Motion and positional error correction for cone beam 3D-reconstruction with mobile C-arms.

PubMed

Bodensteiner, C; Darolti, C; Schumacher, H; Matthäus, L; Schweikard, A

2007-01-01

CT-images acquired by mobile C-arm devices can contain artefacts caused by positioning errors. We propose a data driven method based on iterative 3D-reconstruction and 2D/3D-registration to correct projection data inconsistencies. With a 2D/3D-registration algorithm, transformations are computed to align the acquired projection images to a previously reconstructed volume. In an iterative procedure, the reconstruction algorithm uses the results of the registration step. This algorithm also reduces small motion artefacts within 3D-reconstructions. Experiments with simulated projections from real patient data show the feasibility of the proposed method. In addition, experiments with real projection data acquired with an experimental robotised C-arm device have been performed with promising results.

Ultra Wide-Band Localization and SLAM: A Comparative Study for Mobile Robot Navigation

PubMed Central

Segura, Marcelo J.; Auat Cheein, Fernando A.; Toibero, Juan M.; Mut, Vicente; Carelli, Ricardo

2011-01-01

In this work, a comparative study between an Ultra Wide-Band (UWB) localization system and a Simultaneous Localization and Mapping (SLAM) algorithm is presented. Due to its high bandwidth and short pulses length, UWB potentially allows great accuracy in range measurements based on Time of Arrival (TOA) estimation. SLAM algorithms recursively estimates the map of an environment and the pose (position and orientation) of a mobile robot within that environment. The comparative study presented here involves the performance analysis of implementing in parallel an UWB localization based system and a SLAM algorithm on a mobile robot navigating within an environment. Real time results as well as error analysis are also shown in this work. PMID:22319397

Self-localization for an autonomous mobile robot based on an omni-directional vision system

NASA Astrophysics Data System (ADS)

Chiang, Shu-Yin; Lin, Kuang-Yu; Chia, Tsorng-Lin

2013-12-01

In this study, we designed an autonomous mobile robot based on the rules of the Federation of International Robotsoccer Association (FIRA) RoboSot category, integrating the techniques of computer vision, real-time image processing, dynamic target tracking, wireless communication, self-localization, motion control, path planning, and control strategy to achieve the contest goal. The self-localization scheme of the mobile robot is based on the algorithms featured in the images from its omni-directional vision system. In previous works, we used the image colors of the field goals as reference points, combining either dual-circle or trilateration positioning of the reference points to achieve selflocalization of the autonomous mobile robot. However, because the image of the game field is easily affected by ambient light, positioning systems exclusively based on color model algorithms cause errors. To reduce environmental effects and achieve the self-localization of the robot, the proposed algorithm is applied in assessing the corners of field lines by using an omni-directional vision system. Particularly in the mid-size league of the RobotCup soccer competition, selflocalization algorithms based on extracting white lines from the soccer field have become increasingly popular. Moreover, white lines are less influenced by light than are the color model of the goals. Therefore, we propose an algorithm that transforms the omni-directional image into an unwrapped transformed image, enhancing the extraction features. The process is described as follows: First, radical scan-lines were used to process omni-directional images, reducing the computational load and improving system efficiency. The lines were radically arranged around the center of the omni-directional camera image, resulting in a shorter computational time compared with the traditional Cartesian coordinate system. However, the omni-directional image is a distorted image, which makes it difficult to recognize the position of the robot. Therefore, image transformation was required to implement self-localization. Second, we used an approach to transform the omni-directional images into panoramic images. Hence, the distortion of the white line can be fixed through the transformation. The interest points that form the corners of the landmark were then located using the features from accelerated segment test (FAST) algorithm. In this algorithm, a circle of sixteen pixels surrounding the corner candidate is considered and is a high-speed feature detector in real-time frame rate applications. Finally, the dual-circle, trilateration, and cross-ratio projection algorithms were implemented in choosing the corners obtained from the FAST algorithm and localizing the position of the robot. The results demonstrate that the proposed algorithm is accurate, exhibiting a 2-cm position error in the soccer field measuring 600 cm2 x 400 cm2.

A generic sun-tracking algorithm for on-axis solar collector in mobile platforms

NASA Astrophysics Data System (ADS)

Lai, An-Chow; Chong, Kok-Keong; Lim, Boon-Han; Ho, Ming-Cheng; Yap, See-Hao; Heng, Chun-Kit; Lee, Jer-Vui; King, Yeong-Jin

2015-04-01

This paper proposes a novel dynamic sun-tracking algorithm which allows accurate tracking of the sun for both non-concentrated and concentrated photovoltaic systems located on mobile platforms to maximize solar energy extraction. The proposed algorithm takes not only the date, time, and geographical information, but also the dynamic changes of coordinates of the mobile platforms into account to calculate the sun position angle relative to ideal azimuth-elevation axes in real time using general sun-tracking formulas derived by Chong and Wong. The algorithm acquires data from open-loop sensors, i.e. global position system (GPS) and digital compass, which are readily available in many off-the-shelf portable gadgets, such as smart phone, to instantly capture the dynamic changes of coordinates of mobile platforms. Our experiments found that a highly accurate GPS is not necessary as the coordinate changes of practical mobile platforms are not fast enough to produce significant differences in the calculation of the incident angle. On the contrary, it is critical to accurately identify the quadrant and angle where the mobile platforms are moving toward in real time, which can be resolved by using digital compass. In our implementation, a noise filtering mechanism is found necessary to remove unexpected spikes in the readings of the digital compass to ensure stability in motor actuations and effectiveness in continuous tracking. Filtering mechanisms being studied include simple moving average and linear regression; the results showed that a compound function of simple moving average and linear regression produces a better outcome. Meanwhile, we found that a sampling interval is useful to avoid excessive motor actuations and power consumption while not sacrificing the accuracy of sun-tracking.

A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality

NASA Astrophysics Data System (ADS)

Cheung, KW; So, HC; Ma, W.-K.; Chan, YT

2006-12-01

The problem of locating a mobile terminal has received significant attention in the field of wireless communications. Time-of-arrival (TOA), received signal strength (RSS), time-difference-of-arrival (TDOA), and angle-of-arrival (AOA) are commonly used measurements for estimating the position of the mobile station. In this paper, we present a constrained weighted least squares (CWLS) mobile positioning approach that encompasses all the above described measurement cases. The advantages of CWLS include performance optimality and capability of extension to hybrid measurement cases (e.g., mobile positioning using TDOA and AOA measurements jointly). Assuming zero-mean uncorrelated measurement errors, we show by mean and variance analysis that all the developed CWLS location estimators achieve zero bias and the Cramér-Rao lower bound approximately when measurement error variances are small. The asymptotic optimum performance is also confirmed by simulation results.

Path planning in GPS-denied environments via collective intelligence of distributed sensor networks

NASA Astrophysics Data System (ADS)

Jha, Devesh K.; Chattopadhyay, Pritthi; Sarkar, Soumik; Ray, Asok

2016-05-01

This paper proposes a framework for reactive goal-directed navigation without global positioning facilities in unknown dynamic environments. A mobile sensor network is used for localising regions of interest for path planning of an autonomous mobile robot. The underlying theory is an extension of a generalised gossip algorithm that has been recently developed in a language-measure-theoretic setting. The algorithm has been used to propagate local decisions of target detection over a mobile sensor network and thus, it generates a belief map for the detected target over the network. In this setting, an autonomous mobile robot may communicate only with a few mobile sensing nodes in its own neighbourhood and localise itself relative to the communicating nodes with bounded uncertainties. The robot makes use of the knowledge based on the belief of the mobile sensors to generate a sequence of way-points, leading to a possible goal. The estimated way-points are used by a sampling-based motion planning algorithm to generate feasible trajectories for the robot. The proposed concept has been validated by numerical simulation on a mobile sensor network test-bed and a Dubin's car-like robot.

A Mobile Anchor Assisted Localization Algorithm Based on Regular Hexagon in Wireless Sensor Networks

PubMed Central

Rodrigues, Joel J. P. C.

2014-01-01

Localization is one of the key technologies in wireless sensor networks (WSNs), since it provides fundamental support for many location-aware protocols and applications. Constraints of cost and power consumption make it infeasible to equip each sensor node in the network with a global position system (GPS) unit, especially for large-scale WSNs. A promising method to localize unknown nodes is to use several mobile anchors which are equipped with GPS units moving among unknown nodes and periodically broadcasting their current locations to help nearby unknown nodes with localization. This paper proposes a mobile anchor assisted localization algorithm based on regular hexagon (MAALRH) in two-dimensional WSNs, which can cover the whole monitoring area with a boundary compensation method. Unknown nodes calculate their positions by using trilateration. We compare the MAALRH with HILBERT, CIRCLES, and S-CURVES algorithms in terms of localization ratio, localization accuracy, and path length. Simulations show that the MAALRH can achieve high localization ratio and localization accuracy when the communication range is not smaller than the trajectory resolution. PMID:25133212

Performance Analysis of Grey-World-based Feature Detection and Matching for Mobile Positioning Systems

NASA Astrophysics Data System (ADS)

Bejuri, Wan Mohd Yaakob Wan; Mohamad, Mohd Murtadha

2014-11-01

This paper introduces a new grey-world-based feature detection and matching algorithm, intended for use with mobile positioning systems. This approach uses a combination of a wireless local area network (WLAN) and a mobile phone camera to determine positioning in an illumination environment using a practical and pervasive approach. The signal combination is based on retrieved signal strength from the WLAN access point and the image processing information from the building hallways. The results show our method can handle information better than Harlan Hile's method relative to the illumination environment, producing lower illumination error in five (5) different environments.

Error Estimation for the Linearized Auto-Localization Algorithm

PubMed Central

Guevara, Jorge; Jiménez, Antonio R.; Prieto, Jose Carlos; Seco, Fernando

2012-01-01

The Linearized Auto-Localization (LAL) algorithm estimates the position of beacon nodes in Local Positioning Systems (LPSs), using only the distance measurements to a mobile node whose position is also unknown. The LAL algorithm calculates the inter-beacon distances, used for the estimation of the beacons’ positions, from the linearized trilateration equations. In this paper we propose a method to estimate the propagation of the errors of the inter-beacon distances obtained with the LAL algorithm, based on a first order Taylor approximation of the equations. Since the method depends on such approximation, a confidence parameter τ is defined to measure the reliability of the estimated error. Field evaluations showed that by applying this information to an improved weighted-based auto-localization algorithm (WLAL), the standard deviation of the inter-beacon distances can be improved by more than 30% on average with respect to the original LAL method. PMID:22736965

Integrated WiFi/PDR/Smartphone Using an Unscented Kalman Filter Algorithm for 3D Indoor Localization.

PubMed

Chen, Guoliang; Meng, Xiaolin; Wang, Yunjia; Zhang, Yanzhe; Tian, Peng; Yang, Huachao

2015-09-23

Because of the high calculation cost and poor performance of a traditional planar map when dealing with complicated indoor geographic information, a WiFi fingerprint indoor positioning system cannot be widely employed on a smartphone platform. By making full use of the hardware sensors embedded in the smartphone, this study proposes an integrated approach to a three-dimensional (3D) indoor positioning system. First, an improved K-means clustering method is adopted to reduce the fingerprint database retrieval time and enhance positioning efficiency. Next, with the mobile phone's acceleration sensor, a new step counting method based on auto-correlation analysis is proposed to achieve cell phone inertial navigation positioning. Furthermore, the integration of WiFi positioning with Pedestrian Dead Reckoning (PDR) obtains higher positional accuracy with the help of the Unscented Kalman Filter algorithm. Finally, a hybrid 3D positioning system based on Unity 3D, which can carry out real-time positioning for targets in 3D scenes, is designed for the fluent operation of mobile terminals.

Integrated WiFi/PDR/Smartphone Using an Unscented Kalman Filter Algorithm for 3D Indoor Localization

PubMed Central

Chen, Guoliang; Meng, Xiaolin; Wang, Yunjia; Zhang, Yanzhe; Tian, Peng; Yang, Huachao

2015-01-01

Because of the high calculation cost and poor performance of a traditional planar map when dealing with complicated indoor geographic information, a WiFi fingerprint indoor positioning system cannot be widely employed on a smartphone platform. By making full use of the hardware sensors embedded in the smartphone, this study proposes an integrated approach to a three-dimensional (3D) indoor positioning system. First, an improved K-means clustering method is adopted to reduce the fingerprint database retrieval time and enhance positioning efficiency. Next, with the mobile phone’s acceleration sensor, a new step counting method based on auto-correlation analysis is proposed to achieve cell phone inertial navigation positioning. Furthermore, the integration of WiFi positioning with Pedestrian Dead Reckoning (PDR) obtains higher positional accuracy with the help of the Unscented Kalman Filter algorithm. Finally, a hybrid 3D positioning system based on Unity 3D, which can carry out real-time positioning for targets in 3D scenes, is designed for the fluent operation of mobile terminals. PMID:26404314

On-Line Point Positioning with Single Frame Camera Data

DTIC Science & Technology

1992-03-15

tion algorithms and methods will be found in robotics and industrial quality control. 1. Project data The project has been defined as "On-line point...development and use of the OLT algorithms and meth- ods for applications in robotics , industrial quality control and autonomous vehicle naviga- tion...Of particular interest in robotics and autonomous vehicle navigation is, for example, the task of determining the position and orientation of a mobile

Systems of Geo Positioning of the Mobile Robot

NASA Astrophysics Data System (ADS)

Momot, M. V.; Proskokov, A. V.; Nesteruk, D. N.; Ganiyev, M.; Biktimirov, A. S.

2017-07-01

Article is devoted to the analysis of opportunities of electronic instruments, such as a gyroscope, the accelerometer, the magnetometer together, the video system of image identification and system of infrared indicators during creation of system of exact positioning of the mobile robot. Results of testing and the operating algorithms are given. Possibilities of sharing of these devices and their association in a single system are analyzed. Conclusions on development of opportunities and elimination of shortcomings of the received end-to-end system of positioning of the robot are drawn.

An Improved WiFi Indoor Positioning Algorithm by Weighted Fusion

PubMed Central

Ma, Rui; Guo, Qiang; Hu, Changzhen; Xue, Jingfeng

2015-01-01

The rapid development of mobile Internet has offered the opportunity for WiFi indoor positioning to come under the spotlight due to its low cost. However, nowadays the accuracy of WiFi indoor positioning cannot meet the demands of practical applications. To solve this problem, this paper proposes an improved WiFi indoor positioning algorithm by weighted fusion. The proposed algorithm is based on traditional location fingerprinting algorithms and consists of two stages: the offline acquisition and the online positioning. The offline acquisition process selects optimal parameters to complete the signal acquisition, and it forms a database of fingerprints by error classification and handling. To further improve the accuracy of positioning, the online positioning process first uses a pre-match method to select the candidate fingerprints to shorten the positioning time. After that, it uses the improved Euclidean distance and the improved joint probability to calculate two intermediate results, and further calculates the final result from these two intermediate results by weighted fusion. The improved Euclidean distance introduces the standard deviation of WiFi signal strength to smooth the WiFi signal fluctuation and the improved joint probability introduces the logarithmic calculation to reduce the difference between probability values. Comparing the proposed algorithm, the Euclidean distance based WKNN algorithm and the joint probability algorithm, the experimental results indicate that the proposed algorithm has higher positioning accuracy. PMID:26334278

An Improved WiFi Indoor Positioning Algorithm by Weighted Fusion.

PubMed

Ma, Rui; Guo, Qiang; Hu, Changzhen; Xue, Jingfeng

2015-08-31

The rapid development of mobile Internet has offered the opportunity for WiFi indoor positioning to come under the spotlight due to its low cost. However, nowadays the accuracy of WiFi indoor positioning cannot meet the demands of practical applications. To solve this problem, this paper proposes an improved WiFi indoor positioning algorithm by weighted fusion. The proposed algorithm is based on traditional location fingerprinting algorithms and consists of two stages: the offline acquisition and the online positioning. The offline acquisition process selects optimal parameters to complete the signal acquisition, and it forms a database of fingerprints by error classification and handling. To further improve the accuracy of positioning, the online positioning process first uses a pre-match method to select the candidate fingerprints to shorten the positioning time. After that, it uses the improved Euclidean distance and the improved joint probability to calculate two intermediate results, and further calculates the final result from these two intermediate results by weighted fusion. The improved Euclidean distance introduces the standard deviation of WiFi signal strength to smooth the WiFi signal fluctuation and the improved joint probability introduces the logarithmic calculation to reduce the difference between probability values. Comparing the proposed algorithm, the Euclidean distance based WKNN algorithm and the joint probability algorithm, the experimental results indicate that the proposed algorithm has higher positioning accuracy.

Indoor-Outdoor Detection Using a Smart Phone Sensor.

PubMed

Wang, Weiping; Chang, Qiang; Li, Qun; Shi, Zesen; Chen, Wei

2016-09-22

In the era of mobile internet, Location Based Services (LBS) have developed dramatically. Seamless Indoor and Outdoor Navigation and Localization (SNAL) has attracted a lot of attention. No single positioning technology was capable of meeting the various positioning requirements in different environments. Selecting different positioning techniques for different environments is an alternative method. Detecting the users' current environment is crucial for this technique. In this paper, we proposed to detect the indoor/outdoor environment automatically without high energy consumption. The basic idea was simple: we applied a machine learning algorithm to classify the neighboring Global System for Mobile (GSM) communication cellular base station's signal strength in different environments, and identified the users' current context by signal pattern recognition. We tested the algorithm in four different environments. The results showed that the proposed algorithm was capable of identifying open outdoors, semi-outdoors, light indoors and deep indoors environments with 100% accuracy using the signal strength of four nearby GSM stations. The required hardware and signal are widely available in our daily lives, implying its high compatibility and availability.

Exploiting node mobility for energy optimization in wireless sensor networks

NASA Astrophysics Data System (ADS)

El-Moukaddem, Fatme Mohammad

Wireless Sensor Networks (WSNs) have become increasingly available for data-intensive applications such as micro-climate monitoring, precision agriculture, and audio/video surveillance. A key challenge faced by data-intensive WSNs is to transmit the sheer amount of data generated within an application's lifetime to the base station despite the fact that sensor nodes have limited power supplies such as batteries or small solar panels. The availability of numerous low-cost robotic units (e.g. Robomote and Khepera) has made it possible to construct sensor networks consisting of mobile sensor nodes. It has been shown that the controlled mobility offered by mobile sensors can be exploited to improve the energy efficiency of a network. In this thesis, we propose schemes that use mobile sensor nodes to reduce the energy consumption of data-intensive WSNs. Our approaches differ from previous work in two main aspects. First, our approaches do not require complex motion planning of mobile nodes, and hence can be implemented on a number of low-cost mobile sensor platforms. Second, we integrate the energy consumption due to both mobility and wireless communications into a holistic optimization framework. We consider three problems arising from the limited energy in the sensor nodes. In the first problem, the network consists of mostly static nodes and contains only a few mobile nodes. In the second and third problems, we assume essentially that all nodes in the WSN are mobile. We first study a new problem called max-data mobile relay configuration (MMRC ) that finds the positions of a set of mobile sensors, referred to as relays, that maximize the total amount of data gathered by the network during its lifetime. We show that the MMRC problem is surprisingly complex even for a trivial network topology due to the joint consideration of the energy consumption of both wireless communication and mechanical locomotion. We present optimal MMRC algorithms and practical distributed implementations for several important network topologies and applications. Second, we consider the problem of minimizing the total energy consumption of a network. We design an iterative algorithm that improves a given configuration by relocating nodes to new positions. We show that this algorithm converges to the optimal configuration for the given transmission routes. Moreover, we propose an efficient distributed implementation that does not require explicit synchronization. Finally, we consider the problem of maximizing the lifetime of the network. We propose an approach that exploits the mobility of the nodes to balance the energy consumption throughout the network. We develop efficient algorithms for single and multiple round approaches. For all three problems, we evaluate the efficiency of our algorithms through simulations. Our simulation results based on realistic energy models obtained from existing mobile and static sensor platforms show that our approaches significantly improve the network's performance and outperform existing approaches.

Discriminant analysis of fused positive and negative ion mobility spectra using multivariate self-modeling mixture analysis and neural networks.

PubMed

Chen, Ping; Harrington, Peter B

2008-02-01

A new method coupling multivariate self-modeling mixture analysis and pattern recognition has been developed to identify toxic industrial chemicals using fused positive and negative ion mobility spectra (dual scan spectra). A Smiths lightweight chemical detector (LCD), which can measure positive and negative ion mobility spectra simultaneously, was used to acquire the data. Simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) was used to separate the analytical peaks in the ion mobility spectra from the background reactant ion peaks (RIP). The SIMPLSIMA analytical components of the positive and negative ion peaks were combined together in a butterfly representation (i.e., negative spectra are reported with negative drift times and reflected with respect to the ordinate and juxtaposed with the positive ion mobility spectra). Temperature constrained cascade-correlation neural network (TCCCN) models were built to classify the toxic industrial chemicals. Seven common toxic industrial chemicals were used in this project to evaluate the performance of the algorithm. Ten bootstrapped Latin partitions demonstrated that the classification of neural networks using the SIMPLISMA components was statistically better than neural network models trained with fused ion mobility spectra (IMS).

Application of particle swarm optimization in path planning of mobile robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Cai, Feng; Wang, Ying

2017-08-01

In order to realize the optimal path planning of mobile robot in unknown environment, a particle swarm optimization algorithm based on path length as fitness function is proposed. The location of the global optimal particle is determined by the minimum fitness value, and the robot moves along the points of the optimal particles to the target position. The process of moving to the target point is done with MATLAB R2014a. Compared with the standard particle swarm optimization algorithm, the simulation results show that this method can effectively avoid all obstacles and get the optimal path.

Automatic detection of zebra crossings from mobile LiDAR data

NASA Astrophysics Data System (ADS)

Riveiro, B.; González-Jorge, H.; Martínez-Sánchez, J.; Díaz-Vilariño, L.; Arias, P.

2015-07-01

An algorithm for the automatic detection of zebra crossings from mobile LiDAR data is developed and tested to be applied for road management purposes. The algorithm consists of several subsequent processes starting with road segmentation by performing a curvature analysis for each laser cycle. Then, intensity images are created from the point cloud using rasterization techniques, in order to detect zebra crossing using the Standard Hough Transform and logical constrains. To optimize the results, image processing algorithms are applied to the intensity images from the point cloud. These algorithms include binarization to separate the painting area from the rest of the pavement, median filtering to avoid noisy points, and mathematical morphology to fill the gaps between the pixels in the border of white marks. Once the road marking is detected, its position is calculated. This information is valuable for inventorying purposes of road managers that use Geographic Information Systems. The performance of the algorithm has been evaluated over several mobile LiDAR strips accounting for a total of 30 zebra crossings. That test showed a completeness of 83%. Non-detected marks mainly come from painting deterioration of the zebra crossing or by occlusions in the point cloud produced by other vehicles on the road.

A mobile robots experimental environment with event-based wireless communication.

PubMed

Guinaldo, María; Fábregas, Ernesto; Farias, Gonzalo; Dormido-Canto, Sebastián; Chaos, Dictino; Sánchez, José; Dormido, Sebastián

2013-07-22

An experimental platform to communicate between a set of mobile robots through a wireless network has been developed. The mobile robots get their position through a camera which performs as sensor. The video images are processed in a PC and a Waspmote card sends the corresponding position to each robot using the ZigBee standard. A distributed control algorithm based on event-triggered communications has been designed and implemented to bring the robots into the desired formation. Each robot communicates to its neighbors only at event times. Furthermore, a simulation tool has been developed to design and perform experiments with the system. An example of usage is presented.

A Modified Decision Tree Algorithm Based on Genetic Algorithm for Mobile User Classification Problem

PubMed Central

Liu, Dong-sheng; Fan, Shu-jiang

2014-01-01

In order to offer mobile customers better service, we should classify the mobile user firstly. Aimed at the limitations of previous classification methods, this paper puts forward a modified decision tree algorithm for mobile user classification, which introduced genetic algorithm to optimize the results of the decision tree algorithm. We also take the context information as a classification attributes for the mobile user and we classify the context into public context and private context classes. Then we analyze the processes and operators of the algorithm. At last, we make an experiment on the mobile user with the algorithm, we can classify the mobile user into Basic service user, E-service user, Plus service user, and Total service user classes and we can also get some rules about the mobile user. Compared to C4.5 decision tree algorithm and SVM algorithm, the algorithm we proposed in this paper has higher accuracy and more simplicity. PMID:24688389

Navigation system for a mobile robot with a visual sensor using a fish-eye lens

NASA Astrophysics Data System (ADS)

Kurata, Junichi; Grattan, Kenneth T. V.; Uchiyama, Hironobu

1998-02-01

Various position sensing and navigation systems have been proposed for the autonomous control of mobile robots. Some of these systems have been installed with an omnidirectional visual sensor system that proved very useful in obtaining information on the environment around the mobile robot for position reckoning. In this article, this type of navigation system is discussed. The sensor is composed of one TV camera with a fish-eye lens, using a reference target on a ceiling and hybrid image processing circuits. The position of the robot, with respect to the floor, is calculated by integrating the information obtained from a visual sensor and a gyroscope mounted in the mobile robot, and the use of a simple algorithm based on PTP control for guidance is discussed. An experimental trial showed that the proposed system was both valid and useful for the navigation of an indoor vehicle.

A Simple Interface for 3D Position Estimation of a Mobile Robot with Single Camera

PubMed Central

Chao, Chun-Tang; Chung, Ming-Hsuan; Chiou, Juing-Shian; Wang, Chi-Jo

2016-01-01

In recent years, there has been an increase in the number of mobile robots controlled by a smart phone or tablet. This paper proposes a visual control interface for a mobile robot with a single camera to easily control the robot actions and estimate the 3D position of a target. In this proposal, the mobile robot employed an Arduino Yun as the core processor and was remote-controlled by a tablet with an Android operating system. In addition, the robot was fitted with a three-axis robotic arm for grasping. Both the real-time control signal and video transmission are transmitted via Wi-Fi. We show that with a properly calibrated camera and the proposed prototype procedures, the users can click on a desired position or object on the touchscreen and estimate its 3D coordinates in the real world by simple analytic geometry instead of a complicated algorithm. The results of the measurement verification demonstrates that this approach has great potential for mobile robots. PMID:27023556

A Simple Interface for 3D Position Estimation of a Mobile Robot with Single Camera.

PubMed

Chao, Chun-Tang; Chung, Ming-Hsuan; Chiou, Juing-Shian; Wang, Chi-Jo

2016-03-25

In recent years, there has been an increase in the number of mobile robots controlled by a smart phone or tablet. This paper proposes a visual control interface for a mobile robot with a single camera to easily control the robot actions and estimate the 3D position of a target. In this proposal, the mobile robot employed an Arduino Yun as the core processor and was remote-controlled by a tablet with an Android operating system. In addition, the robot was fitted with a three-axis robotic arm for grasping. Both the real-time control signal and video transmission are transmitted via Wi-Fi. We show that with a properly calibrated camera and the proposed prototype procedures, the users can click on a desired position or object on the touchscreen and estimate its 3D coordinates in the real world by simple analytic geometry instead of a complicated algorithm. The results of the measurement verification demonstrates that this approach has great potential for mobile robots.

A Mobile Robots Experimental Environment with Event-Based Wireless Communication

PubMed Central

Guinaldo, María; Fábregas, Ernesto; Farias, Gonzalo; Dormido-Canto, Sebastián; Chaos, Dictino; Sánchez, José; Dormido, Sebastián

2013-01-01

An experimental platform to communicate between a set of mobile robots through a wireless network has been developed. The mobile robots get their position through a camera which performs as sensor. The video images are processed in a PC and a Waspmote card sends the corresponding position to each robot using the ZigBee standard. A distributed control algorithm based on event-triggered communications has been designed and implemented to bring the robots into the desired formation. Each robot communicates to its neighbors only at event times. Furthermore, a simulation tool has been developed to design and perform experiments with the system. An example of usage is presented. PMID:23881139

Omni-Directional Scanning Localization Method of a Mobile Robot Based on Ultrasonic Sensors.

PubMed

Mu, Wei-Yi; Zhang, Guang-Peng; Huang, Yu-Mei; Yang, Xin-Gang; Liu, Hong-Yan; Yan, Wen

2016-12-20

Improved ranging accuracy is obtained by the development of a novel ultrasonic sensor ranging algorithm, unlike the conventional ranging algorithm, which considers the divergence angle and the incidence angle of the ultrasonic sensor synchronously. An ultrasonic sensor scanning method is developed based on this algorithm for the recognition of an inclined plate and to obtain the localization of the ultrasonic sensor relative to the inclined plate reference frame. The ultrasonic sensor scanning method is then leveraged for the omni-directional localization of a mobile robot, where the ultrasonic sensors are installed on a mobile robot and follow the spin of the robot, the inclined plate is recognized and the position and posture of the robot are acquired with respect to the coordinate system of the inclined plate, realizing the localization of the robot. Finally, the localization method is implemented into an omni-directional scanning localization experiment with the independently researched and developed mobile robot. Localization accuracies of up to ±3.33 mm for the front, up to ±6.21 for the lateral and up to ±0.20° for the posture are obtained, verifying the correctness and effectiveness of the proposed localization method.

Benefits of Mobile Phone Technology for Personal Environmental Monitoring

PubMed Central

Carrasco-Turigas, Glòria; Seto, Edmund; Jerrett, Michael; Nieuwenhuijsen, Mark J

2016-01-01

Background Tracking individuals in environmental epidemiological studies using novel mobile phone technologies can provide valuable information on geolocation and physical activity, which will improve our understanding of environmental exposures. Objective The objective of this study was to assess the performance of one of the least expensive mobile phones on the market to track people's travel-activity pattern. Methods Adults living and working in Barcelona (72/162 bicycle commuters) carried simultaneously a mobile phone and a Global Positioning System (GPS) tracker and filled in a travel-activity diary (TAD) for 1 week (N=162). The CalFit app for mobile phones was used to log participants’ geographical location and physical activity. The geographical location data were assigned to different microenvironments (home, work or school, in transit, others) with a newly developed spatiotemporal map-matching algorithm. The tracking performance of the mobile phones was compared with that of the GPS trackers using chi-square test and Kruskal-Wallis rank sum test. The minute agreement across all microenvironments between the TAD and the algorithm was compared using the Gwet agreement coefficient (AC1). Results The mobile phone acquired locations for 905 (29.2%) more trips reported in travel diaries than the GPS tracker (P<.001) and had a median accuracy of 25 m. Subjects spent on average 57.9%, 19.9%, 9.0%, and 13.2% of time at home, work, in transit, and other places, respectively, according to the TAD and 57.5%, 18.8%, 11.6%, and 12.1%, respectively, according to the map-matching algorithm. The overall minute agreement between both methods was high (AC1 .811, 95% CI .810-.812). Conclusions The use of mobile phones running the CalFit app provides better information on which microenvironments people spend their time in than previous approaches based only on GPS trackers. The improvements of mobile phone technology in microenvironment determination are because the mobile phones are faster at identifying first locations and capable of getting location in challenging environments thanks to the combination of assisted-GPS technology and network positioning systems. Moreover, collecting location information from mobile phones, which are already carried by individuals, allows monitoring more people with a cheaper and less burdensome method than deploying GPS trackers. PMID:27833069

Fuzzy Logic Based Control for Autonomous Mobile Robot Navigation

PubMed Central

Masmoudi, Mohamed Slim; Masmoudi, Mohamed

2016-01-01

This paper describes the design and the implementation of a trajectory tracking controller using fuzzy logic for mobile robot to navigate in indoor environments. Most of the previous works used two independent controllers for navigation and avoiding obstacles. The main contribution of the paper can be summarized in the fact that we use only one fuzzy controller for navigation and obstacle avoidance. The used mobile robot is equipped with DC motor, nine infrared range (IR) sensors to measure the distance to obstacles, and two optical encoders to provide the actual position and speeds. To evaluate the performances of the intelligent navigation algorithms, different trajectories are used and simulated using MATLAB software and SIMIAM navigation platform. Simulation results show the performances of the intelligent navigation algorithms in terms of simulation times and travelled path. PMID:27688748

Intelligent navigation and accurate positioning of an assist robot in indoor environments

NASA Astrophysics Data System (ADS)

Hua, Bin; Rama, Endri; Capi, Genci; Jindai, Mitsuru; Tsuri, Yosuke

2017-12-01

Intact robot's navigation and accurate positioning in indoor environments are still challenging tasks. Especially in robot applications, assisting disabled and/or elderly people in museums/art gallery environments. In this paper, we present a human-like navigation method, where the neural networks control the wheelchair robot to reach the goal location safely, by imitating the supervisor's motions, and positioning in the intended location. In a museum similar environment, the mobile robot starts navigation from various positions, and uses a low-cost camera to track the target picture, and a laser range finder to make a safe navigation. Results show that the neural controller with the Conjugate Gradient Backpropagation training algorithm gives a robust response to guide the mobile robot accurately to the goal position.

Multidimensional Optimization of Signal Space Distance Parameters in WLAN Positioning

PubMed Central

Brković, Milenko; Simić, Mirjana

2014-01-01

Accurate indoor localization of mobile users is one of the challenging problems of the last decade. Besides delivering high speed Internet, Wireless Local Area Network (WLAN) can be used as an effective indoor positioning system, being competitive both in terms of accuracy and cost. Among the localization algorithms, nearest neighbor fingerprinting algorithms based on Received Signal Strength (RSS) parameter have been extensively studied as an inexpensive solution for delivering indoor Location Based Services (LBS). In this paper, we propose the optimization of the signal space distance parameters in order to improve precision of WLAN indoor positioning, based on nearest neighbor fingerprinting algorithms. Experiments in a real WLAN environment indicate that proposed optimization leads to substantial improvements of the localization accuracy. Our approach is conceptually simple, is easy to implement, and does not require any additional hardware. PMID:24757443

Smart mobile robot system for rubbish collection

NASA Astrophysics Data System (ADS)

Ali, Mohammed A. H.; Sien Siang, Tan

2018-03-01

This paper records the research and procedures of developing a smart mobility robot with detection system to collect rubbish. The objective of this paper is to design a mobile robot that can detect and recognize medium-size rubbish such as drinking cans. Besides that, the objective is also to design a mobile robot with the ability to estimate the position of rubbish from the robot. In addition, the mobile robot is also able to approach the rubbish based on position of rubbish. This paper explained about the types of image processing, detection and recognition methods and image filters. This project implements RGB subtraction method as the prior system. Other than that, algorithm for distance measurement based on image plane is implemented in this project. This project is limited to use computer webcam as the sensor. Secondly, the robot is only able to approach the nearest rubbish in the same views of camera vision and any rubbish that contain RGB colour components on its body.

Investigation of a New Handover Approach in LTE and WiMAX

PubMed Central

Hindia, Mohammad Nour; Reza, Ahmed Wasif; Noordin, Kamarul Ariffin

2014-01-01

Nowadays, one of the most important challenges in heterogeneous networks is the connection consistency between the mobile station and the base stations. Furthermore, along the roaming process between the mobile station and the base station, the system performance degrades significantly due to the interferences from neighboring base stations, handovers to inaccurate base station and inappropriate technology selection. In this paper, several algorithms are proposed to improve mobile station performance and seamless mobility across the long-term evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX) technologies, along with a minimum number of redundant handovers. Firstly, the enhanced global positioning system (GPS) and the novel received signal strength (RSS) prediction approaches are suggested to predict the target base station accurately. Then, the multiple criteria with two thresholds algorithm is proposed to prioritize the selection between LTE and WiMAX as the target technology. In addition, this study also covers the intercell and cochannel interference reduction by adjusting the frequency reuse ratio 3 (FRR3) to work with LTE and WiMAX. The obtained results demonstrate high next base station prediction efficiency and high accuracy for both horizontal and vertical handovers. Moreover, the received signal strength is kept at levels higher than the threshold, while maintaining low connection cost and delay within acceptable levels. In order to highlight the combination of the proposed algorithms' performance, it is compared with the existing RSS and multiple criteria handover decision algorithms. PMID:25379524

Investigation of a new handover approach in LTE and WiMAX.

PubMed

Hindia, Mohammad Nour; Reza, Ahmed Wasif; Noordin, Kamarul Ariffin

2014-01-01

Nowadays, one of the most important challenges in heterogeneous networks is the connection consistency between the mobile station and the base stations. Furthermore, along the roaming process between the mobile station and the base station, the system performance degrades significantly due to the interferences from neighboring base stations, handovers to inaccurate base station and inappropriate technology selection. In this paper, several algorithms are proposed to improve mobile station performance and seamless mobility across the long-term evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX) technologies, along with a minimum number of redundant handovers. Firstly, the enhanced global positioning system (GPS) and the novel received signal strength (RSS) prediction approaches are suggested to predict the target base station accurately. Then, the multiple criteria with two thresholds algorithm is proposed to prioritize the selection between LTE and WiMAX as the target technology. In addition, this study also covers the intercell and cochannel interference reduction by adjusting the frequency reuse ratio 3 (FRR3) to work with LTE and WiMAX. The obtained results demonstrate high next base station prediction efficiency and high accuracy for both horizontal and vertical handovers. Moreover, the received signal strength is kept at levels higher than the threshold, while maintaining low connection cost and delay within acceptable levels. In order to highlight the combination of the proposed algorithms' performance, it is compared with the existing RSS and multiple criteria handover decision algorithms.

Scalable Indoor Localization via Mobile Crowdsourcing and Gaussian Process

PubMed Central

Chang, Qiang; Li, Qun; Shi, Zesen; Chen, Wei; Wang, Weiping

2016-01-01

Indoor localization using Received Signal Strength Indication (RSSI) fingerprinting has been extensively studied for decades. The positioning accuracy is highly dependent on the density of the signal database. In areas without calibration data, however, this algorithm breaks down. Building and updating a dense signal database is labor intensive, expensive, and even impossible in some areas. Researchers are continually searching for better algorithms to create and update dense databases more efficiently. In this paper, we propose a scalable indoor positioning algorithm that works both in surveyed and unsurveyed areas. We first propose Minimum Inverse Distance (MID) algorithm to build a virtual database with uniformly distributed virtual Reference Points (RP). The area covered by the virtual RPs can be larger than the surveyed area. A Local Gaussian Process (LGP) is then applied to estimate the virtual RPs’ RSSI values based on the crowdsourced training data. Finally, we improve the Bayesian algorithm to estimate the user’s location using the virtual database. All the parameters are optimized by simulations, and the new algorithm is tested on real-case scenarios. The results show that the new algorithm improves the accuracy by 25.5% in the surveyed area, with an average positioning error below 2.2 m for 80% of the cases. Moreover, the proposed algorithm can localize the users in the neighboring unsurveyed area. PMID:26999139

Toward artifact-free data in Hadamard transform-based double multiplexing of ion mobility-Orbitrap mass spectrometry

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

Tummalacherla, Meghasyam; Garimella, Sandilya V. B.; Prost, Spencer A.

The integration of ion mobility spectrometry (IMS) with trap-based mass spectrometer (MS) such as Orbitrap using the dual gate approach suffers from low duty cycle. Efforts to improve the duty cycle involve the utilization of Hadamard transform based double multiplexing which significantly improve the signal to noise ratio and duty cycle of the ion mobility – Orbitrap mass spectrometry (IM – Orbitrap MS) platform. However, significant fluctuations in ion intensity and the temporal shifts in the encoded data give rise to artifacts and noise in the demultiplexed data which significantly reduce the data quality and negate the benefits of multiplexing.more » We propose a new approach that identifies the true IM peaks and helps in eliminating the artifacts in the demultiplexed data leading to a decrease in false positives in subsequent data processing. The algorithm takes an analytical approach to first identify the position of the IM peak in the temporal domain, and then demultiplex and identify the true data making it easier for subsequent data processing. After the application of the algorithm, the quality of the IM-Orbitrap MS measurements was greatly improved because of the reduction in artifacts.« less

Benefits of Mobile Phone Technology for Personal Environmental Monitoring.

PubMed

Donaire-Gonzalez, David; Valentín, Antònia; de Nazelle, Audrey; Ambros, Albert; Carrasco-Turigas, Glòria; Seto, Edmund; Jerrett, Michael; Nieuwenhuijsen, Mark J

2016-11-10

Tracking individuals in environmental epidemiological studies using novel mobile phone technologies can provide valuable information on geolocation and physical activity, which will improve our understanding of environmental exposures. The objective of this study was to assess the performance of one of the least expensive mobile phones on the market to track people's travel-activity pattern. Adults living and working in Barcelona (72/162 bicycle commuters) carried simultaneously a mobile phone and a Global Positioning System (GPS) tracker and filled in a travel-activity diary (TAD) for 1 week (N=162). The CalFit app for mobile phones was used to log participants' geographical location and physical activity. The geographical location data were assigned to different microenvironments (home, work or school, in transit, others) with a newly developed spatiotemporal map-matching algorithm. The tracking performance of the mobile phones was compared with that of the GPS trackers using chi-square test and Kruskal-Wallis rank sum test. The minute agreement across all microenvironments between the TAD and the algorithm was compared using the Gwet agreement coefficient (AC1). The mobile phone acquired locations for 905 (29.2%) more trips reported in travel diaries than the GPS tracker (P<.001) and had a median accuracy of 25 m. Subjects spent on average 57.9%, 19.9%, 9.0%, and 13.2% of time at home, work, in transit, and other places, respectively, according to the TAD and 57.5%, 18.8%, 11.6%, and 12.1%, respectively, according to the map-matching algorithm. The overall minute agreement between both methods was high (AC1 .811, 95% CI .810-.812). The use of mobile phones running the CalFit app provides better information on which microenvironments people spend their time in than previous approaches based only on GPS trackers. The improvements of mobile phone technology in microenvironment determination are because the mobile phones are faster at identifying first locations and capable of getting location in challenging environments thanks to the combination of assisted-GPS technology and network positioning systems. Moreover, collecting location information from mobile phones, which are already carried by individuals, allows monitoring more people with a cheaper and less burdensome method than deploying GPS trackers. ©David Donaire-Gonzalez, Antònia Valentín, Audrey de Nazelle, Albert Ambros, Glòria Carrasco-Turigas, Edmund Seto, Michael Jerrett, Mark J Nieuwenhuijsen. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 10.11.2016.

Estimating the position and orientation of a mobile robot with respect to a trajectory using omnidirectional imaging and global appearance.

PubMed

Payá, Luis; Reinoso, Oscar; Jiménez, Luis M; Juliá, Miguel

2017-01-01

Along the past years, mobile robots have proliferated both in domestic and in industrial environments to solve some tasks such as cleaning, assistance, or material transportation. One of their advantages is the ability to operate in wide areas without the necessity of introducing changes into the existing infrastructure. Thanks to the sensors they may be equipped with and their processing systems, mobile robots constitute a versatile alternative to solve a wide range of applications. When designing the control system of a mobile robot so that it carries out a task autonomously in an unknown environment, it is expected to take decisions about its localization in the environment and about the trajectory that it has to follow in order to arrive to the target points. More concisely, the robot has to find a relatively good solution to two crucial problems: building a model of the environment, and estimating the position of the robot within this model. In this work, we propose a framework to solve these problems using only visual information. The mobile robot is equipped with a catadioptric vision sensor that provides omnidirectional images from the environment. First, the robot goes along the trajectories to include in the model and uses the visual information captured to build this model. After that, the robot is able to estimate its position and orientation with respect to the trajectory. Among the possible approaches to solve these problems, global appearance techniques are used in this work. They have emerged recently as a robust and efficient alternative compared to landmark extraction techniques. A global description method based on Radon Transform is used to design mapping and localization algorithms and a set of images captured by a mobile robot in a real environment, under realistic operation conditions, is used to test the performance of these algorithms.

High-precision approach to localization scheme of visible light communication based on artificial neural networks and modified genetic algorithms

NASA Astrophysics Data System (ADS)

Guan, Weipeng; Wu, Yuxiang; Xie, Canyu; Chen, Hao; Cai, Ye; Chen, Yingcong

2017-10-01

An indoor positioning algorithm based on visible light communication (VLC) is presented. This algorithm is used to calculate a three-dimensional (3-D) coordinate of an indoor optical wireless environment, which includes sufficient orders of multipath reflections from reflecting surfaces of the room. Leveraging the global optimization ability of the genetic algorithm (GA), an innovative framework for 3-D position estimation based on a modified genetic algorithm is proposed. Unlike other techniques using VLC for positioning, the proposed system can achieve indoor 3-D localization without making assumptions about the height or acquiring the orientation angle of the mobile terminal. Simulation results show that an average localization error of less than 1.02 cm can be achieved. In addition, in most VLC-positioning systems, the effect of reflection is always neglected and its performance is limited by reflection, which makes the results not so accurate for a real scenario and the positioning errors at the corners are relatively larger than other places. So, we take the first-order reflection into consideration and use artificial neural network to match the model of a nonlinear channel. The studies show that under the nonlinear matching of direct and reflected channels the average positioning errors of four corners decrease from 11.94 to 0.95 cm. The employed algorithm is emerged as an effective and practical method for indoor localization and outperform other existing indoor wireless localization approaches.

Development of a two wheeled self balancing robot with speech recognition and navigation algorithm

NASA Astrophysics Data System (ADS)

Rahman, Md. Muhaimin; Ashik-E-Rasul, Haq, Nowab. Md. Aminul; Hassan, Mehedi; Hasib, Irfan Mohammad Al; Hassan, K. M. Rafidh

2016-07-01

This paper is aimed to discuss modeling, construction and development of navigation algorithm of a two wheeled self balancing mobile robot in an enclosure. In this paper, we have discussed the design of two of the main controller algorithms, namely PID algorithms, on the robot model. Simulation is performed in the SIMULINK environment. The controller is developed primarily for self-balancing of the robot and also it's positioning. As for the navigation in an enclosure, template matching algorithm is proposed for precise measurement of the robot position. The navigation system needs to be calibrated before navigation process starts. Almost all of the earlier template matching algorithms that can be found in the open literature can only trace the robot. But the proposed algorithm here can also locate the position of other objects in an enclosure, like furniture, tables etc. This will enable the robot to know the exact location of every stationary object in the enclosure. Moreover, some additional features, such as Speech Recognition and Object Detection, are added. For Object Detection, the single board Computer Raspberry Pi is used. The system is programmed to analyze images captured via the camera, which are then processed through background subtraction, followed by active noise reduction.

A Modular Localization System as a Positioning Service for Road Transport

PubMed Central

Brida, Peter; Machaj, Juraj; Benikovsky, Jozef

2014-01-01

In recent times smart devices have attracted a large number of users. Since many of these devices allow position estimation using Global Navigation Satellite Systems (GNSS) signals, a large number of location-based applications and services have emerged, especially in transport systems. However GNSS signals are affected by the environment and are not always present, especially in dense urban environment or indoors. In this work firstly a Modular Localization Algorithm is proposed to allow seamless switching between different positioning modules. This helps us develop a positioning system that is able to provide position estimates in both indoor and outdoor environments without any user interaction. Since the proposed system can run as a service on any smart device, it could allow users to navigate not only in outdoor environments, but also indoors, e.g., underground garages, tunnels etc. Secondly we present the proposal of a 2-phase map reduction algorithm which allows one to significantly reduce the complexity of position estimation processes in case that positioning is performed using a fingerprinting framework. The proposed 2-phase map reduction algorithm can also improve the accuracy of the position estimates by filtering out reference points that are far from the mobile device. Both algorithms were implemented into a positioning system and tested in real world conditions in both indoor and outdoor environments. PMID:25353979

An Algorithm for Timely Transmission of Solicitation Messages in RPL for Energy-Efficient Node Mobility.

PubMed

Park, Jihong; Kim, Ki-Hyung; Kim, Kangseok

2017-04-19

The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) was proposed for various applications of IPv6 low power wireless networks. While RPL supports various routing metrics and is designed to be suitable for wireless sensor network environments, it does not consider the mobility of nodes. Therefore, there is a need for a method that is energy efficient and that provides stable and reliable data transmission by considering the mobility of nodes in RPL networks. This paper proposes an algorithm to support node mobility in RPL in an energy-efficient manner and describes its operating principle based on different scenarios. The proposed algorithm supports the mobility of nodes by dynamically adjusting the transmission interval of the messages that request the route based on the speed and direction of the motion of mobile nodes, as well as the costs between neighboring nodes. The performance of the proposed algorithm and previous algorithms for supporting node mobility were examined experimentally. From the experiment, it was observed that the proposed algorithm requires fewer messages per unit time for selecting a new parent node following the movement of a mobile node. Since fewer messages are used to select a parent node, the energy consumption is also less than that of previous algorithms.

An Algorithm for Timely Transmission of Solicitation Messages in RPL for Energy-Efficient Node Mobility

PubMed Central

Park, Jihong; Kim, Ki-Hyung; Kim, Kangseok

2017-01-01

The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) was proposed for various applications of IPv6 low power wireless networks. While RPL supports various routing metrics and is designed to be suitable for wireless sensor network environments, it does not consider the mobility of nodes. Therefore, there is a need for a method that is energy efficient and that provides stable and reliable data transmission by considering the mobility of nodes in RPL networks. This paper proposes an algorithm to support node mobility in RPL in an energy-efficient manner and describes its operating principle based on different scenarios. The proposed algorithm supports the mobility of nodes by dynamically adjusting the transmission interval of the messages that request the route based on the speed and direction of the motion of mobile nodes, as well as the costs between neighboring nodes. The performance of the proposed algorithm and previous algorithms for supporting node mobility were examined experimentally. From the experiment, it was observed that the proposed algorithm requires fewer messages per unit time for selecting a new parent node following the movement of a mobile node. Since fewer messages are used to select a parent node, the energy consumption is also less than that of previous algorithms. PMID:28422084

Prehospital Heart Rate and Blood Pressure Increase the Positive Predictive Value of the Glasgow Coma Scale for High-Mortality Traumatic Brain Injury

DTIC Science & Technology

2014-05-15

TBI versus those with abnormalities in GCS alone. This could be useful for mobilizing resources (e.g., neurosurgeons and operating rooms at the...have high-mortality TBI versus those with abnormalities in GCS alone. This could be useful for mobilizing resources (e.g., neurosurgeons and... neurosurgeon at the earliest juncture. Third, improved risk stratification could be used to develop more rational clinical de- cision-making algorithms for

Research into Kinect/Inertial Measurement Units Based on Indoor Robots.

PubMed

Li, Huixia; Wen, Xi; Guo, Hang; Yu, Min

2018-03-12

As indoor mobile navigation suffers from low positioning accuracy and accumulation error, we carried out research into an integrated location system for a robot based on Kinect and an Inertial Measurement Unit (IMU). In this paper, the close-range stereo images are used to calculate the attitude information and the translation amount of the adjacent positions of the robot by means of the absolute orientation algorithm, for improving the calculation accuracy of the robot's movement. Relying on the Kinect visual measurement and the strap-down IMU devices, we also use Kalman filtering to obtain the errors of the position and attitude outputs, in order to seek the optimal estimation and correct the errors. Experimental results show that the proposed method is able to improve the positioning accuracy and stability of the indoor mobile robot.

A Design of Irregular Grid Map for Large-Scale Wi-Fi LAN Fingerprint Positioning Systems

PubMed Central

Kim, Jae-Hoon; Min, Kyoung Sik; Yeo, Woon-Young

2014-01-01

The rapid growth of mobile communication and the proliferation of smartphones have drawn significant attention to location-based services (LBSs). One of the most important factors in the vitalization of LBSs is the accurate position estimation of a mobile device. The Wi-Fi positioning system (WPS) is a new positioning method that measures received signal strength indication (RSSI) data from all Wi-Fi access points (APs) and stores them in a large database as a form of radio fingerprint map. Because of the millions of APs in urban areas, radio fingerprints are seriously contaminated and confused. Moreover, the algorithmic advances for positioning face computational limitation. Therefore, we present a novel irregular grid structure and data analytics for efficient fingerprint map management. The usefulness of the proposed methodology is presented using the actual radio fingerprint measurements taken throughout Seoul, Korea. PMID:25302315

A design of irregular grid map for large-scale Wi-Fi LAN fingerprint positioning systems.

PubMed

Kim, Jae-Hoon; Min, Kyoung Sik; Yeo, Woon-Young

2014-01-01

The rapid growth of mobile communication and the proliferation of smartphones have drawn significant attention to location-based services (LBSs). One of the most important factors in the vitalization of LBSs is the accurate position estimation of a mobile device. The Wi-Fi positioning system (WPS) is a new positioning method that measures received signal strength indication (RSSI) data from all Wi-Fi access points (APs) and stores them in a large database as a form of radio fingerprint map. Because of the millions of APs in urban areas, radio fingerprints are seriously contaminated and confused. Moreover, the algorithmic advances for positioning face computational limitation. Therefore, we present a novel irregular grid structure and data analytics for efficient fingerprint map management. The usefulness of the proposed methodology is presented using the actual radio fingerprint measurements taken throughout Seoul, Korea.

Safety and Feasibility of a Neuroscience Critical Care Program to Mobilize Patients With Primary Intracerebral Hemorrhage.

PubMed

Bahouth, Mona N; Power, Melinda C; Zink, Elizabeth K; Kozeniewski, Kate; Kumble, Sowmya; Deluzio, Sandra; Urrutia, Victor C; Stevens, Robert D

2018-06-01

To measure the impact of a progressive mobility program on patients admitted to a neurocritical critical care unit (NCCU) with intracerebral hemorrhage (ICH). The early mobilization of critically ill patients with spontaneous ICH is a challenge owing to the potential for neurologic deterioration and hemodynamic lability in the acute phase of injury. Patients admitted to the intensive care unit have been excluded from randomized trials of early mobilization after stroke. An interdisciplinary working group developed a formalized NCCU Mobility Algorithm that allocates patients to incremental passive or active mobilization pathways on the basis of level of consciousness and motor function. In a quasi-experimental consecutive group comparison, patients with ICH admitted to the NCCU were analyzed in two 6-month epochs, before and after rollout of the algorithm. Mobilization and safety endpoints were compared between epochs. NCCU in an urban, academic hospital. Adult patients admitted to the NCCU with primary intracerebral hemorrhage. Progressive mobilization after stroke using a formalized mobility algorithm. Time to first mobilization. The 2 groups of patients with ICH (pre-algorithm rolllout, n=28; post-algorithm rollout, n=29) were similar on baseline characteristics. Patients in the postintervention group were significantly more likely to undergo mobilization within the first 7 days after admission (odds ratio 8.7, 95% confidence interval 2.1, 36.6; P=.003). No neurologic deterioration, hypotension, falls, or line dislodgments were reported in association with mobilization. A nonsignificant difference in mortality was noted before and after rollout of the algorithm (4% vs 24%, respectively, P=.12). The implementation of a progressive mobility algorithm was safe and associated with a higher likelihood of mobilization in the first week after spontaneous ICH. Research is needed to investigate methods and the timing for the first mobilization in critically ill stroke patients. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Robust Statistical Approaches for RSS-Based Floor Detection in Indoor Localization.

PubMed

Razavi, Alireza; Valkama, Mikko; Lohan, Elena Simona

2016-05-31

Floor detection for indoor 3D localization of mobile devices is currently an important challenge in the wireless world. Many approaches currently exist, but usually the robustness of such approaches is not addressed or investigated. The goal of this paper is to show how to robustify the floor estimation when probabilistic approaches with a low number of parameters are employed. Indeed, such an approach would allow a building-independent estimation and a lower computing power at the mobile side. Four robustified algorithms are to be presented: a robust weighted centroid localization method, a robust linear trilateration method, a robust nonlinear trilateration method, and a robust deconvolution method. The proposed approaches use the received signal strengths (RSS) measured by the Mobile Station (MS) from various heard WiFi access points (APs) and provide an estimate of the vertical position of the MS, which can be used for floor detection. We will show that robustification can indeed increase the performance of the RSS-based floor detection algorithms.

Virtual target tracking (VTT) as applied to mobile satellite communication networks

NASA Astrophysics Data System (ADS)

Amoozegar, Farid

1999-08-01

Traditionally, target tracking has been used for aerospace applications, such as, tracking highly maneuvering targets in a cluttered environment for missile-to-target intercept scenarios. Although the speed and maneuvering capability of current aerospace targets demand more efficient algorithms, many complex techniques have already been proposed in the literature, which primarily cover the defense applications of tracking methods. On the other hand, the rapid growth of Global Communication Systems, Global Information Systems (GIS), and Global Positioning Systems (GPS) is creating new and more diverse challenges for multi-target tracking applications. Mobile communication and computing can very well appreciate a huge market for Cellular Communication and Tracking Devices (CCTD), which will be tracking networked devices at the cellular level. The objective of this paper is to introduce a new concept, i.e., Virtual Target Tracking (VTT) for commercial applications of multi-target tracking algorithms and techniques as applied to mobile satellite communication networks. It would be discussed how Virtual Target Tracking would bring more diversity to target tracking research.

Platform-dependent optimization considerations for mHealth applications

NASA Astrophysics Data System (ADS)

Kaghyan, Sahak; Akopian, David; Sarukhanyan, Hakob

2015-03-01

Modern mobile devices contain integrated sensors that enable multitude of applications in such fields as mobile health (mHealth), entertainment, sports, etc. Human physical activity monitoring is one of such the emerging applications. There exists a range of challenges that relate to activity monitoring tasks, and, particularly, exploiting optimal solutions and architectures for respective mobile software application development. This work addresses mobile computations related to integrated inertial sensors for activity monitoring, such as accelerometers, gyroscopes, integrated global positioning system (GPS) and WLAN-based positioning, that can be used for activity monitoring. Some of the aspects will be discussed in this paper. Each of the sensing data sources has its own characteristics such as specific data formats, data rates, signal acquisition durations etc., and these specifications affect energy consumption. Energy consumption significantly varies as sensor data acquisition is followed by data analysis including various transformations and signal processing algorithms. This paper will address several aspects of more optimal activity monitoring implementations exploiting state-of-the-art capabilities of modern platforms.

Robust and efficient vision system for group of cooperating mobile robots with application to soccer robots.

PubMed

Klancar, Gregor; Kristan, Matej; Kovacic, Stanislav; Orqueda, Omar

2004-07-01

In this paper a global vision scheme for estimation of positions and orientations of mobile robots is presented. It is applied to robot soccer application which is a fast dynamic game and therefore needs an efficient and robust vision system implemented. General applicability of the vision system can be found in other robot applications such as mobile transport robots in production, warehouses, attendant robots, fast vision tracking of targets of interest and entertainment robotics. Basic operation of the vision system is divided into two steps. In the first, the incoming image is scanned and pixels are classified into a finite number of classes. At the same time, a segmentation algorithm is used to find corresponding regions belonging to one of the classes. In the second step, all the regions are examined. Selection of the ones that are a part of the observed object is made by means of simple logic procedures. The novelty is focused on optimization of the processing time needed to finish the estimation of possible object positions. Better results of the vision system are achieved by implementing camera calibration and shading correction algorithm. The former corrects camera lens distortion, while the latter increases robustness to irregular illumination conditions.

Application-oriented offloading in heterogeneous networks for mobile cloud computing

NASA Astrophysics Data System (ADS)

Tseng, Fan-Hsun; Cho, Hsin-Hung; Chang, Kai-Di; Li, Jheng-Cong; Shih, Timothy K.

2018-04-01

Nowadays Internet applications have become more complicated that mobile device needs more computing resources for shorter execution time but it is restricted to limited battery capacity. Mobile cloud computing (MCC) is emerged to tackle the finite resource problem of mobile device. MCC offloads the tasks and jobs of mobile devices to cloud and fog environments by using offloading scheme. It is vital to MCC that which task should be offloaded and how to offload efficiently. In the paper, we formulate the offloading problem between mobile device and cloud data center and propose two algorithms based on application-oriented for minimum execution time, i.e. the Minimum Offloading Time for Mobile device (MOTM) algorithm and the Minimum Execution Time for Cloud data center (METC) algorithm. The MOTM algorithm minimizes offloading time by selecting appropriate offloading links based on application categories. The METC algorithm minimizes execution time in cloud data center by selecting virtual and physical machines with corresponding resource requirements of applications. Simulation results show that the proposed mechanism not only minimizes total execution time for mobile devices but also decreases their energy consumption.

Sequencing sit-to-stand and upright posture for mobility limitation assessment: determination of the timing of the task phases from force platform data.

PubMed

Mazzà, Claudia; Zok, Mounir; Della Croce, Ugo

2005-06-01

The identification of quantitative tools to assess an individual's mobility limitation is a complex and challenging task. Several motor tasks have been designated as potential indicators of mobility limitation. In this study, a multiple motor task obtained by sequencing sit-to-stand and upright posture was used. Algorithms based on data obtained exclusively from a single force platform were developed to detect the timing of the motor task phases (sit-to-stand, preparation to the upright posture and upright posture). To test these algorithms, an experimental protocol inducing predictable changes in the acquired signals was designed. Twenty-two young, able-bodied subjects performed the task in four different conditions: self-selected natural and high speed with feet kept together, and self-selected natural and high speed with feet pelvis-width apart. The proposed algorithms effectively detected the timing of the task phases, the duration of which was sensitive to the four different experimental conditions. As expected, the duration of the sit-to-stand was sensitive to the speed of the task and not to the foot position, while the duration of the preparation to the upright posture was sensitive to foot position but not to speed. In addition to providing a simple and effective description of the execution of the motor task, the correct timing of the studied multiple task could facilitate the accurate determination of variables descriptive of the single isolated phases, allowing for a more thorough description of the motor task and therefore could contribute to the development of effective quantitative functional evaluation tests.

Using an improved association rules mining optimization algorithm in web-based mobile-learning system

NASA Astrophysics Data System (ADS)

Huang, Yin; Chen, Jianhua; Xiong, Shaojun

2009-07-01

Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.

[Algorithms for early mobilization in intensive care units].

PubMed

Nydahl, P; Dubb, R; Filipovic, S; Hermes, C; Jüttner, F; Kaltwasser, A; Klarmann, S; Mende, H; Nessizius, S; Rottensteiner, C

2017-03-01

Immobility of patients in intensive care units (ICU) can lead to long-lasting physical and cognitive decline. During the last few years, bundles for rehabilitation were developed, including early mobilization. The German guideline for positioning therapy and mobilization, in general, recommends the development of ICU-specific protocols. The aim of this narrative review is to provide guidance when developing a best practice protocol in one's own field of work. It is recommended to a) implement early mobilization as part of a bundle, including screening and management of patient's awareness, pain, anxiety, stress, delirium and family's presence, b) develop a traffic-light system of specific in- and exclusion criteria in an interprofessional process, c) use checklists to assess risks and preparation of mobilization, d) use the ICU Mobility Scale for targeting and documentation of mobilization, e) use relative safety criteria for hemodynamic and respiratory changes, and Borg Scale for subjective evaluation, f) document and evaluate systematically mobilization levels, barriers, unwanted safety events and other parameters.

