capsule surface locations for a specified number of pulses. The computer program developed to create these raster patterns uses inputs such as laser beam intensity profile, the material removal function, the starting surface figure and the desired surface figure. The patterns are optimized to minimize surface roughness. Lastly, in this paper, simulated surfaces are compared with actual ablated surfaces measured using confocal microscopy.« less

IR-MALDESI MASS SPECTROMETRY IMAGING OF BIOLOGICAL TISSUE SECTIONS USING ICE AS A MATRIX

PubMed Central

Robichaud, Guillaume; Barry, Jeremy A.; Muddiman, David C.

2014-01-01

Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) Mass Spectrometry imaging of biological tissue sections using a layer of deposited ice as an energy absorbing matrix was investigated. Dynamics of plume ablation were first explored using a nanosecond exposure shadowgraphy system designed to simultaneously collect pictures of the plume with a camera and collect the FT-ICR mass spectrum corresponding to that same ablation event. Ablation of fresh tissue analyzed with and without using ice as a matrix were both compared using this technique. Effect of spot-to-spot distance, number of laser shots per pixel and tissue condition (matrix) on ion abundance was also investigated for 50 µm thick tissue sections. Finally, the statistical method called design of experiments was used to compare source parameters and determine the optimal conditions for IR-MALDESI of tissue sections using deposited ice as a matrix. With a better understanding of the fundamentals of ablation dynamics and a systematic approach to explore the experimental space, it was possible to improve ion abundance by nearly one order of magnitude. PMID:24385399

Loading of mass spectrometry ion trap with Th ions by laser ablation for nuclear frequency standard application.

PubMed

Borisyuk, Petr V; Derevyashkin, Sergey P; Khabarova, Ksenia Y; Kolachevsky, Nikolay N; Lebedinsky, Yury Y; Poteshin, Sergey S; Sysoev, Alexey A; Tkalya, Evgeny V; Tregubov, Dmitry O; Troyan, Viktor I; Vasiliev, Oleg S; Yakovlev, Valery P; Yudin, Valery I

2017-08-01

We describe an original multisectional quadrupole ion trap aimed to realize nuclear frequency standard based on the unique isomer transition in thorium nucleus. It is shown that the system effectively operates on Th + , Th 2+ and Th 3+ ions produced by laser ablation of metallic thorium-232 target. Laser intensity used for ablation is about 6 GW/cm 2 . Via applying a bias potential to every control voltage including the RF one, we are able not only to manipulate ions within the energy range as wide as 1-500 eV but to specially adjust trap potentials in order to work mainly with ions that belong to energy distribution maximum and therefore to effectively enhance the number of trapped ions. Measurement of energy distributions of 232 Th + , 232 Th 2+ , 232 Th 3+ ions obtained by laser ablation allows us to define optimal potential values for trapping process. Observed number of ions inside trap in dependence on trapping time is found to obey an unusually slow - logarithmic decay law that needs more careful study.

All fiber cladding mode stripper with uniform heat distribution and high cladding light loss manufactured by CO2 laser ablation

NASA Astrophysics Data System (ADS)

Jebali, M. A.; Basso, E. T.

2018-02-01

Cladding mode strippers are primarily used at the end of a fiber laser cavity to remove high-power excess cladding light without inducing core loss and beam quality degradation. Conventional manufacturing methods of cladding mode strippers include acid etching, abrasive blasting or laser ablation. Manufacturing of cladding mode strippers using laser ablation consist of removing parts of the cladding by fused silica ablation with a controlled penetration and shape. We present and characterize an optimized cladding mode stripper design that increases the cladding light loss with a minimal device length and manufacturing time. This design reduces the localized heat generation by improving the heat distribution along the device. We demonstrate a cladding mode stripper written on a 400um fiber with cladding light loss of 20dB, with less than 0.02dB loss in the core and minimal heating of the fiber and coating. The manufacturing process of the designed component is fully automated and takes less than 3 minutes with a very high throughput yield.

A Novel Hybrid Firefly Algorithm for Global Optimization.

PubMed

Zhang, Lina; Liu, Liqiang; Yang, Xin-She; Dai, Yuntao

Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA), is proposed by combining the advantages of both the firefly algorithm (FA) and differential evolution (DE). FA and DE are executed in parallel to promote information sharing among the population and thus enhance searching efficiency. In order to evaluate the performance and efficiency of the proposed algorithm, a diverse set of selected benchmark functions are employed and these functions fall into two groups: unimodal and multimodal. The experimental results show better performance of the proposed algorithm compared to the original version of the firefly algorithm (FA), differential evolution (DE) and particle swarm optimization (PSO) in the sense of avoiding local minima and increasing the convergence rate.

A Novel Hybrid Firefly Algorithm for Global Optimization

PubMed Central

Zhang, Lina; Liu, Liqiang; Yang, Xin-She; Dai, Yuntao

2016-01-01

Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA), is proposed by combining the advantages of both the firefly algorithm (FA) and differential evolution (DE). FA and DE are executed in parallel to promote information sharing among the population and thus enhance searching efficiency. In order to evaluate the performance and efficiency of the proposed algorithm, a diverse set of selected benchmark functions are employed and these functions fall into two groups: unimodal and multimodal. The experimental results show better performance of the proposed algorithm compared to the original version of the firefly algorithm (FA), differential evolution (DE) and particle swarm optimization (PSO) in the sense of avoiding local minima and increasing the convergence rate. PMID:27685869

A preliminary study to metaheuristic approach in multilayer radiation shielding optimization

NASA Astrophysics Data System (ADS)

Arif Sazali, Muhammad; Rashid, Nahrul Khair Alang Md; Hamzah, Khaidzir

2018-01-01

Metaheuristics are high-level algorithmic concepts that can be used to develop heuristic optimization algorithms. One of their applications is to find optimal or near optimal solutions to combinatorial optimization problems (COPs) such as scheduling, vehicle routing, and timetabling. Combinatorial optimization deals with finding optimal combinations or permutations in a given set of problem components when exhaustive search is not feasible. A radiation shield made of several layers of different materials can be regarded as a COP. The time taken to optimize the shield may be too high when several parameters are involved such as the number of materials, the thickness of layers, and the arrangement of materials. Metaheuristics can be applied to reduce the optimization time, trading guaranteed optimal solutions for near-optimal solutions in comparably short amount of time. The application of metaheuristics for radiation shield optimization is lacking. In this paper, we present a review on the suitability of using metaheuristics in multilayer shielding design, specifically the genetic algorithm and ant colony optimization algorithm (ACO). We would also like to propose an optimization model based on the ACO method.

Seeding the initial population with feasible solutions in metaheuristic optimization of steel trusses

NASA Astrophysics Data System (ADS)

Kazemzadeh Azad, Saeid

2018-01-01

In spite of considerable research work on the development of efficient algorithms for discrete sizing optimization of steel truss structures, only a few studies have addressed non-algorithmic issues affecting the general performance of algorithms. For instance, an important question is whether starting the design optimization from a feasible solution is fruitful or not. This study is an attempt to investigate the effect of seeding the initial population with feasible solutions on the general performance of metaheuristic techniques. To this end, the sensitivity of recently proposed metaheuristic algorithms to the feasibility of initial candidate designs is evaluated through practical discrete sizing of real-size steel truss structures. The numerical experiments indicate that seeding the initial population with feasible solutions can improve the computational efficiency of metaheuristic structural optimization algorithms, especially in the early stages of the optimization. This paves the way for efficient metaheuristic optimization of large-scale structural systems.

Joint Optimization of Receiver Placement and Illuminator Selection for a Multiband Passive Radar Network.

PubMed

Xie, Rui; Wan, Xianrong; Hong, Sheng; Yi, Jianxin

2017-06-14

The performance of a passive radar network can be greatly improved by an optimal radar network structure. Generally, radar network structure optimization consists of two aspects, namely the placement of receivers in suitable places and selection of appropriate illuminators. The present study investigates issues concerning the joint optimization of receiver placement and illuminator selection for a passive radar network. Firstly, the required radar cross section (RCS) for target detection is chosen as the performance metric, and the joint optimization model boils down to the partition p -center problem (PPCP). The PPCP is then solved by a proposed bisection algorithm. The key of the bisection algorithm lies in solving the partition set covering problem (PSCP), which can be solved by a hybrid algorithm developed by coupling the convex optimization with the greedy dropping algorithm. In the end, the performance of the proposed algorithm is validated via numerical simulations.

Modified Shuffled Frog Leaping Optimization Algorithm Based Distributed Generation Rescheduling for Loss Minimization

NASA Astrophysics Data System (ADS)

Arya, L. D.; Koshti, Atul

2018-05-01

This paper investigates the Distributed Generation (DG) capacity optimization at location based on the incremental voltage sensitivity criteria for sub-transmission network. The Modified Shuffled Frog Leaping optimization Algorithm (MSFLA) has been used to optimize the DG capacity. Induction generator model of DG (wind based generating units) has been considered for study. Standard test system IEEE-30 bus has been considered for the above study. The obtained results are also validated by shuffled frog leaping algorithm and modified version of bare bones particle swarm optimization (BBExp). The performance of MSFLA has been found more efficient than the other two algorithms for real power loss minimization problem.

Multiobjective Aerodynamic Shape Optimization Using Pareto Differential Evolution and Generalized Response Surface Metamodels

NASA Technical Reports Server (NTRS)

Madavan, Nateri K.

2004-01-01

Differential Evolution (DE) is a simple, fast, and robust evolutionary algorithm that has proven effective in determining the global optimum for several difficult single-objective optimization problems. The DE algorithm has been recently extended to multiobjective optimization problem by using a Pareto-based approach. In this paper, a Pareto DE algorithm is applied to multiobjective aerodynamic shape optimization problems that are characterized by computationally expensive objective function evaluations. To improve computational expensive the algorithm is coupled with generalized response surface meta-models based on artificial neural networks. Results are presented for some test optimization problems from the literature to demonstrate the capabilities of the method.

Modified harmony search

NASA Astrophysics Data System (ADS)

Mohamed, Najihah; Lutfi Amri Ramli, Ahmad; Majid, Ahmad Abd; Piah, Abd Rahni Mt

2017-09-01

A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in many areas. HS is a derivative-free real parameter optimization algorithm, and draws an inspiration from the musical improvisation process of searching for a perfect state of harmony. Propose in this paper Modified Harmony Search for solving optimization problems, which employs a concept from genetic algorithm method and particle swarm optimization for generating new solution vectors that enhances the performance of HS algorithm. The performances of MHS and HS are investigated on ten benchmark optimization problems in order to make a comparison to reflect the efficiency of the MHS in terms of final accuracy, convergence speed and robustness.

MULTI-OBJECTIVE OPTIMAL DESIGN OF GROUNDWATER REMEDIATION SYSTEMS: APPLICATION OF THE NICHED PARETO GENETIC ALGORITHM (NPGA). (R826614)

EPA Science Inventory

A multiobjective optimization algorithm is applied to a groundwater quality management problem involving remediation by pump-and-treat (PAT). The multiobjective optimization framework uses the niched Pareto genetic algorithm (NPGA) and is applied to simultaneously minimize the...

Structural damage identification using an enhanced thermal exchange optimization algorithm

NASA Astrophysics Data System (ADS)

Kaveh, A.; Dadras, A.

2018-03-01

The recently developed optimization algorithm-the so-called thermal exchange optimization (TEO) algorithm-is enhanced and applied to a damage detection problem. An offline parameter tuning approach is utilized to set the internal parameters of the TEO, resulting in the enhanced heat transfer optimization (ETEO) algorithm. The damage detection problem is defined as an inverse problem, and ETEO is applied to a wide range of structures. Several scenarios with noise and noise-free modal data are tested and the locations and extents of damages are identified with good accuracy.

Radiofrequency ablation combined with transcatheter arterial embolisation in rabbit liver: investigation of the ablation zone according to the time interval between the two therapies.

PubMed

Lee, I J; Kim, Y I; Kim, K W; Kim, D H; Ryoo, I; Lee, M W; Chung, J W

2012-11-01

This study was designed to evaluate the extent of the radiofrequency ablation zone in relation to the time interval between transcatheter arterial embolisation (TAE) and radiofrequency ablation (RFA) and, ultimately, to determine the optimal strategy of combining these two therapies for hepatocellular carcinoma. 15 rabbits were evenly divided into three groups: Group A was treated with RFA alone; Group B was treated with TAE immediately followed by RFA; and Group C was treated with TAE followed by RFA 5 days later. All animals underwent perfusion CT (PCT) scans immediately after RFA. Serum liver transaminases were measured to evaluate acute liver damage. Animals were euthanised for pathological analysis of ablated tissues 10 days after RFA. Non-parametric analyses were conducted to compare PCT indices, the RFA zone and liver transaminase levels among the three experimental groups. Group B showed a significantly larger ablation zone than the other two groups. Arterial liver perfusion and hepatic perfusion index represented well the perfusion decrease after TAE on PCT. Although Group B showed the most elevated liver transaminase levels at 1 day post RFA, the enzymes decreased to levels that were not different from the other groups at 10 days post-RFA. When combined TAE and RFA therapy is considered, TAE should be followed by RFA as quickly as possible, as it can be performed safely without serious hepatic deterioration, despite the short interval between the two procedures.

Time-resolved Measurements of ICF Capsule Ablator Properties by Streaked X-Ray Radiography

NASA Astrophysics Data System (ADS)

Hicks, Damien

2008-11-01

Determining the capsule ablator thickness and peak laser or x-ray drive pressure required to optimize fuel compression is a critical part of ensuring ICF ignition on the NIF. If too little ablator is burned off, the implosion velocity will be too low for adequate final compression; if too much ablator is burned off, the fuel will be preheated or the shell will be broken up by growth of hydrodynamic instabilities, again compromising compression. Avoiding such failure modes requires having an accurate, in-flight measure of the implosion velocity, areal density, and remaining mass of the ablator near peak velocity. We present a new technique which achieves simultaneous time-resolved measurements of all these parameters in a single, area-backlit, x-ray streaked radiograph. This is accomplished by tomographic inversion of the radiograph to determine the radial density profile at each time step; scalar quantities such as the average position, areal density, and mass of the ablator can then be calculated by taking moments of this density profile. Details of the successful demonstration of this technique using backlit Cu-doped Be capsule implosions at the Omega facility will be presented. This work was performed under the auspices of the U.S.Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344 and in collaboration with Brian Spears, David Braun, Peter Celliers, Gilbert Collins, and Otto Landen at LLNL and Rick Olson at SNL.

HEURISTIC OPTIMIZATION AND ALGORITHM TUNING APPLIED TO SORPTIVE BARRIER DESIGN

EPA Science Inventory

While heuristic optimization is applied in environmental applications, ad-hoc algorithm configuration is typical. We use a multi-layer sorptive barrier design problem as a benchmark for an algorithm-tuning procedure, as applied to three heuristics (genetic algorithms, simulated ...

An optimized BP neural network based on genetic algorithm for static decoupling of a six-axis force/torque sensor

NASA Astrophysics Data System (ADS)

Fu, Liyue; Song, Aiguo

2018-02-01

In order to improve the measurement precision of 6-axis force/torque sensor for robot, BP decoupling algorithm optimized by GA (GA-BP algorithm) is proposed in this paper. The weights and thresholds of a BP neural network with 6-10-6 topology are optimized by GA to develop decouple a six-axis force/torque sensor. By comparison with other traditional decoupling algorithm, calculating the pseudo-inverse matrix of calibration and classical BP algorithm, the decoupling results validate the good decoupling performance of GA-BP algorithm and the coupling errors are reduced.

A novel metaheuristic for continuous optimization problems: Virus optimization algorithm

NASA Astrophysics Data System (ADS)

Liang, Yun-Chia; Rodolfo Cuevas Juarez, Josue

2016-01-01

A novel metaheuristic for continuous optimization problems, named the virus optimization algorithm (VOA), is introduced and investigated. VOA is an iteratively population-based method that imitates the behaviour of viruses attacking a living cell. The number of viruses grows at each replication and is controlled by an immune system (a so-called 'antivirus') to prevent the explosive growth of the virus population. The viruses are divided into two classes (strong and common) to balance the exploitation and exploration effects. The performance of the VOA is validated through a set of eight benchmark functions, which are also subject to rotation and shifting effects to test its robustness. Extensive comparisons were conducted with over 40 well-known metaheuristic algorithms and their variations, such as artificial bee colony, artificial immune system, differential evolution, evolutionary programming, evolutionary strategy, genetic algorithm, harmony search, invasive weed optimization, memetic algorithm, particle swarm optimization and simulated annealing. The results showed that the VOA is a viable solution for continuous optimization.

