Queuing theory models for computer networks
NASA Technical Reports Server (NTRS)
Galant, David C.
1989-01-01
A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.
An application of queuing theory to waterfowl migration
Sojda, Richard S.; Cornely, John E.; Fredrickson, Leigh H.; Rizzoli, A.E.; Jakeman, A.J.
2002-01-01
There has always been great interest in the migration of waterfowl and other birds. We have applied queuing theory to modelling waterfowl migration, beginning with a prototype system for the Rocky Mountain Population of trumpeter swans (Cygnus buccinator) in Western North America. The queuing model can be classified as a D/BB/28 system, and we describe the input sources, service mechanism, and network configuration of queues and servers. The intrinsic nature of queuing theory is to represent the spatial and temporal characteristics of entities and how they move, are placed in queues, and are serviced. The service mechanism in our system is an algorithm representing how swans move through the flyway based on seasonal life cycle events. The system uses an observed number of swans at each of 27 areas for a breeding season as input and simulates their distribution through four seasonal steps. The result is a simulated distribution of birds for the subsequent year's breeding season. The model was built as a multiagent system with one agent handling movement algorithms, with one facilitating user interface, and with one to seven agents representing specific geographic areas for which swan management interventions can be implemented. The many parallels in queuing model servers and service mechanisms with waterfowl management areas and annual life cycle events made the transfer of the theory to practical application straightforward.
Cultural Geography Model Validation
2010-03-01
the Cultural Geography Model (CGM), a government owned, open source multi - agent system utilizing Bayesian networks, queuing systems, the Theory of...referent determined either from theory or SME opinion. 4. CGM Overview The CGM is a government-owned, open source, data driven multi - agent social...HSCB, validation, social network analysis ABSTRACT: In the current warfighting environment , the military needs robust modeling and simulation (M&S
Jahn, Beate; Theurl, Engelbert; Siebert, Uwe; Pfeiffer, Karl-Peter
2010-01-01
In most decision-analytic models in health care, it is assumed that there is treatment without delay and availability of all required resources. Therefore, waiting times caused by limited resources and their impact on treatment effects and costs often remain unconsidered. Queuing theory enables mathematical analysis and the derivation of several performance measures of queuing systems. Nevertheless, an analytical approach with closed formulas is not always possible. Therefore, simulation techniques are used to evaluate systems that include queuing or waiting, for example, discrete event simulation. To include queuing in decision-analytic models requires a basic knowledge of queuing theory and of the underlying interrelationships. This tutorial introduces queuing theory. Analysts and decision-makers get an understanding of queue characteristics, modeling features, and its strength. Conceptual issues are covered, but the emphasis is on practical issues like modeling the arrival of patients. The treatment of coronary artery disease with percutaneous coronary intervention including stent placement serves as an illustrative queuing example. Discrete event simulation is applied to explicitly model resource capacities, to incorporate waiting lines and queues in the decision-analytic modeling example.
Using queuing theory and simulation model to optimize hospital pharmacy performance.
Bahadori, Mohammadkarim; Mohammadnejhad, Seyed Mohsen; Ravangard, Ramin; Teymourzadeh, Ehsan
2014-03-01
Hospital pharmacy is responsible for controlling and monitoring the medication use process and ensures the timely access to safe, effective and economical use of drugs and medicines for patients and hospital staff. This study aimed to optimize the management of studied outpatient pharmacy by developing suitable queuing theory and simulation technique. A descriptive-analytical study conducted in a military hospital in Iran, Tehran in 2013. A sample of 220 patients referred to the outpatient pharmacy of the hospital in two shifts, morning and evening, was selected to collect the necessary data to determine the arrival rate, service rate, and other data needed to calculate the patients flow and queuing network performance variables. After the initial analysis of collected data using the software SPSS 18, the pharmacy queuing network performance indicators were calculated for both shifts. Then, based on collected data and to provide appropriate solutions, the queuing system of current situation for both shifts was modeled and simulated using the software ARENA 12 and 4 scenarios were explored. Results showed that the queue characteristics of the studied pharmacy during the situation analysis were very undesirable in both morning and evening shifts. The average numbers of patients in the pharmacy were 19.21 and 14.66 in the morning and evening, respectively. The average times spent in the system by clients were 39 minutes in the morning and 35 minutes in the evening. The system utilization in the morning and evening were, respectively, 25% and 21%. The simulation results showed that reducing the staff in the morning from 2 to 1 in the receiving prescriptions stage didn't change the queue performance indicators. Increasing one staff in filling prescription drugs could cause a decrease of 10 persons in the average queue length and 18 minutes and 14 seconds in the average waiting time. On the other hand, simulation results showed that in the evening, decreasing the staff from 2 to 1 in the delivery of prescription drugs, changed the queue performance indicators very little. Increasing a staff to fill prescription drugs could cause a decrease of 5 persons in the average queue length and 8 minutes and 44 seconds in the average waiting time. The patients' waiting times and the number of patients waiting to receive services in both shifts could be reduced by using multitasking persons and reallocating them to the time-consuming stage of filling prescriptions, using queuing theory and simulation techniques.
Using Queuing Theory and Simulation Model to Optimize Hospital Pharmacy Performance
Bahadori, Mohammadkarim; Mohammadnejhad, Seyed Mohsen; Ravangard, Ramin; Teymourzadeh, Ehsan
2014-01-01
Background: Hospital pharmacy is responsible for controlling and monitoring the medication use process and ensures the timely access to safe, effective and economical use of drugs and medicines for patients and hospital staff. Objectives: This study aimed to optimize the management of studied outpatient pharmacy by developing suitable queuing theory and simulation technique. Patients and Methods: A descriptive-analytical study conducted in a military hospital in Iran, Tehran in 2013. A sample of 220 patients referred to the outpatient pharmacy of the hospital in two shifts, morning and evening, was selected to collect the necessary data to determine the arrival rate, service rate, and other data needed to calculate the patients flow and queuing network performance variables. After the initial analysis of collected data using the software SPSS 18, the pharmacy queuing network performance indicators were calculated for both shifts. Then, based on collected data and to provide appropriate solutions, the queuing system of current situation for both shifts was modeled and simulated using the software ARENA 12 and 4 scenarios were explored. Results: Results showed that the queue characteristics of the studied pharmacy during the situation analysis were very undesirable in both morning and evening shifts. The average numbers of patients in the pharmacy were 19.21 and 14.66 in the morning and evening, respectively. The average times spent in the system by clients were 39 minutes in the morning and 35 minutes in the evening. The system utilization in the morning and evening were, respectively, 25% and 21%. The simulation results showed that reducing the staff in the morning from 2 to 1 in the receiving prescriptions stage didn't change the queue performance indicators. Increasing one staff in filling prescription drugs could cause a decrease of 10 persons in the average queue length and 18 minutes and 14 seconds in the average waiting time. On the other hand, simulation results showed that in the evening, decreasing the staff from 2 to 1 in the delivery of prescription drugs, changed the queue performance indicators very little. Increasing a staff to fill prescription drugs could cause a decrease of 5 persons in the average queue length and 8 minutes and 44 seconds in the average waiting time. Conclusions: The patients' waiting times and the number of patients waiting to receive services in both shifts could be reduced by using multitasking persons and reallocating them to the time-consuming stage of filling prescriptions, using queuing theory and simulation techniques. PMID:24829791
2014-12-26
administrators dashboard , so that they can be effectively triaged, analyzed, and used to implement defensive actions to keep the network safe and...For the bank teller, some customers will require straight forward services (a quick deposit or cashing a check) while others will have questions or
Study on combat effectiveness of air defense missile weapon system based on queuing theory
NASA Astrophysics Data System (ADS)
Zhao, Z. Q.; Hao, J. X.; Li, L. J.
2017-01-01
Queuing Theory is a method to analyze the combat effectiveness of air defense missile weapon system. The model of service probability based on the queuing theory was constructed, and applied to analyzing the combat effectiveness of "Sidewinder" and "Tor-M1" air defense missile weapon system. Finally aimed at different targets densities, the combat effectiveness of different combat units of two types' defense missile weapon system is calculated. This method can be used to analyze the usefulness of air defense missile weapon system.
NASA Astrophysics Data System (ADS)
Sun, Y.; Li, Y. P.; Huang, G. H.
2012-06-01
In this study, a queuing-theory-based interval-fuzzy robust two-stage programming (QB-IRTP) model is developed through introducing queuing theory into an interval-fuzzy robust two-stage (IRTP) optimization framework. The developed QB-IRTP model can not only address highly uncertain information for the lower and upper bounds of interval parameters but also be used for analysing a variety of policy scenarios that are associated with different levels of economic penalties when the promised targets are violated. Moreover, it can reflect uncertainties in queuing theory problems. The developed method has been applied to a case of long-term municipal solid waste (MSW) management planning. Interval solutions associated with different waste-generation rates, different waiting costs and different arriving rates have been obtained. They can be used for generating decision alternatives and thus help managers to identify desired MSW management policies under various economic objectives and system reliability constraints.
Queuing Theory and Reference Transactions.
ERIC Educational Resources Information Center
Terbille, Charles
1995-01-01
Examines the implications of applying the queuing theory to three different reference situations: (1) random patron arrivals; (2) random durations of transactions; and (3) use of two librarians. Tables and figures represent results from spreadsheet calculations of queues for each reference situation. (JMV)
NASA Astrophysics Data System (ADS)
Chowdhury, Prasun; Saha Misra, Iti
2014-10-01
Nowadays, due to increased demand for using the Broadband Wireless Access (BWA) networks in a satisfactory manner a promised Quality of Service (QoS) is required to manage the seamless transmission of the heterogeneous handoff calls. To this end, this paper proposes an improved Call Admission Control (CAC) mechanism with prioritized handoff queuing scheme that aims to reduce dropping probability of handoff calls. Handoff calls are queued when no bandwidth is available even after the allowable bandwidth degradation of the ongoing calls and get admitted into the network when an ongoing call is terminated with a higher priority than the newly originated call. An analytical Markov model for the proposed CAC mechanism is developed to analyze various performance parameters. Analytical results show that our proposed CAC with handoff queuing scheme prioritizes the handoff calls effectively and reduces dropping probability of the system by 78.57% for real-time traffic without degrading the number of failed new call attempts. This results in the increased bandwidth utilization of the network.
Human Factors of Queuing: A Library Circulation Model.
ERIC Educational Resources Information Center
Mansfield, Jerry W.
1981-01-01
Classical queuing theories and their accompanying service facilities totally disregard the human factors in the name of efficiency. As library managers we need to be more responsive to human needs in the design of service points and make every effort to minimize queuing and queue frustration. Five references are listed. (Author/RAA)
Metastability of Queuing Networks with Mobile Servers
NASA Astrophysics Data System (ADS)
Baccelli, F.; Rybko, A.; Shlosman, S.; Vladimirov, A.
2018-04-01
We study symmetric queuing networks with moving servers and FIFO service discipline. The mean-field limit dynamics demonstrates unexpected behavior which we attribute to the metastability phenomenon. Large enough finite symmetric networks on regular graphs are proved to be transient for arbitrarily small inflow rates. However, the limiting non-linear Markov process possesses at least two stationary solutions. The proof of transience is based on martingale techniques.
Optimal service using Matlab - simulink controlled Queuing system at call centers
NASA Astrophysics Data System (ADS)
Balaji, N.; Siva, E. P.; Chandrasekaran, A. D.; Tamilazhagan, V.
2018-04-01
This paper presents graphical integrated model based academic research on telephone call centres. This paper introduces an important feature of impatient customers and abandonments in the queue system. However the modern call centre is a complex socio-technical system. Queuing theory has now become a suitable application in the telecom industry to provide better online services. Through this Matlab-simulink multi queuing structured models provide better solutions in complex situations at call centres. Service performance measures analyzed at optimal level through Simulink queuing model.
Averaging principle for second-order approximation of heterogeneous models with homogeneous models.
Fibich, Gadi; Gavious, Arieh; Solan, Eilon
2012-11-27
Typically, models with a heterogeneous property are considerably harder to analyze than the corresponding homogeneous models, in which the heterogeneous property is replaced by its average value. In this study we show that any outcome of a heterogeneous model that satisfies the two properties of differentiability and symmetry is O(ε(2)) equivalent to the outcome of the corresponding homogeneous model, where ε is the level of heterogeneity. We then use this averaging principle to obtain new results in queuing theory, game theory (auctions), and social networks (marketing).
Averaging principle for second-order approximation of heterogeneous models with homogeneous models
Fibich, Gadi; Gavious, Arieh; Solan, Eilon
2012-01-01
Typically, models with a heterogeneous property are considerably harder to analyze than the corresponding homogeneous models, in which the heterogeneous property is replaced by its average value. In this study we show that any outcome of a heterogeneous model that satisfies the two properties of differentiability and symmetry is O(ɛ2) equivalent to the outcome of the corresponding homogeneous model, where ɛ is the level of heterogeneity. We then use this averaging principle to obtain new results in queuing theory, game theory (auctions), and social networks (marketing). PMID:23150569
A Network Flow Approach to the Initial Skills Training Scheduling Problem
2007-12-01
include (but are not limited to) queuing theory, stochastic analysis and simulation. After the demand schedule has been estimated, it can be ...software package has already been purchased and is in use by AFPC, AFPC has requested that the new algorithm be programmed in this language as well ...the discussed outputs from those schedules. Required Inputs A single input file details the students to be scheduled as well as the courses
Average waiting time in FDDI networks with local priorities
NASA Technical Reports Server (NTRS)
Gercek, Gokhan
1994-01-01
A method is introduced to compute the average queuing delay experienced by different priority group messages in an FDDI node. It is assumed that no FDDI MAC layer priorities are used. Instead, a priority structure is introduced to the messages at a higher protocol layer (e.g. network layer) locally. Such a method was planned to be used in Space Station Freedom FDDI network. Conservation of the average waiting time is used as the key concept in computing average queuing delays. It is shown that local priority assignments are feasable specially when the traffic distribution is asymmetric in the FDDI network.
Delay-aware adaptive sleep mechanism for green wireless-optical broadband access networks
NASA Astrophysics Data System (ADS)
Wang, Ruyan; Liang, Alei; Wu, Dapeng; Wu, Dalei
2017-07-01
Wireless-Optical Broadband Access Network (WOBAN) is capacity-high, reliable, flexible, and ubiquitous, as it takes full advantage of the merits from both optical communication and wireless communication technologies. Similar to other access networks, the high energy consumption poses a great challenge for building up WOBANs. To shot this problem, we can make some load-light Optical Network Units (ONUs) sleep to reduce the energy consumption. Such operation, however, causes the increased packet delay. Jointly considering the energy consumption and transmission delay, we propose a delay-aware adaptive sleep mechanism. Specifically, we develop a new analytical method to evaluate the transmission delay and queuing delay over the optical part, instead of adopting M/M/1 queuing model. Meanwhile, we also analyze the access delay and queuing delay of the wireless part. Based on such developed delay models, we mathematically derive ONU's optimal sleep time. In addition, we provide numerous simulation results to show the effectiveness of the proposed mechanism.
Some queuing network models of computer systems
NASA Technical Reports Server (NTRS)
Herndon, E. S.
1980-01-01
Queuing network models of a computer system operating with a single workload type are presented. Program algorithms are adapted for use on the Texas Instruments SR-52 programmable calculator. By slightly altering the algorithm to process the G and H matrices row by row instead of column by column, six devices and an unlimited job/terminal population could be handled on the SR-52. Techniques are also introduced for handling a simple load dependent server and for studying interactive systems with fixed multiprogramming limits.
Khalid, Ruzelan; Nawawi, Mohd Kamal M; Kawsar, Luthful A; Ghani, Noraida A; Kamil, Anton A; Mustafa, Adli
2013-01-01
M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed.
OSLG: A new granting scheme in WDM Ethernet passive optical networks
NASA Astrophysics Data System (ADS)
Razmkhah, Ali; Rahbar, Akbar Ghaffarpour
2011-12-01
Several granting schemes have been proposed to grant transmission window and dynamic bandwidth allocation (DBA) in passive optical networks (PON). Generally, granting schemes suffer from bandwidth wastage of granted windows. Here, we propose a new granting scheme for WDM Ethernet PONs, called optical network unit (ONU) Side Limited Granting (OSLG) that conserves upstream bandwidth, thus resulting in decreasing queuing delay and packet drop ratio. In OSLG instead of optical line terminal (OLT), each ONU determines its transmission window. Two OSLG algorithms are proposed in this paper: the OSLG_GA algorithm that determines the size of its transmission window in such a way that the bandwidth wastage problem is relieved, and the OSLG_SC algorithm that saves unused bandwidth for more bandwidth utilization later on. The OSLG can be used as granting scheme of any DBA to provide better performance in the terms of packet drop ratio and queuing delay. Our performance evaluations show the effectiveness of OSLG in reducing packet drop ratio and queuing delay under different DBA techniques.
NASA Astrophysics Data System (ADS)
Kikuchi, Takahiro; Kubo, Ryogo
2016-08-01
In energy-efficient passive optical network (PON) systems, the increase in the queuing delays caused by the power-saving mechanism of optical network units (ONUs) is an important issue. Some researchers have proposed quality-of-service (QoS)-aware ONU cyclic sleep controllers in PON systems. We have proposed proportional (P) and proportional-derivative (PD)-based controllers to maintain the average queuing delay at a constant level regardless of the amount of downstream traffic. However, sufficient performance has not been obtained because of the sleep period limitation. In this paper, proportional-integral (PI) and proportional-integral-derivative (PID)-based controllers considering the sleep period limitation, i.e., using an anti-windup (AW) technique, are proposed to improve both the QoS and power-saving performance. Simulations confirm that the proposed controllers provide better performance than conventional controllers in terms of the average downstream queuing delay and the time occupancy of ONU active periods.
Modeling and performance analysis of QoS data
NASA Astrophysics Data System (ADS)
Strzeciwilk, Dariusz; Zuberek, Włodzimierz M.
2016-09-01
The article presents the results of modeling and analysis of data transmission performance on systems that support quality of service. Models are designed and tested, taking into account multiservice network architecture, i.e. supporting the transmission of data related to different classes of traffic. Studied were mechanisms of traffic shaping systems, which are based on the Priority Queuing with an integrated source of data and the various sources of data that is generated. Discussed were the basic problems of the architecture supporting QoS and queuing systems. Designed and built were models based on Petri nets, supported by temporal logics. The use of simulation tools was to verify the mechanisms of shaping traffic with the applied queuing algorithms. It is shown that temporal models of Petri nets can be effectively used in the modeling and analysis of the performance of computer networks.
Redesign of a university hospital preanesthesia evaluation clinic using a queuing theory approach.
Zonderland, Maartje E; Boer, Fredrik; Boucherie, Richard J; de Roode, Annemiek; van Kleef, Jack W
2009-11-01
Changes in patient length of stay (the duration of 1 clinic visit) as a result of the introduction of an electronic patient file system forced an anesthesia department to change its outpatient clinic organization. In this study, we sought to demonstrate how the involvement of essential employees combined with mathematical techniques to support the decision-making process resulted in a successful intervention. The setting is the preanesthesia evaluation clinic (PAC) of a university hospital, where patients consult several medical professionals, either by walk-in or appointment. Queuing theory was used to model the initial set-up of the clinic, and later to model possible alternative designs. With the queuing model, possible improvements in efficiency could be investigated. Inputs to the model were patient arrival rates and expected service times with clinic employees, collected from the clinic's logging system and by observation. The performance measures calculated with the model were patient length of stay and employee utilization rate. Supported by the model outcomes, a working group consisting of representatives of all clinic employees decided whether the initial design should be maintained or an intervention was needed. The queuing model predicted that 3 of the proposed alternatives would result in better performance. Key points in the intervention were the rescheduling of appointments and the reallocation of tasks. The intervention resulted in a shortening of the time the anesthesiologist needed to decide upon approving the patient for surgery. Patient arrivals increased sharply over 1 yr by more than 16%; however, patient length of stay at the clinic remained essentially unchanged. If the initial set-up of the clinic would have been maintained, the patient length of stay would have increased dramatically. Queuing theory provides robust methods to evaluate alternative designs for the organization of PACs. In this article, we show that queuing modeling is an adequate approach for redesigning processes in PACs.
Improving queuing service at McDonald's
NASA Astrophysics Data System (ADS)
Koh, Hock Lye; Teh, Su Yean; Wong, Chin Keat; Lim, Hooi Kie; Migin, Melissa W.
2014-07-01
Fast food restaurants are popular among price-sensitive youths and working adults who value the conducive environment and convenient services. McDonald's chains of restaurants promote their sales during lunch hours by offering package meals which are perceived to be inexpensive. These promotional lunch meals attract good response, resulting in occasional long queues and inconvenient waiting times. A study is conducted to monitor the distribution of waiting time, queue length, customer arrival and departure patterns at a McDonald's restaurant located in Kuala Lumpur. A customer survey is conducted to gauge customers' satisfaction regarding waiting time and queue length. An android app named Que is developed to perform onsite queuing analysis and report key performance indices. The queuing theory in Que is based upon the concept of Poisson distribution. In this paper, Que is utilized to perform queuing analysis at this McDonald's restaurant with the aim of improving customer service, with particular reference to reducing queuing time and shortening queue length. Some results will be presented.
Using multi-class queuing network to solve performance models of e-business sites.
Zheng, Xiao-ying; Chen, De-ren
2004-01-01
Due to e-business's variety of customers with different navigational patterns and demands, multi-class queuing network is a natural performance model for it. The open multi-class queuing network(QN) models are based on the assumption that no service center is saturated as a result of the combined loads of all the classes. Several formulas are used to calculate performance measures, including throughput, residence time, queue length, response time and the average number of requests. The solution technique of closed multi-class QN models is an approximate mean value analysis algorithm (MVA) based on three key equations, because the exact algorithm needs huge time and space requirement. As mixed multi-class QN models, include some open and some closed classes, the open classes should be eliminated to create a closed multi-class QN so that the closed model algorithm can be applied. Some corresponding examples are given to show how to apply the algorithms mentioned in this article. These examples indicate that multi-class QN is a reasonably accurate model of e-business and can be solved efficiently.
Khalid, Ruzelan; M. Nawawi, Mohd Kamal; Kawsar, Luthful A.; Ghani, Noraida A.; Kamil, Anton A.; Mustafa, Adli
2013-01-01
M/G/C/C state dependent queuing networks consider service rates as a function of the number of residing entities (e.g., pedestrians, vehicles, and products). However, modeling such dynamic rates is not supported in modern Discrete Simulation System (DES) software. We designed an approach to cater this limitation and used it to construct the M/G/C/C state-dependent queuing model in Arena software. Using the model, we have evaluated and analyzed the impacts of various arrival rates to the throughput, the blocking probability, the expected service time and the expected number of entities in a complex network topology. Results indicated that there is a range of arrival rates for each network where the simulation results fluctuate drastically across replications and this causes the simulation results and analytical results exhibit discrepancies. Detail results that show how tally the simulation results and the analytical results in both abstract and graphical forms and some scientific justifications for these have been documented and discussed. PMID:23560037
NASA Astrophysics Data System (ADS)
Buick, Otto; Falcon, Pat; Alexander, G.; Siegel, Edward Carl-Ludwig
2013-03-01
Einstein[Dover(03)] critical-slowing-down(CSD)[Pais, Subtle in The Lord; Life & Sci. of Albert Einstein(81)] is Siegel CyberWar denial-of-access(DOA) operations-research queuing theory/pinning/jamming/.../Read [Aikido, Aikibojitsu & Natural-Law(90)]/Aikido(!!!) phase-transition critical-phenomenon via Siegel DIGIT-Physics (Newcomb[Am.J.Math. 4,39(1881)]-{Planck[(1901)]-Einstein[(1905)])-Poincare[Calcul Probabilités(12)-p.313]-Weyl [Goett.Nachr.(14); Math.Ann.77,313 (16)]-{Bose[(24)-Einstein[(25)]-Fermi[(27)]-Dirac[(1927)]}-``Benford''[Proc.Am.Phil.Soc. 78,4,551 (38)]-Kac[Maths.Stat.-Reasoning(55)]-Raimi[Sci.Am. 221,109 (69)...]-Jech[preprint, PSU(95)]-Hill[Proc.AMS 123,3,887(95)]-Browne[NYT(8/98)]-Antonoff-Smith-Siegel[AMS Joint-Mtg.,S.-D.(02)] algebraic-inversion to yield ONLY BOSE-EINSTEIN QUANTUM-statistics (BEQS) with ZERO-digit Bose-Einstein CONDENSATION(BEC) ``INTERSECTION''-BECOME-UNION to Barabasi[PRL 876,5632(01); Rev.Mod.Phys.74,47(02)...] Network /Net/GRAPH(!!!)-physics BEC: Strutt/Rayleigh(1881)-Polya(21)-``Anderson''(58)-Siegel[J.Non-crystalline-Sol.40,453(80)
A dynamical framework for integrated corridor management.
DOT National Transportation Integrated Search
2016-01-11
We develop analysis and control synthesis tools for dynamic traffic flow over networks. Our analysis : relies on exploiting monotonicity properties of the dynamics, and on adapting relevant tools from : stochastic queuing networks. We develop proport...
Stochastic Stability in Internet Router Congestion Games
NASA Astrophysics Data System (ADS)
Chung, Christine; Pyrga, Evangelia
Congestion control at bottleneck routers on the internet is a long standing problem. Many policies have been proposed for effective ways to drop packets from the queues of these routers so that network endpoints will be inclined to share router capacity fairly and minimize the overflow of packets trying to enter the queues. We study just how effective some of these queuing policies are when each network endpoint is a self-interested player with no information about the other players’ actions or preferences. By employing the adaptive learning model of evolutionary game theory, we study policies such as Droptail, RED, and the greedy-flow-punishing policy proposed by Gao et al. [10] to find the stochastically stable states: the states of the system that will be reached in the long run.
Developing a cross-docking network design model under uncertain environment
NASA Astrophysics Data System (ADS)
Seyedhoseini, S. M.; Rashid, Reza; Teimoury, E.