On the performances of computer vision algorithms on mobile platforms

NASA Astrophysics Data System (ADS)

Battiato, S.; Farinella, G. M.; Messina, E.; Puglisi, G.; Ravì, D.; Capra, A.; Tomaselli, V.

2012-01-01

Computer Vision enables mobile devices to extract the meaning of the observed scene from the information acquired with the onboard sensor cameras. Nowadays, there is a growing interest in Computer Vision algorithms able to work on mobile platform (e.g., phone camera, point-and-shot-camera, etc.). Indeed, bringing Computer Vision capabilities on mobile devices open new opportunities in different application contexts. The implementation of vision algorithms on mobile devices is still a challenging task since these devices have poor image sensors and optics as well as limited processing power. In this paper we have considered different algorithms covering classic Computer Vision tasks: keypoint extraction, face detection, image segmentation. Several tests have been done to compare the performances of the involved mobile platforms: Nokia N900, LG Optimus One, Samsung Galaxy SII.

A study of malware detection on smart mobile devices

NASA Astrophysics Data System (ADS)

Yu, Wei; Zhang, Hanlin; Xu, Guobin

2013-05-01

The growing in use of smart mobile devices for everyday applications has stimulated the spread of mobile malware, especially on popular mobile platforms. As a consequence, malware detection becomes ever more critical in sustaining the mobile market and providing a better user experience. In this paper, we review the existing malware and detection schemes. Using real-world malware samples with known signatures, we evaluate four popular commercial anti-virus tools and our data shows that these tools can achieve high detection accuracy. To deal with the new malware with unknown signatures, we study the anomaly based detection using decision tree algorithm. We evaluate the effectiveness of our detection scheme using malware and legitimate software samples. Our data shows that the detection scheme using decision tree can achieve a detection rate up to 90% and a false positive rate as low as 10%.

A Leapfrog Navigation System

NASA Astrophysics Data System (ADS)

Opshaug, Guttorm Ringstad

There are times and places where conventional navigation systems, such as the Global Positioning System (GPS), are unavailable due to anything from temporary signal occultations to lack of navigation system infrastructure altogether. The goal of the Leapfrog Navigation System (LNS) is to provide localized positioning services for such cases. The concept behind leapfrog navigation is to advance a group of navigation units teamwise into an area of interest. In a practical 2-D case, leapfrogging assumes known initial positions of at least two currently stationary navigation units. Two or more mobile units can then start to advance into the area of interest. The positions of the mobiles are constantly being calculated based on cross-range distance measurements to the stationary units, as well as cross-ranges among the mobiles themselves. At some point the mobile units stop, and the stationary units are released to move. This second team of units (now mobile) can then overtake the first team (now stationary) and travel even further towards the common goal of the group. Since there always is one stationary team, the position of any unit can be referenced back to the initial positions. Thus, LNS provides absolute positioning. I developed navigation algorithms needed to solve leapfrog positions based on cross-range measurements. I used statistical tools to predict how position errors would grow as a function of navigation unit geometry, cross-range measurement accuracy and previous position errors. Using this knowledge I predicted that a 4-unit Leapfrog Navigation System using 100 m baselines and 200 m leap distances could travel almost 15 km before accumulating absolute position errors of 10 m (1sigma). Finally, I built a prototype leapfrog navigation system using 4 GPS transceiver ranging units. I placed the 4 units in the vertices a 10m x 10m square, and leapfrogged the group 20 meters forwards, and then back again (40 m total travel). Average horizontal RMS position errors never exceeded 16 cm during these field tests.

Designing of routing algorithms in autonomous distributed data transmission system for mobile computing devices with ‘WiFi-Direct’ technology

NASA Astrophysics Data System (ADS)

Nikitin, I. A.; Sherstnev, V. S.; Sherstneva, A. I.; Botygin, I. A.

2017-02-01

The results of the research of existent routing protocols in wireless networks and their main features are discussed in the paper. Basing on the protocol data, the routing protocols in wireless networks, including search routing algorithms and phone directory exchange algorithms, are designed with the ‘WiFi-Direct’ technology. Algorithms without IP-protocol were designed, and that enabled one to increase the efficiency of the algorithms while working only with the MAC-addresses of the devices. The developed algorithms are expected to be used in the mobile software engineering with the Android platform taken as base. Easier algorithms and formats of the well-known route protocols, rejection of the IP-protocols enables to use the developed protocols on more primitive mobile devices. Implementation of the protocols to the engineering industry enables to create data transmission networks among working places and mobile robots without any access points.

Automated Robot Movement in the Mapped Area Using Fuzzy Logic for Wheel Chair Application

NASA Astrophysics Data System (ADS)

Siregar, B.; Efendi, S.; Ramadhana, H.; Andayani, U.; Fahmi, F.

2018-03-01

The difficulties of the disabled to move make them unable to live independently. People with disabilities need supporting device to move from place to place. For that, we proposed a solution that can help people with disabilities to move from one room to another automatically. This study aims to create a wheelchair prototype in the form of a wheeled robot as a means to learn the automatic mobilization. The fuzzy logic algorithm was used to determine motion direction based on initial position, ultrasonic sensors reading in avoiding obstacles, infrared sensors reading as a black line reader for the wheeled robot to move smooth and smartphone as a mobile controller. As a result, smartphones with the Android operating system can control the robot using Bluetooth. Here Bluetooth technology can be used to control the robot from a maximum distance of 15 meters. The proposed algorithm was able to work stable for automatic motion determination based on initial position, and also able to modernize the wheelchair movement from one room to another automatically.

Multi-camera sensor system for 3D segmentation and localization of multiple mobile robots.

PubMed

Losada, Cristina; Mazo, Manuel; Palazuelos, Sira; Pizarro, Daniel; Marrón, Marta

2010-01-01

This paper presents a method for obtaining the motion segmentation and 3D localization of multiple mobile robots in an intelligent space using a multi-camera sensor system. The set of calibrated and synchronized cameras are placed in fixed positions within the environment (intelligent space). The proposed algorithm for motion segmentation and 3D localization is based on the minimization of an objective function. This function includes information from all the cameras, and it does not rely on previous knowledge or invasive landmarks on board the robots. The proposed objective function depends on three groups of variables: the segmentation boundaries, the motion parameters and the depth. For the objective function minimization, we use a greedy iterative algorithm with three steps that, after initialization of segmentation boundaries and depth, are repeated until convergence.

3D interactive surgical visualization system using mobile spatial information acquisition and autostereoscopic display.

PubMed

Fan, Zhencheng; Weng, Yitong; Chen, Guowen; Liao, Hongen

2017-07-01

Three-dimensional (3D) visualization of preoperative and intraoperative medical information becomes more and more important in minimally invasive surgery. We develop a 3D interactive surgical visualization system using mobile spatial information acquisition and autostereoscopic display for surgeons to observe surgical target intuitively. The spatial information of regions of interest (ROIs) is captured by the mobile device and transferred to a server for further image processing. Triangular patches of intraoperative data with texture are calculated with a dimension-reduced triangulation algorithm and a projection-weighted mapping algorithm. A point cloud selection-based warm-start iterative closest point (ICP) algorithm is also developed for fusion of the reconstructed 3D intraoperative image and the preoperative image. The fusion images are rendered for 3D autostereoscopic display using integral videography (IV) technology. Moreover, 3D visualization of medical image corresponding to observer's viewing direction is updated automatically using mutual information registration method. Experimental results show that the spatial position error between the IV-based 3D autostereoscopic fusion image and the actual object was 0.38±0.92mm (n=5). The system can be utilized in telemedicine, operating education, surgical planning, navigation, etc. to acquire spatial information conveniently and display surgical information intuitively. Copyright © 2017 Elsevier Inc. All rights reserved.

Etracker: A Mobile Gaze-Tracking System with Near-Eye Display Based on a Combined Gaze-Tracking Algorithm.

PubMed

Li, Bin; Fu, Hong; Wen, Desheng; Lo, WaiLun

2018-05-19

Eye tracking technology has become increasingly important for psychological analysis, medical diagnosis, driver assistance systems, and many other applications. Various gaze-tracking models have been established by previous researchers. However, there is currently no near-eye display system with accurate gaze-tracking performance and a convenient user experience. In this paper, we constructed a complete prototype of the mobile gaze-tracking system ' Etracker ' with a near-eye viewing device for human gaze tracking. We proposed a combined gaze-tracking algorithm. In this algorithm, the convolutional neural network is used to remove blinking images and predict coarse gaze position, and then a geometric model is defined for accurate human gaze tracking. Moreover, we proposed using the mean value of gazes to resolve pupil center changes caused by nystagmus in calibration algorithms, so that an individual user only needs to calibrate it the first time, which makes our system more convenient. The experiments on gaze data from 26 participants show that the eye center detection accuracy is 98% and Etracker can provide an average gaze accuracy of 0.53° at a rate of 30⁻60 Hz.

Enhancement of Fast Face Detection Algorithm Based on a Cascade of Decision Trees

NASA Astrophysics Data System (ADS)

Khryashchev, V. V.; Lebedev, A. A.; Priorov, A. L.

2017-05-01

Face detection algorithm based on a cascade of ensembles of decision trees (CEDT) is presented. The new approach allows detecting faces other than the front position through the use of multiple classifiers. Each classifier is trained for a specific range of angles of the rotation head. The results showed a high rate of productivity for CEDT on images with standard size. The algorithm increases the area under the ROC-curve of 13% compared to a standard Viola-Jones face detection algorithm. Final realization of given algorithm consist of 5 different cascades for frontal/non-frontal faces. One more thing which we take from the simulation results is a low computational complexity of CEDT algorithm in comparison with standard Viola-Jones approach. This could prove important in the embedded system and mobile device industries because it can reduce the cost of hardware and make battery life longer.

Evaluation of the novel algorithm of flexible ligand docking with moveable target-protein atoms.

PubMed

Sulimov, Alexey V; Zheltkov, Dmitry A; Oferkin, Igor V; Kutov, Danil C; Katkova, Ekaterina V; Tyrtyshnikov, Eugene E; Sulimov, Vladimir B

2017-01-01

We present the novel docking algorithm based on the Tensor Train decomposition and the TT-Cross global optimization. The algorithm is applied to the docking problem with flexible ligand and moveable protein atoms. The energy of the protein-ligand complex is calculated in the frame of the MMFF94 force field in vacuum. The grid of precalculated energy potentials of probe ligand atoms in the field of the target protein atoms is not used. The energy of the protein-ligand complex for any given configuration is computed directly with the MMFF94 force field without any fitting parameters. The conformation space of the system coordinates is formed by translations and rotations of the ligand as a whole, by the ligand torsions and also by Cartesian coordinates of the selected target protein atoms. Mobility of protein and ligand atoms is taken into account in the docking process simultaneously and equally. The algorithm is realized in the novel parallel docking SOL-P program and results of its performance for a set of 30 protein-ligand complexes are presented. Dependence of the docking positioning accuracy is investigated as a function of parameters of the docking algorithm and the number of protein moveable atoms. It is shown that mobility of the protein atoms improves docking positioning accuracy. The SOL-P program is able to perform docking of a flexible ligand into the active site of the target protein with several dozens of protein moveable atoms: the native crystallized ligand pose is correctly found as the global energy minimum in the search space with 157 dimensions using 4700 CPU ∗ h at the Lomonosov supercomputer.

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks.

PubMed

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-07-14

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle's position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.

An Analysis of Navigation Algorithms for Smartphones Using J2ME

NASA Astrophysics Data System (ADS)

Santos, André C.; Tarrataca, Luís; Cardoso, João M. P.

Embedded systems are considered one of the most potential areas for future innovations. Two embedded fields that will most certainly take a primary role in future innovations are mobile robotics and mobile computing. Mobile robots and smartphones are growing in number and functionalities, becoming a presence in our daily life. In this paper, we study the current feasibility of a smartphone to execute navigation algorithms. As a test case, we use a smartphone to control an autonomous mobile robot. We tested three navigation problems: Mapping, Localization and Path Planning. For each of these problems, an algorithm has been chosen, developed in J2ME, and tested on the field. Results show the current mobile Java capacity for executing computationally demanding algorithms and reveal the real possibility of using smartphones for autonomous navigation.

Localization Algorithms of Underwater Wireless Sensor Networks: A Survey

PubMed Central

Han, Guangjie; Jiang, Jinfang; Shu, Lei; Xu, Yongjun; Wang, Feng

2012-01-01

In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes’ mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs. PMID:22438752

A motion algorithm to extract physical and motion parameters of mobile targets from cone-beam computed tomographic images.

PubMed

Alsbou, Nesreen; Ahmad, Salahuddin; Ali, Imad

2016-05-17

A motion algorithm has been developed to extract length, CT number level and motion amplitude of a mobile target from cone-beam CT (CBCT) images. The algorithm uses three measurable parameters: Apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm are tested with mobile targets having different well-known sizes that are made from tissue-equivalent gel which is inserted into a thorax phantom. The phantom moves sinusoidally in one-direction to simulate respiratory motion using eight amplitudes ranging 0-20 mm. Using this motion algorithm, three unknown parameters are extracted that include: Length of the target, CT number level, speed or motion amplitude for the mobile targets from CBCT images. The motion algorithm solves for the three unknown parameters using measured length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agrees with the measured lengths which are dependent on the target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, the target length and motion amplitude. Motion frequency and phase do not affect the elongation and CT number distribution of the mobile target and could not be determined. A motion algorithm has been developed to extract three parameters that include length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement of motion tracking and sorting of the images into different breathing phases. The motion model developed here works well for tumors that have simple shapes, high contrast relative to surrounding tissues and move nearly in regular motion pattern that can be approximated with a simple sinusoidal function. This algorithm has potential applications in diagnostic CT imaging and radiotherapy in terms of motion management.

Applicability Analysis of Cloth Simulation Filtering Algorithm for Mobile LIDAR Point Cloud

NASA Astrophysics Data System (ADS)

Cai, S.; Zhang, W.; Qi, J.; Wan, P.; Shao, J.; Shen, A.

2018-04-01

Classifying the original point clouds into ground and non-ground points is a key step in LiDAR (light detection and ranging) data post-processing. Cloth simulation filtering (CSF) algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS) has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM), 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature) for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44 %, 0.77 % and1.20 %. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks.

PubMed

Ma, Junjie; Meng, Fansheng; Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-02-16

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths.

Distributed Water Pollution Source Localization with Mobile UV-Visible Spectrometer Probes in Wireless Sensor Networks

PubMed Central

Zhou, Yuexi; Wang, Yeyao; Shi, Ping

2018-01-01

Pollution accidents that occur in surface waters, especially in drinking water source areas, greatly threaten the urban water supply system. During water pollution source localization, there are complicated pollutant spreading conditions and pollutant concentrations vary in a wide range. This paper provides a scalable total solution, investigating a distributed localization method in wireless sensor networks equipped with mobile ultraviolet-visible (UV-visible) spectrometer probes. A wireless sensor network is defined for water quality monitoring, where unmanned surface vehicles and buoys serve as mobile and stationary nodes, respectively. Both types of nodes carry UV-visible spectrometer probes to acquire in-situ multiple water quality parameter measurements, in which a self-adaptive optical path mechanism is designed to flexibly adjust the measurement range. A novel distributed algorithm, called Dual-PSO, is proposed to search for the water pollution source, where one particle swarm optimization (PSO) procedure computes the water quality multi-parameter measurements on each node, utilizing UV-visible absorption spectra, and another one finds the global solution of the pollution source position, regarding mobile nodes as particles. Besides, this algorithm uses entropy to dynamically recognize the most sensitive parameter during searching. Experimental results demonstrate that online multi-parameter monitoring of a drinking water source area with a wide dynamic range is achieved by this wireless sensor network and water pollution sources are localized efficiently with low-cost mobile node paths. PMID:29462929

Application of the Approximate Bayesian Computation methods in the stochastic estimation of atmospheric contamination parameters for mobile sources

NASA Astrophysics Data System (ADS)

Kopka, Piotr; Wawrzynczak, Anna; Borysiewicz, Mieczyslaw

2016-11-01

In this paper the Bayesian methodology, known as Approximate Bayesian Computation (ABC), is applied to the problem of the atmospheric contamination source identification. The algorithm input data are on-line arriving concentrations of the released substance registered by the distributed sensors network. This paper presents the Sequential ABC algorithm in detail and tests its efficiency in estimation of probabilistic distributions of atmospheric release parameters of a mobile contamination source. The developed algorithms are tested using the data from Over-Land Atmospheric Diffusion (OLAD) field tracer experiment. The paper demonstrates estimation of seven parameters characterizing the contamination source, i.e.: contamination source starting position (x,y), the direction of the motion of the source (d), its velocity (v), release rate (q), start time of release (ts) and its duration (td). The online-arriving new concentrations dynamically update the probability distributions of search parameters. The atmospheric dispersion Second-order Closure Integrated PUFF (SCIPUFF) Model is used as the forward model to predict the concentrations at the sensors locations.

Leveraging social system networks in ubiquitous high-data-rate health systems.

PubMed

Massey, Tammara; Marfia, Gustavo; Stoelting, Adam; Tomasi, Riccardo; Spirito, Maurizio A; Sarrafzadeh, Majid; Pau, Giovanni

2011-05-01

Social system networks with high data rates and limited storage will discard data if the system cannot connect and upload the data to a central server. We address the challenge of limited storage capacity in mobile health systems during network partitions with a heuristic that achieves efficiency in storage capacity by modifying the granularity of the medical data during long intercontact periods. Patterns in the connectivity, reception rate, distance, and location are extracted from the social system network and leveraged in the global algorithm and online heuristic. In the global algorithm, the stochastic nature of the data is modeled with maximum likelihood estimation based on the distribution of the reception rates. In the online heuristic, the correlation between system position and the reception rate is combined with patterns in human mobility to estimate the intracontact and intercontact time. The online heuristic performs well with a low data loss of 2.1%-6.1%.

Intra-operative adjustment of standard planes in C-arm CT image data.

PubMed

Brehler, Michael; Görres, Joseph; Franke, Jochen; Barth, Karl; Vetter, Sven Y; Grützner, Paul A; Meinzer, Hans-Peter; Wolf, Ivo; Nabers, Diana

2016-03-01

With the help of an intra-operative mobile C-arm CT, medical interventions can be verified and corrected, avoiding the need for a post-operative CT and a second intervention. An exact adjustment of standard plane positions is necessary for the best possible assessment of the anatomical regions of interest but the mobility of the C-arm causes the need for a time-consuming manual adjustment. In this article, we present an automatic plane adjustment at the example of calcaneal fractures. We developed two feature detection methods (2D and pseudo-3D) based on SURF key points and also transferred the SURF approach to 3D. Combined with an atlas-based registration, our algorithm adjusts the standard planes of the calcaneal C-arm images automatically. The robustness of the algorithms is evaluated using a clinical data set. Additionally, we tested the algorithm's performance for two registration approaches, two resolutions of C-arm images and two methods for metal artifact reduction. For the feature extraction, the novel 3D-SURF approach performs best. As expected, a higher resolution ([Formula: see text] voxel) leads also to more robust feature points and is therefore slightly better than the [Formula: see text] voxel images (standard setting of device). Our comparison of two different artifact reduction methods and the complete removal of metal in the images shows that our approach is highly robust against artifacts and the number and position of metal implants. By introducing our fast algorithmic processing pipeline, we developed the first steps for a fully automatic assistance system for the assessment of C-arm CT images.

Robust position estimation of a mobile vehicle

NASA Astrophysics Data System (ADS)

Conan, Vania; Boulanger, Pierre; Elgazzar, Shadia

1994-11-01

The ability to estimate the position of a mobile vehicle is a key task for navigation over large distances in complex indoor environments such as nuclear power plants. Schematics of the plants are available, but they are incomplete, as real settings contain many objects, such as pipes, cables or furniture, that mask part of the model. The position estimation method described in this paper matches 3-D data with a simple schematic of a plant. It is basically independent of odometry information and viewpoint, robust to noisy data and spurious points and largely insensitive to occlusions. The method is based on a hypothesis/verification paradigm and its complexity is polynomial; it runs in (Omicron) (m4n4), where m represents the number of model patches and n the number of scene patches. Heuristics are presented to speed up the algorithm. Results on real 3-D data show good behavior even when the scene is very occluded.

Stereo vision tracking of multiple objects in complex indoor environments.

PubMed

Marrón-Romera, Marta; García, Juan C; Sotelo, Miguel A; Pizarro, Daniel; Mazo, Manuel; Cañas, José M; Losada, Cristina; Marcos, Alvaro

2010-01-01

This paper presents a novel system capable of solving the problem of tracking multiple targets in a crowded, complex and dynamic indoor environment, like those typical of mobile robot applications. The proposed solution is based on a stereo vision set in the acquisition step and a probabilistic algorithm in the obstacles position estimation process. The system obtains 3D position and speed information related to each object in the robot's environment; then it achieves a classification between building elements (ceiling, walls, columns and so on) and the rest of items in robot surroundings. All objects in robot surroundings, both dynamic and static, are considered to be obstacles but the structure of the environment itself. A combination of a Bayesian algorithm and a deterministic clustering process is used in order to obtain a multimodal representation of speed and position of detected obstacles. Performance of the final system has been tested against state of the art proposals; test results validate the authors' proposal. The designed algorithms and procedures provide a solution to those applications where similar multimodal data structures are found.

Developing operation algorithms for vision subsystems in autonomous mobile robots

NASA Astrophysics Data System (ADS)

Shikhman, M. V.; Shidlovskiy, S. V.

2018-05-01

The paper analyzes algorithms for selecting keypoints on the image for the subsequent automatic detection of people and obstacles. The algorithm is based on the histogram of oriented gradients and the support vector method. The combination of these methods allows successful selection of dynamic and static objects. The algorithm can be applied in various autonomous mobile robots.

Peer-to-peer model for the area coverage and cooperative control of mobile sensor networks

NASA Astrophysics Data System (ADS)

Tan, Jindong; Xi, Ning

2004-09-01

This paper presents a novel model and distributed algorithms for the cooperation and redeployment of mobile sensor networks. A mobile sensor network composes of a collection of wireless connected mobile robots equipped with a variety of sensors. In such a sensor network, each mobile node has sensing, computation, communication, and locomotion capabilities. The locomotion ability enhances the autonomous deployment of the system. The system can be rapidly deployed to hostile environment, inaccessible terrains or disaster relief operations. The mobile sensor network is essentially a cooperative multiple robot system. This paper first presents a peer-to-peer model to define the relationship between neighboring communicating robots. Delaunay Triangulation and Voronoi diagrams are used to define the geometrical relationship between sensor nodes. This distributed model allows formal analysis for the fusion of spatio-temporal sensory information of the network. Based on the distributed model, this paper discusses a fault tolerant algorithm for autonomous self-deployment of the mobile robots. The algorithm considers the environment constraints, the presence of obstacles and the nonholonomic constraints of the robots. The distributed algorithm enables the system to reconfigure itself such that the area covered by the system can be enlarged. Simulation results have shown the effectiveness of the distributed model and deployment algorithms.

NAVIS-An UGV Indoor Positioning System Using Laser Scan Matching for Large-Area Real-Time Applications

PubMed Central

Tang, Jian.; Chen, Yuwei.; Jaakkola, Anttoni.; Liu, Jinbing.; Hyyppä, Juha.; Hyyppä, Hannu.

2014-01-01

Laser scan matching with grid-based maps is a promising tool for real-time indoor positioning of mobile Unmanned Ground Vehicles (UGVs). While there are critical implementation problems, such as the ability to estimate the position by sensing the unknown indoor environment with sufficient accuracy and low enough latency for stable vehicle control, further development work is necessary. Unfortunately, most of the existing methods employ heuristics for quick positioning in which numerous accumulated errors easily lead to loss of positioning accuracy. This severely restricts its applications in large areas and over lengthy periods of time. This paper introduces an efficient real-time mobile UGV indoor positioning system for large-area applications using laser scan matching with an improved probabilistically-motivated Maximum Likelihood Estimation (IMLE) algorithm, which is based on a multi-resolution patch-divided grid likelihood map. Compared with traditional methods, the improvements embodied in IMLE include: (a) Iterative Closed Point (ICP) preprocessing, which adaptively decreases the search scope; (b) a totally brute search matching method on multi-resolution map layers, based on the likelihood value between current laser scan and the grid map within refined search scope, adopted to obtain the global optimum position at each scan matching; and (c) a patch-divided likelihood map supporting a large indoor area. A UGV platform called NAVIS was designed, manufactured, and tested based on a low-cost robot integrating a LiDAR and an odometer sensor to verify the IMLE algorithm. A series of experiments based on simulated data and field tests with NAVIS proved that the proposed IMEL algorithm is a better way to perform local scan matching that can offer a quick and stable positioning solution with high accuracy so it can be part of a large area localization/mapping, application. The NAVIS platform can reach an updating rate of 12 Hz in a feature-rich environment and 2 Hz even in a feature-poor environment, respectively. Therefore, it can be utilized in a real-time application. PMID:24999715

NAVIS-An UGV indoor positioning system using laser scan matching for large-area real-time applications.

PubMed

Tang, Jian; Chen, Yuwei; Jaakkola, Anttoni; Liu, Jinbing; Hyyppä, Juha; Hyyppä, Hannu

2014-07-04

Laser scan matching with grid-based maps is a promising tool for real-time indoor positioning of mobile Unmanned Ground Vehicles (UGVs). While there are critical implementation problems, such as the ability to estimate the position by sensing the unknown indoor environment with sufficient accuracy and low enough latency for stable vehicle control, further development work is necessary. Unfortunately, most of the existing methods employ heuristics for quick positioning in which numerous accumulated errors easily lead to loss of positioning accuracy. This severely restricts its applications in large areas and over lengthy periods of time. This paper introduces an efficient real-time mobile UGV indoor positioning system for large-area applications using laser scan matching with an improved probabilistically-motivated Maximum Likelihood Estimation (IMLE) algorithm, which is based on a multi-resolution patch-divided grid likelihood map. Compared with traditional methods, the improvements embodied in IMLE include: (a) Iterative Closed Point (ICP) preprocessing, which adaptively decreases the search scope; (b) a totally brute search matching method on multi-resolution map layers, based on the likelihood value between current laser scan and the grid map within refined search scope, adopted to obtain the global optimum position at each scan matching; and (c) a patch-divided likelihood map supporting a large indoor area. A UGV platform called NAVIS was designed, manufactured, and tested based on a low-cost robot integrating a LiDAR and an odometer sensor to verify the IMLE algorithm. A series of experiments based on simulated data and field tests with NAVIS proved that the proposed IMEL algorithm is a better way to perform local scan matching that can offer a quick and stable positioning solution with high accuracy so it can be part of a large area localization/mapping, application. The NAVIS platform can reach an updating rate of 12 Hz in a feature-rich environment and 2 Hz even in a feature-poor environment, respectively. Therefore, it can be utilized in a real-time application.

Improving mobile robot localization: grid-based approach

NASA Astrophysics Data System (ADS)

Yan, Junchi

2012-02-01

Autonomous mobile robots have been widely studied not only as advanced facilities for industrial and daily life automation, but also as a testbed in robotics competitions for extending the frontier of current artificial intelligence. In many of such contests, the robot is supposed to navigate on the ground with a grid layout. Based on this observation, we present a localization error correction method by exploring the geometric feature of the tile patterns. On top of the classical inertia-based positioning, our approach employs three fiber-optic sensors that are assembled under the bottom of the robot, presenting an equilateral triangle layout. The sensor apparatus, together with the proposed supporting algorithm, are designed to detect a line's direction (vertical or horizontal) by monitoring the grid crossing events. As a result, the line coordinate information can be fused to rectify the cumulative localization deviation from inertia positioning. The proposed method is analyzed theoretically in terms of its error bound and also has been implemented and tested on a customary developed two-wheel autonomous mobile robot.

Advanced Integration of WiFi and Inertial Navigation Systems for Indoor Mobile Positioning

NASA Astrophysics Data System (ADS)

Evennou, Frédéric; Marx, François

2006-12-01

This paper presents an aided dead-reckoning navigation structure and signal processing algorithms for self localization of an autonomous mobile device by fusing pedestrian dead reckoning and WiFi signal strength measurements. WiFi and inertial navigation systems (INS) are used for positioning and attitude determination in a wide range of applications. Over the last few years, a number of low-cost inertial sensors have become available. Although they exhibit large errors, WiFi measurements can be used to correct the drift weakening the navigation based on this technology. On the other hand, INS sensors can interact with the WiFi positioning system as they provide high-accuracy real-time navigation. A structure based on a Kalman filter and a particle filter is proposed. It fuses the heterogeneous information coming from those two independent technologies. Finally, the benefits of the proposed architecture are evaluated and compared with the pure WiFi and INS positioning systems.

SU-E-J-150: Four-Dimensional Cone-Beam CT Algorithm by Extraction of Physical and Motion Parameter of Mobile Targets Retrospective to Image Reconstruction with Motion Modeling

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

Ali, I; Ahmad, S; Alsbou, N

Purpose: To develop 4D-cone-beam CT (CBCT) algorithm by motion modeling that extracts actual length, CT numbers level and motion amplitude of a mobile target retrospective to image reconstruction by motion modeling. Methods: The algorithm used three measurable parameters: apparent length and blurred CT number distribution of a mobile target obtained from CBCT images to determine actual length, CT-number value of the stationary target, and motion amplitude. The predictions of this algorithm were tested with mobile targets that with different well-known sizes made from tissue-equivalent gel which was inserted into a thorax phantom. The phantom moved sinusoidally in one-direction to simulatemore » respiratory motion using eight amplitudes ranging 0–20mm. Results: Using this 4D-CBCT algorithm, three unknown parameters were extracted that include: length of the target, CT number level, speed or motion amplitude for the mobile targets retrospective to image reconstruction. The motion algorithms solved for the three unknown parameters using measurable apparent length, CT number level and gradient for a well-defined mobile target obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on the actual target length and motion amplitude. The gradient of the CT number distribution of the mobile target is dependent on the stationary CT number level, actual target length and motion amplitude. Motion frequency and phase did not affect the elongation and CT number distribution of the mobile target and could not be determined. Conclusion: A 4D-CBCT motion algorithm was developed to extract three parameters that include actual length, CT number level and motion amplitude or speed of mobile targets directly from reconstructed CBCT images without prior knowledge of the stationary target parameters. This algorithm provides alternative to 4D-CBCT without requirement to motion tracking and sorting of the images into different breathing phases which has potential applications in diagnostic CT imaging and radiotherapy.« less

a Voxel-Based Filtering Algorithm for Mobile LIDAR Data

NASA Astrophysics Data System (ADS)

Qin, H.; Guan, G.; Yu, Y.; Zhong, L.

2018-04-01

This paper presents a stepwise voxel-based filtering algorithm for mobile LiDAR data. In the first step, to improve computational efficiency, mobile LiDAR points, in xy-plane, are first partitioned into a set of two-dimensional (2-D) blocks with a given block size, in each of which all laser points are further organized into an octree partition structure with a set of three-dimensional (3-D) voxels. Then, a voxel-based upward growing processing is performed to roughly separate terrain from non-terrain points with global and local terrain thresholds. In the second step, the extracted terrain points are refined by computing voxel curvatures. This voxel-based filtering algorithm is comprehensively discussed in the analyses of parameter sensitivity and overall performance. An experimental study performed on multiple point cloud samples, collected by different commercial mobile LiDAR systems, showed that the proposed algorithm provides a promising solution to terrain point extraction from mobile point clouds.

Mobile robot motion estimation using Hough transform

NASA Astrophysics Data System (ADS)

Aldoshkin, D. N.; Yamskikh, T. N.; Tsarev, R. Yu

2018-05-01

This paper proposes an algorithm for estimation of mobile robot motion. The geometry of surrounding space is described with range scans (samples of distance measurements) taken by the mobile robot’s range sensors. A similar sample of space geometry in any arbitrary preceding moment of time or the environment map can be used as a reference. The suggested algorithm is invariant to isotropic scaling of samples or map that allows using samples measured in different units and maps made at different scales. The algorithm is based on Hough transform: it maps from measurement space to a straight-line parameters space. In the straight-line parameters, space the problems of estimating rotation, scaling and translation are solved separately breaking down a problem of estimating mobile robot localization into three smaller independent problems. The specific feature of the algorithm presented is its robustness to noise and outliers inherited from Hough transform. The prototype of the system of mobile robot orientation is described.

A novel Gravity-FREAK feature extraction and Gravity-KLT tracking registration algorithm based on iPhone MEMS mobile sensor in mobile environment

PubMed Central

Lin, Fan; Xiao, Bin

2017-01-01

Based on the traditional Fast Retina Keypoint (FREAK) feature description algorithm, this paper proposed a Gravity-FREAK feature description algorithm based on Micro-electromechanical Systems (MEMS) sensor to overcome the limited computing performance and memory resources of mobile devices and further improve the reality interaction experience of clients through digital information added to the real world by augmented reality technology. The algorithm takes the gravity projection vector corresponding to the feature point as its feature orientation, which saved the time of calculating the neighborhood gray gradient of each feature point, reduced the cost of calculation and improved the accuracy of feature extraction. In the case of registration method of matching and tracking natural features, the adaptive and generic corner detection based on the Gravity-FREAK matching purification algorithm was used to eliminate abnormal matches, and Gravity Kaneda-Lucas Tracking (KLT) algorithm based on MEMS sensor can be used for the tracking registration of the targets and robustness improvement of tracking registration algorithm under mobile environment. PMID:29088228

A novel Gravity-FREAK feature extraction and Gravity-KLT tracking registration algorithm based on iPhone MEMS mobile sensor in mobile environment.

PubMed

Hong, Zhiling; Lin, Fan; Xiao, Bin

2017-01-01

Based on the traditional Fast Retina Keypoint (FREAK) feature description algorithm, this paper proposed a Gravity-FREAK feature description algorithm based on Micro-electromechanical Systems (MEMS) sensor to overcome the limited computing performance and memory resources of mobile devices and further improve the reality interaction experience of clients through digital information added to the real world by augmented reality technology. The algorithm takes the gravity projection vector corresponding to the feature point as its feature orientation, which saved the time of calculating the neighborhood gray gradient of each feature point, reduced the cost of calculation and improved the accuracy of feature extraction. In the case of registration method of matching and tracking natural features, the adaptive and generic corner detection based on the Gravity-FREAK matching purification algorithm was used to eliminate abnormal matches, and Gravity Kaneda-Lucas Tracking (KLT) algorithm based on MEMS sensor can be used for the tracking registration of the targets and robustness improvement of tracking registration algorithm under mobile environment.

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter.

PubMed

Alatise, Mary B; Hancke, Gerhard P

2017-09-21

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs).

Pose Estimation of a Mobile Robot Based on Fusion of IMU Data and Vision Data Using an Extended Kalman Filter

PubMed Central

Hancke, Gerhard P.

2017-01-01

Using a single sensor to determine the pose estimation of a device cannot give accurate results. This paper presents a fusion of an inertial sensor of six degrees of freedom (6-DoF) which comprises the 3-axis of an accelerometer and the 3-axis of a gyroscope, and a vision to determine a low-cost and accurate position for an autonomous mobile robot. For vision, a monocular vision-based object detection algorithm speeded-up robust feature (SURF) and random sample consensus (RANSAC) algorithms were integrated and used to recognize a sample object in several images taken. As against the conventional method that depend on point-tracking, RANSAC uses an iterative method to estimate the parameters of a mathematical model from a set of captured data which contains outliers. With SURF and RANSAC, improved accuracy is certain; this is because of their ability to find interest points (features) under different viewing conditions using a Hessain matrix. This approach is proposed because of its simple implementation, low cost, and improved accuracy. With an extended Kalman filter (EKF), data from inertial sensors and a camera were fused to estimate the position and orientation of the mobile robot. All these sensors were mounted on the mobile robot to obtain an accurate localization. An indoor experiment was carried out to validate and evaluate the performance. Experimental results show that the proposed method is fast in computation, reliable and robust, and can be considered for practical applications. The performance of the experiments was verified by the ground truth data and root mean square errors (RMSEs). PMID:28934102

RAC-multi: reader anti-collision algorithm for multichannel mobile RFID networks.

PubMed

Shin, Kwangcheol; Song, Wonil

2010-01-01

At present, RFID is installed on mobile devices such as mobile phones or PDAs and provides a means to obtain information about objects equipped with an RFID tag over a multi-channeled telecommunication networks. To use mobile RFIDs, reader collision problems should be addressed given that readers are continuously moving. Moreover, in a multichannel environment for mobile RFIDs, interference between adjacent channels should be considered. This work first defines a new concept of a reader collision problem between adjacent channels and then suggests a novel reader anti-collision algorithm for RFID readers that use multiple channels. To avoid interference with adjacent channels, the suggested algorithm separates data channels into odd and even numbered channels and allocates odd-numbered channels first to readers. It also sets an unused channel between the control channel and data channels to ensure that control messages and the signal of the adjacent channel experience no interference. Experimental results show that suggested algorithm shows throughput improvements ranging from 29% to 46% for tag identifications compared to the GENTLE reader anti-collision algorithm for multichannel RFID networks.

RAC-Multi: Reader Anti-Collision Algorithm for Multichannel Mobile RFID Networks

PubMed Central

Shin, Kwangcheol; Song, Wonil

2010-01-01

At present, RFID is installed on mobile devices such as mobile phones or PDAs and provides a means to obtain information about objects equipped with an RFID tag over a multi-channeled telecommunication networks. To use mobile RFIDs, reader collision problems should be addressed given that readers are continuously moving. Moreover, in a multichannel environment for mobile RFIDs, interference between adjacent channels should be considered. This work first defines a new concept of a reader collision problem between adjacent channels and then suggests a novel reader anti-collision algorithm for RFID readers that use multiple channels. To avoid interference with adjacent channels, the suggested algorithm separates data channels into odd and even numbered channels and allocates odd-numbered channels first to readers. It also sets an unused channel between the control channel and data channels to ensure that control messages and the signal of the adjacent channel experience no interference. Experimental results show that suggested algorithm shows throughput improvements ranging from 29% to 46% for tag identifications compared to the GENTLE reader anti-collision algorithm for multichannel RFID networks. PMID:22315528

Modelling human mobility patterns using photographic data shared online.

PubMed

Barchiesi, Daniele; Preis, Tobias; Bishop, Steven; Moat, Helen Susannah

2015-08-01

Humans are inherently mobile creatures. The way we move around our environment has consequences for a wide range of problems, including the design of efficient transportation systems and the planning of urban areas. Here, we gather data about the position in space and time of about 16 000 individuals who uploaded geo-tagged images from locations within the UK to the Flickr photo-sharing website. Inspired by the theory of Lévy flights, which has previously been used to describe the statistical properties of human mobility, we design a machine learning algorithm to infer the probability of finding people in geographical locations and the probability of movement between pairs of locations. Our findings are in general agreement with official figures in the UK and on travel flows between pairs of major cities, suggesting that online data sources may be used to quantify and model large-scale human mobility patterns.

Modelling human mobility patterns using photographic data shared online

PubMed Central

Barchiesi, Daniele; Preis, Tobias; Bishop, Steven; Moat, Helen Susannah

2015-01-01

Humans are inherently mobile creatures. The way we move around our environment has consequences for a wide range of problems, including the design of efficient transportation systems and the planning of urban areas. Here, we gather data about the position in space and time of about 16 000 individuals who uploaded geo-tagged images from locations within the UK to the Flickr photo-sharing website. Inspired by the theory of Lévy flights, which has previously been used to describe the statistical properties of human mobility, we design a machine learning algorithm to infer the probability of finding people in geographical locations and the probability of movement between pairs of locations. Our findings are in general agreement with official figures in the UK and on travel flows between pairs of major cities, suggesting that online data sources may be used to quantify and model large-scale human mobility patterns. PMID:26361545

Discrete Particle Swarm Optimization Routing Protocol for Wireless Sensor Networks with Multiple Mobile Sinks

PubMed Central

Yang, Jin; Liu, Fagui; Cao, Jianneng; Wang, Liangming

2016-01-01

Mobile sinks can achieve load-balancing and energy-consumption balancing across the wireless sensor networks (WSNs). However, the frequent change of the paths between source nodes and the sinks caused by sink mobility introduces significant overhead in terms of energy and packet delays. To enhance network performance of WSNs with mobile sinks (MWSNs), we present an efficient routing strategy, which is formulated as an optimization problem and employs the particle swarm optimization algorithm (PSO) to build the optimal routing paths. However, the conventional PSO is insufficient to solve discrete routing optimization problems. Therefore, a novel greedy discrete particle swarm optimization with memory (GMDPSO) is put forward to address this problem. In the GMDPSO, particle’s position and velocity of traditional PSO are redefined under discrete MWSNs scenario. Particle updating rule is also reconsidered based on the subnetwork topology of MWSNs. Besides, by improving the greedy forwarding routing, a greedy search strategy is designed to drive particles to find a better position quickly. Furthermore, searching history is memorized to accelerate convergence. Simulation results demonstrate that our new protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption. PMID:27428971

An Adaptive Clustering Approach Based on Minimum Travel Route Planning for Wireless Sensor Networks with a Mobile Sink.

PubMed

Tang, Jiqiang; Yang, Wu; Zhu, Lingyun; Wang, Dong; Feng, Xin

2017-04-26

In recent years, Wireless Sensor Networks with a Mobile Sink (WSN-MS) have been an active research topic due to the widespread use of mobile devices. However, how to get the balance between data delivery latency and energy consumption becomes a key issue of WSN-MS. In this paper, we study the clustering approach by jointly considering the Route planning for mobile sink and Clustering Problem (RCP) for static sensor nodes. We solve the RCP problem by using the minimum travel route clustering approach, which applies the minimum travel route of the mobile sink to guide the clustering process. We formulate the RCP problem as an Integer Non-Linear Programming (INLP) problem to shorten the travel route of the mobile sink under three constraints: the communication hops constraint, the travel route constraint and the loop avoidance constraint. We then propose an Imprecise Induction Algorithm (IIA) based on the property that the solution with a small hop count is more feasible than that with a large hop count. The IIA algorithm includes three processes: initializing travel route planning with a Traveling Salesman Problem (TSP) algorithm, transforming the cluster head to a cluster member and transforming the cluster member to a cluster head. Extensive experimental results show that the IIA algorithm could automatically adjust cluster heads according to the maximum hops parameter and plan a shorter travel route for the mobile sink. Compared with the Shortest Path Tree-based Data-Gathering Algorithm (SPT-DGA), the IIA algorithm has the characteristics of shorter route length, smaller cluster head count and faster convergence rate.

Surgical screw segmentation for mobile C-arm CT devices

NASA Astrophysics Data System (ADS)

Görres, Joseph; Brehler, Michael; Franke, Jochen; Wolf, Ivo; Vetter, Sven Y.; Grützner, Paul A.; Meinzer, Hans-Peter; Nabers, Diana

2014-03-01

Calcaneal fractures are commonly treated by open reduction and internal fixation. An anatomical reconstruction of involved joints is mandatory to prevent cartilage damage and premature arthritis. In order to avoid intraarticular screw placements, the use of mobile C-arm CT devices is required. However, for analyzing the screw placement in detail, a time-consuming human-computer interaction is necessary to navigate through 3D images and therefore to view a single screw in detail. Established interaction procedures of repeatedly positioning and rotating sectional planes are inconvenient and impede the intraoperative assessment of the screw positioning. To simplify the interaction with 3D images, we propose an automatic screw segmentation that allows for an immediate selection of relevant sectional planes. Our algorithm consists of three major steps. At first, cylindrical characteristics are determined from local gradient structures with the help of RANSAC. In a second step, a DBScan clustering algorithm is applied to group similar cylinder characteristics. Each detected cluster represents a screw, whose determined location is then refined by a cylinder-to-image registration in a third step. Our evaluation with 309 screws in 50 images shows robust and precise results. The algorithm detected 98% (303) of the screws correctly. Thirteen clusters led to falsely identified screws. The mean distance error for the screw tip was 0.8 +/- 0.8 mm and for the screw head 1.2 +/- 1 mm. The mean orientation error was 1.4 +/- 1.2 degrees.

A Pseudorange Measurement Scheme Based on Snapshot for Base Station Positioning Receivers.

PubMed

Mo, Jun; Deng, Zhongliang; Jia, Buyun; Bian, Xinmei

2017-12-01

Digital multimedia broadcasting signal is promised to be a wireless positioning signal. This paper mainly studies a multimedia broadcasting technology, named China mobile multimedia broadcasting (CMMB), in the context of positioning. Theoretical and practical analysis on the CMMB signal suggests that the existing CMMB signal does not have the meter positioning capability. So, the CMMB system has been modified to achieve meter positioning capability by multiplexing the CMMB signal and pseudo codes in the same frequency band. The time difference of arrival (TDOA) estimation method is used in base station positioning receivers. Due to the influence of a complex fading channel and the limited bandwidth of receivers, the regular tracking method based on pseudo code ranging is difficult to provide continuous and accurate TDOA estimations. A pseudorange measurement scheme based on snapshot is proposed to solve the problem. This algorithm extracts the TDOA estimation from the stored signal fragments, and utilizes the Taylor expansion of the autocorrelation function to improve the TDOA estimation accuracy. Monte Carlo simulations and real data tests show that the proposed algorithm can significantly reduce the TDOA estimation error for base station positioning receivers, and then the modified CMMB system achieves meter positioning accuracy.

SU-F-J-76: Evaluation of the Performance of Different Deformable Image Registration Algorithms in Helical, Axial and Cone-Beam CT Images of a Mobile Phantom

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

Jaskowiak, J; Ahmad, S; Ali, I

Purpose: To investigate quantitatively the performance of different deformable-image-registration algorithms (DIR) with helical (HCT), axial (ACT) and cone-beam CT (CBCT) by evaluating the variations in the CT-numbers and lengths of targets moving with controlled motion-patterns. Methods: Four DIR-algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from the DIRART-software are used to register CT-images of a mobile-phantom. A mobile-phantom is scanned with different imaging techniques that include helical, axial and cone-beam CT. The phantom includes three targets with different lengths that are made from water-equivalent material and inserted in low-density-foam which is moved with adjustable motion-amplitudes and frequencies. Results: Most of themore » DIR-algorithms are able to produce the lengths of the stationary-targets, however, they do not produce the CT-number values in CBCT. The image-artifacts induced by motion are more regular in CBCT imaging where the mobile-target elongation increases linearly with motion-amplitude. In ACT and HCT, the motion-artifacts are irregular where some mobile -targets are elongated or shrunk depending on the motion-phase during imaging. The DIR-algorithms are successful in deforming the images of the mobile-targets to the images of the stationary-targets producing the CT-number values and length of the target for motion-amplitudes < 20 mm. Similarly in ACT, all DIR-algorithms produced the actual CT-number and length of the stationary-targets for motion-amplitudes < 15 mm. As stronger motion-artifacts are induced in HCT and ACT, DIR-algorithms fail to produce CT-values and shape of the stationary-targets and fast-demons-algorithm has worst performance. Conclusion: Most of DIR-algorithms produce the CT-number values and lengths of the stationary-targets in HCT and ACT images that has motion-artifacts induced by small motion-amplitudes. As motion-amplitudes increase, the DIR-algorithms fail to deform mobile-target images to the stationary-images in HCT and ACT. In CBCT, DIR-algorithms are successful in producing length and shape of the stationary-targets, however, they fail to produce the accurate CT-number level.« less

LiteNet: Lightweight Neural Network for Detecting Arrhythmias at Resource-Constrained Mobile Devices.

PubMed

He, Ziyang; Zhang, Xiaoqing; Cao, Yangjie; Liu, Zhi; Zhang, Bo; Wang, Xiaoyan

2018-04-17

By running applications and services closer to the user, edge processing provides many advantages, such as short response time and reduced network traffic. Deep-learning based algorithms provide significantly better performances than traditional algorithms in many fields but demand more resources, such as higher computational power and more memory. Hence, designing deep learning algorithms that are more suitable for resource-constrained mobile devices is vital. In this paper, we build a lightweight neural network, termed LiteNet which uses a deep learning algorithm design to diagnose arrhythmias, as an example to show how we design deep learning schemes for resource-constrained mobile devices. Compare to other deep learning models with an equivalent accuracy, LiteNet has several advantages. It requires less memory, incurs lower computational cost, and is more feasible for deployment on resource-constrained mobile devices. It can be trained faster than other neural network algorithms and requires less communication across different processing units during distributed training. It uses filters of heterogeneous size in a convolutional layer, which contributes to the generation of various feature maps. The algorithm was tested using the MIT-BIH electrocardiogram (ECG) arrhythmia database; the results showed that LiteNet outperforms comparable schemes in diagnosing arrhythmias, and in its feasibility for use at the mobile devices.

LiteNet: Lightweight Neural Network for Detecting Arrhythmias at Resource-Constrained Mobile Devices

PubMed Central

Zhang, Xiaoqing; Cao, Yangjie; Liu, Zhi; Zhang, Bo; Wang, Xiaoyan

2018-01-01

By running applications and services closer to the user, edge processing provides many advantages, such as short response time and reduced network traffic. Deep-learning based algorithms provide significantly better performances than traditional algorithms in many fields but demand more resources, such as higher computational power and more memory. Hence, designing deep learning algorithms that are more suitable for resource-constrained mobile devices is vital. In this paper, we build a lightweight neural network, termed LiteNet which uses a deep learning algorithm design to diagnose arrhythmias, as an example to show how we design deep learning schemes for resource-constrained mobile devices. Compare to other deep learning models with an equivalent accuracy, LiteNet has several advantages. It requires less memory, incurs lower computational cost, and is more feasible for deployment on resource-constrained mobile devices. It can be trained faster than other neural network algorithms and requires less communication across different processing units during distributed training. It uses filters of heterogeneous size in a convolutional layer, which contributes to the generation of various feature maps. The algorithm was tested using the MIT-BIH electrocardiogram (ECG) arrhythmia database; the results showed that LiteNet outperforms comparable schemes in diagnosing arrhythmias, and in its feasibility for use at the mobile devices. PMID:29673171

Using Locata to augment GNSS in a kinematic urban environment

NASA Astrophysics Data System (ADS)

Bonenberg, L. K.; Roberts, G. W.; Hancock, C. M.

2011-12-01

GNSS has become one of the most widespread measurement technologies, widely used in GIS, mobile mapping applications and civil engineering. Utilisation of differential techniques offers cm-level positioning accuracy. Identified drawbacks are the requirement for line of sight to the satellites and accuracy dependent on the geometric distribution of the satellites. Especially the latter is paramount for any surveying or mobile mapping application in the urban environment. The utilisation of additional constellations (GLONASS, GALILEO or COMPASS) only partly mitigates the problem. Locata is an Australian terrestrial positioning technology, based on the pseudolite concept. It's unique in its utilisation of the 2.4GHz ISM band and proprietary TimeLoc procedure, allowing for network synchronisation at the nanosecond level. This paper focuses on the tight integration of GNSS with Locata, in order to address the described drawbacks and to provide cm level positioning in areas currently "difficult" for GNSS - such as urban canyons. This paper describes the intended deployment and utilisation of the integrated system in the typical urban environment where availability of GPScan be limited or even non-existent, depending on the time and location. The verification of the integration methods has been carried out using simulated GPS and Locata data. Also presented is an application simulation in a typical urban canyon environment (Canary Wharf, London, UK) using proprietary software developed at the University of Nottingham. Simulation of the proposed integration algorithms, using a real life scenario, has shown promising results with centimetre-level positioning accuracy on the moving platform. The algorithm provides code ambiguity estimation for both Locata and GPS on-the-fly, without prior knowledge of the position, providing predominantly 3D position on the cm level.

Embedded mobile farm robot for identification of diseased plants

NASA Astrophysics Data System (ADS)

Sadistap, S. S.; Botre, B. A.; Pandit, Harshavardhan; Chandrasekhar; Rao, Adesh

2013-07-01

This paper presents the development of a mobile robot used in farms for identification of diseased plants. It puts forth two of the major aspects of robotics namely automated navigation and image processing. The robot navigates on the basis of the GPS (Global Positioning System) location and data obtained from IR (Infrared) sensors to avoid any obstacles in its path. It uses an image processing algorithm to differentiate between diseased and non-diseased plants. A robotic platform consisting of an ARM9 processor, motor drivers, robot mechanical assembly, camera and infrared sensors has been used. Mini2440 microcontroller has been used wherein Embedded linux OS (Operating System) is implemented.

The Malaria System MicroApp: A New, Mobile Device-Based Tool for Malaria Diagnosis.

PubMed

Oliveira, Allisson Dantas; Prats, Clara; Espasa, Mateu; Zarzuela Serrat, Francesc; Montañola Sales, Cristina; Silgado, Aroa; Codina, Daniel Lopez; Arruda, Mercia Eliane; I Prat, Jordi Gomez; Albuquerque, Jones

2017-04-25

Malaria is a public health problem that affects remote areas worldwide. Climate change has contributed to the problem by allowing for the survival of Anopheles in previously uninhabited areas. As such, several groups have made developing news systems for the automated diagnosis of malaria a priority. The objective of this study was to develop a new, automated, mobile device-based diagnostic system for malaria. The system uses Giemsa-stained peripheral blood samples combined with light microscopy to identify the Plasmodium falciparum species in the ring stage of development. The system uses image processing and artificial intelligence techniques as well as a known face detection algorithm to identify Plasmodium parasites. The algorithm is based on integral image and haar-like features concepts, and makes use of weak classifiers with adaptive boosting learning. The search scope of the learning algorithm is reduced in the preprocessing step by removing the background around blood cells. As a proof of concept experiment, the tool was used on 555 malaria-positive and 777 malaria-negative previously-made slides. The accuracy of the system was, on average, 91%, meaning that for every 100 parasite-infected samples, 91 were identified correctly. Accessibility barriers of low-resource countries can be addressed with low-cost diagnostic tools. Our system, developed for mobile devices (mobile phones and tablets), addresses this by enabling access to health centers in remote communities, and importantly, not depending on extensive malaria expertise or expensive diagnostic detection equipment. ©Allisson Dantas Oliveira, Clara Prats, Mateu Espasa, Francesc Zarzuela Serrat, Cristina Montañola Sales, Aroa Silgado, Daniel Lopez Codina, Mercia Eliane Arruda, Jordi Gomez i Prat, Jones Albuquerque. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 25.04.2017.

Enhanced TDMA Based Anti-Collision Algorithm with a Dynamic Frame Size Adjustment Strategy for Mobile RFID Readers

PubMed Central

Shin, Kwang Cheol; Park, Seung Bo; Jo, Geun Sik

2009-01-01

In the fields of production, manufacturing and supply chain management, Radio Frequency Identification (RFID) is regarded as one of the most important technologies. Nowadays, Mobile RFID, which is often installed in carts or forklift trucks, is increasingly being applied to the search for and checkout of items in warehouses, supermarkets, libraries and other industrial fields. In using Mobile RFID, since the readers are continuously moving, they can interfere with each other when they attempt to read the tags. In this study, we suggest a Time Division Multiple Access (TDMA) based anti-collision algorithm for Mobile RFID readers. Our algorithm automatically adjusts the frame size of each reader without using manual parameters by adopting the dynamic frame size adjustment strategy when collisions occur at a reader. Through experiments on a simulated environment for Mobile RFID readers, we show that the proposed method improves the number of successful transmissions by about 228% on average, compared with Colorwave, a representative TDMA based anti-collision algorithm. PMID:22399942

Enhanced TDMA Based Anti-Collision Algorithm with a Dynamic Frame Size Adjustment Strategy for Mobile RFID Readers.

PubMed

Shin, Kwang Cheol; Park, Seung Bo; Jo, Geun Sik

2009-01-01

In the fields of production, manufacturing and supply chain management, Radio Frequency Identification (RFID) is regarded as one of the most important technologies. Nowadays, Mobile RFID, which is often installed in carts or forklift trucks, is increasingly being applied to the search for and checkout of items in warehouses, supermarkets, libraries and other industrial fields. In using Mobile RFID, since the readers are continuously moving, they can interfere with each other when they attempt to read the tags. In this study, we suggest a Time Division Multiple Access (TDMA) based anti-collision algorithm for Mobile RFID readers. Our algorithm automatically adjusts the frame size of each reader without using manual parameters by adopting the dynamic frame size adjustment strategy when collisions occur at a reader. Through experiments on a simulated environment for Mobile RFID readers, we show that the proposed method improves the number of successful transmissions by about 228% on average, compared with Colorwave, a representative TDMA based anti-collision algorithm.

Two modular neuro-fuzzy system for mobile robot navigation

NASA Astrophysics Data System (ADS)

Bobyr, M. V.; Titov, V. S.; Kulabukhov, S. A.; Syryamkin, V. I.

2018-05-01

The article considers the fuzzy model for navigation of a mobile robot operating in two modes. In the first mode the mobile robot moves along a line. In the second mode, the mobile robot looks for an target in unknown space. Structural and schematic circuit of four-wheels mobile robot are presented in the article. The article describes the movement of a mobile robot based on two modular neuro-fuzzy system. The algorithm of neuro-fuzzy inference used in two modular control system for movement of a mobile robot is given in the article. The experimental model of the mobile robot and the simulation of the neuro-fuzzy algorithm used for its control are presented in the article.

An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks

PubMed Central

Penumalli, Chakradhar; Palanichamy, Yogesh

2015-01-01

A new energy efficient optimal Connected Dominating Set (CDS) algorithm with activity scheduling for mobile ad hoc networks (MANETs) is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node's remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results. PMID:26221627

A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks

PubMed Central

González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

2017-01-01

Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage. PMID:28075364

A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks.

PubMed

González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

2017-01-09

Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage.

An Adaptive Clustering Approach Based on Minimum Travel Route Planning for Wireless Sensor Networks with a Mobile Sink

PubMed Central

Tang, Jiqiang; Yang, Wu; Zhu, Lingyun; Wang, Dong; Feng, Xin

2017-01-01

In recent years, Wireless Sensor Networks with a Mobile Sink (WSN-MS) have been an active research topic due to the widespread use of mobile devices. However, how to get the balance between data delivery latency and energy consumption becomes a key issue of WSN-MS. In this paper, we study the clustering approach by jointly considering the Route planning for mobile sink and Clustering Problem (RCP) for static sensor nodes. We solve the RCP problem by using the minimum travel route clustering approach, which applies the minimum travel route of the mobile sink to guide the clustering process. We formulate the RCP problem as an Integer Non-Linear Programming (INLP) problem to shorten the travel route of the mobile sink under three constraints: the communication hops constraint, the travel route constraint and the loop avoidance constraint. We then propose an Imprecise Induction Algorithm (IIA) based on the property that the solution with a small hop count is more feasible than that with a large hop count. The IIA algorithm includes three processes: initializing travel route planning with a Traveling Salesman Problem (TSP) algorithm, transforming the cluster head to a cluster member and transforming the cluster member to a cluster head. Extensive experimental results show that the IIA algorithm could automatically adjust cluster heads according to the maximum hops parameter and plan a shorter travel route for the mobile sink. Compared with the Shortest Path Tree-based Data-Gathering Algorithm (SPT-DGA), the IIA algorithm has the characteristics of shorter route length, smaller cluster head count and faster convergence rate. PMID:28445434

Mobile Sensing in Environmental Health and Neighborhood Research.

PubMed

Chaix, Basile

2018-04-01

Public health research has witnessed a rapid development in the use of location, environmental, behavioral, and biophysical sensors that provide high-resolution objective time-stamped data. This burgeoning field is stimulated by the development of novel multisensor devices that collect data for an increasing number of channels and algorithms that predict relevant dimensions from one or several data channels. Global positioning system (GPS) tracking, which enables geographic momentary assessment, permits researchers to assess multiplace personal exposure areas and the algorithm-based identification of trips and places visited, eventually validated and complemented using a GPS-based mobility survey. These methods open a new space-time perspective that considers the full dynamic of residential and nonresidential momentary exposures; spatially and temporally disaggregates the behavioral and health outcomes, thus replacing them in their immediate environmental context; investigates complex time sequences; explores the interplay among individual, environmental, and situational predictors; performs life-segment analyses considering infraindividual statistical units using case-crossover models; and derives recommendations for just-in-time interventions.

Layout Study and Application of Mobile App Recommendation Approach Based On Spark Streaming Framework

NASA Astrophysics Data System (ADS)

Wang, H. T.; Chen, T. T.; Yan, C.; Pan, H.

2018-05-01

For App recommended areas of mobile phone software, made while using conduct App application recommended combined weighted Slope One algorithm collaborative filtering algorithm items based on further improvement of the traditional collaborative filtering algorithm in cold start, data matrix sparseness and other issues, will recommend Spark stasis parallel algorithm platform, the introduction of real-time streaming streaming real-time computing framework to improve real-time software applications recommended.

SU-E-J-252: A Motion Algorithm to Extract Physical and Motion Parameters of a Mobile Target in Cone-Beam Computed Tomographic Imaging Retrospective to Image Reconstruction

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

Ali, I; Ahmad, S; Alsbou, N

Purpose: A motion algorithm was developed to extract actual length, CT-numbers and motion amplitude of a mobile target imaged with cone-beam-CT (CBCT) retrospective to image-reconstruction. Methods: The motion model considered a mobile target moving with a sinusoidal motion and employed three measurable parameters: apparent length, CT number level and gradient of a mobile target obtained from CBCT images to extract information about the actual length and CT number value of the stationary target and motion amplitude. The algorithm was verified experimentally with a mobile phantom setup that has three targets with different sizes manufactured from homogenous tissue-equivalent gel material embeddedmore » into a thorax phantom. The phantom moved sinusoidal in one-direction using eight amplitudes (0–20mm) and a frequency of 15-cycles-per-minute. The model required imaging parameters such as slice thickness, imaging time. Results: This motion algorithm extracted three unknown parameters: length of the target, CT-number-level, motion amplitude for a mobile target retrospective to CBCT image reconstruction. The algorithm relates three unknown parameters to measurable apparent length, CT-number-level and gradient for well-defined mobile targets obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on actual length of the target and motion amplitude. The cumulative CT-number for a mobile target was dependent on CT-number-level of the stationary target and motion amplitude. The gradient of the CT-distribution of mobile target is dependent on the stationary CT-number-level, actual target length along the direction of motion, and motion amplitude. Motion frequency and phase did not affect the elongation and CT-number distributions of mobile targets when imaging time included several motion cycles. Conclusion: The motion algorithm developed in this study has potential applications in diagnostic CT imaging and radiotherapy to extract actual length, size and CT-numbers distorted by motion in CBCT imaging. The model provides further information about motion of the target.« less

An Artificial Neural Network Embedded Position and Orientation Determination Algorithm for Low Cost MEMS INS/GPS Integrated Sensors

PubMed Central

Chiang, Kai-Wei; Chang, Hsiu-Wen; Li, Chia-Yuan; Huang, Yun-Wen

2009-01-01

Digital mobile mapping, which integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. Direct geo-referencing is the determination of the time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using Global Positioning System (GPS) and Inertial Navigation System (INS) using an Inertial Measurement Unit (IMU). They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. The Kalman Filter (KF) is considered as the optimal estimation tool for real-time INS/GPS integrated kinematic position and orientation determination. An intelligent hybrid scheme consisting of an Artificial Neural Network (ANN) and KF has been proposed to overcome the limitations of KF and to improve the performance of the INS/GPS integrated system in previous studies. However, the accuracy requirements of general mobile mapping applications can’t be achieved easily, even by the use of the ANN-KF scheme. Therefore, this study proposes an intelligent position and orientation determination scheme that embeds ANN with conventional Rauch-Tung-Striebel (RTS) smoother to improve the overall accuracy of a MEMS INS/GPS integrated system in post-mission mode. By combining the Micro Electro Mechanical Systems (MEMS) INS/GPS integrated system and the intelligent ANN-RTS smoother scheme proposed in this study, a cheaper but still reasonably accurate position and orientation determination scheme can be anticipated. PMID:22574034

Mobile agent location in distributed environments

NASA Astrophysics Data System (ADS)

Fountoukis, S. G.; Argyropoulos, I. P.