Cost optimization of reinforced concrete cantilever retaining walls under seismic loading using a biogeography-based optimization algorithm with Levy flights

NASA Astrophysics Data System (ADS)

Aydogdu, Ibrahim

2017-03-01

In this article, a new version of a biogeography-based optimization algorithm with Levy flight distribution (LFBBO) is introduced and used for the optimum design of reinforced concrete cantilever retaining walls under seismic loading. The cost of the wall is taken as an objective function, which is minimized under the constraints implemented by the American Concrete Institute (ACI 318-05) design code and geometric limitations. The influence of peak ground acceleration (PGA) on optimal cost is also investigated. The solution of the problem is attained by the LFBBO algorithm, which is developed by adding Levy flight distribution to the mutation part of the biogeography-based optimization (BBO) algorithm. Five design examples, of which two are used in literature studies, are optimized in the study. The results are compared to test the performance of the LFBBO and BBO algorithms, to determine the influence of the seismic load and PGA on the optimal cost of the wall.

Optimal pattern synthesis for speech recognition based on principal component analysis

NASA Astrophysics Data System (ADS)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

Pulmonary Nodule Recognition Based on Multiple Kernel Learning Support Vector Machine-PSO

PubMed Central

Zhu, Zhichuan; Zhao, Qingdong; Liu, Liwei; Zhang, Lijuan

2018-01-01

Pulmonary nodule recognition is the core module of lung CAD. The Support Vector Machine (SVM) algorithm has been widely used in pulmonary nodule recognition, and the algorithm of Multiple Kernel Learning Support Vector Machine (MKL-SVM) has achieved good results therein. Based on grid search, however, the MKL-SVM algorithm needs long optimization time in course of parameter optimization; also its identification accuracy depends on the fineness of grid. In the paper, swarm intelligence is introduced and the Particle Swarm Optimization (PSO) is combined with MKL-SVM algorithm to be MKL-SVM-PSO algorithm so as to realize global optimization of parameters rapidly. In order to obtain the global optimal solution, different inertia weights such as constant inertia weight, linear inertia weight, and nonlinear inertia weight are applied to pulmonary nodules recognition. The experimental results show that the model training time of the proposed MKL-SVM-PSO algorithm is only 1/7 of the training time of the MKL-SVM grid search algorithm, achieving better recognition effect. Moreover, Euclidean norm of normalized error vector is proposed to measure the proximity between the average fitness curve and the optimal fitness curve after convergence. Through statistical analysis of the average of 20 times operation results with different inertial weights, it can be seen that the dynamic inertial weight is superior to the constant inertia weight in the MKL-SVM-PSO algorithm. In the dynamic inertial weight algorithm, the parameter optimization time of nonlinear inertia weight is shorter; the average fitness value after convergence is much closer to the optimal fitness value, which is better than the linear inertial weight. Besides, a better nonlinear inertial weight is verified. PMID:29853983

Pulmonary Nodule Recognition Based on Multiple Kernel Learning Support Vector Machine-PSO.

PubMed

Li, Yang; Zhu, Zhichuan; Hou, Alin; Zhao, Qingdong; Liu, Liwei; Zhang, Lijuan

2018-01-01

Pulmonary nodule recognition is the core module of lung CAD. The Support Vector Machine (SVM) algorithm has been widely used in pulmonary nodule recognition, and the algorithm of Multiple Kernel Learning Support Vector Machine (MKL-SVM) has achieved good results therein. Based on grid search, however, the MKL-SVM algorithm needs long optimization time in course of parameter optimization; also its identification accuracy depends on the fineness of grid. In the paper, swarm intelligence is introduced and the Particle Swarm Optimization (PSO) is combined with MKL-SVM algorithm to be MKL-SVM-PSO algorithm so as to realize global optimization of parameters rapidly. In order to obtain the global optimal solution, different inertia weights such as constant inertia weight, linear inertia weight, and nonlinear inertia weight are applied to pulmonary nodules recognition. The experimental results show that the model training time of the proposed MKL-SVM-PSO algorithm is only 1/7 of the training time of the MKL-SVM grid search algorithm, achieving better recognition effect. Moreover, Euclidean norm of normalized error vector is proposed to measure the proximity between the average fitness curve and the optimal fitness curve after convergence. Through statistical analysis of the average of 20 times operation results with different inertial weights, it can be seen that the dynamic inertial weight is superior to the constant inertia weight in the MKL-SVM-PSO algorithm. In the dynamic inertial weight algorithm, the parameter optimization time of nonlinear inertia weight is shorter; the average fitness value after convergence is much closer to the optimal fitness value, which is better than the linear inertial weight. Besides, a better nonlinear inertial weight is verified.

Research on cutting path optimization of sheet metal parts based on ant colony algorithm

NASA Astrophysics Data System (ADS)

Wu, Z. Y.; Ling, H.; Li, L.; Wu, L. H.; Liu, N. B.

2017-09-01

In view of the disadvantages of the current cutting path optimization methods of sheet metal parts, a new method based on ant colony algorithm was proposed in this paper. The cutting path optimization problem of sheet metal parts was taken as the research object. The essence and optimization goal of the optimization problem were presented. The traditional serial cutting constraint rule was improved. The cutting constraint rule with cross cutting was proposed. The contour lines of parts were discretized and the mathematical model of cutting path optimization was established. Thus the problem was converted into the selection problem of contour lines of parts. Ant colony algorithm was used to solve the problem. The principle and steps of the algorithm were analyzed.

Laser ablation U-Th-Sm/He dating of detrital apatite

NASA Astrophysics Data System (ADS)

Guest, B.; Pickering, J. E.; Matthews, W.; Hamilton, B.; Sykes, C.

2016-12-01

Detrital apatite U-Th-Sm/He thermochronology has the potential to be a powerful tool for conducting basin thermal history analyses as well as complementing the well-established detrital zircon U-Pb approach in source to sink studies. A critical roadblock that prevents the routine application of detrital apatite U-Th-Sm/He thermochronology to solving geological problems is the costly and difficult whole grain approach that is generally used to obtain apatite U-Th-Sm/He data. We present a new analytical method for laser ablation thermochronology on apatite. Samples are ablated using a Resonetics™ 193 nm excimer laser and liberated 4He is measured using an ASI (Australian Scientific Instruments) Alphachron™ quadrupole mass spectrometer system; collectively known as the Resochron™. The ablated sites are imaged using a Zygo ZescopeTM optical profilometer and ablated pit volume measured using PitVol, a custom MatLabTM algorithm. The accuracy and precision of the method presented here was confirmed using well-characterized Durango apatite and Fish Canyon Tuff (FCT) apatite reference materials, with Durango apatite used as a primary reference and FCT apatite used as a secondary reference. The weighted average of our laser ablation Durango ages (30.5±0.35 Ma) compare well with ages obtained using conventional whole grain degassing and dissolution U-Th-Sm/He methods (32.56±0.43 Ma) (Jonckheere et.al., 1 993; Farley, 2000; McDowell et.al., 2005) for chips of the same Durango crystal. These Durango ages were used to produce a K-value to correct the secondary references and unknown samples. After correction, FCT apatite has a weighted average age of 28.37 ± 0.96 Ma, which agrees well with published ages. As a further test of this new method we have conducted a case study on a set of samples from the British Mountains of the Yukon Territory in NW Canada. Sandstone samples collected across the British Mountains were analyzed using conventional U-Th-Sm/He whole grain methods and then reanalyzed using our new Laser ablation approach. The laser ablation results are consistent with those obtained using conventional methods, confirming that apatite laser ablation U-Th-Sm/He thermochronology is a viable alternative for collecting large low temperature thermochronology data sets from detrital samples.

Algorithms for the optimization of RBE-weighted dose in particle therapy.

PubMed

Horcicka, M; Meyer, C; Buschbacher, A; Durante, M; Krämer, M

2013-01-21

We report on various algorithms used for the nonlinear optimization of RBE-weighted dose in particle therapy. Concerning the dose calculation carbon ions are considered and biological effects are calculated by the Local Effect Model. Taking biological effects fully into account requires iterative methods to solve the optimization problem. We implemented several additional algorithms into GSI's treatment planning system TRiP98, like the BFGS-algorithm and the method of conjugated gradients, in order to investigate their computational performance. We modified textbook iteration procedures to improve the convergence speed. The performance of the algorithms is presented by convergence in terms of iterations and computation time. We found that the Fletcher-Reeves variant of the method of conjugated gradients is the algorithm with the best computational performance. With this algorithm we could speed up computation times by a factor of 4 compared to the method of steepest descent, which was used before. With our new methods it is possible to optimize complex treatment plans in a few minutes leading to good dose distributions. At the end we discuss future goals concerning dose optimization issues in particle therapy which might benefit from fast optimization solvers.

Algorithms for the optimization of RBE-weighted dose in particle therapy

NASA Astrophysics Data System (ADS)

Horcicka, M.; Meyer, C.; Buschbacher, A.; Durante, M.; Krämer, M.

2013-01-01

We report on various algorithms used for the nonlinear optimization of RBE-weighted dose in particle therapy. Concerning the dose calculation carbon ions are considered and biological effects are calculated by the Local Effect Model. Taking biological effects fully into account requires iterative methods to solve the optimization problem. We implemented several additional algorithms into GSI's treatment planning system TRiP98, like the BFGS-algorithm and the method of conjugated gradients, in order to investigate their computational performance. We modified textbook iteration procedures to improve the convergence speed. The performance of the algorithms is presented by convergence in terms of iterations and computation time. We found that the Fletcher-Reeves variant of the method of conjugated gradients is the algorithm with the best computational performance. With this algorithm we could speed up computation times by a factor of 4 compared to the method of steepest descent, which was used before. With our new methods it is possible to optimize complex treatment plans in a few minutes leading to good dose distributions. At the end we discuss future goals concerning dose optimization issues in particle therapy which might benefit from fast optimization solvers.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tumuluru, Jaya Shankar; McCulloch, Richard Chet James

In this work a new hybrid genetic algorithm was developed which combines a rudimentary adaptive steepest ascent hill climbing algorithm with a sophisticated evolutionary algorithm in order to optimize complex multivariate design problems. By combining a highly stochastic algorithm (evolutionary) with a simple deterministic optimization algorithm (adaptive steepest ascent) computational resources are conserved and the solution converges rapidly when compared to either algorithm alone. In genetic algorithms natural selection is mimicked by random events such as breeding and mutation. In the adaptive steepest ascent algorithm each variable is perturbed by a small amount and the variable that caused the mostmore » improvement is incremented by a small step. If the direction of most benefit is exactly opposite of the previous direction with the most benefit then the step size is reduced by a factor of 2, thus the step size adapts to the terrain. A graphical user interface was created in MATLAB to provide an interface between the hybrid genetic algorithm and the user. Additional features such as bounding the solution space and weighting the objective functions individually are also built into the interface. The algorithm developed was tested to optimize the functions developed for a wood pelleting process. Using process variables (such as feedstock moisture content, die speed, and preheating temperature) pellet properties were appropriately optimized. Specifically, variables were found which maximized unit density, bulk density, tapped density, and durability while minimizing pellet moisture content and specific energy consumption. The time and computational resources required for the optimization were dramatically decreased using the hybrid genetic algorithm when compared to MATLAB's native evolutionary optimization tool.« less

Discrete size optimization of steel trusses using a refined big bang-big crunch algorithm

NASA Astrophysics Data System (ADS)

Hasançebi, O.; Kazemzadeh Azad, S.

2014-01-01

This article presents a methodology that provides a method for design optimization of steel truss structures based on a refined big bang-big crunch (BB-BC) algorithm. It is shown that a standard formulation of the BB-BC algorithm occasionally falls short of producing acceptable solutions to problems from discrete size optimum design of steel trusses. A reformulation of the algorithm is proposed and implemented for design optimization of various discrete truss structures according to American Institute of Steel Construction Allowable Stress Design (AISC-ASD) specifications. Furthermore, the performance of the proposed BB-BC algorithm is compared to its standard version as well as other well-known metaheuristic techniques. The numerical results confirm the efficiency of the proposed algorithm in practical design optimization of truss structures.

Cognitive Nonlinear Radar

DTIC Science & Technology

2013-01-01

intelligently selecting waveform parameters using adaptive algorithms. The adaptive algorithms optimize the waveform parameters based on (1) the EM...the environment. 15. SUBJECT TERMS cognitive radar, adaptive sensing, spectrum sensing, multi-objective optimization, genetic algorithms, machine...detection and classification block diagram. .........................................................6 Figure 5. Genetic algorithm block diagram

Integrated controls design optimization

DOEpatents

Lou, Xinsheng; Neuschaefer, Carl H.

2015-09-01

A control system (207) for optimizing a chemical looping process of a power plant includes an optimizer (420), an income algorithm (230) and a cost algorithm (225) and a chemical looping process models. The process models are used to predict the process outputs from process input variables. Some of the process in puts and output variables are related to the income of the plant; and some others are related to the cost of the plant operations. The income algorithm (230) provides an income input to the optimizer (420) based on a plurality of input parameters (215) of the power plant. The cost algorithm (225) provides a cost input to the optimizer (420) based on a plurality of output parameters (220) of the power plant. The optimizer (420) determines an optimized operating parameter solution based on at least one of the income input and the cost input, and supplies the optimized operating parameter solution to the power plant.

Particle Swarm Optimization

NASA Technical Reports Server (NTRS)

Venter, Gerhard; Sobieszczanski-Sobieski Jaroslaw

2002-01-01

The purpose of this paper is to show how the search algorithm known as particle swarm optimization performs. Here, particle swarm optimization is applied to structural design problems, but the method has a much wider range of possible applications. The paper's new contributions are improvements to the particle swarm optimization algorithm and conclusions and recommendations as to the utility of the algorithm, Results of numerical experiments for both continuous and discrete applications are presented in the paper. The results indicate that the particle swarm optimization algorithm does locate the constrained minimum design in continuous applications with very good precision, albeit at a much higher computational cost than that of a typical gradient based optimizer. However, the true potential of particle swarm optimization is primarily in applications with discrete and/or discontinuous functions and variables. Additionally, particle swarm optimization has the potential of efficient computation with very large numbers of concurrently operating processors.

A Danger-Theory-Based Immune Network Optimization Algorithm

PubMed Central

Li, Tao; Xiao, Xin; Shi, Yuanquan

2013-01-01

Existing artificial immune optimization algorithms reflect a number of shortcomings, such as premature convergence and poor local search ability. This paper proposes a danger-theory-based immune network optimization algorithm, named dt-aiNet. The danger theory emphasizes that danger signals generated from changes of environments will guide different levels of immune responses, and the areas around danger signals are called danger zones. By defining the danger zone to calculate danger signals for each antibody, the algorithm adjusts antibodies' concentrations through its own danger signals and then triggers immune responses of self-regulation. So the population diversity can be maintained. Experimental results show that the algorithm has more advantages in the solution quality and diversity of the population. Compared with influential optimization algorithms, CLONALG, opt-aiNet, and dopt-aiNet, the algorithm has smaller error values and higher success rates and can find solutions to meet the accuracies within the specified function evaluation times. PMID:23483853

Algorithm comparison for schedule optimization in MR fingerprinting.

PubMed

Cohen, Ouri; Rosen, Matthew S

2017-09-01

In MR Fingerprinting, the flip angles and repetition times are chosen according to a pseudorandom schedule. In previous work, we have shown that maximizing the discrimination between different tissue types by optimizing the acquisition schedule allows reductions in the number of measurements required. The ideal optimization algorithm for this application remains unknown, however. In this work we examine several different optimization algorithms to determine the one best suited for optimizing MR Fingerprinting acquisition schedules. Copyright © 2017 Elsevier Inc. All rights reserved.

A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

PubMed

Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

2017-10-01

The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

Ex Vivo Characterization of Canine Liver Tissue Viscoelasticity Following High Intensity Focused Ultrasound (HIFU) Ablation

PubMed Central

Shahmirzadi, Danial; Hou, Gary Y.; Chen, Jiangang; Konofagou, Elisa E.