2015-06-01
Cross-docking is a logistic concept, which plays an important role in supply chain management by decreasing inventory holding, order packing, transportation costs and delivery time. Paying attention to these concerns, and importance of the congestion in cross docks, we present a mixed-integer model to optimize the location and design of cross docks at the same time to minimize the total transportation and operating costs. The model combines queuing theory for design aspects, for that matter, we consider a network of cross docks and customers where two M/M/c queues have been represented to describe operations of indoor trucks and outdoor trucks in each cross dock. To prepare a perfect illustration for performance of the model, a real case also has been examined that indicated effectiveness of the proposed model.
Optimization of airport security process
NASA Astrophysics Data System (ADS)
Wei, Jianan
2017-05-01
In order to facilitate passenger travel, on the basis of ensuring public safety, the airport security process and scheduling to optimize. The stochastic Petri net is used to simulate the single channel security process, draw the reachable graph, construct the homogeneous Markov chain to realize the performance analysis of the security process network, and find the bottleneck to limit the passenger throughput. Curve changes in the flow of passengers to open a security channel for the initial state. When the passenger arrives at a rate that exceeds the processing capacity of the security channel, it is queued. The passenger reaches the acceptable threshold of the queuing time as the time to open or close the next channel, simulate the number of dynamic security channel scheduling to reduce the passenger queuing time.
Application of queuing theory in inventory systems with substitution flexibility
NASA Astrophysics Data System (ADS)
Seyedhoseini, S. M.; Rashid, Reza; Kamalpour, Iman; Zangeneh, Erfan
2015-03-01
Considering the competition in today's business environment, tactical planning of a supply chain becomes more complex than before. In many multi-product inventory systems, substitution flexibility can improve profits. This paper aims to prepare a comprehensive substitution inventory model, where an inventory system with two substitute products with ignorable lead time has been considered, and effects of simultaneous ordering have been examined. In this paper, demands of customers for both of the products have been regarded as stochastic parameters, and queuing theory has been used to construct a mathematical model. The model has been coded by C++, and it has been analyzed due to a real example, where the results indicate efficiency of proposed model.
Mapping edge-based traffic measurements onto the internal links in MPLS network
NASA Astrophysics Data System (ADS)
Zhao, Guofeng; Tang, Hong; Zhang, Yi
2004-09-01
Applying multi-protocol label switching techniques to IP-based backbone for traffic engineering goals has shown advantageous. Obtaining a volume of load on each internal link of the network is crucial for traffic engineering applying. Though collecting can be available for each link, such as applying traditional SNMP scheme, the approach may cause heavy processing load and sharply degrade the throughput of the core routers. Then monitoring merely at the edge of the network and mapping the measurements onto the core provides a good alternative way. In this paper, we explore a scheme for traffic mapping with edge-based measurements in MPLS network. It is supposed that the volume of traffic on each internal link over the domain would be mapped onto by measurements available only at ingress nodes. We apply path-based measurements at ingress nodes without enabling measurements in the core of the network. We propose a method that can infer a path from the ingress to the egress node using label distribution protocol without collecting routing data from core routers. Based on flow theory and queuing theory, we prove that our approach is effective and present the algorithm for traffic mapping. We also show performance simulation results that indicate potential of our approach.
Application of queuing model in Dubai's busiest megaplex
NASA Astrophysics Data System (ADS)
Bhagchandani, Maneesha; Bajpai, Priti
2013-09-01
This paper provides a study and analysis of the extremely busy booking counters at the Megaplex in Dubai using the queuing model and simulation. Dubai is an emirate in UAE with a multicultural population. Majority of the population in Dubai is foreign born. Cinema is one of the major forms of entertainment. There are more than 13 megaplexes each with a number of screens ranging from 3 to 22. They screen movies in English, Arabic, Hindi and other languages. It has been observed that during the weekends megaplexes attract a large number of crowd resulting in long queues at the booking counters. One of the busiest megaplex was selected for the study. Queuing theory satisfies the model when tested in real time situation. The concepts of arrival rate, service rate, utilization rate, waiting time in the system, average number of people in the queue, using Little's Theorem and M/M/s queuing model along with simulation software have been used to suggest an empirical solution. The aim of the paper is twofold-To assess the present situation at the Megaplex and give recommendations to optimize the use of booking counters.
Modified weighted fair queuing for packet scheduling in mobile WiMAX networks
NASA Astrophysics Data System (ADS)
Satrya, Gandeva B.; Brotoharsono, Tri
2013-03-01
The increase of user mobility and the need for data access anytime also increases the interest in broadband wireless access (BWA). The best available quality of experience for mobile data service users are assured for IEEE 802.16e based users. The main problem of assuring a high QOS value is how to allocate available resources among users in order to meet the QOS requirement for criteria such as delay, throughput, packet loss and fairness. There is no specific standard scheduling mechanism stated by IEEE standards, which leaves it for implementer differentiation. There are five QOS service classes defined by IEEE 802.16: Unsolicited Grant Scheme (UGS), Extended Real Time Polling Service (ertPS), Real Time Polling Service (rtPS), Non Real Time Polling Service (nrtPS) and Best Effort Service (BE). Each class has different QOS parameter requirements for throughput and delay/jitter constraints. This paper proposes Modified Weighted Fair Queuing (MWFQ) scheduling scenario which was based on Weighted Round Robin (WRR) and Weighted Fair Queuing (WFQ). The performance of MWFQ was assessed by using above five QoS criteria. The simulation shows that using the concept of total packet size calculation improves the network's performance.
Bult, Johannes H F; van Putten, Bram; Schifferstein, Hendrik N J; Roozen, Jacques P; Voragen, Alphons G J; Kroeze, Jan H A
2004-10-01
In continuous vigilance tasks, the number of coincident panel responses to stimuli provides an index of stimulus detectability. To determine whether this number is due to chance, panel noise levels have been approximated by the maximum coincidence level obtained in stimulus-free conditions. This study proposes an alternative method by which to assess noise levels, derived from queuing system theory (QST). Instead of critical coincidence levels, QST modeling estimates the duration of coinciding responses in the absence of stimuli. The proposed method has the advantage over previous approaches that it yields more reliable noise estimates and allows for statistical testing. The method was applied in an olfactory detection experiment using 16 panelists in stimulus-present and stimulus-free conditions. We propose that QST may be used as an alternative to signal detection theory for analyzing data from continuous vigilance tasks.
NASA Technical Reports Server (NTRS)
Long, Dou; Lee, David; Johnson, Jesse; Gaier, Eric; Kostiuk, Peter
1999-01-01
This report describes an integrated model of air traffic management (ATM) tools under development in two National Aeronautics and Space Administration (NASA) programs -Terminal Area Productivity (TAP) and Advanced Air Transport Technologies (AATT). The model is made by adjusting parameters of LMINET, a queuing network model of the National Airspace System (NAS), which the Logistics Management Institute (LMI) developed for NASA. Operating LMINET with models of various combinations of TAP and AATT will give quantitative information about the effects of the tools on operations of the NAS. The costs of delays under different scenarios are calculated. An extension of Air Carrier Investment Model (ACIM) under ASAC developed by the Institute for NASA maps the technologies' impacts on NASA operations into cross-comparable benefits estimates for technologies and sets of technologies.
Estimating Performance of Single Bus, Shared Memory Multiprocessors
1987-05-01
Chandy78] K.M. Chandy, C.M. Sauer, "Approximate methods for analyzing queuing network models of computing systems," Computing Surveys, vol10 , no 3...Denning78] P. Denning, J. Buzen, "The operational analysis of queueing network models", Computing Sur- veys, vol10 , no 3, September 1978, pp 225-261
Modeling users' activity on Twitter networks: validation of Dunbar's number
NASA Astrophysics Data System (ADS)
Goncalves, Bruno; Perra, Nicola; Vespignani, Alessandro
2012-02-01
Microblogging and mobile devices appear to augment human social capabilities, which raises the question whether they remove cognitive or biological constraints on human communication. In this paper we analyze a dataset of Twitter conversations collected across six months involving 1.7 million individuals and test the theoretical cognitive limit on the number of stable social relationships known as Dunbar's number. We find that the data are in agreement with Dunbar's result; users can entertain a maximum of 100-200 stable relationships. Thus, the ``economy of attention'' is limited in the online world by cognitive and biological constraints as predicted by Dunbar's theory. We propose a simple model for users' behavior that includes finite priority queuing and time resources that reproduces the observed social behavior.
A Method of Predicting Queuing at Library Online PCs
ERIC Educational Resources Information Center
Beranek, Lea G.
2006-01-01
On-campus networked personal computer (PC) usage at La Trobe University Library was surveyed during September 2005. The survey's objectives were to confirm peak usage times, to measure some of the relevant parameters of online PC usage, and to determine the effect that 24 new networked PCs had on service quality. The survey found that clients…
AIS ASM Operational Integration Plan
2013-08-01
al. | Public August 2013 This page intentionally left blank. AIS ASM Operational Integration Plan v ...that supply AIS Routers as part of their AIS shoreside network software : Kongsberg C-Scope, Gatehouse AIS, Transas AIS Network, and CNS DataSwitch...commercial systems would be suitable for the current USCG traffic conditions. The ASM Manager is software that adds the required queuing and
An Integrated Model of Patient and Staff Satisfaction Using Queuing Theory
Mousavi, Ali; Clarkson, P. John; Young, Terry
2015-01-01
This paper investigates the connection between patient satisfaction, waiting time, staff satisfaction, and service time. It uses a variety of models to enable improvement against experiential and operational health service goals. Patient satisfaction levels are estimated using a model based on waiting (waiting times). Staff satisfaction levels are estimated using a model based on the time spent with patients (service time). An integrated model of patient and staff satisfaction, the effective satisfaction level model, is then proposed (using queuing theory). This links patient satisfaction, waiting time, staff satisfaction, and service time, connecting two important concepts, namely, experience and efficiency in care delivery and leading to a more holistic approach in designing and managing health services. The proposed model will enable healthcare systems analysts to objectively and directly relate elements of service quality to capacity planning. Moreover, as an instrument used jointly by healthcare commissioners and providers, it affords the prospect of better resource allocation. PMID:27170899
An Integrated Model of Patient and Staff Satisfaction Using Queuing Theory.
Komashie, Alexander; Mousavi, Ali; Clarkson, P John; Young, Terry
2015-01-01
This paper investigates the connection between patient satisfaction, waiting time, staff satisfaction, and service time. It uses a variety of models to enable improvement against experiential and operational health service goals. Patient satisfaction levels are estimated using a model based on waiting (waiting times). Staff satisfaction levels are estimated using a model based on the time spent with patients (service time). An integrated model of patient and staff satisfaction, the effective satisfaction level model, is then proposed (using queuing theory). This links patient satisfaction, waiting time, staff satisfaction, and service time, connecting two important concepts, namely, experience and efficiency in care delivery and leading to a more holistic approach in designing and managing health services. The proposed model will enable healthcare systems analysts to objectively and directly relate elements of service quality to capacity planning. Moreover, as an instrument used jointly by healthcare commissioners and providers, it affords the prospect of better resource allocation.
NASA Astrophysics Data System (ADS)
Wang, Haibo; Swee Poo, Gee
2004-08-01
We study the provisioning of virtual private network (VPN) service over WDM optical networks. For this purpose, we investigate the blocking performance of the hose model versus the pipe model for the provisioning. Two techniques are presented: an analytical queuing model and a discrete event simulation. The queuing model is developed from the multirate reduced-load approximation technique. The simulation is done with the OPNET simulator. Several experimental situations were used. The blocking probabilities calculated from the two approaches show a close match, indicating that the multirate reduced-load approximation technique is capable of predicting the blocking performance for the pipe model and the hose model in WDM networks. A comparison of the blocking behavior of the two models shows that the hose model has superior blocking performance as compared with pipe model. By and large, the blocking probability of the hose model is better than that of the pipe model by a few orders of magnitude, particularly at low load regions. The flexibility of the hose model allowing for the sharing of resources on a link among all connections accounts for its superior performance.
Modeling Human Supervisory Control in Heterogeneous Unmanned Vehicle Systems
2009-02-01
events through a queue, nominally due to another queue having reached its capacity limitation (Balsamo, Persone, & Onvural, 2001; Onvural, 1990; Perros ...Communication and Coordination, Athens, Greece. Perros , H. G. (1984). Queuing Networks with Blocking: A Bibliography. ACM Sigmetrics, Performance Evaluation
Modeling Users' Activity on Twitter Networks: Validation of Dunbar's Number
Gonçalves, Bruno; Perra, Nicola; Vespignani, Alessandro
2011-01-01
Microblogging and mobile devices appear to augment human social capabilities, which raises the question whether they remove cognitive or biological constraints on human communication. In this paper we analyze a dataset of Twitter conversations collected across six months involving 1.7 million individuals and test the theoretical cognitive limit on the number of stable social relationships known as Dunbar's number. We find that the data are in agreement with Dunbar's result; users can entertain a maximum of 100–200 stable relationships. Thus, the ‘economy of attention’ is limited in the online world by cognitive and biological constraints as predicted by Dunbar's theory. We propose a simple model for users' behavior that includes finite priority queuing and time resources that reproduces the observed social behavior. PMID:21826200
An analytical study of various telecomminication networks using markov models
NASA Astrophysics Data System (ADS)
Ramakrishnan, M.; Jayamani, E.; Ezhumalai, P.
2015-04-01
The main aim of this paper is to examine issues relating to the performance of various Telecommunication networks, and applied queuing theory for better design and improved efficiency. Firstly, giving an analytical study of queues deals with quantifying the phenomenon of waiting lines using representative measures of performances, such as average queue length (on average number of customers in the queue), average waiting time in queue (on average time to wait) and average facility utilization (proportion of time the service facility is in use). In the second, using Matlab simulator, summarizes the finding of the investigations, from which and where we obtain results and describing methodology for a) compare the waiting time and average number of messages in the queue in M/M/1 and M/M/2 queues b) Compare the performance of M/M/1 and M/D/1 queues and study the effect of increasing the number of servers on the blocking probability M/M/k/k queue model.
NASA Astrophysics Data System (ADS)
Kumar, Love; Sharma, Vishal; Singh, Amarpal
2017-12-01
Wireless Sensor Networks (WSNs) have an assortment of application areas, for instance, civil, military, and video surveillance with restricted power resources and transmission link. To accommodate the massive traffic load in hefty sensor networks is another key issue. Subsequently, there is a necessity to backhaul the sensed information of such networks and prolong the transmission link to access the distinct receivers. Passive Optical Network (PON), a next-generation access technology, comes out as a suitable candidate for the convergence of the sensed data to the core system. The earlier demonstrated work with single-OLT-PON introduces an overloaded buffer akin to video surveillance scenarios. In this paper, to combine the bandwidth potential of PONs with the mobility capability of WSNs, the viability for the convergence of PONs and WSNs incorporating multi-optical line terminals is demonstrated to handle the overloaded OLTs. The existing M/M/1 queue theory with interleaving polling with adaptive cycle time as dynamic bandwidth algorithm is used to shun the probability of packets clash. Further, the proposed multi-sink WSN and multi-OLT PON converged structure is investigated in bidirectional mode analytically and through computer simulations. The observations establish the proposed structure competent to accommodate the colossal data traffic through less time consumption.
QoS support over ultrafast TDM optical networks
NASA Astrophysics Data System (ADS)
Narvaez, Paolo; Siu, Kai-Yeung; Finn, Steven G.
1999-08-01
HLAN is a promising architecture to realize Tb/s access networks based on ultra-fast optical TDM technologies. This paper presents new research results on efficient algorithms for the support of quality of service over the HLAN network architecture. In particular, we propose a new scheduling algorithm that emulates fair queuing in a distributed manner for bandwidth allocation purpose. The proposed scheduler collects information on the queue of each host on the network and then instructs each host how much data to send. Our new scheduling algorithm ensures full bandwidth utilization, while guaranteeing fairness among all hosts.
The methodology for modeling queuing systems using Petri nets
NASA Astrophysics Data System (ADS)
Kotyrba, Martin; Gaj, Jakub; Tvarůžka, Matouš
2017-07-01
This papers deals with the use of Petri nets in modeling and simulation of queuing systems. The first part is focused on the explanation of basic concepts and properties of Petri nets and queuing systems. The proposed methodology for the modeling of queuing systems using Petri nets is described in the practical part. The proposed methodology will be tested on specific cases.
Nested Fork-Join Queuing Networks and Their Application to Mobility Airfield Operations Analysis.
1997-03-01
shortest queue length. Setia , Squillante, and Tripathi [109] extend Makowski and Nelson’s work by performing a quantitative assessment of a range of...Markov chains." Numerical Solution of Markov Chains, edited by W. J. Stewart, 63- 88. Basel: Marcel Dekker, 1991. [109] Setia , S. K., and others
Application of queuing theory to patient satisfaction at a tertiary hospital in Nigeria
Ameh, Nkeiruka; Sabo, B.; Oyefabi, M. O.
2013-01-01
Background: Queuing theory is the mathematical approach to the analysis of waiting lines in any setting where arrival rate of subjects is faster than the system can handle. It is applicable to healthcare settings where the systems have excess capacity to accommodate random variations. Materials and Methods: A cross-sectional descriptive survey was done. Questionnaires were administered to patients who attended the general outpatient department. Observations were also made on the queuing model and the service discipline at the clinic. Questions were meant to obtain demographic characteristics and the time spent on the queue by patients before being seen by a doctor, time spent with the doctor, their views about the time spent on the queue and useful suggestions on how to reduce the time spent on the queue. A total of 210 patients were surveyed. Results: Majority of the patients (164, 78.1%) spent 2 h or less on the queue before being seen by a doctor and less than 1 h to see the doctor. Majority of the patients (144, 68.5%) were satisfied with the time they spent on the queue before being seen by a doctor. Useful suggestions proffered by the patients to decrease the time spent on the queue before seeing a doctor at the clinic included: that more doctors be employed (46, 21.9%), that doctors should come to work on time (25, 11.9%), that first-come-first served be observed strictly (32, 15.2%) and others suggested that the records staff should desist from collecting bribes from patients in order to place their cards before others. The queuing method employed at the clinic is the multiple single channel type and the service discipline is priority service. The patients who spent less time on the queue (<1 h) before seeing the doctor were more satisfied than those who spent more time (P < 0.05). Conclusion: The study has revealed that majority of the patients were satisfied with the practice at the general outpatient department. However, there is a need to employ measures to respond to the suggestions given by the patients who are the beneficiaries of the hospital services. PMID:23661902
NQS - NETWORK QUEUING SYSTEM, VERSION 2.0 (UNIX VERSION)
NASA Technical Reports Server (NTRS)
Walter, H.
1994-01-01
The Network Queuing System, NQS, is a versatile batch and device queuing facility for a single Unix computer or a group of networked computers. With the Unix operating system as a common interface, the user can invoke the NQS collection of user-space programs to move batch and device jobs freely around the different computer hardware tied into the network. NQS provides facilities for remote queuing, request routing, remote status, queue status controls, batch request resource quota limits, and remote output return. This program was developed as part of an effort aimed at tying together diverse UNIX based machines into NASA's Numerical Aerodynamic Simulator Processing System Network. This revision of NQS allows for creating, deleting, adding and setting of complexes that aid in limiting the number of requests to be handled at one time. It also has improved device-oriented queues along with some revision of the displays. NQS was designed to meet the following goals: 1) Provide for the full support of both batch and device requests. 2) Support all of the resource quotas enforceable by the underlying UNIX kernel implementation that are relevant to any particular batch request and its corresponding batch queue. 3) Support remote queuing and routing of batch and device requests throughout the NQS network. 4) Support queue access restrictions through user and group access lists for all queues. 5) Enable networked output return of both output and error files to possibly remote machines. 6) Allow mapping of accounts across machine boundaries. 7) Provide friendly configuration and modification mechanisms for each installation. 8) Support status operations across the network, without requiring a user to log in on remote target machines. 9) Provide for file staging or copying of files for movement to the actual execution machine. To support batch and device requests, NQS v.2 implements three queue types--batch, device and pipe. Batch queues hold and prioritize batch requests; device queues hold and prioritize device requests; pipe queues transport both batch and device requests to other batch, device, or pipe queues at local or remote machines. Unique to batch queues are resource quota limits that restrict the amounts of different resources that a batch request can consume during execution. Unique to each device queue is a set of one or more devices, such as a line printer, to which requests can be sent for execution. Pipe queues have associated destinations to which they route and deliver requests. If the proper destination machine is down or unreachable, pipe queues are able to requeue the request and deliver it later when the destination is available. All NQS network conversations are performed using the Berkeley socket mechanism as ported into the respective vendor kernels. NQS is written in C language. The generic UNIX version (ARC-13179) has been successfully implemented on a variety of UNIX platforms, including Sun3 and Sun4 series computers, SGI IRIS computers running IRIX 3.3, DEC computers running ULTRIX 4.1, AMDAHL computers running UTS 1.3 and 2.1, platforms running BSD 4.3 UNIX. The IBM RS/6000 AIX version (COS-10042) is a vendor port. NQS 2.0 will also communicate with the Cray Research, Inc. and Convex, Inc. versions of NQS. The standard distribution medium for either machine version of NQS 2.0 is a 60Mb, QIC-24, .25 inch streaming magnetic tape cartridge in UNIX tar format. Upon request the generic UNIX version (ARC-13179) can be provided in UNIX tar format on alternate media. Please contact COSMIC to discuss the availability and cost of media to meet your specific needs. An electronic copy of the NQS 2.0 documentation is included on the program media. NQS 2.0 was released in 1991. The IBM RS/6000 port of NQS was developed in 1992. IRIX is a trademark of Silicon Graphics Inc. IRIS is a registered trademark of Silicon Graphics Inc. UNIX is a registered trademark of UNIX System Laboratories Inc. Sun3 and Sun4 are trademarks of Sun Microsystems Inc. DEC and ULTRIX are trademarks of Digital Equipment Corporation.
Single stage queueing/manufacturing system model that involves emission variable
NASA Astrophysics Data System (ADS)
Murdapa, P. S.; Pujawan, I. N.; Karningsih, P. D.; Nasution, A. H.
2018-04-01
Queueing is commonly occured at every industry. The basic model of queueing theory gives a foundation for modeling a manufacturing system. Nowadays, carbon emission is an important and inevitable issue due to its huge impact to our environment. However, existing model of queuing applied for analysis of single stage manufacturing system has not taken Carbon emissions into consideration. If it is applied to manufacturing context, it may lead to improper decisisions. By taking into account of emission variables into queuing models, not only the model become more comprehensive but also it creates awareness on the issue to many parties that involves in the system. This paper discusses the single stage M/M/1 queueing model that involves emission variable. Hopefully it could be a starting point for the next more complex models. It has a main objective for determining how carbon emissions could fit into the basic queueing theory. It turned out that the involvement of emission variables into the model has modified the traditional model of a single stage queue to a calculation model of production lot quantity allowed per period.
NASA Technical Reports Server (NTRS)
Watson, James F., III; Desrochers, Alan A.
1991-01-01
Generalized stochastic Petri nets (GSPNs) are applied to flexible manufacturing systems (FMSs). Throughput subnets and s-transitions are presented. Two FMS examples containing nonexponential distributions which were analyzed in previous papers by queuing theory and probability theory, respectively, are treated using GSPNs developed using throughput subnets and s-transitions. The GSPN results agree with the previous results, and developing and analyzing the GSPN models are straightforward and relatively easy compared to other methodologies.
Temporal Traffic Dynamics Improve the Connectivity of Ad Hoc Cognitive Radio Networks
2014-02-12
more packets to send, and are (re)born when they do. We could also consider this from a duty-cycling perspective: Nodes sleep and wake up...transmitting and receiving activities in the primary network in an intricate way, we obtain the MMD by considering a flooding scheme that tries every...consider the delay caused by scheduling, contention, or queuing. It can be shown that this flooding scheme gives us the MMD. We stress that flooding is used
Shifman, Mark A.; Sayward, Frederick G.; Mattie, Mark E.; Miller, Perry L.
2002-01-01
This case study describes a project that explores issues of quality of service (QoS) relevant to the next-generation Internet (NGI), using the PathMaster application in a testbed environment. PathMaster is a prototype computer system that analyzes digitized cell images from cytology specimens and compares those images against an image database, returning a ranked set of “similar” cell images from the database. To perform NGI testbed evaluations, we used a cluster of nine parallel computation workstations configured as three subclusters using Cisco routers. This architecture provides a local “simulated Internet” in which we explored the following QoS strategies: (1) first-in-first-out queuing, (2) priority queuing, (3) weighted fair queuing, (4) weighted random early detection, and (5) traffic shaping. The study describes the results of using these strategies with a distributed version of the PathMaster system in the presence of different amounts of competing network traffic and discusses certain of the issues that arise. The goal of the study is to help introduce NGI QoS issues to the Medical Informatics community and to use the PathMaster NGI testbed to illustrate concretely certain of the QoS issues that arise. PMID:12223501
Modeling and simulation of M/M/c queuing pharmacy system with adjustable parameters
NASA Astrophysics Data System (ADS)
Rashida, A. R.; Fadzli, Mohammad; Ibrahim, Safwati; Goh, Siti Rohana
2016-02-01
This paper studies a discrete event simulation (DES) as a computer based modelling that imitates a real system of pharmacy unit. M/M/c queuing theo is used to model and analyse the characteristic of queuing system at the pharmacy unit of Hospital Tuanku Fauziah, Kangar in Perlis, Malaysia. The input of this model is based on statistical data collected for 20 working days in June 2014. Currently, patient waiting time of pharmacy unit is more than 15 minutes. The actual operation of the pharmacy unit is a mixed queuing server with M/M/2 queuing model where the pharmacist is referred as the server parameters. DES approach and ProModel simulation software is used to simulate the queuing model and to propose the improvement for queuing system at this pharmacy system. Waiting time for each server is analysed and found out that Counter 3 and 4 has the highest waiting time which is 16.98 and 16.73 minutes. Three scenarios; M/M/3, M/M/4 and M/M/5 are simulated and waiting time for actual queuing model and experimental queuing model are compared. The simulation results show that by adding the server (pharmacist), it will reduce patient waiting time to a reasonable improvement. Almost 50% average patient waiting time is reduced when one pharmacist is added to the counter. However, it is not necessary to fully utilize all counters because eventhough M/M/4 and M/M/5 produced more reduction in patient waiting time, but it is ineffective since Counter 5 is rarely used.