2012-12-01

An agent is a small program acting on behalf of a user or an application which plays the role of a user. Artificial intelligence can be encapsulated in agents so that they can be capable of both behaving autonomously and showing an elementary decision ability regarding movement and some specific actions. Therefore they are often called autonomous mobile agents. In a distributed system, they can move themselves from one processing node to another through the interconnecting network infrastructure. Their purpose is to collect useful information and to carry it back to their user. Also, agents are used to start, monitor and stop processes running on the individual interconnected processing nodes of computer cluster systems. An agent has a unique id to discriminate itself from other agents and a current position. The position can be expressed as the address of the processing node which currently hosts the agent. Very often, it is necessary for a user, a processing node or another agent to know the current position of an agent in a distributed system. Several procedures and algorithms have been proposed for the purpose of position location of mobile agents. The most basic of all employs a fixed computing node, which acts as agent position repository, receiving messages from all the moving agents and keeping records of their current positions. The fixed node, responds to position queries and informs users, other nodes and other agents about the position of an agent. Herein, a model is proposed that considers pairs and triples of agents instead of single ones. A location method, which is investigated in this paper, attempts to exploit this model.

A Localization Method for Underwater Wireless Sensor Networks Based on Mobility Prediction and Particle Swarm Optimization Algorithms

PubMed Central

Zhang, Ying; Liang, Jixing; Jiang, Shengming; Chen, Wei

2016-01-01

Due to their special environment, Underwater Wireless Sensor Networks (UWSNs) are usually deployed over a large sea area and the nodes are usually floating. This results in a lower beacon node distribution density, a longer time for localization, and more energy consumption. Currently most of the localization algorithms in this field do not pay enough consideration on the mobility of the nodes. In this paper, by analyzing the mobility patterns of water near the seashore, a localization method for UWSNs based on a Mobility Prediction and a Particle Swarm Optimization algorithm (MP-PSO) is proposed. In this method, the range-based PSO algorithm is used to locate the beacon nodes, and their velocities can be calculated. The velocity of an unknown node is calculated by using the spatial correlation of underwater object’s mobility, and then their locations can be predicted. The range-based PSO algorithm may cause considerable energy consumption and its computation complexity is a little bit high, nevertheless the number of beacon nodes is relatively smaller, so the calculation for the large number of unknown nodes is succinct, and this method can obviously decrease the energy consumption and time cost of localizing these mobile nodes. The simulation results indicate that this method has higher localization accuracy and better localization coverage rate compared with some other widely used localization methods in this field. PMID:26861348

Real-time optical flow estimation on a GPU for a skied-steered mobile robot

NASA Astrophysics Data System (ADS)

Kniaz, V. V.

2016-04-01

Accurate egomotion estimation is required for mobile robot navigation. Often the egomotion is estimated using optical flow algorithms. For an accurate estimation of optical flow most of modern algorithms require high memory resources and processor speed. However simple single-board computers that control the motion of the robot usually do not provide such resources. On the other hand, most of modern single-board computers are equipped with an embedded GPU that could be used in parallel with a CPU to improve the performance of the optical flow estimation algorithm. This paper presents a new Z-flow algorithm for efficient computation of an optical flow using an embedded GPU. The algorithm is based on the phase correlation optical flow estimation and provide a real-time performance on a low cost embedded GPU. The layered optical flow model is used. Layer segmentation is performed using graph-cut algorithm with a time derivative based energy function. Such approach makes the algorithm both fast and robust in low light and low texture conditions. The algorithm implementation for a Raspberry Pi Model B computer is discussed. For evaluation of the algorithm the computer was mounted on a Hercules mobile skied-steered robot equipped with a monocular camera. The evaluation was performed using a hardware-in-the-loop simulation and experiments with Hercules mobile robot. Also the algorithm was evaluated using KITTY Optical Flow 2015 dataset. The resulting endpoint error of the optical flow calculated with the developed algorithm was low enough for navigation of the robot along the desired trajectory.

Building simplification algorithms based on user cognition in mobile environment

NASA Astrophysics Data System (ADS)

Shen, Jie; Shi, Junfei; Wang, Meizhen; Wu, Chenyan

2008-10-01

With the development of LBS, mobile map should adaptively satisfy the cognitive requirement of user. User cognition in mobile environment is much more objective oriented and also seem to be a heavier burden than the user in static environment. The holistic idea and methods of map generalization can not fully suitable for the mobile map. This paper took the building simplification in habitation generalization as example, analyzed the characteristic of user cognition in mobile environment and the basic rules of building simplification, collected and studied the state-of-the-art of algorithms of building simplification in the static and mobile environment, put forward the idea of hierarchical building simplification based on user cognition. This paper took Hunan road business district of Nanjing as test area and took the building data with shapfile format of ESRI as test data and realized the simplification algorithm. The method took user as center, calculated the distance between user and the building which will be simplified and took the distance as the basis for choosing different simplification algorithm for different spaces. This contribution aimed to hierarchically present the building in different level of detail by real-time simplification.

Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks.

PubMed

La, Hung Manh; Sheng, Weihua

2013-04-01

In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

Assisted Perception, Planning and Control for Remote Mobility and Dexterous Manipulation

DTIC Science & Technology

2017-04-01

on unmanned aerial vehicles (UAVs). The underlying algorithm is based on an Extended Kalman Filter (EKF) that simultaneously estimates robot state...and sensor biases. The filter developed provided a probabilistic fusion of sensor data from many modalities to produce a single consistent position...estimation for a walking humanoid. Given a prior map using a Gaussian particle filter , the LIDAR based system is able to provide a drift-free

SU-F-J-77: Variations in the Displacement Vector Fields Calculated by Different Deformable Image Registration Algorithms Used in Helical, Axial and Cone-Beam CT Images of a Mobile

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

Ali, I; Jaskowiak, J; Ahmad, S

Purpose: To investigate quantitatively the displacement-vector-fields (DVF) obtained from different deformable image registration algorithms (DIR) in helical (HCT), axial (ACT) and cone-beam CT (CBCT) to register CT images of a mobile phantom and its correlation with motion amplitudes and frequencies. Methods: HCT, ACT and CBCT are used to image a mobile phantom which includes three targets with different sizes that are manufactured from water-equivalent material and embedded in low density foam. The phantom is moved with controlled motion patterns where a range of motion amplitudes (0–40mm) and frequencies (0.125–0.5Hz) are used. The CT images obtained from scanning of the mobilemore » phantom are registered with the stationary CT-images using four deformable image registration algorithms including demons, fast-demons, Horn-Schunk and Locas-Kanade from DIRART software. Results: The DVF calculated by the different algorithms correlate well with the motion amplitudes that are applied on the mobile phantom where maximal DVF increase linearly with the motion amplitudes of the mobile phantom in CBCT. Similarly in HCT, DVF increase linearly with motion amplitude, however, its correlation is weaker than CBCT. In ACT, the DVF’s do not correlate well with the motion amplitudes where motion induces strong image artifacts and DIR algorithms are not able to deform the ACT image of the mobile targets to the stationary targets. Three DIR-algorithms produce comparable values and patterns of the DVF for certain CT imaging modality. However, DVF from fast-demons deviated strongly from other algorithms at large motion amplitudes. Conclusion: In CBCT and HCT, the DVF correlate well with the motion amplitude of the mobile phantom. However, in ACT, DVF do not correlate with motion amplitudes. Correlations of DVF with motion amplitude as in CBCT and HCT imaging techniques can provide information about unknown motion parameters of the mobile organs in real patients as demonstrated in this phantom visibility study.« less

A Network Selection Algorithm Considering Power Consumption in Hybrid Wireless Networks

NASA Astrophysics Data System (ADS)

Joe, Inwhee; Kim, Won-Tae; Hong, Seokjoon

In this paper, we propose a novel network selection algorithm considering power consumption in hybrid wireless networks for vertical handover. CDMA, WiBro, WLAN networks are candidate networks for this selection algorithm. This algorithm is composed of the power consumption prediction algorithm and the final network selection algorithm. The power consumption prediction algorithm estimates the expected lifetime of the mobile station based on the current battery level, traffic class and power consumption for each network interface card of the mobile station. If the expected lifetime of the mobile station in a certain network is not long enough compared the handover delay, this particular network will be removed from the candidate network list, thereby preventing unnecessary handovers in the preprocessing procedure. On the other hand, the final network selection algorithm consists of AHP (Analytic Hierarchical Process) and GRA (Grey Relational Analysis). The global factors of the network selection structure are QoS, cost and lifetime. If user preference is lifetime, our selection algorithm selects the network that offers longest service duration due to low power consumption. Also, we conduct some simulations using the OPNET simulation tool. The simulation results show that the proposed algorithm provides longer lifetime in the hybrid wireless network environment.

Analyzing the multiple-target-multiple-agent scenario using optimal assignment algorithms

NASA Astrophysics Data System (ADS)

Kwok, Kwan S.; Driessen, Brian J.; Phillips, Cynthia A.; Tovey, Craig A.

1997-09-01

This work considers the problem of maximum utilization of a set of mobile robots with limited sensor-range capabilities and limited travel distances. The robots are initially in random positions. A set of robots properly guards or covers a region if every point within the region is within the effective sensor range of at least one vehicle. We wish to move the vehicles into surveillance positions so as to guard or cover a region, while minimizing the maximum distance traveled by any vehicle. This problem can be formulated as an assignment problem, in which we must optimally decide which robot to assign to which slot of a desired matrix of grid points. The cost function is the maximum distance traveled by any robot. Assignment problems can be solved very efficiently. Solution times for one hundred robots took only seconds on a silicon graphics crimson workstation. The initial positions of all the robots can be sampled by a central base station and their newly assigned positions communicated back to the robots. Alternatively, the robots can establish their own coordinate system with the origin fixed at one of the robots and orientation determined by the compass bearing of another robot relative to this robot. This paper presents example solutions to the multiple-target-multiple-agent scenario using a matching algorithm. Two separate cases with one hundred agents in each were analyzed using this method. We have found these mobile robot problems to be a very interesting application of network optimization methods, and we expect this to be a fruitful area for future research.

Sliding GAIT Algorithm for the All-Terrain Hex-Limbed Extra-Terrestrial Explorer (ATHLETE)

NASA Technical Reports Server (NTRS)

Townsend, Julie; Biesiadecki, Jeffrey

2012-01-01

The design of a surface robotic system typically involves a trade between the traverse speed of a wheeled rover and the terrain-negotiating capabilities of a multi-legged walker. The ATHLETE mobility system, with both articulated limbs and wheels, is uniquely capable of both driving and walking, and has the flexibility to employ additional hybrid mobility modes. This paper introduces the Sliding Gait, an intermediate mobility algorithm faster than walking with better terrain-handling capabilities than wheeled mobility.

Speech Enhancement of Mobile Devices Based on the Integration of a Dual Microphone Array and a Background Noise Elimination Algorithm.

PubMed

Chen, Yung-Yue

2018-05-08

Mobile devices are often used in our daily lives for the purposes of speech and communication. The speech quality of mobile devices is always degraded due to the environmental noises surrounding mobile device users. Regretfully, an effective background noise reduction solution cannot easily be developed for this speech enhancement problem. Due to these depicted reasons, a methodology is systematically proposed to eliminate the effects of background noises for the speech communication of mobile devices. This methodology integrates a dual microphone array with a background noise elimination algorithm. The proposed background noise elimination algorithm includes a whitening process, a speech modelling method and an H ₂ estimator. Due to the adoption of the dual microphone array, a low-cost design can be obtained for the speech enhancement of mobile devices. Practical tests have proven that this proposed method is immune to random background noises, and noiseless speech can be obtained after executing this denoise process.

Object Transportation by Two Mobile Robots with Hand Carts

PubMed Central

Hara, Tatsunori

2014-01-01

This paper proposes a methodology by which two small mobile robots can grasp, lift, and transport large objects using hand carts. The specific problems involve generating robot actions and determining the hand cart positions to achieve the stable loading of objects onto the carts. These problems are solved using nonlinear optimization, and we propose an algorithm for generating robot actions. The proposed method was verified through simulations and experiments using actual devices in a real environment. The proposed method could reduce the number of robots required to transport large objects with 50–60%. In addition, we demonstrated the efficacy of this task in real environments where errors occur in robot sensing and movement. PMID:27433499

Object Transportation by Two Mobile Robots with Hand Carts.

PubMed

Sakuyama, Takuya; Figueroa Heredia, Jorge David; Ogata, Taiki; Hara, Tatsunori; Ota, Jun

2014-01-01

This paper proposes a methodology by which two small mobile robots can grasp, lift, and transport large objects using hand carts. The specific problems involve generating robot actions and determining the hand cart positions to achieve the stable loading of objects onto the carts. These problems are solved using nonlinear optimization, and we propose an algorithm for generating robot actions. The proposed method was verified through simulations and experiments using actual devices in a real environment. The proposed method could reduce the number of robots required to transport large objects with 50-60%. In addition, we demonstrated the efficacy of this task in real environments where errors occur in robot sensing and movement.

Mobility Models for Systems Evaluation

NASA Astrophysics Data System (ADS)

Musolesi, Mirco; Mascolo, Cecilia

Mobility models are used to simulate and evaluate the performance of mobile wireless systems and the algorithms and protocols at the basis of them. The definition of realistic mobility models is one of the most critical and, at the same time, difficult aspects of the simulation of applications and systems designed for mobile environments. There are essentially two possible types of mobility patterns that can be used to evaluate mobile network protocols and algorithms by means of simulations: traces and synthetic models [130]. Traces are obtained by means of measurements of deployed systems and usually consist of logs of connectivity or location information, whereas synthetic models are mathematical models, such as sets of equations, which try to capture the movement of the devices.

Vision-Aided Context-Aware Framework for Personal Navigation Services

NASA Astrophysics Data System (ADS)

Saeedi, S.; Moussa, A.; El-Sheimy, N., , Dr.

2012-07-01

The ubiquity of mobile devices (such as smartphones and tablet-PCs) has encouraged the use of location-based services (LBS) that are relevant to the current location and context of a mobile user. The main challenge of LBS is to find a pervasive and accurate personal navigation system (PNS) in different situations of a mobile user. In this paper, we propose a method of personal navigation for pedestrians that allows a user to freely move in outdoor environments. This system aims at detection of the context information which is useful for improving personal navigation. The context information for a PNS consists of user activity modes (e.g. walking, stationary, driving, and etc.) and the mobile device orientation and placement with respect to the user. After detecting the context information, a low-cost integrated positioning algorithm has been employed to estimate pedestrian navigation parameters. The method is based on the integration of the relative user's motion (changes of velocity and heading angle) estimation based on the video image matching and absolute position information provided by GPS. A Kalman filter (KF) has been used to improve the navigation solution when the user is walking and the phone is in his/her hand. The Experimental results demonstrate the capabilities of this method for outdoor personal navigation systems.

The Performance Analysis of AN Indoor Mobile Mapping System with Rgb-D Sensor

NASA Astrophysics Data System (ADS)

Tsai, G. J.; Chiang, K. W.; Chu, C. H.; Chen, Y. L.; El-Sheimy, N.; Habib, A.

2015-08-01

Over the years, Mobile Mapping Systems (MMSs) have been widely applied to urban mapping, path management and monitoring and cyber city, etc. The key concept of mobile mapping is based on positioning technology and photogrammetry. In order to achieve the integration, multi-sensor integrated mapping technology has clearly established. In recent years, the robotic technology has been rapidly developed. The other mapping technology that is on the basis of low-cost sensor has generally used in robotic system, it is known as the Simultaneous Localization and Mapping (SLAM). The objective of this study is developed a prototype of indoor MMS for mobile mapping applications, especially to reduce the costs and enhance the efficiency of data collection and validation of direct georeferenced (DG) performance. The proposed indoor MMS is composed of a tactical grade Inertial Measurement Unit (IMU), the Kinect RGB-D sensor and light detection, ranging (LIDAR) and robot. In summary, this paper designs the payload for indoor MMS to generate the floor plan. In first session, it concentrates on comparing the different positioning algorithms in the indoor environment. Next, the indoor plans are generated by two sensors, Kinect RGB-D sensor LIDAR on robot. Moreover, the generated floor plan will compare with the known plan for both validation and verification.

Quantifying Traversability of Terrain for a Mobile Robot

NASA Technical Reports Server (NTRS)

Howard, Ayanna; Seraji, Homayoun; Werger, Barry

2005-01-01

A document presents an updated discussion on a method of autonomous navigation for a robotic vehicle navigating across rough terrain. The method involves, among other things, the use of a measure of traversability, denoted the fuzzy traversability index, which embodies the information about the slope and roughness of terrain obtained from analysis of images acquired by cameras mounted on the robot. The improvements presented in the report focus on the use of the fuzzy traversability index to generate a traversability map and a grid map for planning the safest path for the robot. Once grid traversability values have been computed, they are utilized for rejecting unsafe path segments and for computing a traversalcost function for ranking candidate paths, selected by a search algorithm, from a specified initial position to a specified final position. The output of the algorithm is a set of waypoints designating a path having a minimal-traversal cost.

Path optimisation of a mobile robot using an artificial neural network controller

NASA Astrophysics Data System (ADS)

Singh, M. K.; Parhi, D. R.

2011-01-01

This article proposed a novel approach for design of an intelligent controller for an autonomous mobile robot using a multilayer feed forward neural network, which enables the robot to navigate in a real world dynamic environment. The inputs to the proposed neural controller consist of left, right and front obstacle distance with respect to its position and target angle. The output of the neural network is steering angle. A four layer neural network has been designed to solve the path and time optimisation problem of mobile robots, which deals with the cognitive tasks such as learning, adaptation, generalisation and optimisation. A back propagation algorithm is used to train the network. This article also analyses the kinematic design of mobile robots for dynamic movements. The simulation results are compared with experimental results, which are satisfactory and show very good agreement. The training of the neural nets and the control performance analysis has been done in a real experimental setup.

Optimal Location through Distributed Algorithm to Avoid Energy Hole in Mobile Sink WSNs

PubMed Central

Qing-hua, Li; Wei-hua, Gui; Zhi-gang, Chen

2014-01-01

In multihop data collection sensor network, nodes near the sink need to relay on remote data and, thus, have much faster energy dissipation rate and suffer from premature death. This phenomenon causes energy hole near the sink, seriously damaging the network performance. In this paper, we first compute energy consumption of each node when sink is set at any point in the network through theoretical analysis; then we propose an online distributed algorithm, which can adjust sink position based on the actual energy consumption of each node adaptively to get the actual maximum lifetime. Theoretical analysis and experimental results show that the proposed algorithms significantly improve the lifetime of wireless sensor network. It lowers the network residual energy by more than 30% when it is dead. Moreover, the cost for moving the sink is relatively smaller. PMID:24895668

Symmetric caging formation for convex polygonal object transportation by multiple mobile robots based on fuzzy sliding mode control.

PubMed

Dai, Yanyan; Kim, YoonGu; Wee, SungGil; Lee, DongHa; Lee, SukGyu

2016-01-01

In this paper, the problem of object caging and transporting is considered for multiple mobile robots. With the consideration of minimizing the number of robots and decreasing the rotation of the object, the proper points are calculated and assigned to the multiple mobile robots to allow them to form a symmetric caging formation. The caging formation guarantees that all of the Euclidean distances between any two adjacent robots are smaller than the minimal width of the polygonal object so that the object cannot escape. In order to avoid collision among robots, the parameter of the robots radius is utilized to design the caging formation, and the A⁎ algorithm is used so that mobile robots can move to the proper points. In order to avoid obstacles, the robots and the object are regarded as a rigid body to apply artificial potential field method. The fuzzy sliding mode control method is applied for tracking control of the nonholonomic mobile robots. Finally, the simulation and experimental results show that multiple mobile robots are able to cage and transport the polygonal object to the goal position, avoiding obstacles. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Numerical evaluation of mobile robot navigation in static indoor environment via EGAOR Iteration

NASA Astrophysics Data System (ADS)

Dahalan, A. A.; Saudi, A.; Sulaiman, J.; Din, W. R. W.

2017-09-01

One of the key issues in mobile robot navigation is the ability for the robot to move from an arbitrary start location to a specified goal location without colliding with any obstacles while traveling, also known as mobile robot path planning problem. In this paper, however, we examined the performance of a robust searching algorithm that relies on the use of harmonic potentials of the environment to generate smooth and safe path for mobile robot navigation in a static known indoor environment. The harmonic potentials will be discretized by using Laplacian’s operator to form a system of algebraic approximation equations. This algebraic linear system will be computed via 4-Point Explicit Group Accelerated Over-Relaxation (4-EGAOR) iterative method for rapid computation. The performance of the proposed algorithm will then be compared and analyzed against the existing algorithms in terms of number of iterations and execution time. The result shows that the proposed algorithm performed better than the existing methods.

Ad Hoc Access Gateway Selection Algorithm

NASA Astrophysics Data System (ADS)

Jie, Liu

With the continuous development of mobile communication technology, Ad Hoc access network has become a hot research, Ad Hoc access network nodes can be used to expand capacity of multi-hop communication range of mobile communication system, even business adjacent to the community, improve edge data rates. For mobile nodes in Ad Hoc network to internet, internet communications in the peer nodes must be achieved through the gateway. Therefore, the key Ad Hoc Access Networks will focus on the discovery gateway, as well as gateway selection in the case of multi-gateway and handover problems between different gateways. This paper considers the mobile node and the gateway, based on the average number of hops from an average access time and the stability of routes, improved gateway selection algorithm were proposed. An improved gateway selection algorithm, which mainly considers the algorithm can improve the access time of Ad Hoc nodes and the continuity of communication between the gateways, were proposed. This can improve the quality of communication across the network.

Cluster Based Location-Aided Routing Protocol for Large Scale Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Wang, Yi; Dong, Liang; Liang, Taotao; Yang, Xinyu; Zhang, Deyun

Routing algorithms with low overhead, stable link and independence of the total number of nodes in the network are essential for the design and operation of the large-scale wireless mobile ad hoc networks (MANET). In this paper, we develop and analyze the Cluster Based Location-Aided Routing Protocol for MANET (C-LAR), a scalable and effective routing algorithm for MANET. C-LAR runs on top of an adaptive cluster cover of the MANET, which can be created and maintained using, for instance, the weight-based distributed algorithm. This algorithm takes into consideration the node degree, mobility, relative distance, battery power and link stability of mobile nodes. The hierarchical structure stabilizes the end-to-end communication paths and improves the networks' scalability such that the routing overhead does not become tremendous in large scale MANET. The clusterheads form a connected virtual backbone in the network, determine the network's topology and stability, and provide an efficient approach to minimizing the flooding traffic during route discovery and speeding up this process as well. Furthermore, it is fascinating and important to investigate how to control the total number of nodes participating in a routing establishment process so as to improve the network layer performance of MANET. C-LAR is to use geographical location information provided by Global Position System to assist routing. The location information of destination node is used to predict a smaller rectangle, isosceles triangle, or circle request zone, which is selected according to the relative location of the source and the destination, that covers the estimated region in which the destination may be located. Thus, instead of searching the route in the entire network blindly, C-LAR confines the route searching space into a much smaller estimated range. Simulation results have shown that C-LAR outperforms other protocols significantly in route set up time, routing overhead, mean delay and packet collision, and simultaneously maintains low average end-to-end delay, high success delivery ratio, low control overhead, as well as low route discovery frequency.

Real-time ECG monitoring and arrhythmia detection using Android-based mobile devices.

PubMed

Gradl, Stefan; Kugler, Patrick; Lohmuller, Clemens; Eskofier, Bjoern

2012-01-01

We developed an application for Android™-based mobile devices that allows real-time electrocardiogram (ECG) monitoring and automated arrhythmia detection by analyzing ECG parameters. ECG data provided by pre-recorded files or acquired live by accessing a Shimmer™ sensor node via Bluetooth™ can be processed and evaluated. The application is based on the Pan-Tompkins algorithm for QRS-detection and contains further algorithm blocks to detect abnormal heartbeats. The algorithm was validated using the MIT-BIH Arrhythmia and MIT-BIH Supraventricular Arrhythmia databases. More than 99% of all QRS complexes were detected correctly by the algorithm. Overall sensitivity for abnormal beat detection was 89.5% with a specificity of 80.6%. The application is available for download and may be used for real-time ECG-monitoring on mobile devices.

Enhanced Handover Decision Algorithm in Heterogeneous Wireless Network

PubMed Central

Abdullah, Radhwan Mohamed; Zukarnain, Zuriati Ahmad

2017-01-01

Transferring a huge amount of data between different network locations over the network links depends on the network’s traffic capacity and data rate. Traditionally, a mobile device may be moved to achieve the operations of vertical handover, considering only one criterion, that is the Received Signal Strength (RSS). The use of a single criterion may cause service interruption, an unbalanced network load and an inefficient vertical handover. In this paper, we propose an enhanced vertical handover decision algorithm based on multiple criteria in the heterogeneous wireless network. The algorithm consists of three technology interfaces: Long-Term Evolution (LTE), Worldwide interoperability for Microwave Access (WiMAX) and Wireless Local Area Network (WLAN). It also employs three types of vertical handover decision algorithms: equal priority, mobile priority and network priority. The simulation results illustrate that the three types of decision algorithms outperform the traditional network decision algorithm in terms of handover number probability and the handover failure probability. In addition, it is noticed that the network priority handover decision algorithm produces better results compared to the equal priority and the mobile priority handover decision algorithm. Finally, the simulation results are validated by the analytical model. PMID:28708067

On the Use of a Low-Cost Thermal Sensor to Improve Kinect People Detection in a Mobile Robot

PubMed Central

Susperregi, Loreto; Sierra, Basilio; Castrillón, Modesto; Lorenzo, Javier; Martínez-Otzeta, Jose María; Lazkano, Elena

2013-01-01

Detecting people is a key capability for robots that operate in populated environments. In this paper, we have adopted a hierarchical approach that combines classifiers created using supervised learning in order to identify whether a person is in the view-scope of the robot or not. Our approach makes use of vision, depth and thermal sensors mounted on top of a mobile platform. The set of sensors is set up combining the rich data source offered by a Kinect sensor, which provides vision and depth at low cost, and a thermopile array sensor. Experimental results carried out with a mobile platform in a manufacturing shop floor and in a science museum have shown that the false positive rate achieved using any single cue is drastically reduced. The performance of our algorithm improves other well-known approaches, such as C4 and histogram of oriented gradients (HOG). PMID:24172285

Mobile transporter path planning

NASA Technical Reports Server (NTRS)

Baffes, Paul; Wang, Lui

1990-01-01

The use of a genetic algorithm (GA) for solving the mobile transporter path planning problem is investigated. The mobile transporter is a traveling robotic vehicle proposed for the space station which must be able to reach any point of the structure autonomously. Elements of the genetic algorithm are explored in both a theoretical and experimental sense. Specifically, double crossover, greedy crossover, and tournament selection techniques are examined. Additionally, the use of local optimization techniques working in concert with the GA are also explored. Recent developments in genetic algorithm theory are shown to be particularly effective in a path planning problem domain, though problem areas can be cited which require more research.

Mobile robot dynamic path planning based on improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.

Constrained motion model of mobile robots and its applications.

PubMed

Zhang, Fei; Xi, Yugeng; Lin, Zongli; Chen, Weidong

2009-06-01

Target detecting and dynamic coverage are fundamental tasks in mobile robotics and represent two important features of mobile robots: mobility and perceptivity. This paper establishes the constrained motion model and sensor model of a mobile robot to represent these two features and defines the k -step reachable region to describe the states that the robot may reach. We show that the calculation of the k-step reachable region can be reduced from that of 2(k) reachable regions with the fixed motion styles to k + 1 such regions and provide an algorithm for its calculation. Based on the constrained motion model and the k -step reachable region, the problems associated with target detecting and dynamic coverage are formulated and solved. For target detecting, the k-step detectable region is used to describe the area that the robot may detect, and an algorithm for detecting a target and planning the optimal path is proposed. For dynamic coverage, the k-step detected region is used to represent the area that the robot has detected during its motion, and the dynamic-coverage strategy and algorithm are proposed. Simulation results demonstrate the efficiency of the coverage algorithm in both convex and concave environments.

Blood glucose level prediction based on support vector regression using mobile platforms.

PubMed

Reymann, Maximilian P; Dorschky, Eva; Groh, Benjamin H; Martindale, Christine; Blank, Peter; Eskofier, Bjoern M

2016-08-01

The correct treatment of diabetes is vital to a patient's health: Staying within defined blood glucose levels prevents dangerous short- and long-term effects on the body. Mobile devices informing patients about their future blood glucose levels could enable them to take counter-measures to prevent hypo or hyper periods. Previous work addressed this challenge by predicting the blood glucose levels using regression models. However, these approaches required a physiological model, representing the human body's response to insulin and glucose intake, or are not directly applicable to mobile platforms (smart phones, tablets). In this paper, we propose an algorithm for mobile platforms to predict blood glucose levels without the need for a physiological model. Using an online software simulator program, we trained a Support Vector Regression (SVR) model and exported the parameter settings to our mobile platform. The prediction accuracy of our mobile platform was evaluated with pre-recorded data of a type 1 diabetes patient. The blood glucose level was predicted with an error of 19 % compared to the true value. Considering the permitted error of commercially used devices of 15 %, our algorithm is the basis for further development of mobile prediction algorithms.

OceanRoute: Vessel Mobility Data Processing and Analyzing Model Based on MapReduce

NASA Astrophysics Data System (ADS)

Liu, Chao; Liu, Yingjian; Guo, Zhongwen; Jing, Wei

2018-06-01

The network coverage is a big problem in ocean communication, and there is no low-cost solution in the short term. Based on the knowledge of Mobile Delay Tolerant Network (MDTN), the mobility of vessels can create the chances of end-to-end communication. The mobility pattern of vessel is one of the key metrics on ocean MDTN network. Because of the high cost, few experiments have focused on research of vessel mobility pattern for the moment. In this paper, we study the traces of more than 4000 fishing and freight vessels. Firstly, to solve the data noise and sparsity problem, we design two algorithms to filter the noise and complement the missing data based on the vessel's turning feature. Secondly, after studying the traces of vessels, we observe that the vessel's traces are confined by invisible boundary. Thirdly, through defining the distance between traces, we design MR-Similarity algorithm to find the mobility pattern of vessels. Finally, we realize our algorithm on cluster and evaluate the performance and accuracy. Our results can provide the guidelines on design of data routing protocols on ocean MDTN.

Influence of camera parameters on the quality of mobile 3D capture

NASA Astrophysics Data System (ADS)

Georgiev, Mihail; Boev, Atanas; Gotchev, Atanas; Hannuksela, Miska

2010-01-01

We investigate the effect of camera de-calibration on the quality of depth estimation. Dense depth map is a format particularly suitable for mobile 3D capture (scalable and screen independent). However, in real-world scenario cameras might move (vibrations, temp. bend) form their designated positions. For experiments, we create a test framework, described in the paper. We investigate how mechanical changes will affect different (4) stereo-matching algorithms. We also assess how different geometric corrections (none, motion compensation-like, full rectification) will affect the estimation quality (how much offset can be still compensated with "crop" over a larger CCD). Finally, we show how estimated camera pose change (E) relates with stereo-matching, which can be used for "rectification quality" measure.

Using advanced computer vision algorithms on small mobile robots

NASA Astrophysics Data System (ADS)

Kogut, G.; Birchmore, F.; Biagtan Pacis, E.; Everett, H. R.

2006-05-01

The Technology Transfer project employs a spiral development process to enhance the functionality and autonomy of mobile robot systems in the Joint Robotics Program (JRP) Robotic Systems Pool by converging existing component technologies onto a transition platform for optimization. An example of this approach is the implementation of advanced computer vision algorithms on small mobile robots. We demonstrate the implementation and testing of the following two algorithms useful on mobile robots: 1) object classification using a boosted Cascade of classifiers trained with the Adaboost training algorithm, and 2) human presence detection from a moving platform. Object classification is performed with an Adaboost training system developed at the University of California, San Diego (UCSD) Computer Vision Lab. This classification algorithm has been used to successfully detect the license plates of automobiles in motion in real-time. While working towards a solution to increase the robustness of this system to perform generic object recognition, this paper demonstrates an extension to this application by detecting soda cans in a cluttered indoor environment. The human presence detection from a moving platform system uses a data fusion algorithm which combines results from a scanning laser and a thermal imager. The system is able to detect the presence of humans while both the humans and the robot are moving simultaneously. In both systems, the two aforementioned algorithms were implemented on embedded hardware and optimized for use in real-time. Test results are shown for a variety of environments.

ECG R-R peak detection on mobile phones.

PubMed

Sufi, F; Fang, Q; Cosic, I

2007-01-01

Mobile phones have become an integral part of modern life. Due to the ever increasing processing power, mobile phones are rapidly expanding its arena from a sole device of telecommunication to organizer, calculator, gaming device, web browser, music player, audio/video recording device, navigator etc. The processing power of modern mobile phones has been utilized by many innovative purposes. In this paper, we are proposing the utilization of mobile phones for monitoring and analysis of biosignal. The computation performed inside the mobile phone's processor will now be exploited for healthcare delivery. We performed literature review on RR interval detection from ECG and selected few PC based algorithms. Then, three of those existing RR interval detection algorithms were programmed on Java platform. Performance monitoring and comparison studies were carried out on three different mobile devices to determine their application on a realtime telemonitoring scenario.

A multi-sensor RSS spatial sensing-based robust stochastic optimization algorithm for enhanced wireless tethering.

PubMed

Parasuraman, Ramviyas; Fabry, Thomas; Molinari, Luca; Kershaw, Keith; Di Castro, Mario; Masi, Alessandro; Ferre, Manuel

2014-12-12

The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some electronic components may fail randomly (due to radiation effects), which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the "server-relay-client" framework that uses (multiple) relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO) algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide redundant networking abilities. We use pre-processing techniques, such as exponential moving averaging and spatial averaging filters on the RSS data for smoothing. We apply a receiver spatial diversity concept and employ a position controller on the relay node using a stochastic gradient ascent method for self-positioning the relay node to achieve the RSS balancing task. The effectiveness of the proposed solution is validated by extensive simulations and field experiments in CERN facilities. For the field trials, we used a youBot mobile robot platform as the relay node, and two stand-alone Raspberry Pi computers as the client and server nodes. The algorithm has been proven to be robust to noise in the radio signals and to work effectively even under non-line-of-sight conditions.

A Multi-Sensor RSS Spatial Sensing-Based Robust Stochastic Optimization Algorithm for Enhanced Wireless Tethering

PubMed Central

Parasuraman, Ramviyas; Fabry, Thomas; Molinari, Luca; Kershaw, Keith; Di Castro, Mario; Masi, Alessandro; Ferre, Manuel

2014-01-01

The reliability of wireless communication in a network of mobile wireless robot nodes depends on the received radio signal strength (RSS). When the robot nodes are deployed in hostile environments with ionizing radiations (such as in some scientific facilities), there is a possibility that some electronic components may fail randomly (due to radiation effects), which causes problems in wireless connectivity. The objective of this paper is to maximize robot mission capabilities by maximizing the wireless network capacity and to reduce the risk of communication failure. Thus, in this paper, we consider a multi-node wireless tethering structure called the “server-relay-client” framework that uses (multiple) relay nodes in between a server and a client node. We propose a robust stochastic optimization (RSO) algorithm using a multi-sensor-based RSS sampling method at the relay nodes to efficiently improve and balance the RSS between the source and client nodes to improve the network capacity and to provide redundant networking abilities. We use pre-processing techniques, such as exponential moving averaging and spatial averaging filters on the RSS data for smoothing. We apply a receiver spatial diversity concept and employ a position controller on the relay node using a stochastic gradient ascent method for self-positioning the relay node to achieve the RSS balancing task. The effectiveness of the proposed solution is validated by extensive simulations and field experiments in CERN facilities. For the field trials, we used a youBot mobile robot platform as the relay node, and two stand-alone Raspberry Pi computers as the client and server nodes. The algorithm has been proven to be robust to noise in the radio signals and to work effectively even under non-line-of-sight conditions. PMID:25615734

Mobile, hybrid Compton/coded aperture imaging for detection, identification and localization of gamma-ray sources at stand-off distances

NASA Astrophysics Data System (ADS)

Tornga, Shawn R.

The Stand-off Radiation Detection System (SORDS) program is an Advanced Technology Demonstration (ATD) project through the Department of Homeland Security's Domestic Nuclear Detection Office (DNDO) with the goal of detection, identification and localization of weak radiological sources in the presence of large dynamic backgrounds. The Raytheon-SORDS Tri-Modal Imager (TMI) is a mobile truck-based, hybrid gamma-ray imaging system able to quickly detect, identify and localize, radiation sources at standoff distances through improved sensitivity while minimizing the false alarm rate. Reconstruction of gamma-ray sources is performed using a combination of two imaging modalities; coded aperture and Compton scatter imaging. The TMI consists of 35 sodium iodide (NaI) crystals 5x5x2 in3 each, arranged in a random coded aperture mask array (CA), followed by 30 position sensitive NaI bars each 24x2.5x3 in3 called the detection array (DA). The CA array acts as both a coded aperture mask and scattering detector for Compton events. The large-area DA array acts as a collection detector for both Compton scattered events and coded aperture events. In this thesis, developed coded aperture, Compton and hybrid imaging algorithms will be described along with their performance. It will be shown that multiple imaging modalities can be fused to improve detection sensitivity over a broader energy range than either alone. Since the TMI is a moving system, peripheral data, such as a Global Positioning System (GPS) and Inertial Navigation System (INS) must also be incorporated. A method of adapting static imaging algorithms to a moving platform has been developed. Also, algorithms were developed in parallel with detector hardware, through the use of extensive simulations performed with the Geometry and Tracking Toolkit v4 (GEANT4). Simulations have been well validated against measured data. Results of image reconstruction algorithms at various speeds and distances will be presented as well as localization capability. Utilizing imaging information will show signal-to-noise gains over spectroscopic algorithms alone.

An Energy-Efficient Underground Localization System Based on Heterogeneous Wireless Networks

PubMed Central

Yuan, Yazhou; Chen, Cailian; Guan, Xinping; Yang, Qiuling

2015-01-01

A precision positioning system with energy efficiency is of great necessity for guaranteeing personnel safety in underground mines. The location information of the miners' should be transmitted to the control center timely and reliably; therefore, a heterogeneous network with the backbone based on high speed Industrial Ethernet is deployed. Since the mobile wireless nodes are working in an irregular tunnel, a specific wireless propagation model cannot fit all situations. In this paper, an underground localization system is designed to enable the adaptation to kinds of harsh tunnel environments, but also to reduce the energy consumption and thus prolong the lifetime of the network. Three key techniques are developed and implemented to improve the system performance, including a step counting algorithm with accelerometers, a power control algorithm and an adaptive packets scheduling scheme. The simulation study and experimental results show the effectiveness of the proposed algorithms and the implementation. PMID:26016918

The advanced progress of precoding technology in 5g system

NASA Astrophysics Data System (ADS)

An, Chenyi

2017-09-01

With the development of technology, people began to put forward higher requirements for the mobile system, the emergence of the 5G subvert the track of the development of mobile communication technology. In the research of the core technology of 5G mobile communication, large scale MIMO, and precoding technology is a research hotspot. At present, the research on precoding technology in 5G system analyzes the various methods of linear precoding, the maximum ratio transmission (MRT) precoding algorithm, zero forcing (ZF) precoding algorithm, minimum mean square error (MMSE) precoding algorithm based on maximum signal to leakage and noise ratio (SLNR). Precoding algorithms are analyzed and summarized in detail. At the same time, we also do some research on nonlinear precoding methods, such as dirty paper precoding, THP precoding algorithm and so on. Through these analysis, we can find the advantages and disadvantages of each algorithm, as well as the development trend of each algorithm, grasp the development of the current 5G system precoding technology. Therefore, the research results and data of this paper can be used as reference for the development of precoding technology in 5G system.

An Energy-Efficient Target-Tracking Strategy for Mobile Sensor Networks.

PubMed

Mahboubi, Hamid; Masoudimansour, Walid; Aghdam, Amir G; Sayrafian-Pour, Kamran

2017-02-01

In this paper, an energy-efficient strategy is proposed for tracking a moving target in an environment with obstacles, using a network of mobile sensors. Typically, the most dominant sources of energy consumption in a mobile sensor network are sensing, communication, and movement. The proposed algorithm first divides the field into a grid of sufficiently small cells. The grid is then represented by a graph whose edges are properly weighted to reflect the energy consumption of sensors. The proposed technique searches for near-optimal locations for the sensors in different time instants to route information from the target to destination, using a shortest path algorithm. Simulations confirm the efficacy of the proposed algorithm.

Enhancement of A5/1 encryption algorithm

NASA Astrophysics Data System (ADS)

Thomas, Ria Elin; Chandhiny, G.; Sharma, Katyayani; Santhi, H.; Gayathri, P.

2017-11-01

Mobiles have become an integral part of today’s world. Various standards have been proposed for the mobile communication, one of them being GSM. With the rising increase of mobile-based crimes, it is necessary to improve the security of the information passed in the form of voice or data. GSM uses A5/1 for its encryption. It is known that various attacks have been implemented, exploiting the vulnerabilities present within the A5/1 algorithm. Thus, in this paper, we proceed to look at what these vulnerabilities are, and propose the enhanced A5/1 (E-A5/1) where, we try to improve the security provided by the A5/1 algorithm by XORing the key stream generated with a pseudo random number, without increasing the time complexity. We need to study what the vulnerabilities of the base algorithm (A5/1) is, and try to improve upon its security. This will help in the future releases of the A5 family of algorithms.

Fast instantaneous center of rotation estimation algorithm for a skied-steered robot

NASA Astrophysics Data System (ADS)

Kniaz, V. V.

2015-05-01

Skid-steered robots are widely used as mobile platforms for machine vision systems. However it is hard to achieve a stable motion of such robots along desired trajectory due to an unpredictable wheel slip. It is possible to compensate the unpredictable wheel slip and stabilize the motion of the robot using visual odometry. This paper presents a fast optical flow based algorithm for estimation of instantaneous center of rotation, angular and longitudinal speed of the robot. The proposed algorithm is based on Horn-Schunck variational optical flow estimation method. The instantaneous center of rotation and motion of the robot is estimated by back projection of optical flow field to the ground surface. The developed algorithm was tested using skid-steered mobile robot. The robot is based on a mobile platform that includes two pairs of differential driven motors and a motor controller. Monocular visual odometry system consisting of a singleboard computer and a low cost webcam is mounted on the mobile platform. A state-space model of the robot was derived using standard black-box system identification. The input (commands) and the output (motion) were recorded using a dedicated external motion capture system. The obtained model was used to control the robot without visual odometry data. The paper is concluded with the algorithm quality estimation by comparison of the trajectories estimated by the algorithm with the data from motion capture system.

Simulation of Ion Motion in FAIMS through Combined Use of SIMION and Modified SDS

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

Prasad, Satendra; Tang, Keqi; Manura, David

2009-11-01

Over the years, the use of Field Asymmetric Ion Mobility Spectrometry (FAIMS) has grown with applications spanning from explosives detection to separation of complex biological mixtures. Although, the principles of ion separation in FAIMS is understood and comprehensively characterized, little effort has been made in developing commercially available computational tools that can simulate ion motion in FAIMS. Such a tool could be of great value for refining theory, optimizing the performance of the instrument for specific applications, and in modeling the fringe-fields caused by rf decay at the entrance and exit of FAIMS which can significantly affect ion transmission. Anmore » algorithm using SIMIONTM as its core structure was developed in this study to realistically compute ion trajectory at different ratios of electric field to buffer gas number density (E/N). The E/N can vary from a few Td to ~80 Td in FAIMS as created by an asymmetric square waveform. The Statistical Diffusion Simulation (SDS) model was further incorporated in the algorithm to simulate the ion diffusion in the FAIMS gap. The algorithm was validated using a FAIMS analyzer model similar to the Sionex Corporation model SVAC in terms of its dimensions and geometry. Hydroxyproline and Leucine ions with similar reduced mobility Ko (2.17 and 2.18 cm2.V-1.s-1, respectively) were used as model ions to test the new algorithm and demonstrate the effects of gas flow and waveform (voltage pulse amplitude and frequency) on peak shape and ion current transmission. Simulation results from three ion types: O2-(H2O)3, (A type), (C3H6O)2H+ (B type), and (C12H24O)2H+ (C type) were then compared with the experimental data (available in the literature). The SIMION-SDS-Field Dependent Mobility Calculation (FDMC) algorithm provided good agreement with experimental measurements of the ion peak position in FAIMS compensation voltage (CV) spectrum, peak width, and the ion transmission over a broad range of E/N.« less

Heuristic-based scheduling algorithm for high level synthesis

NASA Technical Reports Server (NTRS)

Mohamed, Gulam; Tan, Han-Ngee; Chng, Chew-Lye

1992-01-01

A new scheduling algorithm is proposed which uses a combination of a resource utilization chart, a heuristic algorithm to estimate the minimum number of hardware units based on operator mobilities, and a list-scheduling technique to achieve fast and near optimal schedules. The schedule time of this algorithm is almost independent of the length of mobilities of operators as can be seen from the benchmark example (fifth order digital elliptical wave filter) presented when the cycle time was increased from 17 to 18 and then to 21 cycles. It is implemented in C on a SUN3/60 workstation.

Securing mobile ad hoc networks using danger theory-based artificial immune algorithm.

PubMed

Abdelhaq, Maha; Alsaqour, Raed; Abdelhaq, Shawkat

2015-01-01

A mobile ad hoc network (MANET) is a set of mobile, decentralized, and self-organizing nodes that are used in special cases, such as in the military. MANET properties render the environment of this network vulnerable to different types of attacks, including black hole, wormhole and flooding-based attacks. Flooding-based attacks are one of the most dangerous attacks that aim to consume all network resources and thus paralyze the functionality of the whole network. Therefore, the objective of this paper is to investigate the capability of a danger theory-based artificial immune algorithm called the mobile dendritic cell algorithm (MDCA) to detect flooding-based attacks in MANETs. The MDCA applies the dendritic cell algorithm (DCA) to secure the MANET with additional improvements. The MDCA is tested and validated using Qualnet v7.1 simulation tool. This work also introduces a new simulation module for a flooding attack called the resource consumption attack (RCA) using Qualnet v7.1. The results highlight the high efficiency of the MDCA in detecting RCAs in MANETs.

Securing Mobile Ad Hoc Networks Using Danger Theory-Based Artificial Immune Algorithm

PubMed Central

2015-01-01

A mobile ad hoc network (MANET) is a set of mobile, decentralized, and self-organizing nodes that are used in special cases, such as in the military. MANET properties render the environment of this network vulnerable to different types of attacks, including black hole, wormhole and flooding-based attacks. Flooding-based attacks are one of the most dangerous attacks that aim to consume all network resources and thus paralyze the functionality of the whole network. Therefore, the objective of this paper is to investigate the capability of a danger theory-based artificial immune algorithm called the mobile dendritic cell algorithm (MDCA) to detect flooding-based attacks in MANETs. The MDCA applies the dendritic cell algorithm (DCA) to secure the MANET with additional improvements. The MDCA is tested and validated using Qualnet v7.1 simulation tool. This work also introduces a new simulation module for a flooding attack called the resource consumption attack (RCA) using Qualnet v7.1. The results highlight the high efficiency of the MDCA in detecting RCAs in MANETs. PMID:25946001

A uniform energy consumption algorithm for wireless sensor and actuator networks based on dynamic polling point selection.

PubMed

Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

2013-12-19

Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation.

Synthesis of the adaptive continuous system for the multi-axle wheeled vehicle body oscillation damping

NASA Astrophysics Data System (ADS)

Zhileykin, M. M.; Kotiev, G. O.; Nagatsev, M. V.

2018-02-01

In order to meet the growing mobility requirements for the wheeled vehicles on all types of terrain the engineers have to develop a large number of specialized control algorithms for the multi-axle wheeled vehicle (MWV) suspension improving such qualities as ride comfort, handling and stability. The authors have developed an adaptive algorithm of the dynamic damping of the MVW body oscillations. The algorithm provides high ride comfort and high mobility of the vehicle. The article discloses a method for synthesis of an adaptive dynamic continuous algorithm of the MVW body oscillation damping and provides simulation results proving high efficiency of the developed control algorithm.

Performance evaluation of power control algorithms in wireless cellular networks

NASA Astrophysics Data System (ADS)

Temaneh-Nyah, C.; Iita, V.

2014-10-01

Power control in a mobile communication network intents to control the transmission power levels in such a way that the required quality of service (QoS) for the users is guaranteed with lowest possible transmission powers. Most of the studies of power control algorithms in the literature are based on some kind of simplified assumptions which leads to compromise in the validity of the results when applied in a real environment. In this paper, a CDMA network was simulated. The real environment was accounted for by defining the analysis area and the network base stations and mobile stations are defined by their geographical coordinates, the mobility of the mobile stations is accounted for. The simulation also allowed for a number of network parameters including the network traffic, and the wireless channel models to be modified. Finally, we present the simulation results of a convergence speed based comparative analysis of three uplink power control algorithms.

Articular dysfunction patterns in patients with mechanical low back pain: A clinical algorithm to guide specific mobilization and manipulation techniques.

PubMed

Dewitte, V; Cagnie, B; Barbe, T; Beernaert, A; Vanthillo, B; Danneels, L

2015-06-01

Recent systematic reviews have demonstrated reasonable evidence that lumbar mobilization and manipulation techniques are beneficial. However, knowledge on optimal techniques and doses, and its clinical reasoning is currently lacking. To address this, a clinical algorithm is presented so as to guide therapists in their clinical reasoning to identify patients who are likely to respond to lumbar mobilization and/or manipulation and to direct appropriate technique selection. Key features in subjective and clinical examination suggestive of mechanical nociceptive pain probably arising from articular structures, can categorize patients into distinct articular dysfunction patterns. Based on these patterns, specific mobilization and manipulation techniques are suggested. This clinical algorithm is merely based on empirical clinical expertise and complemented through knowledge exchange between international colleagues. The added value of the proposed articular dysfunction patterns should be considered within a broader perspective. Copyright © 2014 Elsevier Ltd. All rights reserved.

Energy-Aware Computation Offloading of IoT Sensors in Cloudlet-Based Mobile Edge Computing.

PubMed

Ma, Xiao; Lin, Chuang; Zhang, Han; Liu, Jianwei

2018-06-15

Mobile edge computing is proposed as a promising computing paradigm to relieve the excessive burden of data centers and mobile networks, which is induced by the rapid growth of Internet of Things (IoT). This work introduces the cloud-assisted multi-cloudlet framework to provision scalable services in cloudlet-based mobile edge computing. Due to the constrained computation resources of cloudlets and limited communication resources of wireless access points (APs), IoT sensors with identical computation offloading decisions interact with each other. To optimize the processing delay and energy consumption of computation tasks, theoretic analysis of the computation offloading decision problem of IoT sensors is presented in this paper. In more detail, the computation offloading decision problem of IoT sensors is formulated as a computation offloading game and the condition of Nash equilibrium is derived by introducing the tool of a potential game. By exploiting the finite improvement property of the game, the Computation Offloading Decision (COD) algorithm is designed to provide decentralized computation offloading strategies for IoT sensors. Simulation results demonstrate that the COD algorithm can significantly reduce the system cost compared with the random-selection algorithm and the cloud-first algorithm. Furthermore, the COD algorithm can scale well with increasing IoT sensors.

Segmenting texts from outdoor images taken by mobile phones using color features

NASA Astrophysics Data System (ADS)

Liu, Zongyi; Zhou, Hanning

2011-01-01

Recognizing texts from images taken by mobile phones with low resolution has wide applications. It has been shown that a good image binarization can substantially improve the performances of OCR engines. In this paper, we present a framework to segment texts from outdoor images taken by mobile phones using color features. The framework consists of three steps: (i) the initial process including image enhancement, binarization and noise filtering, where we binarize the input images in each RGB channel, and apply component level noise filtering; (ii) grouping components into blocks using color features, where we compute the component similarities by dynamically adjusting the weights of RGB channels, and merge groups hierachically, and (iii) blocks selection, where we use the run-length features and choose the Support Vector Machine (SVM) as the classifier. We tested the algorithm using 13 outdoor images taken by an old-style LG-64693 mobile phone with 640x480 resolution. We compared the segmentation results with Tsar's algorithm, a state-of-the-art camera text detection algorithm, and show that our algorithm is more robust, particularly in terms of the false alarm rates. In addition, we also evaluated the impacts of our algorithm on the Abbyy's FineReader, one of the most popular commercial OCR engines in the market.

Self-Organized Link State Aware Routing for Multiple Mobile Agents in Wireless Network

NASA Astrophysics Data System (ADS)

Oda, Akihiro; Nishi, Hiroaki

Recently, the importance of data sharing structures in autonomous distributed networks has been increasing. A wireless sensor network is used for managing distributed data. This type of distributed network requires effective information exchanging methods for data sharing. To reduce the traffic of broadcasted messages, reduction of the amount of redundant information is indispensable. In order to reduce packet loss in mobile ad-hoc networks, QoS-sensitive routing algorithm have been frequently discussed. The topology of a wireless network is likely to change frequently according to the movement of mobile nodes, radio disturbance, or fading due to the continuous changes in the environment. Therefore, a packet routing algorithm should guarantee QoS by using some quality indicators of the wireless network. In this paper, a novel information exchanging algorithm developed using a hash function and a Boolean operation is proposed. This algorithm achieves efficient information exchanges by reducing the overhead of broadcasting messages, and it can guarantee QoS in a wireless network environment. It can be applied to a routing algorithm in a mobile ad-hoc network. In the proposed routing algorithm, a routing table is constructed by using the received signal strength indicator (RSSI), and the neighborhood information is periodically broadcasted depending on this table. The proposed hash-based routing entry management by using an extended MAC address can eliminate the overhead of message flooding. An analysis of the collision of hash values contributes to the determination of the length of the hash values, which is minimally required. Based on the verification of a mathematical theory, an optimum hash function for determining the length of hash values can be given. Simulations are carried out to evaluate the effectiveness of the proposed algorithm and to validate the theory in a general wireless network routing algorithm.

A Multi-Objective Compounded Local Mobile Cloud Architecture Using Priority Queues to Process Multiple Jobs.

PubMed

Wei, Xiaohui; Sun, Bingyi; Cui, Jiaxu; Xu, Gaochao

2016-01-01

As a result of the greatly increased use of mobile devices, the disadvantages of portable devices have gradually begun to emerge. To solve these problems, the use of mobile cloud computing assisted by cloud data centers has been proposed. However, cloud data centers are always very far from the mobile requesters. In this paper, we propose an improved multi-objective local mobile cloud model: Compounded Local Mobile Cloud Architecture with Dynamic Priority Queues (LMCpri). This new architecture could briefly store jobs that arrive simultaneously at the cloudlet in different priority positions according to the result of auction processing, and then execute partitioning tasks on capable helpers. In the Scheduling Module, NSGA-II is employed as the scheduling algorithm to shorten processing time and decrease requester cost relative to PSO and sequential scheduling. The simulation results show that the number of iteration times that is defined to 30 is the best choice of the system. In addition, comparing with LMCque, LMCpri is able to effectively accommodate a requester who would like his job to be executed in advance and shorten execution time. Finally, we make a comparing experiment between LMCpri and cloud assisting architecture, and the results reveal that LMCpri presents a better performance advantage than cloud assisting architecture.

A Multi-Objective Compounded Local Mobile Cloud Architecture Using Priority Queues to Process Multiple Jobs

PubMed Central

Wei, Xiaohui; Sun, Bingyi; Cui, Jiaxu; Xu, Gaochao

2016-01-01

As a result of the greatly increased use of mobile devices, the disadvantages of portable devices have gradually begun to emerge. To solve these problems, the use of mobile cloud computing assisted by cloud data centers has been proposed. However, cloud data centers are always very far from the mobile requesters. In this paper, we propose an improved multi-objective local mobile cloud model: Compounded Local Mobile Cloud Architecture with Dynamic Priority Queues (LMCpri). This new architecture could briefly store jobs that arrive simultaneously at the cloudlet in different priority positions according to the result of auction processing, and then execute partitioning tasks on capable helpers. In the Scheduling Module, NSGA-II is employed as the scheduling algorithm to shorten processing time and decrease requester cost relative to PSO and sequential scheduling. The simulation results show that the number of iteration times that is defined to 30 is the best choice of the system. In addition, comparing with LMCque, LMCpri is able to effectively accommodate a requester who would like his job to be executed in advance and shorten execution time. Finally, we make a comparing experiment between LMCpri and cloud assisting architecture, and the results reveal that LMCpri presents a better performance advantage than cloud assisting architecture. PMID:27419854

Designing algorithm visualization on mobile platform: The proposed guidelines

NASA Astrophysics Data System (ADS)

Supli, A. A.; Shiratuddin, N.

2017-09-01

This paper entails an ongoing study about the design guidelines of algorithm visualization (AV) on mobile platform, helping students learning data structures and algorithm (DSA) subject effectively. Our previous review indicated that design guidelines of AV on mobile platform are still few. Mostly, previous guidelines of AV are developed for AV on desktop and website platform. In fact, mobile learning has been proved to enhance engagement in learning circumstances, and thus effect student's performance. In addition, the researchers highly recommend including UI design and Interactivity in designing effective AV system. However, the discussions of these two aspects in previous AV design guidelines are not comprehensive. The UI design in this paper describes the arrangement of AV features in mobile environment, whereas interactivity is about the active learning strategy features based on learning experiences (how to engage learners). Thus, this study main objective is to propose design guidelines of AV on mobile platform (AVOMP) that entails comprehensively UI design and interactivity aspects. These guidelines are developed through content analysis and comparative analysis from various related studies. These guidelines are useful for AV designers to help them constructing AVOMP for various topics on DSA.

Tracking the Evolution of Smartphone Sensing for Monitoring Human Movement.

PubMed

del Rosario, Michael B; Redmond, Stephen J; Lovell, Nigel H

2015-07-31

Advances in mobile technology have led to the emergence of the "smartphone", a new class of device with more advanced connectivity features that have quickly made it a constant presence in our lives. Smartphones are equipped with comparatively advanced computing capabilities, a global positioning system (GPS) receivers, and sensing capabilities (i.e., an inertial measurement unit (IMU) and more recently magnetometer and barometer) which can be found in wearable ambulatory monitors (WAMs). As a result, algorithms initially developed for WAMs that "count" steps (i.e., pedometers); gauge physical activity levels; indirectly estimate energy expenditure and monitor human movement can be utilised on the smartphone. These algorithms may enable clinicians to "close the loop" by prescribing timely interventions to improve or maintain wellbeing in populations who are at risk of falling or suffer from a chronic disease whose progression is linked to a reduction in movement and mobility. The ubiquitous nature of smartphone technology makes it the ideal platform from which human movement can be remotely monitored without the expense of purchasing, and inconvenience of using, a dedicated WAM. In this paper, an overview of the sensors that can be found in the smartphone are presented, followed by a summary of the developments in this field with an emphasis on the evolution of algorithms used to classify human movement. The limitations identified in the literature will be discussed, as well as suggestions about future research directions.

MUSIC algorithm DoA estimation for cooperative node location in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Warty, Chirag; Yu, Richard Wai; ElMahgoub, Khaled; Spinsante, Susanna

In recent years the technological development has encouraged several applications based on distributed communications network without any fixed infrastructure. The problem of providing a collaborative early warning system for multiple mobile nodes against a fast moving object. The solution is provided subject to system level constraints: motion of nodes, antenna sensitivity and Doppler effect at 2.4 GHz and 5.8 GHz. This approach consists of three stages. The first phase consists of detecting the incoming object using a highly directive two element antenna at 5.0 GHz band. The second phase consists of broadcasting the warning message using a low directivity broad antenna beam using 2× 2 antenna array which then in third phase will be detected by receiving nodes by using direction of arrival (DOA) estimation technique. The DOA estimation technique is used to estimate the range and bearing of the incoming nodes. The position of fast arriving object can be estimated using the MUSIC algorithm for warning beam DOA estimation. This paper is mainly intended to demonstrate the feasibility of early detection and warning system using a collaborative node to node communication links. The simulation is performed to show the behavior of detecting and broadcasting antennas as well as performance of the detection algorithm. The idea can be further expanded to implement commercial grade detection and warning system

Study of robot landmark recognition with complex background

NASA Astrophysics Data System (ADS)

Huang, Yuqing; Yang, Jia

2007-12-01

It's of great importance for assisting robot in path planning, position navigating and task performing by perceiving and recognising environment characteristic. To solve the problem of monocular-vision-oriented landmark recognition for mobile intelligent robot marching with complex background, a kind of nested region growing algorithm which fused with transcendental color information and based on current maximum convergence center is proposed, allowing invariance localization to changes in position, scale, rotation, jitters and weather conditions. Firstly, a novel experiment threshold based on RGB vision model is used for the first image segmentation, which allowing some objects and partial scenes with similar color to landmarks also are detected with landmarks together. Secondly, with current maximum convergence center on segmented image as each growing seed point, the above region growing algorithm accordingly starts to establish several Regions of Interest (ROI) orderly. According to shape characteristics, a quick and effectual contour analysis based on primitive element is applied in deciding whether current ROI could be reserved or deleted after each region growing, then each ROI is judged initially and positioned. When the position information as feedback is conveyed to the gray image, the whole landmarks are extracted accurately with the second segmentation on the local image that exclusive to landmark area. Finally, landmarks are recognised by Hopfield neural network. Results issued from experiments on a great number of images with both campus and urban district as background show the effectiveness of the proposed algorithm.