2014-01-01

Elasticity imaging has shown great promise in detecting High Intensity Focused Ultrasound (HIFU) lesions based on their distinct biomechanical properties. However, quantitative mechanical properties of the tissue and the optimal intensity for obtaining the best contrast parameters remain scarce. In this study, fresh canine livers were ablated using combinations of ISPTA intensities of 5.55, 7.16 and 9.07 kW/cm2 and time durations of 10 and 30 s ex vivo; leading to six groups of ablated tissues. Biopsy samples were then interrogated using dynamic shear mechanical testing within the range of 0.1-10 Hz to characterize the post-ablation tissue viscoelastic properties. All mechanical parameters were found to be frequency dependent. Compared to the unablated cases, all six groups of ablated tissues showed statistically-significant higher complex shear modulus and shear viscosity. However, among the ablated groups, both complex shear modulus and shear viscosity were found to monotonically increase in groups 1-4 (5.55 kW/cm2 for 10 s, 7.16 kW/cm2 for 10 s, 9.07 kW/cm2 & 10 s, and 5.55 kW/cm2 & 30 s, respectively), but decrease in groups 5 and 6 (7.16 kW/cm2 for 30 s, and 9.07 kW/cm2 for 30 s, respectively). For groups 5 and 6, the temperature was expected to exceed the boiling point, and therefore, the decreased stiffening could be due to the compromised integrity of the tissue microstructure. Future studies are needed to estimate the tissue mechanical properties in vivo and perform real-time monitoring of tissue alterations during ablation. PMID:24315395

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lorenz, Matthias; Ovchinnikova, Olga S; Van Berkel, Gary J

RATIONALE: Laser ablation provides for the possibility of sampling a large variety of surfaces with high spatial resolution. This type of sampling when employed in conjunction with liquid capture followed by nanoelectrospray ionization provides the opportunity for sensitive and prolonged interrogation of samples by mass spectrometry as well as the ability to analyze surfaces not amenable to direct liquid extraction. METHODS: A fully automated, reflection geometry, laser ablation liquid capture spot sampling system was achieved by incorporating appropriate laser fiber optics and a focusing lens into a commercially available, liquid extraction surface analysis (LESA ) ready Advion TriVersa NanoMate system.more » RESULTS: Under optimized conditions about 10% of laser ablated material could be captured in a droplet positioned vertically over the ablation region using the NanoMate robot controlled pipette. The sampling spot size area with this laser ablation liquid capture surface analysis (LA/LCSA) mode of operation (typically about 120 m x 160 m) was approximately 50 times smaller than that achievable by direct liquid extraction using LESA (ca. 1 mm diameter liquid extraction spot). The set-up was successfully applied for the analysis of ink on glass and paper as well as the endogenous components in Alstroemeria Yellow King flower petals. In a second mode of operation with a comparable sampling spot size, termed laser ablation/LESA , the laser system was used to drill through, penetrate, or otherwise expose material beneath a solvent resistant surface. Once drilled, LESA was effective in sampling soluble material exposed at that location on the surface. CONCLUSIONS: Incorporating the capability for different laser ablation liquid capture spot sampling modes of operation into a LESA ready Advion TriVersa NanoMate enhanced the spot sampling spatial resolution of this device and broadened the surface types amenable to analysis to include absorbent and solvent resistant materials.« less

BIOPHYSICAL PARAMETERS DURING RADIOFREQUENCY CATHETER ABLATION OF SCAR-MEDIATED VENTRICULAR TACHYCARDIA: EPICARDIAL AND ENDOCARDIAL APPLICATIONS VIA MANUAL AND MAGNETIC NAVIGATION

PubMed Central

Bourke, Tara; Buch, Eric; Mathuria, Nilesh; Michowitz, Yoav; Yu, Ricky; Mandapati, Ravi; Shivkumar, Kalyanam; Tung, Roderick

2014-01-01

Background There is a paucity of data on biophysical parameters during radiofrequency ablation of scar-mediated ventricular tachycardia (VT). Methods and Results Data was collected from consecutive patients undergoing VT ablation with open-irrigation. Complete data was available for 372 lesions in 21 patients. The frequency of biophysical parameter changes were: >10Ω reduction (80%), bipolar EGM reduction (69%), while loss of capture was uncommon (32%). Unipolar injury current was seen in 72% of radiofrequency applications. Both EGM reduction and impedance drop were seen in 57% and a change in all 3 parameters was seen in only 20% of lesions. Late potentials were eliminated in 33%, reduced/modified in 56%, and remained after ablation in 11%. Epicardial lesions exhibited an impedance drop (90% vs 76%, p=0.002) and loss of capture (46% vs 27%, p<0.001) more frequently than endocardial lesions. Lesions delivered manually exhibited a >10Ω impedance drop (83% vs 71%, p=0.02) and an EGM reduction (71% vs 40%, p< 0.001) more frequently than lesions applied using magnetic navigation, although loss of capture, elimination of LPs, and a change in all 3 parameters were similarly observed. Conclusions VT ablation is inefficient as the majority of radiofrequency lesions do not achieve more than one targeted biophysical parameter. Only one-third of RF applications targeted at LPs result in complete elimination. Epicardial ablation within scar may be more effective than endocardial lesions and lesions applied manually may be more effective than lesions applied using magnetic navigation. New technologies directed at identifying and optimizing ablation effectiveness in scar are clinically warranted. PMID:24946895

Biophysical parameters during radiofrequency catheter ablation of scar-mediated ventricular tachycardia: epicardial and endocardial applications via manual and magnetic navigation.

PubMed

Bourke, Tara; Buch, Eric; Mathuria, Nilesh; Michowitz, Yoav; Yu, Ricky; Mandapati, Ravi; Shivkumar, Kalyanam; Tung, Roderick

2014-11-01

There is a paucity of data on biophysical parameters during radiofrequency ablation of scar-mediated ventricular tachycardia (VT). Data were collected from consecutive patients undergoing VT ablation with open-irrigation. Complete data were available for 372 lesions in 21 patients. The frequency of biophysical parameter changes were: >10Ω reduction (80%), bipolar EGM reduction (69%), while loss of capture was uncommon (32%). Unipolar injury current was seen in 72% of radiofrequency applications. Both EGM reduction and impedance drop were seen in 57% and a change in all 3 parameters was seen in only 20% of lesions. Late potentials were eliminated in 33%, reduced/modified in 56%, and remained after ablation in 11%. Epicardial lesions exhibited an impedance drop (90% vs. 76%, P = 0.002) and loss of capture (46% vs. 27%, P < 0.001) more frequently than endocardial lesions. Lesions delivered manually exhibited a >10Ω impedance drop (83% vs. 71%, P = 0.02) and an EGM reduction (71% vs. 40%, P < 0.001) more frequently than lesions applied using magnetic navigation, although loss of capture, elimination of LPs, and a change in all 3 parameters were similarly observed. VT ablation is inefficient as the majority of radiofrequency lesions do not achieve more than one targeted biophysical parameter. Only one-third of RF applications targeted at LPs result in complete elimination. Epicardial ablation within scar may be more effective than endocardial lesions, and lesions applied manually may be more effective than lesions applied using magnetic navigation. New technologies directed at identifying and optimizing ablation effectiveness in scar are clinically warranted. © 2014 Wiley Periodicals, Inc.

[INVITED] Control of femtosecond pulsed laser ablation and deposition by temporal pulse shaping

NASA Astrophysics Data System (ADS)

Garrelie, Florence; Bourquard, Florent; Loir, Anne--Sophie; Donnet, Christophe; Colombier, Jean-Philippe

2016-04-01

This study explores the effects of temporal laser pulse shaping on femtosecond pulsed laser deposition (PLD). The potential of laser pulses temporally tailored on ultrafast time scales is used to control the expansion and the excitation degree of ablation products including atomic species and nanoparticles. The ablation plume generated by temporally shaped femtosecond pulsed laser ablation of aluminum and graphite targets is studied by in situ optical diagnostic methods. Taking advantage of automated pulse shaping techniques, an adaptive procedure based on spectroscopic feedback regulates the irradiance for the enhancement of typical plasma features. Thin films elaborated by unshaped femtosecond laser pulses and by optimized sequence indicate that the nanoparticles generation efficiency is strongly influenced by the temporal shaping of the laser irradiation. The ablation processes leading either to the generation of the nanoparticles either to the formation of plasma can be favored by using a temporal shaping of the laser pulse. Insights are given on the possibility to control the quantity of the nanoparticles. The temporal laser pulse shaping is shown also to strongly modify the laser-induced plasma contents and kinetics for graphite ablation. Temporal pulse shaping proves its capability to reduce the number of slow radicals while increasing the proportion of monomers, with the addition of ionized species in front of the plume. This modification of the composition and kinetics of plumes in graphite ablation using temporal laser pulse shaping is discussed in terms of modification of the structural properties of deposited Diamond-Like Carbon films (DLC). This gives rise to a better understanding of the growth processes involved in femtosecond-PLD and picosecond-PLD of DLC suggesting the importance of neutral C atoms, which are responsible for the subplantation process.

A systematical analysis of in vivo contact forces on virtual catheter tip/tissue surface contact during cardiac mapping and intervention.

PubMed

Okumura, Yasuo; Johnson, Susan B; Bunch, T Jared; Henz, Benhur D; O'Brien, Christine J; Packer, Douglas L

2008-06-01

While catheter tip/tissue contact has been shown to be an important determinant of ablative lesions in in vitro studies, the impact of contact on the outcomes of mapping and ablation in the intact heart has not been evaluated. Twelve dogs underwent atrial ablation guided by the Senesitrade mark robotic catheter remote control system. After intracardiac ultrasound (ICE) validation of contact force measured by an in-line mechanical sensor, the relationship between contact force and individual lesion formation was established during irrigated-tipped ablation (flow 17 mL/sec) at 15 watts for 30 seconds. Minimal contact by ICE correlated with force of 4.7 +/- 5.8 grams, consistent contact 9.9 +/- 8.6 grams and tissue tenting produced 25.0 +/- 14.0 grams. Conversely, catheter tip/tissue contact by ICE was predicted by contact force. A contact force of 10-20 and > or =20 grams generated full-thickness, larger volume ablative lesions than that created with <10 grams (98 +/- 69 and 89 +/- 70 mm(3) vs 40 +/- 42 mm(3), P < 0.05). Moderate (10 grams) and marked contact (15-20 grams) application produced 1.5 X greater electroanatomic map volumes that were seen with minimal contact (5 grams) (26 +/- 3 cm(3) vs 33 +/- 6, 39 +/- 3 cm(3), P < 0.05). The electroanatomic map/CT merge process was also more distorted when mapping was generated at moderate to marked contact force. This study shows that mapping and ablation using a robotic sheath guidance system are critically dependent on generated force. These findings suggest that ablative lesion size is optimized by the application of 10-20 grams of contact force, although mapping requires lower-force application to avoid image distortions.

Chaotic particle swarm optimization with mutation for classification.

PubMed

Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

2015-01-01

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms.

Iterative motion compensation approach for ultrasonic thermal imaging

NASA Astrophysics Data System (ADS)

Fleming, Ioana; Hager, Gregory; Guo, Xiaoyu; Kang, Hyun Jae; Boctor, Emad

2015-03-01

As thermal imaging attempts to estimate very small tissue motion (on the order of tens of microns), it can be negatively influenced by signal decorrelation. Patient's breathing and cardiac cycle generate shifts in the RF signal patterns. Other sources of movement could be found outside the patient's body, like transducer slippage or small vibrations due to environment factors like electronic noise. Here, we build upon a robust displacement estimation method for ultrasound elastography and we investigate an iterative motion compensation algorithm, which can detect and remove non-heat induced tissue motion at every step of the ablation procedure. The validation experiments are performed on laboratory induced ablation lesions in ex-vivo tissue. The ultrasound probe is either held by the operator's hand or supported by a robotic arm. We demonstrate the ability to detect and remove non-heat induced tissue motion in both settings. We show that removing extraneous motion helps unmask the effects of heating. Our strain estimation curves closely mirror the temperature changes within the tissue. While previous results in the area of motion compensation were reported for experiments lasting less than 10 seconds, our algorithm was tested on experiments that lasted close to 20 minutes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jo, J.C.; Shin, W.K.; Choi, C.Y.

Transient heat transfer problems with phase changes (Stefan problems) occur in many engineering situations, including potential core melting and solidification during pressurized-water-reactor severe accidents, ablation of thermal shields, melting and solidification of alloys, and many others. This article addresses the numerical analysis of nonlinear transient heat transfer with melting or solidification. An effective and simple procedure is presented for the simulation of the motion of the boundary and the transient temperature field during the phase change process. To accomplish this purpose, an iterative implicit solution algorithm has been developed by employing the dual-reciprocity boundary-element method. The dual-reciprocity boundary-element approach providedmore » in this article is much simpler than the usual boundary-element method in applying a reciprocity principle and an available technique for dealing with the domain integral of the boundary element formulation simultaneously. In this article, attention is focused on two-dimensional melting (ablation)/solidification problems for simplicity. The accuracy and effectiveness of the present analysis method have been illustrated through comparisons of the calculation results of some examples of one-phase ablation/solidification problems with their known semianalytical or numerical solutions where available.« less

Modeling snow accumulation and ablation processes in forested environments

NASA Astrophysics Data System (ADS)

Andreadis, Konstantinos M.; Storck, Pascal; Lettenmaier, Dennis P.

2009-05-01

The effects of forest canopies on snow accumulation and ablation processes can be very important for the hydrology of midlatitude and high-latitude areas. A mass and energy balance model for snow accumulation and ablation processes in forested environments was developed utilizing extensive measurements of snow interception and release in a maritime mountainous site in Oregon. The model was evaluated using 2 years of weighing lysimeter data and was able to reproduce the snow water equivalent (SWE) evolution throughout winters both beneath the canopy and in the nearby clearing, with correlations to observations ranging from 0.81 to 0.99. Additionally, the model was evaluated using measurements from a Boreal Ecosystem-Atmosphere Study (BOREAS) field site in Canada to test the robustness of the canopy snow interception algorithm in a much different climate. Simulated SWE was relatively close to the observations for the forested sites, with discrepancies evident in some cases. Although the model formulation appeared robust for both types of climates, sensitivity to parameters such as snow roughness length and maximum interception capacity suggested the magnitude of improvements of SWE simulations that might be achieved by calibration.

A theoretical comparison of evolutionary algorithms and simulated annealing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, W.E.

1995-08-28

This paper theoretically compares the performance of simulated annealing and evolutionary algorithms. Our main result is that under mild conditions a wide variety of evolutionary algorithms can be shown to have greater performance than simulated annealing after a sufficiently large number of function evaluations. This class of EAs includes variants of evolutionary strategie and evolutionary programming, the canonical genetic algorithm, as well as a variety of genetic algorithms that have been applied to combinatorial optimization problems. The proof of this result is based on a performance analysis of a very general class of stochastic optimization algorithms, which has implications formore » the performance of a variety of other optimization algorithm.« less

Design optimization of single mixed refrigerant LNG process using a hybrid modified coordinate descent algorithm

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Long, Nguyen Van Duc; Minh, Le Quang; Lee, Moonyong

2018-01-01

Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.

Gradient Optimization for Analytic conTrols - GOAT

NASA Astrophysics Data System (ADS)

Assémat, Elie; Machnes, Shai; Tannor, David; Wilhelm-Mauch, Frank

Quantum optimal control becomes a necessary step in a number of studies in the quantum realm. Recent experimental advances showed that superconducting qubits can be controlled with an impressive accuracy. However, most of the standard optimal control algorithms are not designed to manage such high accuracy. To tackle this issue, a novel quantum optimal control algorithm have been introduced: the Gradient Optimization for Analytic conTrols (GOAT). It avoids the piecewise constant approximation of the control pulse used by standard algorithms. This allows an efficient implementation of very high accuracy optimization. It also includes a novel method to compute the gradient that provides many advantages, e.g. the absence of backpropagation or the natural route to optimize the robustness of the control pulses. This talk will present the GOAT algorithm and a few applications to transmons systems.

Development of aerogel-lined targets for inertial confinement fusion experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Braun, Tom

2013-03-28

This thesis explores the formation of ICF compatible foam layers inside of an ablator shell used for inertial confinement fusion experiments at the National Ignition Facility. In particular, the capability of p- DCPD polymer aerogels to serve as a scaffold for the deuterium-tritium mix was analyzed. Four different factors were evaluated: the dependency of different factors such as thickness or composition of a precursor solution on the uniformity of the aerogel layer, how to bring the optimal composition inside of the ablator shell, the mechanical stability of ultra-low density p-DCPD aerogel bulk pieces during wetting and freezing with hydrogen, andmore » the wetting behavior of thin polymer foam layers in HDC carbon ablator shells with liquid deuterium. The research for thesis was done at Lawrence Livermore National Laboratory in cooperation with the Technical University Munich.« less

Investigation of the differentiation of ex vivo nerve and fat tissues using laser-induced breakdown spectroscopy (LIBS): Prospects for tissue-specific laser surgery.

PubMed

Mehari, Fanuel; Rohde, Maximillian; Kanawade, Rajesh; Knipfer, Christian; Adler, Werner; Klämpfl, Florian; Stelzle, Florian; Schmidt, Michael

2016-10-01

In the present study, the elemental compositions of fat and nerve tissue during their plasma mediated laser ablation are studied in the context of tissue differentiation for laser surgery applications by using Laser-Induced Breakdown Spectroscopy (LIBS). Tissue samples of porcine fat and nerve were prepared as ex vivo experimental objects. Plasma mediated laser ablation is performed using an Nd : YAG laser in open air and under normal stray light conditions. The performed measurements suggest that the two tissue types show a high similarity in terms of qualitative elemental composition while at the same time revealing a distinct difference in the concentration of the constituent elements. Different analysis approaches are evaluated and discussed to optimize the tissue-differentiation performance of the LIBS approach. Plasma mediated laser tissue ablation. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evolutionary Dynamic Multiobjective Optimization Via Kalman Filter Prediction.