ERIC Educational Resources Information Center
Allen, Frank R.; Smith, Rita H.
1993-01-01
Describes a survey that was conducted at the University of Tennessee at Knoxville library to count and categorize the types of questions coming into the reference department from telephone calls. Informational and directional calls are examined, implications for staffing are considered, and queuing theory is applied. (seven references) (LRW)
Teaching Mathematical Modelling: Demonstrating Enrichment and Elaboration
ERIC Educational Resources Information Center
Warwick, Jon
2015-01-01
This paper uses a series of models to illustrate one of the fundamental processes of model building--that of enrichment and elaboration. The paper describes how a problem context is given which allows a series of models to be developed from a simple initial model using a queuing theory framework. The process encourages students to think about the…
The study on the Layout of the Charging Station in Chengdu
NASA Astrophysics Data System (ADS)
Cai, yun; Zhang, wanquan; You, wei; Mao, pan
2018-03-01
In this paper, the comprehensive analysis of the factors affecting the layout of the electric car, considering the principle of layout of the charging station. Using queuing theory in operational research to establish mathematical model and basing on the principle of saving resource and convenient owner to optimize site number. Combining the theory of center to determine the service radius, Using the Gravity method to determine the initial location, Finally using the method of center of gravity to locate the charging station’s location.
Queuing Time Prediction Using WiFi Positioning Data in an Indoor Scenario.
Shu, Hua; Song, Ci; Pei, Tao; Xu, Lianming; Ou, Yang; Zhang, Libin; Li, Tao
2016-11-22
Queuing is common in urban public places. Automatically monitoring and predicting queuing time can not only help individuals to reduce their wait time and alleviate anxiety but also help managers to allocate resources more efficiently and enhance their ability to address emergencies. This paper proposes a novel method to estimate and predict queuing time in indoor environments based on WiFi positioning data. First, we use a series of parameters to identify the trajectories that can be used as representatives of queuing time. Next, we divide the day into equal time slices and estimate individuals' average queuing time during specific time slices. Finally, we build a nonstandard autoregressive (NAR) model trained using the previous day's WiFi estimation results and actual queuing time to predict the queuing time in the upcoming time slice. A case study comparing two other time series analysis models shows that the NAR model has better precision. Random topological errors caused by the drift phenomenon of WiFi positioning technology (locations determined by a WiFi positioning system may drift accidently) and systematic topological errors caused by the positioning system are the main factors that affect the estimation precision. Therefore, we optimize the deployment strategy during the positioning system deployment phase and propose a drift ratio parameter pertaining to the trajectory screening phase to alleviate the impact of topological errors and improve estimates. The WiFi positioning data from an eight-day case study conducted at the T3-C entrance of Beijing Capital International Airport show that the mean absolute estimation error is 147 s, which is approximately 26.92% of the actual queuing time. For predictions using the NAR model, the proportion is approximately 27.49%. The theoretical predictions and the empirical case study indicate that the NAR model is an effective method to estimate and predict queuing time in indoor public areas.
Queuing Time Prediction Using WiFi Positioning Data in an Indoor Scenario
Shu, Hua; Song, Ci; Pei, Tao; Xu, Lianming; Ou, Yang; Zhang, Libin; Li, Tao
2016-01-01
Queuing is common in urban public places. Automatically monitoring and predicting queuing time can not only help individuals to reduce their wait time and alleviate anxiety but also help managers to allocate resources more efficiently and enhance their ability to address emergencies. This paper proposes a novel method to estimate and predict queuing time in indoor environments based on WiFi positioning data. First, we use a series of parameters to identify the trajectories that can be used as representatives of queuing time. Next, we divide the day into equal time slices and estimate individuals’ average queuing time during specific time slices. Finally, we build a nonstandard autoregressive (NAR) model trained using the previous day’s WiFi estimation results and actual queuing time to predict the queuing time in the upcoming time slice. A case study comparing two other time series analysis models shows that the NAR model has better precision. Random topological errors caused by the drift phenomenon of WiFi positioning technology (locations determined by a WiFi positioning system may drift accidently) and systematic topological errors caused by the positioning system are the main factors that affect the estimation precision. Therefore, we optimize the deployment strategy during the positioning system deployment phase and propose a drift ratio parameter pertaining to the trajectory screening phase to alleviate the impact of topological errors and improve estimates. The WiFi positioning data from an eight-day case study conducted at the T3-C entrance of Beijing Capital International Airport show that the mean absolute estimation error is 147 s, which is approximately 26.92% of the actual queuing time. For predictions using the NAR model, the proportion is approximately 27.49%. The theoretical predictions and the empirical case study indicate that the NAR model is an effective method to estimate and predict queuing time in indoor public areas. PMID:27879663
Discrete Event Simulation Models for CT Examination Queuing in West China Hospital.
Luo, Li; Liu, Hangjiang; Liao, Huchang; Tang, Shijun; Shi, Yingkang; Guo, Huili
2016-01-01
In CT examination, the emergency patients (EPs) have highest priorities in the queuing system and thus the general patients (GPs) have to wait for a long time. This leads to a low degree of satisfaction of the whole patients. The aim of this study is to improve the patients' satisfaction by designing new queuing strategies for CT examination. We divide the EPs into urgent type and emergency type and then design two queuing strategies: one is that the urgent patients (UPs) wedge into the GPs' queue with fixed interval (fixed priority model) and the other is that the patients have dynamic priorities for queuing (dynamic priority model). Based on the data from Radiology Information Database (RID) of West China Hospital (WCH), we develop some discrete event simulation models for CT examination according to the designed strategies. We compare the performance of different strategies on the basis of the simulation results. The strategy that patients have dynamic priorities for queuing makes the waiting time of GPs decrease by 13 minutes and the degree of satisfaction increase by 40.6%. We design a more reasonable CT examination queuing strategy to decrease patients' waiting time and increase their satisfaction degrees.
Discrete Event Simulation Models for CT Examination Queuing in West China Hospital
Luo, Li; Tang, Shijun; Shi, Yingkang; Guo, Huili
2016-01-01
In CT examination, the emergency patients (EPs) have highest priorities in the queuing system and thus the general patients (GPs) have to wait for a long time. This leads to a low degree of satisfaction of the whole patients. The aim of this study is to improve the patients' satisfaction by designing new queuing strategies for CT examination. We divide the EPs into urgent type and emergency type and then design two queuing strategies: one is that the urgent patients (UPs) wedge into the GPs' queue with fixed interval (fixed priority model) and the other is that the patients have dynamic priorities for queuing (dynamic priority model). Based on the data from Radiology Information Database (RID) of West China Hospital (WCH), we develop some discrete event simulation models for CT examination according to the designed strategies. We compare the performance of different strategies on the basis of the simulation results. The strategy that patients have dynamic priorities for queuing makes the waiting time of GPs decrease by 13 minutes and the degree of satisfaction increase by 40.6%. We design a more reasonable CT examination queuing strategy to decrease patients' waiting time and increase their satisfaction degrees. PMID:27547237
ERIC Educational Resources Information Center
Chiarini, Marc A.
2010-01-01
Traditional methods for system performance analysis have long relied on a mix of queuing theory, detailed system knowledge, intuition, and trial-and-error. These approaches often require construction of incomplete gray-box models that can be costly to build and difficult to scale or generalize. In this thesis, we present a black-box analysis…
CCSDS Advanced Orbiting Systems Virtual Channel Access Service for QoS MACHETE Model
NASA Technical Reports Server (NTRS)
Jennings, Esther H.; Segui, John S.
2011-01-01
To support various communications requirements imposed by different missions, interplanetary communication protocols need to be designed, validated, and evaluated carefully. Multimission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in "Simulator of Space Communication Networks" (NPO-41373), NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. By building abstract behavioral models of network protocols, one can validate performance after identifying the appropriate metrics of interest. The innovators have extended the MACHETE model library to include a generic link-layer Virtual Channel (VC) model supporting quality-of-service (QoS) controls based on IP streams. The main purpose of this generic Virtual Channel model addition was to interface fine-grain flow-based QoS (quality of service) between the network and MAC layers of the QualNet simulator, a commercial component of MACHETE. This software model adds the capability of mapping IP streams, based on header fields, to virtual channel numbers, allowing extended QoS handling at link layer. This feature further refines the QoS v existing at the network layer. QoS at the network layer (e.g. diffserv) supports few QoS classes, so data from one class will be aggregated together; differentiating between flows internal to a class/priority is not supported. By adding QoS classification capability between network and MAC layers through VC, one maps multiple VCs onto the same physical link. Users then specify different VC weights, and different queuing and scheduling policies at the link layer. This VC model supports system performance analysis of various virtual channel link-layer QoS queuing schemes independent of the network-layer QoS systems.
Performance Modeling of Network-Attached Storage Device Based Hierarchical Mass Storage Systems
NASA Technical Reports Server (NTRS)
Menasce, Daniel A.; Pentakalos, Odysseas I.
1995-01-01
Network attached storage devices improve I/O performance by separating control and data paths and eliminating host intervention during the data transfer phase. Devices are attached to both a high speed network for data transfer and to a slower network for control messages. Hierarchical mass storage systems use disks to cache the most recently used files and a combination of robotic and manually mounted tapes to store the bulk of the files in the file system. This paper shows how queuing network models can be used to assess the performance of hierarchical mass storage systems that use network attached storage devices as opposed to host attached storage devices. Simulation was used to validate the model. The analytic model presented here can be used, among other things, to evaluate the protocols involved in 1/0 over network attached devices.
Efficient priority queueing routing strategy on networks of mobile agents
NASA Astrophysics Data System (ADS)
Wu, Gan-Hua; Yang, Hui-Jie; Pan, Jia-Hui
2018-03-01
As a consequence of their practical implications for communications networks, traffic dynamics on complex networks have recently captivated researchers. Previous routing strategies for improving transport efficiency have paid little attention to the orders in which the packets should be forwarded, just simply used first-in-first-out queue discipline. Here, we apply a priority queuing discipline and propose a shortest-distance-first routing strategy on networks of mobile agents. Numerical experiments reveal that the proposed scheme remarkably improves both the network throughput and the packet arrival rate and reduces both the average traveling time and the rate of waiting time to traveling time. Moreover, we find that the network capacity increases with an increase in both the communication radius and the number of agents. Our work may be helpful for the design of routing strategies on networks of mobile agents.
2002-09-01
Protocol LAN Local Area Network LDAP Lightweight Directory Access Protocol LLQ Low Latency Queuing MAC Media Access Control MarCorSysCom Marine...Description Protocol SIP Session Initiation Protocol SMTP Simple Mail Transfer Protocol SPAWAR Space and Naval Warfare Systems Center SS7 ...PSTN infrastructure previously required to carry the conversation. The cost of accessing the PSTN is thereby eliminated. In cases where Internet
Space Link Extension Protocol Emulation for High-Throughput, High-Latency Network Connections
NASA Technical Reports Server (NTRS)
Tchorowski, Nicole; Murawski, Robert
2014-01-01
New space missions require higher data rates and new protocols to meet these requirements. These high data rate space communication links push the limitations of not only the space communication links, but of the ground communication networks and protocols which forward user data to remote ground stations (GS) for transmission. The Consultative Committee for Space Data Systems, (CCSDS) Space Link Extension (SLE) standard protocol is one protocol that has been proposed for use by the NASA Space Network (SN) Ground Segment Sustainment (SGSS) program. New protocol implementations must be carefully tested to ensure that they provide the required functionality, especially because of the remote nature of spacecraft. The SLE protocol standard has been tested in the NASA Glenn Research Center's SCENIC Emulation Lab in order to observe its operation under realistic network delay conditions. More specifically, the delay between then NASA Integrated Services Network (NISN) and spacecraft has been emulated. The round trip time (RTT) delay for the continental NISN network has been shown to be up to 120ms; as such the SLE protocol was tested with network delays ranging from 0ms to 200ms. Both a base network condition and an SLE connection were tested with these RTT delays, and the reaction of both network tests to the delay conditions were recorded. Throughput for both of these links was set at 1.2Gbps. The results will show that, in the presence of realistic network delay, the SLE link throughput is significantly reduced while the base network throughput however remained at the 1.2Gbps specification. The decrease in SLE throughput has been attributed to the implementation's use of blocking calls. The decrease in throughput is not acceptable for high data rate links, as the link requires constant data a flow in order for spacecraft and ground radios to stay synchronized, unless significant data is queued a the ground station. In cases where queuing the data is not an option, such as during real time transmissions, the SLE implementation cannot support high data rate communication.
He, Xinhua; Hu, Wenfa
2014-01-01
This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model.
He, Xinhua
2014-01-01
This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model. PMID:24688367
Queue theory for triangular and weibull arrival distribution models (case study of Banyumanik toll)
NASA Astrophysics Data System (ADS)
Sugito; Rahmawati, Rita; Kusuma Wardhani, Jenesia
2018-05-01
Queuing is one of the most common phenomena in daily life. Queued also happens on highway during busy time. The Electronic Toll Collection (ETC) was the new system of the Banyumanik toll gate which operates in 2014. Before ETC, Banyumanik toll gate users got regular service (regular toll gate) by paying in cash only. The ETC benefits more than regular service, but automatic toll gate (ETC) users are still few compared to regular toll gate users. To know the effectiveness of substance service, this paper used analysis of queuing system. The research was conducted at Toll Gate Banyumanik with the implementation time on 26-28 December 2016 for Ungaran-Semarang direction, and 29-31 December 2016 for Semarang- Ungaran direction. In one day, observation was done for 11 hours. That was at 07.00 a.m. until 06.00 p.m. There are 4 models of queues at Banyumanik toll gate. Here the four models will be used on the number of arrival and service time. Based on the simulation with Arena, the result showed that queue model regular toll gate in Ugaran-Semarang direction is (Tria/G/3):(GD/∞/∞) and the queue model for automatic toll gate is (G/G/3):(GD/∞/∞). While the queue model for the direction of Semarang-Ungaran regular toll gate is (G/G/3):(GD/∞/∞) and the queue model of automatic toll gate is (Weib/G/3):(GD/∞/∞).
Code of Federal Regulations, 2011 CFR
2011-04-01
... 23 Highways 1 2011-04-01 2011-04-01 false Can other sources of funds be used to finance a queued project in advance of receipt of IRRBP funds? 661.43 Section 661.43 Highways FEDERAL HIGHWAY... PROGRAM § 661.43 Can other sources of funds be used to finance a queued project in advance of receipt of...
Code of Federal Regulations, 2013 CFR
2013-04-01
... 23 Highways 1 2013-04-01 2013-04-01 false Can other sources of funds be used to finance a queued project in advance of receipt of IRRBP funds? 661.43 Section 661.43 Highways FEDERAL HIGHWAY... PROGRAM § 661.43 Can other sources of funds be used to finance a queued project in advance of receipt of...
Code of Federal Regulations, 2014 CFR
2014-04-01
... 23 Highways 1 2014-04-01 2014-04-01 false Can other sources of funds be used to finance a queued project in advance of receipt of IRRBP funds? 661.43 Section 661.43 Highways FEDERAL HIGHWAY... PROGRAM § 661.43 Can other sources of funds be used to finance a queued project in advance of receipt of...
Code of Federal Regulations, 2012 CFR
2012-04-01
... 23 Highways 1 2012-04-01 2012-04-01 false Can other sources of funds be used to finance a queued project in advance of receipt of IRRBP funds? 661.43 Section 661.43 Highways FEDERAL HIGHWAY... PROGRAM § 661.43 Can other sources of funds be used to finance a queued project in advance of receipt of...
Capacity-constrained traffic assignment in networks with residual queues
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lam, W.H.K.; Zhang, Y.
2000-04-01
This paper proposes a capacity-constrained traffic assignment model for strategic transport planning in which the steady-state user equilibrium principle is extended for road networks with residual queues. Therefore, the road-exit capacity and the queuing effects can be incorporated into the strategic transport model for traffic forecasting. The proposed model is applicable to the congested network particularly when the traffic demands exceeds the capacity of the network during the peak period. An efficient solution method is proposed for solving the steady-state traffic assignment problem with residual queues. Then a simple numerical example is employed to demonstrate the application of the proposedmore » model and solution method, while an example of a medium-sized arterial highway network in Sioux Falls, South Dakota, is used to test the applicability of the proposed solution to real problems.« less
NASA Astrophysics Data System (ADS)
Duan, Haoran
1997-12-01
This dissertation presents the concepts, principles, performance, and implementation of input queuing and cell-scheduling modules for the Illinois Pulsar-based Optical INTerconnect (iPOINT) input-buffered Asynchronous Transfer Mode (ATM) testbed. Input queuing (IQ) ATM switches are well suited to meet the requirements of current and future ultra-broadband ATM networks. The IQ structure imposes minimum memory bandwidth requirements for cell buffering, tolerates bursty traffic, and utilizes memory efficiently for multicast traffic. The lack of efficient cell queuing and scheduling solutions has been a major barrier to build high-performance, scalable IQ-based ATM switches. This dissertation proposes a new Three-Dimensional Queue (3DQ) and a novel Matrix Unit Cell Scheduler (MUCS) to remove this barrier. 3DQ uses a linked-list architecture based on Synchronous Random Access Memory (SRAM) to combine the individual advantages of per-virtual-circuit (per-VC) queuing, priority queuing, and N-destination queuing. It avoids Head of Line (HOL) blocking and provides per-VC Quality of Service (QoS) enforcement mechanisms. Computer simulation results verify the QoS capabilities of 3DQ. For multicast traffic, 3DQ provides efficient usage of cell buffering memory by storing multicast cells only once. Further, the multicast mechanism of 3DQ prevents a congested destination port from blocking other less- loaded ports. The 3DQ principle has been prototyped in the Illinois Input Queue (iiQueue) module. Using Field Programmable Gate Array (FPGA) devices, SRAM modules, and integrated on a Printed Circuit Board (PCB), iiQueue can process incoming traffic at 800 Mb/s. Using faster circuit technology, the same design is expected to operate at the OC-48 rate (2.5 Gb/s). MUCS resolves the output contention by evaluating the weight index of each candidate and selecting the heaviest. It achieves near-optimal scheduling and has a very short response time. The algorithm originates from a heuristic strategy that leads to 'socially optimal' solutions, yielding a maximum number of contention-free cells being scheduled. A novel mixed digital-analog circuit has been designed to implement the MUCS core functionality. The MUCS circuit maps the cell scheduling computation to the capacitor charging and discharging procedures that are conducted fully in parallel. The design has a uniform circuit structure, low interconnect counts, and low chip I/O counts. Using 2 μm CMOS technology, the design operates on a 100 MHz clock and finds a near-optimal solution within a linear processing time. The circuit has been verified at the transistor level by HSPICE simulation. During this research, a five-port IQ-based optoelectronic iPOINT ATM switch has been developed and demonstrated. It has been fully functional with an aggregate throughput of 800 Mb/s. The second-generation IQ-based switch is currently under development. Equipped with iiQueue modules and MUCS module, the new switch system will deliver a multi-gigabit aggregate throughput, eliminate HOL blocking, provide per-VC QoS, and achieve near-100% link bandwidth utilization. Complete documentation of input modules and trunk module for the existing testbed, and complete documentation of 3DQ, iiQueue, and MUCS for the second-generation testbed are given in this dissertation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chertkov, Michael; Turitsyn, Konstantin; Sulc, Petr
The anticipated increase in the number of plug-in electric vehicles (EV) will put additional strain on electrical distribution circuits. Many control schemes have been proposed to control EV charging. Here, we develop control algorithms based on randomized EV charging start times and simple one-way broadcast communication allowing for a time delay between communication events. Using arguments from queuing theory and statistical analysis, we seek to maximize the utilization of excess distribution circuit capacity while keeping the probability of a circuit overload negligible.
Modeling the effect of bus stops on capacity of curb lane
NASA Astrophysics Data System (ADS)
Luo, Qingyu; Zheng, Tianyao; Wu, Wenjing; Jia, Hongfei; Li, Jin
With the increase of buses and bus lines, a negative effect on road section capacity is made by the prolonged delay and queuing time at bus stops. However, existing methods of measuring the negative effect pay little attention to different bus stop types in the curb lanes. This paper uses Gap theory and Queuing theory to build models for effect-time and potential capacity in different conditions, including curbside bus stops, bus bays with overflow and bus bays without overflow. In order to make the effect-time models accurate and reliable, two types of probabilities are introduced. One is the probability that the dwell time is less than the headway of curb lane at curbside bus stops; the other is the overflow probability at bus bays. Based on the fundamental road capacity model and effect-time models, potential capacity models of curb lane are designed. The new models are calibrated by the survey data from Changchun City, and verified by the simulation software of VISSIM. Furthermore, with different arrival rates of vehicles, the setting conditions of bus stops are researched. Results show that the potential capacity models have high precision. They can offer a reference for recognizing the effect of bus stops on the capacity of curb lane, which can provide a basis for planning, design and management of urban roads and bus stops.
IBM NJE protocol emulator for VAX/VMS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Engert, D.E.
1981-01-01
Communications software has been written at Argonne National Laboratory to enable a VAX/VMS system to participate as an end-node in a standard IBM network by emulating the Network Job Entry (NJE) protocol. NJE is actually a collection of programs that support job networking for the operating systems used on most large IBM-compatible computers (e.g., VM/370, MVS with JES2 or JES3, SVS, MVT with ASP or HASP). Files received by the VAX can be printed or saved in user-selected disk files. Files sent to the network can be routed to any node in the network for printing, punching, or job submission,more » as well as to a VM/370 user's virtual reader. Files sent from the VAX are queued and transmitted asynchronously to allow users to perform other work while files are awaiting transmission. No changes are required to the IBM software.« less
NASA Astrophysics Data System (ADS)
Tadić, Bosiljka; Thurner, Stefan; Rodgers, G. J.
2004-03-01
We study the microscopic time fluctuations of traffic load and the global statistical properties of a dense traffic of particles on scale-free cyclic graphs. For a wide range of driving rates R the traffic is stationary and the load time series exhibits antipersistence due to the regulatory role of the superstructure associated with two hub nodes in the network. We discuss how the superstructure affects the functioning of the network at high traffic density and at the jamming threshold. The degree of correlations systematically decreases with increasing traffic density and eventually disappears when approaching a jamming density Rc. Already before jamming we observe qualitative changes in the global network-load distributions and the particle queuing times. These changes are related to the occurrence of temporary crises in which the network-load increases dramatically, and then slowly falls back to a value characterizing free flow.
Modeling and measurement of fault-tolerant multiprocessors
NASA Technical Reports Server (NTRS)
Shin, K. G.; Woodbury, M. H.; Lee, Y. H.
1985-01-01
The workload effects on computer performance are addressed first for a highly reliable unibus multiprocessor used in real-time control. As an approach to studing these effects, a modified Stochastic Petri Net (SPN) is used to describe the synchronous operation of the multiprocessor system. From this model the vital components affecting performance can be determined. However, because of the complexity in solving the modified SPN, a simpler model, i.e., a closed priority queuing network, is constructed that represents the same critical aspects. The use of this model for a specific application requires the partitioning of the workload into job classes. It is shown that the steady state solution of the queuing model directly produces useful results. The use of this model in evaluating an existing system, the Fault Tolerant Multiprocessor (FTMP) at the NASA AIRLAB, is outlined with some experimental results. Also addressed is the technique of measuring fault latency, an important microscopic system parameter. Most related works have assumed no or a negligible fault latency and then performed approximate analyses. To eliminate this deficiency, a new methodology for indirectly measuring fault latency is presented.
Berkeley lab checkpoint/restart (BLCR) for Linux clusters
Hargrove, Paul H.; Duell, Jason C.
2006-09-01
This article describes the motivation, design and implementation of Berkeley Lab Checkpoint/Restart (BLCR), a system-level checkpoint/restart implementation for Linux clusters that targets the space of typical High Performance Computing applications, including MPI. Application-level solutions, including both checkpointing and fault-tolerant algorithms, are recognized as more time and space efficient than system-level checkpoints, which cannot make use of any application-specific knowledge. However, system-level checkpointing allows for preemption, making it suitable for responding to fault precursors (for instance, elevated error rates from ECC memory or network CRCs, or elevated temperature from sensors). Preemption can also increase the efficiency of batch scheduling; for instancemore » reducing idle cycles (by allowing for shutdown without any queue draining period or reallocation of resources to eliminate idle nodes when better fitting jobs are queued), and reducing the average queued time (by limiting large jobs to running during off-peak hours, without the need to limit the length of such jobs). Each of these potential uses makes BLCR a valuable tool for efficient resource management in Linux clusters. © 2006 IOP Publishing Ltd.« less
A Study on Coexistence Capability Evaluations of the Enhanced Channel Hopping Mechanism in WBANs
Wei, Zhongcheng; Sun, Yongmei; Ji, Yuefeng
2017-01-01
As an important coexistence technology, channel hopping can reduce the interference among Wireless Body Area Networks (WBANs). However, it simultaneously brings some issues, such as energy waste, long latency and communication interruptions, etc. In this paper, we propose an enhanced channel hopping mechanism that allows multiple WBANs coexisted in the same channel. In order to evaluate the coexistence performance, some critical metrics are designed to reflect the possibility of channel conflict. Furthermore, by taking the queuing and non-queuing behaviors into consideration, we present a set of analysis approaches to evaluate the coexistence capability. On the one hand, we present both service-dependent and service-independent analysis models to estimate the number of coexisting WBANs. On the other hand, based on the uniform distribution assumption and the additive property of Possion-stream, we put forward two approximate methods to compute the number of occupied channels. Extensive simulation results demonstrate that our estimation approaches can provide an effective solution for coexistence capability estimation. Moreover, the enhanced channel hopping mechanism can significantly improve the coexistence capability and support a larger arrival rate of WBANs. PMID:28098818
Evolving Requirements for Magnetic Tape Data Storage Systems
NASA Technical Reports Server (NTRS)
Gniewek, John J.