Bioinspired Intelligent Algorithm and Its Applications for Mobile Robot Control: A Survey.

PubMed

Ni, Jianjun; Wu, Liuying; Fan, Xinnan; Yang, Simon X

2016-01-01

Bioinspired intelligent algorithm (BIA) is a kind of intelligent computing method, which is with a more lifelike biological working mechanism than other types. BIAs have made significant progress in both understanding of the neuroscience and biological systems and applying to various fields. Mobile robot control is one of the main application fields of BIAs which has attracted more and more attention, because mobile robots can be used widely and general artificial intelligent algorithms meet a development bottleneck in this field, such as complex computing and the dependence on high-precision sensors. This paper presents a survey of recent research in BIAs, which focuses on the research in the realization of various BIAs based on different working mechanisms and the applications for mobile robot control, to help in understanding BIAs comprehensively and clearly. The survey has four primary parts: a classification of BIAs from the biomimetic mechanism, a summary of several typical BIAs from different levels, an overview of current applications of BIAs in mobile robot control, and a description of some possible future directions for research.

Classifier dependent feature preprocessing methods

NASA Astrophysics Data System (ADS)

Rodriguez, Benjamin M., II; Peterson, Gilbert L.

2008-04-01

In mobile applications, computational complexity is an issue that limits sophisticated algorithms from being implemented on these devices. This paper provides an initial solution to applying pattern recognition systems on mobile devices by combining existing preprocessing algorithms for recognition. In pattern recognition systems, it is essential to properly apply feature preprocessing tools prior to training classification models in an attempt to reduce computational complexity and improve the overall classification accuracy. The feature preprocessing tools extended for the mobile environment are feature ranking, feature extraction, data preparation and outlier removal. Most desktop systems today are capable of processing a majority of the available classification algorithms without concern of processing while the same is not true on mobile platforms. As an application of pattern recognition for mobile devices, the recognition system targets the problem of steganalysis, determining if an image contains hidden information. The measure of performance shows that feature preprocessing increases the overall steganalysis classification accuracy by an average of 22%. The methods in this paper are tested on a workstation and a Nokia 6620 (Symbian operating system) camera phone with similar results.

Bioinspired Intelligent Algorithm and Its Applications for Mobile Robot Control: A Survey

PubMed Central

Ni, Jianjun; Wu, Liuying; Fan, Xinnan; Yang, Simon X.

2016-01-01

Bioinspired intelligent algorithm (BIA) is a kind of intelligent computing method, which is with a more lifelike biological working mechanism than other types. BIAs have made significant progress in both understanding of the neuroscience and biological systems and applying to various fields. Mobile robot control is one of the main application fields of BIAs which has attracted more and more attention, because mobile robots can be used widely and general artificial intelligent algorithms meet a development bottleneck in this field, such as complex computing and the dependence on high-precision sensors. This paper presents a survey of recent research in BIAs, which focuses on the research in the realization of various BIAs based on different working mechanisms and the applications for mobile robot control, to help in understanding BIAs comprehensively and clearly. The survey has four primary parts: a classification of BIAs from the biomimetic mechanism, a summary of several typical BIAs from different levels, an overview of current applications of BIAs in mobile robot control, and a description of some possible future directions for research. PMID:26819582

Cold regions mobility models

DOT National Transportation Integrated Search

1995-02-01

This report annotates the cold regions mobility prediction routines included in the CAAMS/ALBE mobility models. It further explains the development of the algorithms that are used in these models to describe the interaction of a vehicle with terrain ...

Machine vision and appearance based learning

NASA Astrophysics Data System (ADS)

Bernstein, Alexander

2017-03-01

Smart algorithms are used in Machine vision to organize or extract high-level information from the available data. The resulted high-level understanding the content of images received from certain visual sensing system and belonged to an appearance space can be only a key first step in solving various specific tasks such as mobile robot navigation in uncertain environments, road detection in autonomous driving systems, etc. Appearance-based learning has become very popular in the field of machine vision. In general, the appearance of a scene is a function of the scene content, the lighting conditions, and the camera position. Mobile robots localization problem in machine learning framework via appearance space analysis is considered. This problem is reduced to certain regression on an appearance manifold problem, and newly regression on manifolds methods are used for its solution.

BlueDetect: An iBeacon-Enabled Scheme for Accurate and Energy-Efficient Indoor-Outdoor Detection and Seamless Location-Based Service

PubMed Central

Zou, Han; Jiang, Hao; Luo, Yiwen; Zhu, Jianjie; Lu, Xiaoxuan; Xie, Lihua

2016-01-01

The location and contextual status (indoor or outdoor) is fundamental and critical information for upper-layer applications, such as activity recognition and location-based services (LBS) for individuals. In addition, optimizations of building management systems (BMS), such as the pre-cooling or heating process of the air-conditioning system according to the human traffic entering or exiting a building, can utilize the information, as well. The emerging mobile devices, which are equipped with various sensors, become a feasible and flexible platform to perform indoor-outdoor (IO) detection. However, power-hungry sensors, such as GPS and WiFi, should be used with caution due to the constrained battery storage on mobile device. We propose BlueDetect: an accurate, fast response and energy-efficient scheme for IO detection and seamless LBS running on the mobile device based on the emerging low-power iBeacon technology. By leveraging the on-broad Bluetooth module and our proposed algorithms, BlueDetect provides a precise IO detection service that can turn on/off on-board power-hungry sensors smartly and automatically, optimize their performances and reduce the power consumption of mobile devices simultaneously. Moreover, seamless positioning and navigation services can be realized by it, especially in a semi-outdoor environment, which cannot be achieved by GPS or an indoor positioning system (IPS) easily. We prototype BlueDetect on Android mobile devices and evaluate its performance comprehensively. The experimental results have validated the superiority of BlueDetect in terms of IO detection accuracy, localization accuracy and energy consumption. PMID:26907295

Low cost coherent demodulation for mobile satellite terminals

NASA Technical Reports Server (NTRS)

Dutta, Santanu; Henely, Steven J.

1993-01-01

This paper describes some low cost approaches to coherent BPSK demodulation for mobile satellite receivers. The specific application is an Inmarsat-C Land Mobile Earth Station (LMES), but the techniques are applicable to any PSK demodulator. The techniques discussed include combined sampling and quadrature downconversion with a single A/D and novel DSP algorithms for carrier acquisition offering both superior performance and economy of DSP resources. The DSP algorithms run at 5.7 MIPS, and the entire DSP subsystem, built with commercially available parts, costs under $60 at quantity-10,000.

Verification hybrid control of a wheeled mobile robot and manipulator

NASA Astrophysics Data System (ADS)

Muszynska, Magdalena; Burghardt, Andrzej; Kurc, Krzysztof; Szybicki, Dariusz

2016-04-01

In this article, innovative approaches to realization of the wheeled mobile robots and manipulator tracking are presented. Conceptions include application of the neural-fuzzy systems to compensation of the controlled system's nonlinearities in the tracking control task. Proposed control algorithms work on-line, contain structure, that adapt to the changeable work conditions of the controlled systems, and do not require the preliminary learning. The algorithm was verification on the real object which was a Scorbot - ER 4pc robotic manipulator and a Pioneer - 2DX mobile robot.

Platform Architecture for Decentralized Positioning Systems.

PubMed

Kasmi, Zakaria; Norrdine, Abdelmoumen; Blankenbach, Jörg

2017-04-26

A platform architecture for positioning systems is essential for the realization of a flexible localization system, which interacts with other systems and supports various positioning technologies and algorithms. The decentralized processing of a position enables pushing the application-level knowledge into a mobile station and avoids the communication with a central unit such as a server or a base station. In addition, the calculation of the position on low-cost and resource-constrained devices presents a challenge due to the limited computing, storage capacity, as well as power supply. Therefore, we propose a platform architecture that enables the design of a system with the reusability of the components, extensibility (e.g., with other positioning technologies) and interoperability. Furthermore, the position is computed on a low-cost device such as a microcontroller, which simultaneously performs additional tasks such as data collecting or preprocessing based on an operating system. The platform architecture is designed, implemented and evaluated on the basis of two positioning systems: a field strength system and a time of arrival-based positioning system.

Platform Architecture for Decentralized Positioning Systems

PubMed Central

Kasmi, Zakaria; Norrdine, Abdelmoumen; Blankenbach, Jörg

2017-01-01

A platform architecture for positioning systems is essential for the realization of a flexible localization system, which interacts with other systems and supports various positioning technologies and algorithms. The decentralized processing of a position enables pushing the application-level knowledge into a mobile station and avoids the communication with a central unit such as a server or a base station. In addition, the calculation of the position on low-cost and resource-constrained devices presents a challenge due to the limited computing, storage capacity, as well as power supply. Therefore, we propose a platform architecture that enables the design of a system with the reusability of the components, extensibility (e.g., with other positioning technologies) and interoperability. Furthermore, the position is computed on a low-cost device such as a microcontroller, which simultaneously performs additional tasks such as data collecting or preprocessing based on an operating system. The platform architecture is designed, implemented and evaluated on the basis of two positioning systems: a field strength system and a time of arrival-based positioning system. PMID:28445414

An energy efficient multiple mobile sinks based routing algorithm for wireless sensor networks

NASA Astrophysics Data System (ADS)

Zhong, Peijun; Ruan, Feng

2018-03-01

With the fast development of wireless sensor networks (WSNs), more and more energy efficient routing algorithms have been proposed. However, one of the research challenges is how to alleviate the hot spot problem since nodes close to static sink (or base station) tend to die earlier than other sensors. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we mainly study the energy efficient routing method with multiple mobile sinks support. We divide the whole network into several clusters and study the influence of mobile sink number on network lifetime. Simulation results show that the best network performance appears when mobile sink number is about 3 under our simulation environment.

A Uniform Energy Consumption Algorithm for Wireless Sensor and Actuator Networks Based on Dynamic Polling Point Selection

PubMed Central

Li, Shuo; Peng, Jun; Liu, Weirong; Zhu, Zhengfa; Lin, Kuo-Chi

2014-01-01

Recent research has indicated that using the mobility of the actuator in wireless sensor and actuator networks (WSANs) to achieve mobile data collection can greatly increase the sensor network lifetime. However, mobile data collection may result in unacceptable collection delays in the network if the path of the actuator is too long. Because real-time network applications require meeting data collection delay constraints, planning the path of the actuator is a very important issue to balance the prolongation of the network lifetime and the reduction of the data collection delay. In this paper, a multi-hop routing mobile data collection algorithm is proposed based on dynamic polling point selection with delay constraints to address this issue. The algorithm can actively update the selection of the actuator's polling points according to the sensor nodes' residual energies and their locations while also considering the collection delay constraint. It also dynamically constructs the multi-hop routing trees rooted by these polling points to balance the sensor node energy consumption and the extension of the network lifetime. The effectiveness of the algorithm is validated by simulation. PMID:24451455

Real-time video streaming using H.264 scalable video coding (SVC) in multihomed mobile networks: a testbed approach

NASA Astrophysics Data System (ADS)

Nightingale, James; Wang, Qi; Grecos, Christos

2011-03-01

Users of the next generation wireless paradigm known as multihomed mobile networks expect satisfactory quality of service (QoS) when accessing streamed multimedia content. The recent H.264 Scalable Video Coding (SVC) extension to the Advanced Video Coding standard (AVC), offers the facility to adapt real-time video streams in response to the dynamic conditions of multiple network paths encountered in multihomed wireless mobile networks. Nevertheless, preexisting streaming algorithms were mainly proposed for AVC delivery over multipath wired networks and were evaluated by software simulation. This paper introduces a practical, hardware-based testbed upon which we implement and evaluate real-time H.264 SVC streaming algorithms in a realistic multihomed wireless mobile networks environment. We propose an optimised streaming algorithm with multi-fold technical contributions. Firstly, we extended the AVC packet prioritisation schemes to reflect the three-dimensional granularity of SVC. Secondly, we designed a mechanism for evaluating the effects of different streamer 'read ahead window' sizes on real-time performance. Thirdly, we took account of the previously unconsidered path switching and mobile networks tunnelling overheads encountered in real-world deployments. Finally, we implemented a path condition monitoring and reporting scheme to facilitate the intelligent path switching. The proposed system has been experimentally shown to offer a significant improvement in PSNR of the received stream compared with representative existing algorithms.

Wireless acoustic modules for real-time data fusion using asynchronous sniper localization algorithms

NASA Astrophysics Data System (ADS)

Hengy, S.; De Mezzo, S.; Duffner, P.; Naz, P.

2012-11-01

The presence of snipers in modern conflicts leads to high insecurity for the soldiers. In order to improve the soldier's protection against this threat, the French German Research Institute of Saint-Louis (ISL) has been conducting studies in the domain of acoustic localization of shots. Mobile antennas mounted on the soldier's helmet were initially used for real-time detection, classification and localization of sniper shots. It showed good performances in land scenarios, but also in urban scenarios if the array was in the shot corridor, meaning that the microphones first detect the direct wave and then the reflections of the Mach and muzzle waves (15% distance estimation error compared to the actual shooter array distance). Fusing data sent by multiple sensor nodes distributed on the field showed some of the limitations of the technologies that have been implemented in ISL's demonstrators. Among others, the determination of the arrays' orientation was not accurate enough, thereby degrading the performance of data fusion. Some new solutions have been developed in the past year in order to obtain better performance for data fusion. Asynchronous localization algorithms have been developed and post-processed on data measured in both free-field and urban environments with acoustic modules on the line of sight of the shooter. These results are presented in the first part of the paper. The impact of GPS position estimation error is also discussed in the article in order to evaluate the possible use of those algorithms for real-time processing using mobile acoustic nodes. In the frame of ISL's transverse project IMOTEP (IMprovement Of optical and acoustical TEchnologies for the Protection), some demonstrators are developed that will allow real-time asynchronous localization of sniper shots. An embedded detection and classification algorithm is implemented on wireless acoustic modules that send the relevant information to a central PC. Data fusion is then processed and the estimated position of the shooter is sent back to the users. A SWIR active imaging system is used for localization refinement. A built-in DSP is related to the detection/classification tasks for each acoustic module. A GPS module is used for time difference of arrival and module's position estimation. Wireless communication is supported using ZigBee technology. These acoustic modules are described in the article and first results of real-time asynchronous sniper localization using those modules are discussed.

Computer simulator for a mobile telephone system

NASA Technical Reports Server (NTRS)

Schilling, D. L.

1981-01-01

A software simulator was developed to assist NASA in the design of the land mobile satellite service. Structured programming techniques were used by developing the algorithm using an ALCOL-like pseudo language and then encoding the algorithm into FORTRAN 4. The basic input data to the system is a sine wave signal although future plans call for actual sampled voice as the input signal. The simulator is capable of studying all the possible combinations of types and modes of calls through the use of five communication scenarios: single hop systems; double hop, signal gateway system; double hop, double gateway system; mobile to wireline system; and wireline to mobile system. The transmitter, fading channel, and interference source simulation are also discussed.

Syndromic Algorithms for Detection of Gambiense Human African Trypanosomiasis in South Sudan

PubMed Central

Palmer, Jennifer J.; Surur, Elizeous I.; Goch, Garang W.; Mayen, Mangar A.; Lindner, Andreas K.; Pittet, Anne; Kasparian, Serena; Checchi, Francesco; Whitty, Christopher J. M.

2013-01-01

Background Active screening by mobile teams is considered the best method for detecting human African trypanosomiasis (HAT) caused by Trypanosoma brucei gambiense but the current funding context in many post-conflict countries limits this approach. As an alternative, non-specialist health care workers (HCWs) in peripheral health facilities could be trained to identify potential cases who need testing based on their symptoms. We explored the predictive value of syndromic referral algorithms to identify symptomatic cases of HAT among a treatment-seeking population in Nimule, South Sudan. Methodology/Principal Findings Symptom data from 462 patients (27 cases) presenting for a HAT test via passive screening over a 7 month period were collected to construct and evaluate over 14,000 four item syndromic algorithms considered simple enough to be used by peripheral HCWs. For comparison, algorithms developed in other settings were also tested on our data, and a panel of expert HAT clinicians were asked to make referral decisions based on the symptom dataset. The best performing algorithms consisted of three core symptoms (sleep problems, neurological problems and weight loss), with or without a history of oedema, cervical adenopathy or proximity to livestock. They had a sensitivity of 88.9–92.6%, a negative predictive value of up to 98.8% and a positive predictive value in this context of 8.4–8.7%. In terms of sensitivity, these out-performed more complex algorithms identified in other studies, as well as the expert panel. The best-performing algorithm is predicted to identify about 9/10 treatment-seeking HAT cases, though only 1/10 patients referred would test positive. Conclusions/Significance In the absence of regular active screening, improving referrals of HAT patients through other means is essential. Systematic use of syndromic algorithms by peripheral HCWs has the potential to increase case detection and would increase their participation in HAT programmes. The algorithms proposed here, though promising, should be validated elsewhere. PMID:23350005

Robust mobility in human-populated environments

NASA Astrophysics Data System (ADS)

Gonzalez, Juan Pablo; Phillips, Mike; Neuman, Brad; Likhachev, Max

2012-06-01

Creating robots that can help humans in a variety of tasks requires robust mobility and the ability to safely navigate among moving obstacles. This paper presents an overview of recent research in the Robotics Collaborative Technology Alliance (RCTA) that addresses many of the core requirements for robust mobility in human-populated environments. Safe Interval Path Planning (SIPP) allows for very fast planning in dynamic environments when planning timeminimal trajectories. Generalized Safe Interval Path Planning extends this concept to trajectories that minimize arbitrary cost functions. Finally, generalized PPCP algorithm is used to generate plans that reason about the uncertainty in the predicted trajectories of moving obstacles and try to actively disambiguate the intentions of humans whenever necessary. We show how these approaches consider moving obstacles and temporal constraints and produce high-fidelity paths. Experiments in simulated environments show the performance of the algorithms under different controlled conditions, and experiments on physical mobile robots interacting with humans show how the algorithms perform under the uncertainties of the real world.

Use of radio-tagging to map spatial organization and social interactions in insects.

PubMed

Moreau, Mathieu; Arrufat, Patrick; Latil, Gérard; Jeanson, Raphaël

2011-01-01

Understanding of the organization of animal societies often requires knowledge of the identity of group members and their spatial location. We propose an original experimental design to track automatically the position of individuals using radio frequency identification technology (RFID). Ants equipped with passive transponders were detected by a reader mounted on a mobile arm moving across the nest surface. We developed an algorithm to accurately extract the positions of individuals moving in two dimensions. Our method was validated on synthetic test cases and then used for characterization of the spatial distribution of ants within nests. This approach provides an amenable system for monitoring large populations of individuals over long periods of time.

Toward Improving Electrocardiogram (ECG) Biometric Verification using Mobile Sensors: A Two-Stage Classifier Approach

PubMed Central

Tan, Robin; Perkowski, Marek

2017-01-01

Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest and wavelet distance measure through a probabilistic threshold schema, to improve the effectiveness and robustness of a biometric recognition system using ECG data acquired from a biosensor integrated into mobile devices. The proposed algorithm is evaluated using a mixed dataset from 184 subjects under different health conditions. The proposed two-stage classifier achieves a total of 99.52% subject verification accuracy, better than the 98.33% accuracy from random forest alone and 96.31% accuracy from wavelet distance measure algorithm alone. These results demonstrate the superiority of the proposed algorithm for biometric identification, hence supporting its practicality in areas such as cloud data security, cyber-security or remote healthcare systems. PMID:28230745

Toward Improving Electrocardiogram (ECG) Biometric Verification using Mobile Sensors: A Two-Stage Classifier Approach.

PubMed

Tan, Robin; Perkowski, Marek

2017-02-20

Electrocardiogram (ECG) signals sensed from mobile devices pertain the potential for biometric identity recognition applicable in remote access control systems where enhanced data security is demanding. In this study, we propose a new algorithm that consists of a two-stage classifier combining random forest and wavelet distance measure through a probabilistic threshold schema, to improve the effectiveness and robustness of a biometric recognition system using ECG data acquired from a biosensor integrated into mobile devices. The proposed algorithm is evaluated using a mixed dataset from 184 subjects under different health conditions. The proposed two-stage classifier achieves a total of 99.52% subject verification accuracy, better than the 98.33% accuracy from random forest alone and 96.31% accuracy from wavelet distance measure algorithm alone. These results demonstrate the superiority of the proposed algorithm for biometric identification, hence supporting its practicality in areas such as cloud data security, cyber-security or remote healthcare systems.

Intelligent mobility research for robotic locomotion in complex terrain

NASA Astrophysics Data System (ADS)

Trentini, Michael; Beckman, Blake; Digney, Bruce; Vincent, Isabelle; Ricard, Benoit

2006-05-01

The objective of the Autonomous Intelligent Systems Section of Defence R&D Canada - Suffield is best described by its mission statement, which is "to augment soldiers and combat systems by developing and demonstrating practical, cost effective, autonomous intelligent systems capable of completing military missions in complex operating environments." The mobility requirement for ground-based mobile systems operating in urban settings must increase significantly if robotic technology is to augment human efforts in these roles and environments. The intelligence required for autonomous systems to operate in complex environments demands advances in many fields of robotics. This has resulted in large bodies of research in areas of perception, world representation, and navigation, but the problem of locomotion in complex terrain has largely been ignored. In order to achieve its objective, the Autonomous Intelligent Systems Section is pursuing research that explores the use of intelligent mobility algorithms designed to improve robot mobility. Intelligent mobility uses sensing, control, and learning algorithms to extract measured variables from the world, control vehicle dynamics, and learn by experience. These algorithms seek to exploit available world representations of the environment and the inherent dexterity of the robot to allow the vehicle to interact with its surroundings and produce locomotion in complex terrain. The primary focus of the paper is to present the intelligent mobility research within the framework of the research methodology, plan and direction defined at Defence R&D Canada - Suffield. It discusses the progress and future direction of intelligent mobility research and presents the research tools, topics, and plans to address this critical research gap. This research will create effective intelligence to improve the mobility of ground-based mobile systems operating in urban settings to assist the Canadian Forces in their future urban operations.

Mobile GPU-based implementation of automatic analysis method for long-term ECG.

PubMed

Fan, Xiaomao; Yao, Qihang; Li, Ye; Chen, Runge; Cai, Yunpeng

2018-05-03

Long-term electrocardiogram (ECG) is one of the important diagnostic assistant approaches in capturing intermittent cardiac arrhythmias. Combination of miniaturized wearable holters and healthcare platforms enable people to have their cardiac condition monitored at home. The high computational burden created by concurrent processing of numerous holter data poses a serious challenge to the healthcare platform. An alternative solution is to shift the analysis tasks from healthcare platforms to the mobile computing devices. However, long-term ECG data processing is quite time consuming due to the limited computation power of the mobile central unit processor (CPU). This paper aimed to propose a novel parallel automatic ECG analysis algorithm which exploited the mobile graphics processing unit (GPU) to reduce the response time for processing long-term ECG data. By studying the architecture of the sequential automatic ECG analysis algorithm, we parallelized the time-consuming parts and reorganized the entire pipeline in the parallel algorithm to fully utilize the heterogeneous computing resources of CPU and GPU. The experimental results showed that the average executing time of the proposed algorithm on a clinical long-term ECG dataset (duration 23.0 ± 1.0 h per signal) is 1.215 ± 0.140 s, which achieved an average speedup of 5.81 ± 0.39× without compromising analysis accuracy, comparing with the sequential algorithm. Meanwhile, the battery energy consumption of the automatic ECG analysis algorithm was reduced by 64.16%. Excluding energy consumption from data loading, 79.44% of the energy consumption could be saved, which alleviated the problem of limited battery working hours for mobile devices. The reduction of response time and battery energy consumption in ECG analysis not only bring better quality of experience to holter users, but also make it possible to use mobile devices as ECG terminals for healthcare professions such as physicians and health advisers, enabling them to inspect patient ECG recordings onsite efficiently without the need of a high-quality wide-area network environment.

Recognizable-image selection for fingerprint recognition with a mobile-device camera.

PubMed

Lee, Dongjae; Choi, Kyoungtaek; Choi, Heeseung; Kim, Jaihie

2008-02-01

This paper proposes a recognizable-image selection algorithm for fingerprint-verification systems that use a camera embedded in a mobile device. A recognizable image is defined as the fingerprint image which includes the characteristics that are sufficiently discriminating an individual from other people. While general camera systems obtain focused images by using various gradient measures to estimate high-frequency components, mobile cameras cannot acquire recognizable images in the same way because the obtained images may not be adequate for fingerprint recognition, even if they are properly focused. A recognizable image has to meet the following two conditions: First, valid region in the recognizable image should be large enough compared with other nonrecognizable images. Here, a valid region is a well-focused part, and ridges in the region are clearly distinguishable from valleys. In order to select valid regions, this paper proposes a new focus-measurement algorithm using the secondary partial derivatives and a quality estimation utilizing the coherence and symmetry of gradient distribution. Second, rolling and pitching degrees of a finger measured from the camera plane should be within some limit for a recognizable image. The position of a core point and the contour of a finger are used to estimate the degrees of rolling and pitching. Experimental results show that our proposed method selects valid regions and estimates the degrees of rolling and pitching properly. In addition, fingerprint-verification performance is improved by detecting the recognizable images.

Robust multiperson detection and tracking for mobile service and social robots.

PubMed

Li, Liyuan; Yan, Shuicheng; Yu, Xinguo; Tan, Yeow Kee; Li, Haizhou

2012-10-01

This paper proposes an efficient system which integrates multiple vision models for robust multiperson detection and tracking for mobile service and social robots in public environments. The core technique is a novel maximum likelihood (ML)-based algorithm which combines the multimodel detections in mean-shift tracking. First, a likelihood probability which integrates detections and similarity to local appearance is defined. Then, an expectation-maximization (EM)-like mean-shift algorithm is derived under the ML framework. In each iteration, the E-step estimates the associations to the detections, and the M-step locates the new position according to the ML criterion. To be robust to the complex crowded scenarios for multiperson tracking, an improved sequential strategy to perform the mean-shift tracking is proposed. Under this strategy, human objects are tracked sequentially according to their priority order. To balance the efficiency and robustness for real-time performance, at each stage, the first two objects from the list of the priority order are tested, and the one with the higher score is selected. The proposed method has been successfully implemented on real-world service and social robots. The vision system integrates stereo-based and histograms-of-oriented-gradients-based human detections, occlusion reasoning, and sequential mean-shift tracking. Various examples to show the advantages and robustness of the proposed system for multiperson tracking from mobile robots are presented. Quantitative evaluations on the performance of multiperson tracking are also performed. Experimental results indicate that significant improvements have been achieved by using the proposed method.

Inertial aided cycle slip detection and identification for integrated PPP GPS and INS.

PubMed

Du, Shuang; Gao, Yang

2012-10-25

The recently developed integrated Precise Point Positioning (PPP) GPS/INS system can be useful to many applications, such as UAV navigation systems, land vehicle/machine automation and mobile mapping systems. Since carrier phase measurements are the primary observables in PPP GPS, cycle slips, which often occur due to high dynamics, signal obstructions and low satellite elevation, must be detected and repaired in order to ensure the navigation performance. In this research, a new algorithm of cycle slip detection and identification has been developed. With the aiding from INS, the proposed method jointly uses WL and EWL phase combinations to uniquely determine cycle slips in the L1 and L2 frequencies. To verify the efficiency of the algorithm, both tactical-grade and consumer-grade IMUs are tested by using a real dataset collected from two field tests. The results indicate that the proposed algorithm can efficiently detect and identify the cycle slips and subsequently improve the navigation performance of the integrated system.

HyMoTrack: A Mobile AR Navigation System for Complex Indoor Environments.

PubMed

Gerstweiler, Georg; Vonach, Emanuel; Kaufmann, Hannes

2015-12-24

Navigating in unknown big indoor environments with static 2D maps is a challenge, especially when time is a critical factor. In order to provide a mobile assistant, capable of supporting people while navigating in indoor locations, an accurate and reliable localization system is required in almost every corner of the building. We present a solution to this problem through a hybrid tracking system specifically designed for complex indoor spaces, which runs on mobile devices like smartphones or tablets. The developed algorithm only uses the available sensors built into standard mobile devices, especially the inertial sensors and the RGB camera. The combination of multiple optical tracking technologies, such as 2D natural features and features of more complex three-dimensional structures guarantees the robustness of the system. All processing is done locally and no network connection is needed. State-of-the-art indoor tracking approaches use mainly radio-frequency signals like Wi-Fi or Bluetooth for localizing a user. In contrast to these approaches, the main advantage of the developed system is the capability of delivering a continuous 3D position and orientation of the mobile device with centimeter accuracy. This makes it usable for localization and 3D augmentation purposes, e.g. navigation tasks or location-based information visualization.

HyMoTrack: A Mobile AR Navigation System for Complex Indoor Environments

PubMed Central

Gerstweiler, Georg; Vonach, Emanuel; Kaufmann, Hannes

2015-01-01

Navigating in unknown big indoor environments with static 2D maps is a challenge, especially when time is a critical factor. In order to provide a mobile assistant, capable of supporting people while navigating in indoor locations, an accurate and reliable localization system is required in almost every corner of the building. We present a solution to this problem through a hybrid tracking system specifically designed for complex indoor spaces, which runs on mobile devices like smartphones or tablets. The developed algorithm only uses the available sensors built into standard mobile devices, especially the inertial sensors and the RGB camera. The combination of multiple optical tracking technologies, such as 2D natural features and features of more complex three-dimensional structures guarantees the robustness of the system. All processing is done locally and no network connection is needed. State-of-the-art indoor tracking approaches use mainly radio-frequency signals like Wi-Fi or Bluetooth for localizing a user. In contrast to these approaches, the main advantage of the developed system is the capability of delivering a continuous 3D position and orientation of the mobile device with centimeter accuracy. This makes it usable for localization and 3D augmentation purposes, e.g. navigation tasks or location-based information visualization. PMID:26712755

Location-Aware Mobile Learning of Spatial Algorithms

ERIC Educational Resources Information Center

Karavirta, Ville

2013-01-01

Learning an algorithm--a systematic sequence of operations for solving a problem with given input--is often difficult for students due to the abstract nature of the algorithms and the data they process. To help students understand the behavior of algorithms, a subfield in computing education research has focused on algorithm…

Photogrammetric 3D reconstruction using mobile imaging

NASA Astrophysics Data System (ADS)

Fritsch, Dieter; Syll, Miguel

2015-03-01

In our paper we demonstrate the development of an Android Application (AndroidSfM) for photogrammetric 3D reconstruction that works on smartphones and tablets likewise. The photos are taken with mobile devices, and can thereafter directly be calibrated using standard calibration algorithms of photogrammetry and computer vision, on that device. Due to still limited computing resources on mobile devices, a client-server handshake using Dropbox transfers the photos to the sever to run AndroidSfM for the pose estimation of all photos by Structure-from-Motion and, thereafter, uses the oriented bunch of photos for dense point cloud estimation by dense image matching algorithms. The result is transferred back to the mobile device for visualization and ad-hoc on-screen measurements.

The design of mobile robot control system for the aged and the disabled

NASA Astrophysics Data System (ADS)

Qiang, Wang; Lei, Shi; Xiang, Gao; Jin, Zhang

2017-01-01

This paper designs a control system of mobile robot for the aged and the disabled, which consists of two main parts: human-computer interaction and drive control module. The data of the two parts is transferred via universal asynchronous receiver/transmitter. In the former part, the speed and direction information of the mobile robot is obtained by hall joystick. In the latter part, the electronic differential algorithm is developed to implement the robot mobile function by driving two-wheel motors. In order to improve the comfort of the robot when speed or direction is changed, the least squares algorithm is used to optimize the speed characteristic curves of the two motors. Experimental results have verified the effectiveness of the designed system.

Optimization of image processing algorithms on mobile platforms

NASA Astrophysics Data System (ADS)

Poudel, Pramod; Shirvaikar, Mukul

2011-03-01

This work presents a technique to optimize popular image processing algorithms on mobile platforms such as cell phones, net-books and personal digital assistants (PDAs). The increasing demand for video applications like context-aware computing on mobile embedded systems requires the use of computationally intensive image processing algorithms. The system engineer has a mandate to optimize them so as to meet real-time deadlines. A methodology to take advantage of the asymmetric dual-core processor, which includes an ARM and a DSP core supported by shared memory, is presented with implementation details. The target platform chosen is the popular OMAP 3530 processor for embedded media systems. It has an asymmetric dual-core architecture with an ARM Cortex-A8 and a TMS320C64x Digital Signal Processor (DSP). The development platform was the BeagleBoard with 256 MB of NAND RAM and 256 MB SDRAM memory. The basic image correlation algorithm is chosen for benchmarking as it finds widespread application for various template matching tasks such as face-recognition. The basic algorithm prototypes conform to OpenCV, a popular computer vision library. OpenCV algorithms can be easily ported to the ARM core which runs a popular operating system such as Linux or Windows CE. However, the DSP is architecturally more efficient at handling DFT algorithms. The algorithms are tested on a variety of images and performance results are presented measuring the speedup obtained due to dual-core implementation. A major advantage of this approach is that it allows the ARM processor to perform important real-time tasks, while the DSP addresses performance-hungry algorithms.

Dual stage potential field method for robotic path planning

NASA Astrophysics Data System (ADS)

Singh, Pradyumna Kumar; Parida, Pramod Kumar

2018-04-01

Path planning for autonomous mobile robots are the root for all autonomous mobile systems. Various methods are used for optimization of path to be followed by the autonomous mobile robots. Artificial potential field based path planning method is one of the most used methods for the researchers. Various algorithms have been proposed using the potential field approach. But in most of the common problems are encounters while heading towards the goal or target. i.e. local minima problem, zero potential regions problem, complex shaped obstacles problem, target near obstacle problem. In this paper we provide a new algorithm in which two types of potential functions are used one after another. The former one is to use to get the probable points and later one for getting the optimum path. In this algorithm we consider only the static obstacle and goal.

Cooperative Search and Rescue with Artificial Fishes Based on Fish-Swarm Algorithm for Underwater Wireless Sensor Networks

PubMed Central

Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua

2014-01-01

This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties. PMID:24741341

Cooperative search and rescue with artificial fishes based on fish-swarm algorithm for underwater wireless sensor networks.

PubMed

Zhao, Wei; Tang, Zhenmin; Yang, Yuwang; Wang, Lei; Lan, Shaohua

2014-01-01

This paper presents a searching control approach for cooperating mobile sensor networks. We use a density function to represent the frequency of distress signals issued by victims. The mobile nodes' moving in mission space is similar to the behaviors of fish-swarm in water. So, we take the mobile node as artificial fish node and define its operations by a probabilistic model over a limited range. A fish-swarm based algorithm is designed requiring local information at each fish node and maximizing the joint detection probabilities of distress signals. Optimization of formation is also considered for the searching control approach and is optimized by fish-swarm algorithm. Simulation results include two schemes: preset route and random walks, and it is showed that the control scheme has adaptive and effective properties.

Energy optimization in mobile sensor networks

NASA Astrophysics Data System (ADS)

Yu, Shengwei

Mobile sensor networks are considered to consist of a network of mobile robots, each of which has computation, communication and sensing capabilities. Energy efficiency is a critical issue in mobile sensor networks, especially when mobility (i.e., locomotion control), routing (i.e., communications) and sensing are unique characteristics of mobile robots for energy optimization. This thesis focuses on the problem of energy optimization of mobile robotic sensor networks, and the research results can be extended to energy optimization of a network of mobile robots that monitors the environment, or a team of mobile robots that transports materials from stations to stations in a manufacturing environment. On the energy optimization of mobile robotic sensor networks, our research focuses on the investigation and development of distributed optimization algorithms to exploit the mobility of robotic sensor nodes for network lifetime maximization. In particular, the thesis studies these five problems: 1. Network-lifetime maximization by controlling positions of networked mobile sensor robots based on local information with distributed optimization algorithms; 2. Lifetime maximization of mobile sensor networks with energy harvesting modules; 3. Lifetime maximization using joint design of mobility and routing; 4. Optimal control for network energy minimization; 5. Network lifetime maximization in mobile visual sensor networks. In addressing the first problem, we consider only the mobility strategies of the robotic relay nodes in a mobile sensor network in order to maximize its network lifetime. By using variable substitutions, the original problem is converted into a convex problem, and a variant of the sub-gradient method for saddle-point computation is developed for solving this problem. An optimal solution is obtained by the method. Computer simulations show that mobility of robotic sensors can significantly prolong the lifetime of the whole robotic sensor network while consuming negligible amount of energy for mobility cost. For the second problem, the problem is extended to accommodate mobile robotic nodes with energy harvesting capability, which makes it a non-convex optimization problem. The non-convexity issue is tackled by using the existing sequential convex approximation method, based on which we propose a novel procedure of modified sequential convex approximation that has fast convergence speed. For the third problem, the proposed procedure is used to solve another challenging non-convex problem, which results in utilizing mobility and routing simultaneously in mobile robotic sensor networks to prolong the network lifetime. The results indicate that joint design of mobility and routing has an edge over other methods in prolonging network lifetime, which is also the justification for the use of mobility in mobile sensor networks for energy efficiency purpose. For the fourth problem, we include the dynamics of the robotic nodes in the problem by modeling the networked robotic system using hybrid systems theory. A novel distributed method for the networked hybrid system is used to solve the optimal moving trajectories for robotic nodes and optimal network links, which are not answered by previous approaches. Finally, the fact that mobility is more effective in prolonging network lifetime for a data-intensive network leads us to apply our methods to study mobile visual sensor networks, which are useful in many applications. We investigate the joint design of mobility, data routing, and encoding power to help improving the video quality while maximizing the network lifetime. This study leads to a better understanding of the role mobility can play in data-intensive surveillance sensor networks.

A novel field search and rescue system based on SIM card location

NASA Astrophysics Data System (ADS)

Zhang, Huihui; Guo, Shutao; Cui, Dejing

2017-06-01

Nowadays, the rapid development of outdoor sports and adventure leads to the increase of the frequency of missing accidents. On the other hand, it becomes much more convenient and efficient for the criminals to escape with the help of new technologies. So we have developed a long-distance raids targeted field search and rescue system which utilizes RSSI ranging and Kalman filtering algorithm to realize remote positioning and dynamic supervision management only by a mobile phone with a SIM card, without any additional terminal equipment.

A new clustering strategy

NASA Astrophysics Data System (ADS)

Feng, Jian-xin; Tang, Jia-fu; Wang, Guang-xing

2007-04-01

On the basis of the analysis of clustering algorithm that had been proposed for MANET, a novel clustering strategy was proposed in this paper. With the trust defined by statistical hypothesis in probability theory and the cluster head selected by node trust and node mobility, this strategy can realize the function of the malicious nodes detection which was neglected by other clustering algorithms and overcome the deficiency of being incapable of implementing the relative mobility metric of corresponding nodes in the MOBIC algorithm caused by the fact that the receiving power of two consecutive HELLO packet cannot be measured. It's an effective solution to cluster MANET securely.

The Location GNSS Modules for the Components of Proteus System

NASA Astrophysics Data System (ADS)

Brzostowski, K.; Darakchiev, R.; Foks-Ryznar, A.; Sitek, P.

2012-01-01

The Proteus system - the Integrated Mobile System for Counterterrorism and Rescue Operations is a complex innovative project. To assure the best possible localization of mobile components of the system, many different Global Navigation Satellite System (GNSS) modules were taken into account. In order to chose the best solution many types of tests were done. Full results and conclusions are presented in this paper. The idea of measurements was to test modules in GPS Standard Positioning Service (SPS) with EGNOS system specification according to certain algorithms. The tests had to answer the question: what type of GNSS modules should be used on different components with respect to specific usage of Proteus system. The second goal of tests was to check the solution quality of integrated GNSS/INS (Inertial Navigation System) and its possible usage in some Proteus system components.

New algorithms for processing time-series big EEG data within mobile health monitoring systems.

PubMed

Serhani, Mohamed Adel; Menshawy, Mohamed El; Benharref, Abdelghani; Harous, Saad; Navaz, Alramzana Nujum

2017-10-01

Recent advances in miniature biomedical sensors, mobile smartphones, wireless communications, and distributed computing technologies provide promising techniques for developing mobile health systems. Such systems are capable of monitoring epileptic seizures reliably, which are classified as chronic diseases. Three challenging issues raised in this context with regard to the transformation, compression, storage, and visualization of big data, which results from a continuous recording of epileptic seizures using mobile devices. In this paper, we address the above challenges by developing three new algorithms to process and analyze big electroencephalography data in a rigorous and efficient manner. The first algorithm is responsible for transforming the standard European Data Format (EDF) into the standard JavaScript Object Notation (JSON) and compressing the transformed JSON data to decrease the size and time through the transfer process and to increase the network transfer rate. The second algorithm focuses on collecting and storing the compressed files generated by the transformation and compression algorithm. The collection process is performed with respect to the on-the-fly technique after decompressing files. The third algorithm provides relevant real-time interaction with signal data by prospective users. It particularly features the following capabilities: visualization of single or multiple signal channels on a smartphone device and query data segments. We tested and evaluated the effectiveness of our approach through a software architecture model implementing a mobile health system to monitor epileptic seizures. The experimental findings from 45 experiments are promising and efficiently satisfy the approach's objectives in a price of linearity. Moreover, the size of compressed JSON files and transfer times are reduced by 10% and 20%, respectively, while the average total time is remarkably reduced by 67% through all performed experiments. Our approach successfully develops efficient algorithms in terms of processing time, memory usage, and energy consumption while maintaining a high scalability of the proposed solution. Our approach efficiently supports data partitioning and parallelism relying on the MapReduce platform, which can help in monitoring and automatic detection of epileptic seizures. Copyright © 2017 Elsevier B.V. All rights reserved.

Fast T Wave Detection Calibrated by Clinical Knowledge with Annotation of P and T Waves.

PubMed

Elgendi, Mohamed; Eskofier, Bjoern; Abbott, Derek

2015-07-21

There are limited studies on the automatic detection of T waves in arrhythmic electrocardiogram (ECG) signals. This is perhaps because there is no available arrhythmia dataset with annotated T waves. There is a growing need to develop numerically-efficient algorithms that can accommodate the new trend of battery-driven ECG devices. Moreover, there is also a need to analyze long-term recorded signals in a reliable and time-efficient manner, therefore improving the diagnostic ability of mobile devices and point-of-care technologies. Here, the T wave annotation of the well-known MIT-BIH arrhythmia database is discussed and provided. Moreover, a simple fast method for detecting T waves is introduced. A typical T wave detection method has been reduced to a basic approach consisting of two moving averages and dynamic thresholds. The dynamic thresholds were calibrated using four clinically known types of sinus node response to atrial premature depolarization (compensation, reset, interpolation, and reentry). The determination of T wave peaks is performed and the proposed algorithm is evaluated on two well-known databases, the QT and MIT-BIH Arrhythmia databases. The detector obtained a sensitivity of 97.14% and a positive predictivity of 99.29% over the first lead of the validation databases (total of 221,186 beats). We present a simple yet very reliable T wave detection algorithm that can be potentially implemented on mobile battery-driven devices. In contrast to complex methods, it can be easily implemented in a digital filter design.

Tracking the Evolution of Smartphone Sensing for Monitoring Human Movement

PubMed Central

del Rosario, Michael B.; Redmond, Stephen J.; Lovell, Nigel H.

2015-01-01

Advances in mobile technology have led to the emergence of the “smartphone”, a new class of device with more advanced connectivity features that have quickly made it a constant presence in our lives. Smartphones are equipped with comparatively advanced computing capabilities, a global positioning system (GPS) receivers, and sensing capabilities (i.e., an inertial measurement unit (IMU) and more recently magnetometer and barometer) which can be found in wearable ambulatory monitors (WAMs). As a result, algorithms initially developed for WAMs that “count” steps (i.e., pedometers); gauge physical activity levels; indirectly estimate energy expenditure and monitor human movement can be utilised on the smartphone. These algorithms may enable clinicians to “close the loop” by prescribing timely interventions to improve or maintain wellbeing in populations who are at risk of falling or suffer from a chronic disease whose progression is linked to a reduction in movement and mobility. The ubiquitous nature of smartphone technology makes it the ideal platform from which human movement can be remotely monitored without the expense of purchasing, and inconvenience of using, a dedicated WAM. In this paper, an overview of the sensors that can be found in the smartphone are presented, followed by a summary of the developments in this field with an emphasis on the evolution of algorithms used to classify human movement. The limitations identified in the literature will be discussed, as well as suggestions about future research directions. PMID:26263998

Object tracking with adaptive HOG detector and adaptive Rao-Blackwellised particle filter

NASA Astrophysics Data System (ADS)

Rosa, Stefano; Paleari, Marco; Ariano, Paolo; Bona, Basilio

2012-01-01

Scenarios for a manned mission to the Moon or Mars call for astronaut teams to be accompanied by semiautonomous robots. A prerequisite for human-robot interaction is the capability of successfully tracking humans and objects in the environment. In this paper we present a system for real-time visual object tracking in 2D images for mobile robotic systems. The proposed algorithm is able to specialize to individual objects and to adapt to substantial changes in illumination and object appearance during tracking. The algorithm is composed by two main blocks: a detector based on Histogram of Oriented Gradient (HOG) descriptors and linear Support Vector Machines (SVM), and a tracker which is implemented by an adaptive Rao-Blackwellised particle filter (RBPF). The SVM is re-trained online on new samples taken from previous predicted positions. We use the effective sample size to decide when the classifier needs to be re-trained. Position hypotheses for the tracked object are the result of a clustering procedure applied on the set of particles. The algorithm has been tested on challenging video sequences presenting strong changes in object appearance, illumination, and occlusion. Experimental tests show that the presented method is able to achieve near real-time performances with a precision of about 7 pixels on standard video sequences of dimensions 320 × 240.

Vehicle parts detection based on Faster - RCNN with location constraints of vehicle parts feature point

NASA Astrophysics Data System (ADS)

Yang, Liqin; Sang, Nong; Gao, Changxin

2018-03-01

Vehicle parts detection plays an important role in public transportation safety and mobility. The detection of vehicle parts is to detect the position of each vehicle part. We propose a new approach by combining Faster RCNN and three level cascaded convolutional neural network (DCNN). The output of Faster RCNN is a series of bounding boxes with coordinate information, from which we can locate vehicle parts. DCNN can precisely predict feature point position, which is the center of vehicle part. We design an output strategy by combining these two results. There are two advantages for this. The quality of the bounding boxes are greatly improved, which means vehicle parts feature point position can be located more precise. Meanwhile we preserve the position relationship between vehicle parts and effectively improve the validity and reliability of the result. By using our algorithm, the performance of the vehicle parts detection improve obviously compared with Faster RCNN.

Test and assessment method of Automotive Safety Systems (SSB) particularly to monitor traffic incidents

NASA Astrophysics Data System (ADS)

Pijanowski, B.; Łukjanow, S.; Burliński, R.

2016-09-01

The rapid development of telematics, particularly mobile telephony (GSM), wireless data transmission (GPRS) and satellite positioning (GPS) noticeable in the last decade, resulted in an almost unlimited growth of the possibilities for monitoring of mobile objects. These solutions are already widely used in the so-called “Intelligent Transport Systems” - ITS and affect a significant increase for road safety. The article describes a method of testing and evaluation of Car Safety Systems (Polish abbreviation - SSB) especially for monitoring traffic incidents, such as collisions and accidents. The algorithm of SSB testing process is also presented. Tests are performed on the dynamic test bench, part of which is movable platform with car security system mounted on it. Crash tests with a rigid obstacle are carried out instead of destructive attempts to crash test of the entire vehicle which is expensive. The tested system, depending on the simulated traffic conditions, is mounted in such a position and with the use of components, indicated by the manufacturer for the automotive safety system installation in a vehicle, for which it is intended. Then, the tests and assessments are carried out.

Development and Evaluation of Real-Time Volumetric Compton Gamma-Ray Imaging

NASA Astrophysics Data System (ADS)

Barnowski, Ross Wegner

An approach to gamma-ray imaging has been developed that enables near real-time volumetric (3D) imaging of unknown environments thus improving the utility of gamma-ray imaging for source-search and radiation mapping applications. The approach, herein dubbed scene data fusion (SDF), is based on integrating mobile radiation imagers with real time tracking and scene reconstruction algorithms to enable a mobile mode of operation and 3D localization of gamma-ray sources. The real-time tracking allows the imager to be moved throughout the environment or around a particular object of interest, obtaining the multiple perspectives necessary for standoff 3D imaging. A 3D model of the scene, provided in real-time by a simultaneous localization and mapping (SLAM) algorithm, can be incorporated into the image reconstruction reducing the reconstruction time and improving imaging performance. The SDF concept is demonstrated in this work with a Microsoft Kinect RGB-D sensor, a real-time SLAM solver, and two different mobile gamma-ray imaging platforms. The first is a cart-based imaging platform known as the Volumetric Compton Imager (VCI), comprising two 3D position-sensitive high purity germanium (HPGe) detectors, exhibiting excellent gamma-ray imaging characteristics, but with limited mobility due to the size and weight of the cart. The second system is the High Efficiency Multimodal Imager (HEMI) a hand-portable gamma-ray imager comprising 96 individual cm3 CdZnTe crystals arranged in a two-plane, active-mask configuration. The HEMI instrument has poorer energy and angular resolution than the VCI, but is truly hand-portable, allowing the SDF concept to be tested in multiple environments and for more challenging imaging scenarios. An iterative algorithm based on Compton kinematics is used to reconstruct the gamma-ray source distribution in all three spatial dimensions. Each of the two mobile imaging systems are used to demonstrate SDF for a variety of scenarios, including general search and mapping scenarios with several point gamma-ray sources over the range of energies relevant for Compton imaging. More specific imaging scenarios are also addressed, including directed search and object interrogation scenarios. Finally, the volumetric image quality is quantitatively investigated with respect to the number of Compton events acquired during a measurement, the list-mode uncertainty of the Compton cone data, and the uncertainty in the pose estimate from the real-time tracking algorithm. SDF advances the real-world applicability of gamma-ray imaging for many search, mapping, and verification scenarios by improving the tractability of the gamma-ray image reconstruction and providing context for the 3D localization of gamma-ray sources within the environment in real-time.

Model of load balancing using reliable algorithm with multi-agent system

NASA Astrophysics Data System (ADS)

Afriansyah, M. F.; Somantri, M.; Riyadi, M. A.

2017-04-01

Massive technology development is linear with the growth of internet users which increase network traffic activity. It also increases load of the system. The usage of reliable algorithm and mobile agent in distributed load balancing is a viable solution to handle the load issue on a large-scale system. Mobile agent works to collect resource information and can migrate according to given task. We propose reliable load balancing algorithm using least time first byte (LFB) combined with information from the mobile agent. In system overview, the methodology consisted of defining identification system, specification requirements, network topology and design system infrastructure. The simulation method for simulated system was using 1800 request for 10 s from the user to the server and taking the data for analysis. Software simulation was based on Apache Jmeter by observing response time and reliability of each server and then compared it with existing method. Results of performed simulation show that the LFB method with mobile agent can perform load balancing with efficient systems to all backend server without bottleneck, low risk of server overload, and reliable.

Message Efficient Checkpointing and Rollback Recovery in Heterogeneous Mobile Networks

NASA Astrophysics Data System (ADS)

Jaggi, Parmeet Kaur; Singh, Awadhesh Kumar

2016-06-01

Heterogeneous networks provide an appealing way of expanding the computing capability of mobile networks by combining infrastructure-less mobile ad-hoc networks with the infrastructure-based cellular mobile networks. The nodes in such a network range from low-power nodes to macro base stations and thus, vary greatly in their capabilities such as computation power and battery power. The nodes are susceptible to different types of transient and permanent failures and therefore, the algorithms designed for such networks need to be fault-tolerant. The article presents a checkpointing algorithm for the rollback recovery of mobile hosts in a heterogeneous mobile network. Checkpointing is a well established approach to provide fault tolerance in static and cellular mobile distributed systems. However, the use of checkpointing for fault tolerance in a heterogeneous environment remains to be explored. The proposed protocol is based on the results of zigzag paths and zigzag cycles by Netzer-Xu. Considering the heterogeneity prevalent in the network, an uncoordinated checkpointing technique is employed. Yet, useless checkpoints are avoided without causing a high message overhead.

MOlecular MAterials Property Prediction Package (MOMAP) 1.0: a software package for predicting the luminescent properties and mobility of organic functional materials

NASA Astrophysics Data System (ADS)

Niu, Yingli; Li, Wenqiang; Peng, Qian; Geng, Hua; Yi, Yuanping; Wang, Linjun; Nan, Guangjun; Wang, Dong; Shuai, Zhigang

2018-04-01

MOlecular MAterials Property Prediction Package (MOMAP) is a software toolkit for molecular materials property prediction. It focuses on luminescent properties and charge mobility properties. This article contains a brief descriptive introduction of key features, theoretical models and algorithms of the software, together with examples that illustrate the performance. First, we present the theoretical models and algorithms for molecular luminescent properties calculation, which includes the excited-state radiative/non-radiative decay rate constant and the optical spectra. Then, a multi-scale simulation approach and its algorithm for the molecular charge mobility are described. This approach is based on hopping model and combines with Kinetic Monte Carlo and molecular dynamics simulations, and it is especially applicable for describing a large category of organic semiconductors, whose inter-molecular electronic coupling is much smaller than intra-molecular charge reorganisation energy.

Control of mechanical systems with rolling constraints: Application to dynamic control of mobile robots

NASA Technical Reports Server (NTRS)

Sarkar, Nilanjan; Yun, Xiaoping; Kumar, Vijay

1994-01-01

There are many examples of mechanical systems that require rolling contacts between two or more rigid bodies. Rolling contacts engender nonholonomic constraints in an otherwise holonomic system. In this article, we develop a unified approach to the control of mechanical systems subject to both holonomic and nonholonomic constraints. We first present a state space realization of a constrained system. We then discuss the input-output linearization and zero dynamics of the system. This approach is applied to the dynamic control of mobile robots. Two types of control algorithms for mobile robots are investigated: trajectory tracking and path following. In each case, a smooth nonlinear feedback is obtained to achieve asymptotic input-output stability and Lagrange stability of the overall system. Simulation results are presented to demonstrate the effectiveness of the control algorithms and to compare the performane of trajectory-tracking and path-following algorithms.

Real-time spectrum estimation–based dual-channel speech-enhancement algorithm for cochlear implant

PubMed Central

2012-01-01

Background Improvement of the cochlear implant (CI) front-end signal acquisition is needed to increase speech recognition in noisy environments. To suppress the directional noise, we introduce a speech-enhancement algorithm based on microphone array beamforming and spectral estimation. The experimental results indicate that this method is robust to directional mobile noise and strongly enhances the desired speech, thereby improving the performance of CI devices in a noisy environment. Methods The spectrum estimation and the array beamforming methods were combined to suppress the ambient noise. The directivity coefficient was estimated in the noise-only intervals, and was updated to fit for the mobile noise. Results The proposed algorithm was realized in the CI speech strategy. For actual parameters, we use Maxflat filter to obtain fractional sampling points and cepstrum method to differentiate the desired speech frame and the noise frame. The broadband adjustment coefficients were added to compensate the energy loss in the low frequency band. Discussions The approximation of the directivity coefficient is tested and the errors are discussed. We also analyze the algorithm constraint for noise estimation and distortion in CI processing. The performance of the proposed algorithm is analyzed and further be compared with other prevalent methods. Conclusions The hardware platform was constructed for the experiments. The speech-enhancement results showed that our algorithm can suppresses the non-stationary noise with high SNR. Excellent performance of the proposed algorithm was obtained in the speech enhancement experiments and mobile testing. And signal distortion results indicate that this algorithm is robust with high SNR improvement and low speech distortion. PMID:23006896

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones

PubMed Central

Chen, Jing; Cao, Ruochen; Wang, Yongtian

2015-01-01

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters. PMID:26690439

Sensor-Aware Recognition and Tracking for Wide-Area Augmented Reality on Mobile Phones.

PubMed

Chen, Jing; Cao, Ruochen; Wang, Yongtian

2015-12-10

Wide-area registration in outdoor environments on mobile phones is a challenging task in mobile augmented reality fields. We present a sensor-aware large-scale outdoor augmented reality system for recognition and tracking on mobile phones. GPS and gravity information is used to improve the VLAD performance for recognition. A kind of sensor-aware VLAD algorithm, which is self-adaptive to different scale scenes, is utilized to recognize complex scenes. Considering vision-based registration algorithms are too fragile and tend to drift, data coming from inertial sensors and vision are fused together by an extended Kalman filter (EKF) to achieve considerable improvements in tracking stability and robustness. Experimental results show that our method greatly enhances the recognition rate and eliminates the tracking jitters.

Adaptive density trajectory cluster based on time and space distance

NASA Astrophysics Data System (ADS)

Liu, Fagui; Zhang, Zhijie

2017-10-01

There are some hotspot problems remaining in trajectory cluster for discovering mobile behavior regularity, such as the computation of distance between sub trajectories, the setting of parameter values in cluster algorithm and the uncertainty/boundary problem of data set. As a result, based on the time and space, this paper tries to define the calculation method of distance between sub trajectories. The significance of distance calculation for sub trajectories is to clearly reveal the differences in moving trajectories and to promote the accuracy of cluster algorithm. Besides, a novel adaptive density trajectory cluster algorithm is proposed, in which cluster radius is computed through using the density of data distribution. In addition, cluster centers and number are selected by a certain strategy automatically, and uncertainty/boundary problem of data set is solved by designed weighted rough c-means. Experimental results demonstrate that the proposed algorithm can perform the fuzzy trajectory cluster effectively on the basis of the time and space distance, and obtain the optimal cluster centers and rich cluster results information adaptably for excavating the features of mobile behavior in mobile and sociology network.

Autonomous Navigation by a Mobile Robot

NASA Technical Reports Server (NTRS)

Huntsberger, Terrance; Aghazarian, Hrand

2005-01-01

ROAMAN is a computer program for autonomous navigation of a mobile robot on a long (as much as hundreds of meters) traversal of terrain. Developed for use aboard a robotic vehicle (rover) exploring the surface of a remote planet, ROAMAN could also be adapted to similar use on terrestrial mobile robots. ROAMAN implements a combination of algorithms for (1) long-range path planning based on images acquired by mast-mounted, wide-baseline stereoscopic cameras, and (2) local path planning based on images acquired by body-mounted, narrow-baseline stereoscopic cameras. The long-range path-planning algorithm autonomously generates a series of waypoints that are passed to the local path-planning algorithm, which plans obstacle-avoiding legs between the waypoints. Both the long- and short-range algorithms use an occupancy-grid representation in computations to detect obstacles and plan paths. Maps that are maintained by the long- and short-range portions of the software are not shared because substantial localization errors can accumulate during any long traverse. ROAMAN is not guaranteed to generate an optimal shortest path, but does maintain the safety of the rover.

Cooperative Autonomous Robots for Reconnaissance

DTIC Science & Technology

2009-03-06

REPORT Cooperative Autonomous Robots for Reconnaissance 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: Collaborating mobile robots equipped with WiFi ...Cooperative Autonomous Robots for Reconnaissance Report Title ABSTRACT Collaborating mobile robots equipped with WiFi transceivers are configured as a mobile...equipped with WiFi transceivers are configured as a mobile ad-hoc network. Algorithms are developed to take advantage of the distributed processing

An enhanced technique for mobile cloudlet offloading with reduced computation using compression in the cloud

NASA Astrophysics Data System (ADS)

Moro, A. C.; Nadesh, R. K.

2017-11-01

The cloud computing paradigm has transformed the way we do business in today’s world. Services on cloud have come a long way since just providing basic storage or software on demand. One of the fastest growing factor in this is mobile cloud computing. With the option of offloading now available to mobile users, mobile users can offload entire applications onto cloudlets. With the problems regarding availability and limited-storage capacity of these mobile cloudlets, it becomes difficult to decide for the mobile user when to use his local memory or the cloudlets. Hence, we take a look at a fast algorithm that decides whether the mobile user should go for cloudlet or rely on local memory based on an offloading probability. We have partially implemented the algorithm which decides whether the task can be carried out locally or given to a cloudlet. But as it becomes a burden on the mobile devices to perform the complete computation, so we look to offload this on to a cloud in our paper. Also further we use a file compression technique before sending the file onto the cloud to further reduce the load.

Multi-frame knowledge based text enhancement for mobile phone captured videos

NASA Astrophysics Data System (ADS)

Ozarslan, Suleyman; Eren, P. Erhan

2014-02-01

In this study, we explore automated text recognition and enhancement using mobile phone captured videos of store receipts. We propose a method which includes Optical Character Resolution (OCR) enhanced by our proposed Row Based Multiple Frame Integration (RB-MFI), and Knowledge Based Correction (KBC) algorithms. In this method, first, the trained OCR engine is used for recognition; then, the RB-MFI algorithm is applied to the output of the OCR. The RB-MFI algorithm determines and combines the most accurate rows of the text outputs extracted by using OCR from multiple frames of the video. After RB-MFI, KBC algorithm is applied to these rows to correct erroneous characters. Results of the experiments show that the proposed video-based approach which includes the RB-MFI and the KBC algorithm increases the word character recognition rate to 95%, and the character recognition rate to 98%.

A Novel Segment-Based Approach for Improving Classification Performance of Transport Mode Detection.

PubMed

Guvensan, M Amac; Dusun, Burak; Can, Baris; Turkmen, H Irem

2017-12-30

Transportation planning and solutions have an enormous impact on city life. To minimize the transport duration, urban planners should understand and elaborate the mobility of a city. Thus, researchers look toward monitoring people's daily activities including transportation types and duration by taking advantage of individual's smartphones. This paper introduces a novel segment-based transport mode detection architecture in order to improve the results of traditional classification algorithms in the literature. The proposed post-processing algorithm, namely the Healing algorithm, aims to correct the misclassification results of machine learning-based solutions. Our real-life test results show that the Healing algorithm could achieve up to 40% improvement of the classification results. As a result, the implemented mobile application could predict eight classes including stationary, walking, car, bus, tram, train, metro and ferry with a success rate of 95% thanks to the proposed multi-tier architecture and Healing algorithm.