PubMed

Muruganantham, Arrchana; Tan, Kay Chen; Vadakkepat, Prahlad

2016-12-01

Evolutionary algorithms are effective in solving static multiobjective optimization problems resulting in the emergence of a number of state-of-the-art multiobjective evolutionary algorithms (MOEAs). Nevertheless, the interest in applying them to solve dynamic multiobjective optimization problems has only been tepid. Benchmark problems, appropriate performance metrics, as well as efficient algorithms are required to further the research in this field. One or more objectives may change with time in dynamic optimization problems. The optimization algorithm must be able to track the moving optima efficiently. A prediction model can learn the patterns from past experience and predict future changes. In this paper, a new dynamic MOEA using Kalman filter (KF) predictions in decision space is proposed to solve the aforementioned problems. The predictions help to guide the search toward the changed optima, thereby accelerating convergence. A scoring scheme is devised to hybridize the KF prediction with a random reinitialization method. Experimental results and performance comparisons with other state-of-the-art algorithms demonstrate that the proposed algorithm is capable of significantly improving the dynamic optimization performance.

Visualization of risk structures for interactive planning of image guided radiofrequency ablation of liver tumors

NASA Astrophysics Data System (ADS)

Rieder, Christian; Schwier, Michael; Weihusen, Andreas; Zidowitz, Stephan; Peitgen, Heinz-Otto

2009-02-01

Image guided radiofrequency ablation (RFA) is becoming a standard procedure as a minimally invasive method for tumor treatment in the clinical routine. The visualization of pathological tissue and potential risk structures like vessels or important organs gives essential support in image guided pre-interventional RFA planning. In this work our aim is to present novel visualization techniques for interactive RFA planning to support the physician with spatial information of pathological structures as well as the finding of trajectories without harming vitally important tissue. Furthermore, we illustrate three-dimensional applicator models of different manufactures combined with corresponding ablation areas in homogenous tissue, as specified by the manufacturers, to enhance the estimated amount of cell destruction caused by ablation. The visualization techniques are embedded in a workflow oriented application, designed for the use in the clinical routine. To allow a high-quality volume rendering we integrated a visualization method using the fuzzy c-means algorithm. This method automatically defines a transfer function for volume visualization of vessels without the need of a segmentation mask. However, insufficient visualization results of the displayed vessels caused by low data quality can be improved using local vessel segmentation in the vicinity of the lesion. We also provide an interactive segmentation technique of liver tumors for the volumetric measurement and for the visualization of pathological tissue combined with anatomical structures. In order to support coagulation estimation with respect to the heat-sink effect of the cooling blood flow which decreases thermal ablation, a numerical simulation of the heat distribution is provided.

An optimized algorithm for multiscale wideband deconvolution of radio astronomical images

NASA Astrophysics Data System (ADS)

Offringa, A. R.; Smirnov, O.

2017-10-01

We describe a new multiscale deconvolution algorithm that can also be used in a multifrequency mode. The algorithm only affects the minor clean loop. In single-frequency mode, the minor loop of our improved multiscale algorithm is over an order of magnitude faster than the casa multiscale algorithm, and produces results of similar quality. For multifrequency deconvolution, a technique named joined-channel cleaning is used. In this mode, the minor loop of our algorithm is two to three orders of magnitude faster than casa msmfs. We extend the multiscale mode with automated scale-dependent masking, which allows structures to be cleaned below the noise. We describe a new scale-bias function for use in multiscale cleaning. We test a second deconvolution method that is a variant of the moresane deconvolution technique, and uses a convex optimization technique with isotropic undecimated wavelets as dictionary. On simple well-calibrated data, the convex optimization algorithm produces visually more representative models. On complex or imperfect data, the convex optimization algorithm has stability issues.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beltran, C; Kamal, H

Purpose: To provide a multicriteria optimization algorithm for intensity modulated radiation therapy using pencil proton beam scanning. Methods: Intensity modulated radiation therapy using pencil proton beam scanning requires efficient optimization algorithms to overcome the uncertainties in the Bragg peaks locations. This work is focused on optimization algorithms that are based on Monte Carlo simulation of the treatment planning and use the weights and the dose volume histogram (DVH) control points to steer toward desired plans. The proton beam treatment planning process based on single objective optimization (representing a weighted sum of multiple objectives) usually leads to time-consuming iterations involving treatmentmore » planning team members. We proved a time efficient multicriteria optimization algorithm that is developed to run on NVIDIA GPU (Graphical Processing Units) cluster. The multicriteria optimization algorithm running time benefits from up-sampling of the CT voxel size of the calculations without loss of fidelity. Results: We will present preliminary results of Multicriteria optimization for intensity modulated proton therapy based on DVH control points. The results will show optimization results of a phantom case and a brain tumor case. Conclusion: The multicriteria optimization of the intensity modulated radiation therapy using pencil proton beam scanning provides a novel tool for treatment planning. Work support by a grant from Varian Inc.« less

Beam-steering efficiency optimization method based on a rapid-search algorithm for liquid crystal optical phased array.

PubMed

Xiao, Feng; Kong, Lingjiang; Chen, Jian

2017-06-01

A rapid-search algorithm to improve the beam-steering efficiency for a liquid crystal optical phased array was proposed and experimentally demonstrated in this paper. This proposed algorithm, in which the value of steering efficiency is taken as the objective function and the controlling voltage codes are considered as the optimization variables, consisted of a detection stage and a construction stage. It optimized the steering efficiency in the detection stage and adjusted its search direction adaptively in the construction stage to avoid getting caught in a wrong search space. Simulations had been conducted to compare the proposed algorithm with the widely used pattern-search algorithm using criteria of convergence rate and optimized efficiency. Beam-steering optimization experiments had been performed to verify the validity of the proposed method.

Photoactive dye-enhanced tissue ablation for endoscopic laser prostatectomy.

PubMed

Ahn, Minwoo; Hau, Nguyen Trung; Van Phuc, Nguyen; Oh, Junghwan; Kang, Hyun Wook

2014-11-01

Laser light has been widely used as a surgical tool to treat benign prostate hyperplasia (BPH) over 20 years. Recently, application of high laser power up to 200 W was often reported to swiftly remove a large amount of prostatic tissue. The purpose of this study was to validate the feasibility of photoactive dye injection to enhance light absorption and eventually to facilitate tissue vaporization with low laser power. Chicken breast tissue was selected as a target tissue due to minimal optical absorption at the visible wavelength. Four biocompatible photoactive dyes, including amaranth (AR), black dye (BD), hemoglobin powder (HP), and endoscopic marker (EM), were selected and tested in vitro with a customized 532 nm laser system with radiant exposure ranging from 0.9 to 3.9 J/cm(2) . Light absorbance and ablation threshold were measured with UV-Vis spectrometer and Probit analysis, respectively, and compared to feature the function of the injected dyes. Ablation performance with dye-injection was evaluated in light of radiant exposure, dye concentration, and number of injection. Higher light absorption by injected dyes led to lower ablation threshold as well as more efficient tissue removal in the order of AR, BD, HP, and EM. Regardless of the injected dyes, ablation efficiency principally increased with radiant exposure, dye concentration, and number of injection. Among the dyes, AR created the highest ablation rate of 44.2 ± 0.2 µm/pulse due to higher absorbance and lower ablation threshold. High aspect ratios up to 7.1 ± 0.4 entailed saturation behavior in the tissue ablation injected with AR and BD, possibly resulting from plume shielding and increased scattering due to coagulation. Preliminary tests on canine prostate with a hydraulic injection system demonstrated that 80 W with dye injection yielded comparable ablation efficiency to 120 W with no injection, indicating 33% reduced laser power with almost equivalent performance. Due to efficient coupling of optical energy, pre-injection of photoactive dyes promoted the degree of tissue removal during laser irradiation. Further studies will investigate spatial distribution of dyes and optimal injecting pressure to govern the extent of dye-assisted ablation in a predictable manner. In-depth comprehension on photoactive dye-enhanced tissue ablation can help accomplish efficient and safe laser vaporization for BPH with low power application. © 2014 Wiley Periodicals, Inc.

An Improved Co-evolutionary Particle Swarm Optimization for Wireless Sensor Networks with Dynamic Deployment

PubMed Central

Wang, Xue; Wang, Sheng; Ma, Jun-Jie

2007-01-01

The effectiveness of wireless sensor networks (WSNs) depends on the coverage and target detection probability provided by dynamic deployment, which is usually supported by the virtual force (VF) algorithm. However, in the VF algorithm, the virtual force exerted by stationary sensor nodes will hinder the movement of mobile sensor nodes. Particle swarm optimization (PSO) is introduced as another dynamic deployment algorithm, but in this case the computation time required is the big bottleneck. This paper proposes a dynamic deployment algorithm which is named “virtual force directed co-evolutionary particle swarm optimization” (VFCPSO), since this algorithm combines the co-evolutionary particle swarm optimization (CPSO) with the VF algorithm, whereby the CPSO uses multiple swarms to optimize different components of the solution vectors for dynamic deployment cooperatively and the velocity of each particle is updated according to not only the historical local and global optimal solutions, but also the virtual forces of sensor nodes. Simulation results demonstrate that the proposed VFCPSO is competent for dynamic deployment in WSNs and has better performance with respect to computation time and effectiveness than the VF, PSO and VFPSO algorithms.

Continuous intensity map optimization (CIMO): A novel approach to leaf sequencing in step and shoot IMRT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao Daliang; Earl, Matthew A.; Luan, Shuang

2006-04-15

A new leaf-sequencing approach has been developed that is designed to reduce the number of required beam segments for step-and-shoot intensity modulated radiation therapy (IMRT). This approach to leaf sequencing is called continuous-intensity-map-optimization (CIMO). Using a simulated annealing algorithm, CIMO seeks to minimize differences between the optimized and sequenced intensity maps. Two distinguishing features of the CIMO algorithm are (1) CIMO does not require that each optimized intensity map be clustered into discrete levels and (2) CIMO is not rule-based but rather simultaneously optimizes both the aperture shapes and weights. To test the CIMO algorithm, ten IMRT patient cases weremore » selected (four head-and-neck, two pancreas, two prostate, one brain, and one pelvis). For each case, the optimized intensity maps were extracted from the Pinnacle{sup 3} treatment planning system. The CIMO algorithm was applied, and the optimized aperture shapes and weights were loaded back into Pinnacle. A final dose calculation was performed using Pinnacle's convolution/superposition based dose calculation. On average, the CIMO algorithm provided a 54% reduction in the number of beam segments as compared with Pinnacle's leaf sequencer. The plans sequenced using the CIMO algorithm also provided improved target dose uniformity and a reduced discrepancy between the optimized and sequenced intensity maps. For ten clinical intensity maps, comparisons were performed between the CIMO algorithm and the power-of-two reduction algorithm of Xia and Verhey [Med. Phys. 25(8), 1424-1434 (1998)]. When the constraints of a Varian Millennium multileaf collimator were applied, the CIMO algorithm resulted in a 26% reduction in the number of segments. For an Elekta multileaf collimator, the CIMO algorithm resulted in a 67% reduction in the number of segments. An average leaf sequencing time of less than one minute per beam was observed.« less

Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling

PubMed Central

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220

Discrete bat algorithm for optimal problem of permutation flow shop scheduling.

PubMed

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem.

Stochastic optimization algorithms for barrier dividend strategies

NASA Astrophysics Data System (ADS)

Yin, G.; Song, Q. S.; Yang, H.

2009-01-01

This work focuses on finding optimal barrier policy for an insurance risk model when the dividends are paid to the share holders according to a barrier strategy. A new approach based on stochastic optimization methods is developed. Compared with the existing results in the literature, more general surplus processes are considered. Precise models of the surplus need not be known; only noise-corrupted observations of the dividends are used. Using barrier-type strategies, a class of stochastic optimization algorithms are developed. Convergence of the algorithm is analyzed; rate of convergence is also provided. Numerical results are reported to demonstrate the performance of the algorithm.

A graph decomposition-based approach for water distribution network optimization

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Simpson, Angus R.; Zecchin, Aaron C.; Deuerlein, Jochen W.

2013-04-01

A novel optimization approach for water distribution network design is proposed in this paper. Using graph theory algorithms, a full water network is first decomposed into different subnetworks based on the connectivity of the network's components. The original whole network is simplified to a directed augmented tree, in which the subnetworks are substituted by augmented nodes and directed links are created to connect them. Differential evolution (DE) is then employed to optimize each subnetwork based on the sequence specified by the assigned directed links in the augmented tree. Rather than optimizing the original network as a whole, the subnetworks are sequentially optimized by the DE algorithm. A solution choice table is established for each subnetwork (except for the subnetwork that includes a supply node) and the optimal solution of the original whole network is finally obtained by use of the solution choice tables. Furthermore, a preconditioning algorithm is applied to the subnetworks to produce an approximately optimal solution for the original whole network. This solution specifies promising regions for the final optimization algorithm to further optimize the subnetworks. Five water network case studies are used to demonstrate the effectiveness of the proposed optimization method. A standard DE algorithm (SDE) and a genetic algorithm (GA) are applied to each case study without network decomposition to enable a comparison with the proposed method. The results show that the proposed method consistently outperforms the SDE and GA (both with tuned parameters) in terms of both the solution quality and efficiency.

Variational Trajectory Optimization Tool Set: Technical description and user's manual

NASA Technical Reports Server (NTRS)

Bless, Robert R.; Queen, Eric M.; Cavanaugh, Michael D.; Wetzel, Todd A.; Moerder, Daniel D.

1993-01-01

The algorithms that comprise the Variational Trajectory Optimization Tool Set (VTOTS) package are briefly described. The VTOTS is a software package for solving nonlinear constrained optimal control problems from a wide range of engineering and scientific disciplines. The VTOTS package was specifically designed to minimize the amount of user programming; in fact, for problems that may be expressed in terms of analytical functions, the user needs only to define the problem in terms of symbolic variables. This version of the VTOTS does not support tabular data; thus, problems must be expressed in terms of analytical functions. The VTOTS package consists of two methods for solving nonlinear optimal control problems: a time-domain finite-element algorithm and a multiple shooting algorithm. These two algorithms, under the VTOTS package, may be run independently or jointly. The finite-element algorithm generates approximate solutions, whereas the shooting algorithm provides a more accurate solution to the optimization problem. A user's manual, some examples with results, and a brief description of the individual subroutines are included.

Self-adaptive multi-objective harmony search for optimal design of water distribution networks

NASA Astrophysics Data System (ADS)

Choi, Young Hwan; Lee, Ho Min; Yoo, Do Guen; Kim, Joong Hoon

2017-11-01

In multi-objective optimization computing, it is important to assign suitable parameters to each optimization problem to obtain better solutions. In this study, a self-adaptive multi-objective harmony search (SaMOHS) algorithm is developed to apply the parameter-setting-free technique, which is an example of a self-adaptive methodology. The SaMOHS algorithm attempts to remove some of the inconvenience from parameter setting and selects the most adaptive parameters during the iterative solution search process. To verify the proposed algorithm, an optimal least cost water distribution network design problem is applied to three different target networks. The results are compared with other well-known algorithms such as multi-objective harmony search and the non-dominated sorting genetic algorithm-II. The efficiency of the proposed algorithm is quantified by suitable performance indices. The results indicate that SaMOHS can be efficiently applied to the search for Pareto-optimal solutions in a multi-objective solution space.

Evolutionary Beamforming Optimization for Radio Frequency Charging in Wireless Rechargeable Sensor Networks

PubMed Central

Yao, Ke-Han; Jiang, Jehn-Ruey; Tsai, Chung-Hsien; Wu, Zong-Syun

2017-01-01

This paper investigates how to efficiently charge sensor nodes in a wireless rechargeable sensor network (WRSN) with radio frequency (RF) chargers to make the network sustainable. An RF charger is assumed to be equipped with a uniform circular array (UCA) of 12 antennas with the radius λ, where λ is the RF wavelength. The UCA can steer most RF energy in a target direction to charge a specific WRSN node by the beamforming technology. Two evolutionary algorithms (EAs) using the evolution strategy (ES), namely the Evolutionary Beamforming Optimization (EBO) algorithm and the Evolutionary Beamforming Optimization Reseeding (EBO-R) algorithm, are proposed to nearly optimize the power ratio of the UCA beamforming peak side lobe (PSL) and the main lobe (ML) aimed at the given target direction. The proposed algorithms are simulated for performance evaluation and are compared with a related algorithm, called Particle Swarm Optimization Gravitational Search Algorithm-Explore (PSOGSA-Explore), to show their superiority. PMID:28825648

Optimized data fusion for K-means Laplacian clustering

PubMed Central

Yu, Shi; Liu, Xinhai; Tranchevent, Léon-Charles; Glänzel, Wolfgang; Suykens, Johan A. K.; De Moor, Bart; Moreau, Yves

2011-01-01

Motivation: We propose a novel algorithm to combine multiple kernels and Laplacians for clustering analysis. The new algorithm is formulated on a Rayleigh quotient objective function and is solved as a bi-level alternating minimization procedure. Using the proposed algorithm, the coefficients of kernels and Laplacians can be optimized automatically. Results: Three variants of the algorithm are proposed. The performance is systematically validated on two real-life data fusion applications. The proposed Optimized Kernel Laplacian Clustering (OKLC) algorithms perform significantly better than other methods. Moreover, the coefficients of kernels and Laplacians optimized by OKLC show some correlation with the rank of performance of individual data source. Though in our evaluation the K values are predefined, in practical studies, the optimal cluster number can be consistently estimated from the eigenspectrum of the combined kernel Laplacian matrix. Availability: The MATLAB code of algorithms implemented in this paper is downloadable from http://homes.esat.kuleuven.be/~sistawww/bioi/syu/oklc.html. Contact: shiyu@uchicago.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20980271

Particle swarm optimization - Genetic algorithm (PSOGA) on linear transportation problem

NASA Astrophysics Data System (ADS)

Rahmalia, Dinita

2017-08-01

Linear Transportation Problem (LTP) is the case of constrained optimization where we want to minimize cost subject to the balance of the number of supply and the number of demand. The exact method such as northwest corner, vogel, russel, minimal cost have been applied at approaching optimal solution. In this paper, we use heurisitic like Particle Swarm Optimization (PSO) for solving linear transportation problem at any size of decision variable. In addition, we combine mutation operator of Genetic Algorithm (GA) at PSO to improve optimal solution. This method is called Particle Swarm Optimization - Genetic Algorithm (PSOGA). The simulations show that PSOGA can improve optimal solution resulted by PSO.