1996-01-01
Magnetic tape data storage systems have evolved in an environment where the major applications have been back-up/restore, disaster recovery, and long term archive. Coincident with the rapidly improving price-performance of disk storage systems, the prime requirements for tape storage systems have remained: (1) low cost per MB, (2) a data rate balanced to the remaining system components. Little emphasis was given to configuring the technology components to optimize retrieval of the stored data. Emerging new applications such as network attached high speed memory (HSM), and digital libraries, place additional emphasis and requirements on the retrieval of the stored data. It is therefore desirable to consider the system to be defined both by STorage And Retrieval System (STARS) requirements. It is possible to provide comparative performance analysis of different STARS by incorporating parameters related to (1) device characteristics, and (2) application characteristics in combination with queuing theory analysis. Results of these analyses are presented here in the form of response time as a function of system configuration for two different types of devices and for a variety of applications.
Airport Facility Queuing Model Validation
DOT National Transportation Integrated Search
1977-05-01
Criteria are presented for selection of analytic models to represent waiting times due to queuing processes. An existing computer model by M.F. Neuts which assumes general nonparametric distributions of arrivals per unit time and service times for a ...
Principles of Queued Service Observing at CFHT
NASA Astrophysics Data System (ADS)
Manset, Nadine; Burdullis, T.; Devost, D.
2011-03-01
CFHT started to use Queued Service Observing in 2001, and is now operating in that mode over 95% of the time. Ten years later, the observations are now carried out by Remote Observers who are not present at the telescope (see the companion presentation "Remote Queued Service Observing at CFHT"). The next phase at CFHT will likley involve assisted or autonomous service observing (see the presentation "Artificial Intelligence in Autonomous Telescopes"), which would not be possible without first having a Queued observations system already in place. The advantages and disadvantages of QSO at CFHT will be reviewed. The principles of QSO at CFHT, which allow CFHT to complete 90-100% of the top 30-40% programs and often up to 80% of other accepted programs, will be presented, along with the strategic use of overfill programs, the method of agency balance, and the suite of planning, scheduling, analysis and data quality assessment tools available to Queue Coordinators and Remote Observers.
System model the processing of heterogeneous sensory information in robotized complex
NASA Astrophysics Data System (ADS)
Nikolaev, V.; Titov, V.; Syryamkin, V.
2018-05-01
Analyzed the scope and the types of robotic systems consisting of subsystems of the form "a heterogeneous sensors data processing subsystem". On the basis of the Queuing theory model is developed taking into account the unevenness of the intensity of information flow from the sensors to the subsystem of information processing. Analytical solution to assess the relationship of subsystem performance and uneven flows. The research of the obtained solution in the range of parameter values of practical interest.
A queuing model for road traffic simulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Guerrouahane, N.; Aissani, D.; Bouallouche-Medjkoune, L.
We present in this article a stochastic queuing model for the raod traffic. The model is based on the M/G/c/c state dependent queuing model, and is inspired from the deterministic Godunov scheme for the road traffic simulation. We first propose a variant of M/G/c/c state dependent model that works with density-flow fundamental diagrams rather than density-speed relationships. We then extend this model in order to consider upstream traffic demand as well as downstream traffic supply. Finally, we show how to model a whole raod by concatenating raod sections as in the deterministic Godunov scheme.
Capacity utilization study for aviation security cargo inspection queuing system
NASA Astrophysics Data System (ADS)
Allgood, Glenn O.; Olama, Mohammed M.; Lake, Joe E.; Brumback, Daryl
2010-04-01
In this paper, we conduct performance evaluation study for an aviation security cargo inspection queuing system for material flow and accountability. The queuing model employed in our study is based on discrete-event simulation and processes various types of cargo simultaneously. Onsite measurements are collected in an airport facility to validate the queuing model. The overall performance of the aviation security cargo inspection system is computed, analyzed, and optimized for the different system dynamics. Various performance measures are considered such as system capacity, residual capacity, throughput, capacity utilization, subscribed capacity utilization, resources capacity utilization, subscribed resources capacity utilization, and number of cargo pieces (or pallets) in the different queues. These metrics are performance indicators of the system's ability to service current needs and response capacity to additional requests. We studied and analyzed different scenarios by changing various model parameters such as number of pieces per pallet, number of TSA inspectors and ATS personnel, number of forklifts, number of explosives trace detection (ETD) and explosives detection system (EDS) inspection machines, inspection modality distribution, alarm rate, and cargo closeout time. The increased physical understanding resulting from execution of the queuing model utilizing these vetted performance measures should reduce the overall cost and shipping delays associated with new inspection requirements.
Belciug, Smaranda; Gorunescu, Florin
2015-02-01
Scarce healthcare resources require carefully made policies ensuring optimal bed allocation, quality healthcare service, and adequate financial support. This paper proposes a complex analysis of the resource allocation in a hospital department by integrating in the same framework a queuing system, a compartmental model, and an evolutionary-based optimization. The queuing system shapes the flow of patients through the hospital, the compartmental model offers a feasible structure of the hospital department in accordance to the queuing characteristics, and the evolutionary paradigm provides the means to optimize the bed-occupancy management and the resource utilization using a genetic algorithm approach. The paper also focuses on a "What-if analysis" providing a flexible tool to explore the effects on the outcomes of the queuing system and resource utilization through systematic changes in the input parameters. The methodology was illustrated using a simulation based on real data collected from a geriatric department of a hospital from London, UK. In addition, the paper explores the possibility of adapting the methodology to different medical departments (surgery, stroke, and mental illness). Moreover, the paper also focuses on the practical use of the model from the healthcare point of view, by presenting a simulated application. Copyright © 2014 Elsevier Inc. All rights reserved.
Capacity Utilization Study for Aviation Security Cargo Inspection Queuing System
DOE Office of Scientific and Technical Information (OSTI.GOV)
Allgood, Glenn O; Olama, Mohammed M; Lake, Joe E
In this paper, we conduct performance evaluation study for an aviation security cargo inspection queuing system for material flow and accountability. The queuing model employed in our study is based on discrete-event simulation and processes various types of cargo simultaneously. Onsite measurements are collected in an airport facility to validate the queuing model. The overall performance of the aviation security cargo inspection system is computed, analyzed, and optimized for the different system dynamics. Various performance measures are considered such as system capacity, residual capacity, throughput, capacity utilization, subscribed capacity utilization, resources capacity utilization, subscribed resources capacity utilization, and number ofmore » cargo pieces (or pallets) in the different queues. These metrics are performance indicators of the system s ability to service current needs and response capacity to additional requests. We studied and analyzed different scenarios by changing various model parameters such as number of pieces per pallet, number of TSA inspectors and ATS personnel, number of forklifts, number of explosives trace detection (ETD) and explosives detection system (EDS) inspection machines, inspection modality distribution, alarm rate, and cargo closeout time. The increased physical understanding resulting from execution of the queuing model utilizing these vetted performance measures should reduce the overall cost and shipping delays associated with new inspection requirements.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Engert, D.E.; Raffenetti, C.
NJE is communications software developed to enable a VAX VMS system to participate as an end-node in a standard IBM network by emulating the Network Job Entry (NJE) protocol. NJE supports job networking for the operating systems used on most large IBM-compatible computers (e.g., VM/370, MVS with JES2 or JES3, SVS, MVT with ASP or HASP). Files received by the VAX can be printed or saved in user-selected disk files. Files sent to the network can be routed to any network node for printing, punching, or job submission, or to a VM/370 user's virtual reader. Files sent from the VAXmore » are queued and transmitted asynchronously. No changes are required to the IBM software.DEC VAX11/780; VAX-11 FORTRAN 77 (99%) and MACRO-11 (1%); VMS 2.5; VAX11/780 with DUP-11 UNIBUS interface and 9600 baud synchronous modem..« less
TinyOS-based quality of service management in wireless sensor networks
Peterson, N.; Anusuya-Rangappa, L.; Shirazi, B.A.; Huang, R.; Song, W.-Z.; Miceli, M.; McBride, D.; Hurson, A.; LaHusen, R.
2009-01-01
Previously the cost and extremely limited capabilities of sensors prohibited Quality of Service (QoS) implementations in wireless sensor networks. With advances in technology, sensors are becoming significantly less expensive and the increases in computational and storage capabilities are opening the door for new, sophisticated algorithms to be implemented. Newer sensor network applications require higher data rates with more stringent priority requirements. We introduce a dynamic scheduling algorithm to improve bandwidth for high priority data in sensor networks, called Tiny-DWFQ. Our Tiny-Dynamic Weighted Fair Queuing scheduling algorithm allows for dynamic QoS for prioritized communications by continually adjusting the treatment of communication packages according to their priorities and the current level of network congestion. For performance evaluation, we tested Tiny-DWFQ, Tiny-WFQ (traditional WFQ algorithm implemented in TinyOS), and FIFO queues on an Imote2-based wireless sensor network and report their throughput and packet loss. Our results show that Tiny-DWFQ performs better in all test cases. ?? 2009 IEEE.
The evaluation model of the design of toll
NASA Astrophysics Data System (ADS)
Feng, Shuting
2018-04-01
In recent years, the dramatic increase in traffic burden has highlighted the necessity of rational allocation of toll plaza. At the same time, the need to consider a lot of factors has enhanced the design requirements. In this background, we carry out research on this subject. We propose a reasonable assumption, and abstract the toll plaza into a model only related to B and L. By using the queuing theory and traffic flow theory, we define the throughput, cost and accident prevent with B and L to acquire the base model. By using the method of linear weighting in economics to calculate this model, the optimal B and L strategies are obtained.
Assessing the Queuing Process Using Data Envelopment Analysis: an Application in Health Centres.
Safdar, Komal A; Emrouznejad, Ali; Dey, Prasanta K
2016-01-01
Queuing is one of the very important criteria for assessing the performance and efficiency of any service industry, including healthcare. Data Envelopment Analysis (DEA) is one of the most widely-used techniques for performance measurement in healthcare. However, no queue management application has been reported in the health-related DEA literature. Most of the studies regarding patient flow systems had the objective of improving an already existing Appointment System. The current study presents a novel application of DEA for assessing the queuing process at an Outpatients' department of a large public hospital in a developing country where appointment systems do not exist. The main aim of the current study is to demonstrate the usefulness of DEA modelling in the evaluation of a queue system. The patient flow pathway considered for this study consists of two stages; consultation with a doctor and pharmacy. The DEA results indicated that waiting times and other related queuing variables included need considerable minimisation at both stages.
A heuristic method for consumable resource allocation in multi-class dynamic PERT networks
NASA Astrophysics Data System (ADS)
Yaghoubi, Saeed; Noori, Siamak; Mazdeh, Mohammad Mahdavi
2013-06-01
This investigation presents a heuristic method for consumable resource allocation problem in multi-class dynamic Project Evaluation and Review Technique (PERT) networks, where new projects from different classes (types) arrive to system according to independent Poisson processes with different arrival rates. Each activity of any project is operated at a devoted service station located in a node of the network with exponential distribution according to its class. Indeed, each project arrives to the first service station and continues its routing according to precedence network of its class. Such system can be represented as a queuing network, while the discipline of queues is first come, first served. On the basis of presented method, a multi-class system is decomposed into several single-class dynamic PERT networks, whereas each class is considered separately as a minisystem. In modeling of single-class dynamic PERT network, we use Markov process and a multi-objective model investigated by Azaron and Tavakkoli-Moghaddam in 2007. Then, after obtaining the resources allocated to service stations in every minisystem, the final resources allocated to activities are calculated by the proposed method.
Cell transmission model of dynamic assignment for urban rail transit networks.
Xu, Guangming; Zhao, Shuo; Shi, Feng; Zhang, Feilian
2017-01-01
For urban rail transit network, the space-time flow distribution can play an important role in evaluating and optimizing the space-time resource allocation. For obtaining the space-time flow distribution without the restriction of schedules, a dynamic assignment problem is proposed based on the concept of continuous transmission. To solve the dynamic assignment problem, the cell transmission model is built for urban rail transit networks. The priority principle, queuing process, capacity constraints and congestion effects are considered in the cell transmission mechanism. Then an efficient method is designed to solve the shortest path for an urban rail network, which decreases the computing cost for solving the cell transmission model. The instantaneous dynamic user optimal state can be reached with the method of successive average. Many evaluation indexes of passenger flow can be generated, to provide effective support for the optimization of train schedules and the capacity evaluation for urban rail transit network. Finally, the model and its potential application are demonstrated via two numerical experiments using a small-scale network and the Beijing Metro network.
Tuset-Peiro, Pere; Vazquez-Gallego, Francisco; Alonso-Zarate, Jesus; Alonso, Luis; Vilajosana, Xavier
2014-07-24
Data collection is a key scenario for the Internet of Things because it enables gathering sensor data from distributed nodes that use low-power and long-range wireless technologies to communicate in a single-hop approach. In this kind of scenario, the network is composed of one coordinator that covers a particular area and a large number of nodes, typically hundreds or thousands, that transmit data to the coordinator upon request. Considering this scenario, in this paper we experimentally validate the energy consumption of two Medium Access Control (MAC) protocols, Frame Slotted ALOHA (FSA) and Distributed Queuing (DQ). We model both protocols as a state machine and conduct experiments to measure the average energy consumption in each state and the average number of times that a node has to be in each state in order to transmit a data packet to the coordinator. The results show that FSA is more energy efficient than DQ if the number of nodes is known a priori because the number of slots per frame can be adjusted accordingly. However, in such scenarios the number of nodes cannot be easily anticipated, leading to additional packet collisions and a higher energy consumption due to retransmissions. Contrarily, DQ does not require to know the number of nodes in advance because it is able to efficiently construct an ad hoc network schedule for each collection round. This kind of a schedule ensures that there are no packet collisions during data transmission, thus leading to an energy consumption reduction above 10% compared to FSA.
Network Configuration Analysis for Formation Flying Satellites
NASA Technical Reports Server (NTRS)
Knoblock, Eric J.; Wallett, Thomas M.; Konangi, Vijay K.; Bhasin, Kul B.
2001-01-01
The performance of two networks to support autonomous multi-spacecraft formation flying systems is presented. Both systems are comprised of a ten-satellite formation, with one of the satellites designated as the central or 'mother ship.' All data is routed through the mother ship to the terrestrial network. The first system uses a TCP/EP over ATM protocol architecture within the formation, and the second system uses the IEEE 802.11 protocol architecture within the formation. The simulations consist of file transfers using either the File Transfer Protocol (FTP) or the Simple Automatic File Exchange (SAFE) Protocol. The results compare the IP queuing delay, IP queue size and IP processing delay at the mother ship as well as end-to-end delay for both systems. In all cases, using IEEE 802.11 within the formation yields less delay. Also, the throughput exhibited by SAFE is better than FTP.
Effects of diversity and procrastination in priority queuing theory: The different power law regimes
NASA Astrophysics Data System (ADS)
Saichev, A.; Sornette, D.
2010-01-01
Empirical analyses show that after the update of a browser, or the publication of the vulnerability of a software, or the discovery of a cyber worm, the fraction of computers still using the older browser or software version, or not yet patched, or exhibiting worm activity decays as a power law ˜1/tα with 0<α≤1 over a time scale of years. We present a simple model for this persistence phenomenon, framed within the standard priority queuing theory, of a target task which has the lowest priority compared to all other tasks that flow on the computer of an individual. We identify a “time deficit” control parameter β and a bifurcation to a regime where there is a nonzero probability for the target task to never be completed. The distribution of waiting time T until the completion of the target task has the power law tail ˜1/t1/2 , resulting from a first-passage solution of an equivalent Wiener process. Taking into account a diversity of time deficit parameters in a population of individuals, the power law tail is changed into 1/tα , with αɛ(0.5,∞) , including the well-known case 1/t . We also study the effect of “procrastination,” defined as the situation in which the target task may be postponed or delayed even after the individual has solved all other pending tasks. This regime provides an explanation for even slower apparent decay and longer persistence.
Jagger, Pamela; Shively, Gerald
Using data from 433 firms operating along Uganda's charcoal and timber supply chains we investigate patterns of bribe payment and tax collection between supply chain actors and government officials responsible for collecting taxes and fees. We examine the factors associated with the presence and magnitude of bribe and tax payments using a series of bivariate probit and Tobit regression models. We find empirical support for a number of hypotheses related to payments, highlighting the role of queuing, capital-at-risk, favouritism, networks, and role in the supply chain. We also find that taxes crowd-in bribery in the charcoal market.
Jagger, Pamela; Shively, Gerald
2016-01-01
Using data from 433 firms operating along Uganda’s charcoal and timber supply chains we investigate patterns of bribe payment and tax collection between supply chain actors and government officials responsible for collecting taxes and fees. We examine the factors associated with the presence and magnitude of bribe and tax payments using a series of bivariate probit and Tobit regression models. We find empirical support for a number of hypotheses related to payments, highlighting the role of queuing, capital-at-risk, favouritism, networks, and role in the supply chain. We also find that taxes crowd-in bribery in the charcoal market. PMID:27274568
Yang, Muer; Fry, Michael J; Raikhelkar, Jayashree; Chin, Cynthia; Anyanwu, Anelechi; Brand, Jordan; Scurlock, Corey
2013-02-01
To develop queuing and simulation-based models to understand the relationship between ICU bed availability and operating room schedule to maximize the use of critical care resources and minimize case cancellation while providing equity to patients and surgeons. Retrospective analysis of 6-month unit admission data from a cohort of cardiothoracic surgical patients, to create queuing and simulation-based models of ICU bed flow. Three different admission policies (current admission policy, shortest-processing-time policy, and a dynamic policy) were then analyzed using simulation models, representing 10 yr worth of potential admissions. Important output data consisted of the "average waiting time," a proxy for unit efficiency, and the "maximum waiting time," a surrogate for patient equity. A cardiothoracic surgical ICU in a tertiary center in New York, NY. Six hundred thirty consecutive cardiothoracic surgical patients admitted to the cardiothoracic surgical ICU. None. Although the shortest-processing-time admission policy performs best in terms of unit efficiency (0.4612 days), it did so at expense of patient equity prolonging surgical waiting time by as much as 21 days. The current policy gives the greatest equity but causes inefficiency in unit bed-flow (0.5033 days). The dynamic policy performs at a level (0.4997 days) 8.3% below that of the shortest-processing-time in average waiting time; however, it balances this with greater patient equity (maximum waiting time could be shortened by 4 days compared to the current policy). Queuing theory and computer simulation can be used to model case flow through a cardiothoracic operating room and ICU. A dynamic admission policy that looks at current waiting time and expected ICU length of stay allows for increased equity between patients with only minimum losses of efficiency. This dynamic admission policy would seem to be a superior in maximizing case-flow. These results may be generalized to other surgical ICUs.
Storage assignment optimization in a multi-tier shuttle warehousing system
NASA Astrophysics Data System (ADS)
Wang, Yanyan; Mou, Shandong; Wu, Yaohua
2016-03-01
The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem(TSP), which has been widely applied in the conventional automated storage and retrieval system(AS/RS). However, the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems(MSWS) because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP. In this study, a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period (SWP) and lift idle period (LIP) during transaction cycle time. A mean arrival time difference matrix for pairwise stock keeping units(SKUs) is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation. The decomposition method is applied to analyze the interactions among outbound task time, SWP, and LIP. The ant colony clustering algorithm is designed to determine storage partitions using clustering items. In addition, goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane. This combination is derived based on the analysis results of the queuing network model and on three basic principles. The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry. The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.
Belciug, Smaranda; Gorunescu, Florin
2016-03-01
Explore how efficient intelligent decision support systems, both easily understandable and straightforwardly implemented, can help modern hospital managers to optimize both bed occupancy and utilization costs. This paper proposes a hybrid genetic algorithm-queuing multi-compartment model for the patient flow in hospitals. A finite capacity queuing model with phase-type service distribution is combined with a compartmental model, and an associated cost model is set up. An evolutionary-based approach is used for enhancing the ability to optimize both bed management and associated costs. In addition, a "What-if analysis" shows how changing the model parameters could improve performance while controlling costs. The study uses bed-occupancy data collected at the Department of Geriatric Medicine - St. George's Hospital, London, period 1969-1984, and January 2000. The hybrid model revealed that a bed-occupancy exceeding 91%, implying a patient rejection rate around 1.1%, can be carried out with 159 beds plus 8 unstaffed beds. The same holding and penalty costs, but significantly different bed allocations (156 vs. 184 staffed beds, and 8 vs. 9 unstaffed beds, respectively) will result in significantly different costs (£755 vs. £1172). Moreover, once the arrival rate exceeds 7 patient/day, the costs associated to the finite capacity system become significantly smaller than those associated to an Erlang B queuing model (£134 vs. £947). Encoding the whole information provided by both the queuing system and the cost model through chromosomes, the genetic algorithm represents an efficient tool in optimizing the bed allocation and associated costs. The methodology can be extended to different medical departments with minor modifications in structure and parameterization. Copyright © 2016 Elsevier B.V. All rights reserved.
A comparison of queueing, cluster and distributed computing systems
NASA Technical Reports Server (NTRS)
Kaplan, Joseph A.; Nelson, Michael L.
1993-01-01
Using workstation clusters for distributed computing has become popular with the proliferation of inexpensive, powerful workstations. Workstation clusters offer both a cost effective alternative to batch processing and an easy entry into parallel computing. However, a number of workstations on a network does not constitute a cluster. Cluster management software is necessary to harness the collective computing power. A variety of cluster management and queuing systems are compared: Distributed Queueing Systems (DQS), Condor, Load Leveler, Load Balancer, Load Sharing Facility (LSF - formerly Utopia), Distributed Job Manager (DJM), Computing in Distributed Networked Environments (CODINE), and NQS/Exec. The systems differ in their design philosophy and implementation. Based on published reports on the different systems and conversations with the system's developers and vendors, a comparison of the systems are made on the integral issues of clustered computing.
Achieving fast and stable failure detection in WDM Networks
NASA Astrophysics Data System (ADS)
Gao, Donghui; Zhou, Zhiyu; Zhang, Hanyi
2005-02-01
In dynamic networks, the failure detection time takes a major part of the convergence time, which is an important network performance index. To detect a node or link failure in the network, traditional protocols, like Hello protocol in OSPF or RSVP, exchanges keep-alive messages between neighboring nodes to keep track of the link/node state. But by default settings, it can get a minimum detection time in the measure of dozens of seconds, which can not meet the demands of fast network convergence and failure recovery. When configuring the related parameters to reduce the detection time, there will be notable instability problems. In this paper, we analyzed the problem and designed a new failure detection algorithm to reduce the network overhead of detection signaling. Through our experiment we found it is effective to enhance the stability by implicitly acknowledge other signaling messages as keep-alive messages. We conducted our proposal and the previous approaches on the ASON test-bed. The experimental results show that our algorithm gives better performances than previous schemes in about an order magnitude reduction of both false failure alarms and queuing delay to other messages, especially under light traffic load.
Highball: A high speed, reserved-access, wide area network
NASA Technical Reports Server (NTRS)
Mills, David L.; Boncelet, Charles G.; Elias, John G.; Schragger, Paul A.; Jackson, Alden W.
1990-01-01
A network architecture called Highball and a preliminary design for a prototype, wide-area data network designed to operate at speeds of 1 Gbps and beyond are described. It is intended for applications requiring high speed burst transmissions where some latency between requesting a transmission and granting the request can be anticipated and tolerated. Examples include real-time video and disk-disk transfers, national filestore access, remote sensing, and similar applications. The network nodes include an intelligent crossbar switch, but have no buffering capabilities; thus, data must be queued at the end nodes. There are no restrictions on the network topology, link speeds, or end-end protocols. The end system, nodes, and links can operate at any speed up to the limits imposed by the physical facilities. An overview of an initial design approach is presented and is intended as a benchmark upon which a detailed design can be developed. It describes the network architecture and proposed access protocols, as well as functional descriptions of the hardware and software components that could be used in a prototype implementation. It concludes with a discussion of additional issues to be resolved in continuing stages of this project.
Bandwidth Allocation to Interactive Users in DBS-Based Hybrid Internet
1998-01-01
policies 12 3.1 Framework for queuing analysis: ON/OFF source traffic model . 13 3.2 Service quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14...minimizing the queuing delay. In consequence, we were interested in ob- taining improvements in the service quality , as perceived by the users. A...the service quality as per- ceived by users. The merit of this approach, first introduced in [8], is the ability to capture the characteristics of the
Quantifying Cyber-Resilience Against Resource-Exhaustion Attacks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fink, Glenn A.; Griswold, Richard L.; Beech, Zachary W.
2014-07-11
Resilience in the information sciences is notoriously difficult to define much less to measure. But in mechanical engi- neering, the resilience of a substance is mathematically defined as the area under the stress vs. strain curve. We took inspiration from mechanics in an attempt to define resilience precisely for information systems. We first examine the meaning of resilience in language and engineering terms and then translate these definitions to information sciences. Then we tested our definitions of resilience for a very simple problem in networked queuing systems. We discuss lessons learned and make recommendations for using this approach in futuremore » work.« less
A general model for memory interference in a multiprocessor system with memory hierarchy
NASA Technical Reports Server (NTRS)
Taha, Badie A.; Standley, Hilda M.
1989-01-01
The problem of memory interference in a multiprocessor system with a hierarchy of shared buses and memories is addressed. The behavior of the processors is represented by a sequence of memory requests with each followed by a determined amount of processing time. A statistical queuing network model for determining the extent of memory interference in multiprocessor systems with clusters of memory hierarchies is presented. The performance of the system is measured by the expected number of busy memory clusters. The results of the analytic model are compared with simulation results, and the correlation between them is found to be very high.
Scalability Analysis and Use of Compression at the Goddard DAAC and End-to-End MODIS Transfers
NASA Technical Reports Server (NTRS)
Menasce, Daniel A.
1998-01-01
The goal of this task is to analyze the performance of single and multiple FTP transfer between SCF's and the Goddard DAAC. We developed an analytic model to compute the performance of FTP sessions as a function of various key parameters, implemented the model as a program called FTP Analyzer, and carried out validations with real data obtained by running single and multiple FTP transfer between GSFC and the Miami SCF. The input parameters to the model include the mix to FTP sessions (scenario), and for each FTP session, the file size. The network parameters include the round trip time, packet loss rate, the limiting bandwidth of the network connecting the SCF to a DAAC, TCP's basic timeout, TCP's Maximum Segment Size, and TCP's Maximum Receiver's Window Size. The modeling approach used consisted of modeling TCP's overall throughput, computing TCP's delay per FTP transfer, and then solving a queuing network model that includes the FTP clients and servers.