Prediction based active ramp metering control strategy with mobility and safety assessment

NASA Astrophysics Data System (ADS)

Fang, Jie; Tu, Lili

2018-04-01

Ramp metering is one of the most direct and efficient motorway traffic flow management measures so as to improve traffic conditions. However, owing to short of traffic conditions prediction, in earlier studies, the impact on traffic flow dynamics of the applied RM control was not quantitatively evaluated. In this study, a RM control algorithm adopting Model Predictive Control (MPC) framework to predict and assess future traffic conditions, which taking both the current traffic conditions and the RM-controlled future traffic states into consideration, was presented. The designed RM control algorithm targets at optimizing the network mobility and safety performance. The designed algorithm is evaluated in a field-data-based simulation. Through comparing the presented algorithm controlled scenario with the uncontrolled scenario, it was proved that the proposed RM control algorithm can effectively relieve the congestion of traffic network with no significant compromises in safety aspect.

Articular dysfunction patterns in patients with mechanical neck pain: a clinical algorithm to guide specific mobilization and manipulation techniques.

PubMed

Dewitte, Vincent; Beernaert, Axel; Vanthillo, Bart; Barbe, Tom; Danneels, Lieven; Cagnie, Barbara

2014-02-01

In view of a didactical approach for teaching cervical mobilization and manipulation techniques to students as well as their use in daily practice, it is mandatory to acquire sound clinical reasoning to optimally apply advanced technical skills. The aim of this Masterclass is to present a clinical algorithm to guide (novice) therapists in their clinical reasoning to identify patients who are likely to respond to mobilization and/or manipulation. The presented clinical reasoning process is situated within the context of pain mechanisms and is narrowed to and applicable in patients with a dominant input pain mechanism. Based on key features in subjective and clinical examination, patients with mechanical nociceptive pain probably arising from articular structures can be categorized into specific articular dysfunction patterns. Pending on these patterns, specific mobilization and manipulation techniques are warranted. The proposed patterns are illustrated in 3 case studies. This clinical algorithm is the corollary of empirical expertise and is complemented by in-depth discussions and knowledge exchange with international colleagues. Consequently, it is intended that a carefully targeted approach contributes to an increase in specificity and safety in the use of cervical mobilizations and manipulation techniques as valuable adjuncts to other manual therapy modalities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Stereo-Based Region-Growing using String Matching

NASA Technical Reports Server (NTRS)

Mandelbaum, Robert; Mintz, Max

1995-01-01

We present a novel stereo algorithm based on a coarse texture segmentation preprocessing phase. Matching is performed using a string comparison. Matching sub-strings correspond to matching sequences of textures. Inter-scanline clustering of matching sub-strings yields regions of matching texture. The shape of these regions yield information concerning object's height, width and azimuthal position relative to the camera pair. Hence, rather than the standard dense depth map, the output of this algorithm is a segmentation of objects in the scene. Such a format is useful for the integration of stereo with other sensor modalities on a mobile robotic platform. It is also useful for localization; the height and width of a detected object may be used for landmark recognition, while depth and relative azimuthal location determine pose. The algorithm does not rely on the monotonicity of order of image primitives. Occlusions, exposures, and foreshortening effects are not problematic. The algorithm can deal with certain types of transparencies. It is computationally efficient, and very amenable to parallel implementation. Further, the epipolar constraints may be relaxed to some small but significant degree. A version of the algorithm has been implemented and tested on various types of images. It performs best on random dot stereograms, on images with easily filtered backgrounds (as in synthetic images), and on real scenes with uncontrived backgrounds.

Implementation of LSCMA adaptive array terminal for mobile satellite communications

NASA Astrophysics Data System (ADS)

Zhou, Shun; Wang, Huali; Xu, Zhijun

2007-11-01

This paper considers the application of adaptive array antenna based on the least squares constant modulus algorithm (LSCMA) for interference rejection in mobile SATCOM terminals. A two-element adaptive array scheme is implemented with a combination of ADI TS201S DSP chips and Altera Stratix II FPGA device, which makes a cooperating computation for adaptive beamforming. Its interference suppressing performance is verified via Matlab simulations. Digital hardware system is implemented to execute the operations of LSCMA beamforming algorithm that is represented by an algorithm flowchart. The result of simulations and test indicate that this scheme can improve the anti-jamming performance of terminals.

Identification of Mobile Phones Using the Built-In Magnetometers Stimulated by Motion Patterns.

PubMed

Baldini, Gianmarco; Dimc, Franc; Kamnik, Roman; Steri, Gary; Giuliani, Raimondo; Gentile, Claudio

2017-04-06

We investigate the identification of mobile phones through their built-in magnetometers. These electronic components have started to be widely deployed in mass market phones in recent years, and they can be exploited to uniquely identify mobile phones due their physical differences, which appear in the digital output generated by them. This is similar to approaches reported in the literature for other components of the mobile phone, including the digital camera, the microphones or their RF transmission components. In this paper, the identification is performed through an inexpensive device made up of a platform that rotates the mobile phone under test and a fixed magnet positioned on the edge of the rotating platform. When the mobile phone passes in front of the fixed magnet, the built-in magnetometer is stimulated, and its digital output is recorded and analyzed. For each mobile phone, the experiment is repeated over six different days to ensure consistency in the results. A total of 10 phones of different brands and models or of the same model were used in our experiment. The digital output from the magnetometers is synchronized and correlated, and statistical features are extracted to generate a fingerprint of the built-in magnetometer and, consequently, of the mobile phone. A SVM machine learning algorithm is used to classify the mobile phones on the basis of the extracted statistical features. Our results show that inter-model classification (i.e., different models and brands classification) is possible with great accuracy, but intra-model (i.e., phones with different serial numbers and same model) classification is more challenging, the resulting accuracy being just slightly above random choice.

Identification of Mobile Phones Using the Built-In Magnetometers Stimulated by Motion Patterns

PubMed Central

Baldini, Gianmarco; Dimc, Franc; Kamnik, Roman; Steri, Gary; Giuliani, Raimondo; Gentile, Claudio

2017-01-01

We investigate the identification of mobile phones through their built-in magnetometers. These electronic components have started to be widely deployed in mass market phones in recent years, and they can be exploited to uniquely identify mobile phones due their physical differences, which appear in the digital output generated by them. This is similar to approaches reported in the literature for other components of the mobile phone, including the digital camera, the microphones or their RF transmission components. In this paper, the identification is performed through an inexpensive device made up of a platform that rotates the mobile phone under test and a fixed magnet positioned on the edge of the rotating platform. When the mobile phone passes in front of the fixed magnet, the built-in magnetometer is stimulated, and its digital output is recorded and analyzed. For each mobile phone, the experiment is repeated over six different days to ensure consistency in the results. A total of 10 phones of different brands and models or of the same model were used in our experiment. The digital output from the magnetometers is synchronized and correlated, and statistical features are extracted to generate a fingerprint of the built-in magnetometer and, consequently, of the mobile phone. A SVM machine learning algorithm is used to classify the mobile phones on the basis of the extracted statistical features. Our results show that inter-model classification (i.e., different models and brands classification) is possible with great accuracy, but intra-model (i.e., phones with different serial numbers and same model) classification is more challenging, the resulting accuracy being just slightly above random choice. PMID:28383482

Agent-Based Chemical Plume Tracing Using Fluid Dynamics

NASA Technical Reports Server (NTRS)

Zarzhitsky, Dimitri; Spears, Diana; Thayer, David; Spears, William

2004-01-01

This paper presents a rigorous evaluation of a novel, distributed chemical plume tracing algorithm. The algorithm is a combination of the best aspects of the two most popular predecessors for this task. Furthermore, it is based on solid, formal principles from the field of fluid mechanics. The algorithm is applied by a network of mobile sensing agents (e.g., robots or micro-air vehicles) that sense the ambient fluid velocity and chemical concentration, and calculate derivatives. The algorithm drives the robotic network to the source of the toxic plume, where measures can be taken to disable the source emitter. This work is part of a much larger effort in research and development of a physics-based approach to developing networks of mobile sensing agents for monitoring, tracking, reporting and responding to hazardous conditions.

Analysis of three-dimensional SAR distributions emitted by mobile phones in an epidemiological perspective.

PubMed

Deltour, Isabelle; Wiart, Joe; Taki, Masao; Wake, Kanako; Varsier, Nadège; Mann, Simon; Schüz, Joachim; Cardis, Elisabeth

2011-12-01

The three-dimensional distribution of the specific absorption rate of energy (SAR) in phantom models was analysed to detect clusters of mobile phones producing similar spatial deposition of energy in the head. The clusters' characteristics were described from the phones external features, frequency band and communication protocol. Compliance measurements with phones in cheek and tilt positions, and on the left and right side of a physical phantom were used. Phones used the Personal Digital Cellular (PDC), Code division multiple access One (CdmaOne), Global System for Mobile Communications (GSM) and Nordic Mobile Telephony (NMT) communication systems, in the 800, 900, 1500 and 1800 MHz bands. Each phone's measurements were summarised by the half-ellipsoid in which the SAR values were above half the maximum value. Cluster analysis used the Partitioning Around Medoids algorithm. The dissimilarity measure was based on the overlap of the ellipsoids, and the Manhattan distance was used for robustness analysis. Within the 800 MHz frequency band, and in part within the 900 MHz and the 1800 MHz frequency bands, weak clustering was obtained for the handset shape (bar phone, flip with top and flip with central antennas), but only in specific positions (tilt or cheek). On measurements of 120 phones, the three-dimensional distribution of SAR in phantom models did not appear to be related to particular external phone characteristics or measurement characteristics, which could be used for refining the assessment of exposure to radiofrequency energy within the brain in epidemiological studies such as the Interphone. Copyright © 2011 Wiley Periodicals, Inc.

HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario.

PubMed

Alvarado-Uribe, Joanna; Gómez-Oliva, Andrea; Barrera-Animas, Ari Yair; Molina, Germán; Gonzalez-Mendoza, Miguel; Parra-Meroño, María Concepción; Jara, Antonio J

2018-03-17

Nowadays, Physical Web together with the increase in the use of mobile devices, Global Positioning System (GPS), and Social Networking Sites (SNS) have caused users to share enriched information on the Web such as their tourist experiences. Therefore, an area that has been significantly improved by using the contextual information provided by these technologies is tourism. In this way, the main goals of this work are to propose and develop an algorithm focused on the recommendation of Smart Point of Interaction (Smart POI) for a specific user according to his/her preferences and the Smart POIs' context. Hence, a novel Hybrid Recommendation Algorithm (HyRA) is presented by incorporating an aggregation operator into the user-based Collaborative Filtering (CF) algorithm as well as including the Smart POIs' categories and geographical information. For the experimental phase, two real-world datasets have been collected and preprocessed. In addition, one Smart POIs' categories dataset was built. As a result, a dataset composed of 16 Smart POIs, another constituted by the explicit preferences of 200 respondents, and the last dataset integrated by 13 Smart POIs' categories are provided. The experimental results show that the recommendations suggested by HyRA are promising.

HyRA: A Hybrid Recommendation Algorithm Focused on Smart POI. Ceutí as a Study Scenario

PubMed Central

Gómez-Oliva, Andrea; Molina, Germán

2018-01-01

Nowadays, Physical Web together with the increase in the use of mobile devices, Global Positioning System (GPS), and Social Networking Sites (SNS) have caused users to share enriched information on the Web such as their tourist experiences. Therefore, an area that has been significantly improved by using the contextual information provided by these technologies is tourism. In this way, the main goals of this work are to propose and develop an algorithm focused on the recommendation of Smart Point of Interaction (Smart POI) for a specific user according to his/her preferences and the Smart POIs’ context. Hence, a novel Hybrid Recommendation Algorithm (HyRA) is presented by incorporating an aggregation operator into the user-based Collaborative Filtering (CF) algorithm as well as including the Smart POIs’ categories and geographical information. For the experimental phase, two real-world datasets have been collected and preprocessed. In addition, one Smart POIs’ categories dataset was built. As a result, a dataset composed of 16 Smart POIs, another constituted by the explicit preferences of 200 respondents, and the last dataset integrated by 13 Smart POIs’ categories are provided. The experimental results show that the recommendations suggested by HyRA are promising. PMID:29562590

Multisensor-based human detection and tracking for mobile service robots.

PubMed

Bellotto, Nicola; Hu, Huosheng

2009-02-01

One of fundamental issues for service robots is human-robot interaction. In order to perform such a task and provide the desired services, these robots need to detect and track people in the surroundings. In this paper, we propose a solution for human tracking with a mobile robot that implements multisensor data fusion techniques. The system utilizes a new algorithm for laser-based leg detection using the onboard laser range finder (LRF). The approach is based on the recognition of typical leg patterns extracted from laser scans, which are shown to also be very discriminative in cluttered environments. These patterns can be used to localize both static and walking persons, even when the robot moves. Furthermore, faces are detected using the robot's camera, and the information is fused to the legs' position using a sequential implementation of unscented Kalman filter. The proposed solution is feasible for service robots with a similar device configuration and has been successfully implemented on two different mobile platforms. Several experiments illustrate the effectiveness of our approach, showing that robust human tracking can be performed within complex indoor environments.

Secure Cooperation of Autonomous Mobile Sensors Using an Underwater Acoustic Network

PubMed Central

Caiti, Andrea; Calabrò, Vincenzo; Dini, Gianluca; Duca, Angelica Lo; Munafò, Andrea

2012-01-01

Methodologies and algorithms are presented for the secure cooperation of a team of autonomous mobile underwater sensors, connected through an acoustic communication network, within surveillance and patrolling applications. In particular, the work proposes a cooperative algorithm in which the mobile underwater sensors (installed on Autonomous Underwater Vehicles—AUVs) respond to simple local rules based on the available information to perform the mission and maintain the communication link with the network (behavioral approach). The algorithm is intrinsically robust: with loss of communication among the vehicles the coverage performance (i.e., the mission goal) is degraded but not lost. The ensuing form of graceful degradation provides also a reactive measure against Denial of Service. The cooperative algorithm relies on the fact that the available information from the other sensors, though not necessarily complete, is trustworthy. To ensure trustworthiness, a security suite has been designed, specifically oriented to the underwater scenario, and in particular with the goal of reducing the communication overhead introduced by security in terms of number and size of messages. The paper gives implementation details on the integration between the security suite and the cooperative algorithm and provides statistics on the performance of the system as collected during the UAN project sea trial held in Trondheim, Norway, in May 2011. PMID:22438748

Detection and Tracking of Dynamic Objects by Using a Multirobot System: Application to Critical Infrastructures Surveillance

PubMed Central

Rodríguez-Canosa, Gonzalo; Giner, Jaime del Cerro; Barrientos, Antonio

2014-01-01

The detection and tracking of mobile objects (DATMO) is progressively gaining importance for security and surveillance applications. This article proposes a set of new algorithms and procedures for detecting and tracking mobile objects by robots that work collaboratively as part of a multirobot system. These surveillance algorithms are conceived of to work with data provided by long distance range sensors and are intended for highly reliable object detection in wide outdoor environments. Contrary to most common approaches, in which detection and tracking are done by an integrated procedure, the approach proposed here relies on a modular structure, in which detection and tracking are carried out independently, and the latter might accept input data from different detection algorithms. Two movement detection algorithms have been developed for the detection of dynamic objects by using both static and/or mobile robots. The solution to the overall problem is based on the use of a Kalman filter to predict the next state of each tracked object. Additionally, new tracking algorithms capable of combining dynamic objects lists coming from either one or various sources complete the solution. The complementary performance of the separated modular structure for detection and identification is evaluated and, finally, a selection of test examples discussed. PMID:24526305

Secure cooperation of autonomous mobile sensors using an underwater acoustic network.

PubMed

Caiti, Andrea; Calabrò, Vincenzo; Dini, Gianluca; Lo Duca, Angelica; Munafò, Andrea

2012-01-01

Methodologies and algorithms are presented for the secure cooperation of a team of autonomous mobile underwater sensors, connected through an acoustic communication network, within surveillance and patrolling applications. In particular, the work proposes a cooperative algorithm in which the mobile underwater sensors (installed on Autonomous Underwater Vehicles-AUVs) respond to simple local rules based on the available information to perform the mission and maintain the communication link with the network (behavioral approach). The algorithm is intrinsically robust: with loss of communication among the vehicles the coverage performance (i.e., the mission goal) is degraded but not lost. The ensuing form of graceful degradation provides also a reactive measure against Denial of Service. The cooperative algorithm relies on the fact that the available information from the other sensors, though not necessarily complete, is trustworthy. To ensure trustworthiness, a security suite has been designed, specifically oriented to the underwater scenario, and in particular with the goal of reducing the communication overhead introduced by security in terms of number and size of messages. The paper gives implementation details on the integration between the security suite and the cooperative algorithm and provides statistics on the performance of the system as collected during the UAN project sea trial held in Trondheim, Norway, in May 2011.

Mobile Robot Positioning with 433-MHz Wireless Motes with Varying Transmission Powers and a Particle Filter.

PubMed

Canedo-Rodriguez, Adrian; Rodriguez, Jose Manuel; Alvarez-Santos, Victor; Iglesias, Roberto; Regueiro, Carlos V

2015-04-30

In wireless positioning systems, the transmitter's power is usually fixed. In this paper, we explore the use of varying transmission powers to increase the performance of a wireless localization system. To this extent, we have designed a robot positioning system based on wireless motes. Our motes use an inexpensive, low-power sub-1-GHz system-on-chip (CC1110) working in the 433-MHz ISM band. Our localization algorithm is based on a particle filter and infers the robot position by: (1) comparing the power received with the expected one; and (2) integrating the robot displacement. We demonstrate that the use of transmitters that vary their transmission power over time improves the performance of the wireless positioning system significantly, with respect to a system that uses fixed power transmitters. This opens the door for applications where the robot can localize itself actively by requesting the transmitters to change their power in real time.

Mobile Robot Positioning with 433-MHz Wireless Motes with Varying Transmission Powers and a Particle Filter

PubMed Central

Canedo-Rodriguez, Adrian; Rodriguez, Jose Manuel; Alvarez-Santos, Victor; Iglesias, Roberto; Regueiro, Carlos V.

2015-01-01

In wireless positioning systems, the transmitter's power is usually fixed. In this paper, we explore the use of varying transmission powers to increase the performance of a wireless localization system. To this extent, we have designed a robot positioning system based on wireless motes. Our motes use an inexpensive, low-power sub-1-GHz system-on-chip (CC1110) working in the 433-MHz ISM band. Our localization algorithm is based on a particle filter and infers the robot position by: (1) comparing the power received with the expected one; and (2) integrating the robot displacement. We demonstrate that the use of transmitters that vary their transmission power over time improves the performance of the wireless positioning system significantly, with respect to a system that uses fixed power transmitters. This opens the door for applications where the robot can localize itself actively by requesting the transmitters to change their power in real time. PMID:25942641

Vision based object pose estimation for mobile robots

NASA Technical Reports Server (NTRS)

Wu, Annie; Bidlack, Clint; Katkere, Arun; Feague, Roy; Weymouth, Terry

1994-01-01

Mobile robot navigation using visual sensors requires that a robot be able to detect landmarks and obtain pose information from a camera image. This paper presents a vision system for finding man-made markers of known size and calculating the pose of these markers. The algorithm detects and identifies the markers using a weighted pattern matching template. Geometric constraints are then used to calculate the position of the markers relative to the robot. The selection of geometric constraints comes from the typical pose of most man-made signs, such as the sign standing vertical and the dimensions of known size. This system has been tested successfully on a wide range of real images. Marker detection is reliable, even in cluttered environments, and under certain marker orientations, estimation of the orientation has proven accurate to within 2 degrees, and distance estimation to within 0.3 meters.

SLAM algorithm applied to robotics assistance for navigation in unknown environments.

PubMed

Cheein, Fernando A Auat; Lopez, Natalia; Soria, Carlos M; di Sciascio, Fernando A; Pereira, Fernando Lobo; Carelli, Ricardo

2010-02-17

The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI). In this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface. The integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation.

A Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks.

PubMed

Luo, Junhai; Fan, Liying

2017-03-30

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of the underwater propagation problems. Hence, some localization algorithms based on the precise time synchronization between sensor nodes that have been proposed for UWSNs are not feasible. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme based on the Particle Swarm Optimization (PSO) algorithm to obtain the coordinates of the unknown sensor nodes. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence, in this algorithm, we use a small number of mobile beacons to help obtain the location information without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA achieved by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization.

A Two-Phase Time Synchronization-Free Localization Algorithm for Underwater Sensor Networks

PubMed Central

Luo, Junhai; Fan, Liying

2017-01-01

Underwater Sensor Networks (UWSNs) can enable a broad range of applications such as resource monitoring, disaster prevention, and navigation-assistance. Sensor nodes location in UWSNs is an especially relevant topic. Global Positioning System (GPS) information is not suitable for use in UWSNs because of the underwater propagation problems. Hence, some localization algorithms based on the precise time synchronization between sensor nodes that have been proposed for UWSNs are not feasible. In this paper, we propose a localization algorithm called Two-Phase Time Synchronization-Free Localization Algorithm (TP-TSFLA). TP-TSFLA contains two phases, namely, range-based estimation phase and range-free evaluation phase. In the first phase, we address a time synchronization-free localization scheme based on the Particle Swarm Optimization (PSO) algorithm to obtain the coordinates of the unknown sensor nodes. In the second phase, we propose a Circle-based Range-Free Localization Algorithm (CRFLA) to locate the unlocalized sensor nodes which cannot obtain the location information through the first phase. In the second phase, sensor nodes which are localized in the first phase act as the new anchor nodes to help realize localization. Hence, in this algorithm, we use a small number of mobile beacons to help obtain the location information without any other anchor nodes. Besides, to improve the precision of the range-free method, an extension of CRFLA achieved by designing a coordinate adjustment scheme is updated. The simulation results show that TP-TSFLA can achieve a relative high localization ratio without time synchronization. PMID:28358342

Optimized mobile retroreflectivity unit data processing algorithms.

DOT National Transportation Integrated Search

2017-04-01

The University of North Florida, in collaboration with the FDOT, was tasked to establish precise line-stripe evaluation methods using the Mobile Retroreflectivity Unit (MRU). Initial implementation of the manufacturers software resulted in measure...

Absolute position calculation for a desktop mobile rehabilitation robot based on three optical mouse sensors.

PubMed

Zabaleta, Haritz; Valencia, David; Perry, Joel; Veneman, Jan; Keller, Thierry

2011-01-01

ArmAssist is a wireless robot for post stroke upper limb rehabilitation. Knowing the position of the arm is essential for any rehabilitation device. In this paper, we describe a method based on an artificial landmark navigation system. The navigation system uses three optical mouse sensors. This enables the building of a cheap but reliable position sensor. Two of the sensors are the data source for odometry calculations, and the third optical mouse sensor takes very low resolution pictures of a custom designed mat. These pictures are processed by an optical symbol recognition algorithm which will estimate the orientation of the robot and recognize the landmarks placed on the mat. The data fusion strategy is described to detect the misclassifications of the landmarks in order to fuse only reliable information. The orientation given by the optical symbol recognition (OSR) algorithm is used to improve significantly the odometry and the recognition of the landmarks is used to reference the odometry to a absolute coordinate system. The system was tested using a 3D motion capture system. With the actual mat configuration, in a field of motion of 710 × 450 mm, the maximum error in position estimation was 49.61 mm with an average error of 36.70 ± 22.50 mm. The average test duration was 36.5 seconds and the average path length was 4173 mm.

Mobile/android application for QRS detection using zero cross method

NASA Astrophysics Data System (ADS)

Rizqyawan, M. I.; Simbolon, A. I.; Suhendra, M. A.; Amri, M. F.; Kusumandari, D. E.

2018-03-01

In automatic ECG signal processing, one of the main topics of research is QRS complex detection. Detecting correct QRS complex or R peak is important since it is used to measure several other ECG metrics. One of the robust methods for QRS detection is Zero Cross method. This method uses an addition of high-frequency signal and zero crossing count to detect QRS complex which has a low-frequency oscillation. This paper presents an application of QRS detection using Zero Cross algorithm in the Android-based system. The performance of the algorithm in the mobile environment is measured. The result shows that this method is suitable for real-time QRS detection in a mobile application.

Fast T Wave Detection Calibrated by Clinical Knowledge with Annotation of P and T Waves

PubMed Central

Elgendi, Mohamed; Eskofier, Bjoern; Abbott, Derek

2015-01-01

Background There are limited studies on the automatic detection of T waves in arrhythmic electrocardiogram (ECG) signals. This is perhaps because there is no available arrhythmia dataset with annotated T waves. There is a growing need to develop numerically-efficient algorithms that can accommodate the new trend of battery-driven ECG devices. Moreover, there is also a need to analyze long-term recorded signals in a reliable and time-efficient manner, therefore improving the diagnostic ability of mobile devices and point-of-care technologies. Methods Here, the T wave annotation of the well-known MIT-BIH arrhythmia database is discussed and provided. Moreover, a simple fast method for detecting T waves is introduced. A typical T wave detection method has been reduced to a basic approach consisting of two moving averages and dynamic thresholds. The dynamic thresholds were calibrated using four clinically known types of sinus node response to atrial premature depolarization (compensation, reset, interpolation, and reentry). Results The determination of T wave peaks is performed and the proposed algorithm is evaluated on two well-known databases, the QT and MIT-BIH Arrhythmia databases. The detector obtained a sensitivity of 97.14% and a positive predictivity of 99.29% over the first lead of the validation databases (total of 221,186 beats). Conclusions We present a simple yet very reliable T wave detection algorithm that can be potentially implemented on mobile battery-driven devices. In contrast to complex methods, it can be easily implemented in a digital filter design. PMID:26197321

Edge-Based Efficient Search over Encrypted Data Mobile Cloud Storage

PubMed Central

Liu, Fang; Cai, Zhiping; Xiao, Nong; Zhao, Ziming

2018-01-01

Smart sensor-equipped mobile devices sense, collect, and process data generated by the edge network to achieve intelligent control, but such mobile devices usually have limited storage and computing resources. Mobile cloud storage provides a promising solution owing to its rich storage resources, great accessibility, and low cost. But it also brings a risk of information leakage. The encryption of sensitive data is the basic step to resist the risk. However, deploying a high complexity encryption and decryption algorithm on mobile devices will greatly increase the burden of terminal operation and the difficulty to implement the necessary privacy protection algorithm. In this paper, we propose ENSURE (EfficieNt and SecURE), an efficient and secure encrypted search architecture over mobile cloud storage. ENSURE is inspired by edge computing. It allows mobile devices to offload the computation intensive task onto the edge server to achieve a high efficiency. Besides, to protect data security, it reduces the information acquisition of untrusted cloud by hiding the relevance between query keyword and search results from the cloud. Experiments on a real data set show that ENSURE reduces the computation time by 15% to 49% and saves the energy consumption by 38% to 69% per query. PMID:29652810

Edge-Based Efficient Search over Encrypted Data Mobile Cloud Storage.

PubMed

Guo, Yeting; Liu, Fang; Cai, Zhiping; Xiao, Nong; Zhao, Ziming

2018-04-13

Smart sensor-equipped mobile devices sense, collect, and process data generated by the edge network to achieve intelligent control, but such mobile devices usually have limited storage and computing resources. Mobile cloud storage provides a promising solution owing to its rich storage resources, great accessibility, and low cost. But it also brings a risk of information leakage. The encryption of sensitive data is the basic step to resist the risk. However, deploying a high complexity encryption and decryption algorithm on mobile devices will greatly increase the burden of terminal operation and the difficulty to implement the necessary privacy protection algorithm. In this paper, we propose ENSURE (EfficieNt and SecURE), an efficient and secure encrypted search architecture over mobile cloud storage. ENSURE is inspired by edge computing. It allows mobile devices to offload the computation intensive task onto the edge server to achieve a high efficiency. Besides, to protect data security, it reduces the information acquisition of untrusted cloud by hiding the relevance between query keyword and search results from the cloud. Experiments on a real data set show that ENSURE reduces the computation time by 15% to 49% and saves the energy consumption by 38% to 69% per query.

Truncated Lévy flights and agenda-based mobility are useful for the assessment of personal human exposure.

PubMed

Schlink, Uwe; Ragas, Ad M J

2011-01-01

Receptor-oriented approaches can assess the individual-specific exposure to air pollution. In such an individual-based model we analyse the impact of human mobility to the personal exposure that is perceived by individuals simulated in an exemplified urban area. The mobility models comprise random walk (reference point mobility, RPM), truncated Lévy flights (TLF), and agenda-based walk (RPMA). We describe and review the general concepts and provide an inter-comparison of these concepts. Stationary and ergodic behaviour are explained and applied as well as performance criteria for a comparative evaluation of the investigated algorithms. We find that none of the studied algorithm results in purely random trajectories. TLF and RPMA prove to be suitable for human mobility modelling, because they provide conditions for very individual-specific trajectories and exposure. Suggesting these models we demonstrate the plausibility of their results for exposure to air-borne benzene and the combined exposure to benzene and nonane. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multilayer Statistical Intrusion Detection in Wireless Networks

NASA Astrophysics Data System (ADS)

Hamdi, Mohamed; Meddeb-Makhlouf, Amel; Boudriga, Noureddine

2008-12-01

The rapid proliferation of mobile applications and services has introduced new vulnerabilities that do not exist in fixed wired networks. Traditional security mechanisms, such as access control and encryption, turn out to be inefficient in modern wireless networks. Given the shortcomings of the protection mechanisms, an important research focuses in intrusion detection systems (IDSs). This paper proposes a multilayer statistical intrusion detection framework for wireless networks. The architecture is adequate to wireless networks because the underlying detection models rely on radio parameters and traffic models. Accurate correlation between radio and traffic anomalies allows enhancing the efficiency of the IDS. A radio signal fingerprinting technique based on the maximal overlap discrete wavelet transform (MODWT) is developed. Moreover, a geometric clustering algorithm is presented. Depending on the characteristics of the fingerprinting technique, the clustering algorithm permits to control the false positive and false negative rates. Finally, simulation experiments have been carried out to validate the proposed IDS.

A Reinforcement Sensor Embedded Vertical Handoff Controller for Vehicular Heterogeneous Wireless Networks

PubMed Central

Li, Limin; Xu, Yubin; Soong, Boon-Hee; Ma, Lin

2013-01-01

Vehicular communication platforms that provide real-time access to wireless networks have drawn more and more attention in recent years. IEEE 802.11p is the main radio access technology that supports communication for high mobility terminals, however, due to its limited coverage, IEEE 802.11p is usually deployed by coupling with cellular networks to achieve seamless mobility. In a heterogeneous cellular/802.11p network, vehicular communication is characterized by its short time span in association with a wireless local area network (WLAN). Moreover, for the media access control (MAC) scheme used for WLAN, the network throughput dramatically decreases with increasing user quantity. In response to these compelling problems, we propose a reinforcement sensor (RFS) embedded vertical handoff control strategy to support mobility management. The RFS has online learning capability and can provide optimal handoff decisions in an adaptive fashion without prior knowledge. The algorithm integrates considerations including vehicular mobility, traffic load, handoff latency, and network status. Simulation results verify that the proposed algorithm can adaptively adjust the handoff strategy, allowing users to stay connected to the best network. Furthermore, the algorithm can ensure that RSUs are adequate, thereby guaranteeing a high quality user experience. PMID:24193101

Dynamic optical resource allocation for mobile core networks with software defined elastic optical networking.

PubMed

Zhao, Yongli; Chen, Zhendong; Zhang, Jie; Wang, Xinbo

2016-07-25

Driven by the forthcoming of 5G mobile communications, the all-IP architecture of mobile core networks, i.e. evolved packet core (EPC) proposed by 3GPP, has been greatly challenged by the users' demands for higher data rate and more reliable end-to-end connection, as well as operators' demands for low operational cost. These challenges can be potentially met by software defined optical networking (SDON), which enables dynamic resource allocation according to the users' requirement. In this article, a novel network architecture for mobile core network is proposed based on SDON. A software defined network (SDN) controller is designed to realize the coordinated control over different entities in EPC networks. We analyze the requirement of EPC-lightpath (EPCL) in data plane and propose an optical switch load balancing (OSLB) algorithm for resource allocation in optical layer. The procedure of establishment and adjustment of EPCLs is demonstrated on a SDON-based EPC testbed with extended OpenFlow protocol. We also evaluate the OSLB algorithm through simulation in terms of bandwidth blocking ratio, traffic load distribution, and resource utilization ratio compared with link-based load balancing (LLB) and MinHops algorithms.

Dynamic Task Allocation in Multi-Hop Multimedia Wireless Sensor Networks with Low Mobility

PubMed Central

Jin, Yichao; Vural, Serdar; Gluhak, Alexander; Moessner, Klaus

2013-01-01

This paper presents a task allocation-oriented framework to enable efficient in-network processing and cost-effective multi-hop resource sharing for dynamic multi-hop multimedia wireless sensor networks with low node mobility, e.g., pedestrian speeds. The proposed system incorporates a fast task reallocation algorithm to quickly recover from possible network service disruptions, such as node or link failures. An evolutional self-learning mechanism based on a genetic algorithm continuously adapts the system parameters in order to meet the desired application delay requirements, while also achieving a sufficiently long network lifetime. Since the algorithm runtime incurs considerable time delay while updating task assignments, we introduce an adaptive window size to limit the delay periods and ensure an up-to-date solution based on node mobility patterns and device processing capabilities. To the best of our knowledge, this is the first study that yields multi-objective task allocation in a mobile multi-hop wireless environment under dynamic conditions. Simulations are performed in various settings, and the results show considerable performance improvement in extending network lifetime compared to heuristic mechanisms. Furthermore, the proposed framework provides noticeable reduction in the frequency of missing application deadlines. PMID:24135992

Link Scheduling Algorithm with Interference Prediction for Multiple Mobile WBANs

PubMed Central

Le, Thien T. T.

2017-01-01

As wireless body area networks (WBANs) become a key element in electronic healthcare (e-healthcare) systems, the coexistence of multiple mobile WBANs is becoming an issue. The network performance is negatively affected by the unpredictable movement of the human body. In such an environment, inter-WBAN interference can be caused by the overlapping transmission range of nearby WBANs. We propose a link scheduling algorithm with interference prediction (LSIP) for multiple mobile WBANs, which allows multiple mobile WBANs to transmit at the same time without causing inter-WBAN interference. In the LSIP, a superframe includes the contention access phase using carrier sense multiple access with collision avoidance (CSMA/CA) and the scheduled phase using time division multiple access (TDMA) for non-interfering nodes and interfering nodes, respectively. For interference prediction, we define a parameter called interference duration as the duration during which disparate WBANs interfere with each other. The Bayesian model is used to estimate and classify the interference using a signal to interference plus noise ratio (SINR) and the number of neighboring WBANs. The simulation results show that the proposed LSIP algorithm improves the packet delivery ratio and throughput significantly with acceptable delay. PMID:28956827

Path planning for mobile robot using the novel repulsive force algorithm

NASA Astrophysics Data System (ADS)

Sun, Siyue; Yin, Guoqiang; Li, Xueping

2018-01-01

A new type of repulsive force algorithm is proposed to solve the problem of local minimum and the target unreachable of the classic Artificial Potential Field (APF) method in this paper. The Gaussian function that is related to the distance between the robot and the target is added to the traditional repulsive force, solving the problem of the goal unreachable with the obstacle nearby; variable coefficient is added to the repulsive force component to resize the repulsive force, which can solve the local minimum problem when the robot, the obstacle and the target point are in the same line. The effectiveness of the algorithm is verified by simulation based on MATLAB and actual mobile robot platform.

On data processing required to derive mobility patterns from passively-generated mobile phone data

PubMed Central

Wang, Feilong; Chen, Cynthia

2018-01-01

Passively-generated mobile phone data is emerging as a potential data source for transportation research and applications. Despite the large amount of studies based on the mobile phone data, only a few have reported the properties of such data, and documented how they have processed the data. In this paper, we describe two types of common mobile phone data: Call Details Record (CDR) data and sightings data, and propose a data processing framework and the associated algorithms to address two key issues associated with the sightings data: locational uncertainty and oscillation. We show the effectiveness of our proposed methods in addressing these two issues compared to the state of art algorithms in the field. We also demonstrate that without proper processing applied to the data, the statistical regularity of human mobility patterns—a key, significant trait identified for human mobility—is over-estimated. We hope this study will stimulate more studies in examining the properties of such data and developing methods to address them. Though not as glamorous as those directly deriving insights on mobility patterns (such as statistical regularity), understanding properties of such data and developing methods to address them is a fundamental research topic on which important insights are derived on mobility patterns. PMID:29398790

Revisiting QRS detection methodologies for portable, wearable, battery-operated, and wireless ECG systems.

PubMed

Elgendi, Mohamed; Eskofier, Björn; Dokos, Socrates; Abbott, Derek

2014-01-01

Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices.

Revisiting QRS Detection Methodologies for Portable, Wearable, Battery-Operated, and Wireless ECG Systems

PubMed Central

Elgendi, Mohamed; Eskofier, Björn; Dokos, Socrates; Abbott, Derek

2014-01-01

Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices. PMID:24409290

Cooperative mobile agents search using beehive partitioned structure and Tabu Random search algorithm

NASA Astrophysics Data System (ADS)

Ramazani, Saba; Jackson, Delvin L.; Selmic, Rastko R.

2013-05-01

In search and surveillance operations, deploying a team of mobile agents provides a robust solution that has multiple advantages over using a single agent in efficiency and minimizing exploration time. This paper addresses the challenge of identifying a target in a given environment when using a team of mobile agents by proposing a novel method of mapping and movement of agent teams in a cooperative manner. The approach consists of two parts. First, the region is partitioned into a hexagonal beehive structure in order to provide equidistant movements in every direction and to allow for more natural and flexible environment mapping. Additionally, in search environments that are partitioned into hexagons, mobile agents have an efficient travel path while performing searches due to this partitioning approach. Second, we use a team of mobile agents that move in a cooperative manner and utilize the Tabu Random algorithm to search for the target. Due to the ever-increasing use of robotics and Unmanned Aerial Vehicle (UAV) platforms, the field of cooperative multi-agent search has developed many applications recently that would benefit from the use of the approach presented in this work, including: search and rescue operations, surveillance, data collection, and border patrol. In this paper, the increased efficiency of the Tabu Random Search algorithm method in combination with hexagonal partitioning is simulated, analyzed, and advantages of this approach are presented and discussed.

Analysis of Sources of Large Positioning Errors in Deterministic Fingerprinting

PubMed Central

2017-01-01

Wi-Fi fingerprinting is widely used for indoor positioning and indoor navigation due to the ubiquity of wireless networks, high proliferation of Wi-Fi-enabled mobile devices, and its reasonable positioning accuracy. The assumption is that the position can be estimated based on the received signal strength intensity from multiple wireless access points at a given point. The positioning accuracy, within a few meters, enables the use of Wi-Fi fingerprinting in many different applications. However, it has been detected that the positioning error might be very large in a few cases, which might prevent its use in applications with high accuracy positioning requirements. Hybrid methods are the new trend in indoor positioning since they benefit from multiple diverse technologies (Wi-Fi, Bluetooth, and Inertial Sensors, among many others) and, therefore, they can provide a more robust positioning accuracy. In order to have an optimal combination of technologies, it is crucial to identify when large errors occur and prevent the use of extremely bad positioning estimations in hybrid algorithms. This paper investigates why large positioning errors occur in Wi-Fi fingerprinting and how to detect them by using the received signal strength intensities. PMID:29186921

Robust and Cost-Efficient Communication Based on SNMP in Mobile Networks

NASA Astrophysics Data System (ADS)

Ryu, Sang-Hoon; Baik, Doo-Kwon

A main challenge in the design of this mobile network is the development of dynamic routing protocols that can efficiently find routes between two communicating nodes. Multimedia streaming services are receiving considerable interest in the mobile network business. An entire mobile network may change its point of attachment to the Internet. The mobile network is operated by a basic specification to support network mobility called Network Mobility (NEMO) Basic Support. However, NEMO basic Support mechanism has some problem in continuous communication. In this paper, we propose robust and cost-efficient algorithm. And we simulate proposed method and conclude some remarks.

Using In Silico Fragmentation to Improve Routine Residue Screening in Complex Matrices.

PubMed

Kaufmann, Anton; Butcher, Patrick; Maden, Kathryn; Walker, Stephan; Widmer, Mirjam

2017-12-01

Targeted residue screening requires the use of reference substances in order to identify potential residues. This becomes a difficult issue when using multi-residue methods capable of analyzing several hundreds of analytes. Therefore, the capability of in silico fragmentation based on a structure database ("suspect screening") instead of physical reference substances for routine targeted residue screening was investigated. The detection of fragment ions that can be predicted or explained by in silico software was utilized to reduce the number of false positives. These "proof of principle" experiments were done with a tool that is integrated into a commercial MS vendor instrument operating software (UNIFI) as well as with a platform-independent MS tool (Mass Frontier). A total of 97 analytes belonging to different chemical families were separated by reversed phase liquid chromatography and detected in a data-independent acquisition (DIA) mode using ion mobility hyphenated with quadrupole time of flight mass spectrometry. The instrument was operated in the MS E mode with alternating low and high energy traces. The fragments observed from product ion spectra were investigated using a "chopping" bond disconnection algorithm and a rule-based algorithm. The bond disconnection algorithm clearly explained more analyte product ions and a greater percentage of the spectral abundance than the rule-based software (92 out of the 97 compounds produced ≥1 explainable fragment ions). On the other hand, tests with a complex blank matrix (bovine liver extract) indicated that the chopping algorithm reports significantly more false positive fragments than the rule based software. Graphical Abstract.

Using In Silico Fragmentation to Improve Routine Residue Screening in Complex Matrices

NASA Astrophysics Data System (ADS)

Kaufmann, Anton; Butcher, Patrick; Maden, Kathryn; Walker, Stephan; Widmer, Mirjam

2017-12-01

Targeted residue screening requires the use of reference substances in order to identify potential residues. This becomes a difficult issue when using multi-residue methods capable of analyzing several hundreds of analytes. Therefore, the capability of in silico fragmentation based on a structure database ("suspect screening") instead of physical reference substances for routine targeted residue screening was investigated. The detection of fragment ions that can be predicted or explained by in silico software was utilized to reduce the number of false positives. These "proof of principle" experiments were done with a tool that is integrated into a commercial MS vendor instrument operating software (UNIFI) as well as with a platform-independent MS tool (Mass Frontier). A total of 97 analytes belonging to different chemical families were separated by reversed phase liquid chromatography and detected in a data-independent acquisition (DIA) mode using ion mobility hyphenated with quadrupole time of flight mass spectrometry. The instrument was operated in the MSE mode with alternating low and high energy traces. The fragments observed from product ion spectra were investigated using a "chopping" bond disconnection algorithm and a rule-based algorithm. The bond disconnection algorithm clearly explained more analyte product ions and a greater percentage of the spectral abundance than the rule-based software (92 out of the 97 compounds produced ≥1 explainable fragment ions). On the other hand, tests with a complex blank matrix (bovine liver extract) indicated that the chopping algorithm reports significantly more false positive fragments than the rule based software. [Figure not available: see fulltext.

Secure and Efficient Signature Scheme Based on NTRU for Mobile Payment

NASA Astrophysics Data System (ADS)

Xia, Yunhao; You, Lirong; Sun, Zhe; Sun, Zhixin

2017-10-01

Mobile payment becomes more and more popular, however the traditional public-key encryption algorithm has higher requirements for hardware which is not suitable for mobile terminals of limited computing resources. In addition, these public-key encryption algorithms do not have the ability of anti-quantum computing. This paper researches public-key encryption algorithm NTRU for quantum computation through analyzing the influence of parameter q and k on the probability of generating reasonable signature value. Two methods are proposed to improve the probability of generating reasonable signature value. Firstly, increase the value of parameter q. Secondly, add the authentication condition that meet the reasonable signature requirements during the signature phase. Experimental results show that the proposed signature scheme can realize the zero leakage of the private key information of the signature value, and increase the probability of generating the reasonable signature value. It also improve rate of the signature, and avoid the invalid signature propagation in the network, but the scheme for parameter selection has certain restrictions.

Training Toddlers Seated on Mobile Robots to Steer Using Force-Feedback Joystick.

PubMed

Agrawal, S K; Xi Chen; Ragonesi, C; Galloway, J C

2012-01-01

The broader goal of our research is to train infants with special needs to safely and purposefully drive a mobile robot to explore the environment. The hypothesis is that these impaired infants will benefit from mobility in their early years and attain childhood milestones, similar to their healthy peers. In this paper, we present an algorithm and training method using a force-feedback joystick with an "assist-as-needed" paradigm for driving training. In this "assist-as-needed" approach, if the child steers the joystick outside a force tunnel centered on the desired direction, the driver experiences a bias force on the hand. We show results with a group study on typically developing toddlers that such a haptic guidance algorithm is superior to training with a conventional joystick. We also provide a case study on two special needs children, under three years old, who learn to make sharp turns during driving, when trained over a five-day period with the force-feedback joystick using the algorithm.

Multi-Objective Constraint Satisfaction for Mobile Robot Area Defense

DTIC Science & Technology

2010-03-01

17 NSGA-II non-dominated sorting genetic algorithm II . . . . . . . . . . . . . . . . . . . 17 jMetal Metaheuristic Algorithms in...to alert the other agents and ensure trust in the system. This research presents an algorithm that tasks robots to meet the two specific goals of...problem is defined as a constraint satisfaction problem solved using the Non-dominated Sorting Genetic Algorithm II (NSGA-II). Both goals of

Energy minimization of mobile video devices with a hardware H.264/AVC encoder based on energy-rate-distortion optimization

NASA Astrophysics Data System (ADS)

Kang, Donghun; Lee, Jungeon; Jung, Jongpil; Lee, Chul-Hee; Kyung, Chong-Min

2014-09-01

In mobile video systems powered by battery, reducing the encoder's compression energy consumption is critical to prolong its lifetime. Previous Energy-rate-distortion (E-R-D) optimization methods based on a software codec is not suitable for practical mobile camera systems because the energy consumption is too large and encoding rate is too low. In this paper, we propose an E-R-D model for the hardware codec based on the gate-level simulation framework to measure the switching activity and the energy consumption. From the proposed E-R-D model, an energy minimizing algorithm for mobile video camera sensor have been developed with the GOP (Group of Pictures) size and QP(Quantization Parameter) as run-time control variables. Our experimental results show that the proposed algorithm provides up to 31.76% of energy consumption saving while satisfying the rate and distortion constraints.

Self-deployable mobile sensor networks for on-demand surveillance

NASA Astrophysics Data System (ADS)

Miao, Lidan; Qi, Hairong; Wang, Feiyi

2005-05-01

This paper studies two interconnected problems in mobile sensor network deployment, the optimal placement of heterogeneous mobile sensor platforms for cost-efficient and reliable coverage purposes, and the self-organizable deployment. We first develop an optimal placement algorithm based on a "mosaicked technology" such that different types of mobile sensors form a mosaicked pattern uniquely determined by the popularity of different types of sensor nodes. The initial state is assumed to be random. In order to converge to the optimal state, we investigate the swarm intelligence (SI)-based sensor movement strategy, through which the randomly deployed sensors can self-organize themselves to reach the optimal placement state. The proposed algorithm is compared with the random movement and the centralized method using performance metrics such as network coverage, convergence time, and energy consumption. Simulation results are presented to demonstrate the effectiveness of the mosaic placement and the SI-based movement.

Location-Based Augmented Reality for Mobile Learning: Algorithm, System, and Implementation

ERIC Educational Resources Information Center

Tan, Qing; Chang, William; Kinshuk

2015-01-01

AR technology can be considered as mainly consisting of two aspects: identification of real-world object and display of computer-generated digital contents related the identified real-world object. The technical challenge of mobile AR is to identify the real-world object that mobile device's camera aim at. In this paper, we will present a…

Algorithmic Skin: Health-Tracking Technologies, Personal Analytics and the Biopedagogies of Digitized Health and Physical Education

ERIC Educational Resources Information Center

Williamson, Ben

2015-01-01

The emergence of digitized health and physical education, or "eHPE", embeds software algorithms in the organization of health and physical education pedagogies. Particularly with the emergence of wearable and mobile activity trackers, biosensors and personal analytics apps, algorithmic processes have an increasingly powerful part to play…

Navigable points estimation for mobile robots using binary image skeletonization

NASA Astrophysics Data System (ADS)

Martinez S., Fernando; Jacinto G., Edwar; Montiel A., Holman

2017-02-01

This paper describes the use of image skeletonization for the estimation of all the navigable points, inside a scene of mobile robots navigation. Those points are used for computing a valid navigation path, using standard methods. The main idea is to find the middle and the extreme points of the obstacles in the scene, taking into account the robot size, and create a map of navigable points, in order to reduce the amount of information for the planning algorithm. Those points are located by means of the skeletonization of a binary image of the obstacles and the scene background, along with some other digital image processing algorithms. The proposed algorithm automatically gives a variable number of navigable points per obstacle, depending on the complexity of its shape. As well as, the way how the algorithm can change some of their parameters in order to change the final number of the resultant key points is shown. The results shown here were obtained applying different kinds of digital image processing algorithms on static scenes.

Obstacle Detection in Indoor Environment for Visually Impaired Using Mobile Camera

NASA Astrophysics Data System (ADS)

Rahman, Samiur; Ullah, Sana; Ullah, Sehat

2018-01-01

Obstacle detection can improve the mobility as well as the safety of visually impaired people. In this paper, we present a system using mobile camera for visually impaired people. The proposed algorithm works in indoor environment and it uses a very simple technique of using few pre-stored floor images. In indoor environment all unique floor types are considered and a single image is stored for each unique floor type. These floor images are considered as reference images. The algorithm acquires an input image frame and then a region of interest is selected and is scanned for obstacle using pre-stored floor images. The algorithm compares the present frame and the next frame and compute mean square error of the two frames. If mean square error is less than a threshold value α then it means that there is no obstacle in the next frame. If mean square error is greater than α then there are two possibilities; either there is an obstacle or the floor type is changed. In order to check if the floor is changed, the algorithm computes mean square error of next frame and all stored floor types. If minimum of mean square error is less than a threshold value α then flour is changed otherwise there exist an obstacle. The proposed algorithm works in real-time and 96% accuracy has been achieved.

Retrieval Algorithms for Road Surface Modelling Using Laser-Based Mobile Mapping.

PubMed

Jaakkola, Anttoni; Hyyppä, Juha; Hyyppä, Hannu; Kukko, Antero

2008-09-01

Automated processing of the data provided by a laser-based mobile mapping system will be a necessity due to the huge amount of data produced. In the future, vehiclebased laser scanning, here called mobile mapping, should see considerable use for road environment modelling. Since the geometry of the scanning and point density is different from airborne laser scanning, new algorithms are needed for information extraction. In this paper, we propose automatic methods for classifying the road marking and kerbstone points and modelling the road surface as a triangulated irregular network. On the basis of experimental tests, the mean classification accuracies obtained using automatic method for lines, zebra crossings and kerbstones were 80.6%, 92.3% and 79.7%, respectively.

NASA Satellite Monitoring of Water Clarity in Mobile Bay for Nutrient Criteria Development

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Holekamp, Kara; Spiering, Bruce A.

2009-01-01

This project has demonstrated feasibility of deriving from MODIS daily measurements time series of water clarity parameters that provide coverage of a specific location or an area of interest for 30-50% of days. Time series derived for estuarine and coastal waters display much higher variability than time series of ecological parameters (such as vegetation indices) derived for land areas. (Temporal filtering often applied in terrestrial studies cannot be used effectively in ocean color processing). IOP-based algorithms for retrieval of diffuse light attenuation coefficient and TSS concentration perform well for the Mobile Bay environment: only a minor adjustment was needed in the TSS algorithm, despite generally recognized dependence of such algorithms on local conditions. The current IOP-based algorithm for retrieval of chlorophyll a concentration has not performed as well: a more reliable algorithm is needed that may be based on IOPs at additional wavelengths or on remote sensing reflectance from multiple spectral bands. CDOM algorithm also needs improvement to provide better separation between effects of gilvin (gelbstoff) and detritus. (Identification or development of such algorithm requires more data from in situ measurements of CDOM concentration in Gulf of Mexico coastal waters (ongoing collaboration with the EPA Gulf Ecology Division))

NLOS mitigation and ranging accuracy for building indoor positioning system in UWB using commercial radio modules

NASA Astrophysics Data System (ADS)

Alsudani, Ahlam

2018-05-01

In recent years, indoor positioning system (IPS) plays a very important role in several environments such as hospitals, airports, males, Etc. It is used to locate mobile stations such as human and robots inside buildings. Some of IPSs applications are: locating an elder or child needed for an urgent help in hospitals, emergency situations such as locating firefighters inside building on fire or policemen fitting terrorists inside building by a commander to help for expedite evacuation in case one of them need for help. In indoor positioning applications, the accuracy should be high as can as possible, in another word; the error should be less than 1 meter. The indoor environment is the major challenging to obtain such accuracy. In this paper, we present a novel algorithm to identify the line of sight (LOS) and non-line of sight (NLOS) channels and improve the positioning accuracy using ultra-wideband (UWB) technology implementing DW1000 devices.

FD/DAMA Scheme For Mobile/Satellite Communications

NASA Technical Reports Server (NTRS)

Yan, Tsun-Yee; Wang, Charles C.; Cheng, Unjeng; Rafferty, William; Dessouky, Khaled I.

1992-01-01

Integrated-Adaptive Mobile Access Protocol (I-AMAP) proposed to allocate communication channels to subscribers in first-generation MSAT-X mobile/satellite communication network. Based on concept of frequency-division/demand-assigned multiple access (FD/DAMA) where partition of available spectrum adapted to subscribers' demands for service. Requests processed, and competing requests resolved according to channel-access protocol, or free-access tree algorithm described in "Connection Protocol for Mobile/Satellite Communications" (NPO-17735). Assigned spectrum utilized efficiently.

EV Charging Algorithm Implementation with User Price Preference

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

Wang, Bin; Hu, Boyang; Qiu, Charlie

2015-02-17

in this paper, we propose and implement a smart Electric Vehicle (EV) charging algorithm to control the EV charging infrastructures according to users’ price preferences. EVSE (Electric Vehicle Supply Equipment), equipped with bidirectional communication devices and smart meters, can be remotely monitored by the proposed charging algorithm applied to EV control center and mobile app. On the server side, ARIMA model is utilized to fit historical charging load data and perform day-ahead prediction. A pricing strategy with energy bidding policy is proposed and implemented to generate a charging price list to be broadcasted to EV users through mobile app. Onmore » the user side, EV drivers can submit their price preferences and daily travel schedules to negotiate with Control Center to consume the expected energy and minimize charging cost simultaneously. The proposed algorithm is tested and validated through the experimental implementations in UCLA parking lots.« less

Optimal path planning for a mobile robot using cuckoo search algorithm

NASA Astrophysics Data System (ADS)

Mohanty, Prases K.; Parhi, Dayal R.

2016-03-01

The shortest/optimal path planning is essential for efficient operation of autonomous vehicles. In this article, a new nature-inspired meta-heuristic algorithm has been applied for mobile robot path planning in an unknown or partially known environment populated by a variety of static obstacles. This meta-heuristic algorithm is based on the levy flight behaviour and brood parasitic behaviour of cuckoos. A new objective function has been formulated between the robots and the target and obstacles, which satisfied the conditions of obstacle avoidance and target-seeking behaviour of robots present in the terrain. Depending upon the objective function value of each nest (cuckoo) in the swarm, the robot avoids obstacles and proceeds towards the target. The smooth optimal trajectory is framed with this algorithm when the robot reaches its goal. Some simulation and experimental results are presented at the end of the paper to show the effectiveness of the proposed navigational controller.

An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones.

PubMed

Li, Huaiyu; Chen, Xiuwan; Jing, Guifei; Wang, Yuan; Cao, Yanfeng; Li, Fei; Zhang, Xinlong; Xiao, Han

2015-12-11

Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel "quasi-dynamic" Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the "process-level" fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move.

Implementation and Evaluation of a Mobile Mapping System Based on Integrated Range and Intensity Images for Traffic Signs Localization

NASA Astrophysics Data System (ADS)

Shahbazi, M.; Sattari, M.; Homayouni, S.; Saadatseresht, M.

2012-07-01

Recent advances in positioning techniques have made it possible to develop Mobile Mapping Systems (MMS) for detection and 3D localization of various objects from a moving platform. On the other hand, automatic traffic sign recognition from an equipped mobile platform has recently been a challenging issue for both intelligent transportation and municipal database collection. However, there are several inevitable problems coherent to all the recognition methods completely relying on passive chromatic or grayscale images. This paper presents the implementation and evaluation of an operational MMS. Being distinct from the others, the developed MMS comprises one range camera based on Photonic Mixer Device (PMD) technology and one standard 2D digital camera. The system benefits from certain algorithms to detect, recognize and localize the traffic signs by fusing the shape, color and object information from both range and intensity images. As the calibrating stage, a self-calibration method based on integrated bundle adjustment via joint setup with the digital camera is applied in this study for PMD camera calibration. As the result, an improvement of 83 % in RMS of range error and 72 % in RMS of coordinates residuals for PMD camera, over that achieved with basic calibration is realized in independent accuracy assessments. Furthermore, conventional photogrammetric techniques based on controlled network adjustment are utilized for platform calibration. Likewise, the well-known Extended Kalman Filtering (EKF) is applied to integrate the navigation sensors, namely GPS and INS. The overall acquisition system along with the proposed techniques leads to 90 % true positive recognition and the average of 12 centimetres 3D positioning accuracy.

Implementation and Evaluation of a Mobile Mapping System Based on Integrated Range and Intensity Images for Traffic Signs Localization

NASA Astrophysics Data System (ADS)

Shahbazi, M.; Sattari, M.; Homayouni, S.; Saadatseresht, M.

2012-07-01

Recent advances in positioning techniques have made it possible to develop Mobile Mapping Systems (MMS) for detection and 3D localization of various objects from a moving platform. On the other hand, automatic traffic sign recognition from an equipped mobile platform has recently been a challenging issue for both intelligent transportation and municipal database collection. However, there are several inevitable problems coherent to all the recognition methods completely relying on passive chromatic or grayscale images. This paper presents the implementation and evaluation of an operational MMS. Being distinct from the others, the developed MMS comprises one range camera based on Photonic Mixer Device (PMD) technology and one standard 2D digital camera. The system benefits from certain algorithms to detect, recognize and localize the traffic signs by fusing the shape, color and object information from both range and intensity images. As the calibrating stage, a self-calibration method based on integrated bundle adjustment via joint setup with the digital camera is applied in this study for PMD camera calibration. As the result, an improvement of 83% in RMS of range error and 72% in RMS of coordinates residuals for PMD camera, over that achieved with basic calibration is realized in independent accuracy assessments. Furthermore, conventional photogrammetric techniques based on controlled network adjustment are utilized for platform calibration. Likewise, the well-known Extended Kalman Filtering (EKF) is applied to integrate the navigation sensors, namely GPS and INS. The overall acquisition system along with the proposed techniques leads to 90% true positive recognition and the average of 12 centimetres 3D positioning accuracy.

Light-weight cyptography for resource constrained environments

NASA Astrophysics Data System (ADS)

Baier, Patrick; Szu, Harold

2006-04-01

We give a survey of "light-weight" encryption algorithms designed to maximise security within tight resource constraints (limited memory, power consumption, processor speed, chip area, etc.) The target applications of such algorithms are RFIDs, smart cards, mobile phones, etc., which may store, process and transmit sensitive data, but at the same time do not always support conventional strong algorithms. A survey of existing algorithms is given and new proposal is introduced.

Use of a Designed Peptide Array To Infer Dissociation Trends for Nontryptic Peptides in Quadrupole Ion Trap and Quadrupole Time-of-Flight Mass Spectrometry

DOE PAGES

Gaucher, Sara P.; Morrow, Jeffrey A.; Faulon, Jean-Loup M.

2007-09-14

Observed peptide gas-phase fragmentation patterns are a complex function of many variables. In order to systematically probe this phenomenon, an array of 40 peptides was synthesized for study. The array of sequences was designed to hold certain variables (peptide length) constant and randomize or balance others (peptide amino acid distribution and position). A high-quality tandem mass spectrometry (MS/MS) data set was acquired for each peptide for all observed charge states on multiple MS instruments, quadrupole-time-of-flight and quadrupole ion trap. The data were analyzed as a function of total charge state and number of mobile protons. Previously known dissociation trends weremore » observed, validating our approach. In addition, the general influence of basic amino acids on dissociation could be determined because, in contrast to the more widely studied tryptic peptides, the amino acids H, K, and R were positionally distributed. Interestingly, our results suggest that cleavage at all basic amino acids is suppressed when a mobile proton is available. Cleavage at H becomes favored only under conditions where a partially mobile proton is present, a caveat to the previously reported trend of enhanced cleavage at H. In conclusion, all acquired data were used as a benchmark to determine how well these sequences would have been identified in a database search using a common algorithm, Mascot.« less

SLAM algorithm applied to robotics assistance for navigation in unknown environments

PubMed Central

2010-01-01

Background The combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or user's preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI). Methods In this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robot's movements can be adapted to the patient's disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robot's collisions with the environment and moving agents. Results The entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface. Conclusions The integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation. PMID:20163735

Classification of Odours for Mobile Robots Using an Ensemble of Linear Classifiers

NASA Astrophysics Data System (ADS)

Trincavelli, Marco; Coradeschi, Silvia; Loutfi, Amy

2009-05-01

This paper investigates the classification of odours using an electronic nose mounted on a mobile robot. The samples are collected as the robot explores the environment. Under such conditions, the sensor response differs from typical three phase sampling processes. In this paper, we focus particularly on the classification problem and how it is influenced by the movement of the robot. To cope with these influences, an algorithm consisting of an ensemble of classifiers is presented. Experimental results show that this algorithm increases classification performance compared to other traditional classification methods.

Situational awareness for unmanned ground vehicles in semi-structured environments

NASA Astrophysics Data System (ADS)

Goodsell, Thomas G.; Snorrason, Magnus; Stevens, Mark R.