Fast optimization of glide vehicle reentry trajectory based on genetic algorithm

NASA Astrophysics Data System (ADS)

Jia, Jun; Dong, Ruixing; Yuan, Xuejun; Wang, Chuangwei

2018-02-01

An optimization method of reentry trajectory based on genetic algorithm is presented to meet the need of reentry trajectory optimization for glide vehicle. The dynamic model for the glide vehicle during reentry period is established. Considering the constraints of heat flux, dynamic pressure, overload etc., the optimization of reentry trajectory is investigated by utilizing genetic algorithm. The simulation shows that the method presented by this paper is effective for the optimization of reentry trajectory of glide vehicle. The efficiency and speed of this method is comparative with the references. Optimization results meet all constraints, and the on-line fast optimization is potential by pre-processing the offline samples.

Adaptive reference update (ARU) algorithm. A stochastic search algorithm for efficient optimization of multi-drug cocktails

PubMed Central

2012-01-01

Background Multi-target therapeutics has been shown to be effective for treating complex diseases, and currently, it is a common practice to combine multiple drugs to treat such diseases to optimize the therapeutic outcomes. However, considering the huge number of possible ways to mix multiple drugs at different concentrations, it is practically difficult to identify the optimal drug combination through exhaustive testing. Results In this paper, we propose a novel stochastic search algorithm, called the adaptive reference update (ARU) algorithm, that can provide an efficient and systematic way for optimizing multi-drug cocktails. The ARU algorithm iteratively updates the drug combination to improve its response, where the update is made by comparing the response of the current combination with that of a reference combination, based on which the beneficial update direction is predicted. The reference combination is continuously updated based on the drug response values observed in the past, thereby adapting to the underlying drug response function. To demonstrate the effectiveness of the proposed algorithm, we evaluated its performance based on various multi-dimensional drug functions and compared it with existing algorithms. Conclusions Simulation results show that the ARU algorithm significantly outperforms existing stochastic search algorithms, including the Gur Game algorithm. In fact, the ARU algorithm can more effectively identify potent drug combinations and it typically spends fewer iterations for finding effective combinations. Furthermore, the ARU algorithm is robust to random fluctuations and noise in the measured drug response, which makes the algorithm well-suited for practical drug optimization applications. PMID:23134742

Firefly algorithm for cardinality constrained mean-variance portfolio optimization problem with entropy diversity constraint.

PubMed

Bacanin, Nebojsa; Tuba, Milan

2014-01-01

Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results.

Firefly Algorithm for Cardinality Constrained Mean-Variance Portfolio Optimization Problem with Entropy Diversity Constraint

PubMed Central

2014-01-01

Portfolio optimization (selection) problem is an important and hard optimization problem that, with the addition of necessary realistic constraints, becomes computationally intractable. Nature-inspired metaheuristics are appropriate for solving such problems; however, literature review shows that there are very few applications of nature-inspired metaheuristics to portfolio optimization problem. This is especially true for swarm intelligence algorithms which represent the newer branch of nature-inspired algorithms. No application of any swarm intelligence metaheuristics to cardinality constrained mean-variance (CCMV) portfolio problem with entropy constraint was found in the literature. This paper introduces modified firefly algorithm (FA) for the CCMV portfolio model with entropy constraint. Firefly algorithm is one of the latest, very successful swarm intelligence algorithm; however, it exhibits some deficiencies when applied to constrained problems. To overcome lack of exploration power during early iterations, we modified the algorithm and tested it on standard portfolio benchmark data sets used in the literature. Our proposed modified firefly algorithm proved to be better than other state-of-the-art algorithms, while introduction of entropy diversity constraint further improved results. PMID:24991645

Range image registration based on hash map and moth-flame optimization

NASA Astrophysics Data System (ADS)

Zou, Li; Ge, Baozhen; Chen, Lei

2018-03-01

Over the past decade, evolutionary algorithms (EAs) have been introduced to solve range image registration problems because of their robustness and high precision. However, EA-based range image registration algorithms are time-consuming. To reduce the computational time, an EA-based range image registration algorithm using hash map and moth-flame optimization is proposed. In this registration algorithm, a hash map is used to avoid over-exploitation in registration process. Additionally, we present a search equation that is better at exploration and a restart mechanism to avoid being trapped in local minima. We compare the proposed registration algorithm with the registration algorithms using moth-flame optimization and several state-of-the-art EA-based registration algorithms. The experimental results show that the proposed algorithm has a lower computational cost than other algorithms and achieves similar registration precision.

An improved chaotic fruit fly optimization based on a mutation strategy for simultaneous feature selection and parameter optimization for SVM and its applications.

PubMed

Ye, Fei; Lou, Xin Yuan; Sun, Lin Fu

2017-01-01

This paper proposes a new support vector machine (SVM) optimization scheme based on an improved chaotic fly optimization algorithm (FOA) with a mutation strategy to simultaneously perform parameter setting turning for the SVM and feature selection. In the improved FOA, the chaotic particle initializes the fruit fly swarm location and replaces the expression of distance for the fruit fly to find the food source. However, the proposed mutation strategy uses two distinct generative mechanisms for new food sources at the osphresis phase, allowing the algorithm procedure to search for the optimal solution in both the whole solution space and within the local solution space containing the fruit fly swarm location. In an evaluation based on a group of ten benchmark problems, the proposed algorithm's performance is compared with that of other well-known algorithms, and the results support the superiority of the proposed algorithm. Moreover, this algorithm is successfully applied in a SVM to perform both parameter setting turning for the SVM and feature selection to solve real-world classification problems. This method is called chaotic fruit fly optimization algorithm (CIFOA)-SVM and has been shown to be a more robust and effective optimization method than other well-known methods, particularly in terms of solving the medical diagnosis problem and the credit card problem.

Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm.

PubMed

Ma, Changxi; Hao, Wei; Pan, Fuquan; Xiang, Wang

2018-01-01

Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution route is optimized. For road screening issues of hazardous materials transportation, a road screening algorithm of hazardous materials transportation is built based on genetic algorithm and Levenberg-Marquardt neural network (GA-LM-NN) by analyzing 15 attributes data of each road network section. A multi-objective robust optimization model with adjustable robustness is constructed for the hazardous materials transportation problem of single distribution center to minimize transportation risk and time. A multi-objective genetic algorithm is designed to solve the problem according to the characteristics of the model. The algorithm uses an improved strategy to complete the selection operation, applies partial matching cross shift and single ortho swap methods to complete the crossover and mutation operation, and employs an exclusive method to construct Pareto optimal solutions. Studies show that the sets of hazardous materials transportation road can be found quickly through the proposed road screening algorithm based on GA-LM-NN, whereas the distribution route Pareto solutions with different levels of robustness can be found rapidly through the proposed multi-objective robust optimization model and algorithm.

Clinical impact of rotor ablation in atrial fibrillation: a systematic review.

PubMed

Parameswaran, Ramanathan; Voskoboinik, Aleksandr; Gorelik, Alexandra; Lee, Geoffrey; Kistler, Peter M; Sanders, Prashanthan; Kalman, Jonathan M

2018-01-11

Rotor mapping and ablation have gained favour over the recent years as an emerging ablation strategy targeting drivers of atrial fibrillation (AF). Their efficacy, however, has been a topic of great debate with variable outcomes across centres. The aim of this study was to systematically review the recent medical literature to determine the medium-term outcomes of rotor ablation in patients with paroxysmal atrial fibrillation (PAF) and persistent atrial fibrillation (PeAF). A systematic search of the contemporary scientific literature (PubMed and EMBASE) was performed in August 2017. Only studies assessing arrhythmia-free survival from rotor ablation of AF were included. We used the random-effects model to assess the primary outcome of pooled medium-term single-procedure AF-free survival for both PAF and PeAF. Success rates from multiple procedures and complication rates were also examined. We included 11 observational studies (4 PAF and 10 PeAF) with a total of 556 patients (166 PAF and 390 PeAF). Pooled single-procedure freedom from AF was 37.8% [95% confidence interval 5.6-86.3%] at a mean follow-up period of 13.8 ± 1.8 months for PAF and 59.2% (95% CI 41.4-74.9%) at a mean follow-up period of 12.9 ± 6 months for PeAF. There was a marked heterogeneity between studies (I2 = 93.8% for PAF and 88.3% for PeAF). The mean complication rate of rotor ablation among the reported studies was 3.4%. The wide variability in success rate between different centres performing rotor ablations suggests that the optimal ablation strategy, particularly targeting rotors, is unclear. Results from randomized studies are necessary before this technique can be considered as an established clinical tool. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com.

A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems

PubMed Central

Cao, Leilei; Xu, Lihong; Goodman, Erik D.

2016-01-01

A Guiding Evolutionary Algorithm (GEA) with greedy strategy for global optimization problems is proposed. Inspired by Particle Swarm Optimization, the Genetic Algorithm, and the Bat Algorithm, the GEA was designed to retain some advantages of each method while avoiding some disadvantages. In contrast to the usual Genetic Algorithm, each individual in GEA is crossed with the current global best one instead of a randomly selected individual. The current best individual served as a guide to attract offspring to its region of genotype space. Mutation was added to offspring according to a dynamic mutation probability. To increase the capability of exploitation, a local search mechanism was applied to new individuals according to a dynamic probability of local search. Experimental results show that GEA outperformed the other three typical global optimization algorithms with which it was compared. PMID:27293421

Structures vibration control via Tuned Mass Dampers using a co-evolution Coral Reefs Optimization algorithm

NASA Astrophysics Data System (ADS)

Salcedo-Sanz, S.; Camacho-Gómez, C.; Magdaleno, A.; Pereira, E.; Lorenzana, A.

2017-04-01

In this paper we tackle a problem of optimal design and location of Tuned Mass Dampers (TMDs) for structures subjected to earthquake ground motions, using a novel meta-heuristic algorithm. Specifically, the Coral Reefs Optimization (CRO) with Substrate Layer (CRO-SL) is proposed as a competitive co-evolution algorithm with different exploration procedures within a single population of solutions. The proposed approach is able to solve the TMD design and location problem, by exploiting the combination of different types of searching mechanisms. This promotes a powerful evolutionary-like algorithm for optimization problems, which is shown to be very effective in this particular problem of TMDs tuning. The proposed algorithm's performance has been evaluated and compared with several reference algorithms in two building models with two and four floors, respectively.

A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems.

PubMed

Cao, Leilei; Xu, Lihong; Goodman, Erik D

2016-01-01

A Guiding Evolutionary Algorithm (GEA) with greedy strategy for global optimization problems is proposed. Inspired by Particle Swarm Optimization, the Genetic Algorithm, and the Bat Algorithm, the GEA was designed to retain some advantages of each method while avoiding some disadvantages. In contrast to the usual Genetic Algorithm, each individual in GEA is crossed with the current global best one instead of a randomly selected individual. The current best individual served as a guide to attract offspring to its region of genotype space. Mutation was added to offspring according to a dynamic mutation probability. To increase the capability of exploitation, a local search mechanism was applied to new individuals according to a dynamic probability of local search. Experimental results show that GEA outperformed the other three typical global optimization algorithms with which it was compared.

Adaptive particle swarm optimization for optimal orbital elements of binary stars

NASA Astrophysics Data System (ADS)

Attia, Abdel-Fattah

2016-12-01

The paper presents an adaptive particle swarm optimization (APSO) as an alternative method to determine the optimal orbital elements of the star η Bootis of MK type G0 IV. The proposed algorithm transforms the problem of finding periodic orbits into the problem of detecting global minimizers as a function, to get a best fit of Keplerian and Phase curves. The experimental results demonstrate that the proposed approach of APSO generally more accurate than the standard particle swarm optimization (PSO) and other published optimization algorithms, in terms of solution accuracy, convergence speed and algorithm reliability.

Comparison of genetic algorithm methods for fuel management optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeChaine, M.D.; Feltus, M.A.

1995-12-31

The CIGARO system was developed for genetic algorithm fuel management optimization. Tests are performed to find the best fuel location swap mutation operator probability and to compare genetic algorithm to a truly random search method. Tests showed the fuel swap probability should be between 0% and 10%, and a 50% definitely hampered the optimization. The genetic algorithm performed significantly better than the random search method, which did not even satisfy the peak normalized power constraint.

Multiple shooting algorithms for jump-discontinuous problems in optimal control and estimation

NASA Technical Reports Server (NTRS)

Mook, D. J.; Lew, Jiann-Shiun

1991-01-01

Multiple shooting algorithms are developed for jump-discontinuous two-point boundary value problems arising in optimal control and optimal estimation. Examples illustrating the origin of such problems are given to motivate the development of the solution algorithms. The algorithms convert the necessary conditions, consisting of differential equations and transversality conditions, into algebraic equations. The solution of the algebraic equations provides exact solutions for linear problems. The existence and uniqueness of the solution are proved.

Aerodynamic Shape Optimization Using A Real-Number-Encoded Genetic Algorithm

NASA Technical Reports Server (NTRS)

Holst, Terry L.; Pulliam, Thomas H.

2001-01-01

A new method for aerodynamic shape optimization using a genetic algorithm with real number encoding is presented. The algorithm is used to optimize three different problems, a simple hill climbing problem, a quasi-one-dimensional nozzle problem using an Euler equation solver and a three-dimensional transonic wing problem using a nonlinear potential solver. Results indicate that the genetic algorithm is easy to implement and extremely reliable, being relatively insensitive to design space noise.

GAMBIT: A Parameterless Model-Based Evolutionary Algorithm for Mixed-Integer Problems.

PubMed

Sadowski, Krzysztof L; Thierens, Dirk; Bosman, Peter A N

2018-01-01

Learning and exploiting problem structure is one of the key challenges in optimization. This is especially important for black-box optimization (BBO) where prior structural knowledge of a problem is not available. Existing model-based Evolutionary Algorithms (EAs) are very efficient at learning structure in both the discrete, and in the continuous domain. In this article, discrete and continuous model-building mechanisms are integrated for the Mixed-Integer (MI) domain, comprising discrete and continuous variables. We revisit a recently introduced model-based evolutionary algorithm for the MI domain, the Genetic Algorithm for Model-Based mixed-Integer opTimization (GAMBIT). We extend GAMBIT with a parameterless scheme that allows for practical use of the algorithm without the need to explicitly specify any parameters. We furthermore contrast GAMBIT with other model-based alternatives. The ultimate goal of processing mixed dependences explicitly in GAMBIT is also addressed by introducing a new mechanism for the explicit exploitation of mixed dependences. We find that processing mixed dependences with this novel mechanism allows for more efficient optimization. We further contrast the parameterless GAMBIT with Mixed-Integer Evolution Strategies (MIES) and other state-of-the-art MI optimization algorithms from the General Algebraic Modeling System (GAMS) commercial algorithm suite on problems with and without constraints, and show that GAMBIT is capable of solving problems where variable dependences prevent many algorithms from successfully optimizing them.