Quality of service routing in wireless ad hoc networks
NASA Astrophysics Data System (ADS)
Sane, Sachin J.; Patcha, Animesh; Mishra, Amitabh
2003-08-01
An efficient routing protocol is essential to guarantee application level quality of service running on wireless ad hoc networks. In this paper we propose a novel routing algorithm that computes a path between a source and a destination by considering several important constraints such as path-life, availability of sufficient energy as well as buffer space in each of the nodes on the path between the source and destination. The algorithm chooses the best path from among the multiples paths that it computes between two endpoints. We consider the use of control packets that run at a priority higher than the data packets in determining the multiple paths. The paper also examines the impact of different schedulers such as weighted fair queuing, and weighted random early detection among others in preserving the QoS level guarantees. Our extensive simulation results indicate that the algorithm improves the overall lifetime of a network, reduces the number of dropped packets, and decreases the end-to-end delay for real-time voice application.
Revisiting Street Intersections Using Slot-Based Systems.
Tachet, Remi; Santi, Paolo; Sobolevsky, Stanislav; Reyes-Castro, Luis Ignacio; Frazzoli, Emilio; Helbing, Dirk; Ratti, Carlo
2016-01-01
Since their appearance at the end of the 19th century, traffic lights have been the primary mode of granting access to road intersections. Today, this centuries-old technology is challenged by advances in intelligent transportation, which are opening the way to new solutions built upon slot-based systems similar to those commonly used in aerial traffic: what we call Slot-based Intersections (SIs). Despite simulation-based evidence of the potential benefits of SIs, a comprehensive, analytical framework to compare their relative performance with traffic lights is still lacking. Here, we develop such a framework. We approach the problem in a novel way, by generalizing classical queuing theory. Having defined safety conditions, we characterize capacity and delay of SIs. In the 2-road crossing configuration, we provide a capacity-optimal SI management system. For arbitrary intersection configurations, near-optimal solutions are developed. Results theoretically show that transitioning from a traffic light system to SI has the potential of doubling capacity and significantly reducing delays. This suggests a reduction of non-linear dynamics induced by intersection bottlenecks, with positive impact on the road network. Such findings can provide transportation engineers and planners with crucial insights as they prepare to manage the transition towards a more intelligent transportation infrastructure in cities.
The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code.
Kunkel, Susanne; Schenck, Wolfram
2017-01-01
NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling.
Networks for Autonomous Formation Flying Satellite Systems
NASA Technical Reports Server (NTRS)
Knoblock, Eric J.; Konangi, Vijay K.; Wallett, Thomas M.; Bhasin, Kul B.
2001-01-01
The performance of three communications networks to support autonomous multi-spacecraft formation flying systems is presented. All systems are comprised of a ten-satellite formation arranged in a star topology, with one of the satellites designated as the central or "mother ship." All data is routed through the mother ship to the terrestrial network. The first system uses a TCP/lP over ATM protocol architecture within the formation the second system uses the IEEE 802.11 protocol architecture within the formation and the last system uses both of the previous architectures with a constellation of geosynchronous satellites serving as an intermediate point-of-contact between the formation and the terrestrial network. The simulations consist of file transfers using either the File Transfer Protocol (FTP) or the Simple Automatic File Exchange (SAFE) Protocol. The results compare the IF queuing delay, and IP processing delay at the mother ship as well as application-level round-trip time for both systems, In all cases, using IEEE 802.11 within the formation yields less delay. Also, the throughput exhibited by SAFE is better than FTP.
The NEST Dry-Run Mode: Efficient Dynamic Analysis of Neuronal Network Simulation Code
Kunkel, Susanne; Schenck, Wolfram
2017-01-01
NEST is a simulator for spiking neuronal networks that commits to a general purpose approach: It allows for high flexibility in the design of network models, and its applications range from small-scale simulations on laptops to brain-scale simulations on supercomputers. Hence, developers need to test their code for various use cases and ensure that changes to code do not impair scalability. However, running a full set of benchmarks on a supercomputer takes up precious compute-time resources and can entail long queuing times. Here, we present the NEST dry-run mode, which enables comprehensive dynamic code analysis without requiring access to high-performance computing facilities. A dry-run simulation is carried out by a single process, which performs all simulation steps except communication as if it was part of a parallel environment with many processes. We show that measurements of memory usage and runtime of neuronal network simulations closely match the corresponding dry-run data. Furthermore, we demonstrate the successful application of the dry-run mode in the areas of profiling and performance modeling. PMID:28701946
Code of Federal Regulations, 2010 CFR
2010-04-01
... 23 Highways 1 2010-04-01 2010-04-01 false Can other sources of funds be used to finance a queued project in advance of receipt of IRRBP funds? 661.43 Section 661.43 Highways FEDERAL HIGHWAY ADMINISTRATION, DEPARTMENT OF TRANSPORTATION ENGINEERING AND TRAFFIC OPERATIONS INDIAN RESERVATION ROAD BRIDGE PROGRAM § 661.43 Can other sources of funds be...
MODELING AND PERFORMANCE EVALUATION FOR AVIATION SECURITY CARGO INSPECTION QUEUING SYSTEM
DOE Office of Scientific and Technical Information (OSTI.GOV)
Allgood, Glenn O; Olama, Mohammed M; Rose, Terri A
Beginning in 2010, the U.S. will require that all cargo loaded in passenger aircraft be inspected. This will require more efficient processing of cargo and will have a significant impact on the inspection protocols and business practices of government agencies and the airlines. In this paper, we conduct performance evaluation study for an aviation security cargo inspection queuing system for material flow and accountability. The overall performance of the aviation security cargo inspection system is computed, analyzed, and optimized for the different system dynamics. Various performance measures are considered such as system capacity, residual capacity, and throughput. These metrics aremore » performance indicators of the system s ability to service current needs and response capacity to additional requests. The increased physical understanding resulting from execution of the queuing model utilizing these vetted performance measures will reduce the overall cost and shipping delays associated with the new inspection requirements.« less
Queuing Models of Tertiary Storage
NASA Technical Reports Server (NTRS)
Johnson, Theodore
1996-01-01
Large scale scientific projects generate and use large amounts of data. For example, the NASA Earth Observation System Data and Information System (EOSDIS) project is expected to archive one petabyte per year of raw satellite data. This data is made automatically available for processing into higher level data products and for dissemination to the scientific community. Such large volumes of data can only be stored in robotic storage libraries (RSL's) for near-line access. A characteristic of RSL's is the use of a robot arm that transfers media between a storage rack and the read/write drives, thus multiplying the capacity of the system. The performance of the RSL's can be a critical limiting factor for the performance of the archive system. However, the many interacting components of an RSL make a performance analysis difficult. In addition, different RSL components can have widely varying performance characteristics. This paper describes our work to develop performance models of an RSL in isolation. Next we show how the RSL model can be incorporated into a queuing network model. We use the models to make some example performance studies of archive systems. The models described in this paper, developed for the NASA EODIS project, are implemented in C with a well defined interface. The source code, accompanying documentation, and also sample JAVA applets are available at: http://www.cis.ufl.edu/ted/
Video transmission on ATM networks. Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Chen, Yun-Chung
1993-01-01
The broadband integrated services digital network (B-ISDN) is expected to provide high-speed and flexible multimedia applications. Multimedia includes data, graphics, image, voice, and video. Asynchronous transfer mode (ATM) is the adopted transport techniques for B-ISDN and has the potential for providing a more efficient and integrated environment for multimedia. It is believed that most broadband applications will make heavy use of visual information. The prospect of wide spread use of image and video communication has led to interest in coding algorithms for reducing bandwidth requirements and improving image quality. The major results of a study on the bridging of network transmission performance and video coding are: Using two representative video sequences, several video source models are developed. The fitness of these models are validated through the use of statistical tests and network queuing performance. A dual leaky bucket algorithm is proposed as an effective network policing function. The concept of the dual leaky bucket algorithm can be applied to a prioritized coding approach to achieve transmission efficiency. A mapping of the performance/control parameters at the network level into equivalent parameters at the video coding level is developed. Based on that, a complete set of principles for the design of video codecs for network transmission is proposed.
Integrating LMINET with TAAM and SIMMOD: A Feasibility Study
NASA Technical Reports Server (NTRS)
Long, Dou; Stouffer-Coston, Virginia; Kostiuk, Peter; Kula, Richard; Yackovetsky, Robert (Technical Monitor)
2001-01-01
LMINET is a queuing network air traffic simulation model implemented at 64 large airports and the entire National Airspace System in the United States. TAAM and SIMMOD are two widely used air traffic event-driven simulation models mostly for airports. Based on our proposed Progressive Augmented window approach, TAAM and SIMMOD are integrated with LMINET though flight schedules. In the integration, the flight schedules are modified through the flight delays reported by the other models. The benefit to the local simulation study is to let TAAM or SIMMOD take the modified schedule from LMINET, which takes into account of the air traffic congestion and flight delays at the national network level. We demonstrate the value of the integrated models by the case studies at Chicago O'Hare International Airport and Washington Dulles International Airport. Details of the integration are reported and future work for a full-blown integration is identified.
A queueing theory based model for business continuity in hospitals.
Miniati, R; Cecconi, G; Dori, F; Frosini, F; Iadanza, E; Biffi Gentili, G; Niccolini, F; Gusinu, R
2013-01-01
Clinical activities can be seen as results of precise and defined events' succession where every single phase is characterized by a waiting time which includes working duration and possible delay. Technology makes part of this process. For a proper business continuity management, planning the minimum number of devices according to the working load only is not enough. A risk analysis on the whole process should be carried out in order to define which interventions and extra purchase have to be made. Markov models and reliability engineering approaches can be used for evaluating the possible interventions and to protect the whole system from technology failures. The following paper reports a case study on the application of the proposed integrated model, including risk analysis approach and queuing theory model, for defining the proper number of device which are essential to guarantee medical activity and comply the business continuity management requirements in hospitals.
NAS Requirements Checklist for Job Queuing/Scheduling Software
NASA Technical Reports Server (NTRS)
Jones, James Patton
1996-01-01
The increasing reliability of parallel systems and clusters of computers has resulted in these systems becoming more attractive for true production workloads. Today, the primary obstacle to production use of clusters of computers is the lack of a functional and robust Job Management System for parallel applications. This document provides a checklist of NAS requirements for job queuing and scheduling in order to make most efficient use of parallel systems and clusters for parallel applications. Future requirements are also identified to assist software vendors with design planning.
Density profiles of the exclusive queuing process
NASA Astrophysics Data System (ADS)
Arita, Chikashi; Schadschneider, Andreas
2012-12-01
The exclusive queuing process (EQP) incorporates the exclusion principle into classic queuing models. It is characterized by, in addition to the entrance probability α and exit probability β, a third parameter: the hopping probability p. The EQP can be interpreted as an exclusion process of variable system length. Its phase diagram in the parameter space (α,β) is divided into a convergent phase and a divergent phase by a critical line which consists of a curved part and a straight part. Here we extend previous studies of this phase diagram. We identify subphases in the divergent phase, which can be distinguished by means of the shape of the density profile, and determine the velocity of the system length growth. This is done for EQPs with different update rules (parallel, backward sequential and continuous time). We also investigate the dynamics of the system length and the number of customers on the critical line. They are diffusive or subdiffusive with non-universal exponents that also depend on the update rules.
Decentralized Hypothesis Testing in Energy Harvesting Wireless Sensor Networks
NASA Astrophysics Data System (ADS)
Tarighati, Alla; Gross, James; Jalden, Joakim
2017-09-01
We consider the problem of decentralized hypothesis testing in a network of energy harvesting sensors, where sensors make noisy observations of a phenomenon and send quantized information about the phenomenon towards a fusion center. The fusion center makes a decision about the present hypothesis using the aggregate received data during a time interval. We explicitly consider a scenario under which the messages are sent through parallel access channels towards the fusion center. To avoid limited lifetime issues, we assume each sensor is capable of harvesting all the energy it needs for the communication from the environment. Each sensor has an energy buffer (battery) to save its harvested energy for use in other time intervals. Our key contribution is to formulate the problem of decentralized detection in a sensor network with energy harvesting devices. Our analysis is based on a queuing-theoretic model for the battery and we propose a sensor decision design method by considering long term energy management at the sensors. We show how the performance of the system changes for different battery capacities. We then numerically show how our findings can be used in the design of sensor networks with energy harvesting sensors.
Aviation security cargo inspection queuing simulation model for material flow and accountability
DOE Office of Scientific and Technical Information (OSTI.GOV)
Olama, Mohammed M; Allgood, Glenn O; Rose, Terri A
Beginning in 2010, the U.S. will require that all cargo loaded in passenger aircraft be inspected. This will require more efficient processing of cargo and will have a significant impact on the inspection protocols and business practices of government agencies and the airlines. In this paper, we develop an aviation security cargo inspection queuing simulation model for material flow and accountability that will allow cargo managers to conduct impact studies of current and proposed business practices as they relate to inspection procedures, material flow, and accountability.
NASA Astrophysics Data System (ADS)
Seyedhosseini, Seyed Mohammad; Makui, Ahmad; Shahanaghi, Kamran; Torkestani, Sara Sadat
2016-09-01
Determining the best location to be profitable for the facility's lifetime is the important decision of public and private firms, so this is why discussion about dynamic location problems (DLPs) is a critical significance. This paper presented a comprehensive review from 1968 up to most recent on published researches about DLPs and classified them into two parts. First, mathematical models developed based on different characteristics: type of parameters (deterministic, probabilistic or stochastic), number and type of objective function, numbers of commodity and modes, relocation time, number of relocation and relocating facilities, time horizon, budget and capacity constraints and their applicability. In second part, It have been also presented solution algorithms, main specification, applications and some real-world case studies of DLPs. At the ends, we concluded that in the current literature of DLPs, distribution systems and production-distribution systems with simple assumption of the tackle to the complexity of these models studied more than any other fields, as well as the concept of variety of services (hierarchical network), reliability, sustainability, relief management, waiting time for services (queuing theory) and risk of facility disruption need for further investigation. All of the available categories based on different criteria, solution methods and applicability of them, gaps and analysis which have been done in this paper suggest the ways for future research.
Stochastic switching in biology: from genotype to phenotype
NASA Astrophysics Data System (ADS)
Bressloff, Paul C.
2017-03-01
There has been a resurgence of interest in non-equilibrium stochastic processes in recent years, driven in part by the observation that the number of molecules (genes, mRNA, proteins) involved in gene expression are often of order 1-1000. This means that deterministic mass-action kinetics tends to break down, and one needs to take into account the discrete, stochastic nature of biochemical reactions. One of the major consequences of molecular noise is the occurrence of stochastic biological switching at both the genotypic and phenotypic levels. For example, individual gene regulatory networks can switch between graded and binary responses, exhibit translational/transcriptional bursting, and support metastability (noise-induced switching between states that are stable in the deterministic limit). If random switching persists at the phenotypic level then this can confer certain advantages to cell populations growing in a changing environment, as exemplified by bacterial persistence in response to antibiotics. Gene expression at the single-cell level can also be regulated by changes in cell density at the population level, a process known as quorum sensing. In contrast to noise-driven phenotypic switching, the switching mechanism in quorum sensing is stimulus-driven and thus noise tends to have a detrimental effect. A common approach to modeling stochastic gene expression is to assume a large but finite system and to approximate the discrete processes by continuous processes using a system-size expansion. However, there is a growing need to have some familiarity with the theory of stochastic processes that goes beyond the standard topics of chemical master equations, the system-size expansion, Langevin equations and the Fokker-Planck equation. Examples include stochastic hybrid systems (piecewise deterministic Markov processes), large deviations and the Wentzel-Kramers-Brillouin (WKB) method, adiabatic reductions, and queuing/renewal theory. The major aim of this review is to provide a self-contained survey of these mathematical methods, mainly within the context of biological switching processes at both the genotypic and phenotypic levels. However, applications to other examples of biological switching are also discussed, including stochastic ion channels, diffusion in randomly switching environments, bacterial chemotaxis, and stochastic neural networks.
Ruiz-Patiño, Alejandro; Acosta-Ospina, Laura Elena; Rueda, Juan-David
2017-04-01
Congestion in the postanesthesia care unit (PACU) leads to the formation of waiting queues for patients being transferred after surgery, negatively affecting hospital resources. As patients recover in the operating room, incoming surgeries are delayed. The purpose of this study was to establish the impact of this phenomenon in multiple settings. An operational mathematical study based on the queuing theory was performed. Average queue length, average queue waiting time, and daily queue waiting time were evaluated. Calculations were based on the mean patient daily flow, PACU length of stay, occupation, and current number of beds. Data was prospectively collected during a period of 2 months, and the entry and exit time was recorded for each patient taken to the PACU. Data was imputed in a computational model made with MS Excel. To account for data uncertainty, deterministic and probabilistic sensitivity analyses for all dependent variables were performed. With a mean patient daily flow of 40.3 and an average PACU length of stay of 4 hours, average total lost surgical opportunity time was estimated at 2.36 hours (95% CI: 0.36-4.74 hours). Cost of opportunity was calculated at $1592 per lost hour. Sensitivity analysis showed that an increase of two beds is required to solve the queue formation. When congestion has a negative impact on cost of opportunity in the surgical setting, queuing analysis grants definitive actions to solve the problem, improving quality of service and resource utilization. Copyright © 2016 Elsevier Inc. All rights reserved.
Priority Queuing on the Docket: Universality of Judicial Dispute Resolution Timing
NASA Astrophysics Data System (ADS)
Mukherjee, Satyam; Whalen, Ryan
2018-01-01
This paper analyzes court priority queuing behavior by examining the time lapse between when a case enters a court’s docket and when it is ultimately disposed of. Using data from the Supreme courts of the United States, Massachusetts, and Canada we show that each court’s docket features a slow decay with a decreasing tail. This demonstrates that, in each of the courts examined, the vast majority of cases are resolved relatively quickly, while there remains a small number of outlier cases that take an extremely long time to resolve. We discuss the implications for this on legal systems, the study of the law, and future research.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shorgin, Sergey Ya.; Pechinkin, Alexander V.; Samouylov, Konstantin E.
Cloud computing is promising technology to manage and improve utilization of computing center resources to deliver various computing and IT services. For the purpose of energy saving there is no need to unnecessarily operate many servers under light loads, and they are switched off. On the other hand, some servers should be switched on in heavy load cases to prevent very long delays. Thus, waiting times and system operating cost can be maintained on acceptable level by dynamically adding or removing servers. One more fact that should be taken into account is significant server setup costs and activation times. Formore » better energy efficiency, cloud computing system should not react on instantaneous increase or instantaneous decrease of load. That is the main motivation for using queuing systems with hysteresis for cloud computing system modelling. In the paper, we provide a model of cloud computing system in terms of multiple server threshold-based infinite capacity queuing system with hysteresis and noninstantanuous server activation. For proposed model, we develop a method for computing steady-state probabilities that allow to estimate a number of performance measures.« less
NASA Astrophysics Data System (ADS)
Strzałka, Dominik; Dymora, Paweł; Mazurek, Mirosław
2018-02-01
In this paper we present some preliminary results in the field of computer systems management with relation to Tsallis thermostatistics and the ubiquitous problem of hardware limited resources. In the case of systems with non-deterministic behaviour, management of their resources is a key point that guarantees theirs acceptable performance and proper working. This is very wide problem that stands for many challenges in financial, transport, water and food, health, etc. areas. We focus on computer systems with attention paid to cache memory and propose to use an analytical model that is able to connect non-extensive entropy formalism, long-range dependencies, management of system resources and queuing theory. Obtained analytical results are related to the practical experiment showing interesting and valuable results.
Modeling and simulation of queuing system for customer service improvement: A case study
NASA Astrophysics Data System (ADS)
Xian, Tan Chai; Hong, Chai Weng; Hawari, Nurul Nazihah
2016-10-01
This study aims to develop a queuing model at UniMall by using discrete event simulation approach in analyzing the service performance that affects customer satisfaction. The performance measures that considered in this model are such as the average time in system, the total number of student served, the number of student in waiting queue, the waiting time in queue as well as the maximum length of buffer. ARENA simulation software is used to develop a simulation model and the output is analyzed. Based on the analysis of output, it is recommended that management of UniMall consider introducing shifts and adding another payment counter in the morning.
NASA Astrophysics Data System (ADS)
Tamazian, A.; Nguyen, V. D.; Markelov, O. A.; Bogachev, M. I.
2016-07-01
We suggest a universal phenomenological description for the collective access patterns in the Internet traffic dynamics both at local and wide area network levels that takes into account erratic fluctuations imposed by cooperative user behaviour. Our description is based on the superstatistical approach and leads to the q-exponential inter-session time and session size distributions that are also in perfect agreement with empirical observations. The validity of the proposed description is confirmed explicitly by the analysis of complete 10-day traffic traces from the WIDE backbone link and from the local campus area network downlink from the Internet Service Provider. Remarkably, the same functional forms have been observed in the historic access patterns from single WWW servers. The suggested approach effectively accounts for the complex interplay of both “calm” and “bursty” user access patterns within a single-model setting. It also provides average sojourn time estimates with reasonable accuracy, as indicated by the queuing system performance simulation, this way largely overcoming the failure of Poisson modelling of the Internet traffic dynamics.
Social stability and helping in small animal societies
Field, Jeremy; Cant, Michael A.
2009-01-01
In primitively eusocial societies, all individuals can potentially reproduce independently. The key fact that we focus on in this paper is that individuals in such societies instead often queue to inherit breeding positions. Queuing leads to systematic differences in expected future fitness. We first discuss the implications this has for variation in behaviour. For example, because helpers nearer to the front of the queue have more to lose, they should work less hard to rear the dominant's offspring. However, higher rankers may be more aggressive than low rankers, even if they risk injury in the process, if aggression functions to maintain or enhance queue position. Second, we discuss how queuing rules may be enforced through hidden threats that rarely have to be carried out. In fishes, rule breakers face the threat of eviction from the group. In contrast, subordinate paper wasps are not injured or evicted during escalated challenges against the dominant, perhaps because they are more valuable to the dominant. We discuss evidence that paper-wasp dominants avoid escalated conflicts by ceding reproduction to subordinates. Queuing rules appear usually to be enforced by individuals adjacent in the queue rather than by dominants. Further manipulative studies are required to reveal mechanisms underlying queue stability and to elucidate what determines queue position in the first place. PMID:19805426
Priority Queuing Models for Hospital Intensive Care Units and Impacts to Severe Case Patients
Hagen, Matthew S.; Jopling, Jeffrey K; Buchman, Timothy G; Lee, Eva K.
2013-01-01
This paper examines several different queuing models for intensive care units (ICU) and the effects on wait times, utilization, return rates, mortalities, and number of patients served. Five separate intensive care units at an urban hospital are analyzed and distributions are fitted for arrivals and service durations. A system-based simulation model is built to capture all possible cases of patient flow after ICU admission. These include mortalities and returns before and after hospital exits. Patients are grouped into 9 different classes that are categorized by severity and length of stay (LOS). Each queuing model varies by the policies that are permitted and by the order the patients are admitted. The first set of models does not prioritize patients, but examines the advantages of smoothing the operating schedule for elective surgeries. The second set analyzes the differences between prioritizing admissions by expected LOS or patient severity. The last set permits early ICU discharges and conservative and aggressive bumping policies are contrasted. It was found that prioritizing patients by severity considerably reduced delays for critical cases, but also increased the average waiting time for all patients. Aggressive bumping significantly raised the return and mortality rates, but more conservative methods balance quality and efficiency with lowered wait times without serious consequences. PMID:24551379
An investigation of the impact of prolonged waiting times on blood donors in Ireland.
McKeever, T; Sweeney, M R; Staines, A
2006-02-01
The aim of this study was to investigate the impact of prolonged queuing times on blood donors, by measuring their satisfaction levels, and positive and negative affects. As donation times have increased over the past number of years within the Irish Blood Transfusion Service, this is an important issue to examine in a climate where voluntary donors are becoming scarce and demands on people's time are increasing. Eighty-five blood donors were sampled from one urban and one rural blood donor clinic. The respondents conducted a questionnaire by means of face-to-face interview, while waiting in the clinic. The questionnaire contained the Positive and Negative Affect Scale (PANAS), and a waiting satisfaction scale. Both actual and perceived waiting times of the donors were noted. Waiting time was found to be negatively related to satisfaction. Inexperienced donors expressed higher levels of negative affect than experienced donors. Urban donors were significantly more satisfied than rural donors. There was a significant difference in perceived waiting time between lone donors and those queuing in a group, with those waiting alone perceiving their wait as shorter. While all respondents stated that they intended to donate again, over one-third stated that prolonged waiting times would be their most likely deterrent. However, only 15% stated that long queuing times might actually prevent them from donating in the future, and almost all respondents said that they would recommend donation to a friend, despite long queuing times. Although our results show that the respondents were not satisfied with current waiting times, it did not seem to affect their future intentions to donate. These findings provide some optimism for the future of blood donation in Ireland, as they suggest a strong sense of commitment to donation within the population sampled. Future research could explore the application of 'the service industry' approach to waiting times to blood donation clinics.
Gateway-Assisted Retransmission for Lightweight and Reliable IoT Communications.
Chang, Hui-Ling; Wang, Cheng-Gang; Wu, Mong-Ting; Tsai, Meng-Hsun; Lin, Chia-Ying
2016-09-22
Message Queuing Telemetry Transport for Sensor Networks (MQTT-SN) and Constrained Application Protocol (CoAP) are two protocols supporting publish/subscribe models for IoT devices to publish messages to interested subscribers. Retransmission mechanisms are introduced to compensate for the lack of data reliability. If the device does not receive the acknowledgement (ACK) before retransmission timeout (RTO) expires, the device will retransmit data. Setting an appropriate RTO is important because the delay may be large or retransmission may be too frequent when the RTO is inappropriate. We propose a Gateway-assisted CoAP (GaCoAP) to dynamically compute RTO for devices. Simulation models are proposed to investigate the performance of GaCoAP compared with four other methods. The experiment results show that GaCoAP is more suitable for IoT devices.