2002-07-01

Situational Awareness (SA) is a critical component of effective autonomous vehicles, reducing operator workload and allowing an operator to command multiple vehicles or simultaneously perform other tasks. Our Scene Estimation & Situational Awareness Mapping Engine (SESAME) provides SA for mobile robots in semi-structured scenes, such as parking lots and city streets. SESAME autonomously builds volumetric models for scene analysis. For example, a SES-AME equipped robot can build a low-resolution 3-D model of a row of cars, then approach a specific car and build a high-resolution model from a few stereo snapshots. The model can be used onboard to determine the type of car and locate its license plate, or the model can be segmented out and sent back to an operator who can view it from different viewpoints. As new views of the scene are obtained, the model is updated and changes are tracked (such as cars arriving or departing). Since the robot's position must be accurately known, SESAME also has automated techniques for deter-mining the position and orientation of the camera (and hence, robot) with respect to existing maps. This paper presents an overview of the SESAME architecture and algorithms, including our model generation algorithm.

Accelerating image recognition on mobile devices using GPGPU

NASA Astrophysics Data System (ADS)

Bordallo López, Miguel; Nykänen, Henri; Hannuksela, Jari; Silvén, Olli; Vehviläinen, Markku

2011-01-01

The future multi-modal user interfaces of battery-powered mobile devices are expected to require computationally costly image analysis techniques. The use of Graphic Processing Units for computing is very well suited for parallel processing and the addition of programmable stages and high precision arithmetic provide for opportunities to implement energy-efficient complete algorithms. At the moment the first mobile graphics accelerators with programmable pipelines are available, enabling the GPGPU implementation of several image processing algorithms. In this context, we consider a face tracking approach that uses efficient gray-scale invariant texture features and boosting. The solution is based on the Local Binary Pattern (LBP) features and makes use of the GPU on the pre-processing and feature extraction phase. We have implemented a series of image processing techniques in the shader language of OpenGL ES 2.0, compiled them for a mobile graphics processing unit and performed tests on a mobile application processor platform (OMAP3530). In our contribution, we describe the challenges of designing on a mobile platform, present the performance achieved and provide measurement results for the actual power consumption in comparison to using the CPU (ARM) on the same platform.

Radial polar histogram: obstacle avoidance and path planning for robotic cognition and motion control

NASA Astrophysics Data System (ADS)

Wang, Po-Jen; Keyawa, Nicholas R.; Euler, Craig

2012-01-01

In order to achieve highly accurate motion control and path planning for a mobile robot, an obstacle avoidance algorithm that provided a desired instantaneous turning radius and velocity was generated. This type of obstacle avoidance algorithm, which has been implemented in California State University Northridge's Intelligent Ground Vehicle (IGV), is known as Radial Polar Histogram (RPH). The RPH algorithm utilizes raw data in the form of a polar histogram that is read from a Laser Range Finder (LRF) and a camera. A desired open block is determined from the raw data utilizing a navigational heading and an elliptical approximation. The left and right most radii are determined from the calculated edges of the open block and provide the range of possible radial paths the IGV can travel through. In addition, the calculated obstacle edge positions allow the IGV to recognize complex obstacle arrangements and to slow down accordingly. A radial path optimization function calculates the best radial path between the left and right most radii and is sent to motion control for speed determination. Overall, the RPH algorithm allows the IGV to autonomously travel at average speeds of 3mph while avoiding all obstacles, with a processing time of approximately 10ms.

The prioritization of mobility improvements using a multicriteria prioritization algorithm : final report

DOT National Transportation Integrated Search

1998-07-01

A prioritization process has been prepared by the University of California, Davis, for use by the Oregon Department of Transportation (ODOT) in selecting multimodal mobility improvement projects to fund, given a budget constraint. The process involve...

Autonomous Soil Assessment System: A Data-Driven Approach to Planetary Mobility Hazard Detection

NASA Astrophysics Data System (ADS)

Raimalwala, K.; Faragalli, M.; Reid, E.

2018-04-01

The Autonomous Soil Assessment System predicts mobility hazards for rovers. Its development and performance are presented, with focus on its data-driven models, machine learning algorithms, and real-time sensor data fusion for predictive analytics.

Integrated Solution for Physical Activity Monitoring Based on Mobile Phone and PC.

PubMed

Lee, Mi Hee; Kim, Jungchae; Jee, Sun Ha; Yoo, Sun Kook

2011-03-01

This study is part of the ongoing development of treatment methods for metabolic syndrome (MS) project, which involves monitoring daily physical activity. In this study, we have focused on detecting walking activity from subjects which includes many other physical activities such as standing, sitting, lying, walking, running, and falling. Specially, we implemented an integrated solution for various physical activities monitoring using a mobile phone and PC. We put the iPod touch has built in a tri-axial accelerometer on the waist of the subjects, and measured change in acceleration signal according to change in ambulatory movement and physical activities. First, we developed of programs that are aware of step counts, velocity of walking, energy consumptions, and metabolic equivalents based on iPod. Second, we have developed the activity recognition program based on PC. iPod synchronization with PC to transmit measured data using iPhoneBrowser program. Using the implemented system, we analyzed change in acceleration signal according to the change of six activity patterns. We compared results of the step counting algorithm with different positions. The mean accuracy across these tests was 99.6 ± 0.61%, 99.1 ± 0.87% (right waist location, right pants pocket). Moreover, six activities recognition was performed using Fuzzy c means classification algorithm recognized over 98% accuracy. In addition we developed of programs that synchronization of data between PC and iPod for long-term physical activity monitoring. This study will provide evidence on using mobile phone and PC for monitoring various activities in everyday life. The next step in our system will be addition of a standard value of various physical activities in everyday life such as household duties and a health guideline how to select and plan exercise considering one's physical characteristics and condition.

An Indoor Continuous Positioning Algorithm on the Move by Fusing Sensors and Wi-Fi on Smartphones

PubMed Central

Li, Huaiyu; Chen, Xiuwan; Jing, Guifei; Wang, Yuan; Cao, Yanfeng; Li, Fei; Zhang, Xinlong; Xiao, Han

2015-01-01

Wi-Fi indoor positioning algorithms experience large positioning error and low stability when continuously positioning terminals that are on the move. This paper proposes a novel indoor continuous positioning algorithm that is on the move, fusing sensors and Wi-Fi on smartphones. The main innovative points include an improved Wi-Fi positioning algorithm and a novel positioning fusion algorithm named the Trust Chain Positioning Fusion (TCPF) algorithm. The improved Wi-Fi positioning algorithm was designed based on the properties of Wi-Fi signals on the move, which are found in a novel “quasi-dynamic” Wi-Fi signal experiment. The TCPF algorithm is proposed to realize the “process-level” fusion of Wi-Fi and Pedestrians Dead Reckoning (PDR) positioning, including three parts: trusted point determination, trust state and positioning fusion algorithm. An experiment is carried out for verification in a typical indoor environment, and the average positioning error on the move is 1.36 m, a decrease of 28.8% compared to an existing algorithm. The results show that the proposed algorithm can effectively reduce the influence caused by the unstable Wi-Fi signals, and improve the accuracy and stability of indoor continuous positioning on the move. PMID:26690447

The Performance Analysis of the Map-Aided Fuzzy Decision Tree Based on the Pedestrian Dead Reckoning Algorithm in an Indoor Environment

PubMed Central

Chiang, Kai-Wei; Liao, Jhen-Kai; Tsai, Guang-Je; Chang, Hsiu-Wen

2015-01-01

Hardware sensors embedded in a smartphone allow the device to become an excellent mobile navigator. A smartphone is ideal for this task because its great international popularity has led to increased phone power and since most of the necessary infrastructure is already in place. However, using a smartphone for indoor pedestrian navigation can be problematic due to the low accuracy of sensors, imprecise predictability of pedestrian motion, and inaccessibility of the Global Navigation Satellite System (GNSS) in some indoor environments. Pedestrian Dead Reckoning (PDR) is one of the most common technologies used for pedestrian navigation, but in its present form, various errors tend to accumulate. This study introduces a fuzzy decision tree (FDT) aided by map information to improve the accuracy and stability of PDR with less dependency on infrastructure. First, the map is quickly surveyed by the Indoor Mobile Mapping System (IMMS). Next, Bluetooth beacons are implemented to enable the initializing of any position. Finally, map-aided FDT can estimate navigation solutions in real time. The experiments were conducted in different fields using a variety of smartphones and users in order to verify stability. The contrast PDR system demonstrates low stability for each case without pre-calibration and post-processing, but the proposed low-complexity FDT algorithm shows good stability and accuracy under the same conditions. PMID:26729114

Development of Mobile Mapping System for 3D Road Asset Inventory.

PubMed

Sairam, Nivedita; Nagarajan, Sudhagar; Ornitz, Scott

2016-03-12

Asset Management is an important component of an infrastructure project. A significant cost is involved in maintaining and updating the asset information. Data collection is the most time-consuming task in the development of an asset management system. In order to reduce the time and cost involved in data collection, this paper proposes a low cost Mobile Mapping System using an equipped laser scanner and cameras. First, the feasibility of low cost sensors for 3D asset inventory is discussed by deriving appropriate sensor models. Then, through calibration procedures, respective alignments of the laser scanner, cameras, Inertial Measurement Unit and GPS (Global Positioning System) antenna are determined. The efficiency of this Mobile Mapping System is experimented by mounting it on a truck and golf cart. By using derived sensor models, geo-referenced images and 3D point clouds are derived. After validating the quality of the derived data, the paper provides a framework to extract road assets both automatically and manually using techniques implementing RANSAC plane fitting and edge extraction algorithms. Then the scope of such extraction techniques along with a sample GIS (Geographic Information System) database structure for unified 3D asset inventory are discussed.

Development of Mobile Mapping System for 3D Road Asset Inventory

PubMed Central

Sairam, Nivedita; Nagarajan, Sudhagar; Ornitz, Scott

2016-01-01

Asset Management is an important component of an infrastructure project. A significant cost is involved in maintaining and updating the asset information. Data collection is the most time-consuming task in the development of an asset management system. In order to reduce the time and cost involved in data collection, this paper proposes a low cost Mobile Mapping System using an equipped laser scanner and cameras. First, the feasibility of low cost sensors for 3D asset inventory is discussed by deriving appropriate sensor models. Then, through calibration procedures, respective alignments of the laser scanner, cameras, Inertial Measurement Unit and GPS (Global Positioning System) antenna are determined. The efficiency of this Mobile Mapping System is experimented by mounting it on a truck and golf cart. By using derived sensor models, geo-referenced images and 3D point clouds are derived. After validating the quality of the derived data, the paper provides a framework to extract road assets both automatically and manually using techniques implementing RANSAC plane fitting and edge extraction algorithms. Then the scope of such extraction techniques along with a sample GIS (Geographic Information System) database structure for unified 3D asset inventory are discussed. PMID:26985897

A new JPEG-based steganographic algorithm for mobile devices

NASA Astrophysics Data System (ADS)

Agaian, Sos S.; Cherukuri, Ravindranath C.; Schneider, Erik C.; White, Gregory B.

2006-05-01

Currently, cellular phones constitute a significant portion of the global telecommunications market. Modern cellular phones offer sophisticated features such as Internet access, on-board cameras, and expandable memory which provide these devices with excellent multimedia capabilities. Because of the high volume of cellular traffic, as well as the ability of these devices to transmit nearly all forms of data. The need for an increased level of security in wireless communications is becoming a growing concern. Steganography could provide a solution to this important problem. In this article, we present a new algorithm for JPEG-compressed images which is applicable to mobile platforms. This algorithm embeds sensitive information into quantized discrete cosine transform coefficients obtained from the cover JPEG. These coefficients are rearranged based on certain statistical properties and the inherent processing and memory constraints of mobile devices. Based on the energy variation and block characteristics of the cover image, the sensitive data is hidden by using a switching embedding technique proposed in this article. The proposed system offers high capacity while simultaneously withstanding visual and statistical attacks. Based on simulation results, the proposed method demonstrates an improved retention of first-order statistics when compared to existing JPEG-based steganographic algorithms, while maintaining a capacity which is comparable to F5 for certain cover images.

A social activity and physical contact-based routing algorithm in mobile opportunistic networks for emergency response to sudden disasters

NASA Astrophysics Data System (ADS)

Wang, Xiaoming; Lin, Yaguang; Zhang, Shanshan; Cai, Zhipeng

2017-05-01

Sudden disasters such as earthquake, flood and hurricane necessitate the employment of communication networks to carry out emergency response activities. Routing has a significant impact on the functionality, performance and flexibility of communication networks. In this article, the routing problem is studied considering the delivery ratio of messages, the overhead ratio of messages and the average delay of messages in mobile opportunistic networks (MONs) for enterprise-level emergency response communications in sudden disaster scenarios. Unlike the traditional routing methods for MONS, this article presents a new two-stage spreading and forwarding dynamic routing algorithm based on the proposed social activity degree and physical contact factor for mobile customers. A new modelling method for describing a dynamic evolving process of the topology structure of a MON is first proposed. Then a multi-copy spreading strategy based on the social activity degree of nodes and a single-copy forwarding strategy based on the physical contact factor between nodes are designed. Compared with the most relevant routing algorithms such as Epidemic, Prophet, Labelled-sim, Dlife-comm and Distribute-sim, the proposed routing algorithm can significantly increase the delivery ratio of messages, and decrease the overhead ratio and average delay of messages.

Networked localization of sniper shots using acoustics

NASA Astrophysics Data System (ADS)

Hengy, S.; Hamery, P.; De Mezzo, S.; Duffner, P.

2011-06-01

The presence of snipers in modern conflicts leads to high insecurity for the soldiers. In order to improve the soldier's protection against this threat, the French German Research Institute of Saint-Louis (ISL) initiated studies in the domain of acoustic localization of shots. Mobile antennas mounted on the soldier's helmet were initially used for real-time detection, classification and localization of sniper shots. It showed good performances in land scenarios, but also in urban scenarios if the array was in the shot corridor, meaning that the microphones first detect the direct wave and then the reflections of the Mach and muzzle waves. As soon as the acoustic arrays were not near to the shot corridor (only reflections are detected) this solution lost its efficiency and erroneous estimated position were given. In order to estimate the position of the shooter in every kind of urban scenario, ISL started studying time reversal techniques. Knowing the position of every reflective object in the environment (buildings, walls, ...) it should be possible to estimate the position of the shooter. First, a synthetic propagation algorithm has been developed and validated for real scale applications. It has then been validated for small scale models, allowing us to test our time reversal based algorithms in our laboratory. In this paper we discuss all the challenges that are induced by the application of sniper detection using time reversal techniques. We will discuss all the hard points that can be encountered and try to find some solutions in order to optimize the use of this technique.

Real time chromametry measurement for food quality detection using mobile device

NASA Astrophysics Data System (ADS)

Witjaksono, Gunawan; Mohamad Hussin, Nur Haziqah Farah Binti; Abdelkreem Saeed Rabih, Almur; Alfa, Sagir

2017-09-01

Freshness of the food is the main factor in determining the quality and safety of the consumed food and hence consumers satisfaction. Current technologies for food quality determination depend on colour changing labels to indicate the freshness level, which is subjective to human eyes. The goal of this paper is to design and develop chromatic algorithm based on RGB colour reading and correlation with pH values for real time determination of freshness level of shrimp. The results show that the developed algorithm is able to measure, analyse and display the freshness level of food directly on the screen of a mobile app technology. The mobile app is developed on Android platform and is tested in the shrimp freshness range by stating whether it is “fresh, good or spoiled”.

Robot path planning algorithm based on symbolic tags in dynamic environment

NASA Astrophysics Data System (ADS)

Vokhmintsev, A.; Timchenko, M.; Melnikov, A.; Kozko, A.; Makovetskii, A.

2017-09-01

The present work will propose a new heuristic algorithms for path planning of a mobile robot in an unknown dynamic space that have theoretically approved estimates of computational complexity and are approbated for solving specific applied problems.

Decryption of pure-position permutation algorithms.

PubMed

Zhao, Xiao-Yu; Chen, Gang; Zhang, Dan; Wang, Xiao-Hong; Dong, Guang-Chang

2004-07-01

Pure position permutation image encryption algorithms, commonly used as image encryption investigated in this work are unfortunately frail under known-text attack. In view of the weakness of pure position permutation algorithm, we put forward an effective decryption algorithm for all pure-position permutation algorithms. First, a summary of the pure position permutation image encryption algorithms is given by introducing the concept of ergodic matrices. Then, by using probability theory and algebraic principles, the decryption probability of pure-position permutation algorithms is verified theoretically; and then, by defining the operation system of fuzzy ergodic matrices, we improve a specific decryption algorithm. Finally, some simulation results are shown.

Wireless Relay Selection in Pocket Switched Networks Based on Spatial Regularity of Human Mobility †

PubMed Central

Huang, Jianhui; Cheng, Xiuzhen; Bi, Jingping; Chen, Biao

2016-01-01

Pocket switched networks (PSNs) take advantage of human mobility to deliver data. Investigations on real-world trace data indicate that human mobility shows an obvious spatial regularity: a human being usually visits a few places at high frequencies. These most frequently visited places form the home of a node, which is exploited in this paper to design two HomE based Relay selectiOn (HERO) algorithms. Both algorithms input single data copy into the network at any time. In the basic HERO, only the first node encountered by the source and whose home overlaps a destination’s home is selected as a relay while the enhanced HERO keeps finding more optimal relay that visits the destination’s home with higher probability. The two proposed algorithms only require the relays to exchange the information of their home and/or the visiting frequencies to their home when two nodes meet. As a result, the information update is reduced and there is no global status information that needs to be maintained. This causes light loads on relays because of the low communication cost and storage requirements. Additionally, only simple operations are needed in the two proposed algorithms, resulting in little computation overhead at relays. At last, a theoretical analysis is performed on some key metrics and then the real-world based simulations indicate that the two HERO algorithms are efficient and effective through employing only one or a few relays. PMID:26797609

PDF file encryption on mobile phone using super-encryption of Variably Modified Permutation Composition (VMPC) and two square cipher algorithm

NASA Astrophysics Data System (ADS)

Rachmawati, D.; Budiman, M. A.; Atika, F.

2018-03-01

Data security is becoming one of the most significant challenges in the digital world. Retrieval of data by unauthorized parties will result in harm to the owner of the data. PDF data are also susceptible to data security disorder. These things affect the security of the information. To solve the security problem, it needs a method to maintain the protection of the data, such as cryptography. In cryptography, several algorithms can encode data, one of them is Two Square Cipher algorithm which is a symmetric algorithm. At this research, Two Square Cipher algorithm has already developed into a 16 x 16 key aims to enter the various plaintexts. However, for more enhancement security it will be combined with the VMPC algorithm which is a symmetric algorithm. The combination of the two algorithms is called with the super-encryption. At this point, the data already can be stored on a mobile phone allowing users to secure data flexibly and can be accessed anywhere. The application of PDF document security on this research built by Android-platform. At this study will also calculate the complexity of algorithms and process time. Based on the test results the complexity of the algorithm is θ (n) for Two Square Cipher and θ (n) for VMPC algorithm, so the complexity of the super-encryption is also θ (n). VMPC algorithm processing time results quicker than on Two Square Cipher. And the processing time is directly proportional to the length of the plaintext and passwords.

Automatic Rail Extraction and Celarance Check with a Point Cloud Captured by Mls in a Railway

NASA Astrophysics Data System (ADS)

Niina, Y.; Honma, R.; Honma, Y.; Kondo, K.; Tsuji, K.; Hiramatsu, T.; Oketani, E.

2018-05-01

Recently, MLS (Mobile Laser Scanning) has been successfully used in a road maintenance. In this paper, we present the application of MLS for the inspection of clearance along railway tracks of West Japan Railway Company. Point clouds around the track are captured by MLS mounted on a bogie and rail position can be determined by matching the shape of the ideal rail head with respect to the point cloud by ICP algorithm. A clearance check is executed automatically with virtual clearance model laid along the extracted rail. As a result of evaluation, the accuracy of extracting rail positions is less than 3 mm. With respect to the automatic clearance check, the objects inside the clearance and the ones related to a contact line is successfully detected by visual confirmation.

A convex optimization method for self-organization in dynamic (FSO/RF) wireless networks

NASA Astrophysics Data System (ADS)

Llorca, Jaime; Davis, Christopher C.; Milner, Stuart D.

2008-08-01

Next generation communication networks are becoming increasingly complex systems. Previously, we presented a novel physics-based approach to model dynamic wireless networks as physical systems which react to local forces exerted on network nodes. We showed that under clear atmospheric conditions the network communication energy can be modeled as the potential energy of an analogous spring system and presented a distributed mobility control algorithm where nodes react to local forces driving the network to energy minimizing configurations. This paper extends our previous work by including the effects of atmospheric attenuation and transmitted power constraints in the optimization problem. We show how our new formulation still results in a convex energy minimization problem. Accordingly, an updated force-driven mobility control algorithm is presented. Forces on mobile backbone nodes are computed as the negative gradient of the new energy function. Results show how in the presence of atmospheric obscuration stronger forces are exerted on network nodes that make them move closer to each other, avoiding loss of connectivity. We show results in terms of network coverage and backbone connectivity and compare the developed algorithms for different scenarios.

Mamdani Fuzzy System for Indoor Autonomous Mobile Robot

NASA Astrophysics Data System (ADS)

Khan, M. K. A. Ahamed; Rashid, Razif; Elamvazuthi, I.

2011-06-01

Several control algorithms for autonomous mobile robot navigation have been proposed in the literature. Recently, the employment of non-analytical methods of computing such as fuzzy logic, evolutionary computation, and neural networks has demonstrated the utility and potential of these paradigms for intelligent control of mobile robot navigation. In this paper, Mamdani fuzzy system for an autonomous mobile robot is developed. The paper begins with the discussion on the conventional controller and then followed by the description of fuzzy logic controller in detail.

Accurate Mobile Urban Mapping via Digital Map-Based SLAM †

PubMed Central

Roh, Hyunchul; Jeong, Jinyong; Cho, Younggun; Kim, Ayoung

2016-01-01

This paper presents accurate urban map generation using digital map-based Simultaneous Localization and Mapping (SLAM). Throughout this work, our main objective is generating a 3D and lane map aiming for sub-meter accuracy. In conventional mapping approaches, achieving extremely high accuracy was performed by either (i) exploiting costly airborne sensors or (ii) surveying with a static mapping system in a stationary platform. Mobile scanning systems recently have gathered popularity but are mostly limited by the availability of the Global Positioning System (GPS). We focus on the fact that the availability of GPS and urban structures are both sporadic but complementary. By modeling both GPS and digital map data as measurements and integrating them with other sensor measurements, we leverage SLAM for an accurate mobile mapping system. Our proposed algorithm generates an efficient graph SLAM and achieves a framework running in real-time and targeting sub-meter accuracy with a mobile platform. Integrated with the SLAM framework, we implement a motion-adaptive model for the Inverse Perspective Mapping (IPM). Using motion estimation derived from SLAM, the experimental results show that the proposed approaches provide stable bird’s-eye view images, even with significant motion during the drive. Our real-time map generation framework is validated via a long-distance urban test and evaluated at randomly sampled points using Real-Time Kinematic (RTK)-GPS. PMID:27548175

Actigraphy features for predicting mobility disability in older adults

USDA-ARS?s Scientific Manuscript database

Actigraphy has attracted much attention for assessing physical activity in the past decade. Many algorithms have been developed to automate the analysis process, but none has targeted a general model to discover related features for detecting or predicting mobility function, or more specifically, mo...

Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic Safety and Mobility in Connected Vehicle Environment

EPA Science Inventory

With the development of Connected Vehicle Technology that facilitates wireless communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at...

Research and application of multi-agent genetic algorithm in tower defense game

NASA Astrophysics Data System (ADS)

Jin, Shaohua

2018-04-01

In this paper, a new multi-agent genetic algorithm based on orthogonal experiment is proposed, which is based on multi-agent system, genetic algorithm and orthogonal experimental design. The design of neighborhood competition operator, orthogonal crossover operator, Son and self-learning operator. The new algorithm is applied to mobile tower defense game, according to the characteristics of the game, the establishment of mathematical models, and finally increases the value of the game's monster.

iTrack: instrumented mobile electrooculography (EOG) eye-tracking in older adults and Parkinson's disease.

PubMed

Stuart, Samuel; Hickey, Aodhán; Galna, Brook; Lord, Sue; Rochester, Lynn; Godfrey, Alan

2017-01-01

Detection of saccades (fast eye-movements) within raw mobile electrooculography (EOG) data involves complex algorithms which typically process data acquired during seated static tasks only. Processing of data during dynamic tasks such as walking is relatively rare and complex, particularly in older adults or people with Parkinson's disease (PD). Development of algorithms that can be easily implemented to detect saccades is required. This study aimed to develop an algorithm for the detection and measurement of saccades in EOG data during static (sitting) and dynamic (walking) tasks, in older adults and PD. Eye-tracking via mobile EOG and infra-red (IR) eye-tracker (with video) was performed with a group of older adults (n  =  10) and PD participants (n  =  10) (⩾50 years). Horizontal saccades made between targets set 5°, 10° and 15° apart were first measured while seated. Horizontal saccades were then measured while a participant walked and executed a 40° turn left and right. The EOG algorithm was evaluated by comparing the number of correct saccade detections and agreement (ICC 2,1 ) between output from visual inspection of eye-tracker videos and IR eye-tracker. The EOG algorithm detected 75-92% of saccades compared to video inspection and IR output during static testing, with fair to excellent agreement (ICC 2,1 0.49-0.93). However, during walking EOG saccade detection reduced to 42-88% compared to video inspection or IR output, with poor to excellent (ICC 2,1 0.13-0.88) agreement between methodologies. The algorithm was robust during seated testing but less so during walking, which was likely due to increased measurement and analysis error with a dynamic task. Future studies may consider a combination of EOG and IR for comprehensive measurement.

Improving Remote Health Monitoring: A Low-Complexity ECG Compression Approach

PubMed Central

Al-Ali, Abdulla; Mohamed, Amr; Ward, Rabab

2018-01-01

Recent advances in mobile technology have created a shift towards using battery-driven devices in remote monitoring settings and smart homes. Clinicians are carrying out diagnostic and screening procedures based on the electrocardiogram (ECG) signals collected remotely for outpatients who need continuous monitoring. High-speed transmission and analysis of large recorded ECG signals are essential, especially with the increased use of battery-powered devices. Exploring low-power alternative compression methodologies that have high efficiency and that enable ECG signal collection, transmission, and analysis in a smart home or remote location is required. Compression algorithms based on adaptive linear predictors and decimation by a factor B/K are evaluated based on compression ratio (CR), percentage root-mean-square difference (PRD), and heartbeat detection accuracy of the reconstructed ECG signal. With two databases (153 subjects), the new algorithm demonstrates the highest compression performance (CR=6 and PRD=1.88) and overall detection accuracy (99.90% sensitivity, 99.56% positive predictivity) over both databases. The proposed algorithm presents an advantage for the real-time transmission of ECG signals using a faster and more efficient method, which meets the growing demand for more efficient remote health monitoring. PMID:29337892

Improving Remote Health Monitoring: A Low-Complexity ECG Compression Approach.

PubMed

Elgendi, Mohamed; Al-Ali, Abdulla; Mohamed, Amr; Ward, Rabab

2018-01-16

Recent advances in mobile technology have created a shift towards using battery-driven devices in remote monitoring settings and smart homes. Clinicians are carrying out diagnostic and screening procedures based on the electrocardiogram (ECG) signals collected remotely for outpatients who need continuous monitoring. High-speed transmission and analysis of large recorded ECG signals are essential, especially with the increased use of battery-powered devices. Exploring low-power alternative compression methodologies that have high efficiency and that enable ECG signal collection, transmission, and analysis in a smart home or remote location is required. Compression algorithms based on adaptive linear predictors and decimation by a factor B / K are evaluated based on compression ratio (CR), percentage root-mean-square difference (PRD), and heartbeat detection accuracy of the reconstructed ECG signal. With two databases (153 subjects), the new algorithm demonstrates the highest compression performance ( CR = 6 and PRD = 1.88 ) and overall detection accuracy (99.90% sensitivity, 99.56% positive predictivity) over both databases. The proposed algorithm presents an advantage for the real-time transmission of ECG signals using a faster and more efficient method, which meets the growing demand for more efficient remote health monitoring.

Arikan and Alamouti matrices based on fast block-wise inverse Jacket transform

NASA Astrophysics Data System (ADS)

Lee, Moon Ho; Khan, Md Hashem Ali; Kim, Kyeong Jin

2013-12-01

Recently, Lee and Hou (IEEE Signal Process Lett 13: 461-464, 2006) proposed one-dimensional and two-dimensional fast algorithms for block-wise inverse Jacket transforms (BIJTs). Their BIJTs are not real inverse Jacket transforms from mathematical point of view because their inverses do not satisfy the usual condition, i.e., the multiplication of a matrix with its inverse matrix is not equal to the identity matrix. Therefore, we mathematically propose a fast block-wise inverse Jacket transform of orders N = 2 k , 3 k , 5 k , and 6 k , where k is a positive integer. Based on the Kronecker product of the successive lower order Jacket matrices and the basis matrix, the fast algorithms for realizing these transforms are obtained. Due to the simple inverse and fast algorithms of Arikan polar binary and Alamouti multiple-input multiple-output (MIMO) non-binary matrices, which are obtained from BIJTs, they can be applied in areas such as 3GPP physical layer for ultra mobile broadband permutation matrices design, first-order q-ary Reed-Muller code design, diagonal channel design, diagonal subchannel decompose for interference alignment, and 4G MIMO long-term evolution Alamouti precoding design.

77 FR 62247 - Dynamic Positioning Operations Guidance for Vessels Other Than Mobile Offshore Drilling Units...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-12

... DEPARTMENT OF HOMELAND SECURITY Coast Guard [Docket No. USCG-2011-1106] Dynamic Positioning... ``Mobile Offshore Drilling Unit Dynamic Positioning Guidance''. The notice recommended owners and operators of Mobile Offshore Drilling Units (MODUs) follow Marine Technology Society (MTS) Dynamic Positioning...

JOMAR: Joint Operations with Mobile Autonomous Robots

DTIC Science & Technology

2015-12-21

AFRL-AFOSR-JP-TR-2015-0009 JOMAR: Joint Operations with Mobile Autonomous Robots Edwin Olson UNIVERSITY OF MICHIGAN Final Report 12/21/2015...SUBTITLE JOMAR: Joint Operations with Mobile Autonomous Robots 5a. CONTRACT NUMBER FA23861114024 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...14. ABSTRACT Under this grant, we formulated and implemented a variety of novel algorithms that address core problems in multi- robot systems. These

Fourier-domain Mobility Spectrum Analysis (FMSA) for Characterizing Semiconductors with Multi-Electron/Hole Species

NASA Astrophysics Data System (ADS)

Cui, Boya; Kielb, Edward; Luo, Jiajun; Tang, Yang; Grayson, Matthew

Superlattices and narrow gap semiconductors often host multiple conducting species, such as electrons and holes, requiring a mobility spectral analysis (MSA) method to separate contributions to the conductivity. Here, a least-squares MSA method is introduced: the QR-algorithm Fourier-domain MSA (FMSA). Like other MSA methods, the FMSA sorts the conductivity contributions of different carrier species from magnetotransport measurements, arriving at a best fit to the experimentally measured longitudinal and Hall conductivities σxx and σxy, respectively. This method distinguishes itself from other methods by using the so-called QR-algorithm of linear algebra to achieve rapid convergence of the mobility spectrum as the solution to an eigenvalue problem, and by alternately solving this problem in both the mobility domain and its Fourier reciprocal-space. The result accurately fits a mobility range spanning nearly four orders of magnitude (μ = 300 to 1,000,000 cm2/V .s). This method resolves the mobility spectra as well as, or better than, competing MSA methods while also achieving high computational efficiency, requiring less than 30 second on average to converge to a solution on a standard desktop computer. Acknowledgement: Funded by AFOSR FA9550-15-1-0377 and AFOSR FA9550-15-1-0247.

Performance analysis of visual tracking algorithms for motion-based user interfaces on mobile devices

NASA Astrophysics Data System (ADS)

Winkler, Stefan; Rangaswamy, Karthik; Tedjokusumo, Jefry; Zhou, ZhiYing

2008-02-01

Determining the self-motion of a camera is useful for many applications. A number of visual motion-tracking algorithms have been developed till date, each with their own advantages and restrictions. Some of them have also made their foray into the mobile world, powering augmented reality-based applications on phones with inbuilt cameras. In this paper, we compare the performances of three feature or landmark-guided motion tracking algorithms, namely marker-based tracking with MXRToolkit, face tracking based on CamShift, and MonoSLAM. We analyze and compare the complexity, accuracy, sensitivity, robustness and restrictions of each of the above methods. Our performance tests are conducted over two stages: The first stage of testing uses video sequences created with simulated camera movements along the six degrees of freedom in order to compare accuracy in tracking, while the second stage analyzes the robustness of the algorithms by testing for manipulative factors like image scaling and frame-skipping.

Traffic sharing algorithms for hybrid mobile networks

NASA Technical Reports Server (NTRS)

Arcand, S.; Murthy, K. M. S.; Hafez, R.

1995-01-01

In a hybrid (terrestrial + satellite) mobile personal communications networks environment, a large size satellite footprint (supercell) overlays on a large number of smaller size, contiguous terrestrial cells. We assume that the users have either a terrestrial only single mode terminal (SMT) or a terrestrial/satellite dual mode terminal (DMT) and the ratio of DMT to the total terminals is defined gamma. It is assumed that the call assignments to and handovers between terrestrial cells and satellite supercells take place in a dynamic fashion when necessary. The objectives of this paper are twofold, (1) to propose and define a class of traffic sharing algorithms to manage terrestrial and satellite network resources efficiently by handling call handovers dynamically, and (2) to analyze and evaluate the algorithms by maximizing the traffic load handling capability (defined in erl/cell) over a wide range of terminal ratios (gamma) given an acceptable range of blocking probabilities. Two of the algorithms (G & S) in the proposed class perform extremely well for a wide range of gamma.

Off-the-shelf mobile handset environments for deploying accelerometer based gait and activity analysis algorithms.

PubMed

Hynes, Martin; Wang, Han; Kilmartin, Liam

2009-01-01

Over the last decade, there has been substantial research interest in the application of accelerometry data for many forms of automated gait and activity analysis algorithms. This paper introduces a summary of new "of-the-shelf" mobile phone handset platforms containing embedded accelerometers which support the development of custom software to implement real time analysis of the accelerometer data. An overview of the main software programming environments which support the development of such software, including Java ME based JSR 256 API, C++ based Motion Sensor API and the Python based "aXYZ" module, is provided. Finally, a sample application is introduced and its performance evaluated in order to illustrate how a standard mobile phone can be used to detect gait activity using such a non-intrusive and easily accepted sensing platform.

A Real-Time Marker-Based Visual Sensor Based on a FPGA and a Soft Core Processor

PubMed Central

Tayara, Hilal; Ham, Woonchul; Chong, Kil To

2016-01-01

This paper introduces a real-time marker-based visual sensor architecture for mobile robot localization and navigation. A hardware acceleration architecture for post video processing system was implemented on a field-programmable gate array (FPGA). The pose calculation algorithm was implemented in a System on Chip (SoC) with an Altera Nios II soft-core processor. For every frame, single pass image segmentation and Feature Accelerated Segment Test (FAST) corner detection were used for extracting the predefined markers with known geometries in FPGA. Coplanar PosIT algorithm was implemented on the Nios II soft-core processor supplied with floating point hardware for accelerating floating point operations. Trigonometric functions have been approximated using Taylor series and cubic approximation using Lagrange polynomials. Inverse square root method has been implemented for approximating square root computations. Real time results have been achieved and pixel streams have been processed on the fly without any need to buffer the input frame for further implementation. PMID:27983714

A Real-Time Marker-Based Visual Sensor Based on a FPGA and a Soft Core Processor.

PubMed

Tayara, Hilal; Ham, Woonchul; Chong, Kil To

2016-12-15

This paper introduces a real-time marker-based visual sensor architecture for mobile robot localization and navigation. A hardware acceleration architecture for post video processing system was implemented on a field-programmable gate array (FPGA). The pose calculation algorithm was implemented in a System on Chip (SoC) with an Altera Nios II soft-core processor. For every frame, single pass image segmentation and Feature Accelerated Segment Test (FAST) corner detection were used for extracting the predefined markers with known geometries in FPGA. Coplanar PosIT algorithm was implemented on the Nios II soft-core processor supplied with floating point hardware for accelerating floating point operations. Trigonometric functions have been approximated using Taylor series and cubic approximation using Lagrange polynomials. Inverse square root method has been implemented for approximating square root computations. Real time results have been achieved and pixel streams have been processed on the fly without any need to buffer the input frame for further implementation.

Do you see what I see? Mobile eye-tracker contextual analysis and inter-rater reliability.

PubMed

Stuart, S; Hunt, D; Nell, J; Godfrey, A; Hausdorff, J M; Rochester, L; Alcock, L

2018-02-01

Mobile eye-trackers are currently used during real-world tasks (e.g. gait) to monitor visual and cognitive processes, particularly in ageing and Parkinson's disease (PD). However, contextual analysis involving fixation locations during such tasks is rarely performed due to its complexity. This study adapted a validated algorithm and developed a classification method to semi-automate contextual analysis of mobile eye-tracking data. We further assessed inter-rater reliability of the proposed classification method. A mobile eye-tracker recorded eye-movements during walking in five healthy older adult controls (HC) and five people with PD. Fixations were identified using a previously validated algorithm, which was adapted to provide still images of fixation locations (n = 116). The fixation location was manually identified by two raters (DH, JN), who classified the locations. Cohen's kappa correlation coefficients determined the inter-rater reliability. The algorithm successfully provided still images for each fixation, allowing manual contextual analysis to be performed. The inter-rater reliability for classifying the fixation location was high for both PD (kappa = 0.80, 95% agreement) and HC groups (kappa = 0.80, 91% agreement), which indicated a reliable classification method. This study developed a reliable semi-automated contextual analysis method for gait studies in HC and PD. Future studies could adapt this methodology for various gait-related eye-tracking studies.

A Node Localization Algorithm Based on Multi-Granularity Regional Division and the Lagrange Multiplier Method in Wireless Sensor Networks.

PubMed

Shang, Fengjun; Jiang, Yi; Xiong, Anping; Su, Wen; He, Li

2016-11-18

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed. When the unknown node is inside positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is outside positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

An adaptive SVSF-SLAM algorithm to improve the success and solving the UGVs cooperation problem

NASA Astrophysics Data System (ADS)

Demim, Fethi; Nemra, Abdelkrim; Louadj, Kahina; Hamerlain, Mustapha; Bazoula, Abdelouahab

2018-05-01

This paper aims to present a Decentralised Cooperative Simultaneous Localization and Mapping (DCSLAM) solution based on 2D laser data using an Adaptive Covariance Intersection (ACI). The ACI-DCSLAM algorithm will be validated on a swarm of Unmanned Ground Vehicles (UGVs) receiving features to estimate the position and covariance of shared features before adding them to the global map. With the proposed solution, a group of (UGVs) will be able to construct a large reliable map and localise themselves within this map without any user intervention. The most popular solutions to this problem are the EKF-SLAM, Nonlinear H-infinity ? SLAM and the FAST-SLAM. The former suffers from two important problems which are the poor consistency caused by the linearization problem and the calculation of Jacobian. The second solution is the ? which is a very promising filter because it doesn't make any assumption about noise characteristics, while the latter is not suitable for real time implementation. Therefore, a new alternative solution based on the smooth variable structure filter (SVSF) is adopted. Cooperative adaptive SVSF-SLAM algorithm is proposed in this paper to solve the UGVs SLAM problem. Our main contribution consists in adapting the SVSF filter to solve the Decentralised Cooperative SLAM problem for multiple UGVs. The algorithms developed in this paper were implemented using two mobile robots Pioneer ?, equiped with 2D laser telemetry sensors. Good results are obtained by the Cooperative adaptive SVSF-SLAM algorithm compared to the Cooperative EKF/?-SLAM algorithms, especially when the noise is colored or affected by a variable bias. Simulation results confirm and show the efficiency of the proposed algorithm which is more robust, stable and adapted to real time applications.

Evaluation of an Automated Swallow-Detection Algorithm Using Visual Biofeedback in Healthy Adults and Head and Neck Cancer Survivors.

PubMed

Constantinescu, Gabriela; Kuffel, Kristina; Aalto, Daniel; Hodgetts, William; Rieger, Jana

2018-06-01

Mobile health (mHealth) technologies may offer an opportunity to address longstanding clinical challenges, such as access and adherence to swallowing therapy. Mobili-T ® is an mHealth device that uses surface electromyography (sEMG) to provide biofeedback on submental muscles activity during exercise. An automated swallow-detection algorithm was developed for Mobili-T ® . This study evaluated the performance of the swallow-detection algorithm. Ten healthy participants and 10 head and neck cancer (HNC) patients were fitted with the device. Signal was acquired during regular, effortful, and Mendelsohn maneuver saliva swallows, as well as lip presses, tongue, and head movements. Signals of interest were tagged during data acquisition and used to evaluate algorithm performance. Sensitivity and positive predictive values (PPV) were calculated for each participant. Saliva swallows were compared between HNC and controls in the four sEMG-based parameters used in the algorithm: duration, peak amplitude ratio, median frequency, and 15th percentile of the power spectrum density. In healthy participants, sensitivity and PPV were 92.3 and 83.9%, respectively. In HNC patients, sensitivity was 92.7% and PPV was 72.2%. In saliva swallows, HNC patients had longer event durations (U = 1925.5, p < 0.001), lower median frequency (U = 2674.0, p < 0.001), and lower 15th percentile of the power spectrum density [t(176.9) = 2.07, p < 0.001] than healthy participants. The automated swallow-detection algorithm performed well with healthy participants and retained a high sensitivity, but had lowered PPV with HNC patients. With respect to Mobili-T ® , the algorithm will next be evaluated using the mHealth system.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database.

PubMed

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-28

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m.

An Imaging Sensor-Aided Vision Navigation Approach that Uses a Geo-Referenced Image Database

PubMed Central

Li, Yan; Hu, Qingwu; Wu, Meng; Gao, Yang

2016-01-01

In determining position and attitude, vision navigation via real-time image processing of data collected from imaging sensors is advanced without a high-performance global positioning system (GPS) and an inertial measurement unit (IMU). Vision navigation is widely used in indoor navigation, far space navigation, and multiple sensor-integrated mobile mapping. This paper proposes a novel vision navigation approach aided by imaging sensors and that uses a high-accuracy geo-referenced image database (GRID) for high-precision navigation of multiple sensor platforms in environments with poor GPS. First, the framework of GRID-aided vision navigation is developed with sequence images from land-based mobile mapping systems that integrate multiple sensors. Second, a highly efficient GRID storage management model is established based on the linear index of a road segment for fast image searches and retrieval. Third, a robust image matching algorithm is presented to search and match a real-time image with the GRID. Subsequently, the image matched with the real-time scene is considered to calculate the 3D navigation parameter of multiple sensor platforms. Experimental results show that the proposed approach retrieves images efficiently and has navigation accuracies of 1.2 m in a plane and 1.8 m in height under GPS loss in 5 min and within 1500 m. PMID:26828496

Active case-finding for tuberculosis by mobile teams in Myanmar: yield and treatment outcomes.

PubMed

Myint, Ohnmar; Saw, Saw; Isaakidis, Petros; Khogali, Mohammed; Reid, Anthony; Hoa, Nguyen Binh; Kyaw, Thi Thi; Zaw, Ko Ko; Khaing, Tin Mi Mi; Aung, Si Thu

2017-06-02

Since 2005, the Myanmar National Tuberculosis Programme (NTP) has been implementing active case finding (ACF) activities involving mobile teams in hard-to-reach areas. This study revealed the contribution of mobile team activities to total tuberculosis (TB) case detection, characteristics of TB patients detected by mobile teams and their treatment outcomes. This was a descriptive study using routine programme data between October 2014 and December 2014. Mobile team activities were a one-stop service and included portable digital chest radiography (CXR) and microscopy of two sputum samples. The algorithm of the case detection included screening patients by symptoms, then by CXR followed by sputum microscopy for confirmation. Diagnosed patients were started on treatment and followed until a final outcome was ascertained. A total of 9 349 people with symptoms suggestive of TB were screened by CXR, with an uptake of 96.6%. Of those who were meant to undergo sputum smear microscopy, 51.4% had sputum examinations. Finally, 504 TB patients were identified by the mobile teams and the overall contribution to total TB case detection in the respective townships was 25.3%. Among total cases examined by microscopy, 6.4% were sputum smear positive TB. Treatment success rate was high as 91.8% in study townships compared to national rate 85% (2014 cohort). This study confirmed the feasibility and acceptability of ACF by mobile teams in hard-to-reach contexts, especially when equipped with portable, digital CXR machines that provided immediate results. However, the follow-up process of sputum examination created a significant barrier to confirmation of the diagnosis. In order to optimize the ACF through mobile team activity, future ACF activities were needed to be strengthened one stop service including molecular diagnostics or provision of sputum cups to all presumptive TB cases prior to CXR and testing if CXR suggestive of TB.

Firefly algorithm with chaos

NASA Astrophysics Data System (ADS)

Gandomi, A. H.; Yang, X.-S.; Talatahari, S.; Alavi, A. H.

2013-01-01

A recently developed metaheuristic optimization algorithm, firefly algorithm (FA), mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies. In the present study, we will introduce chaos into FA so as to increase its global search mobility for robust global optimization. Detailed studies are carried out on benchmark problems with different chaotic maps. Here, 12 different chaotic maps are utilized to tune the attractive movement of the fireflies in the algorithm. The results show that some chaotic FAs can clearly outperform the standard FA.

Hybrid Packet-Pheromone-Based Probabilistic Routing for Mobile Ad Hoc Networks

NASA Astrophysics Data System (ADS)

Kashkouli Nejad, Keyvan; Shawish, Ahmed; Jiang, Xiaohong; Horiguchi, Susumu

Ad-Hoc networks are collections of mobile nodes communicating using wireless media without any fixed infrastructure. Minimal configuration and quick deployment make Ad-Hoc networks suitable for emergency situations like natural disasters or military conflicts. The current Ad-Hoc networks can only support either high mobility or high transmission rate at a time because they employ static approaches in their routing schemes. However, due to the continuous expansion of the Ad-Hoc network size, node-mobility and transmission rate, the development of new adaptive and dynamic routing schemes has become crucial. In this paper we propose a new routing scheme to support high transmission rates and high node-mobility simultaneously in a big Ad-Hoc network, by combining a new proposed packet-pheromone-based approach with the Hint Based Probabilistic Protocol (HBPP) for congestion avoidance with dynamic path selection in packet forwarding process. Because of using the available feedback information, the proposed algorithm does not introduce any additional overhead. The extensive simulation-based analysis conducted in this paper indicates that the proposed algorithm offers small packet-latency and achieves a significantly higher delivery probability in comparison with the available Hint-Based Probabilistic Protocol (HBPP).

A Network Topology Control and Identity Authentication Protocol with Support for Movable Sensor Nodes

PubMed Central

Zhang, Ying; Chen, Wei; Liang, Jixing; Zheng, Bingxin; Jiang, Shengming

2015-01-01

It is expected that in the near future wireless sensor network (WSNs) will be more widely used in the mobile environment, in applications such as Autonomous Underwater Vehicles (AUVs) for marine monitoring and mobile robots for environmental investigation. The sensor nodes’ mobility can easily cause changes to the structure of a network topology, and lead to the decline in the amount of transmitted data, excessive energy consumption, and lack of security. To solve these problems, a kind of efficient Topology Control algorithm for node Mobility (TCM) is proposed. In the topology construction stage, an efficient clustering algorithm is adopted, which supports sensor node movement. It can ensure the balance of clustering, and reduce the energy consumption. In the topology maintenance stage, the digital signature authentication based on Error Correction Code (ECC) and the communication mechanism of soft handover are adopted. After verifying the legal identity of the mobile nodes, secure communications can be established, and this can increase the amount of data transmitted. Compared to some existing schemes, the proposed scheme has significant advantages regarding network topology stability, amounts of data transferred, lifetime and safety performance of the network. PMID:26633405

A Network Topology Control and Identity Authentication Protocol with Support for Movable Sensor Nodes.

PubMed

Zhang, Ying; Chen, Wei; Liang, Jixing; Zheng, Bingxin; Jiang, Shengming

2015-12-01

It is expected that in the near future wireless sensor network (WSNs) will be more widely used in the mobile environment, in applications such as Autonomous Underwater Vehicles (AUVs) for marine monitoring and mobile robots for environmental investigation. The sensor nodes' mobility can easily cause changes to the structure of a network topology, and lead to the decline in the amount of transmitted data, excessive energy consumption, and lack of security. To solve these problems, a kind of efficient Topology Control algorithm for node Mobility (TCM) is proposed. In the topology construction stage, an efficient clustering algorithm is adopted, which supports sensor node movement. It can ensure the balance of clustering, and reduce the energy consumption. In the topology maintenance stage, the digital signature authentication based on Error Correction Code (ECC) and the communication mechanism of soft handover are adopted. After verifying the legal identity of the mobile nodes, secure communications can be established, and this can increase the amount of data transmitted. Compared to some existing schemes, the proposed scheme has significant advantages regarding network topology stability, amounts of data transferred, lifetime and safety performance of the network.

Cooperative Multi-Agent Mobile Sensor Platforms for Jet Engine Inspection: Concept and Implementation

NASA Technical Reports Server (NTRS)

Litt, Jonathan S.; Wong, Edmond; Krasowski, Michael J.; Greer, Lawrence C.

2003-01-01

Cooperative behavior algorithms utilizing swarm intelligence are being developed for mobile sensor platforms to inspect jet engines on-wing. Experiments are planned in which several relatively simple autonomous platforms will work together in a coordinated fashion to carry out complex maintenance-type tasks within the constrained working environment modeled on the interior of a turbofan engine. The algorithms will emphasize distribution of the tasks among multiple units; they will be scalable and flexible so that units may be added in the future; and will be designed to operate on an individual unit level to produce the desired global effect. This proof of concept demonstration will validate the algorithms and provide justification for further miniaturization and specialization of the hardware toward the true application of on-wing in situ turbine engine maintenance.

Centimeter-Level Robust Gnss-Aided Inertial Post-Processing for Mobile Mapping Without Local Reference Stations

NASA Astrophysics Data System (ADS)

Hutton, J. J.; Gopaul, N.; Zhang, X.; Wang, J.; Menon, V.; Rieck, D.; Kipka, A.; Pastor, F.

2016-06-01

For almost two decades mobile mapping systems have done their georeferencing using Global Navigation Satellite Systems (GNSS) to measure position and inertial sensors to measure orientation. In order to achieve cm level position accuracy, a technique referred to as post-processed carrier phase differential GNSS (DGNSS) is used. For this technique to be effective the maximum distance to a single Reference Station should be no more than 20 km, and when using a network of Reference Stations the distance to the nearest station should no more than about 70 km. This need to set up local Reference Stations limits productivity and increases costs, especially when mapping large areas or long linear features such as roads or pipelines. An alternative technique to DGNSS for high-accuracy positioning from GNSS is the so-called Precise Point Positioning or PPP method. In this case instead of differencing the rover observables with the Reference Station observables to cancel out common errors, an advanced model for every aspect of the GNSS error chain is developed and parameterized to within an accuracy of a few cm. The Trimble Centerpoint RTX positioning solution combines the methodology of PPP with advanced ambiguity resolution technology to produce cm level accuracies without the need for local reference stations. It achieves this through a global deployment of highly redundant monitoring stations that are connected through the internet and are used to determine the precise satellite data with maximum accuracy, robustness, continuity and reliability, along with advance algorithms and receiver and antenna calibrations. This paper presents a new post-processed realization of the Trimble Centerpoint RTX technology integrated into the Applanix POSPac MMS GNSS-Aided Inertial software for mobile mapping. Real-world results from over 100 airborne flights evaluated against a DGNSS network reference are presented which show that the post-processed Centerpoint RTX solution agrees with the DGNSS solution to better than 2.9 cm RMSE Horizontal and 5.5 cm RMSE Vertical. Such accuracies are sufficient to meet the requirements for a majority of airborne mapping applications.

Sensitivity of GRETINA position resolution to hole mobility

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

Prasher, V. S.; Cromaz, M.; Merchan, E.

The sensitivity of the position resolution of the gamma-ray tracking array GRETINA to the hole charge-carrier mobility parameter is investigated. The χ 2 results from a fit of averaged signal (“superpulse”) data exhibit a shallow minimum for hole mobilities 15% lower than the currently adopted values. Calibration data on position resolution is analyzed, together with simulations that isolate the hole mobility dependence of signal decomposition from other effects such as electronics cross-talk. Our results effectively exclude hole mobility as a dominant parameter for improving the position resolution for reconstruction of gamma-ray interaction points in GRETINA.

Sensitivity of GRETINA position resolution to hole mobility

DOE PAGES

Prasher, V. S.; Cromaz, M.; Merchan, E.; ...

2017-02-01

The sensitivity of the position resolution of the gamma-ray tracking array GRETINA to the hole charge-carrier mobility parameter is investigated. The χ 2 results from a fit of averaged signal (“superpulse”) data exhibit a shallow minimum for hole mobilities 15% lower than the currently adopted values. Calibration data on position resolution is analyzed, together with simulations that isolate the hole mobility dependence of signal decomposition from other effects such as electronics cross-talk. Our results effectively exclude hole mobility as a dominant parameter for improving the position resolution for reconstruction of gamma-ray interaction points in GRETINA.

Image-Based Localization for Indoor Environment Using Mobile Phone

NASA Astrophysics Data System (ADS)

Huang, Y.; Wang, H.; Zhan, K.; Zhao, J.; Gui, P.; Feng, T.

2015-05-01

Real-time indoor localization based on supporting infrastructures like wireless devices and QR codes are usually costly and labor intensive to implement. In this study, we explored a cheap alternative approach based on images for indoor localization. A user can localize him/herself by just shooting a photo of the surrounding indoor environment using the mobile phone. No any other equipment is required. This is achieved by employing image-matching and searching techniques with a dataset of pre-captured indoor images. In the beginning, a database of structured images of the indoor environment is constructed by using image matching and the bundle adjustment algorithm. Then each image's relative pose (its position and orientation) is estimated and the semantic locations of images are tagged. A user's location can then be determined by comparing a photo taken by the mobile phone to the database. This is done by combining quick image searching, matching and the relative orientation. This study also try to explore image acquisition plans and the processing capacity of off-the-shell mobile phones. During the whole pipeline, a collection of indoor images with both rich and poor textures are examined. Several feature detectors are used and compared. Pre-processing of complex indoor photo is also implemented on the mobile phone. The preliminary experimental results prove the feasibility of this method. In the future, we are trying to raise the efficiency of matching between indoor images and explore the fast 4G wireless communication to ensure the speed and accuracy of the localization based on a client-server framework.

A Low Cost Mobile Robot Based on Proportional Integral Derivative (PID) Control System and Odometer for Education

NASA Astrophysics Data System (ADS)

Haq, R.; Prayitno, H.; Dzulkiflih; Sucahyo, I.; Rahmawati, E.

2018-03-01

In this article, the development of a low cost mobile robot based on PID controller and odometer for education is presented. PID controller and odometer is applied for controlling mobile robot position. Two-dimensional position vector in cartesian coordinate system have been inserted to robot controller as an initial and final position. Mobile robot has been made based on differential drive and sensor magnetic rotary encoder which measured robot position from a number of wheel rotation. Odometry methode use data from actuator movements for predicting change of position over time. The mobile robot is examined to get final position with three different heading angle 30°, 45° and 60° by applying various value of KP, KD and KI constant.

Time Delay Measurements of Key Generation Process on Smart Cards

DTIC Science & Technology

2015-03-01

random number generator is available (Chatterjee & Gupta, 2009). The ECC algorithm will grow in usage as information becomes more and more secure. Figure...Worldwide Mobile Enterprise Security Software 2012–2016 Forecast and Analysis), mobile identity and access management is expected to grow by 27.6 percent...iPad, tablets) as well as 80000 BlackBerry phones. The mobility plan itself will be deployed in three phases over 2014, with the first phase

Person detection, tracking and following using stereo camera

NASA Astrophysics Data System (ADS)

Wang, Xiaofeng; Zhang, Lilian; Wang, Duo; Hu, Xiaoping

2018-04-01

Person detection, tracking and following is a key enabling technology for mobile robots in many human-robot interaction applications. In this article, we present a system which is composed of visual human detection, video tracking and following. The detection is based on YOLO(You only look once), which applies a single convolution neural network(CNN) to the full image, thus can predict bounding boxes and class probabilities directly in one evaluation. Then the bounding box provides initial person position in image to initialize and train the KCF(Kernelized Correlation Filter), which is a video tracker based on discriminative classifier. At last, by using a stereo 3D sparse reconstruction algorithm, not only the position of the person in the scene is determined, but also it can elegantly solve the problem of scale ambiguity in the video tracker. Extensive experiments are conducted to demonstrate the effectiveness and robustness of our human detection and tracking system.

Dynamic detection of window starting positions and its implementation within an activity recognition framework.

PubMed

Ni, Qin; Patterson, Timothy; Cleland, Ian; Nugent, Chris

2016-08-01

Activity recognition is an intrinsic component of many pervasive computing and ambient intelligent solutions. This has been facilitated by an explosion of technological developments in the area of wireless sensor network, wearable and mobile computing. Yet, delivering robust activity recognition, which could be deployed at scale in a real world environment, still remains an active research challenge. Much of the existing literature to date has focused on applying machine learning techniques to pre-segmented data collected in controlled laboratory environments. Whilst this approach can provide valuable ground truth information from which to build recognition models, these techniques often do not function well when implemented in near real time applications. This paper presents the application of a multivariate online change detection algorithm to dynamically detect the starting position of windows for the purposes of activity recognition. Copyright © 2016 Elsevier Inc. All rights reserved.

ICPL: Intelligent Cooperative Planning and Learning for Multi-agent Systems

DTIC Science & Technology

2012-02-29

objective was to develop a new planning approach for teams!of multiple UAVs that tightly integrates learning and cooperative!control algorithms at... algorithms at multiple levels of the planning architecture. The research results enabled a team of mobile agents to learn to adapt and react to uncertainty in...expressive representation that incorporates feature conjunctions. Our algorithm is simple to implement, fast to execute, and can be combined with any

A novel combined SLAM based on RBPF-SLAM and EIF-SLAM for mobile system sensing in a large scale environment.

PubMed

He, Bo; Zhang, Shujing; Yan, Tianhong; Zhang, Tao; Liang, Yan; Zhang, Hongjin

2011-01-01

Mobile autonomous systems are very important for marine scientific investigation and military applications. Many algorithms have been studied to deal with the computational efficiency problem required for large scale simultaneous localization and mapping (SLAM) and its related accuracy and consistency. Among these methods, submap-based SLAM is a more effective one. By combining the strength of two popular mapping algorithms, the Rao-Blackwellised particle filter (RBPF) and extended information filter (EIF), this paper presents a combined SLAM-an efficient submap-based solution to the SLAM problem in a large scale environment. RBPF-SLAM is used to produce local maps, which are periodically fused into an EIF-SLAM algorithm. RBPF-SLAM can avoid linearization of the robot model during operating and provide a robust data association, while EIF-SLAM can improve the whole computational speed, and avoid the tendency of RBPF-SLAM to be over-confident. In order to further improve the computational speed in a real time environment, a binary-tree-based decision-making strategy is introduced. Simulation experiments show that the proposed combined SLAM algorithm significantly outperforms currently existing algorithms in terms of accuracy and consistency, as well as the computing efficiency. Finally, the combined SLAM algorithm is experimentally validated in a real environment by using the Victoria Park dataset.

A fast and automatic fusion algorithm for unregistered multi-exposure image sequence

NASA Astrophysics Data System (ADS)

Liu, Yan; Yu, Feihong

2014-09-01

Human visual system (HVS) can visualize all the brightness levels of the scene through visual adaptation. However, the dynamic range of most commercial digital cameras and display devices are smaller than the dynamic range of human eye. This implies low dynamic range (LDR) images captured by normal digital camera may lose image details. We propose an efficient approach to high dynamic (HDR) image fusion that copes with image displacement and image blur degradation in a computationally efficient manner, which is suitable for implementation on mobile devices. The various image registration algorithms proposed in the previous literatures are unable to meet the efficiency and performance requirements in the application of mobile devices. In this paper, we selected Oriented Brief (ORB) detector to extract local image structures. The descriptor selected in multi-exposure image fusion algorithm has to be fast and robust to illumination variations and geometric deformations. ORB descriptor is the best candidate in our algorithm. Further, we perform an improved RANdom Sample Consensus (RANSAC) algorithm to reject incorrect matches. For the fusion of images, a new approach based on Stationary Wavelet Transform (SWT) is used. The experimental results demonstrate that the proposed algorithm generates high quality images at low computational cost. Comparisons with a number of other feature matching methods show that our method gets better performance.

Development and Evaluation of Model Algorithms to Account for Chemical Transformation in the Nearroad Environment

EPA Science Inventory

We describe the development and evaluation of two new model algorithms for NOx chemistry in the R-LINE near-road dispersion model for traffic sources. With increased urbanization, there is increased mobility leading to higher amount of traffic related activity on a global scale. ...

Traffic model for the satellite component of UMTS

NASA Technical Reports Server (NTRS)

Hu, Y. F.; Sheriff, R. E.

1995-01-01

An algorithm for traffic volume estimation for satellite mobile communications systems has been developed. This algorithm makes use of worldwide databases for demographic and economic data. In order to provide for such an estimation, the effects of competing services have been considered so that likely market demand can be forecasted. Different user groups of the predicted market have been identified according to expectations in the quality of services and mobility requirement. The number of users for different user groups are calculated taking into account the gross potential market, the penetration rate of the identified services and the profitability to provide such services via satellite.

Performance of a low data rate speech codec for land-mobile satellite communications

NASA Technical Reports Server (NTRS)

Gersho, Allen; Jedrey, Thomas C.

1990-01-01

In an effort to foster the development of new technologies for the emerging land mobile satellite communications services, JPL funded two development contracts in 1984: one to the Univ. of Calif., Santa Barbara and the other to the Georgia Inst. of Technology, to develop algorithms and real time hardware for near toll quality speech compression at 4800 bits per second. Both universities have developed and delivered speech codecs to JPL, and the UCSB codec was extensively tested by JPL in a variety of experimental setups. The basic UCSB speech codec algorithms and the test results of the various experiments performed with this codec are presented.

A secure 3-way routing protocols for intermittently connected mobile ad hoc networks.