Finite Set Control Transcription for Optimal Control Applications

DTIC Science & Technology

2009-05-01

Figures 1.1 The Parameters of x . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.1 Categories of Optimization Algorithms ...Programming (NLP) algorithm , such as SNOPT2 (hereafter, called the optimizer). The Finite Set Control Transcription (FSCT) method is essentially a...artificial neural networks, ge- netic algorithms , or combinations thereof for analysis.4,5 Indeed, an actual biological neural network is an example of

Design Genetic Algorithm Optimization Education Software Based Fuzzy Controller for a Tricopter Fly Path Planning

ERIC Educational Resources Information Center

Tran, Huu-Khoa; Chiou, Juing -Shian; Peng, Shou-Tao

2016-01-01

In this paper, the feasibility of a Genetic Algorithm Optimization (GAO) education software based Fuzzy Logic Controller (GAO-FLC) for simulating the flight motion control of Unmanned Aerial Vehicles (UAVs) is designed. The generated flight trajectories integrate the optimized Scaling Factors (SF) fuzzy controller gains by using GAO algorithm. The…

Comparison and optimization of radar-based hail detection algorithms in Slovenia

NASA Astrophysics Data System (ADS)

Stržinar, Gregor; Skok, Gregor

2018-05-01

Four commonly used radar-based hail detection algorithms are evaluated and optimized in Slovenia. The algorithms are verified against ground observations of hail at manned stations in the period between May and August, from 2002 to 2010. The algorithms are optimized by determining the optimal values of all possible algorithm parameters. A number of different contingency-table-based scores are evaluated with a combination of Critical Success Index and frequency bias proving to be the best choice for optimization. The best performance indexes are given by Waldvogel and the severe hail index, followed by vertically integrated liquid and maximum radar reflectivity. Using the optimal parameter values, a hail frequency climatology map for the whole of Slovenia is produced. The analysis shows that there is a considerable variability of hail occurrence within the Republic of Slovenia. The hail frequency ranges from almost 0 to 1.7 hail days per year with an average value of about 0.7 hail days per year.

A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system.

PubMed

Mohamed, Ahmed F; Elarini, Mahdi M; Othman, Ahmed M

2014-05-01

One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system

PubMed Central

Mohamed, Ahmed F.; Elarini, Mahdi M.; Othman, Ahmed M.

2013-01-01

One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt. PMID:25685507

Hybrid-optimization strategy for the communication of large-scale Kinetic Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Wu, Baodong; Li, Shigang; Zhang, Yunquan; Nie, Ningming

2017-02-01

The parallel Kinetic Monte Carlo (KMC) algorithm based on domain decomposition has been widely used in large-scale physical simulations. However, the communication overhead of the parallel KMC algorithm is critical, and severely degrades the overall performance and scalability. In this paper, we present a hybrid optimization strategy to reduce the communication overhead for the parallel KMC simulations. We first propose a communication aggregation algorithm to reduce the total number of messages and eliminate the communication redundancy. Then, we utilize the shared memory to reduce the memory copy overhead of the intra-node communication. Finally, we optimize the communication scheduling using the neighborhood collective operations. We demonstrate the scalability and high performance of our hybrid optimization strategy by both theoretical and experimental analysis. Results show that the optimized KMC algorithm exhibits better performance and scalability than the well-known open-source library-SPPARKS. On 32-node Xeon E5-2680 cluster (total 640 cores), the optimized algorithm reduces the communication time by 24.8% compared with SPPARKS.

Genetic algorithms for multicriteria shape optimization of induction furnace

NASA Astrophysics Data System (ADS)

Kůs, Pavel; Mach, František; Karban, Pavel; Doležel, Ivo

2012-09-01

In this contribution we deal with a multi-criteria shape optimization of an induction furnace. We want to find shape parameters of the furnace in such a way, that two different criteria are optimized. Since they cannot be optimized simultaneously, instead of one optimum we find set of partially optimal designs, so called Pareto front. We compare two different approaches to the optimization, one using nonlinear conjugate gradient method and second using variation of genetic algorithm. As can be seen from the numerical results, genetic algorithm seems to be the right choice for this problem. Solution of direct problem (coupled problem consisting of magnetic and heat field) is done using our own code Agros2D. It uses finite elements of higher order leading to fast and accurate solution of relatively complicated coupled problem. It also provides advanced scripting support, allowing us to prepare parametric model of the furnace and simply incorporate various types of optimization algorithms.

Robust tracking of a virtual electrode on a coronary sinus catheter for atrial fibrillation ablation procedures

NASA Astrophysics Data System (ADS)

Wu, Wen; Chen, Terrence; Strobel, Norbert; Comaniciu, Dorin

2012-02-01

Catheter tracking in X-ray fluoroscopic images has become more important in interventional applications for atrial fibrillation (AF) ablation procedures. It provides real-time guidance for the physicians and can be used as reference for motion compensation applications. In this paper, we propose a novel approach to track a virtual electrode (VE), which is a non-existing electrode on the coronary sinus (CS) catheter at a more proximal location than any real electrodes. Successful tracking of the VE can provide more accurate motion information than tracking of real electrodes. To achieve VE tracking, we first model the CS catheter as a set of electrodes which are detected by our previously published learning-based approach.1 The tracked electrodes are then used to generate the hypotheses for tracking the VE. Model-based hypotheses are fused and evaluated by a Bayesian framework. Evaluation has been conducted on a database of clinical AF ablation data including challenging scenarios such as low signal-to-noise ratio (SNR), occlusion and nonrigid deformation. Our approach obtains 0.54mm median error and 90% of evaluated data have errors less than 1.67mm. The speed of our tracking algorithm reaches 6 frames-per-second on most data. Our study on motion compensation shows that using the VE as reference provides a good point to detect non-physiological catheter motion during the AF ablation procedures.2

Automated Lead Optimization of MMP-12 Inhibitors Using a Genetic Algorithm.

PubMed

Pickett, Stephen D; Green, Darren V S; Hunt, David L; Pardoe, David A; Hughes, Ian

2011-01-13

Traditional lead optimization projects involve long synthesis and testing cycles, favoring extensive structure-activity relationship (SAR) analysis and molecular design steps, in an attempt to limit the number of cycles that a project must run to optimize a development candidate. Microfluidic-based chemistry and biology platforms, with cycle times of minutes rather than weeks, lend themselves to unattended autonomous operation. The bottleneck in the lead optimization process is therefore shifted from synthesis or test to SAR analysis and design. As such, the way is open to an algorithm-directed process, without the need for detailed user data analysis. Here, we present results of two synthesis and screening experiments, undertaken using traditional methodology, to validate a genetic algorithm optimization process for future application to a microfluidic system. The algorithm has several novel features that are important for the intended application. For example, it is robust to missing data and can suggest compounds for retest to ensure reliability of optimization. The algorithm is first validated on a retrospective analysis of an in-house library embedded in a larger virtual array of presumed inactive compounds. In a second, prospective experiment with MMP-12 as the target protein, 140 compounds are submitted for synthesis over 10 cycles of optimization. Comparison is made to the results from the full combinatorial library that was synthesized manually and tested independently. The results show that compounds selected by the algorithm are heavily biased toward the more active regions of the library, while the algorithm is robust to both missing data (compounds where synthesis failed) and inactive compounds. This publication places the full combinatorial library and biological data into the public domain with the intention of advancing research into algorithm-directed lead optimization methods.

Automated Lead Optimization of MMP-12 Inhibitors Using a Genetic Algorithm

PubMed Central

2010-01-01

Traditional lead optimization projects involve long synthesis and testing cycles, favoring extensive structure−activity relationship (SAR) analysis and molecular design steps, in an attempt to limit the number of cycles that a project must run to optimize a development candidate. Microfluidic-based chemistry and biology platforms, with cycle times of minutes rather than weeks, lend themselves to unattended autonomous operation. The bottleneck in the lead optimization process is therefore shifted from synthesis or test to SAR analysis and design. As such, the way is open to an algorithm-directed process, without the need for detailed user data analysis. Here, we present results of two synthesis and screening experiments, undertaken using traditional methodology, to validate a genetic algorithm optimization process for future application to a microfluidic system. The algorithm has several novel features that are important for the intended application. For example, it is robust to missing data and can suggest compounds for retest to ensure reliability of optimization. The algorithm is first validated on a retrospective analysis of an in-house library embedded in a larger virtual array of presumed inactive compounds. In a second, prospective experiment with MMP-12 as the target protein, 140 compounds are submitted for synthesis over 10 cycles of optimization. Comparison is made to the results from the full combinatorial library that was synthesized manually and tested independently. The results show that compounds selected by the algorithm are heavily biased toward the more active regions of the library, while the algorithm is robust to both missing data (compounds where synthesis failed) and inactive compounds. This publication places the full combinatorial library and biological data into the public domain with the intention of advancing research into algorithm-directed lead optimization methods. PMID:24900251

An Optimizing Space Data-Communications Scheduling Method and Algorithm with Interference Mitigation, Generalized for a Broad Class of Optimization Problems

NASA Technical Reports Server (NTRS)

Rash, James

2014-01-01

NASA's space data-communications infrastructure-the Space Network and the Ground Network-provide scheduled (as well as some limited types of unscheduled) data-communications services to user spacecraft. The Space Network operates several orbiting geostationary platforms (the Tracking and Data Relay Satellite System (TDRSS)), each with its own servicedelivery antennas onboard. The Ground Network operates service-delivery antennas at ground stations located around the world. Together, these networks enable data transfer between user spacecraft and their mission control centers on Earth. Scheduling data-communications events for spacecraft that use the NASA communications infrastructure-the relay satellites and the ground stations-can be accomplished today with software having an operational heritage dating from the 1980s or earlier. An implementation of the scheduling methods and algorithms disclosed and formally specified herein will produce globally optimized schedules with not only optimized service delivery by the space data-communications infrastructure but also optimized satisfaction of all user requirements and prescribed constraints, including radio frequency interference (RFI) constraints. Evolutionary algorithms, a class of probabilistic strategies for searching large solution spaces, is the essential technology invoked and exploited in this disclosure. Also disclosed are secondary methods and algorithms for optimizing the execution efficiency of the schedule-generation algorithms themselves. The scheduling methods and algorithms as presented are adaptable to accommodate the complexity of scheduling the civilian and/or military data-communications infrastructure within the expected range of future users and space- or ground-based service-delivery assets. Finally, the problem itself, and the methods and algorithms, are generalized and specified formally. The generalized methods and algorithms are applicable to a very broad class of combinatorial-optimization problems that encompasses, among many others, the problem of generating optimal space-data communications schedules.

An Efficient Optimization Method for Solving Unsupervised Data Classification Problems.

PubMed

Shabanzadeh, Parvaneh; Yusof, Rubiyah

2015-01-01

Unsupervised data classification (or clustering) analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has its own advantages, limitations, and deficiencies. Hence, research for novel and effective approaches for unsupervised data classification is still active. In this paper a heuristic algorithm, Biogeography-Based Optimization (BBO) algorithm, was adapted for data clustering problems by modifying the main operators of BBO algorithm, which is inspired from the natural biogeography distribution of different species. Similar to other population-based algorithms, BBO algorithm starts with an initial population of candidate solutions to an optimization problem and an objective function that is calculated for them. To evaluate the performance of the proposed algorithm assessment was carried on six medical and real life datasets and was compared with eight well known and recent unsupervised data classification algorithms. Numerical results demonstrate that the proposed evolutionary optimization algorithm is efficient for unsupervised data classification.

Study of 201 non-small cell lung cancer patients given stereotactic ablative radiation therapy shows local control dependence on dose calculation algorithm.

PubMed

Latifi, Kujtim; Oliver, Jasmine; Baker, Ryan; Dilling, Thomas J; Stevens, Craig W; Kim, Jongphil; Yue, Binglin; Demarco, Marylou; Zhang, Geoffrey G; Moros, Eduardo G; Feygelman, Vladimir

2014-04-01

Pencil beam (PB) and collapsed cone convolution (CCC) dose calculation algorithms differ significantly when used in the thorax. However, such differences have seldom been previously directly correlated with outcomes of lung stereotactic ablative body radiation (SABR). Data for 201 non-small cell lung cancer patients treated with SABR were analyzed retrospectively. All patients were treated with 50 Gy in 5 fractions of 10 Gy each. The radiation prescription mandated that 95% of the planning target volume (PTV) receive the prescribed dose. One hundred sixteen patients were planned with BrainLab treatment planning software (TPS) with the PB algorithm and treated on a Novalis unit. The other 85 were planned on the Pinnacle TPS with the CCC algorithm and treated on a Varian linac. Treatment planning objectives were numerically identical for both groups. The median follow-up times were 24 and 17 months for the PB and CCC groups, respectively. The primary endpoint was local/marginal control of the irradiated lesion. Gray's competing risk method was used to determine the statistical differences in local/marginal control rates between the PB and CCC groups. Twenty-five patients planned with PB and 4 patients planned with the CCC algorithms to the same nominal doses experienced local recurrence. There was a statistically significant difference in recurrence rates between the PB and CCC groups (hazard ratio 3.4 [95% confidence interval: 1.18-9.83], Gray's test P=.019). The differences (Δ) between the 2 algorithms for target coverage were as follows: ΔD99GITV = 7.4 Gy, ΔD99PTV = 10.4 Gy, ΔV90GITV = 13.7%, ΔV90PTV = 37.6%, ΔD95PTV = 9.8 Gy, and ΔDISO = 3.4 Gy. GITV = gross internal tumor volume. Local control in patients receiving who were planned to the same nominal dose with PB and CCC algorithms were statistically significantly different. Possible alternative explanations are described in the report, although they are not thought likely to explain the difference. We conclude that the difference is due to relative dosimetric underdosing of tumors with the PB algorithm. Copyright © 2014 Elsevier Inc. All rights reserved.

Fuel management optimization using genetic algorithms and expert knowledge

DOE Office of Scientific and Technical Information (OSTI.GOV)

DeChaine, M.D.; Feltus, M.A.

1996-09-01

The CIGARO fuel management optimization code based on genetic algorithms is described and tested. The test problem optimized the core lifetime for a pressurized water reactor with a penalty function constraint on the peak normalized power. A bit-string genotype encoded the loading patterns, and genotype bias was reduced with additional bits. Expert knowledge about fuel management was incorporated into the genetic algorithm. Regional crossover exchanged physically adjacent fuel assemblies and improved the optimization slightly. Biasing the initial population toward a known priority table significantly improved the optimization.

Network-optimized congestion pricing : a parable, model and algorithm

DOT National Transportation Integrated Search

1995-05-31

This paper recites a parable, formulates a model and devises an algorithm for optimizing tolls on a road network. Such tolls induce an equilibrium traffic flow that is at once system-optimal and user-optimal. The parable introduces the network-wide c...

Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high-dimensional data

PubMed Central

2017-01-01

In this paper, we propose a new automatic hyperparameter selection approach for determining the optimal network configuration (network structure and hyperparameters) for deep neural networks using particle swarm optimization (PSO) in combination with a steepest gradient descent algorithm. In the proposed approach, network configurations were coded as a set of real-number m-dimensional vectors as the individuals of the PSO algorithm in the search procedure. During the search procedure, the PSO algorithm is employed to search for optimal network configurations via the particles moving in a finite search space, and the steepest gradient descent algorithm is used to train the DNN classifier with a few training epochs (to find a local optimal solution) during the population evaluation of PSO. After the optimization scheme, the steepest gradient descent algorithm is performed with more epochs and the final solutions (pbest and gbest) of the PSO algorithm to train a final ensemble model and individual DNN classifiers, respectively. The local search ability of the steepest gradient descent algorithm and the global search capabilities of the PSO algorithm are exploited to determine an optimal solution that is close to the global optimum. We constructed several experiments on hand-written characters and biological activity prediction datasets to show that the DNN classifiers trained by the network configurations expressed by the final solutions of the PSO algorithm, employed to construct an ensemble model and individual classifier, outperform the random approach in terms of the generalization performance. Therefore, the proposed approach can be regarded an alternative tool for automatic network structure and parameter selection for deep neural networks. PMID:29236718

Optimally stopped variational quantum algorithms

NASA Astrophysics Data System (ADS)

Vinci, Walter; Shabani, Alireza

2018-04-01

Quantum processors promise a paradigm shift in high-performance computing which needs to be assessed by accurate benchmarking measures. In this article, we introduce a benchmark for the variational quantum algorithm (VQA), recently proposed as a heuristic algorithm for small-scale quantum processors. In VQA, a classical optimization algorithm guides the processor's quantum dynamics to yield the best solution for a given problem. A complete assessment of the scalability and competitiveness of VQA should take into account both the quality and the time of dynamics optimization. The method of optimal stopping, employed here, provides such an assessment by explicitly including time as a cost factor. Here, we showcase this measure for benchmarking VQA as a solver for some quadratic unconstrained binary optimization. Moreover, we show that a better choice for the cost function of the classical routine can significantly improve the performance of the VQA algorithm and even improve its scaling properties.