Gateway-Assisted Retransmission for Lightweight and Reliable IoT Communications
Chang, Hui-Ling; Wang, Cheng-Gang; Wu, Mong-Ting; Tsai, Meng-Hsun; Lin, Chia-Ying
2016-01-01
Message Queuing Telemetry Transport for Sensor Networks (MQTT-SN) and Constrained Application Protocol (CoAP) are two protocols supporting publish/subscribe models for IoT devices to publish messages to interested subscribers. Retransmission mechanisms are introduced to compensate for the lack of data reliability. If the device does not receive the acknowledgement (ACK) before retransmission timeout (RTO) expires, the device will retransmit data. Setting an appropriate RTO is important because the delay may be large or retransmission may be too frequent when the RTO is inappropriate. We propose a Gateway-assisted CoAP (GaCoAP) to dynamically compute RTO for devices. Simulation models are proposed to investigate the performance of GaCoAP compared with four other methods. The experiment results show that GaCoAP is more suitable for IoT devices. PMID:27669243
Fleet Sizing of Automated Material Handling Using Simulation Approach
NASA Astrophysics Data System (ADS)
Wibisono, Radinal; Ai, The Jin; Ratna Yuniartha, Deny
2018-03-01
Automated material handling tends to be chosen rather than using human power in material handling activity for production floor in manufacturing company. One critical issue in implementing automated material handling is designing phase to ensure that material handling activity more efficient in term of cost spending. Fleet sizing become one of the topic in designing phase. In this research, simulation approach is being used to solve fleet sizing problem in flow shop production to ensure optimum situation. Optimum situation in this research means minimum flow time and maximum capacity in production floor. Simulation approach is being used because flow shop can be modelled into queuing network and inter-arrival time is not following exponential distribution. Therefore, contribution of this research is solving fleet sizing problem with multi objectives in flow shop production using simulation approach with ARENA Software
NASA Astrophysics Data System (ADS)
Impemba, Ernesto; Inzerilli, Tiziano
2003-07-01
Integration of satellite access networks with the Internet is seen as a strategic goal to achieve in order to provide ubiquitous broadband access to Internet services in Next Generation Networks (NGNs). One of the main interworking aspects which has been most studied is an efficient management of satellite resources, i.e. bandwidth and buffer space, in order to satisfy most demanding application requirements as to delay control and bandwidth assurance. In this context, resource management in DVB-S/DVB-RCS satellite technologies, emerging technologies for broadband satellite access and transport of IP applications, is a research issue largely investigated as a means to provide efficient bi-directional communications across satellites. This is in particular one of the principal goals of the SATIP6 project, sponsored within the 5th EU Research Programme Framework, i.e. IST. In this paper we present a possible approach to efficiently exploit bandwidth, the most critical resource in a broadband satellite access network, while pursuing satisfaction of delay and bandwidth requirements for applications with guaranteed QoS through a traffic control architecture to be implemented in ground terminals. Performance of this approach is assessed in terms of efficient exploitation of the uplink bandwidth and differentiation and minimization of queuing delays for most demanding applications over a time-varying capacity. Opnet simulations is used as analysis tool.
Job-mix modeling and system analysis of an aerospace multiprocessor.
NASA Technical Reports Server (NTRS)
Mallach, E. G.
1972-01-01
An aerospace guidance computer organization, consisting of multiple processors and memory units attached to a central time-multiplexed data bus, is described. A job mix for this type of computer is obtained by analysis of Apollo mission programs. Multiprocessor performance is then analyzed using: 1) queuing theory, under certain 'limiting case' assumptions; 2) Markov process methods; and 3) system simulation. Results of the analyses indicate: 1) Markov process analysis is a useful and efficient predictor of simulation results; 2) efficient job execution is not seriously impaired even when the system is so overloaded that new jobs are inordinately delayed in starting; 3) job scheduling is significant in determining system performance; and 4) a system having many slow processors may or may not perform better than a system of equal power having few fast processors, but will not perform significantly worse.
Developing a new stochastic competitive model regarding inventory and price
NASA Astrophysics Data System (ADS)
Rashid, Reza; Bozorgi-Amiri, Ali; Seyedhoseini, S. M.
2015-09-01
Within the competition in today's business environment, the design of supply chains becomes more complex than before. This paper deals with the retailer's location problem when customers choose their vendors, and inventory costs have been considered for retailers. In a competitive location problem, price and location of facilities affect demands of customers; consequently, simultaneous optimization of the location and inventory system is needed. To prepare a realistic model, demand and lead time have been assumed as stochastic parameters, and queuing theory has been used to develop a comprehensive mathematical model. Due to complexity of the problem, a branch and bound algorithm has been developed, and its performance has been validated in several numerical examples, which indicated effectiveness of the algorithm. Also, a real case has been prepared to demonstrate performance of the model for real world.
NASA Astrophysics Data System (ADS)
Tavakkoli-Moghaddam, Reza; Vazifeh-Noshafagh, Samira; Taleizadeh, Ata Allah; Hajipour, Vahid; Mahmoudi, Amin
2017-01-01
This article presents a new multi-objective model for a facility location problem with congestion and pricing policies. This model considers situations in which immobile service facilities are congested by a stochastic demand following M/M/m/k queues. The presented model belongs to the class of mixed-integer nonlinear programming models and NP-hard problems. To solve such a hard model, a new multi-objective optimization algorithm based on a vibration theory, namely multi-objective vibration damping optimization (MOVDO), is developed. In order to tune the algorithms parameters, the Taguchi approach using a response metric is implemented. The computational results are compared with those of the non-dominated ranking genetic algorithm and non-dominated sorting genetic algorithm. The outputs demonstrate the robustness of the proposed MOVDO in large-sized problems.
An agent-based model for queue formation of powered two-wheelers in heterogeneous traffic
NASA Astrophysics Data System (ADS)
Lee, Tzu-Chang; Wong, K. I.
2016-11-01
This paper presents an agent-based model (ABM) for simulating the queue formation of powered two-wheelers (PTWs) in heterogeneous traffic at a signalized intersection. The main novelty is that the proposed interaction rule describing the position choice behavior of PTWs when queuing in heterogeneous traffic can capture the stochastic nature of the decision making process. The interaction rule is formulated as a multinomial logit model, which is calibrated by using a microscopic traffic trajectory dataset obtained from video footage. The ABM is validated against the survey data for the vehicular trajectory patterns, queuing patterns, queue lengths, and discharge rates. The results demonstrate that the proposed model is capable of replicating the observed queue formation process for heterogeneous traffic.
Evaluation of Job Queuing/Scheduling Software: Phase I Report
NASA Technical Reports Server (NTRS)
Jones, James Patton
1996-01-01
The recent proliferation of high performance work stations and the increased reliability of parallel systems have illustrated the need for robust job management systems to support parallel applications. To address this issue, the national Aerodynamic Simulation (NAS) supercomputer facility compiled a requirements checklist for job queuing/scheduling software. Next, NAS began an evaluation of the leading job management system (JMS) software packages against the checklist. This report describes the three-phase evaluation process, and presents the results of Phase 1: Capabilities versus Requirements. We show that JMS support for running parallel applications on clusters of workstations and parallel systems is still insufficient, even in the leading JMS's. However, by ranking each JMS evaluated against the requirements, we provide data that will be useful to other sites in selecting a JMS.
A soft computing-based approach to optimise queuing-inventory control problem
NASA Astrophysics Data System (ADS)
Alaghebandha, Mohammad; Hajipour, Vahid
2015-04-01
In this paper, a multi-product continuous review inventory control problem within batch arrival queuing approach (MQr/M/1) is developed to find the optimal quantities of maximum inventory. The objective function is to minimise summation of ordering, holding and shortage costs under warehouse space, service level and expected lost-sales shortage cost constraints from retailer and warehouse viewpoints. Since the proposed model is Non-deterministic Polynomial-time hard, an efficient imperialist competitive algorithm (ICA) is proposed to solve the model. To justify proposed ICA, both ganetic algorithm and simulated annealing algorithm are utilised. In order to determine the best value of algorithm parameters that result in a better solution, a fine-tuning procedure is executed. Finally, the performance of the proposed ICA is analysed using some numerical illustrations.
Optimizing Resource Utilization in Grid Batch Systems
NASA Astrophysics Data System (ADS)
Gellrich, Andreas
2012-12-01
On Grid sites, the requirements of the computing tasks (jobs) to computing, storage, and network resources differ widely. For instance Monte Carlo production jobs are almost purely CPU-bound, whereas physics analysis jobs demand high data rates. In order to optimize the utilization of the compute node resources, jobs must be distributed intelligently over the nodes. Although the job resource requirements cannot be deduced directly, jobs are mapped to POSIX UID/GID according to the VO, VOMS group and role information contained in the VOMS proxy. The UID/GID then allows to distinguish jobs, if users are using VOMS proxies as planned by the VO management, e.g. ‘role=production’ for Monte Carlo jobs. It is possible to setup and configure batch systems (queuing system and scheduler) at Grid sites based on these considerations although scaling limits were observed with the scheduler MAUI. In tests these limitations could be overcome with a home-made scheduler.
A Computer Graphics Human Figure Application Of Biostereometrics
NASA Astrophysics Data System (ADS)
Fetter, William A.
1980-07-01
A study of improved computer graphic representation of the human figure is being conducted under a National Science Foundation grant. Special emphasis is given biostereometrics as a primary data base from which applications requiring a variety of levels of detail may be prepared. For example, a human figure represented by a single point can be very useful in overview plots of a population. A crude ten point figure can be adequate for queuing theory studies and simulated movement of groups. A one hundred point figure can usefully be animated to achieve different overall body activities including male and female figures. A one thousand point figure si-milarly animated, begins to be useful in anthropometrics and kinesiology gross body movements. Extrapolations of this order-of-magnitude approach ultimately should achieve very complex data bases and a program which automatically selects the correct level of detail for the task at hand. See Summary Figure 1.
Territory inheritance in clownfish.
Buston, Peter M
2004-01-01
Animal societies composed of breeders and non-breeders present a challenge to evolutionary theory because it is not immediately apparent how natural selection can preserve the genes that underlie non-breeding strategies. The clownfish Amphiprion percula forms groups composed of a breeding pair and 0-4 non-breeders. Non-breeders gain neither present direct, nor present indirect benefits from the association. To determine whether non-breeders obtain future direct benefits, I investigated the pattern of territory inheritance. I show that non-breeders stand to inherit the territory within which they reside. Moreover, they form a perfect queue for breeding positions; a queue from which nobody disperses and within which nobody contests. I suggest that queuing might be favoured by selection because it confers a higher probability of attaining breeding status than either dispersing or contesting. This study illustrates that, within animal societies, individuals may tolerate non-breeding positions solely because of their potential to realize benefits in the future. PMID:15252999
Territory inheritance in clownfish.
Buston, Peter M
2004-05-07
Animal societies composed of breeders and non-breeders present a challenge to evolutionary theory because it is not immediately apparent how natural selection can preserve the genes that underlie non-breeding strategies. The clownfish Amphiprion percula forms groups composed of a breeding pair and 0-4 non-breeders. Non-breeders gain neither present direct, nor present indirect benefits from the association. To determine whether non-breeders obtain future direct benefits, I investigated the pattern of territory inheritance. I show that non-breeders stand to inherit the territory within which they reside. Moreover, they form a perfect queue for breeding positions; a queue from which nobody disperses and within which nobody contests. I suggest that queuing might be favoured by selection because it confers a higher probability of attaining breeding status than either dispersing or contesting. This study illustrates that, within animal societies, individuals may tolerate non-breeding positions solely because of their potential to realize benefits in the future.
A framework for service enterprise workflow simulation with multi-agents cooperation
NASA Astrophysics Data System (ADS)
Tan, Wenan; Xu, Wei; Yang, Fujun; Xu, Lida; Jiang, Chuanqun
2013-11-01
Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.
Morrison, Abigail; Straube, Sirko; Plesser, Hans Ekkehard; Diesmann, Markus
2007-01-01
Very large networks of spiking neurons can be simulated efficiently in parallel under the constraint that spike times are bound to an equidistant time grid. Within this scheme, the subthreshold dynamics of a wide class of integrate-and-fire-type neuron models can be integrated exactly from one grid point to the next. However, the loss in accuracy caused by restricting spike times to the grid can have undesirable consequences, which has led to interest in interpolating spike times between the grid points to retrieve an adequate representation of network dynamics. We demonstrate that the exact integration scheme can be combined naturally with off-grid spike events found by interpolation. We show that by exploiting the existence of a minimal synaptic propagation delay, the need for a central event queue is removed, so that the precision of event-driven simulation on the level of single neurons is combined with the efficiency of time-driven global scheduling. Further, for neuron models with linear subthreshold dynamics, even local event queuing can be avoided, resulting in much greater efficiency on the single-neuron level. These ideas are exemplified by two implementations of a widely used neuron model. We present a measure for the efficiency of network simulations in terms of their integration error and show that for a wide range of input spike rates, the novel techniques we present are both more accurate and faster than standard techniques.
Performance Evaluation Model for Application Layer Firewalls.
Xuan, Shichang; Yang, Wu; Dong, Hui; Zhang, Jiangchuan
2016-01-01
Application layer firewalls protect the trusted area network against information security risks. However, firewall performance may affect user experience. Therefore, performance analysis plays a significant role in the evaluation of application layer firewalls. This paper presents an analytic model of the application layer firewall, based on a system analysis to evaluate the capability of the firewall. In order to enable users to improve the performance of the application layer firewall with limited resources, resource allocation was evaluated to obtain the optimal resource allocation scheme in terms of throughput, delay, and packet loss rate. The proposed model employs the Erlangian queuing model to analyze the performance parameters of the system with regard to the three layers (network, transport, and application layers). Then, the analysis results of all the layers are combined to obtain the overall system performance indicators. A discrete event simulation method was used to evaluate the proposed model. Finally, limited service desk resources were allocated to obtain the values of the performance indicators under different resource allocation scenarios in order to determine the optimal allocation scheme. Under limited resource allocation, this scheme enables users to maximize the performance of the application layer firewall.
Las Cumbres Observatory Global Telescope Network: Keeping Education in the Dark
NASA Astrophysics Data System (ADS)
Ross, Rachel J.
2007-12-01
Las Cumbres Observatory Global Telescope Network is a non-profit organization that is building a completely robotic network of telescopes for education (24 x 0.4m, clusters of 4) and science (18 x 1.0m, clusters of 3 and 2 x 2.0 meters) which will be longitudinally spaced so there will always be at least one cluster in the dark. The network will be completely accessible online with observations being completed in either real-time or queued-based modes. The network will also have the ability to complete very long observations of all kinds of variable objects and include a rapid response system will allow the telescopes to quickly slew to unexpected phenomena and provide around-the-clock monitoring. Students will be able to do research projects using and collecting data from both the long observations (e.g. extrasolar planet follow-up, variable star light curves, etc.) and the quick response (e.g. supernovae, GRBs, etc.), as well as use their own ideas to create personalized projects. Also available online will be a huge archive of data and the ability to use online software to process it. A large library of activities and resources will be available for all age groups and levels of science. LCOGTN will work cooperatively with international organizations to bring a vast amount of knowledge and experience together to create a world class program. Through these collaborations, pilots have already been started in a few European countries, as well as trial programs involving schools partnered between the USA and UK. LCOGTN's education network will provide an avenue for educators and learners to use cutting edge technology to do real science. All you need is a broadband internet connection, computer, and lots of enthusiasm and imagination.
Optimization of airport security lanes
NASA Astrophysics Data System (ADS)
Chen, Lin
2018-05-01
Current airport security management system is widely implemented all around the world to ensure the safety of passengers, but it might not be an optimum one. This paper aims to seek a better security system, which can maximize security while minimize inconvenience to passengers. Firstly, we apply Petri net model to analyze the steps where the main bottlenecks lie. Based on average tokens and time transition, the most time-consuming steps of security process can be found, including inspection of passengers' identification and documents, preparing belongings to be scanned and the process for retrieving belongings back. Then, we develop a queuing model to figure out factors affecting those time-consuming steps. As for future improvement, the effective measures which can be taken include transferring current system as single-queuing and multi-served, intelligently predicting the number of security checkpoints supposed to be opened, building up green biological convenient lanes. Furthermore, to test the theoretical results, we apply some data to stimulate the model. And the stimulation results are consistent with what we have got through modeling. Finally, we apply our queuing model to a multi-cultural background. The result suggests that by quantifying and modifying the variance in wait time, the model can be applied to individuals with various habits customs and habits. Generally speaking, our paper considers multiple affecting factors, employs several models and does plenty of calculations, which is practical and reliable for handling in reality. In addition, with more precise data available, we can further test and improve our models.
A Modern Operating System for Near-real-time Environmental Observatories
NASA Astrophysics Data System (ADS)
Orcutt, John; Vernon, Frank
2014-05-01
The NSF Ocean Observatory Initiative (OOI) provided an opportunity for expanding the capabilities for managing open, near-real-time (latencies of seconds) data from ocean observatories. The sensors deployed in this system largely return data from seafloor, cabled fiber optic cables as well as satellite telemetry. Bandwidth demands range from high-definition movies to the transmission of data via Iridium satellite. The extended Internet also provides an opportunity to not only return data, but to also control the sensors and platforms that comprise the observatory. The data themselves are openly available to any users. In order to provide heightened network security and overall reliability, the connections to and from the sensors/platforms are managed without Layer 3 of the Internet, but instead rely upon message passing using an open protocol termed Advanced Queuing Messaging Protocol (AMQP). The highest bandwidths in the system are in the Regional Scale Network (RSN) off Oregon and Washington and on the continent with highly reliable network connections between observatory components at 10 Gbps. The maintenance of metadata and life cycle histories of sensors and platforms is critical for providing data provenance over the years. The integrated cyberinfrastructure is best thought of as an operating system for the observatory - like the data, the software is also open and can be readily applied to new observatories, for example, in the rapidly evolving Arctic.
Queuing theory models used for port equipment sizing
NASA Astrophysics Data System (ADS)
Dragu, V.; Dinu, O.; Ruscă, A.; Burciu, Ş.; Roman, E. A.
2017-08-01
The significant growth of volumes and distances on road transportation led to the necessity of finding solutions to increase water transportation market share together with the handling and transfer technologies within its terminals. It is widely known that the biggest times are consumed within the transport terminals (loading/unloading/transfer) and so the necessity of constantly developing handling techniques and technologies in concordance with the goods flows size so that the total waiting time of ships within ports is reduced. Port development should be achieved by harmonizing the contradictory interests of port administration and users. Port administrators aim profit increase opposite to users that want savings by increasing consumers’ surplus. The difficulty consists in the fact that the transport demand - supply equilibrium must be realised at costs and goods quantities transiting the port in order to satisfy the interests of both parties involved. This paper presents a port equipment sizing model by using queueing theory so that the sum of costs for ships waiting operations and equipment usage would be minimum. Ship operation within the port is assimilated to a mass service waiting system in which parameters are later used to determine the main costs for ships and port equipment.
NASA Astrophysics Data System (ADS)
Wei, Pei; Gu, Rentao; Ji, Yuefeng
2014-06-01
As an innovative and promising technology, network coding has been introduced to passive optical networks (PON) in recent years to support inter optical network unit (ONU) communication, yet the signaling process and dynamic bandwidth allocation (DBA) in PON with network coding (NC-PON) still need further study. Thus, we propose a joint signaling and DBA scheme for efficiently supporting differentiated services of inter ONU communication in NC-PON. In the proposed joint scheme, the signaling process lays the foundation to fulfill network coding in PON, and it can not only avoid the potential threat to downstream security in previous schemes but also be suitable for the proposed hybrid dynamic bandwidth allocation (HDBA) scheme. In HDBA, a DBA cycle is divided into two sub-cycles for applying different coding, scheduling and bandwidth allocation strategies to differentiated classes of services. Besides, as network traffic load varies, the entire upstream transmission window for all REPORT messages slides accordingly, leaving the transmission time of one or two sub-cycles to overlap with the bandwidth allocation calculation time at the optical line terminal (the OLT), so that the upstream idle time can be efficiently eliminated. Performance evaluation results validate that compared with the existing two DBA algorithms deployed in NC-PON, HDBA demonstrates the best quality of service (QoS) support in terms of delay for all classes of services, especially guarantees the end-to-end delay bound of high class services. Specifically, HDBA can eliminate queuing delay and scheduling delay of high class services, reduce those of lower class services by at least 20%, and reduce the average end-to-end delay of all services over 50%. Moreover, HDBA also achieves the maximum delay fairness between coded and uncoded lower class services, and medium delay fairness for high class services.
The Northwest Indiana Robotic Telescope
NASA Astrophysics Data System (ADS)
Slavin, Shawn D.; Rengstorf, A. W.; Aros, J. C.; Segally, W. B.
2011-01-01
The Northwest Indiana Robotic (NIRo) Telescope is a remote, automated observing facility recently built by Purdue University Calumet (PUC) at a site in Lowell, IN, approximately 30 miles from the PUC campus. The recently dedicated observatory will be used for broadband and narrowband optical observations by PUC students and faculty, as well as pre-college students through the implementation of standards-based, middle-school modules developed by PUC astronomers and education faculty. The NIRo observatory and its web portal are the central technical elements of a project to improve astronomy education at Purdue Calumet and, more broadly, to improve science education in middle schools of the surrounding region. The NIRo Telescope is a 0.5-meter (20-inch) Ritchey-Chrétien design on a Paramount ME robotic mount, featuring a seven-position filter wheel (UBVRI, Hα, Clear), Peltier (thermoelectrically) cooled CCD camera with 3056 x 3056, square, 12 μm pixels, and off-axis guiding. It provides a coma-free imaging field of 0.5 degrees square, with a plate scale of 0.6 arcseconds per pixel. The observatory has a wireless internet connection, local weather station which publishes data to an internet weather site, and a suite of CCTV security cameras on an IP-based, networked video server. Control of power to every piece of instrumentation is maintained via internet-accessible power distribution units. The telescope can be controlled on-site, or off-site in an attended fashion via an internet connection, but will be used primarily in an unattended mode of automated observation, where queued observations will be scheduled daily from a database of requests. Completed observational data from queued operation will be stored on a campus-based server, which also runs the web portal and observation database. Partial support for this work was provided by the National Science Foundation's Course, Curriculum, and Laboratory Improvement (CCLI) program under Award No. 0736592.
Data-driven traffic impact assessment tool for work zones.
DOT National Transportation Integrated Search
2017-03-01
Traditionally, traffic impacts of work zones have been assessed using planning software such as Quick Zone, custom spreadsheets, and others. These software programs generate delay, queuing, and other mobility measures but are difficult to validate du...
Traffic flow characteristic and capacity in intelligent work zones.
DOT National Transportation Integrated Search
2009-10-15
Intellgent transportation system (ITS) technologies are utilized to manage traffic flow and safety in : highway work zones. Traffic management plans for work zones require queuing analyses to determine : the anticipated traffic backups, but the predi...
Job Scheduling Under the Portable Batch System
NASA Technical Reports Server (NTRS)
Henderson, Robert L.; Woodrow, Thomas S. (Technical Monitor)
1995-01-01
The typical batch queuing system schedules jobs for execution by a set of queue controls. The controls determine from which queues jobs may be selected. Within the queue, jobs are ordered first-in, first-run. This limits the set of scheduling policies available to a site. The Portable Batch System removes this limitation by providing an external scheduling module. This separate program has full knowledge of the available queued jobs, running jobs, and system resource usage. Sites are able to implement any policy expressible in one of several procedural language. Policies may range from "bet fit" to "fair share" to purely political. Scheduling decisions can be made over the full set of jobs regardless of queue or order. The scheduling policy can be changed to fit a wide variety of computing environments and scheduling goals. This is demonstrated by the use of PBS on an IBM SP-2 system at NASA Ames.
Virtual Queue in a Centralized Database Environment
NASA Astrophysics Data System (ADS)
Kar, Amitava; Pal, Dibyendu Kumar
2010-10-01
Today is the era of the Internet. Every matter whether it be a gather of knowledge or planning a holiday or booking of ticket etc everything can be obtained from the internet. This paper intends to calculate the different queuing measures when some booking or purchase is done through the internet subject to the limitations in the number of tickets or seats. It involves a lot of database activities like read and write. This paper takes care of the time involved in the requests of a service, taken as arrival and the time involved in providing the required information, taken as service and thereby tries to calculate the distribution of arrival and service and the various measures of the queuing. This paper considers the database as centralized database for the sake of simplicity as the alternating concept of distributed database would rather complicate the calculation.
Second Evaluation of Job Queuing/Scheduling Software. Phase 1
NASA Technical Reports Server (NTRS)
Jones, James Patton; Brickell, Cristy; Chancellor, Marisa (Technical Monitor)
1997-01-01
The recent proliferation of high performance workstations and the increased reliability of parallel systems have illustrated the need for robust job management systems to support parallel applications. To address this issue, NAS compiled a requirements checklist for job queuing/scheduling software. Next, NAS evaluated the leading job management system (JMS) software packages against the checklist. A year has now elapsed since the first comparison was published, and NAS has repeated the evaluation. This report describes this second evaluation, and presents the results of Phase 1: Capabilities versus Requirements. We show that JMS support for running parallel applications on clusters of workstations and parallel systems is still lacking, however, definite progress has been made by the vendors to correct the deficiencies. This report is supplemented by a WWW interface to the data collected, to aid other sites in extracting the evaluation information on specific requirements of interest.
Work-related symptoms and checkstand configuration: an experimental study.
Harber, P; Bloswick, D; Luo, J; Beck, J; Greer, D; Peña, L F
1993-07-01
Supermarket checkers are known to be at risk of upper-extremity cumulative trauma disorders. Forty-two experienced checkers checked a standard "market basket" of items on an experimental checkstand. The counter height could be adjusted (high = 35.5, low = 31.5 inches), and the pre-scan queuing area length (between conveyor belt and laser scanner) could be set to "near" or "far" lengths. Each subject scanned under the high-near, high-far, low-near, and low-far conditions in random order. Seven ordinal symptom scales were used to describe comfort. Analysis showed that both counter height and queuing length had significant effects on symptoms. Furthermore, the height of the subject affected the degree and direction of the impact of the checkstand configuration differences. The study suggests that optimization of design may be experimentally evaluated, that modification of postural as well as frequency loading may be beneficial, and that adjustability for the individual may be advisable.