PubMed

Sekaran, Ramesh; Parasuraman, Ganesh Kumar

2014-01-01

The mobile ad hoc network may be partially connected or it may be disconnected in nature and these forms of networks are termed intermittently connected mobile ad hoc network (ICMANET). The routing in such disconnected network is commonly an arduous task. Many routing protocols have been proposed for routing in ICMANET since decades. The routing techniques in existence for ICMANET are, namely, flooding, epidemic, probabilistic, copy case, spray and wait, and so forth. These techniques achieve an effective routing with minimum latency, higher delivery ratio, lesser overhead, and so forth. Though these techniques generate effective results, in this paper, we propose novel routing algorithms grounded on agent and cryptographic techniques, namely, location dissemination service (LoDiS) routing with agent AES, A-LoDiS with agent AES routing, and B-LoDiS with agent AES routing, ensuring optimal results with respect to various network routing parameters. The algorithm along with efficient routing ensures higher degree of security. The security level is cited testing with respect to possibility of malicious nodes into the network. This paper also aids, with the comparative results of proposed algorithms, for secure routing in ICMANET.

A Secure 3-Way Routing Protocols for Intermittently Connected Mobile Ad Hoc Networks

PubMed Central

Parasuraman, Ganesh Kumar

2014-01-01

The mobile ad hoc network may be partially connected or it may be disconnected in nature and these forms of networks are termed intermittently connected mobile ad hoc network (ICMANET). The routing in such disconnected network is commonly an arduous task. Many routing protocols have been proposed for routing in ICMANET since decades. The routing techniques in existence for ICMANET are, namely, flooding, epidemic, probabilistic, copy case, spray and wait, and so forth. These techniques achieve an effective routing with minimum latency, higher delivery ratio, lesser overhead, and so forth. Though these techniques generate effective results, in this paper, we propose novel routing algorithms grounded on agent and cryptographic techniques, namely, location dissemination service (LoDiS) routing with agent AES, A-LoDiS with agent AES routing, and B-LoDiS with agent AES routing, ensuring optimal results with respect to various network routing parameters. The algorithm along with efficient routing ensures higher degree of security. The security level is cited testing with respect to possibility of malicious nodes into the network. This paper also aids, with the comparative results of proposed algorithms, for secure routing in ICMANET. PMID:25136697

Evaluation of Driver Visibility from Mobile LIDAR Data and Weather Conditions

NASA Astrophysics Data System (ADS)

González-Jorge, H.; Díaz-Vilariño, L.; Lorenzo, H.; Arias, P.

2016-06-01

Visibility of drivers is crucial to ensure road safety. Visibility is influenced by two main factors, the geometry of the road and the weather present therein. The present work depicts an approach for automatic visibility evaluation using mobile LiDAR data and climate information provided from weather stations located in the neighbourhood of the road. The methodology is based on a ray-tracing algorithm to detect occlusions from point clouds with the purpose of identifying the visibility area from each driver position. The resulting data are normalized with the climate information to provide a polyline with an accurate area of visibility. Visibility ranges from 25 m (heavy fog) to more than 10,000 m (clean atmosphere). Values over 250 m are not taken into account for road safety purposes, since this value corresponds to the maximum braking distance of a vehicle. Two case studies are evaluated an urban road in the city of Vigo (Spain) and an inter-urban road between the city of Ourense and the village of Castro Caldelas (Spain). In both cases, data from the Galician Weather Agency (Meteogalicia) are used. The algorithm shows promising results allowing the detection of particularly dangerous areas from the viewpoint of driver visibility. The mountain road between Ourense and Castro Caldelas, with great presence of slopes and sharp curves, shows special interest for this type of application. In this case, poor visibility can especially contribute to the run over of pedestrians or cyclists traveling on the road shoulders.

Real Time Energy Management Control Strategies for Hybrid Powertrains

NASA Astrophysics Data System (ADS)

Zaher, Mohamed Hegazi Mohamed

In order to improve fuel efficiency and reduce emissions of mobile vehicles, various hybrid power-train concepts have been developed over the years. This thesis focuses on embedded control of hybrid powertrain concepts for mobile vehicle applications. Optimal robust control approach is used to develop a real time energy management strategy for continuous operations. The main idea is to store the normally wasted mechanical regenerative energy in energy storage devices for later usage. The regenerative energy recovery opportunity exists in any condition where the speed of motion is in opposite direction to the applied force or torque. This is the case when the vehicle is braking, decelerating, or the motion is driven by gravitational force, or load driven. There are three main concepts for regernerative energy storing devices in hybrid vehicles: electric, hydraulic, and flywheel. The real time control challenge is to balance the system power demand from the engine and the hybrid storage device, without depleting the energy storage device or stalling the engine in any work cycle, while making optimal use of the energy saving opportunities in a given operational, often repetitive cycle. In the worst case scenario, only engine is used and hybrid system completely disabled. A rule based control is developed and tuned for different work cycles and linked to a gain scheduling algorithm. A gain scheduling algorithm identifies the cycle being performed by the machine and its position via GPS, and maps them to the gains.

Localization of Non-Linearly Modeled Autonomous Mobile Robots Using Out-of-Sequence Measurements

PubMed Central

Besada-Portas, Eva; Lopez-Orozco, Jose A.; Lanillos, Pablo; de la Cruz, Jesus M.

2012-01-01

This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost. PMID:22736962

Localization of non-linearly modeled autonomous mobile robots using out-of-sequence measurements.

PubMed

Besada-Portas, Eva; Lopez-Orozco, Jose A; Lanillos, Pablo; de la Cruz, Jesus M

2012-01-01

This paper presents a state of the art of the estimation algorithms dealing with Out-of-Sequence (OOS) measurements for non-linearly modeled systems. The state of the art includes a critical analysis of the algorithm properties that takes into account the applicability of these techniques to autonomous mobile robot navigation based on the fusion of the measurements provided, delayed and OOS, by multiple sensors. Besides, it shows a representative example of the use of one of the most computationally efficient approaches in the localization module of the control software of a real robot (which has non-linear dynamics, and linear and non-linear sensors) and compares its performance against other approaches. The simulated results obtained with the selected OOS algorithm shows the computational requirements that each sensor of the robot imposes to it. The real experiments show how the inclusion of the selected OOS algorithm in the control software lets the robot successfully navigate in spite of receiving many OOS measurements. Finally, the comparison highlights that not only is the selected OOS algorithm among the best performing ones of the comparison, but it also has the lowest computational and memory cost.

Agent Collaborative Target Localization and Classification in Wireless Sensor Networks

PubMed Central

Wang, Xue; Bi, Dao-wei; Ding, Liang; Wang, Sheng

2007-01-01

Wireless sensor networks (WSNs) are autonomous networks that have been frequently deployed to collaboratively perform target localization and classification tasks. Their autonomous and collaborative features resemble the characteristics of agents. Such similarities inspire the development of heterogeneous agent architecture for WSN in this paper. The proposed agent architecture views WSN as multi-agent systems and mobile agents are employed to reduce in-network communication. According to the architecture, an energy based acoustic localization algorithm is proposed. In localization, estimate of target location is obtained by steepest descent search. The search algorithm adapts to measurement environments by dynamically adjusting its termination condition. With the agent architecture, target classification is accomplished by distributed support vector machine (SVM). Mobile agents are employed for feature extraction and distributed SVM learning to reduce communication load. Desirable learning performance is guaranteed by combining support vectors and convex hull vectors. Fusion algorithms are designed to merge SVM classification decisions made from various modalities. Real world experiments with MICAz sensor nodes are conducted for vehicle localization and classification. Experimental results show the proposed agent architecture remarkably facilitates WSN designs and algorithm implementation. The localization and classification algorithms also prove to be accurate and energy efficient.

Anchor-Free Localization Method for Mobile Targets in Coal Mine Wireless Sensor Networks

PubMed Central

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes’ location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines. PMID:22574048

Anchor-free localization method for mobile targets in coal mine wireless sensor networks.

PubMed

Pei, Zhongmin; Deng, Zhidong; Xu, Shuo; Xu, Xiao

2009-01-01

Severe natural conditions and complex terrain make it difficult to apply precise localization in underground mines. In this paper, an anchor-free localization method for mobile targets is proposed based on non-metric multi-dimensional scaling (Multi-dimensional Scaling: MDS) and rank sequence. Firstly, a coal mine wireless sensor network is constructed in underground mines based on the ZigBee technology. Then a non-metric MDS algorithm is imported to estimate the reference nodes' location. Finally, an improved sequence-based localization algorithm is presented to complete precise localization for mobile targets. The proposed method is tested through simulations with 100 nodes, outdoor experiments with 15 ZigBee physical nodes, and the experiments in the mine gas explosion laboratory with 12 ZigBee nodes. Experimental results show that our method has better localization accuracy and is more robust in underground mines.

SmartMal: a service-oriented behavioral malware detection framework for mobile devices.

PubMed

Wang, Chao; Wu, Zhizhong; Li, Xi; Zhou, Xuehai; Wang, Aili; Hung, Patrick C K

2014-01-01

This paper presents SmartMal--a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. The highlight of SmartMal is to introduce service-oriented architecture (SOA) concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server's main task is to detect anomalies using state-of-art detection algorithms. Multiple distributed servers simultaneously analyze the feature vector using various detectors and information fusion is used to concatenate the results of detectors. We also propose a cycle-based statistical approach for mobile device anomaly detection. We accomplish this by analyzing the users' regular usage patterns. Empirical results suggest that the proposed framework and novel anomaly detection algorithm are highly effective in detecting malware on Android devices.

Reconstructing Spatial Distributions from Anonymized Locations

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

Horey, James L; Forrest, Stephanie; Groat, Michael

2012-01-01

Devices such as mobile phones, tablets, and sensors are often equipped with GPS that accurately report a person's location. Combined with wireless communication, these devices enable a wide range of new social tools and applications. These same qualities, however, leave location-aware applications vulnerable to privacy violations. This paper introduces the Negative Quad Tree, a privacy protection method for location aware applications. The method is broadly applicable to applications that use spatial density information, such as social applications that measure the popularity of social venues. The method employs a simple anonymization algorithm running on mobile devices, and a more complex reconstructionmore » algorithm on a central server. This strategy is well suited to low-powered mobile devices. The paper analyzes the accuracy of the reconstruction method in a variety of simulated and real-world settings and demonstrates that the method is accurate enough to be used in many real-world scenarios.« less

Diffusion control for a tempered anomalous diffusion system using fractional-order PI controllers.

PubMed

Juan Chen; Zhuang, Bo; Chen, YangQuan; Cui, Baotong

2017-05-09

This paper is concerned with diffusion control problem of a tempered anomalous diffusion system based on fractional-order PI controllers. The contribution of this paper is to introduce fractional-order PI controllers into the tempered anomalous diffusion system for mobile actuators motion and spraying control. For the proposed control force, convergence analysis of the system described by mobile actuator dynamical equations is presented based on Lyapunov stability arguments. Moreover, a new Centroidal Voronoi Tessellation (CVT) algorithm based on fractional-order PI controllers, henceforth called FOPI-based CVT algorithm, is provided together with a modified simulation platform called Fractional-Order Diffusion Mobile Actuator-Sensor 2-Dimension Fractional-Order Proportional Integral (FO-Diff-MAS2D-FOPI). Finally, extensive numerical simulations for the tempered anomalous diffusion process are presented to verify the effectiveness of our proposed fractional-order PI controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

SmartMal: A Service-Oriented Behavioral Malware Detection Framework for Mobile Devices

PubMed Central

Wu, Zhizhong; Li, Xi; Zhou, Xuehai; Wang, Aili; Hung, Patrick C. K.

2014-01-01

This paper presents SmartMal—a novel service-oriented behavioral malware detection framework for vehicular and mobile devices. The highlight of SmartMal is to introduce service-oriented architecture (SOA) concepts and behavior analysis into the malware detection paradigms. The proposed framework relies on client-server architecture, the client continuously extracts various features and transfers them to the server, and the server's main task is to detect anomalies using state-of-art detection algorithms. Multiple distributed servers simultaneously analyze the feature vector using various detectors and information fusion is used to concatenate the results of detectors. We also propose a cycle-based statistical approach for mobile device anomaly detection. We accomplish this by analyzing the users' regular usage patterns. Empirical results suggest that the proposed framework and novel anomaly detection algorithm are highly effective in detecting malware on Android devices. PMID:25165729

Access point selection game with mobile users using correlated equilibrium.

PubMed

Sohn, Insoo

2015-01-01

One of the most important issues in wireless local area network (WLAN) systems with multiple access points (APs) is the AP selection problem. Game theory is a mathematical tool used to analyze the interactions in multiplayer systems and has been applied to various problems in wireless networks. Correlated equilibrium (CE) is one of the powerful game theory solution concepts, which is more general than the Nash equilibrium for analyzing the interactions in multiplayer mixed strategy games. A game-theoretic formulation of the AP selection problem with mobile users is presented using a novel scheme based on a regret-based learning procedure. Through convergence analysis, we show that the joint actions based on the proposed algorithm achieve CE. Simulation results illustrate that the proposed algorithm is effective in a realistic WLAN environment with user mobility and achieves maximum system throughput based on the game-theoretic formulation.

Access Point Selection Game with Mobile Users Using Correlated Equilibrium

PubMed Central

Sohn, Insoo

2015-01-01

One of the most important issues in wireless local area network (WLAN) systems with multiple access points (APs) is the AP selection problem. Game theory is a mathematical tool used to analyze the interactions in multiplayer systems and has been applied to various problems in wireless networks. Correlated equilibrium (CE) is one of the powerful game theory solution concepts, which is more general than the Nash equilibrium for analyzing the interactions in multiplayer mixed strategy games. A game-theoretic formulation of the AP selection problem with mobile users is presented using a novel scheme based on a regret-based learning procedure. Through convergence analysis, we show that the joint actions based on the proposed algorithm achieve CE. Simulation results illustrate that the proposed algorithm is effective in a realistic WLAN environment with user mobility and achieves maximum system throughput based on the game-theoretic formulation. PMID:25785726

Mobile capture of remote points of interest using line of sight modelling

NASA Astrophysics Data System (ADS)

Meek, Sam; Priestnall, Gary; Sharples, Mike; Goulding, James

2013-03-01

Recording points of interest using GPS whilst working in the field is an established technique in geographical fieldwork, where the user's current position is used as the spatial reference to be captured; this is known as geo-tagging. We outline the development and evaluation of a smartphone application called Zapp that enables geo-tagging of any distant point on the visible landscape. The ability of users to log or retrieve information relating to what they can see, rather than where they are standing, allows them to record observations of points in the broader landscape scene, or to access descriptions of landscape features from any viewpoint. The application uses the compass orientation and tilt of the phone to provide data for a line of sight algorithm that intersects with a Digital Surface Model stored on the mobile device. We describe the development process and design decisions for Zapp present the results of a controlled study of the accuracy of the application, and report on the use of Zapp for a student field exercise. The studies indicate the feasibility of the approach, but also how the appropriate use of such techniques will be constrained by current levels of precision in mobile sensor technology. The broader implications for interactive query of the distant landscape and for remote data logging are discussed.

Approach and Evaluation of a Mobile Video-Based and Location-Based Augmented Reality Platform for Information Brokerage

NASA Astrophysics Data System (ADS)

Dastageeri, H.; Storz, M.; Koukofikis, A.; Knauth, S.; Coors, V.

2016-09-01

Providing mobile location-based information for pedestrians faces many challenges. On one hand the accuracy of localisation indoors and outdoors is restricted due to technical limitations of GPS and Beacons. Then again only a small display is available to display information as well as to develop a user interface. Plus, the software solution has to consider the hardware characteristics of mobile devices during the implementation process for aiming a performance with minimum latency. This paper describes our approach by including a combination of image tracking and GPS or Beacons to ensure orientation and precision of localisation. To communicate the information on Points of Interest (POIs), we decided to choose Augmented Reality (AR). For this concept of operations, we used besides the display also the acceleration and positions sensors as a user interface. This paper especially goes into detail on the optimization of the image tracking algorithms, the development of the video-based AR player for the Android platform and the evaluation of videos as an AR element in consideration of providing a good user experience. For setting up content for the POIs or even generate a tour we used and extended the Open Geospatial Consortium (OGC) standard Augmented Reality Markup Language (ARML).

Olfaction and Hearing Based Mobile Robot Navigation for Odor/Sound Source Search

PubMed Central

Song, Kai; Liu, Qi; Wang, Qi

2011-01-01

Bionic technology provides a new elicitation for mobile robot navigation since it explores the way to imitate biological senses. In the present study, the challenging problem was how to fuse different biological senses and guide distributed robots to cooperate with each other for target searching. This paper integrates smell, hearing and touch to design an odor/sound tracking multi-robot system. The olfactory robot tracks the chemical odor plume step by step through information fusion from gas sensors and airflow sensors, while two hearing robots localize the sound source by time delay estimation (TDE) and the geometrical position of microphone array. Furthermore, this paper presents a heading direction based mobile robot navigation algorithm, by which the robot can automatically and stably adjust its velocity and direction according to the deviation between the current heading direction measured by magnetoresistive sensor and the expected heading direction acquired through the odor/sound localization strategies. Simultaneously, one robot can communicate with the other robots via a wireless sensor network (WSN). Experimental results show that the olfactory robot can pinpoint the odor source within the distance of 2 m, while two hearing robots can quickly localize and track the olfactory robot in 2 min. The devised multi-robot system can achieve target search with a considerable success ratio and high stability. PMID:22319401

Teaching Robotics Software with the Open Hardware Mobile Manipulator

ERIC Educational Resources Information Center

Vona, M.; Shekar, N. H.

2013-01-01

The "open hardware mobile manipulator" (OHMM) is a new open platform with a unique combination of features for teaching robotics software and algorithms. On-board low- and high-level processors support real-time embedded programming and motor control, as well as higher-level coding with contemporary libraries. Full hardware designs and…

Greedy data transportation scheme with hard packet deadlines for wireless ad hoc networks.

PubMed

Lee, HyungJune

2014-01-01

We present a greedy data transportation scheme with hard packet deadlines in ad hoc sensor networks of stationary nodes and multiple mobile nodes with scheduled trajectory path and arrival time. In the proposed routing strategy, each stationary ad hoc node en route decides whether to relay a shortest-path stationary node toward destination or a passing-by mobile node that will carry closer to destination. We aim to utilize mobile nodes to minimize the total routing cost as far as the selected route can satisfy the end-to-end packet deadline. We evaluate our proposed routing algorithm in terms of routing cost, packet delivery ratio, packet delivery time, and usability of mobile nodes based on network level simulations. Simulation results show that our proposed algorithm fully exploits the remaining time till packet deadline to turn into networking benefits of reducing the overall routing cost and improving packet delivery performance. Also, we demonstrate that the routing scheme guarantees packet delivery with hard deadlines, contributing to QoS improvement in various network services.

Greedy Data Transportation Scheme with Hard Packet Deadlines for Wireless Ad Hoc Networks

PubMed Central

Lee, HyungJune

2014-01-01

We present a greedy data transportation scheme with hard packet deadlines in ad hoc sensor networks of stationary nodes and multiple mobile nodes with scheduled trajectory path and arrival time. In the proposed routing strategy, each stationary ad hoc node en route decides whether to relay a shortest-path stationary node toward destination or a passing-by mobile node that will carry closer to destination. We aim to utilize mobile nodes to minimize the total routing cost as far as the selected route can satisfy the end-to-end packet deadline. We evaluate our proposed routing algorithm in terms of routing cost, packet delivery ratio, packet delivery time, and usability of mobile nodes based on network level simulations. Simulation results show that our proposed algorithm fully exploits the remaining time till packet deadline to turn into networking benefits of reducing the overall routing cost and improving packet delivery performance. Also, we demonstrate that the routing scheme guarantees packet delivery with hard deadlines, contributing to QoS improvement in various network services. PMID:25258736

Dynamic Multiple-Threshold Call Admission Control Based on Optimized Genetic Algorithm in Wireless/Mobile Networks

NASA Astrophysics Data System (ADS)

Wang, Shengling; Cui, Yong; Koodli, Rajeev; Hou, Yibin; Huang, Zhangqin

Due to the dynamics of topology and resources, Call Admission Control (CAC) plays a significant role for increasing resource utilization ratio and guaranteeing users' QoS requirements in wireless/mobile networks. In this paper, a dynamic multi-threshold CAC scheme is proposed to serve multi-class service in a wireless/mobile network. The thresholds are renewed at the beginning of each time interval to react to the changing mobility rate and network load. To find suitable thresholds, a reward-penalty model is designed, which provides different priorities between different service classes and call types through different reward/penalty policies according to network load and average call arrival rate. To speed up the running time of CAC, an Optimized Genetic Algorithm (OGA) is presented, whose components such as encoding, population initialization, fitness function and mutation etc., are all optimized in terms of the traits of the CAC problem. The simulation demonstrates that the proposed CAC scheme outperforms the similar schemes, which means the optimization is realized. Finally, the simulation shows the efficiency of OGA.

Mobile robots for localizing gas emission sources on landfill sites: is bio-inspiration the way to go?

PubMed

Hernandez Bennetts, Victor; Lilienthal, Achim J; Neumann, Patrick P; Trincavelli, Marco

2011-01-01

Roboticists often take inspiration from animals for designing sensors, actuators, or algorithms that control the behavior of robots. Bio-inspiration is motivated with the uncanny ability of animals to solve complex tasks like recognizing and manipulating objects, walking on uneven terrains, or navigating to the source of an odor plume. In particular the task of tracking an odor plume up to its source has nearly exclusively been addressed using biologically inspired algorithms and robots have been developed, for example, to mimic the behavior of moths, dung beetles, or lobsters. In this paper we argue that biomimetic approaches to gas source localization are of limited use, primarily because animals differ fundamentally in their sensing and actuation capabilities from state-of-the-art gas-sensitive mobile robots. To support our claim, we compare actuation and chemical sensing available to mobile robots to the corresponding capabilities of moths. We further characterize airflow and chemosensor measurements obtained with three different robot platforms (two wheeled robots and one flying micro-drone) in four prototypical environments and show that the assumption of a constant and unidirectional airflow, which is the basis of many gas source localization approaches, is usually far from being valid. This analysis should help to identify how underlying principles, which govern the gas source tracking behavior of animals, can be usefully "translated" into gas source localization approaches that fully take into account the capabilities of mobile robots. We also describe the requirements for a reference application, monitoring of gas emissions at landfill sites with mobile robots, and discuss an engineered gas source localization approach based on statistics as an alternative to biologically inspired algorithms.

A mobile platform for automated screening of asthma and chronic obstructive pulmonary disease.

PubMed

Chamberlain, Daniel B; Kodgule, Rahul; Fletcher, Richard Ribon

2016-08-01

Chronic Obstructive Pulmonary Disease (COPD) and asthma each represent a large proportion of the global disease burden; COPD is the third leading cause of death worldwide and asthma is one of the most prevalent chronic diseases, afflicting over 300 million people. Much of this burden is concentrated in the developing world, where patients lack access to physicians trained in the diagnosis of pulmonary disease. As a result, these patients experience high rates of underdiagnosis and misdiagnosis. To address this need, we present a mobile platform capable of screening for Asthma and COPD. Our solution is based on a mobile smart phone and consists of an electronic stethoscope, a peak flow meter application, and a patient questionnaire. This data is combined with a machine learning algorithm to identify patients with asthma and COPD. To test and validate the design, we collected data from 119 healthy and sick participants using our custom mobile application and ran the analysis on a PC computer. For comparison, all subjects were examined by an experienced pulmonologist using a full pulmonary testing laboratory. Employing a two-stage logistic regression model, our algorithms were first able to identify patients with either asthma or COPD from the general population, yielding an ROC curve with an AUC of 0.95. Then, after identifying these patients, our algorithm was able to distinguish between patients with asthma and patients with COPD, yielding an ROC curve with AUC of 0.97. This work represents an important milestone towards creating a self-contained mobile phone-based platform that can be used for screening and diagnosis of pulmonary disease in many parts of the world.

Mobile Robots for Localizing Gas Emission Sources on Landfill Sites: Is Bio-Inspiration the Way to Go?

PubMed Central

Hernandez Bennetts, Victor; Lilienthal, Achim J.; Neumann, Patrick P.; Trincavelli, Marco

2011-01-01

Roboticists often take inspiration from animals for designing sensors, actuators, or algorithms that control the behavior of robots. Bio-inspiration is motivated with the uncanny ability of animals to solve complex tasks like recognizing and manipulating objects, walking on uneven terrains, or navigating to the source of an odor plume. In particular the task of tracking an odor plume up to its source has nearly exclusively been addressed using biologically inspired algorithms and robots have been developed, for example, to mimic the behavior of moths, dung beetles, or lobsters. In this paper we argue that biomimetic approaches to gas source localization are of limited use, primarily because animals differ fundamentally in their sensing and actuation capabilities from state-of-the-art gas-sensitive mobile robots. To support our claim, we compare actuation and chemical sensing available to mobile robots to the corresponding capabilities of moths. We further characterize airflow and chemosensor measurements obtained with three different robot platforms (two wheeled robots and one flying micro-drone) in four prototypical environments and show that the assumption of a constant and unidirectional airflow, which is the basis of many gas source localization approaches, is usually far from being valid. This analysis should help to identify how underlying principles, which govern the gas source tracking behavior of animals, can be usefully “translated” into gas source localization approaches that fully take into account the capabilities of mobile robots. We also describe the requirements for a reference application, monitoring of gas emissions at landfill sites with mobile robots, and discuss an engineered gas source localization approach based on statistics as an alternative to biologically inspired algorithms. PMID:22319493

Haptic augmented skin surface generation toward telepalpation from a mobile skin image.

PubMed

Kim, K

2018-05-01

Very little is known about the methods of integrating palpation techniques to existing mobile teleskin imaging that delivers low quality tactile information (roughness) for telepalpation. However, no study has been reported yet regarding telehaptic palpation using mobile phone images for teledermatology or teleconsultations of skincare. This study is therefore aimed at introducing a new algorithm accurately reconstructing a haptic augmented skin surface for telehaptic palpation using a low-cost clip-on microscope simply attached to a mobile phone. Multiple algorithms such as gradient-based image enhancement, roughness-adaptive tactile mask generation, roughness-enhanced 3D tactile map building, and visual and haptic rendering with a three-degrees-of-freedom (DOF) haptic device were developed and integrated as one system. Evaluation experiments have been conducted to test the performance of 3D roughness reconstruction with/without the tactile mask. The results confirm that reconstructed haptic roughness with the tactile mask is superior to the reconstructed haptic roughness without the tactile mask. Additional experiments demonstrate that the proposed algorithm is robust against varying lighting conditions and blurring. In last, a user study has been designed to see the effect of the haptic modality to the existing visual only interface and the results attest that the haptic skin palpation can significantly improve the skin exam performance. Mobile image-based telehaptic palpation technology was proposed, and an initial version was developed. The developed technology was tested with several skin images and the experimental results showed the superiority of the proposed scheme in terms of the performance of haptic augmentation of real skin images. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Lane Detection on the iPhone

NASA Astrophysics Data System (ADS)

Ren, Feixiang; Huang, Jinsheng; Terauchi, Mutsuhiro; Jiang, Ruyi; Klette, Reinhard

A robust and efficient lane detection system is an essential component of Lane Departure Warning Systems, which are commonly used in many vision-based Driver Assistance Systems (DAS) in intelligent transportation. Various computation platforms have been proposed in the past few years for the implementation of driver assistance systems (e.g., PC, laptop, integrated chips, PlayStation, and so on). In this paper, we propose a new platform for the implementation of lane detection, which is based on a mobile phone (the iPhone). Due to physical limitations of the iPhone w.r.t. memory and computing power, a simple and efficient lane detection algorithm using a Hough transform is developed and implemented on the iPhone, as existing algorithms developed based on the PC platform are not suitable for mobile phone devices (currently). Experiments of the lane detection algorithm are made both on PC and on iPhone.

A vertical handoff decision algorithm based on ARMA prediction model

NASA Astrophysics Data System (ADS)

Li, Ru; Shen, Jiao; Chen, Jun; Liu, Qiuhuan

2012-01-01

With the development of computer technology and the increasing demand for mobile communications, the next generation wireless networks will be composed of various wireless networks (e.g., WiMAX and WiFi). Vertical handoff is a key technology of next generation wireless networks. During the vertical handoff procedure, handoff decision is a crucial issue for an efficient mobility. Based on auto regression moving average (ARMA) prediction model, we propose a vertical handoff decision algorithm, which aims to improve the performance of vertical handoff and avoid unnecessary handoff. Based on the current received signal strength (RSS) and the previous RSS, the proposed approach adopt ARMA model to predict the next RSS. And then according to the predicted RSS to determine whether trigger the link layer triggering event and complete vertical handoff. The simulation results indicate that the proposed algorithm outperforms the RSS-based scheme with a threshold in the performance of handoff and the number of handoff.

Direction of Arrival Estimation with a Novel Single-Port Smart Antenna

NASA Astrophysics Data System (ADS)

Sun, Chen; Karmakar, Nemai C.

2004-12-01

A novel direction of arrival (DOA) estimation technique that uses the conventional multiple-signal classification (MUSIC) algorithm with periodic signals is applied to a single-port smart antenna. Results show that the proposed method gives a high-resolution (1 degree) DOA estimation in an uncorrelated signal environment. The novelty lies in that the MUSIC algorithm is applied to a simplified antenna configuration. Only 1 analogue-to-digital converter (ADC) is used in this antenna, which features low power consumption, low cost, and ease of fabrication. Modifications to the conventional MUSIC algorithm do not bring much additional complexity. The proposed technique is also free from the negative influence by the mutual coupling among antenna elements. Therefore, it offers an economical way to extensively implement smart antennas into the existing wireless mobile communications systems, especially at the power consumption limited mobile terminals such as laptops in wireless networks.

Rule-Based vs. Behavior-Based Self-Deployment for Mobile Wireless Sensor Networks

PubMed Central

Urdiales, Cristina; Aguilera, Francisco; González-Parada, Eva; Cano-García, Jose; Sandoval, Francisco

2016-01-01

In mobile wireless sensor networks (MWSN), nodes are allowed to move autonomously for deployment. This process is meant: (i) to achieve good coverage; and (ii) to distribute the communication load as homogeneously as possible. Rather than optimizing deployment, reactive algorithms are based on a set of rules or behaviors, so nodes can determine when to move. This paper presents an experimental evaluation of both reactive deployment approaches: rule-based and behavior-based ones. Specifically, we compare a backbone dispersion algorithm with a social potential fields algorithm. Most tests are done under simulation for a large number of nodes in environments with and without obstacles. Results are validated using a small robot network in the real world. Our results show that behavior-based deployment tends to provide better coverage and communication balance, especially for a large number of nodes in areas with obstacles. PMID:27399709

Tracked robot controllers for climbing obstacles autonomously

NASA Astrophysics Data System (ADS)

Vincent, Isabelle

2009-05-01

Research in mobile robot navigation has demonstrated some success in navigating flat indoor environments while avoiding obstacles. However, the challenge of analyzing complex environments to climb obstacles autonomously has had very little success due to the complexity of the task. Unmanned ground vehicles currently exhibit simple autonomous behaviours compared to the human ability to move in the world. This paper presents the control algorithms designed for a tracked mobile robot to autonomously climb obstacles by varying its tracks configuration. Two control algorithms are proposed to solve the autonomous locomotion problem for climbing obstacles. First, a reactive controller evaluates the appropriate geometric configuration based on terrain and vehicle geometric considerations. Then, a reinforcement learning algorithm finds alternative solutions when the reactive controller gets stuck while climbing an obstacle. The methodology combines reactivity to learning. The controllers have been demonstrated in box and stair climbing simulations. The experiments illustrate the effectiveness of the proposed approach for crossing obstacles.

Characterization of Extremely Lightweight Intrusion Detection (ELIDe) Power Utilization with Varying Throughput and Payload Sizes

DTIC Science & Technology

2015-09-01

Extremely Lightweight Intrusion Detection (ELIDe) algorithm on an Android -based mobile device. Our results show that the hashing and inner product...approximately 2.5 megabits per second (assuming a normal distribution of packet sizes) with no significant packet loss. 15. SUBJECT TERMS ELIDe, Android , pcap...system (OS). To run ELIDe, the current version was ported for use on Android .4 2.1 Mobile Device After ELIDe was ported to the Android mobile

Spatial-Temporal Data Collection with Compressive Sensing in Mobile Sensor Networks

PubMed Central

Li, Jiayin; Guo, Wenzhong; Chen, Zhonghui; Xiong, Neal

2017-01-01

Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a novel mobile data gathering scheme by employing the Metropolis-Hastings algorithm with delayed acceptance, an improved random walk algorithm for a mobile collector to collect data from a sensing field. The proposed scheme exploits Kronecker compressive sensing (KCS) for spatial-temporal correlation of sensory data by allowing the mobile collector to gather temporal compressive measurements from a small subset of randomly selected nodes along a random routing path. More importantly, from the theoretical perspective we prove that the equivalent sensing matrix constructed from the proposed scheme for spatial-temporal compressible signal can satisfy the property of KCS models. The simulation results demonstrate that the proposed scheme can not only significantly reduce communication cost but also improve recovery accuracy for mobile data gathering compared to the other existing schemes. In particular, we also show that the proposed scheme is robust in unreliable wireless environment under various packet losses. All this indicates that the proposed scheme can be an efficient alternative for data gathering application in WSNs. PMID:29117152

Spatial-Temporal Data Collection with Compressive Sensing in Mobile Sensor Networks.

PubMed

Zheng, Haifeng; Li, Jiayin; Feng, Xinxin; Guo, Wenzhong; Chen, Zhonghui; Xiong, Neal

2017-11-08

Compressive sensing (CS) provides an energy-efficient paradigm for data gathering in wireless sensor networks (WSNs). However, the existing work on spatial-temporal data gathering using compressive sensing only considers either multi-hop relaying based or multiple random walks based approaches. In this paper, we exploit the mobility pattern for spatial-temporal data collection and propose a novel mobile data gathering scheme by employing the Metropolis-Hastings algorithm with delayed acceptance, an improved random walk algorithm for a mobile collector to collect data from a sensing field. The proposed scheme exploits Kronecker compressive sensing (KCS) for spatial-temporal correlation of sensory data by allowing the mobile collector to gather temporal compressive measurements from a small subset of randomly selected nodes along a random routing path. More importantly, from the theoretical perspective we prove that the equivalent sensing matrix constructed from the proposed scheme for spatial-temporal compressible signal can satisfy the property of KCS models. The simulation results demonstrate that the proposed scheme can not only significantly reduce communication cost but also improve recovery accuracy for mobile data gathering compared to the other existing schemes. In particular, we also show that the proposed scheme is robust in unreliable wireless environment under various packet losses. All this indicates that the proposed scheme can be an efficient alternative for data gathering application in WSNs .

AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL.

PubMed

Zhang, Tao; Chen, Liping; Li, Yao

2015-12-30

This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV.

On-Line Method and Apparatus for Coordinated Mobility and Manipulation of Mobile Robots

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1996-01-01

A simple and computationally efficient approach is disclosed for on-line coordinated control of mobile robots consisting of a manipulator arm mounted on a mobile base. The effect of base mobility on the end-effector manipulability index is discussed. The base mobility and arm manipulation degrees-of-freedom are treated equally as the joints of a kinematically redundant composite robot. The redundancy introduced by the mobile base is exploited to satisfy a set of user-defined additional tasks during the end-effector motion. A simple on-line control scheme is proposed which allows the user to assign weighting factors to individual degrees-of-mobility and degrees-of-manipulation, as well as to each task specification. The computational efficiency of the control algorithm makes it particularly suitable for real-time implementations. Four case studies are discussed in detail to demonstrate the application of the coordinated control scheme to various mobile robots.

Point-of-care mobile digital microscopy and deep learning for the detection of soil-transmitted helminths and Schistosoma haematobium.

PubMed

Holmström, Oscar; Linder, Nina; Ngasala, Billy; Mårtensson, Andreas; Linder, Ewert; Lundin, Mikael; Moilanen, Hannu; Suutala, Antti; Diwan, Vinod; Lundin, Johan

2017-06-01

Microscopy remains the gold standard in the diagnosis of neglected tropical diseases. As resource limited, rural areas often lack laboratory equipment and trained personnel, new diagnostic techniques are needed. Low-cost, point-of-care imaging devices show potential in the diagnosis of these diseases. Novel, digital image analysis algorithms can be utilized to automate sample analysis. Evaluation of the imaging performance of a miniature digital microscopy scanner for the diagnosis of soil-transmitted helminths and Schistosoma haematobium, and training of a deep learning-based image analysis algorithm for automated detection of soil-transmitted helminths in the captured images. A total of 13 iodine-stained stool samples containing Ascaris lumbricoides, Trichuris trichiura and hookworm eggs and 4 urine samples containing Schistosoma haematobium were digitized using a reference whole slide-scanner and the mobile microscopy scanner. Parasites in the images were identified by visual examination and by analysis with a deep learning-based image analysis algorithm in the stool samples. Results were compared between the digital and visual analysis of the images showing helminth eggs. Parasite identification by visual analysis of digital slides captured with the mobile microscope was feasible for all analyzed parasites. Although the spatial resolution of the reference slide-scanner is higher, the resolution of the mobile microscope is sufficient for reliable identification and classification of all parasites studied. Digital image analysis of stool sample images captured with the mobile microscope showed high sensitivity for detection of all helminths studied (range of sensitivity = 83.3-100%) in the test set (n = 217) of manually labeled helminth eggs. In this proof-of-concept study, the imaging performance of a mobile, digital microscope was sufficient for visual detection of soil-transmitted helminths and Schistosoma haematobium. Furthermore, we show that deep learning-based image analysis can be utilized for the automated detection and classification of helminths in the captured images.

Point-of-care mobile digital microscopy and deep learning for the detection of soil-transmitted helminths and Schistosoma haematobium

PubMed Central

Holmström, Oscar; Linder, Nina; Ngasala, Billy; Mårtensson, Andreas; Linder, Ewert; Lundin, Mikael; Moilanen, Hannu; Suutala, Antti; Diwan, Vinod; Lundin, Johan

2017-01-01

ABSTRACT Background: Microscopy remains the gold standard in the diagnosis of neglected tropical diseases. As resource limited, rural areas often lack laboratory equipment and trained personnel, new diagnostic techniques are needed. Low-cost, point-of-care imaging devices show potential in the diagnosis of these diseases. Novel, digital image analysis algorithms can be utilized to automate sample analysis. Objective: Evaluation of the imaging performance of a miniature digital microscopy scanner for the diagnosis of soil-transmitted helminths and Schistosoma haematobium, and training of a deep learning-based image analysis algorithm for automated detection of soil-transmitted helminths in the captured images. Methods: A total of 13 iodine-stained stool samples containing Ascaris lumbricoides, Trichuris trichiura and hookworm eggs and 4 urine samples containing Schistosoma haematobium were digitized using a reference whole slide-scanner and the mobile microscopy scanner. Parasites in the images were identified by visual examination and by analysis with a deep learning-based image analysis algorithm in the stool samples. Results were compared between the digital and visual analysis of the images showing helminth eggs. Results: Parasite identification by visual analysis of digital slides captured with the mobile microscope was feasible for all analyzed parasites. Although the spatial resolution of the reference slide-scanner is higher, the resolution of the mobile microscope is sufficient for reliable identification and classification of all parasites studied. Digital image analysis of stool sample images captured with the mobile microscope showed high sensitivity for detection of all helminths studied (range of sensitivity = 83.3–100%) in the test set (n = 217) of manually labeled helminth eggs. Conclusions: In this proof-of-concept study, the imaging performance of a mobile, digital microscope was sufficient for visual detection of soil-transmitted helminths and Schistosoma haematobium. Furthermore, we show that deep learning-based image analysis can be utilized for the automated detection and classification of helminths in the captured images. PMID:28838305

A Novel Energy Saving Algorithm with Frame Response Delay Constraint in IEEE 802.16e

NASA Astrophysics Data System (ADS)

Nga, Dinh Thi Thuy; Kim, Mingon; Kang, Minho

Sleep-mode operation of a Mobile Subscriber Station (MSS) in IEEE 802.16e effectively saves energy consumption; however, it induces frame response delay. In this letter, we propose an algorithm to quickly find the optimal value of the final sleep interval in sleep-mode in order to minimize energy consumption with respect to a given frame response delay constraint. The validations of our proposed algorithm through analytical results and simulation results suggest that our algorithm provide a potential guidance to energy saving.

Multifactorial Understanding of Ion Abundance in Tandem Mass Spectrometry Experiments.

PubMed

Fazal, Zeeshan; Southey, Bruce R; Sweedler, Jonathan V; Rodriguez-Zas, Sandra L

2013-01-29

In a bottom-up shotgun approach, the proteins of a mixture are enzymatically digested, separated, and analyzed via tandem mass spectrometry. The mass spectra relating fragment ion intensities (abundance) to the mass-to-charge are used to deduce the amino acid sequence and identify the peptides and proteins. The variables that influence intensity were characterized using a multi-factorial mixed-effects model, a ten-fold cross-validation, and stepwise feature selection on 6,352,528 fragment ions from 61,543 peptide ions. Intensity was higher in fragment ions that did not have neutral mass loss relative to any mass loss or that had a +1 charge state. Peptide ions classified for proton mobility as non-mobile had lowest intensity of all mobility levels. Higher basic residue (arginine, lysine or histidine) counts in the peptide ion and low counts in the fragment ion were associated with lower fragment ion intensities. Higher counts of proline in peptide and fragment ions were associated with lower intensities. These results are consistent with the mobile proton theory. Opposite trends between peptide and fragment ion counts and intensity may be due to the different impact of factor under consideration at different stages of the MS/MS experiment or to the different distribution of observations across peptide and fragment ion levels. Presence of basic residues at all three positions next to the fragmentation site was associated with lower fragment ion intensity. The presence of proline proximal to the fragmentation site enhanced fragmentation and had the opposite trend when located distant from the site. A positive association between fragment ion intensity and presence of sulfur residues (cysteine and methionine) on the vicinity of the fragmentation site was identified. These results highlight the multi-factorial nature of fragment ion intensity and could improve the algorithms for peptide identification and the simulation in tandem mass spectrometry experiments.

Multifactorial Understanding of Ion Abundance in Tandem Mass Spectrometry Experiments

PubMed Central

Fazal, Zeeshan; Southey, Bruce R; Sweedler, Jonathan V.; Rodriguez-Zas, Sandra L.

2013-01-01

In a bottom-up shotgun approach, the proteins of a mixture are enzymatically digested, separated, and analyzed via tandem mass spectrometry. The mass spectra relating fragment ion intensities (abundance) to the mass-to-charge are used to deduce the amino acid sequence and identify the peptides and proteins. The variables that influence intensity were characterized using a multi-factorial mixed-effects model, a ten-fold cross-validation, and stepwise feature selection on 6,352,528 fragment ions from 61,543 peptide ions. Intensity was higher in fragment ions that did not have neutral mass loss relative to any mass loss or that had a +1 charge state. Peptide ions classified for proton mobility as non-mobile had lowest intensity of all mobility levels. Higher basic residue (arginine, lysine or histidine) counts in the peptide ion and low counts in the fragment ion were associated with lower fragment ion intensities. Higher counts of proline in peptide and fragment ions were associated with lower intensities. These results are consistent with the mobile proton theory. Opposite trends between peptide and fragment ion counts and intensity may be due to the different impact of factor under consideration at different stages of the MS/MS experiment or to the different distribution of observations across peptide and fragment ion levels. Presence of basic residues at all three positions next to the fragmentation site was associated with lower fragment ion intensity. The presence of proline proximal to the fragmentation site enhanced fragmentation and had the opposite trend when located distant from the site. A positive association between fragment ion intensity and presence of sulfur residues (cysteine and methionine) on the vicinity of the fragmentation site was identified. These results highlight the multi-factorial nature of fragment ion intensity and could improve the algorithms for peptide identification and the simulation in tandem mass spectrometry experiments. PMID:24031159

Strengths and Weaknesses of Global Positioning System (GPS) Data-Loggers and Semi-structured Interviews for Capturing Fine-scale Human Mobility: Findings from Iquitos, Peru

PubMed Central

Paz-Soldan, Valerie A.; Reiner, Robert C.; Morrison, Amy C.; Stoddard, Steven T.; Kitron, Uriel; Scott, Thomas W.; Elder, John P.; Halsey, Eric S.; Kochel, Tadeusz J.; Astete, Helvio; Vazquez-Prokopec, Gonzalo M.

2014-01-01

Quantifying human mobility has significant consequences for studying physical activity, exposure to pathogens, and generating more realistic infectious disease models. Location-aware technologies such as Global Positioning System (GPS)-enabled devices are used increasingly as a gold standard for mobility research. The main goal of this observational study was to compare and contrast the information obtained through GPS and semi-structured interviews (SSI) to assess issues affecting data quality and, ultimately, our ability to measure fine-scale human mobility. A total of 160 individuals, ages 7 to 74, from Iquitos, Peru, were tracked using GPS data-loggers for 14 days and later interviewed using the SSI about places they visited while tracked. A total of 2,047 and 886 places were reported in the SSI and identified by GPS, respectively. Differences in the concordance between methods occurred by location type, distance threshold (within a given radius to be considered a match) selected, GPS data collection frequency (i.e., 30, 90 or 150 seconds) and number of GPS points near the SSI place considered to define a match. Both methods had perfect concordance identifying each participant's house, followed by 80–100% concordance for identifying schools and lodgings, and 50–80% concordance for residences and commercial and religious locations. As the distance threshold selected increased, the concordance between SSI and raw GPS data increased (beyond 20 meters most locations reached their maximum concordance). Processing raw GPS data using a signal-clustering algorithm decreased overall concordance to 14.3%. The most common causes of discordance as described by a sub-sample (n = 101) with whom we followed-up were GPS units being accidentally off (30%), forgetting or purposely not taking the units when leaving home (24.8%), possible barriers to the signal (4.7%) and leaving units home to recharge (4.6%). We provide a quantitative assessment of the strengths and weaknesses of both methods for capturing fine-scale human mobility. PMID:24922530

Development and Validation of a New Method to Measure Walking Speed in Free-Living Environments Using the Actibelt® Platform

PubMed Central

Schimpl, Michaela; Lederer, Christian; Daumer, Martin

2011-01-01

Walking speed is a fundamental indicator for human well-being. In a clinical setting, walking speed is typically measured by means of walking tests using different protocols. However, walking speed obtained in this way is unlikely to be representative of the conditions in a free-living environment. Recently, mobile accelerometry has opened up the possibility to extract walking speed from long-time observations in free-living individuals, but the validity of these measurements needs to be determined. In this investigation, we have developed algorithms for walking speed prediction based on 3D accelerometry data (actibelt®) and created a framework using a standardized data set with gold standard annotations to facilitate the validation and comparison of these algorithms. For this purpose 17 healthy subjects operated a newly developed mobile gold standard while walking/running on an indoor track. Subsequently, the validity of 12 candidate algorithms for walking speed prediction ranging from well-known simple approaches like combining step length with frequency to more sophisticated algorithms such as linear and non-linear models was assessed using statistical measures. As a result, a novel algorithm employing support vector regression was found to perform best with a concordance correlation coefficient of 0.93 (95%CI 0.92–0.94) and a coverage probability CP1 of 0.46 (95%CI 0.12–0.70) for a deviation of 0.1 m/s (CP2 0.78, CP3 0.94) when compared to the mobile gold standard while walking indoors. A smaller outdoor experiment confirmed those results with even better coverage probability. We conclude that walking speed thus obtained has the potential to help establish walking speed in free-living environments as a patient-oriented outcome measure. PMID:21850254

An E-Learning Environment for Algorithmic: Toward an Active Construction of Skills

ERIC Educational Resources Information Center

Babori, Abdelghani; Fassi, Hicham Fihri; Hariri, Abdellah; Bideq, Mustapha

2016-01-01

Assimilating an algorithmic course is a persistent problem for many undergraduate students. The major problem faced by students is the lack of problem solving ability and flexibility. Therefore, students are generally passive, unmotivated and unable to mobilize all the acquired knowledge (loops, test, variables, etc.) to deal with new encountered…

Demonstration of Prognostics-Enabled Decision Making Algorithms on a Hardware Mobile Robot Test Platform

DTIC Science & Technology

2014-10-02

were described in (Balaban, Saxena, Bansal , Goebel, & Curran, 2009; Poll et al., 2011), and, in the course of this work, three types of sensor faults...enabled decision making algorithms. International Journal of Prognostics and Health Management, 4(1). Balaban, E., Saxena, A., Bansal , P., Goebel, K. F

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

Kurt Derr

Mobile Ad hoc NETworks (MANETs) are distributed self-organizing networks that can change locations and configure themselves on the fly. This paper focuses on an algorithmic approach for the deployment of a MANET within an enclosed area, such as a building in a disaster scenario, which can provide a robust communication infrastructure for search and rescue operations. While a virtual spring mesh (VSM) algorithm provides scalable, self-organizing, and fault-tolerant capabilities required by aMANET, the VSM lacks the MANET's capabilities of deployment mechanisms for blanket coverage of an area and does not provide an obstacle avoidance mechanism. This paper presents a newmore » technique, an extended VSM (EVSM) algorithm that provides the following novelties: (1) new control laws for exploration and expansion to provide blanket coverage, (2) virtual adaptive springs enabling the mesh to expand as necessary, (3) adapts to communications disturbances by varying the density and movement of mobile nodes, and (4) new metrics to assess the performance of the EVSM algorithm. Simulation results show that EVSM provides up to 16% more coverage and is 3.5 times faster than VSM in environments with eight obstacles.« less

Communication target object recognition for D2D connection with feature size limit

NASA Astrophysics Data System (ADS)

Ok, Jiheon; Kim, Soochang; Kim, Young-hoon; Lee, Chulhee

2015-03-01

Recently, a new concept of device-to-device (D2D) communication, which is called "point-and-link communication" has attracted great attentions due to its intuitive and simple operation. This approach enables user to communicate with target devices without any pre-identification information such as SSIDs, MAC addresses by selecting the target image displayed on the user's own device. In this paper, we present an efficient object matching algorithm that can be applied to look(point)-and-link communications for mobile services. Due to the limited channel bandwidth and low computational power of mobile terminals, the matching algorithm should satisfy low-complexity, low-memory and realtime requirements. To meet these requirements, we propose fast and robust feature extraction by considering the descriptor size and processing time. The proposed algorithm utilizes a HSV color histogram, SIFT (Scale Invariant Feature Transform) features and object aspect ratios. To reduce the descriptor size under 300 bytes, a limited number of SIFT key points were chosen as feature points and histograms were binarized while maintaining required performance. Experimental results show the robustness and the efficiency of the proposed algorithm.

Development of a mobile satellite communication unit

NASA Technical Reports Server (NTRS)

Suzuki, Ryutaro; Ikegami, Tetsushi; Hamamoto, Naokazu; Taguchi, Tetsu; Endo, Nobuhiro; Yamamoto, Osamu; Ichiyoshi, Osamu

1988-01-01

A compact 210(W) x 280(H) x 330(D) mm mobile terminal capable of transmitting voice and data through L-band mobile satellites is described. The Voice Codec can convert an analog voice to or from digital codes at rates of 9.6, 8 and 4.8 kb/s by an MPC algorithm. The terminal functions with a single 12 V power supplied vehicle battery. The equipment can operate at any L-band frequency allocated for mobile uses in a full duplex mode and will soon be put into a field test via Japans's ETS-V satellite.

Positive Educational Responses to Indigenous Student Mobility

ERIC Educational Resources Information Center

Hill, Angela; Lynch, Andrea; Dalley-Trim, Leanne

2012-01-01

Engaging positively with the mobility of Indigenous students has been the centre of a 5-year action research project in Queensland, Australia. Drawing on responses developed for other marginalised mobile populations, and with consideration for the extent of mobility amongst many Indigenous people in Australia, this paper focuses on the…

AUV Underwater Positioning Algorithm Based on Interactive Assistance of SINS and LBL

PubMed Central

Zhang, Tao; Chen, Liping; Li, Yao

2015-01-01

This paper studies an underwater positioning algorithm based on the interactive assistance of a strapdown inertial navigation system (SINS) and LBL, and this algorithm mainly includes an optimal correlation algorithm with aided tracking of an SINS/Doppler velocity log (DVL)/magnetic compass pilot (MCP), a three-dimensional TDOA positioning algorithm of Taylor series expansion and a multi-sensor information fusion algorithm. The final simulation results show that compared to traditional underwater positioning algorithms, this scheme can not only directly correct accumulative errors caused by a dead reckoning algorithm, but also solves the problem of ambiguous correlation peaks caused by multipath transmission of underwater acoustic signals. The proposed method can calibrate the accumulative error of the AUV position more directly and effectively, which prolongs the underwater operating duration of the AUV. PMID:26729120

Mobility-Dependent Motion Planning for High Speed Robotic Vehicles

DTIC Science & Technology

2008-07-25

of the vehicle’s mobility in such type of terrain. Moreover, autonomous driv- ing of wheeled vehicles at high speeds adds a new level of complexity due...dynamic effects such as wheel slip, skidding, ballistic behavior, rollover, and vehicle-terrain interaction phenomena. Navigation algorithms must also...description of mobility was defined as the probability that for a given 6 ini ial v 10 ity at an initial po ition h robo will hav a non-n gative ve- loci y

Secure Infrastructure-Less Network (SINET)

DTIC Science & Technology

2017-06-01

Protocol CNSA Commercial National Security Algorithm COMSEC Communications Security COTS Commercial off the Shelf CSfC Commercial Solutions for...ABSTRACT (maximum 200 words) Military leaders and first responders desire the familiarity of commercial -off-the-shelf lightweight mobile devices while...since they lack reliable or secure communication infrastructure. Routine and simple mobile information-sharing tasks become a challenge over the

SU-E-J-115: Correlation of Displacement Vector Fields Calculated by Deformable Image Registration Algorithms with Motion Parameters of CT Images with Well-Defined Targets and Controlled-Motion

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

Jaskowiak, J; Ahmad, S; Ali, I

Purpose: To investigate correlation of displacement vector fields (DVF) calculated by deformable image registration algorithms with motion parameters in helical axial and cone-beam CT images with motion artifacts. Methods: A mobile thorax phantom with well-known targets with different sizes that were made from water-equivalent material and inserted in foam to simulate lung lesions. The thorax phantom was imaged with helical, axial and cone-beam CT. The phantom was moved with a cyclic motion with different motion amplitudes and frequencies along the superior-inferior direction. Different deformable image registration algorithms including demons, fast demons, Horn-Shunck and iterative-optical-flow from the DIRART software were usedmore » to deform CT images for the phantom with different motion patterns. The CT images of the mobile phantom were deformed to CT images of the stationary phantom. Results: The values of displacement vectors calculated by deformable image registration algorithm correlated strongly with motion amplitude where large displacement vectors were calculated for CT images with large motion amplitudes. For example, the maximal displacement vectors were nearly equal to the motion amplitudes (5mm, 10mm or 20mm) at interfaces between the mobile targets lung tissue, while the minimal displacement vectors were nearly equal to negative the motion amplitudes. The maximal and minimal displacement vectors matched with edges of the blurred targets along the Z-axis (motion-direction), while DVF’s were small in the other directions. This indicates that the blurred edges by phantom motion were shifted largely to match with the actual target edge. These shifts were nearly equal to the motion amplitude. Conclusions: The DVF from deformable-image registration algorithms correlated well with motion amplitude of well-defined mobile targets. This can be used to extract motion parameters such as amplitude. However, as motion amplitudes increased, image artifacts increased significantly and that limited image quality and poor correlation between the motion amplitude and DVF was obtained.« less

Fuzzy Logic-based Intelligent Scheme for Enhancing QoS of Vertical Handover Decision in Vehicular Ad-hoc Networks

NASA Astrophysics Data System (ADS)

Azzali, F.; Ghazali, O.; Omar, M. H.

2017-08-01

The design of next generation networks in various technologies under the “Anywhere, Anytime” paradigm offers seamless connectivity across different coverage. A conventional algorithm such as RSSThreshold algorithm, that only uses the received strength signal (RSS) as a metric, will decrease handover performance regarding handover latency, delay, packet loss, and handover failure probability. Moreover, the RSS-based algorithm is only suitable for horizontal handover decision to examine the quality of service (QoS) compared to the vertical handover decision in advanced technologies. In the next generation network, vertical handover can be started based on the user’s convenience or choice rather than connectivity reasons. This study proposes a vertical handover decision algorithm that uses a Fuzzy Logic (FL) algorithm, to increase QoS performance in heterogeneous vehicular ad-hoc networks (VANET). The study uses network simulator 2.29 (NS 2.29) along with the mobility traffic network and generator to implement simulation scenarios and topologies. This helps the simulation to achieve a realistic VANET mobility scenario. The required analysis on the performance of QoS in the vertical handover can thus be conducted. The proposed Fuzzy Logic algorithm shows improvement over the conventional algorithm (RSSThreshold) in the average percentage of handover QoS whereby it achieves 20%, 21% and 13% improvement on handover latency, delay, and packet loss respectively. This is achieved through triggering a process in layer two and three that enhances the handover performance.

Some Novel Design Principles for Collective Behaviors in Mobile Robots

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

OSBOURN, GORDON C.

2002-09-01

We present a set of novel design principles to aid in the development of complex collective behaviors in fleets of mobile robots. The key elements are: the use of a graph algorithm that we have created, with certain proven properties, that guarantee scalable local communications for fleets of arbitrary size; the use of artificial forces to simplify the design of motion control; the use of certain proximity values in the graph algorithm to simplify the sharing of robust navigation and sensor information among the robots. We describe these design elements and present a computer simulation that illustrates the behaviors readilymore » achievable with these design tools.« less

Prevention of Malicious Nodes Communication in MANETs by Using Authorized Tokens

NASA Astrophysics Data System (ADS)

Chandrakant, N.; Shenoy, P. Deepa; Venugopal, K. R.; Patnaik, L. M.

A rapid increase of wireless networks and mobile computing applications has changed the landscape of network security. A MANET is more susceptible to the attacks than wired network. As a result, attacks with malicious intent have been and will be devised to take advantage of these vulnerabilities and to cripple the MANET operation. Hence we need to search for new architecture and mechanisms to protect the wireless networks and mobile computing applications. In this paper, we examine the nodes that come under the vicinity of base node and members of the network and communication is provided to genuine nodes only. It is found that the proposed algorithm is a effective algorithm for security in MANETs.

Gating based on internal/external signals with dynamic correlation updates.

PubMed

Wu, Huanmei; Zhao, Qingya; Berbeco, Ross I; Nishioka, Seiko; Shirato, Hiroki; Jiang, Steve B

2008-12-21

Precise localization of mobile tumor positions in real time is critical to the success of gated radiotherapy. Tumor positions are usually derived from either internal or external surrogates. Fluoroscopic gating based on internal surrogates, such as implanted fiducial markers, is accurate however requiring a large amount of imaging dose. Gating based on external surrogates, such as patient abdominal surface motion, is non-invasive however less accurate due to the uncertainty in the correlation between tumor location and external surrogates. To address these complications, we propose to investigate an approach based on hybrid gating with dynamic internal/external correlation updates. In this approach, the external signal is acquired at high frequency (such as 30 Hz) while the internal signal is sparsely acquired (such as 0.5 Hz or less). The internal signal is used to validate and update the internal/external correlation during treatment. Tumor positions are derived from the external signal based on the newly updated correlation. Two dynamic correlation updating algorithms are introduced. One is based on the motion amplitude and the other is based on the motion phase. Nine patients with synchronized internal/external motion signals are simulated retrospectively to evaluate the effectiveness of hybrid gating. The influences of different clinical conditions on hybrid gating, such as the size of gating windows, the optimal timing for internal signal acquisition and the acquisition frequency are investigated. The results demonstrate that dynamically updating the internal/external correlation in or around the gating window will reduce false positive with relatively diminished treatment efficiency. This improvement will benefit patients with mobile tumors, especially greater for early stage lung cancers, for which the tumors are less attached or freely floating in the lung.

A Novel Walking Detection and Step Counting Algorithm Using Unconstrained Smartphones.

PubMed

Kang, Xiaomin; Huang, Baoqi; Qi, Guodong

2018-01-19

Recently, with the development of artificial intelligence technologies and the popularity of mobile devices, walking detection and step counting have gained much attention since they play an important role in the fields of equipment positioning, saving energy, behavior recognition, etc. In this paper, a novel algorithm is proposed to simultaneously detect walking motion and count steps through unconstrained smartphones in the sense that the smartphone placement is not only arbitrary but also alterable. On account of the periodicity of the walking motion and sensitivity of gyroscopes, the proposed algorithm extracts the frequency domain features from three-dimensional (3D) angular velocities of a smartphone through FFT (fast Fourier transform) and identifies whether its holder is walking or not irrespective of its placement. Furthermore, the corresponding step frequency is recursively updated to evaluate the step count in real time. Extensive experiments are conducted by involving eight subjects and different walking scenarios in a realistic environment. It is shown that the proposed method achieves the precision of 93.76 % and recall of 93.65 % for walking detection, and its overall performance is significantly better than other well-known methods. Moreover, the accuracy of step counting by the proposed method is 95.74 % , and is better than both of the several well-known counterparts and commercial products.

Differential-Drive Mobile Robot Control Design based-on Linear Feedback Control Law

NASA Astrophysics Data System (ADS)

Nurmaini, Siti; Dewi, Kemala; Tutuko, Bambang

2017-04-01

This paper deals with the problem of how to control differential driven mobile robot with simple control law. When mobile robot moves from one position to another to achieve a position destination, it always produce some errors. Therefore, a mobile robot requires a certain control law to drive the robot’s movement to the position destination with a smallest possible error. In this paper, in order to reduce position error, a linear feedback control is proposed with pole placement approach to regulate the polynoms desired. The presented work leads to an improved understanding of differential-drive mobile robot (DDMR)-based kinematics equation, which will assist to design of suitable controllers for DDMR movement. The result show by using the linier feedback control method with pole placement approach the position error is reduced and fast convergence is achieved.

Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network.

PubMed

Al-Mayouf, Yusor Rafid Bahar; Ismail, Mahamod; Abdullah, Nor Fadzilah; Wahab, Ainuddin Wahid Abdul; Mahdi, Omar Adil; Khan, Suleman; Choo, Kim-Kwang Raymond

2016-01-01

Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destination node via multi-hop routing techniques. An appropriate, efficient, and stable routing algorithm must be developed for various VANET applications to address the issues of dynamic topology and intermittent connectivity. Therefore, this paper proposes a novel routing algorithm called efficient and stable routing algorithm based on user mobility and node density (ESRA-MD). The proposed algorithm can adapt to significant changes that may occur in the urban vehicular environment. This algorithm works by selecting an optimal route on the basis of hop count and link duration for delivering data from source to destination, thereby satisfying various quality of service considerations. The validity of the proposed algorithm is investigated by its comparison with ARP-QD protocol, which works on the mechanism of optimal route finding in VANETs in urban environments. Simulation results reveal that the proposed ESRA-MD algorithm shows remarkable improvement in terms of delivery ratio, delivery delay, and communication overhead.