Voltage stability index based optimal placement of static VAR compensator and sizing using Cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Venkateswara Rao, B.; Kumar, G. V. Nagesh; Chowdary, D. Deepak; Bharathi, M. Aruna; Patra, Stutee

2017-07-01

This paper furnish the new Metaheuristic algorithm called Cuckoo Search Algorithm (CSA) for solving optimal power flow (OPF) problem with minimization of real power generation cost. The CSA is found to be the most efficient algorithm for solving single objective optimal power flow problems. The CSA performance is tested on IEEE 57 bus test system with real power generation cost minimization as objective function. Static VAR Compensator (SVC) is one of the best shunt connected device in the Flexible Alternating Current Transmission System (FACTS) family. It has capable of controlling the voltage magnitudes of buses by injecting the reactive power to system. In this paper SVC is integrated in CSA based Optimal Power Flow to optimize the real power generation cost. SVC is used to improve the voltage profile of the system. CSA gives better results as compared to genetic algorithm (GA) in both without and with SVC conditions.

Application of Particle Swarm Optimization Algorithm in the Heating System Planning Problem

PubMed Central

Ma, Rong-Jiang; Yu, Nan-Yang; Hu, Jun-Yi

2013-01-01

Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was improved. An actual case study was calculated to check its feasibility in practical use. The results show that the improved particle swarm optimization (IPSO) algorithm can more preferably solve the HSP problem than PSO algorithm. Moreover, the results also present the potential to provide useful information when making decisions in the practical planning process. Therefore, it is believed that if this approach is applied correctly and in combination with other elements, it can become a powerful and effective optimization tool for HSP problem. PMID:23935429

Optimization of wireless sensor networks based on chicken swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Wang, Qingxi; Zhu, Lihua

2017-05-01

In order to reduce the energy consumption of wireless sensor network and improve the survival time of network, the clustering routing protocol of wireless sensor networks based on chicken swarm optimization algorithm was proposed. On the basis of LEACH agreement, it was improved and perfected that the points on the cluster and the selection of cluster head using the chicken group optimization algorithm, and update the location of chicken which fall into the local optimum by Levy flight, enhance population diversity, ensure the global search capability of the algorithm. The new protocol avoided the die of partial node of intensive using by making balanced use of the network nodes, improved the survival time of wireless sensor network. The simulation experiments proved that the protocol is better than LEACH protocol on energy consumption, also is better than that of clustering routing protocol based on particle swarm optimization algorithm.

Particle swarm optimization based space debris surveillance network scheduling

NASA Astrophysics Data System (ADS)

Jiang, Hai; Liu, Jing; Cheng, Hao-Wen; Zhang, Yao

2017-02-01

The increasing number of space debris has created an orbital debris environment that poses increasing impact risks to existing space systems and human space flights. For the safety of in-orbit spacecrafts, we should optimally schedule surveillance tasks for the existing facilities to allocate resources in a manner that most significantly improves the ability to predict and detect events involving affected spacecrafts. This paper analyzes two criteria that mainly affect the performance of a scheduling scheme and introduces an artificial intelligence algorithm into the scheduling of tasks of the space debris surveillance network. A new scheduling algorithm based on the particle swarm optimization algorithm is proposed, which can be implemented in two different ways: individual optimization and joint optimization. Numerical experiments with multiple facilities and objects are conducted based on the proposed algorithm, and simulation results have demonstrated the effectiveness of the proposed algorithm.

A general optimality criteria algorithm for a class of engineering optimization problems

NASA Astrophysics Data System (ADS)

Belegundu, Ashok D.

2015-05-01

An optimality criteria (OC)-based algorithm for optimization of a general class of nonlinear programming (NLP) problems is presented. The algorithm is only applicable to problems where the objective and constraint functions satisfy certain monotonicity properties. For multiply constrained problems which satisfy these assumptions, the algorithm is attractive compared with existing NLP methods as well as prevalent OC methods, as the latter involve computationally expensive active set and step-size control strategies. The fixed point algorithm presented here is applicable not only to structural optimization problems but also to certain problems as occur in resource allocation and inventory models. Convergence aspects are discussed. The fixed point update or resizing formula is given physical significance, which brings out a strength and trim feature. The number of function evaluations remains independent of the number of variables, allowing the efficient solution of problems with large number of variables.

Asymptotic analysis of SPTA-based algorithms for no-wait flow shop scheduling problem with release dates.

PubMed

Ren, Tao; Zhang, Chuan; Lin, Lin; Guo, Meiting; Xie, Xionghang

2014-01-01

We address the scheduling problem for a no-wait flow shop to optimize total completion time with release dates. With the tool of asymptotic analysis, we prove that the objective values of two SPTA-based algorithms converge to the optimal value for sufficiently large-sized problems. To further enhance the performance of the SPTA-based algorithms, an improvement scheme based on local search is provided for moderate scale problems. New lower bound is presented for evaluating the asymptotic optimality of the algorithms. Numerical simulations demonstrate the effectiveness of the proposed algorithms.

Asymptotic Analysis of SPTA-Based Algorithms for No-Wait Flow Shop Scheduling Problem with Release Dates

PubMed Central

Ren, Tao; Zhang, Chuan; Lin, Lin; Guo, Meiting; Xie, Xionghang

2014-01-01

We address the scheduling problem for a no-wait flow shop to optimize total completion time with release dates. With the tool of asymptotic analysis, we prove that the objective values of two SPTA-based algorithms converge to the optimal value for sufficiently large-sized problems. To further enhance the performance of the SPTA-based algorithms, an improvement scheme based on local search is provided for moderate scale problems. New lower bound is presented for evaluating the asymptotic optimality of the algorithms. Numerical simulations demonstrate the effectiveness of the proposed algorithms. PMID:24764774

Sensitivity Analysis of Genetic Algorithm Parameters for Optimal Groundwater Monitoring Network Design

NASA Astrophysics Data System (ADS)

Abdeh-Kolahchi, A.; Satish, M.; Datta, B.

2004-05-01

A state art groundwater monitoring network design is introduced. The method combines groundwater flow and transport results with optimization Genetic Algorithm (GA) to identify optimal monitoring well locations. Optimization theory uses different techniques to find a set of parameter values that minimize or maximize objective functions. The suggested groundwater optimal monitoring network design is based on the objective of maximizing the probability of tracking a transient contamination plume by determining sequential monitoring locations. The MODFLOW and MT3DMS models included as separate modules within the Groundwater Modeling System (GMS) are used to develop three dimensional groundwater flow and contamination transport simulation. The groundwater flow and contamination simulation results are introduced as input to the optimization model, using Genetic Algorithm (GA) to identify the groundwater optimal monitoring network design, based on several candidate monitoring locations. The groundwater monitoring network design model is used Genetic Algorithms with binary variables representing potential monitoring location. As the number of decision variables and constraints increase, the non-linearity of the objective function also increases which make difficulty to obtain optimal solutions. The genetic algorithm is an evolutionary global optimization technique, which is capable of finding the optimal solution for many complex problems. In this study, the GA approach capable of finding the global optimal solution to a groundwater monitoring network design problem involving 18.4X 1018 feasible solutions will be discussed. However, to ensure the efficiency of the solution process and global optimality of the solution obtained using GA, it is necessary that appropriate GA parameter values be specified. The sensitivity analysis of genetic algorithms parameters such as random number, crossover probability, mutation probability, and elitism are discussed for solution of monitoring network design.

[Process-oriented cost calculation in interventional radiology. A case study].

PubMed

Mahnken, A H; Bruners, P; Günther, R W; Rasche, C

2012-01-01

Currently used costing methods such as cost centre accounting do not sufficiently reflect the process-based resource utilization in medicine. The goal of this study was to establish a process-oriented cost assessment of percutaneous radiofrequency (RF) ablation of liver and lung metastases. In each of 15 patients a detailed task analysis of the primary process of hepatic and pulmonary RF ablation was performed. Based on these data a dedicated cost calculation model was developed for each primary process. The costs of each process were computed and compared with the revenue for in-patients according to the German diagnosis-related groups (DRG) system 2010. The RF ablation of liver metastases in patients without relevant comorbidities and a low patient complexity level results in a loss of EUR 588.44, whereas the treatment of patients with a higher complexity level yields an acceptable profit. The treatment of pulmonary metastases is profitable even in cases of additional expenses due to complications. Process-oriented costing provides relevant information that is needed for understanding the economic impact of treatment decisions. It is well suited as a starting point for economically driven process optimization and reengineering. Under the terms of the German DRG 2010 system percutaneous RF ablation of lung metastases is economically reasonable, while RF ablation of liver metastases in cases of low patient complexity levels does not cover the costs.

Comparison of evolutionary algorithms for LPDA antenna optimization

NASA Astrophysics Data System (ADS)

Lazaridis, Pavlos I.; Tziris, Emmanouil N.; Zaharis, Zaharias D.; Xenos, Thomas D.; Cosmas, John P.; Gallion, Philippe B.; Holmes, Violeta; Glover, Ian A.

2016-08-01

A novel approach to broadband log-periodic antenna design is presented, where some of the most powerful evolutionary algorithms are applied and compared for the optimal design of wire log-periodic dipole arrays (LPDA) using Numerical Electromagnetics Code. The target is to achieve an optimal antenna design with respect to maximum gain, gain flatness, front-to-rear ratio (F/R) and standing wave ratio. The parameters of the LPDA optimized are the dipole lengths, the spacing between the dipoles, and the dipole wire diameters. The evolutionary algorithms compared are the Differential Evolution (DE), Particle Swarm (PSO), Taguchi, Invasive Weed (IWO), and Adaptive Invasive Weed Optimization (ADIWO). Superior performance is achieved by the IWO (best results) and PSO (fast convergence) algorithms.

Optimal recombination in genetic algorithms for flowshop scheduling problems

NASA Astrophysics Data System (ADS)

Kovalenko, Julia

2016-10-01

The optimal recombination problem consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. We prove NP-hardness of the optimal recombination for various variants of the flowshop scheduling problem with makespan criterion and criterion of maximum lateness. An algorithm for solving the optimal recombination problem for permutation flowshop problems is built, using enumeration of prefect matchings in a special bipartite graph. The algorithm is adopted for the classical flowshop scheduling problem and for the no-wait flowshop problem. It is shown that the optimal recombination problem for the permutation flowshop scheduling problem is solvable in polynomial time for almost all pairs of parent solutions as the number of jobs tends to infinity.

Application of genetic algorithm in modeling on-wafer inductors for up to 110 Ghz

NASA Astrophysics Data System (ADS)

Liu, Nianhong; Fu, Jun; Liu, Hui; Cui, Wenpu; Liu, Zhihong; Liu, Linlin; Zhou, Wei; Wang, Quan; Guo, Ao

2018-05-01

In this work, the genetic algorithm has been introducted into parameter extraction for on-wafer inductors for up to 110 GHz millimeter-wave operations, and nine independent parameters of the equivalent circuit model are optimized together. With the genetic algorithm, the model with the optimized parameters gives a better fitting accuracy than the preliminary parameters without optimization. Especially, the fitting accuracy of the Q value achieves a significant improvement after the optimization.

Social Emotional Optimization Algorithm for Nonlinear Constrained Optimization Problems

NASA Astrophysics Data System (ADS)

Xu, Yuechun; Cui, Zhihua; Zeng, Jianchao

Nonlinear programming problem is one important branch in operational research, and has been successfully applied to various real-life problems. In this paper, a new approach called Social emotional optimization algorithm (SEOA) is used to solve this problem which is a new swarm intelligent technique by simulating the human behavior guided by emotion. Simulation results show that the social emotional optimization algorithm proposed in this paper is effective and efficiency for the nonlinear constrained programming problems.

Chaotic Particle Swarm Optimization with Mutation for Classification

PubMed Central

Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

2015-01-01

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms. PMID:25709937

Cost versus life cycle assessment-based environmental impact optimization of drinking water production plants.

PubMed

Capitanescu, F; Rege, S; Marvuglia, A; Benetto, E; Ahmadi, A; Gutiérrez, T Navarrete; Tiruta-Barna, L

2016-07-15

Empowering decision makers with cost-effective solutions for reducing industrial processes environmental burden, at both design and operation stages, is nowadays a major worldwide concern. The paper addresses this issue for the sector of drinking water production plants (DWPPs), seeking for optimal solutions trading-off operation cost and life cycle assessment (LCA)-based environmental impact while satisfying outlet water quality criteria. This leads to a challenging bi-objective constrained optimization problem, which relies on a computationally expensive intricate process-modelling simulator of the DWPP and has to be solved with limited computational budget. Since mathematical programming methods are unusable in this case, the paper examines the performances in tackling these challenges of six off-the-shelf state-of-the-art global meta-heuristic optimization algorithms, suitable for such simulation-based optimization, namely Strength Pareto Evolutionary Algorithm (SPEA2), Non-dominated Sorting Genetic Algorithm (NSGA-II), Indicator-based Evolutionary Algorithm (IBEA), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), Differential Evolution (DE), and Particle Swarm Optimization (PSO). The results of optimization reveal that good reduction in both operating cost and environmental impact of the DWPP can be obtained. Furthermore, NSGA-II outperforms the other competing algorithms while MOEA/D and DE perform unexpectedly poorly. Copyright © 2016 Elsevier Ltd. All rights reserved.

Radiofrequency ablation for hepatocellular carcinoma: a prospective comparison of four radiofrequency devices.

PubMed

Lin, Shi-Ming; Lin, Chen-Chun; Chen, Wei-Ting; Chen, Yi-Chen; Hsu, Chao-Wei

2007-09-01

To compare the effectiveness of ablation techniques for hepatocellular carcinoma (HCC) with the use of four radiofrequency (RF) devices. One hundred patients with 133 HCC lesions no larger than 4 cm were treated with one of four RF devices: RF 2000 (maximum power, 100 W) and RF 3000 generators (maximum power, 200 W) with LeVeen expandable electrodes with a maximum dimension of 3.5 cm or 4 cm, internally cooled single electrode with a thermal dimension of 3 cm, and a RITA RF generator with expandable electrodes with a maximum dimension of 5 cm. Numbers of RF sessions needed per HCC to achieve complete necrosis were 1.4 +/- 0.5 with the RF 2000 device and greater than 1.1 +/- 0.3 with the other three devices (P < .05). The RF 2000 device required a more interactive algorithm than the RF 3000 device. Session times per patient were 31.7 minutes +/- 13.2 in the RF 2000 group and longer than 16.6 minutes +/- 7.5 in the RF 3000 group, 28.3 minutes +/- 12 in the RITA device group, and 27.1 minutes +/- 12 with the internally cooled electrode device (P < .005 for RF 2000 vs other devices and for RF 3000 vs RITA or internally cooled electrode device). Complete necrosis and local tumor progression rates at 2 years in the RF 2000, RF 3000, RITA, and internally cooled electrode device groups were 91.1%, 97.1%, 96.7%, and 96.8% and 12%, 8%, 8.2%, and 8.3%, respectively (P = .37). Ablation with the RF 3000 device required a shorter time than the other three devices and required a less interactive algorithm than the RF 2000 device. However, complete necrosis and local tumor progression rates were similar among devices.

AI-BL1.0: a program for automatic on-line beamline optimization using the evolutionary algorithm.

PubMed

Xi, Shibo; Borgna, Lucas Santiago; Zheng, Lirong; Du, Yonghua; Hu, Tiandou

2017-01-01

In this report, AI-BL1.0, an open-source Labview-based program for automatic on-line beamline optimization, is presented. The optimization algorithms used in the program are Genetic Algorithm and Differential Evolution. Efficiency was improved by use of a strategy known as Observer Mode for Evolutionary Algorithm. The program was constructed and validated at the XAFCA beamline of the Singapore Synchrotron Light Source and 1W1B beamline of the Beijing Synchrotron Radiation Facility.

[Endoscopic radiofrequency ablation for liver metastasis of colorectal cancer].

PubMed

Takahashi, Masahiro; Nitta, Hiroyuki; Sasaki, Akira; Fujita, Tomohiro; Obuchi, Toru; Hoshikawa, Koichi; Otsuka, Koki; Kawamura, Hidenobu; Higuchi, Taro; Asahi, Hiroshi; Saito, Kazuyoshi

2005-10-01

The application of radiofrequency ablation (RFA) for liver metastasis of colorectal cancer has not yet acquired an established status in clinical cancer therapy research. Removing as much tumor tissue as possible is desirable, but some cases do not allow optimal surgical ablation due to general condition of the patient and tumor status. We introduced endoscopic RFA for liver cancer in 2003, and have applied the procedure to 6 cases with H1 or H2 liver metastases of colorectal cancer to which surgical ablation could not be applied due to the poor general health of patients. Mean tumor diameter was 22.9 mm, and mean number of tumors per patient was 1.2. Tumor location was: S4, n = 2; S5, n = 1; S4, n = 1; S7, n = 2; and S8, n = 1. Mean frequency of session was 3.0. No complications occurred in any cases, and no reoperations were required. Although no recurrence of tumors in the vicinity of ablation was observed, 2 cases of each lung metastasis and intrahepatic recurrence were identified. Intrahepatic recurrence underwent hepatic arterial infusion (HAI) chemotherapy for simultaneous metastatic hepatic tumors (H2) prior to RFA, and relapses occurred in the metastatic focus where the efficacy of HAI was observed. At this point, 2 deaths were reported, 1 each from cancer and other diseases, and mean duration of survival after the procedure was 451.2 days. These results indicate that endoscopic RFA with good local control should be an available treatment for cases involving colorectal cancer with metastasis to the liver in which surgical ablation is difficult to apply.