Design of object-oriented distributed simulation classes
NASA Technical Reports Server (NTRS)
Schoeffler, James D. (Principal Investigator)
1995-01-01
Distributed simulation of aircraft engines as part of a computer aided design package is being developed by NASA Lewis Research Center for the aircraft industry. The project is called NPSS, an acronym for 'Numerical Propulsion Simulation System'. NPSS is a flexible object-oriented simulation of aircraft engines requiring high computing speed. It is desirable to run the simulation on a distributed computer system with multiple processors executing portions of the simulation in parallel. The purpose of this research was to investigate object-oriented structures such that individual objects could be distributed. The set of classes used in the simulation must be designed to facilitate parallel computation. Since the portions of the simulation carried out in parallel are not independent of one another, there is the need for communication among the parallel executing processors which in turn implies need for their synchronization. Communication and synchronization can lead to decreased throughput as parallel processors wait for data or synchronization signals from other processors. As a result of this research, the following have been accomplished. The design and implementation of a set of simulation classes which result in a distributed simulation control program have been completed. The design is based upon MIT 'Actor' model of a concurrent object and uses 'connectors' to structure dynamic connections between simulation components. Connectors may be dynamically created according to the distribution of objects among machines at execution time without any programming changes. Measurements of the basic performance have been carried out with the result that communication overhead of the distributed design is swamped by the computation time of modules unless modules have very short execution times per iteration or time step. An analytical performance model based upon queuing network theory has been designed and implemented. Its application to realistic configurations has not been carried out.
Design of Object-Oriented Distributed Simulation Classes
NASA Technical Reports Server (NTRS)
Schoeffler, James D.
1995-01-01
Distributed simulation of aircraft engines as part of a computer aided design package being developed by NASA Lewis Research Center for the aircraft industry. The project is called NPSS, an acronym for "Numerical Propulsion Simulation System". NPSS is a flexible object-oriented simulation of aircraft engines requiring high computing speed. It is desirable to run the simulation on a distributed computer system with multiple processors executing portions of the simulation in parallel. The purpose of this research was to investigate object-oriented structures such that individual objects could be distributed. The set of classes used in the simulation must be designed to facilitate parallel computation. Since the portions of the simulation carried out in parallel are not independent of one another, there is the need for communication among the parallel executing processors which in turn implies need for their synchronization. Communication and synchronization can lead to decreased throughput as parallel processors wait for data or synchronization signals from other processors. As a result of this research, the following have been accomplished. The design and implementation of a set of simulation classes which result in a distributed simulation control program have been completed. The design is based upon MIT "Actor" model of a concurrent object and uses "connectors" to structure dynamic connections between simulation components. Connectors may be dynamically created according to the distribution of objects among machines at execution time without any programming changes. Measurements of the basic performance have been carried out with the result that communication overhead of the distributed design is swamped by the computation time of modules unless modules have very short execution times per iteration or time step. An analytical performance model based upon queuing network theory has been designed and implemented. Its application to realistic configurations has not been carried out.
Use of an administrative data set to determine optimal scheduling of an alcohol intervention worker.
Peterson, Timothy A; Desmond, Jeffrey S; Cunningham, Rebecca
2012-06-01
Brief alcohol interventions are efficacious in reducing alcohol-related consequences among emergency department (ED) patients. Use of non-clinical staff may increase alcohol screening and intervention; however, optimal scheduling of an alcohol intervention worker (AIW) is unknown. Determine optimal scheduling of an AIW based on peak discharge time of alcohol-related ED visits. Discharge times for consecutive patients with an alcohol-related diagnosis were abstracted from an urban ED's administrative data set from September 2005 through August 2007. Queuing theory was used to identify optimal scheduling. Data for weekends and weekdays were analyzed separately. Stationary independent period-by-period analysis was performed for hourly periods. An M/M/s queuing model, for Markovian inter-arrival time/Markovian service time/and potentially more than one server, was developed for each hour assuming: 1) a single unlimited queue; 2) 75% of patients waited no longer than 30 min for intervention; 3) AIW spent an average 20 min/patient. Estimated average utilization/hour was calculated; if utilization/hour exceeded 25%, AIW staff was considered necessary. There were 2282 patient visits (mean age 38 years, range 11-84 years). Weekdays accounted for 45% of visits; weekends 55%. On weekdays, one AIW from 6:00 a.m.-9:00 a.m. (max utilization 42%/hour) would accommodate 28% of weekday alcohol-related patients. On weekends, 5:00 a.m.-11:00 a.m. (max utilization 50%), one AIW would cover 54% of all weekend alcohol-related visits. During other hours the utilization rate falls below 25%/hour. Evaluating 2 years of discharge data revealed that 30 h of dedicated AIW time--18 weekend hours (5:00 a.m.-11:00 a.m.), 12 weekday hours (6:00 a.m.-9:00 a.m.)--would allow maximal patient alcohol screening and intervention with minimal additional burden to clinical staff. Copyright © 2012 Elsevier Inc. All rights reserved.
Simple Models for Airport Delays During Transition to a Trajectory-Based Air Traffic System
NASA Astrophysics Data System (ADS)
Brooker, Peter
It is now widely recognised that a paradigm shift in air traffic control concepts is needed. This requires state-of-the-art innovative technologies, making much better use of the information in the air traffic management (ATM) system. These paradigm shifts go under the names of NextGen in the USA and SESAR in Europe, which inter alia will make dramatic changes to the nature of airport operations. A vital part of moving from an existing system to a new paradigm is the operational implications of the transition process. There would be business incentives for early aircraft fitment, it is generally safer to introduce new technologies gradually, and researchers are already proposing potential transition steps to the new system. Simple queuing theory models are used to establish rough quantitative estimates of the impact of the transition to a more efficient time-based navigational and ATM system. Such models are approximate, but they do offer insight into the broad implications of system change and its significant features. 4D-equipped aircraft in essence have a contract with the airport runway and, in return, they would get priority over any other aircraft waiting for use of the runway. The main operational feature examined here is the queuing delays affecting non-4D-equipped arrivals. These get a reasonable service if the proportion of 4D-equipped aircraft is low, but this can deteriorate markedly for high proportions, and be economically unviable. Preventative measures would be to limit the additional growth of 4D-equipped flights and/or to modify their contracts to provide sufficient space for the non-4D-equipped flights to operate without excessive delays. There is a potential for non-Poisson models, for which there is little in the literature, and for more complex models, e.g. grouping a succession of 4D-equipped aircraft as a batch.
A Cellular Neural Networks Based DiffServ Switch for Satellite Communication Systems
NASA Astrophysics Data System (ADS)
Tarchi, Daniele; Fantacci, Romano; Gubellini, Roberto; Pecorella, Tommaso
2003-07-01
Recent developments of Internet services and advanced compression methods has revived interest on IP based multimedia satellite communication systems. However a main problem arising here is to guarantee specific Quality of Service (QoS) constraints in order to have good performance for each traffic class.Among various QoS approach used in Internet, recently the DiffServ technique has became the most promising so- lution, mainly for its simplicity with respect to different alternatives. Moreover, in satellite communication systems, DiffServ policy computational capabilities are placed at the edge points (end-to-end philosophy); this is very important for a network constituted by one satellite link because it allows to reduce the implementation complexity of the satellite on-board equipments.The satellite switch under consideration makes use of the Multiple Input Queuing approach. Packets arrived at a switch input are stored in a shared buffer but they are logically ordered in individual queues, one for each possible output link. According to the DiffServ policy, within a same logical queue, packets are reordered in individual sub-queues according to the priority. A suitable implementation of the DiffServ policy based on a Cellular Neural Network (CNN) is proposed in the paper in order to achieve QoS requirements.The CNNs are a set of linear and nonlinear circuits connected among them that allow parallel and asynchronous computation. CNNs are a class of neural networks similar to Hopfield Neural Networks (HNN), but more flexible and suitable for solving the output contention problem, inherent of switching systems, for VLSI implementation.In this paper a CNN has been designed in order to maximize a cost functional, related to the on-board switch through- put and QoS constraints. The initial state for each neural cell is obtained looking at the presence of at least one packet from a certain input logical queue to a specific output line. The input value for each neural cell is a function of priority and length of each input logical queue. The versatility of neural network make feasible to take the best decision for the packet to be delivered to each output satellite beam, in order to meet specific QoS constraints. Numerical results for CNN approach highlights that Neural network convergence within a time slot is guaranteed, and an optimal, or at least near-optimal, solution in terms of cost function is achieved.The proposed system is based on the IETF (Internet Engineering Task Force) recommendations; this means that traffic entering the switching fabric could be marked as Expedited Forward (EF) or Assured Forward (AF), otherwise handled as Best Effort (BE). Two Assured Forward classes with different emission priority have been implemented, taking into account time spent inside the logical queue and its length. Expedited Forward traffic is typical of services to be delivered with the maximum priority, as streaming or interactive services. The packets, belonging to services that need a certain level of priority with low packet loss, are marked as Assured Forward. Best Effort traffic is related to e-mail or file transfer, or other that have not particular QoS requirements. The CNN used to solve conflict situations act as an arbiter for all the output links. Differently from other Multiple Input Queuing approach, where one arbiter for each output line is present, in proposed approach there exist only one arbiter that make the best decision. The selected rule has been defined in order to give priority to packets, according to opportunely defined functionals characteristic of each traffic class, under the constraint that no more than one packet can be delivered to the same output line. The functionals depend on queue length and time spent inside the queue by front packet.The performance of the proposed DiffServ switch has been derived in terms of delay and jitter; buffer occupancy has been analyzed for different configuration, such as a unique common buffer, one buffer for each input line, one buffer for each input line and each priority class.The obtained results highlight an high flexibility of satellite switch with CNN, taking into account that functional used to calculate priority of each queue could be easily changed, without any complexity gain nor change in CNN structure, in order to consider different traffic characteristic. Numerical results show that proposed algorithm outperform the switches based on Multiple Input Queuing, that use strictly priority methods, in terms of delay and jitter. Different buffer size have been also considered in order to analyze packet loss for CNN switch algorithm, comparing different configuration described above.The good behavior of the proposed DiffServ switch has been verified in the case of traffic with pareto distribution for packet length and a geometrical distribution for packet interarrival time, highlighting good performance in terms of delay and jitter. Numerical results also demonstrate the stability of this method for heavy load traffic; in particular maximum permitted load is higher for higher priority classes.
Emergence of bursts and communities in evolving weighted networks.
Jo, Hang-Hyun; Pan, Raj Kumar; Kaski, Kimmo
2011-01-01
Understanding the patterns of human dynamics and social interaction and the way they lead to the formation of an organized and functional society are important issues especially for techno-social development. Addressing these issues of social networks has recently become possible through large scale data analysis of mobile phone call records, which has revealed the existence of modular or community structure with many links between nodes of the same community and relatively few links between nodes of different communities. The weights of links, e.g., the number of calls between two users, and the network topology are found correlated such that intra-community links are stronger compared to the weak inter-community links. This feature is known as Granovetter's "The strength of weak ties" hypothesis. In addition to this inhomogeneous community structure, the temporal patterns of human dynamics turn out to be inhomogeneous or bursty, characterized by the heavy tailed distribution of time interval between two consecutive events, i.e., inter-event time. In this paper, we study how the community structure and the bursty dynamics emerge together in a simple evolving weighted network model. The principal mechanisms behind these patterns are social interaction by cyclic closure, i.e., links to friends of friends and the focal closure, links to individuals sharing similar attributes or interests, and human dynamics by task handling process. These three mechanisms have been implemented as a network model with local attachment, global attachment, and priority-based queuing processes. By comprehensive numerical simulations we show that the interplay of these mechanisms leads to the emergence of heavy tailed inter-event time distribution and the evolution of Granovetter-type community structure. Moreover, the numerical results are found to be in qualitative agreement with empirical analysis results from mobile phone call dataset.
Optimizing a Drone Network to Deliver Automated External Defibrillators.
Boutilier, Justin J; Brooks, Steven C; Janmohamed, Alyf; Byers, Adam; Buick, Jason E; Zhan, Cathy; Schoellig, Angela P; Cheskes, Sheldon; Morrison, Laurie J; Chan, Timothy C Y
2017-06-20
Public access defibrillation programs can improve survival after out-of-hospital cardiac arrest, but automated external defibrillators (AEDs) are rarely available for bystander use at the scene. Drones are an emerging technology that can deliver an AED to the scene of an out-of-hospital cardiac arrest for bystander use. We hypothesize that a drone network designed with the aid of a mathematical model combining both optimization and queuing can reduce the time to AED arrival. We applied our model to 53 702 out-of-hospital cardiac arrests that occurred in the 8 regions of the Toronto Regional RescuNET between January 1, 2006, and December 31, 2014. Our primary analysis quantified the drone network size required to deliver an AED 1, 2, or 3 minutes faster than historical median 911 response times for each region independently. A secondary analysis quantified the reduction in drone resources required if RescuNET was treated as a large coordinated region. The region-specific analysis determined that 81 bases and 100 drones would be required to deliver an AED ahead of median 911 response times by 3 minutes. In the most urban region, the 90th percentile of the AED arrival time was reduced by 6 minutes and 43 seconds relative to historical 911 response times in the region. In the most rural region, the 90th percentile was reduced by 10 minutes and 34 seconds. A single coordinated drone network across all regions required 39.5% fewer bases and 30.0% fewer drones to achieve similar AED delivery times. An optimized drone network designed with the aid of a novel mathematical model can substantially reduce the AED delivery time to an out-of-hospital cardiac arrest event. © 2017 American Heart Association, Inc.
Advance traffic control warning systems for maintenance operations : final report.
DOT National Transportation Integrated Search
1976-07-01
The report discusses the effect of certain variables defined by sign size, height of installation and legend on the driver responses as measured by speed, conflict and queuing parameters. Effects of electronically actuated, directional flashing signs...
Real-Time Operating System/360
NASA Technical Reports Server (NTRS)
Hoffman, R. L.; Kopp, R. S.; Mueller, H. H.; Pollan, W. D.; Van Sant, B. W.; Weiler, P. W.
1969-01-01
RTOS has a cost savings advantage for real-time applications, such as those with random inputs requiring a flexible data routing facility, display systems simplified by a device independent interface language, and complex applications needing added storage protection and data queuing.
NASA Astrophysics Data System (ADS)
Ahmad, Afandi; Roslan, Muhammad Faris; Amira, Abbes
2017-09-01
In high jump sports, approach take-off speed and force during the take-off are two (2) main important parts to gain maximum jump. To measure both parameters, wireless sensor network (WSN) that contains microcontroller and sensor are needed to describe the results of speed and force for jumpers. Most of the microcontroller exhibit transmission issues in terms of throughput, latency and cost. Thus, this study presents the comparison of wireless microcontrollers in terms of throughput, latency and cost, and the microcontroller that have best performances and cost will be implemented in high jump wearable device. In the experiments, three (3) parts have been integrated - input, process and output. Force (for ankle) and global positioning system (GPS) sensor (for body waist) acts as an input for data transmission. These data were then being processed by both microcontrollers, ESP8266 and Arduino Yun Mini to transmit the data from sensors to the server (host-PC) via message queuing telemetry transport (MQTT) protocol. The server acts as receiver and the results was calculated from the MQTT log files. At the end, results obtained have shown ESP8266 microcontroller had been chosen since it achieved high throughput, low latency and 11 times cheaper in term of prices compared to Arduino Yun Mini microcontroller.
Evaluation of Scheduling Methods for Multiple Runways
NASA Technical Reports Server (NTRS)
Bolender, Michael A.; Slater, G. L.
1996-01-01
Several scheduling strategies are analyzed in order to determine the most efficient means of scheduling aircraft when multiple runways are operational and the airport is operating at different utilization rates. The study compares simulation data for two and three runway scenarios to results from queuing theory for an M/D/n queue. The direction taken, however, is not to do a steady-state, or equilibrium, analysis since this is not the case during a rush period at a typical airport. Instead, a transient analysis of the delay per aircraft is performed. It is shown that the scheduling strategy that reduces the delay depends upon the density of the arrival traffic. For light traffic, scheduling aircraft to their preferred runways is sufficient; however, as the arrival rate increases, it becomes more important to separate traffic by weight class. Significant delay reduction is realized when aircraft that belong to the heavy and small weight classes are sent to separate runways with large aircraft put into the 'best' landing slot.
Performance modeling for large database systems
NASA Astrophysics Data System (ADS)
Schaar, Stephen; Hum, Frank; Romano, Joe
1997-02-01
One of the unique approaches Science Applications International Corporation took to meet performance requirements was to start the modeling effort during the proposal phase of the Interstate Identification Index/Federal Bureau of Investigations (III/FBI) project. The III/FBI Performance Model uses analytical modeling techniques to represent the III/FBI system. Inputs to the model include workloads for each transaction type, record size for each record type, number of records for each file, hardware envelope characteristics, engineering margins and estimates for software instructions, memory, and I/O for each transaction type. The model uses queuing theory to calculate the average transaction queue length. The model calculates a response time and the resources needed for each transaction type. Outputs of the model include the total resources needed for the system, a hardware configuration, and projected inherent and operational availability. The III/FBI Performance Model is used to evaluate what-if scenarios and allows a rapid response to engineering change proposals and technical enhancements.
NASA Astrophysics Data System (ADS)
Ismail, Zurina; Shokor, Shahrul Suhaimi AB
2016-03-01
Rapid life time change of the Malaysian lifestyle had served the overwhelming growth in the service operation industry. On that occasion, this paper will provide the idea to improve the waiting line system (WLS) practices in Malaysia fast food chains. The study will compare the results in between the single server single phase (SSSP) and the single server multi-phase (SSMP) which providing Markovian Queuing (MQ) to be used for analysis. The new system will improve the current WLS, plus intensifying the organization performance. This new WLS were designed and tested in a real case scenario and in order to develop and implemented the new styles, it need to be focusing on the average number of customers (ANC), average number of customer spending time waiting in line (ACS), and the average time customers spend in waiting and being served (ABS). We introduced new WLS design and there will be prompt discussion upon theories of benefits and potential issues that will benefit other researchers.
L&D Manual Turn Lane Storage Validation/Update : Executive Summary Report
DOT National Transportation Integrated Search
2012-08-01
The formation of queues on a highway facility is a sign of the presence of operationally : inefficient sections of the facility. Queuing occurs at intersections in large part due to overflow : or inadequacy of turn bays, inadequate capacity, or poor ...
Standfield, L; Comans, T; Raymer, M; O'Leary, S; Moretto, N; Scuffham, P
2016-08-01
Hospital outpatient orthopaedic services traditionally rely on medical specialists to assess all new patients to determine appropriate care. This has resulted in significant delays in service provision. In response, Orthopaedic Physiotherapy Screening Clinics and Multidisciplinary Services (OPSC) have been introduced to assess and co-ordinate care for semi- and non-urgent patients. To compare the efficiency of delivering increased semi- and non-urgent orthopaedic outpatient services through: (1) additional OPSC services; (2) additional traditional orthopaedic medical services with added surgical resources (TOMS + Surg); or (3) additional TOMS without added surgical resources (TOMS - Surg). A cost-utility analysis using discrete event simulation (DES) with dynamic queuing (DQ) was used to predict the cost effectiveness, throughput, queuing times, and resource utilisation, associated with introducing additional OPSC or TOMS ± Surg versus usual care. The introduction of additional OPSC or TOMS (±surgery) would be considered cost effective in Australia. However, OPSC was the most cost-effective option. Increasing the capacity of current OPSC services is an efficient way to improve patient throughput and waiting times without exceeding current surgical resources. An OPSC capacity increase of ~100 patients per month appears cost effective (A$8546 per quality-adjusted life-year) and results in a high level of OPSC utilisation (98 %). Increasing OPSC capacity to manage semi- and non-urgent patients would be cost effective, improve throughput, and reduce waiting times without exceeding current surgical resources. Unlike Markov cohort modelling, microsimulation, or DES without DQ, employing DES-DQ in situations where capacity constraints predominate provides valuable additional information beyond cost effectiveness to guide resource allocation decisions.
L&D Manual Turn Lane Storage Validation/Update
DOT National Transportation Integrated Search
2012-08-01
Queuing occurs at intersections mostly due to overflow or inadequacy of turn bays. The ODOT L&D : Manual Volume 1 has storage requirements for both signalized and unsignalized intersections. Figures : 401-9E and 401-10E of the L&D Manual provide the ...
Spectrally queued feature selection for robotic visual odometery
NASA Astrophysics Data System (ADS)
Pirozzo, David M.; Frederick, Philip A.; Hunt, Shawn; Theisen, Bernard; Del Rose, Mike
2011-01-01
Over the last two decades, research in Unmanned Vehicles (UV) has rapidly progressed and become more influenced by the field of biological sciences. Researchers have been investigating mechanical aspects of varying species to improve UV air and ground intrinsic mobility, they have been exploring the computational aspects of the brain for the development of pattern recognition and decision algorithms and they have been exploring perception capabilities of numerous animals and insects. This paper describes a 3 month exploratory applied research effort performed at the US ARMY Research, Development and Engineering Command's (RDECOM) Tank Automotive Research, Development and Engineering Center (TARDEC) in the area of biologically inspired spectrally augmented feature selection for robotic visual odometry. The motivation for this applied research was to develop a feasibility analysis on multi-spectrally queued feature selection, with improved temporal stability, for the purposes of visual odometry. The intended application is future semi-autonomous Unmanned Ground Vehicle (UGV) control as the richness of data sets required to enable human like behavior in these systems has yet to be defined.
NASA Astrophysics Data System (ADS)
Motaghedi-Larijani, Arash; Aminnayeri, Majid
2017-03-01
Cross-docking is a supply-chain strategy that can reduce transportation and inventory costs. This study is motivated by a fruit and vegetable distribution centre in Tehran, which has cross-docks and a limited time to admit outbound trucks. In this article, outbound trucks are assumed to arrive at the cross-dock with a single outbound door with a uniform distribution (0,L). The total number of assigned trucks is constant and the loading time is fixed. A queuing model is modified for this situation and the expected waiting time of each customer is calculated. Then, a curve for the waiting time is calculated. Finally, the length of window time L is optimized to minimize the total cost, which includes the waiting time of the trucks and the admission cost of the cross-dock. Some illustrative examples of cross-docking are presented and solved using the proposed method.
The Queued Service Observing Project at CFHT
NASA Astrophysics Data System (ADS)
Martin, Pierre; Savalle, Renaud; Vermeulen, Tom; Shapiro, Joshua N.
2002-12-01
In order to maximize the scientific productivity of the CFH12K mosaic wide-field imager (and soon MegaCam), the Queued Service Observing (QSO) mode was implemented at the Canada-France-Hawaii Telescope at the beginning of 2001. The QSO system consists of an ensemble of software components allowing for the submission of programs, the preparation of queues, and finally the execution and evaluation of observations. The QSO project is part of a broader system known as the New Observing Process (NOP). This system includes data acquisition, data reduction and analysis through a pipeline named Elixir, and a data archiving and distribution component (DADS). In this paper, we review several technical and operational aspects of the QSO project. In particular, we present our strategy, technical architecture, program submission system, and the tools developed for the preparation and execution of the queues. Our successful experience of over 150 nights of QSO operations is also discussed along with the future plans for queue observing with MegaCam and other instruments at CFHT.
Real-Time Multimission Event Notification System for Mars Relay
NASA Technical Reports Server (NTRS)
Wallick, Michael N.; Allard, Daniel A.; Gladden, Roy E.; Wang, Paul; Hy, Franklin H.
2013-01-01
As the Mars Relay Network is in constant flux (missions and teams going through their daily workflow), it is imperative that users are aware of such state changes. For example, a change by an orbiter team can affect operations on a lander team. This software provides an ambient view of the real-time status of the Mars network. The Mars Relay Operations Service (MaROS) comprises a number of tools to coordinate, plan, and visualize various aspects of the Mars Relay Network. As part of MaROS, a feature set was developed that operates on several levels of the software architecture. These levels include a Web-based user interface, a back-end "ReSTlet" built in Java, and databases that store the data as it is received from the network. The result is a real-time event notification and management system, so mission teams can track and act upon events on a moment-by-moment basis. This software retrieves events from MaROS and displays them to the end user. Updates happen in real time, i.e., messages are pushed to the user while logged into the system, and queued when the user is not online for later viewing. The software does not do away with the email notifications, but augments them with in-line notifications. Further, this software expands the events that can generate a notification, and allows user-generated notifications. Existing software sends a smaller subset of mission-generated notifications via email. A common complaint of users was that the system-generated e-mails often "get lost" with other e-mail that comes in. This software allows for an expanded set (including user-generated) of notifications displayed in-line of the program. By separating notifications, this can improve a user's workflow.
TIME SHARING WITH AN EXPLICIT PRIORITY QUEUING DISCIPLINE.
exponentially distributed service times and an ordered priority queue. Each new arrival buys a position in this queue by offering a non-negative bribe to the...parameters is investigated through numerical examples. Finally, to maximize the expected revenue per unit time accruing from bribes , an optimization
Integrating Reservations and Queuing in Remote Laboratory Scheduling
ERIC Educational Resources Information Center
Lowe, D.
2013-01-01
Remote laboratories (RLs) have become increasingly seen as a useful tool in supporting flexible shared access to scarce laboratory resources. An important element in supporting shared access is coordinating the scheduling of the laboratory usage. Optimized scheduling can significantly decrease access waiting times and improve the utilization level…
Targeting LSD1 Epigenetic Signature in Castration-Recurrent Prostate Cancer
2014-10-01
Sequencing libraries have been prepared and samples are currently queued at the Genomic Core facility at Roswell Park and results will be available...results to various meetings and seminars at Roswell Park, allowing me to get useful feedback from both clinicians and researchers. Furthermore, a brief
Minimizing the Delay at Traffic Lights
ERIC Educational Resources Information Center
Van Hecke, Tanja
2009-01-01
Vehicles holding at traffic lights is a typical queuing problem. At crossings the vehicles experience delay in both directions. Longer periods with green lights in one direction are disadvantageous for the vehicles coming from the other direction. The total delay for getting through the traffic point is what counts. This article presents an…
Implementation of the Automated Numerical Model Performance Metrics System
2011-09-26
question. As of this writing, the DSRC IBM AIX machines DaVinci and Pascal, and the Cray XT Einstein all use the PBS batch queuing system for...3.3). 12 Appendix A – General Automation System This system provides general purpose tools and a general way to automatically run
Phenomena of drag reduction on saltating sediment in shallow, supercritical flows
USDA-ARS?s Scientific Manuscript database
ABSTRACT: When a group of objects move through a fluid, it often exhibits coordinated behavior in which bodies in the wake of a leader generally experience reduced drag. Locomotion provides well known examples including the maneuvering and clustering of racing automobiles and bicyclists and queuing...