Toward Risk Reduction for Mobile Service Composition.

PubMed

Deng, Shuiguang; Huang, Longtao; Li, Ying; Zhou, Honggeng; Wu, Zhaohui; Cao, Xiongfei; Kataev, Mikhail Yu; Li, Ling

2016-08-01

The advances in mobile technologies enable us to consume or even provide services through powerful mobile devices anytime and anywhere. Services running on mobile devices within limited range can be composed to coordinate together through wireless communication technologies and perform complex tasks. However, the mobility of users and devices in mobile environment imposes high risk on the execution of the tasks. This paper targets reducing this risk by constructing a dependable service composition after considering the mobility of both service requesters and providers. It first proposes a risk model and clarifies the risk of mobile service composition; and then proposes a service composition approach by modifying the simulated annealing algorithm. Our objective is to form a service composition by selecting mobile services under the mobility model and to ensure the service composition have the best quality of service and the lowest risk. The experimental results demonstrate that our approach can yield near-optimal solutions and has a nearly linear complexity with respect to a problem size.

Mediator Effects of Positive Emotions on Social Support and Depression among Adolescents Suffering from Mobile Phone Addiction.

PubMed

Li, Menglong; Jiang, Xia; Ren, Yujia

2017-06-01

Depression is a common mental disorder that is widely seen among adolescents suffering from mobile phone addiction. While it is well known that both positive emtions in adolescents wiotions and social support can have a positive impact by helping individuals to maintain a positive attitude, the correlation between positive emotions, social support, and depression among these adolescents remains to be investigated. This study examined the mediator effects of positive emotions on the relationship between social support and depression among adolescents suffering from mobile phone addiction. For this study, conducted in 2016, we selected 1,346 adolescent students from three middle schools (ranging from Junior Grade One to Senior Grade Three) in Hunan Province of China, to participate in the survey. Participants were selected using the stratified cluster random sampling method, and all participants remained anonymous throughout the study. Each participant completed the Self-made General Situation Questionnaire, the Social Support Rating Scale, the Positive and Negative Affect Schedule, the Center for Epidemiological Studies Depression Scale, and the Mobile Phone Addiction Tendency Scale. There was significant positive correlation between positive emotions and social support. Both positive emotions and social support demonstrated significant negative correlation with depression. Positive emotions had partial mediator effects on the relationship between social support and depression (P<0.01). Both social support and positive emotions can lower levels of depression among adolescents suffering from mobile phone addiction. Social support contributes to positive emoth mobile phone addiction, thereby reducing their levels of depression. These findings suggest that more support and care should be given to this particular adolescent population.

Fine-Tuning ADAS Algorithm Parameters for Optimizing Traffic ...

EPA Pesticide Factsheets

With the development of the Connected Vehicle technology that facilitates wirelessly communication among vehicles and road-side infrastructure, the Advanced Driver Assistance Systems (ADAS) can be adopted as an effective tool for accelerating traffic safety and mobility optimization at various highway facilities. To this end, the traffic management centers identify the optimal ADAS algorithm parameter set that enables the maximum improvement of the traffic safety and mobility performance, and broadcast the optimal parameter set wirelessly to individual ADAS-equipped vehicles. After adopting the optimal parameter set, the ADAS-equipped drivers become active agents in the traffic stream that work collectively and consistently to prevent traffic conflicts, lower the intensity of traffic disturbances, and suppress the development of traffic oscillations into heavy traffic jams. Successful implementation of this objective requires the analysis capability of capturing the impact of the ADAS on driving behaviors, and measuring traffic safety and mobility performance under the influence of the ADAS. To address this challenge, this research proposes a synthetic methodology that incorporates the ADAS-affected driving behavior modeling and state-of-the-art microscopic traffic flow modeling into a virtually simulated environment. Building on such an environment, the optimal ADAS algorithm parameter set is identified through an optimization programming framework to enable th

An agenda-based routing protocol in delay tolerant mobile sensor networks.

PubMed

Wang, Xiao-Min; Zhu, Jin-Qi; Liu, Ming; Gong, Hai-Gang

2010-01-01

Routing in delay tolerant mobile sensor networks (DTMSNs) is challenging due to the networks' intermittent connectivity. Most existing routing protocols for DTMSNs use simplistic random mobility models for algorithm design and performance evaluation. In the real world, however, due to the unique characteristics of human mobility, currently existing random mobility models may not work well in environments where mobile sensor units are carried (such as DTMSNs). Taking a person's social activities into consideration, in this paper, we seek to improve DTMSN routing in terms of social structure and propose an agenda based routing protocol (ARP). In ARP, humans are classified based on their agendas and data transmission is made according to sensor nodes' transmission rankings. The effectiveness of ARP is demonstrated through comprehensive simulation studies.

Securing Mobile Networks in an Operational Setting

NASA Technical Reports Server (NTRS)

Ivancic, William D.; Stewart, David H.; Bell, Terry L.; Paulsen, Phillip E.; Shell, Dan

2004-01-01

This paper describes a network demonstration and three month field trial of mobile networking using mobile-IPv4. The network was implemented as part of the US Coast Guard operational network which is a ".mil" network and requires stringent levels of security. The initial demonstrations took place in November 2002 and a three month field trial took place from July through September of 2003. The mobile network utilized encryptors capable of NSA-approved Type 1 algorithms, mobile router from Cisco Systems and 802.11 and satellite wireless links. This paper also describes a conceptual architecture for wide-scale deployment of secure mobile networking in operational environments where both private and public infrastructure is used. Additional issues presented include link costs, placement of encryptors and running routing protocols over layer-3 encryption devices.

Efficient audio signal processing for embedded systems

NASA Astrophysics Data System (ADS)

Chiu, Leung Kin

As mobile platforms continue to pack on more computational power, electronics manufacturers start to differentiate their products by enhancing the audio features. However, consumers also demand smaller devices that could operate for longer time, hence imposing design constraints. In this research, we investigate two design strategies that would allow us to efficiently process audio signals on embedded systems such as mobile phones and portable electronics. In the first strategy, we exploit properties of the human auditory system to process audio signals. We designed a sound enhancement algorithm to make piezoelectric loudspeakers sound ”richer" and "fuller." Piezoelectric speakers have a small form factor but exhibit poor response in the low-frequency region. In the algorithm, we combine psychoacoustic bass extension and dynamic range compression to improve the perceived bass coming out from the tiny speakers. We also developed an audio energy reduction algorithm for loudspeaker power management. The perceptually transparent algorithm extends the battery life of mobile devices and prevents thermal damage in speakers. This method is similar to audio compression algorithms, which encode audio signals in such a ways that the compression artifacts are not easily perceivable. Instead of reducing the storage space, however, we suppress the audio contents that are below the hearing threshold, therefore reducing the signal energy. In the second strategy, we use low-power analog circuits to process the signal before digitizing it. We designed an analog front-end for sound detection and implemented it on a field programmable analog array (FPAA). The system is an example of an analog-to-information converter. The sound classifier front-end can be used in a wide range of applications because programmable floating-gate transistors are employed to store classifier weights. Moreover, we incorporated a feature selection algorithm to simplify the analog front-end. A machine learning algorithm AdaBoost is used to select the most relevant features for a particular sound detection application. In this classifier architecture, we combine simple "base" analog classifiers to form a strong one. We also designed the circuits to implement the AdaBoost-based analog classifier.

Review of electronic-nose technologies and algorithms to detect hazardous chemicals in the environment

Treesearch

Alphus D. Wilson

2012-01-01

Novel mobile electronic-nose (e-nose) devices and algorithms capable of real-time detection of industrial and municipal pollutants, released from point-sources, recently have been developed by scientists worldwide that are useful for monitoring specific environmental-pollutant levels for enforcement and implementation of effective pollution-abatement programs. E-nose...

Ground truth and benchmarks for performance evaluation

NASA Astrophysics Data System (ADS)

Takeuchi, Ayako; Shneier, Michael; Hong, Tsai Hong; Chang, Tommy; Scrapper, Christopher; Cheok, Geraldine S.

2003-09-01

Progress in algorithm development and transfer of results to practical applications such as military robotics requires the setup of standard tasks, of standard qualitative and quantitative measurements for performance evaluation and validation. Although the evaluation and validation of algorithms have been discussed for over a decade, the research community still faces a lack of well-defined and standardized methodology. The range of fundamental problems include a lack of quantifiable measures of performance, a lack of data from state-of-the-art sensors in calibrated real-world environments, and a lack of facilities for conducting realistic experiments. In this research, we propose three methods for creating ground truth databases and benchmarks using multiple sensors. The databases and benchmarks will provide researchers with high quality data from suites of sensors operating in complex environments representing real problems of great relevance to the development of autonomous driving systems. At NIST, we have prototyped a High Mobility Multi-purpose Wheeled Vehicle (HMMWV) system with a suite of sensors including a Riegl ladar, GDRS ladar, stereo CCD, several color cameras, Global Position System (GPS), Inertial Navigation System (INS), pan/tilt encoders, and odometry . All sensors are calibrated with respect to each other in space and time. This allows a database of features and terrain elevation to be built. Ground truth for each sensor can then be extracted from the database. The main goal of this research is to provide ground truth databases for researchers and engineers to evaluate algorithms for effectiveness, efficiency, reliability, and robustness, thus advancing the development of algorithms.

Multi-modal low cost mobile indoor surveillance system on the Robust Artificial Intelligence-based Defense Electro Robot (RAIDER)

NASA Astrophysics Data System (ADS)

Nair, Binu M.; Diskin, Yakov; Asari, Vijayan K.

2012-10-01

We present an autonomous system capable of performing security check routines. The surveillance machine, the Clearpath Husky robotic platform, is equipped with three IP cameras with different orientations for the surveillance tasks of face recognition, human activity recognition, autonomous navigation and 3D reconstruction of its environment. Combining the computer vision algorithms onto a robotic machine has given birth to the Robust Artificial Intelligencebased Defense Electro-Robot (RAIDER). The end purpose of the RAIDER is to conduct a patrolling routine on a single floor of a building several times a day. As the RAIDER travels down the corridors off-line algorithms use two of the RAIDER's side mounted cameras to perform a 3D reconstruction from monocular vision technique that updates a 3D model to the most current state of the indoor environment. Using frames from the front mounted camera, positioned at the human eye level, the system performs face recognition with real time training of unknown subjects. Human activity recognition algorithm will also be implemented in which each detected person is assigned to a set of action classes picked to classify ordinary and harmful student activities in a hallway setting.The system is designed to detect changes and irregularities within an environment as well as familiarize with regular faces and actions to distinguish potentially dangerous behavior. In this paper, we present the various algorithms and their modifications which when implemented on the RAIDER serves the purpose of indoor surveillance.

Beyond where to how: a machine learning approach for sensing mobility contexts using smartphone sensors.

PubMed

Guinness, Robert E

2015-04-28

This paper presents the results of research on the use of smartphone sensors (namely, GPS and accelerometers), geospatial information (points of interest, such as bus stops and train stations) and machine learning (ML) to sense mobility contexts. Our goal is to develop techniques to continuously and automatically detect a smartphone user's mobility activities, including walking, running, driving and using a bus or train, in real-time or near-real-time (<5 s). We investigated a wide range of supervised learning techniques for classification, including decision trees (DT), support vector machines (SVM), naive Bayes classifiers (NB), Bayesian networks (BN), logistic regression (LR), artificial neural networks (ANN) and several instance-based classifiers (KStar, LWLand IBk). Applying ten-fold cross-validation, the best performers in terms of correct classification rate (i.e., recall) were DT (96.5%), BN (90.9%), LWL (95.5%) and KStar (95.6%). In particular, the DT-algorithm RandomForest exhibited the best overall performance. After a feature selection process for a subset of algorithms, the performance was improved slightly. Furthermore, after tuning the parameters of RandomForest, performance improved to above 97.5%. Lastly, we measured the computational complexity of the classifiers, in terms of central processing unit (CPU) time needed for classification, to provide a rough comparison between the algorithms in terms of battery usage requirements. As a result, the classifiers can be ranked from lowest to highest complexity (i.e., computational cost) as follows: SVM, ANN, LR, BN, DT, NB, IBk, LWL and KStar. The instance-based classifiers take considerably more computational time than the non-instance-based classifiers, whereas the slowest non-instance-based classifier (NB) required about five-times the amount of CPU time as the fastest classifier (SVM). The above results suggest that DT algorithms are excellent candidates for detecting mobility contexts in smartphones, both in terms of performance and computational complexity.

Beyond Where to How: A Machine Learning Approach for Sensing Mobility Contexts Using Smartphone Sensors †

PubMed Central

Guinness, Robert E.

2015-01-01

This paper presents the results of research on the use of smartphone sensors (namely, GPS and accelerometers), geospatial information (points of interest, such as bus stops and train stations) and machine learning (ML) to sense mobility contexts. Our goal is to develop techniques to continuously and automatically detect a smartphone user's mobility activities, including walking, running, driving and using a bus or train, in real-time or near-real-time (<5 s). We investigated a wide range of supervised learning techniques for classification, including decision trees (DT), support vector machines (SVM), naive Bayes classifiers (NB), Bayesian networks (BN), logistic regression (LR), artificial neural networks (ANN) and several instance-based classifiers (KStar, LWLand IBk). Applying ten-fold cross-validation, the best performers in terms of correct classification rate (i.e., recall) were DT (96.5%), BN (90.9%), LWL (95.5%) and KStar (95.6%). In particular, the DT-algorithm RandomForest exhibited the best overall performance. After a feature selection process for a subset of algorithms, the performance was improved slightly. Furthermore, after tuning the parameters of RandomForest, performance improved to above 97.5%. Lastly, we measured the computational complexity of the classifiers, in terms of central processing unit (CPU) time needed for classification, to provide a rough comparison between the algorithms in terms of battery usage requirements. As a result, the classifiers can be ranked from lowest to highest complexity (i.e., computational cost) as follows: SVM, ANN, LR, BN, DT, NB, IBk, LWL and KStar. The instance-based classifiers take considerably more computational time than the non-instance-based classifiers, whereas the slowest non-instance-based classifier (NB) required about five-times the amount of CPU time as the fastest classifier (SVM). The above results suggest that DT algorithms are excellent candidates for detecting mobility contexts in smartphones, both in terms of performance and computational complexity. PMID:25928060

Fast words boundaries localization in text fields for low quality document images

NASA Astrophysics Data System (ADS)

Ilin, Dmitry; Novikov, Dmitriy; Polevoy, Dmitry; Nikolaev, Dmitry

2018-04-01

The paper examines the problem of word boundaries precise localization in document text zones. Document processing on a mobile device consists of document localization, perspective correction, localization of individual fields, finding words in separate zones, segmentation and recognition. While capturing an image with a mobile digital camera under uncontrolled capturing conditions, digital noise, perspective distortions or glares may occur. Further document processing gets complicated because of its specifics: layout elements, complex background, static text, document security elements, variety of text fonts. However, the problem of word boundaries localization has to be solved at runtime on mobile CPU with limited computing capabilities under specified restrictions. At the moment, there are several groups of methods optimized for different conditions. Methods for the scanned printed text are quick but limited only for images of high quality. Methods for text in the wild have an excessively high computational complexity, thus, are hardly suitable for running on mobile devices as part of the mobile document recognition system. The method presented in this paper solves a more specialized problem than the task of finding text on natural images. It uses local features, a sliding window and a lightweight neural network in order to achieve an optimal algorithm speed-precision ratio. The duration of the algorithm is 12 ms per field running on an ARM processor of a mobile device. The error rate for boundaries localization on a test sample of 8000 fields is 0.3

The Effects of International Mobility on European Researchers: Comparing Intra-EU and U.S. Mobility

ERIC Educational Resources Information Center

Veugelers, Reinhilde; Van Bouwel, Linda

2015-01-01

Using econometric analysis on survey data from European-born and European-educated researchers who are internationally mobile after their PhD within Europe or to the United States, we find significant positive effects from international mobility on scientific productivity, as well as several other positive career development effects. European…

Ubiquitous User Localization in LBS - The Need for Implementing Ethical Thinking in Our Research Field

NASA Astrophysics Data System (ADS)

Retscher, Guenther; Obex, Franz

2015-12-01

Location-based Services (LBS) influence nowadays every individual's life due to the emerging market penetration of smartphones and other mobile devices. For smartphone Apps localization technologies are developed ranging from GNSS beyond to other alternative ubiquitous positioning methods as well as the use of the in-built inertial sensors, such as accelerometers, gyroscopes, magnetometer, barometer, etc. Moreover, signals-of-opportunity which are not intended for positioning at the first sight but are receivable in many environments such as in buildings and public spaces are more and more utilized for positioning and navigation. The use of Wi-Fi (Wireless Fidelity) is a typical example. These technologies, however, have become very powerful tools as the enable to track an individual or even a group of users. Most technical researchers imply that it is mainly about further enhancing technologies and algorithms including the development of new advanced Apps to improve personal navigation and to deliver location oriented information just in time to a single LBS user or group of users. The authors claim that there is a need that ethical and political issues have to be addressed within our research community from the very beginning. Although there is a lot of research going on in developing algorithms to keep ones data and LBS search request in private, researchers can no longer keep their credibility without cooperating with ethical experts or an ethical committee. In a study called InKoPoMoVer (Cooperative Positioning for Real-time User Assistance and Guidance at Multi-modal Public Transit Junctions) a cooperation with social scientists was initiated for the first time at the Vienna University of Technology, Austria, in this context. The major aims of this study in relation to ethical questions are addressed in this paper.

Estimation of TOA based MUSIC algorithm and cross correlation algorithm of appropriate interval

NASA Astrophysics Data System (ADS)

Lin, Wei; Liu, Jun; Zhou, Yineng; Huang, Jiyan

2017-03-01

Localization of mobile station (MS) has now gained considerable attention due to its wide applications in military, environmental, health and commercial systems. Phrase angle and encode data of MSK system model are two critical parameters in time-of-arrival (TOA) localization technique; nevertheless, precise value of phrase angle and encode data are not easy to achieved in general. In order to meet the actual situation, we should consider the condition that phase angle and encode data is unknown. In this paper, a novel TOA localization method, which combine MUSIC algorithm and cross correlation algorithm in an appropriate interval, is proposed. Simulations show that the proposed method has better performance than music algorithm and cross correlation algorithm of the whole interval.

The influence of alexithymia on mobile phone addiction: The role of depression, anxiety and stress.

PubMed

Gao, Tingting; Li, Jiaomeng; Zhang, Han; Gao, Jinglei; Kong, Yixi; Hu, Yueyang; Mei, Songli

2018-01-01

Alexithymia is an important predictor of mobile phone addiction. Enhancing and improving college students' mental health can reduce the rate of mobile phone addiction. However, it is not clear about the role of depression, anxiety and stress in the relationship between college students' alexithymia and mobile phone addiction. A total of 1105 college students were tested with the Toronto Alexithymia Scale, the Depression Anxiety Stress Scale and the Mobile Phone Addiction Index. An individual's level of alexithymia was significantly correlated with depression, anxiety, stress and mobile phone addiction. Alexithymia had a significantly positive prediction effect on mobile phone addiction, and depression, anxiety, and stress on mobile phone are positive predictors. Depression, anxiety or stress had partially mediating effects between alexithymia and mobile phone addiction. Alexithymia not only directly had a positively impact on mobile phone addiction, but both also had an indirect effect on mobile phone addiction through depression, anxiety or stress. Limitations included sampling method and modest sample size, self-report measures, and unmeasured potential confounders. Alexithymia is an important correlate of mobile phone addiction, and depression, anxiety or stress is an important mediator in this relationship. Copyright © 2017 Elsevier B.V. All rights reserved.

Design of Compressed Sensing Algorithm for Coal Mine IoT Moving Measurement Data Based on a Multi-Hop Network and Total Variation.

PubMed

Wang, Gang; Zhao, Zhikai; Ning, Yongjie

2018-05-28

As the application of a coal mine Internet of Things (IoT), mobile measurement devices, such as intelligent mine lamps, cause moving measurement data to be increased. How to transmit these large amounts of mobile measurement data effectively has become an urgent problem. This paper presents a compressed sensing algorithm for the large amount of coal mine IoT moving measurement data based on a multi-hop network and total variation. By taking gas data in mobile measurement data as an example, two network models for the transmission of gas data flow, namely single-hop and multi-hop transmission modes, are investigated in depth, and a gas data compressed sensing collection model is built based on a multi-hop network. To utilize the sparse characteristics of gas data, the concept of total variation is introduced and a high-efficiency gas data compression and reconstruction method based on Total Variation Sparsity based on Multi-Hop (TVS-MH) is proposed. According to the simulation results, by using the proposed method, the moving measurement data flow from an underground distributed mobile network can be acquired and transmitted efficiently.

Aided target recognition processing of MUDSS sonar data

NASA Astrophysics Data System (ADS)

Lau, Brian; Chao, Tien-Hsin

1998-09-01

The Mobile Underwater Debris Survey System (MUDSS) is a collaborative effort by the Navy and the Jet Propulsion Lab to demonstrate multi-sensor, real-time, survey of underwater sites for ordnance and explosive waste (OEW). We describe the sonar processing algorithm, a novel target recognition algorithm incorporating wavelets, morphological image processing, expansion by Hermite polynomials, and neural networks. This algorithm has found all planted targets in MUDSS tests and has achieved spectacular success upon another Coastal Systems Station (CSS) sonar image database.

A novel cooperative localization algorithm using enhanced particle filter technique in maritime search and rescue wireless sensor network.

PubMed

Wu, Huafeng; Mei, Xiaojun; Chen, Xinqiang; Li, Junjun; Wang, Jun; Mohapatra, Prasant

2018-07-01

Maritime search and rescue (MSR) play a significant role in Safety of Life at Sea (SOLAS). However, it suffers from scenarios that the measurement information is inaccurate due to wave shadow effect when utilizing wireless Sensor Network (WSN) technology in MSR. In this paper, we develop a Novel Cooperative Localization Algorithm (NCLA) in MSR by using an enhanced particle filter method to reduce measurement errors on observation model caused by wave shadow effect. First, we take into account the mobility of nodes at sea to develop a motion model-Lagrangian model. Furthermore, we introduce both state model and observation model to constitute a system model for particle filter (PF). To address the impact of the wave shadow effect on the observation model, we develop an optimal parameter derived by Kullback-Leibler divergence (KLD) to mitigate the error. After the optimal parameter is acquired, an improved likelihood function is presented. Finally, the estimated position is acquired. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Cloud-based mobility management in heterogeneous wireless networks

NASA Astrophysics Data System (ADS)

Kravchuk, Serhii; Minochkin, Dmytro; Omiotek, Zbigniew; Bainazarov, Ulan; Weryńska-Bieniasz, RóŻa; Iskakova, Aigul

2017-08-01

Mobility management is the key feature that supports the roaming of users between different systems. Handover is the essential aspect in the development of solutions supporting mobility scenarios. The handover process becomes more complex in a heterogeneous environment compared to the homogeneous one. Seamlessness and reduction of delay in servicing the handover calls, which can reduce the handover dropping probability, also require complex algorithms to provide a desired QoS for mobile users. A challenging problem to increase the scalability and availability of handover decision mechanisms is discussed. The aim of the paper is to propose cloud based handover as a service concept to cope with the challenges that arise.

Evaluation of HIV testing algorithms in Ethiopia: the role of the tie-breaker algorithm and weakly reacting test lines in contributing to a high rate of false positive HIV diagnoses.

PubMed

Shanks, Leslie; Siddiqui, M Ruby; Kliescikova, Jarmila; Pearce, Neil; Ariti, Cono; Muluneh, Libsework; Pirou, Erwan; Ritmeijer, Koert; Masiga, Johnson; Abebe, Almaz

2015-02-03

In Ethiopia a tiebreaker algorithm using 3 rapid diagnostic tests (RDTs) in series is used to diagnose HIV. Discordant results between the first 2 RDTs are resolved by a third 'tiebreaker' RDT. Médecins Sans Frontières uses an alternate serial algorithm of 2 RDTs followed by a confirmation test for all double positive RDT results. The primary objective was to compare the performance of the tiebreaker algorithm with a serial algorithm, and to evaluate the addition of a confirmation test to both algorithms. A secondary objective looked at the positive predictive value (PPV) of weakly reactive test lines. The study was conducted in two HIV testing sites in Ethiopia. Study participants were recruited sequentially until 200 positive samples were reached. Each sample was re-tested in the laboratory on the 3 RDTs and on a simple to use confirmation test, the Orgenics Immunocomb Combfirm® (OIC). The gold standard test was the Western Blot, with indeterminate results resolved by PCR testing. 2620 subjects were included with a HIV prevalence of 7.7%. Each of the 3 RDTs had an individual specificity of at least 99%. The serial algorithm with 2 RDTs had a single false positive result (1 out of 204) to give a PPV of 99.5% (95% CI 97.3%-100%). The tiebreaker algorithm resulted in 16 false positive results (PPV 92.7%, 95% CI: 88.4%-95.8%). Adding the OIC confirmation test to either algorithm eliminated the false positives. All the false positives had at least one weakly reactive test line in the algorithm. The PPV of weakly reacting RDTs was significantly lower than those with strongly positive test lines. The risk of false positive HIV diagnosis in a tiebreaker algorithm is significant. We recommend abandoning the tie-breaker algorithm in favour of WHO recommended serial or parallel algorithms, interpreting weakly reactive test lines as indeterminate results requiring further testing except in the setting of blood transfusion, and most importantly, adding a confirmation test to the RDT algorithm. It is now time to focus research efforts on how best to translate this knowledge into practice at the field level. Clinical Trial registration #: NCT01716299.

Dynamic Resource Adjustment to Provide Seamless Streaming Services on Multimedia Mobile Cellular Networks

NASA Astrophysics Data System (ADS)

Lin, Chow-Sing; Yen, Fang-Zhi

With the rapid advances in wireless network communication, multimedia presentation has become more applicable. However, due to the limited wireless network resource and the mobility of Mobile Host (MH), QoS for wireless streaming is much more difficult to maintain. How to decrease Call Dropping Probability (CDP) in multimedia traffic while still keeping acceptable Call Block Probability (CBP) without sacrificing QoS has become an significant issue in providing wireless streaming services. In this paper, we propose a novel Dynamic Resources Adjustment (DRA) algorithm, which can dynamically borrow idle reserved resources in the serving cell or the target cell for handoffing MHs to compensate the shortage of bandwidth in media streaming. The experimental simulation results show that compared with traditional No Reservation (NR), and Resource Reservation in the six neighboring cells (RR-nb), and Resource Reservation in the target cell (RR-t), our proposed DRA algorithm can fully utilize unused reserved resources to effectively decrease the CDP while still keeping acceptable CBP with high bandwidth utilization.

Traffic light detection and intersection crossing using mobile computer vision

NASA Astrophysics Data System (ADS)

Grewei, Lynne; Lagali, Christopher

2017-05-01

The solution for Intersection Detection and Crossing to support the development of blindBike an assisted biking system for the visually impaired is discussed. Traffic light detection and intersection crossing are key needs in the task of biking. These problems are tackled through the use of mobile computer vision, in the form of a mobile application on an Android phone. This research builds on previous Traffic Light detection algorithms with a focus on efficiency and compatibility on a resource-limited platform. Light detection is achieved through blob detection algorithms utilizing training data to detect patterns of Red, Green and Yellow in complex real world scenarios where multiple lights may be present. Also, issues of obscurity and scale are addressed. Safe Intersection crossing in blindBike is also discussed. This module takes a conservative "assistive" technology approach. To achieve this blindBike use's not only the Android device but, an external bike cadence Bluetooth/Ant enabled sensor. Real world testing results are given and future work is discussed.

Real-time dual-band haptic music player for mobile devices.

PubMed

Hwang, Inwook; Lee, Hyeseon; Choi, Seungmoon

2013-01-01

We introduce a novel dual-band haptic music player for real-time simultaneous vibrotactile playback with music in mobile devices. Our haptic music player features a new miniature dual-mode actuator that can produce vibrations consisting of two principal frequencies and a real-time vibration generation algorithm that can extract vibration commands from a music file for dual-band playback (bass and treble). The algorithm uses a "haptic equalizer" and provides plausible sound-to-touch modality conversion based on human perceptual data. In addition, we present a user study carried out to evaluate the subjective performance (precision, harmony, fun, and preference) of the haptic music player, in comparison with the current practice of bass-band-only vibrotactile playback via a single-frequency voice-coil actuator. The evaluation results indicated that the new dual-band playback outperforms the bass-only rendering, also providing several insights for further improvements. The developed system and experimental findings have implications for improving the multimedia experience with mobile devices.

Wave energy focusing to subsurface poroelastic formations to promote oil mobilization

NASA Astrophysics Data System (ADS)

Karve, Pranav M.; Kallivokas, Loukas F.

2015-07-01

We discuss an inverse source formulation aimed at focusing wave energy produced by ground surface sources to target subsurface poroelastic formations. The intent of the focusing is to facilitate or enhance the mobility of oil entrapped within the target formation. The underlying forward wave propagation problem is cast in two spatial dimensions for a heterogeneous poroelastic target embedded within a heterogeneous elastic semi-infinite host. The semi-infiniteness of the elastic host is simulated by augmenting the (finite) computational domain with a buffer of perfectly matched layers. The inverse source algorithm is based on a systematic framework of partial-differential-equation-constrained optimization. It is demonstrated, via numerical experiments, that the algorithm is capable of converging to the spatial and temporal characteristics of surface loads that maximize energy delivery to the target formation. Consequently, the methodology is well-suited for designing field implementations that could meet a desired oil mobility threshold. Even though the methodology, and the results presented herein are in two dimensions, extensions to three dimensions are straightforward.

Distributed Matrix Completion: Applications to Cooperative Positioning in Noisy Environments

DTIC Science & Technology

2013-12-11

positioning, and a gossip version of low-rank approximation were developed. A convex relaxation for positioning in the presence of noise was shown...computing the leading eigenvectors of a large data matrix through gossip algorithms. A new algorithm is proposed that amounts to iteratively multiplying...generalization of gossip algorithms for consensus. The algorithms outperform state-of-the-art methods in a communication-limited scenario. Positioning via

Calculating the return on investment of mobile healthcare.

PubMed

Oriol, Nancy E; Cote, Paul J; Vavasis, Anthony P; Bennet, Jennifer; Delorenzo, Darien; Blanc, Philip; Kohane, Isaac

2009-06-02

Mobile health clinics provide an alternative portal into the healthcare system for the medically disenfranchised, that is, people who are underinsured, uninsured or who are otherwise outside of mainstream healthcare due to issues of trust, language, immigration status or simply location. Mobile health clinics as providers of last resort are an essential component of the healthcare safety net providing prevention, screening, and appropriate triage into mainstream services. Despite the face value of providing services to underserved populations, a focused analysis of the relative value of the mobile health clinic model has not been elucidated. The question that the return on investment algorithm has been designed to answer is: can the value of the services provided by mobile health programs be quantified in terms of quality adjusted life years saved and estimated emergency department expenditures avoided? Using a sample mobile health clinic and published research that quantifies health outcomes, we developed and tested an algorithm to calculate the return on investment of a typical broad-service mobile health clinic: the relative value of mobile health clinic services = annual projected emergency department costs avoided + value of potential life years saved from the services provided. Return on investment ratio = the relative value of the mobile health clinic services/annual cost to run the mobile health clinic. Based on service data provided by The Family Van for 2008 we calculated the annual cost savings from preventing emergency room visits, $3,125,668 plus the relative value of providing 7 of the top 25 priority prevention services during the same period, US$17,780,000 for a total annual value of $20,339,968. Given that the annual cost to run the program was $567,700, the calculated return on investment of The Family Van was 36:1. By using published data that quantify the value of prevention practices and the value of preventing unnecessary use of emergency departments, an empirical method was developed to determine the value of a typical mobile health clinic. The Family Van, a mobile health clinic that has been serving the medically disenfranchised of Boston for 16 years, was evaluated accordingly and found to have return on investment of $36 for every $1 invested in the program.

Model Predictive Control considering Reachable Range of Wheels for Leg / Wheel Mobile Robots

NASA Astrophysics Data System (ADS)

Suzuki, Naito; Nonaka, Kenichiro; Sekiguchi, Kazuma

2016-09-01

Obstacle avoidance is one of the important tasks for mobile robots. In this paper, we study obstacle avoidance control for mobile robots equipped with four legs comprised of three DoF SCARA leg/wheel mechanism, which enables the robot to change its shape adapting to environments. Our previous method achieves obstacle avoidance by model predictive control (MPC) considering obstacle size and lateral wheel positions. However, this method does not ensure existence of joint angles which achieves reference wheel positions calculated by MPC. In this study, we propose a model predictive control considering reachable mobile ranges of wheels positions by combining multiple linear constraints, where each reachable mobile range is approximated as a convex trapezoid. Thus, we achieve to formulate a MPC as a quadratic problem with linear constraints for nonlinear problem of longitudinal and lateral wheel position control. By optimization of MPC, the reference wheel positions are calculated, while each joint angle is determined by inverse kinematics. Considering reachable mobile ranges explicitly, the optimal joint angles are calculated, which enables wheels to reach the reference wheel positions. We verify its advantages by comparing the proposed method with the previous method through numerical simulations.

Mobile Tele-Mental Health: Increasing Applications and a Move to Hybrid Models of Care

PubMed Central

Chan, Steven Richard; Torous, John; Hinton, Ladson; Yellowlees, Peter

2014-01-01

Mobile telemental health is defined as the use of mobile phones and other wireless devices as applied to psychiatric and mental health practice. Applications of such include treatment monitoring and adherence, health promotion, ecological momentary assessment, and decision support systems. Advantages of mobile telemental health are underscored by its interactivity, just-in-time interventions, and low resource requirements and portability. Challenges in realizing this potential of mobile telemental health include the low penetration rates of health applications on mobile devices in part due to health literacy, the delay in current published research in evaluating newer technologies, and outdated research methodologies. Despite such challenges, one immediate opportunity for mobile telemental health is utilizing mobile devices as videoconferencing mediums for psychotherapy and psychosocial interventions enhanced by novel sensor based monitoring and behavior-prediction algorithms. This paper provides an overview of mobile telemental health and its current trends, as well as future opportunities as applied to patient care in both academic research and commercial ventures. PMID:27429272

Mobile Tele-Mental Health: Increasing Applications and a Move to Hybrid Models of Care.

PubMed

Chan, Steven Richard; Torous, John; Hinton, Ladson; Yellowlees, Peter

2014-05-06

Mobile telemental health is defined as the use of mobile phones and other wireless devices as applied to psychiatric and mental health practice. Applications of such include treatment monitoring and adherence, health promotion, ecological momentary assessment, and decision support systems. Advantages of mobile telemental health are underscored by its interactivity, just-in-time interventions, and low resource requirements and portability. Challenges in realizing this potential of mobile telemental health include the low penetration rates of health applications on mobile devices in part due to health literacy, the delay in current published research in evaluating newer technologies, and outdated research methodologies. Despite such challenges, one immediate opportunity for mobile telemental health is utilizing mobile devices as videoconferencing mediums for psychotherapy and psychosocial interventions enhanced by novel sensor based monitoring and behavior-prediction algorithms. This paper provides an overview of mobile telemental health and its current trends, as well as future opportunities as applied to patient care in both academic research and commercial ventures.

Self-Adaptive Correction of Heading Direction in Stair Climbing for Tracked Mobile Robots Using Visual Servoing Approach

NASA Astrophysics Data System (ADS)

Ji, Peng; Song, Aiguo; Song, Zimo; Liu, Yuqing; Jiang, Guohua; Zhao, Guopu

2017-02-01

In this paper, we describe a heading direction correction algorithm for a tracked mobile robot. To save hardware resources as far as possible, the mobile robot’s wrist camera is used as the only sensor, which is rotated to face stairs. An ensemble heading deviation detector is proposed to help the mobile robot correct its heading direction. To improve the generalization ability, a multi-scale Gabor filter is used to process the input image previously. Final deviation result is acquired by applying the majority vote strategy on all the classifiers’ results. The experimental results show that our detector is able to enable the mobile robot to correct its heading direction adaptively while it is climbing the stairs.

A framework with Cucho algorithm for discovering regular plans in mobile clients

NASA Astrophysics Data System (ADS)

Tsiligaridis, John

2017-09-01

In a mobile computing system, broadcasting has become a very interesting and challenging research issue. The server continuously broadcasts data to mobile users; the data can be inserted into customized size relations and broadcasted as Regular Broadcast Plan (RBP) with multiple channels. Two algorithms, given the data size for each provided service, the Basic Regular (BRA) and the Partition Value Algorithm (PVA) can provide a static and dynamic RBP construction with multiple constraints solutions respectively. Servers have to define the data size of the services and can provide a feasible RBP working with many broadcasting plan operations. The operations become more complicated when there are many kinds of services and the sizes of data sets are unknown to the server. To that end a framework has been developed that also gives the ability to select low or high capacity channels for servicing. Theorems with new analytical results can provide direct conditions that can state the existence of solutions for the RBP problem with the compound criterion. Two kinds of solutions are provided: the equal and the non equal subrelation solutions. The Cucho Search Algorithm (CS) with the Levy flight behavior has been selected for the optimization. The CS for RBP (CSRP) is developed applying the theorems to the discovery of RBPs. An additional change to CS has been made in order to increase the local search. The CS can also discover RBPs with the minimum number of channels. From all the above modern servers can be upgraded with these possibilities in regards to RBPs discovery with fewer channels.

Algorithms for Automatic Alignment of Arrays

NASA Technical Reports Server (NTRS)

Chatterjee, Siddhartha; Gilbert, John R.; Oliker, Leonid; Schreiber, Robert; Sheffler, Thomas J.

1996-01-01

Aggregate data objects (such as arrays) are distributed across the processor memories when compiling a data-parallel language for a distributed-memory machine. The mapping determines the amount of communication needed to bring operands of parallel operations into alignment with each other. A common approach is to break the mapping into two stages: an alignment that maps all the objects to an abstract template, followed by a distribution that maps the template to the processors. This paper describes algorithms for solving the various facets of the alignment problem: axis and stride alignment, static and mobile offset alignment, and replication labeling. We show that optimal axis and stride alignment is NP-complete for general program graphs, and give a heuristic method that can explore the space of possible solutions in a number of ways. We show that some of these strategies can give better solutions than a simple greedy approach proposed earlier. We also show how local graph contractions can reduce the size of the problem significantly without changing the best solution. This allows more complex and effective heuristics to be used. We show how to model the static offset alignment problem using linear programming, and we show that loop-dependent mobile offset alignment is sometimes necessary for optimum performance. We describe an algorithm with for determining mobile alignments for objects within do loops. We also identify situations in which replicated alignment is either required by the program itself or can be used to improve performance. We describe an algorithm based on network flow that replicates objects so as to minimize the total amount of broadcast communication in replication.

Seeking sex partners through the internet and mobile phone applications among men who have sex with men in Taiwan.

PubMed

Ko, Nai-Ying; Tseng, Po-Chia; Huang, Yu-Chao; Chen, Yen-Chin; Hsu, Su-Ting

2016-07-01

It has become popular for men who have sex with men (MSM) to use mobile-phone geosocial networking applications (mobile apps) to find sex partners. A cross-sectional online survey was conducted in Taiwan to compare the sexual and substance-use behaviors of MSM seeking sex partners through the internet and mobile apps. Of the 1060 participants, 65.8% used the internet via computer and 37.7% used a mobile app to find sexual partners, while 30.3% used recreational drugs or alcohol in the previous 6 months. MSM who exclusively used mobile apps to seek sex partners were significantly more likely than MSM seeking sex via computer to be older, to have used recreational drugs or alcohol, and to have sex with HIV-positive partners. Additionally, using mobile apps to seek sex partners was significantly associated with having sex with online partners through either mobile apps or computer-based internet use (adjusted odds ratio (AOR), 7.12 [3.87-13.11]), self-reporting as HIV-positive (AOR, 2.24 [1.12-4.12]), using recreational drugs (AOR, 1.67 [1.21-2.32]), having disclosed HIV status to sexual partners (AOR, 1.44 [1.03-2.02]), and having sex with HIV-positive partners (AOR, 1.81 [1.06-3.10]). In conclusion, the mobile apps may serve as a feasible platform for HIV-positive MSM to find other HIV-positive partners.

Physiological Parameter Monitoring from Optical Recordings with a Mobile Phone

PubMed Central

Scully, Christopher G.; Lee, Jinseok; Meyer, Joseph; Gorbach, Alexander M.; Granquist-Fraser, Domhnull; Mendelson, Yitzhak

2012-01-01

We show that a mobile phone can serve as an accurate monitor for several physiological variables, based on its ability to record and analyze the varying color signals of a fingertip placed in contact with its optical sensor. We confirm the accuracy of measurements of breathing rate, cardiac R-R intervals, and blood oxygen saturation, by comparisons to standard methods for making such measurements (respiration belts, ECGs, and pulse-oximeters, respectively). Measurement of respiratory rate uses a previously reported algorithm developed for use with a pulse-oximeter, based on amplitude and frequency modulation sequences within the light signal. We note that this technology can also be used with recently developed algorithms for detection of atrial fibrillation or blood loss. PMID:21803676

A development of intelligent entertainment robot for home life

NASA Astrophysics Data System (ADS)

Kim, Cheoltaek; Lee, Ju-Jang

2005-12-01

The purpose of this paper was to present the study and design idea for entertainment robot with educational purpose (IRFEE). The robot has been designed for home life considering dependability and interaction. The developed robot has three objectives - 1. Develop autonomous robot, 2. Design robot considering mobility and robustness, 3. Develop robot interface and software considering entertainment and education functionalities. The autonomous navigation was implemented by active vision based SLAM and modified EPF algorithm. The two differential wheels, the pan-tilt were designed mobility and robustness and the exterior was designed considering esthetic element and minimizing interference. The speech and tracking algorithm provided the good interface with human. The image transfer and Internet site connection is needed for service of remote connection and educational purpose.

Speech coding at 4800 bps for mobile satellite communications

NASA Technical Reports Server (NTRS)

Gersho, Allen; Chan, Wai-Yip; Davidson, Grant; Chen, Juin-Hwey; Yong, Mei

1988-01-01

A speech compression project has recently been completed to develop a speech coding algorithm suitable for operation in a mobile satellite environment aimed at providing telephone quality natural speech at 4.8 kbps. The work has resulted in two alternative techniques which achieve reasonably good communications quality at 4.8 kbps while tolerating vehicle noise and rather severe channel impairments. The algorithms are embodied in a compact self-contained prototype consisting of two AT and T 32-bit floating-point DSP32 digital signal processors (DSP). A Motorola 68HC11 microcomputer chip serves as the board controller and interface handler. On a wirewrapped card, the prototype's circuit footprint amounts to only 200 sq cm, and consumes about 9 watts of power.

Face verification system for Android mobile devices using histogram based features

NASA Astrophysics Data System (ADS)

Sato, Sho; Kobayashi, Kazuhiro; Chen, Qiu

2016-07-01

This paper proposes a face verification system that runs on Android mobile devices. In this system, facial image is captured by a built-in camera on the Android device firstly, and then face detection is implemented using Haar-like features and AdaBoost learning algorithm. The proposed system verify the detected face using histogram based features, which are generated by binary Vector Quantization (VQ) histogram using DCT coefficients in low frequency domains, as well as Improved Local Binary Pattern (Improved LBP) histogram in spatial domain. Verification results with different type of histogram based features are first obtained separately and then combined by weighted averaging. We evaluate our proposed algorithm by using publicly available ORL database and facial images captured by an Android tablet.

The spectral positioning algorithm of new spectrum vehicle based on convex programming in wireless sensor network

NASA Astrophysics Data System (ADS)

Zhang, Yongjun; Lu, Zhixin

2017-10-01

Spectrum resources are very precious, so it is increasingly important to locate interference signals rapidly. Convex programming algorithms in wireless sensor networks are often used as localization algorithms. But in view of the traditional convex programming algorithm is too much overlap of wireless sensor nodes that bring low positioning accuracy, the paper proposed a new algorithm. Which is mainly based on the traditional convex programming algorithm, the spectrum car sends unmanned aerial vehicles (uses) that can be used to record data periodically along different trajectories. According to the probability density distribution, the positioning area is segmented to further reduce the location area. Because the algorithm only increases the communication process of the power value of the unknown node and the sensor node, the advantages of the convex programming algorithm are basically preserved to realize the simple and real-time performance. The experimental results show that the improved algorithm has a better positioning accuracy than the original convex programming algorithm.

Wire-positioning algorithm for coreless Hall array sensors in current measurement

NASA Astrophysics Data System (ADS)

Chen, Wenli; Zhang, Huaiqing; Chen, Lin; Gu, Shanyun

2018-05-01

This paper presents a scheme of circular-arrayed, coreless Hall-effect current transformers. It can satisfy the demands of wide dynamic range and bandwidth current in the distribution system, as well as the demand of AC and DC simultaneous measurements. In order to improve the signal to noise ratio (SNR) of the sensor, a wire-positioning algorithm is proposed, which can improve the measurement accuracy based on the post-processing of measurement data. The simulation results demonstrate that the maximum errors are 70%, 6.1% and 0.95% corresponding to Ampère’s circuital method, approximate positioning algorithm and precise positioning algorithm, respectively. It is obvious that the accuracy of the positioning algorithm is significantly improved when compared with that of the Ampère’s circuital method. The maximum error of the positioning algorithm is smaller in the experiment.

LC-IMS-MS Feature Finder. Detecting Multidimensional Liquid Chromatography, Ion Mobility, and Mass Spectrometry Features in Complex Datasets

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

Crowell, Kevin L.; Slysz, Gordon W.; Baker, Erin Shammel

2013-09-05

We introduce a command line software application LC-IMS-MS Feature Finder that searches for molecular ion signatures in multidimensional liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data by clustering deisotoped peaks with similar monoisotopic mass, charge state, LC elution time, and ion mobility drift time values. The software application includes an algorithm for detecting and quantifying co-eluting chemical species, including species that exist in multiple conformations that may have been separated in the IMS dimension.

Distributed Finite-Time Cooperative Control of Multiple High-Order Nonholonomic Mobile Robots.

PubMed

Du, Haibo; Wen, Guanghui; Cheng, Yingying; He, Yigang; Jia, Ruting

2017-12-01

The consensus problem of multiple nonholonomic mobile robots in the form of high-order chained structure is considered in this paper. Based on the model features and the finite-time control technique, a finite-time cooperative controller is explicitly constructed which guarantees that the states consensus is achieved in a finite time. As an application of the proposed results, finite-time formation control of multiple wheeled mobile robots is studied and a finite-time formation control algorithm is proposed. To show effectiveness of the proposed approach, a simulation example is given.

Efficient and Stable Routing Algorithm Based on User Mobility and Node Density in Urban Vehicular Network

PubMed Central

Al-Mayouf, Yusor Rafid Bahar; Ismail, Mahamod; Abdullah, Nor Fadzilah; Wahab, Ainuddin Wahid Abdul; Mahdi, Omar Adil; Khan, Suleman; Choo, Kim-Kwang Raymond

2016-01-01

Vehicular ad hoc networks (VANETs) are considered an emerging technology in the industrial and educational fields. This technology is essential in the deployment of the intelligent transportation system, which is targeted to improve safety and efficiency of traffic. The implementation of VANETs can be effectively executed by transmitting data among vehicles with the use of multiple hops. However, the intrinsic characteristics of VANETs, such as its dynamic network topology and intermittent connectivity, limit data delivery. One particular challenge of this network is the possibility that the contributing node may only remain in the network for a limited time. Hence, to prevent data loss from that node, the information must reach the destination node via multi-hop routing techniques. An appropriate, efficient, and stable routing algorithm must be developed for various VANET applications to address the issues of dynamic topology and intermittent connectivity. Therefore, this paper proposes a novel routing algorithm called efficient and stable routing algorithm based on user mobility and node density (ESRA-MD). The proposed algorithm can adapt to significant changes that may occur in the urban vehicular environment. This algorithm works by selecting an optimal route on the basis of hop count and link duration for delivering data from source to destination, thereby satisfying various quality of service considerations. The validity of the proposed algorithm is investigated by its comparison with ARP-QD protocol, which works on the mechanism of optimal route finding in VANETs in urban environments. Simulation results reveal that the proposed ESRA-MD algorithm shows remarkable improvement in terms of delivery ratio, delivery delay, and communication overhead. PMID:27855165

Aerosol mobility imaging for rapid size distribution measurements

DOEpatents

Wang, Jian; Hering, Susanne Vera; Spielman, Steven Russel; Kuang, Chongai

2016-07-19

A parallel plate dimensional electrical mobility separator and laminar flow water condensation provide rapid, mobility-based particle sizing at concentrations typical of the remote atmosphere. Particles are separated spatially within the electrical mobility separator, enlarged through water condensation, and imaged onto a CCD array. The mobility separation distributes particles in accordance with their size. The condensation enlarges size-separated particles by water condensation while they are still within the gap of the mobility drift tube. Once enlarged the particles are illuminated by a laser. At a pre-selected frequency, typically 10 Hz, the position of all of the individual particles illuminated by the laser are captured by CCD camera. This instantly records the particle number concentration at each position. Because the position is directly related to the particle size (or mobility), the particle size spectra is derived from the images recorded by the CCD.

Using Motion Planning to Determine the Existence of an Accessible Route in a CAD Environment

ERIC Educational Resources Information Center

Pan, Xiaoshan; Han, Charles S.; Law, Kincho H.

2010-01-01

We describe an algorithm based on motion-planning techniques to determine the existence of an accessible route through a facility for a wheeled mobility device. The algorithm is based on LaValle's work on rapidly exploring random trees and is enhanced to take into consideration the particularities of the accessible route domain. Specifically, the…

Parallel Climate Data Assimilation PSAS Package Achieves 18 GFLOPs on 512-Node Intel Paragon

NASA Technical Reports Server (NTRS)

Ding, H. Q.; Chan, C.; Gennery, D. B.; Ferraro, R. D.

1995-01-01

Several algorithms were added to the Physical-space Statistical Analysis System (PSAS) from Goddard, which assimilates observational weather data by correcting for different levels of uncertainty about the data and different locations for mobile observation platforms. The new algorithms and use of the 512-node Intel Paragon allowed a hundred-fold decrease in processing time.

Pseudo-random dynamic address configuration (PRDAC) algorithm for mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Wu, Shaochuan; Tan, Xuezhi

2007-11-01

By analyzing all kinds of address configuration algorithms, this paper provides a new pseudo-random dynamic address configuration (PRDAC) algorithm for mobile ad hoc networks. Based on PRDAC, the first node that initials this network randomly chooses a nonlinear shift register that can generates an m-sequence. When another node joins this network, the initial node will act as an IP address configuration sever to compute an IP address according to this nonlinear shift register, and then allocates this address and tell the generator polynomial of this shift register to this new node. By this means, when other node joins this network, any node that has obtained an IP address can act as a server to allocate address to this new node. PRDAC can also efficiently avoid IP conflicts and deal with network partition and merge as same as prophet address (PA) allocation and dynamic configuration and distribution protocol (DCDP). Furthermore, PRDAC has less algorithm complexity, less computational complexity and more sufficient assumption than PA. In addition, PRDAC radically avoids address conflicts and maximizes the utilization rate of IP addresses. Analysis and simulation results show that PRDAC has rapid convergence, low overhead and immune from topological structures.

Mobile chemical detector (AP2C+SP4E) as an aid for medical decision making in the battlefield.

PubMed

Eisenkraft, Arik; Markel, Gal; Simovich, Shirley; Layish, Ido; Hoffman, Azik; Finkelstein, Arseny; Rotman, Eran; Dushnitsky, Tsvika; Krivoy, Amir

2007-09-01

The combination of the AP2C unit with the SP4E kit composes a lightweight mobile detector of chemical warfare agents (CWA), such as nerve and mustard agents, with both vapor- and liquid-sampling capabilities. This apparatus was recently introduced into our military medical units as an aid for detection of CWA on casualties. Importantly, critical information regarding the applicability in the battlefield was absent. In view of the serious consequences that might follow a proclamation of CWA recognition in battlefield, a high false-positive rate positions the utilization of this apparatus as a medical decision tool in question. We have therefore conducted a field experiment to test the false-positive rate as well as analyze possible factors leading to false-positive readings with this device. The experiment was carried out before and after a 4-day army field exercise, using a standard AP2C device, a SP4E surface sampling kit, and a specially designed medical sampling kit for casualties, intended for medical teams. Soldiers were examined at rest, after mild exercise, and after 4 days in the field. The readings with AP2C alone were compared to the combination of AP2C and SP4E and to the medical sampling kit. Various body fluids served as negative controls. Remarkably, we found a false-positive rate of 57% at rest and after mild exercise, and an even higher rate of 64% after the 4-day field exercise with the AP2C detector alone, as compared to almost no false-positive readings with the combination of AP2C and SP4E. Strikingly, the medical sampling kit has yielded numerous false-positive readings, even in normal body fluids such as blood, urine, and saliva. We therefore see no place for using the medical sampling kit due to an unaccepted high rate of false-positive readings. Finally, we have designed an algorithm that uses the entire apparatus of AP2C and SP4E as a reliable validation tool for medical triage in the setting of exposure to nerve agents in the battlefield.

Integrating Conjoint Analysis with TOPSIS Algorithm to the Visual Effect of Icon Design Based on Multiple Users' Image Perceptions

ERIC Educational Resources Information Center

Tung, Ting-Chun; Chen, Hung-Yuan

2017-01-01

With the advance of mobile computing and wireless technology, a user's intent to interact with the interface of a mobile device is motivated not only by its intuitional operation, but also by the emotional perception induced by its aesthetic appeal. A graphical interface employing icons with suitable visual effect based on the users' emotional…

Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

PubMed

Wright, Cameron H G; Barrett, Steven F; Pack, Daniel J

2005-01-01

We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.

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.

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

The research of autonomous obstacle avoidance of mobile robot based on multi-sensor integration

NASA Astrophysics Data System (ADS)

Zhao, Ming; Han, Baoling

2016-11-01

The object of this study is the bionic quadruped mobile robot. The study has proposed a system design plan for mobile robot obstacle avoidance with the binocular stereo visual sensor and the self-control 3D Lidar integrated with modified ant colony optimization path planning to realize the reconstruction of the environmental map. Because the working condition of a mobile robot is complex, the result of the 3D reconstruction with a single binocular sensor is undesirable when feature points are few and the light condition is poor. Therefore, this system integrates the stereo vision sensor blumblebee2 and the Lidar sensor together to detect the cloud information of 3D points of environmental obstacles. This paper proposes the sensor information fusion technology to rebuild the environment map. Firstly, according to the Lidar data and visual data on obstacle detection respectively, and then consider two methods respectively to detect the distribution of obstacles. Finally fusing the data to get the more complete, more accurate distribution of obstacles in the scene. Then the thesis introduces ant colony algorithm. It has analyzed advantages and disadvantages of the ant colony optimization and its formation cause deeply, and then improved the system with the help of the ant colony optimization to increase the rate of convergence and precision of the algorithm in robot path planning. Such improvements and integrations overcome the shortcomings of the ant colony optimization like involving into the local optimal solution easily, slow search speed and poor search results. This experiment deals with images and programs the motor drive under the compiling environment of Matlab and Visual Studio and establishes the visual 2.5D grid map. Finally it plans a global path for the mobile robot according to the ant colony algorithm. The feasibility and effectiveness of the system are confirmed by ROS and simulation platform of Linux.

Inverse Source Data-Processing Strategies for Radio-Frequency Localization in Indoor Environments.

PubMed

Gennarelli, Gianluca; Al Khatib, Obada; Soldovieri, Francesco

2017-10-27

Indoor positioning of mobile devices plays a key role in many aspects of our daily life. These include real-time people tracking and monitoring, activity recognition, emergency detection, navigation, and numerous location based services. Despite many wireless technologies and data-processing algorithms have been developed in recent years, indoor positioning is still a problem subject of intensive research. This paper deals with the active radio-frequency (RF) source localization in indoor scenarios. The localization task is carried out at the physical layer thanks to receiving sensor arrays which are deployed on the border of the surveillance region to record the signal emitted by the source. The localization problem is formulated as an imaging one by taking advantage of the inverse source approach. Different measurement configurations and data-processing/fusion strategies are examined to investigate their effectiveness in terms of localization accuracy under both line-of-sight (LOS) and non-line of sight (NLOS) conditions. Numerical results based on full-wave synthetic data are reported to support the analysis.

Inverse Source Data-Processing Strategies for Radio-Frequency Localization in Indoor Environments

PubMed Central

Gennarelli, Gianluca; Al Khatib, Obada; Soldovieri, Francesco

2017-01-01

Indoor positioning of mobile devices plays a key role in many aspects of our daily life. These include real-time people tracking and monitoring, activity recognition, emergency detection, navigation, and numerous location based services. Despite many wireless technologies and data-processing algorithms have been developed in recent years, indoor positioning is still a problem subject of intensive research. This paper deals with the active radio-frequency (RF) source localization in indoor scenarios. The localization task is carried out at the physical layer thanks to receiving sensor arrays which are deployed on the border of the surveillance region to record the signal emitted by the source. The localization problem is formulated as an imaging one by taking advantage of the inverse source approach. Different measurement configurations and data-processing/fusion strategies are examined to investigate their effectiveness in terms of localization accuracy under both line-of-sight (LOS) and non-line of sight (NLOS) conditions. Numerical results based on full-wave synthetic data are reported to support the analysis. PMID:29077071

STEPPING - Smartphone-Based Portable Pedestrian Indoor Navigation

NASA Astrophysics Data System (ADS)

Lukianto, C.; Sternberg, H.

2011-12-01

Many current smartphones are fitted with GPS receivers, which, in combination with a map application form a pedestrian navigation system for outdoor purposes. However, once an area with insufficient satellite signal coverage is entered, these navigation systems cease to function. For indoor positioning, there are already several solutions available which are usually based on measured distances to reference points. These solutions can achieve resolutions as low as the sub-millimetre range depending on the complexity of the set-up. STEPPING project, developed at HCU Hamburg Germany aims at designing an indoor navigation system consisting of a small inertial navigation system and a new, robust sensor fusion algorithm running on a current smartphone. As this system is theoretically able to integrate any available positioning method, it is independent of a particular method and can thus be realized on a smartphone without affecting user mobility. Potential applications include --but are not limited to: Large trade fairs, airports, parking decks and shopping malls, as well as ambient assisted living scenarios.

A novel wearable smart button system for fall detection

NASA Astrophysics Data System (ADS)

Zhuang, Wei; Sun, Xiang; Zhi, Yueyan; Han, Yue; Mao, Hande

2017-05-01

Fall has been the second most cause of accidental injury to death in the world. It has been a serious threat to the physical and mental health of the elders. Therefore, developing wearable node system with fall detecting ability has become increasingly pressing at present. A novel smart button for long-term fall detection is proposed in this paper, which is able to accurately monitor the falling behavior, and sending warning message online as well. The smart button is based on the tri-axis acceleration sensor which is used to collect the body motion signals. By using the statistical metrics of acceleration characteristics, a new SVM classification algorithm with high positive accuracy and stability is proposed so as to classify the falls and activities of daily living, and the results can be real-time displayed on Android based mobile phone. The experiments show that our wearable node system can continuously monitor the falling behavior with positive rate 94.8%.

Homography-based visual servo regulation of mobile robots.

PubMed

Fang, Yongchun; Dixon, Warren E; Dawson, Darren M; Chawda, Prakash

2005-10-01

A monocular camera-based vision system attached to a mobile robot (i.e., the camera-in-hand configuration) is considered in this paper. By comparing corresponding target points of an object from two different camera images, geometric relationships are exploited to derive a transformation that relates the actual position and orientation of the mobile robot to a reference position and orientation. This transformation is used to synthesize a rotation and translation error system from the current position and orientation to the fixed reference position and orientation. Lyapunov-based techniques are used to construct an adaptive estimate to compensate for a constant, unmeasurable depth parameter, and to prove asymptotic regulation of the mobile robot. The contribution of this paper is that Lyapunov techniques are exploited to craft an adaptive controller that enables mobile robot position and orientation regulation despite the lack of an object model and the lack of depth information. Experimental results are provided to illustrate the performance of the controller.

An Indoor Pedestrian Positioning Method Using HMM with a Fuzzy Pattern Recognition Algorithm in a WLAN Fingerprint System

PubMed Central

Ni, Yepeng; Liu, Jianbo; Liu, Shan; Bai, Yaxin

2016-01-01

With the rapid development of smartphones and wireless networks, indoor location-based services have become more and more prevalent. Due to the sophisticated propagation of radio signals, the Received Signal Strength Indicator (RSSI) shows a significant variation during pedestrian walking, which introduces critical errors in deterministic indoor positioning. To solve this problem, we present a novel method to improve the indoor pedestrian positioning accuracy by embedding a fuzzy pattern recognition algorithm into a Hidden Markov Model. The fuzzy pattern recognition algorithm follows the rule that the RSSI fading has a positive correlation to the distance between the measuring point and the AP location even during a dynamic positioning measurement. Through this algorithm, we use the RSSI variation trend to replace the specific RSSI value to achieve a fuzzy positioning. The transition probability of the Hidden Markov Model is trained by the fuzzy pattern recognition algorithm with pedestrian trajectories. Using the Viterbi algorithm with the trained model, we can obtain a set of hidden location states. In our experiments, we demonstrate that, compared with the deterministic pattern matching algorithm, our method can greatly improve the positioning accuracy and shows robust environmental adaptability. PMID:27618053

Evaluation of Laser Based Alignment Algorithms Under Additive Random and Diffraction Noise

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

McClay, W A; Awwal, A; Wilhelmsen, K

2004-09-30

The purpose of the automatic alignment algorithm at the National Ignition Facility (NIF) is to determine the position of a laser beam based on the position of beam features from video images. The position information obtained is used to command motors and attenuators to adjust the beam lines to the desired position, which facilitates the alignment of all 192 beams. One of the goals of the algorithm development effort is to ascertain the performance, reliability, and uncertainty of the position measurement. This paper describes a method of evaluating the performance of algorithms using Monte Carlo simulation. In particular we showmore » the application of this technique to the LM1{_}LM3 algorithm, which determines the position of a series of two beam light sources. The performance of the algorithm was evaluated for an ensemble of over 900 simulated images with varying image intensities and noise counts, as well as varying diffraction noise amplitude and frequency. The performance of the algorithm on the image data set had a tolerance well beneath the 0.5-pixel system requirement.« less

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.