Persistent Atrial Fibrillation Ablation using the Tip-Versatile Ablation Catheter.

PubMed

Davies, Edward J; Clayton, Ben; Lines, Ian; Haywood, Guy A

2016-07-01

The mechanisms by which persistent atrial fibrillation (PsAF) develops are incompletely understood. Consequently, the optimal strategy for the ablative management of PsAF remains debated. Current methods are often time consuming, complex and non-reproducible. We assessed the Tip-Versatile Ablation Catheter (T-VAC) technique, a rapidly delivered, empirical technique based on the box-set concept using duty-cycled linear catheter ablation technology. Forty-four procedures in 40 patients undergoing PsAF ablation with the novel technique were prospectively entered onto a database: 27 de novo. Primary endpoint was freedom from arrhythmia at over two-year follow-up. Secondary endpoints were time to first arrhythmia recurrence, freedom from atrial fibrillation (AF) on and off antiarrhythmic drugs (AAD), procedural and fluoroscopy duration and complication rate. At mean follow-up of 33 months, absolute freedom from arrhythmia recurrence was 45% in the de novo group. Overall, at 33 (IQR 24-63) months, 60% of de novo patients were in sustained normal sinus rhythm and a further 15% reported only occasional paroxysms of AF at long-term follow-up. Procedure time was 192±25 mins, total energy delivered 2239±883s and fluoroscopy time was 60±10mins. In selected patients with persistent AF, a long-term rate of 60% arrhythmia free survival off AAD can be achieved using this novel T-VAC technique. Copyright © 2016 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

Computational Fluid Dynamic Solutions of Optimized Heat Shields Designed for Earth Entry

DTIC Science & Technology

2010-01-01

domain ρ = Density (kg/m3) σ = Stefan Boltzmann constant τ = Shear stress tensor τT−V = T-V relaxation time τe−V = e-V relaxation time xi φ = Sweep angle...Vehicle DES = Differential evolutionary Scheme DOR = Design Optimization Tools DPLR = Data Parallel Line Relaxation GSLR = Gauss- Seidel Line... Stefan - Boltzmann constant. This model provides accurate heating predictions, especially for the non-ablating heat-shields explored in this work. Various

Belief Propagation Algorithm for Portfolio Optimization Problems

PubMed Central

2015-01-01

The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007)]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm. PMID:26305462

Nash equilibrium and multi criterion aerodynamic optimization

NASA Astrophysics Data System (ADS)

Tang, Zhili; Zhang, Lianhe

2016-06-01

Game theory and its particular Nash Equilibrium (NE) are gaining importance in solving Multi Criterion Optimization (MCO) in engineering problems over the past decade. The solution of a MCO problem can be viewed as a NE under the concept of competitive games. This paper surveyed/proposed four efficient algorithms for calculating a NE of a MCO problem. Existence and equivalence of the solution are analyzed and proved in the paper based on fixed point theorem. Specific virtual symmetric Nash game is also presented to set up an optimization strategy for single objective optimization problems. Two numerical examples are presented to verify proposed algorithms. One is mathematical functions' optimization to illustrate detailed numerical procedures of algorithms, the other is aerodynamic drag reduction of civil transport wing fuselage configuration by using virtual game. The successful application validates efficiency of algorithms in solving complex aerodynamic optimization problem.

Belief Propagation Algorithm for Portfolio Optimization Problems.

PubMed

Shinzato, Takashi; Yasuda, Muneki

2015-01-01

The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007)]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm.

Thrust stand evaluation of engine performance improvement algorithms in an F-15 airplane

NASA Technical Reports Server (NTRS)

Conners, Timothy R.

1992-01-01

Results are presented from the evaluation of the performance seeking control (PSC) optimization algorithm developed by Smith et al. (1990) for F-15 aircraft, which optimizes the quasi-steady-state performance of an F100 derivative turbofan engine for several modes of operation. The PSC algorithm uses onboard software engine model that calculates thrust, stall margin, and other unmeasured variables for use in the optimization. Comparisons are presented between the load cell measurements, PSC onboard model thrust calculations, and posttest state variable model computations. Actual performance improvements using the PSC algorithm are presented for its various modes. The results of using PSC algorithm are compared with similar test case results using the HIDEC algorithm.

Dual-slot antennas for microwave tissue heating: parametric design analysis and experimental validation.

PubMed

Brace, Christopher L

2011-07-01

Design and validate an efficient dual-slot coaxial microwave ablation antenna that produces an approximately spherical heating pattern to match the shape of most abdominal and pulmonary tumor targets. A dual-slot antenna geometry was utilized for this study. Permutations of the antenna geometry using proximal and distal slot widths from 1 to 10 mm separated by 1-20 mm were analyzed using finite-element electromagnetic simulations. From this series, the most optimal antenna geometry was selected using a two-term sigmoidal objective function to minimize antenna reflection coefficient and maximize the diameter-to-length aspect ratio of heat generation. Sensitivities to variations in tissue properties and insertion depth were also evaluated in numerical models. The most optimal dual-slot geometry of the parametric analysis was then fabricated from semirigid coaxial cable. Antenna reflection coefficients at various insertion depths were recorded in ex vivo bovine livers and compared to numerical results. Ablation zones were then created by applying 50 W for 2-10 min in simulations and ex vivo livers. Mean zone diameter, length, aspect ratio, and reflection coefficients before and after heating were then compared to a conventional monopole antenna using ANOVA with post-hoc t-tests. Statistical significance was indicated for P <0.05. Antenna performance was highly sensitive to dual-slot geometry. The best-performing designs utilized a proximal slot width of 1 mm, distal slot width of 4 mm +/- 1 mm and separation of 8 mm +/- 1 mm. These designs were characterized by an active choking mechanism that focused heating to the distal tip of the antenna. A dual-band resonance was observed in the most optimal design, with a minimum reflection coefficient of -20.9 dB at 2.45 and 1.25 GHz. Total operating bandwidth was greater than 1 GHz, but the desired heating pattern was achieved only near 2.45 GHz. As a result, antenna performance was robust to changes in insertion depth and variations in relative permittivity of the surrounding tissue medium. In both simulations and ex vivo liver, the dual-slot antenna created ablations greater in diameter than a coaxial monopole (35 mm +/- 2 mm versus 31 mm +/- 2 mm; P<0.05), while also shorter in length (49 mm +/- 2 mm versus 60 mm +/- 6 mm; P < 0.001) after 10 min. Similar results were obtained after 2 and 5 min as well. Dual-slot antennas can produce more spherical ablation zones while retaining low reflection coefficients. These benefits are obtained without adding to the antenna diameter. Further evaluation for clinical microwave ablation appears warranted.

An Effective Hybrid Evolutionary Algorithm for Solving the Numerical Optimization Problems

NASA Astrophysics Data System (ADS)

Qian, Xiaohong; Wang, Xumei; Su, Yonghong; He, Liu

2018-04-01

There are many different algorithms for solving complex optimization problems. Each algorithm has been applied successfully in solving some optimization problems, but not efficiently in other problems. In this paper the Cauchy mutation and the multi-parent hybrid operator are combined to propose a hybrid evolutionary algorithm based on the communication (Mixed Evolutionary Algorithm based on Communication), hereinafter referred to as CMEA. The basic idea of the CMEA algorithm is that the initial population is divided into two subpopulations. Cauchy mutation operators and multiple paternal crossover operators are used to perform two subpopulations parallelly to evolve recursively until the downtime conditions are met. While subpopulation is reorganized, the individual is exchanged together with information. The algorithm flow is given and the performance of the algorithm is compared using a number of standard test functions. Simulation results have shown that this algorithm converges significantly faster than FEP (Fast Evolutionary Programming) algorithm, has good performance in global convergence and stability and is superior to other compared algorithms.

Hybrid simulated annealing and its application to optimization of hidden Markov models for visual speech recognition.

PubMed

Lee, Jong-Seok; Park, Cheol Hoon

2010-08-01

We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solution for the current one to improve the convergence speed and the quality of solutions. We mathematically prove that the sequence of the objective values converges in probability to the global optimum in the algorithm. The algorithm is applied to train HMMs that are used as visual speech recognizers. While the popular training method of HMMs, the expectation-maximization algorithm, achieves only local optima in the parameter space, the proposed method can perform global optimization of the parameters of HMMs and thereby obtain solutions yielding improved recognition performance. The superiority of the proposed algorithm to the conventional ones is demonstrated via isolated word recognition experiments.

Capacity improvement using simulation optimization approaches: A case study in the thermotechnology industry

NASA Astrophysics Data System (ADS)

Yelkenci Köse, Simge; Demir, Leyla; Tunalı, Semra; Türsel Eliiyi, Deniz

2015-02-01

In manufacturing systems, optimal buffer allocation has a considerable impact on capacity improvement. This study presents a simulation optimization procedure to solve the buffer allocation problem in a heat exchanger production plant so as to improve the capacity of the system. For optimization, three metaheuristic-based search algorithms, i.e. a binary-genetic algorithm (B-GA), a binary-simulated annealing algorithm (B-SA) and a binary-tabu search algorithm (B-TS), are proposed. These algorithms are integrated with the simulation model of the production line. The simulation model, which captures the stochastic and dynamic nature of the production line, is used as an evaluation function for the proposed metaheuristics. The experimental study with benchmark problem instances from the literature and the real-life problem show that the proposed B-TS algorithm outperforms B-GA and B-SA in terms of solution quality.

Design and Optimization Method of a Two-Disk Rotor System

NASA Astrophysics Data System (ADS)

Huang, Jingjing; Zheng, Longxi; Mei, Qing

2016-04-01

An integrated analytical method based on multidisciplinary optimization software Isight and general finite element software ANSYS was proposed in this paper. Firstly, a two-disk rotor system was established and the mode, humorous response and transient response at acceleration condition were analyzed with ANSYS. The dynamic characteristics of the two-disk rotor system were achieved. On this basis, the two-disk rotor model was integrated to the multidisciplinary design optimization software Isight. According to the design of experiment (DOE) and the dynamic characteristics, the optimization variables, optimization objectives and constraints were confirmed. After that, the multi-objective design optimization of the transient process was carried out with three different global optimization algorithms including Evolutionary Optimization Algorithm, Multi-Island Genetic Algorithm and Pointer Automatic Optimizer. The optimum position of the two-disk rotor system was obtained at the specified constraints. Meanwhile, the accuracy and calculation numbers of different optimization algorithms were compared. The optimization results indicated that the rotor vibration reached the minimum value and the design efficiency and quality were improved by the multidisciplinary design optimization in the case of meeting the design requirements, which provided the reference to improve the design efficiency and reliability of the aero-engine rotor.

A Novel Latin Hypercube Algorithm via Translational Propagation

PubMed Central

Pan, Guang; Ye, Pengcheng

2014-01-01

Metamodels have been widely used in engineering design to facilitate analysis and optimization of complex systems that involve computationally expensive simulation programs. The accuracy of metamodels is directly related to the experimental designs used. Optimal Latin hypercube designs are frequently used and have been shown to have good space-filling and projective properties. However, the high cost in constructing them limits their use. In this paper, a methodology for creating novel Latin hypercube designs via translational propagation and successive local enumeration algorithm (TPSLE) is developed without using formal optimization. TPSLE algorithm is based on the inspiration that a near optimal Latin Hypercube design can be constructed by a simple initial block with a few points generated by algorithm SLE as a building block. In fact, TPSLE algorithm offers a balanced trade-off between the efficiency and sampling performance. The proposed algorithm is compared to two existing algorithms and is found to be much more efficient in terms of the computation time and has acceptable space-filling and projective properties. PMID:25276844

A study on the performance comparison of metaheuristic algorithms on the learning of neural networks

NASA Astrophysics Data System (ADS)

Lai, Kee Huong; Zainuddin, Zarita; Ong, Pauline

2017-08-01

The learning or training process of neural networks entails the task of finding the most optimal set of parameters, which includes translation vectors, dilation parameter, synaptic weights, and bias terms. Apart from the traditional gradient descent-based methods, metaheuristic methods can also be used for this learning purpose. Since the inception of genetic algorithm half a century ago, the last decade witnessed the explosion of a variety of novel metaheuristic algorithms, such as harmony search algorithm, bat algorithm, and whale optimization algorithm. Despite the proof of the no free lunch theorem in the discipline of optimization, a survey in the literature of machine learning gives contrasting results. Some researchers report that certain metaheuristic algorithms are superior to the others, whereas some others argue that different metaheuristic algorithms give comparable performance. As such, this paper aims to investigate if a certain metaheuristic algorithm will outperform the other algorithms. In this work, three metaheuristic algorithms, namely genetic algorithms, particle swarm optimization, and harmony search algorithm are considered. The algorithms are incorporated in the learning of neural networks and their classification results on the benchmark UCI machine learning data sets are compared. It is found that all three metaheuristic algorithms give similar and comparable performance, as captured in the average overall classification accuracy. The results corroborate the findings reported in the works done by previous researchers. Several recommendations are given, which include the need of statistical analysis to verify the results and further theoretical works to support the obtained empirical results.

Planning Under Uncertainty: Methods and Applications

DTIC Science & Technology

2010-06-09

begun research into fundamental algorithms for optimization and re?optimization of continuous optimization problems (such as linear and quadratic... algorithm yields a 14.3% improvement over the original design while saving 68.2 % of the simulation evaluations compared to standard sample-path...They provide tools for building and justifying computational algorithms for such problems. Year. 2010 Month: 03 Final Research under this grant

Application of cellular automatons and ant algorithms in avionics

NASA Astrophysics Data System (ADS)

Kuznetsov, A. V.; Selvesiuk, N. I.; Platoshin, G. A.; Semenova, E. V.

2018-03-01

The paper considers two algorithms for searching quasi-optimal solutions of discrete optimization problems with regard to the tasks of avionics placing. The first one solves the problem of optimal placement of devices by installation locations, the second one is for the problem of finding the shortest route between devices. Solutions are constructed using a cellular automaton and the ant colony algorithm.

Genetic evolutionary taboo search for optimal marker placement in infrared patient setup

NASA Astrophysics Data System (ADS)

Riboldi, M.; Baroni, G.; Spadea, M. F.; Tagaste, B.; Garibaldi, C.; Cambria, R.; Orecchia, R.; Pedotti, A.

2007-09-01

In infrared patient setup adequate selection of the external fiducial configuration is required for compensating inner target displacements (target registration error, TRE). Genetic algorithms (GA) and taboo search (TS) were applied in a newly designed approach to optimal marker placement: the genetic evolutionary taboo search (GETS) algorithm. In the GETS paradigm, multiple solutions are simultaneously tested in a stochastic evolutionary scheme, where taboo-based decision making and adaptive memory guide the optimization process. The GETS algorithm was tested on a group of ten prostate patients, to be compared to standard optimization and to randomly selected configurations. The changes in the optimal marker configuration, when TRE is minimized for OARs, were specifically examined. Optimal GETS configurations ensured a 26.5% mean decrease in the TRE value, versus 19.4% for conventional quasi-Newton optimization. Common features in GETS marker configurations were highlighted in the dataset of ten patients, even when multiple runs of the stochastic algorithm were performed. Including OARs in TRE minimization did not considerably affect the spatial distribution of GETS marker configurations. In conclusion, the GETS algorithm proved to be highly effective in solving the optimal marker placement problem. Further work is needed to embed site-specific deformation models in the optimization process.

Application of the gravity search algorithm to multi-reservoir operation optimization

NASA Astrophysics Data System (ADS)

Bozorg-Haddad, Omid; Janbaz, Mahdieh; Loáiciga, Hugo A.

2016-12-01

Complexities in river discharge, variable rainfall regime, and drought severity merit the use of advanced optimization tools in multi-reservoir operation. The gravity search algorithm (GSA) is an evolutionary optimization algorithm based on the law of gravity and mass interactions. This paper explores the GSA's efficacy for solving benchmark functions, single reservoir, and four-reservoir operation optimization problems. The GSA's solutions are compared with those of the well-known genetic algorithm (GA) in three optimization problems. The results show that the GSA's results are closer to the optimal solutions than the GA's results in minimizing the benchmark functions. The average values of the objective function equal 1.218 and 1.746 with the GSA and GA, respectively, in solving the single-reservoir hydropower operation problem. The global solution equals 1.213 for this same problem. The GSA converged to 99.97% of the global solution in its average-performing history, while the GA converged to 97% of the global solution of the four-reservoir problem. Requiring fewer parameters for algorithmic implementation and reaching the optimal solution in fewer number of functional evaluations are additional advantages of the GSA over the GA. The results of the three optimization problems demonstrate a superior performance of the GSA for optimizing general mathematical problems and the operation of reservoir systems.