NASA Astrophysics Data System (ADS)
Aulenbach, S. M.; Berukoff, S. J.
2010-12-01
The National Ecological Observatory Network (NEON) will collect data across the United States on the impacts of climate change, land use change and invasive species on ecosystem functions and biodiversity. In-situ sampling and distributed sensor networks, linked by an advanced cyberinfrastructure, will collect site-based data on a variety of organisms, soils, aquatic systems, atmosphere and climate. Targeted airborne remote sensing observations made by NEON as well as geographical data sets and satellite resources produced by Federal agencies will provide data at regional and national scales. The resulting data streams, collected over a 30-year period, will be synthesized into fully traceable information products that are freely and openly accessible to all users. We provide an overview of several collection, access and presentation technologies evaluated for use by observatory systems throughout the data product life cycle. Specifically, we discuss smart phone applications for citizen scientists as well as the use of handheld devices for sample collection and reporting from the field. Protocols for storing, queuing, and retrieving data from observatory sites located throughout the nation are highlighted as are the application of standards throughout the pipelined production of data products. We discuss the automated incorporation of provenance information and digital object identifiers for published data products. The use of widgets and personalized user portals for the discovery and dissemination of NEON data products are also presented.
Interdisciplinary and physics challenges of network theory
NASA Astrophysics Data System (ADS)
Bianconi, Ginestra
2015-09-01
Network theory has unveiled the underlying structure of complex systems such as the Internet or the biological networks in the cell. It has identified universal properties of complex networks, and the interplay between their structure and dynamics. After almost twenty years of the field, new challenges lie ahead. These challenges concern the multilayer structure of most of the networks, the formulation of a network geometry and topology, and the development of a quantum theory of networks. Making progress on these aspects of network theory can open new venues to address interdisciplinary and physics challenges including progress on brain dynamics, new insights into quantum technologies, and quantum gravity.
Application of Game Theory Approaches in Routing Protocols for Wireless Networks
NASA Astrophysics Data System (ADS)
Javidi, Mohammad M.; Aliahmadipour, Laya
2011-09-01
An important and essential issue for wireless networks is routing protocol design that is a major technical challenge due to the function of the network. Game theory is a powerful mathematical tool that analyzes the strategic interactions among multiple decision makers and the results of researches show that applied game theory in routing protocol lead to improvement the network performance through reduce overhead and motivates selfish nodes to collaborate in the network. This paper presents a review and comparison for typical representatives of routing protocols designed that applied game theory approaches for various wireless networks such as ad hoc networks, mobile ad hoc networks and sensor networks that all of them lead to improve the network performance.
Dynamic resource allocation scheme for distributed heterogeneous computer systems
NASA Technical Reports Server (NTRS)
Liu, Howard T. (Inventor); Silvester, John A. (Inventor)
1991-01-01
This invention relates to a resource allocation in computer systems, and more particularly, to a method and associated apparatus for shortening response time and improving efficiency of a heterogeneous distributed networked computer system by reallocating the jobs queued up for busy nodes to idle, or less-busy nodes. In accordance with the algorithm (SIDA for short), the load-sharing is initiated by the server device in a manner such that extra overhead in not imposed on the system during heavily-loaded conditions. The algorithm employed in the present invention uses a dual-mode, server-initiated approach. Jobs are transferred from heavily burdened nodes (i.e., over a high threshold limit) to low burdened nodes at the initiation of the receiving node when: (1) a job finishes at a node which is burdened below a pre-established threshold level, or (2) a node is idle for a period of time as established by a wakeup timer at the node. The invention uses a combination of the local queue length and the local service rate ratio at each node as the workload indicator.
Service Management Database for DSN Equipment
NASA Technical Reports Server (NTRS)
Zendejas, Silvino; Bui, Tung; Bui, Bach; Malhotra, Shantanu; Chen, Fannie; Wolgast, Paul; Allen, Christopher; Luong, Ivy; Chang, George; Sadaqathulla, Syed
2009-01-01
This data- and event-driven persistent storage system leverages the use of commercial software provided by Oracle for portability, ease of maintenance, scalability, and ease of integration with embedded, client-server, and multi-tiered applications. In this role, the Service Management Database (SMDB) is a key component of the overall end-to-end process involved in the scheduling, preparation, and configuration of the Deep Space Network (DSN) equipment needed to perform the various telecommunication services the DSN provides to its customers worldwide. SMDB makes efficient use of triggers, stored procedures, queuing functions, e-mail capabilities, data management, and Java integration features provided by the Oracle relational database management system. SMDB uses a third normal form schema design that allows for simple data maintenance procedures and thin layers of integration with client applications. The software provides an integrated event logging system with ability to publish events to a JMS messaging system for synchronous and asynchronous delivery to subscribed applications. It provides a structured classification of events and application-level messages stored in database tables that are accessible by monitoring applications for real-time monitoring or for troubleshooting and analysis over historical archives.
Wake Vortex Advisory System (WakeVAS) Evaluation of Impacts on the National Airspace System
NASA Technical Reports Server (NTRS)
Smith, Jeremy C.; Dollyhigh, Samuel M.
2005-01-01
This report is one of a series that describes an ongoing effort in high-fidelity modeling/simulation, evaluation and analysis of the benefits and performance metrics of the Wake Vortex Advisory System (WakeVAS) Concept of Operations being developed as part of the Virtual Airspace Modeling and Simulation (VAMS) project. A previous study, determined the overall increases in runway arrival rates that could be achieved at 12 selected airports due to WakeVAS reduced aircraft spacing under Instrument Meteorological Conditions. This study builds on the previous work to evaluate the NAS wide impacts of equipping various numbers of airports with WakeVAS. A queuing network model of the National Airspace System, built by the Logistics Management Institute, Mclean, VA, for NASA (LMINET) was used to estimate the reduction in delay that could be achieved by using WakeVAS under non-visual meteorological conditions for the projected air traffic demand in 2010. The results from LMINET were used to estimate the total annual delay reduction that could be achieved and from this, an estimate of the air carrier variable operating cost saving was made.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-08-01
... following methods: A. http://www.regulations.gov . Follow the on-line instructions for submitting comments... the equipment is in good working order, if necessary as part of the inspection; (6) idling of a... off school property during queuing for the sequential discharge or pickup of students where the...
Hoflund, A Bryce
2013-01-01
This paper describes how grounded theory was used to investigate the "black box" of network leadership in the creation of the National Quality Forum. Scholars are beginning to recognize the importance of network organizations and are in the embryonic stages of collecting and analyzing data about network leadership processes. Grounded theory, with its focus on deriving theory from empirical data, offers researchers a distinctive way of studying little-known phenomena and is therefore well suited to exploring network leadership processes. Specifically, this paper provides an overview of grounded theory, a discussion of the appropriateness of grounded theory to investigating network phenomena, a description of how the research was conducted, and a discussion of the limitations and lessons learned from using this approach.
A new task scheduling algorithm based on value and time for cloud platform
NASA Astrophysics Data System (ADS)
Kuang, Ling; Zhang, Lichen
2017-08-01
Tasks scheduling, a key part of increasing resource utilization and enhancing system performance, is a never outdated problem especially in cloud platforms. Based on the value density algorithm of the real-time task scheduling system and the character of the distributed system, the paper present a new task scheduling algorithm by further studying the cloud technology and the real-time system: Least Level Value Density First (LLVDF). The algorithm not only introduces some attributes of time and value for tasks, it also can describe weighting relationships between these properties mathematically. As this feature of the algorithm, it can gain some advantages to distinguish between different tasks more dynamically and more reasonably. When the scheme was used in the priority calculation of the dynamic task scheduling on cloud platform, relying on its advantage, it can schedule and distinguish tasks with large amounts and many kinds more efficiently. The paper designs some experiments, some distributed server simulation models based on M/M/C model of queuing theory and negative arrivals, to compare the algorithm against traditional algorithm to observe and show its characters and advantages.
Leveraging human decision making through the optimal management of centralized resources
NASA Astrophysics Data System (ADS)
Hyden, Paul; McGrath, Richard G.
2016-05-01
Combining results from mixed integer optimization, stochastic modeling and queuing theory, we will advance the interdisciplinary problem of efficiently and effectively allocating centrally managed resources. Academia currently fails to address this, as the esoteric demands of each of these large research areas limits work across traditional boundaries. The commercial space does not currently address these challenges due to the absence of a profit metric. By constructing algorithms that explicitly use inputs across boundaries, we are able to incorporate the advantages of using human decision makers. Key improvements in the underlying algorithms are made possible by aligning decision maker goals with the feedback loops introduced between the core optimization step and the modeling of the overall stochastic process of supply and demand. A key observation is that human decision-makers must be explicitly included in the analysis for these approaches to be ultimately successful. Transformative access gives warfighters and mission owners greater understanding of global needs and allows for relationships to guide optimal resource allocation decisions. Mastery of demand processes and optimization bottlenecks reveals long term maximum marginal utility gaps in capabilities.
Duda, Catherine; Rajaram, Kumar; Barz, Christiane; Rosenthal, J Thomas
2013-01-01
There has been an increasing emphasis on health care efficiency and costs and on improving quality in health care settings such as hospitals or clinics. However, there has not been sufficient work on methods of improving access and customer service times in health care settings. The study develops a framework for improving access and customer service time for health care settings. In the framework, the operational concept of the bottleneck is synthesized with queuing theory to improve access and reduce customer service times without reduction in clinical quality. The framework is applied at the Ronald Reagan UCLA Medical Center to determine the drivers for access and customer service times and then provides guidelines on how to improve these drivers. Validation using simulation techniques shows significant potential for reducing customer service times and increasing access at this institution. Finally, the study provides several practice implications that could be used to improve access and customer service times without reduction in clinical quality across a range of health care settings from large hospitals to small community clinics.
Saloma, Caesar; Perez, Gay Jane; Gavile, Catherine Ann; Ick-Joson, Jacqueline Judith; Palmes-Saloma, Cynthia
2015-01-01
We study the impact of prior individual training during group emergency evacuation using mice that escape from an enclosed water pool to a dry platform via any of two possible exits. Experimenting with mice avoids serious ethical and legal issues that arise when dealing with unwitting human participants while minimizing concerns regarding the reliability of results obtained from simulated experiments using ‘actors’. First, mice were trained separately and their individual escape times measured over several trials. Mice learned quickly to swim towards an exit–they achieved their fastest escape times within the first four trials. The trained mice were then placed together in the pool and allowed to escape. No two mice were permitted in the pool beforehand and only one could pass through an exit opening at any given time. At first trial, groups of trained mice escaped seven and five times faster than their corresponding control groups of untrained mice at pool occupancy rate ρ of 11.9% and 4%, respectively. Faster evacuation happened because trained mice: (a) had better recognition of the available pool space and took shorter escape routes to an exit, (b) were less likely to form arches that blocked an exit opening, and (c) utilized the two exits efficiently without preference. Trained groups achieved continuous egress without an apparent leader-coordinator (self-organized queuing)—a collective behavior not experienced during individual training. Queuing was unobserved in untrained groups where mice were prone to wall seeking, aimless swimming and/or blind copying that produced circuitous escape routes, biased exit use and clogging. The experiments also reveal that faster and less costly group training at ρ = 4%, yielded an average individual escape time that is comparable with individualized training. However, group training in a more crowded pool (ρ = 11.9%) produced a longer average individual escape time. PMID:25693170
Modeling bursts and heavy tails in human dynamics
NASA Astrophysics Data System (ADS)
Vázquez, Alexei; Oliveira, João Gama; Dezsö, Zoltán; Goh, Kwang-Il; Kondor, Imre; Barabási, Albert-László
2006-03-01
The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. Here we provide direct evidence that for five human activity patterns, such as email and letter based communications, web browsing, library visits and stock trading, the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. We show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experiencing very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. We discuss two queuing models that capture human activity. The first model assumes that there are no limitations on the number of tasks an individual can hadle at any time, predicting that the waiting time of the individual tasks follow a heavy tailed distribution P(τw)˜τw-α with α=3/2 . The second model imposes limitations on the queue length, resulting in a heavy tailed waiting time distribution characterized by α=1 . We provide empirical evidence supporting the relevance of these two models to human activity patterns, showing that while emails, web browsing and library visitation display α=1 , the surface mail based communication belongs to the α=3/2 universality class. Finally, we discuss possible extension of the proposed queuing models and outline some future challenges in exploring the statistical mechanics of human dynamics.
Fairness in the coronary angiography queue.
Alter, D A; Basinski, A S; Cohen, E A; Naylor, C D
1999-10-05
Since waiting lists for coronary angiography are generally managed without explicit queuing criteria, patients may not receive priority on the basis of clinical acuity. The objective of this study was to examine clinical and nonclinical determinants of the length of time patients wait for coronary angiography. In this single-centre prospective cohort study conducted in the autumn of 1997, 357 consecutive patients were followed from initial triage until a coronary angiography was performed or an adverse cardiac event occurred. The referring physicians' hospital affiliation (physicians at Sunnybrook & Women's College Health Sciences Centre, those who practice at another centre but perform angiography at Sunnybrook and those with no previous association with Sunnybrook) was used to compare processes of care. A clinical urgency rating scale was used to assign a recommended maximum waiting time (RMWT) to each patient retrospectively, but this was not used in the queuing process. RMWTs and actual waiting times for patients in the 3 referral groups were compared; the influence clinical and nonclinical variables had on the actual length of time patients waited for coronary angiography was assessed; and possible predictors of adverse events were examined. Of 357 patients referred to Sunnybrook, 22 (6.2%) experienced adverse events while in the queue. Among those who remained, 308 (91.9%) were in need of coronary angiography; 201 (60.0%) of those patients received one within the RMWT. The length of time to angiography was influenced by clinical characteristics similar to those specified on the urgency rating scale, leading to a moderate agreement between actual waiting times and RMWTs (kappa = 0.53). However, physician affiliation was a highly significant (p < 0.001) and independent predictor of waiting time. Whereas 45.6% of the variation in waiting time was explained by all clinical factors combined, 9.3% of the variation was explained by physician affiliation alone. Informal queuing practices for coronary angiography do reflect clinical acuity, but they are also influenced by nonclinical factors, such as the nature of the physicians' association with the catheterization facility.
Modeling bursts and heavy tails in human dynamics.
Vázquez, Alexei; Oliveira, João Gama; Dezsö, Zoltán; Goh, Kwang-Il; Kondor, Imre; Barabási, Albert-László
2006-03-01
The dynamics of many social, technological and economic phenomena are driven by individual human actions, turning the quantitative understanding of human behavior into a central question of modern science. Current models of human dynamics, used from risk assessment to communications, assume that human actions are randomly distributed in time and thus well approximated by Poisson processes. Here we provide direct evidence that for five human activity patterns, such as email and letter based communications, web browsing, library visits and stock trading, the timing of individual human actions follow non-Poisson statistics, characterized by bursts of rapidly occurring events separated by long periods of inactivity. We show that the bursty nature of human behavior is a consequence of a decision based queuing process: when individuals execute tasks based on some perceived priority, the timing of the tasks will be heavy tailed, most tasks being rapidly executed, while a few experiencing very long waiting times. In contrast, priority blind execution is well approximated by uniform interevent statistics. We discuss two queuing models that capture human activity. The first model assumes that there are no limitations on the number of tasks an individual can handle at any time, predicting that the waiting time of the individual tasks follow a heavy tailed distribution P(tau(w)) approximately tau(w)(-alpha) with alpha=3/2. The second model imposes limitations on the queue length, resulting in a heavy tailed waiting time distribution characterized by alpha=1. We provide empirical evidence supporting the relevance of these two models to human activity patterns, showing that while emails, web browsing and library visitation display alpha=1, the surface mail based communication belongs to the alpha=3/2 universality class. Finally, we discuss possible extension of the proposed queuing models and outline some future challenges in exploring the statistical mechanics of human dynamics.
Nonlinear adaptive networks: A little theory, a few applications
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jones, R.D.; Qian, S.; Barnes, C.W.
1990-01-01
We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We than present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series tidal prediction in Venice Lagoon, sonar transient detection, control of nonlinear processes, balancing a double inverted pendulum and design advice for free electron lasers. 26 refs., 23 figs.
'people queued for hours to see him'.
Carlisle, Daloni
2012-05-30
I met Khalil Dale (pictured) in 1995 when writing about the International Committee of the Red Cross (ICRC) campaign to end the use of landmines. I spent a week alongside him, reporting on his work for the ICRC in northern Afghanistan. Khalil was a gentle, quiet man who left a big impression on everyone who met him.
Development and Analysis of Models for Handling the Refrigerated Containerized Cargoes
NASA Astrophysics Data System (ADS)
Nyrkov, A.; Pavlova, L.; Nikiforov, V.; Sokolov, S.; Budnik, V.
2017-07-01
This paper considers the open multi-channel queuing system, which receives irregular homogeneous or heterogeneous applications with an unlimited flow of standby time. The system is regarded as an example of a container terminal, having conditionally functional sections with a certain duty cycle, which receives an irregular, non-uniform flow of vessels with the resultant intensity.
NASA Astrophysics Data System (ADS)
Patti, Andrew; Tan, Wai-tian; Shen, Bo
2007-09-01
Streaming video in consumer homes over wireless IEEE 802.11 networks is becoming commonplace. Wireless 802.11 networks pose unique difficulties for streaming high definition (HD), low latency video due to their error-prone physical layer and media access procedures which were not designed for real-time traffic. HD video streaming, even with sophisticated H.264 encoding, is particularly challenging due to the large number of packet fragments per slice. Cross-layer design strategies have been proposed to address the issues of video streaming over 802.11. These designs increase streaming robustness by imposing some degree of monitoring and control over 802.11 parameters from application level, or by making the 802.11 layer media-aware. Important contributions are made, but none of the existing approaches directly take the 802.11 queuing into account. In this paper we take a different approach and propose a cross-layer design allowing direct, expedient control over the wireless packet queue, while obtaining timely feedback on transmission status for each packet in a media flow. This method can be fully implemented on a media sender with no explicit support or changes required to the media client. We assume that due to congestion or deteriorating signal-to-noise levels, the available throughput may drop substantially for extended periods of time, and thus propose video source adaptation methods that allow matching the bit-rate to available throughput. A particular H.264 slice encoding is presented to enable seamless stream switching between streams at multiple bit-rates, and we explore using new computationally efficient transcoding methods when only a high bit-rate stream is available.
Finding influential nodes for integration in brain networks using optimal percolation theory.
Del Ferraro, Gino; Moreno, Andrea; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C; Holodny, Andrei; Canals, Santiago; Makse, Hernán A
2018-06-11
Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.
Network anomaly detection system with optimized DS evidence theory.
Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu
2014-01-01
Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network-complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each sensor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly.
Unified-theory-of-reinforcement neural networks do not simulate the blocking effect.
Calvin, Nicholas T; J McDowell, J
2015-11-01
For the last 20 years the unified theory of reinforcement (Donahoe et al., 1993) has been used to develop computer simulations to evaluate its plausibility as an account for behavior. The unified theory of reinforcement states that operant and respondent learning occurs via the same neural mechanisms. As part of a larger project to evaluate the operant behavior predicted by the theory, this project was the first replication of neural network models based on the unified theory of reinforcement. In the process of replicating these neural network models it became apparent that a previously published finding, namely, that the networks simulate the blocking phenomenon (Donahoe et al., 1993), was a misinterpretation of the data. We show that the apparent blocking produced by these networks is an artifact of the inability of these networks to generate the same conditioned response to multiple stimuli. The piecemeal approach to evaluate the unified theory of reinforcement via simulation is critiqued and alternatives are discussed. Copyright © 2015 Elsevier B.V. All rights reserved.
Beam queuing for aeronautical free space optical networks
NASA Astrophysics Data System (ADS)
Karras, Kimon; Marinos, Dimitris; Kouros, Pavlos
2010-08-01
Free space optical technologies are currently only very marginally used in aviation, particularly for communication purposes. Most applications occur in a military environment, with civilian aviation remaining oblivious to its advantages. One of these is high-bandwidth communication between the various actors available in an aeronautical network. Considerable research is underway in order to resolve a multitude of issues like reliable reception and transmission of the optical signal and the construction of high performance, small and lightweight terminals for the optical transceiver. The slow Pointing, Acquisition and Tracking of the latter represents a significant issue, which detracts from their usability in such an environment. Since an aircraft may carry only a limited number of such terminals on board, the delay of a terminal in reacquiring a target (which is in the order of several seconds) constitutes a significant hurdle in achieving satisfactory connectivity. This paper proposes an optimization technique, in which packet are reordered dynamically before transmission in the sender node in order to minimize terminal movement and thus avoid the time-consuming PAT process. Several parameters are considered such as QoS of the packets, minimization of the number of movements of the terminal and of the distance it must traverse when it reacquires a target. The algorithm was tested by integrating it into a custom built, discrete event SystemC simulator. The results verify that incorporating into such a system yields tangible benefits in terms of the practical throughput achieved by the system through the minimization of idle time, while moving.
Brain and Cognitive Reserve: Translation via Network Control Theory
Medaglia, John Dominic; Pasqualetti, Fabio; Hamilton, Roy H.; Thompson-Schill, Sharon L.; Bassett, Danielle S.
2017-01-01
Traditional approaches to understanding the brain’s resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive “reserve,” associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity in the human brain. We describe the theoretical opportunities offered by the application of network control theory at the level of the human connectome to understand cognitive resilience and inform translational intervention. PMID:28104411
Affirmative Action Case Queued Up for Airing at High Court
ERIC Educational Resources Information Center
Walsh, Mark
2012-01-01
The future of affirmative action in education--not just for colleges but potentially for K-12 schools as well--may be on the line when the U.S. Supreme Court takes up a race-conscious admissions plan from the University of Texas next month. That seems apparent to the scores of education groups that have lined up behind the university with…
Occupational Feminization and Pay: Assessing Causal Dynamics Using 1950-2000 U.S. Census Data
ERIC Educational Resources Information Center
Levanon, Asaf; England, Paula; Allison, Paul
2009-01-01
Occupations with a greater share of females pay less than those with a lower share, controlling for education and skill. This association is explained by two dominant views: devaluation and queuing. The former views the pay offered in an occupation to affect its female proportion, due to employers' preference for men--a gendered labor queue. The…
Modelling Pedestrian Travel Time and the Design of Facilities: A Queuing Approach
Rahman, Khalidur; Abdul Ghani, Noraida; Abdulbasah Kamil, Anton; Mustafa, Adli; Kabir Chowdhury, Md. Ahmed
2013-01-01
Pedestrian movements are the consequence of several complex and stochastic facts. The modelling of pedestrian movements and the ability to predict the travel time are useful for evaluating the performance of a pedestrian facility. However, only a few studies can be found that incorporate the design of the facility, local pedestrian body dimensions, the delay experienced by the pedestrians, and level of service to the pedestrian movements. In this paper, a queuing based analytical model is developed as a function of relevant determinants and functional factors to predict the travel time on pedestrian facilities. The model can be used to assess the overall serving rate or performance of a facility layout and correlate it to the level of service that is possible to provide the pedestrians. It has also the ability to provide a clear suggestion on the designing and sizing of pedestrian facilities. The model is empirically validated and is found to be a robust tool to understand how well a particular walking facility makes possible comfort and convenient pedestrian movements. The sensitivity analysis is also performed to see the impact of some crucial parameters of the developed model on the performance of pedestrian facilities. PMID:23691055
Advances in the Theory of Complex Networks
NASA Astrophysics Data System (ADS)
Peruani, Fernando
An exhaustive and comprehensive review on the theory of complex networks would imply nowadays a titanic task, and it would result in a lengthy work containing plenty of technical details of arguable relevance. Instead, this chapter addresses very briefly the ABC of complex network theory, visiting only the hallmarks of the theoretical founding, to finally focus on two of the most interesting and promising current research problems: the study of dynamical processes on transportation networks and the identification of communities in complex networks.
Network Anomaly Detection System with Optimized DS Evidence Theory
Liu, Yuan; Wang, Xiaofeng; Liu, Kaiyu
2014-01-01
Network anomaly detection has been focused on by more people with the fast development of computer network. Some researchers utilized fusion method and DS evidence theory to do network anomaly detection but with low performance, and they did not consider features of network—complicated and varied. To achieve high detection rate, we present a novel network anomaly detection system with optimized Dempster-Shafer evidence theory (ODS) and regression basic probability assignment (RBPA) function. In this model, we add weights for each senor to optimize DS evidence theory according to its previous predict accuracy. And RBPA employs sensor's regression ability to address complex network. By four kinds of experiments, we find that our novel network anomaly detection model has a better detection rate, and RBPA as well as ODS optimization methods can improve system performance significantly. PMID:25254258
Intra- Versus Intersex Aggression: Testing Theories of Sex Differences Using Aggression Networks.
Wölfer, Ralf; Hewstone, Miles
2015-08-01
Two theories offer competing explanations of sex differences in aggressive behavior: sexual-selection theory and social-role theory. While each theory has specific strengths and limitations depending on the victim's sex, research hardly differentiates between intrasex and intersex aggression. In the present study, 11,307 students (mean age = 14.96 years; 50% girls, 50% boys) from 597 school classes provided social-network data (aggression and friendship networks) as well as physical (body mass index) and psychosocial (gender and masculinity norms) information. Aggression networks were used to disentangle intra- and intersex aggression, whereas their class-aggregated sex differences were analyzed using contextual predictors derived from sexual-selection and social-role theories. As expected, results revealed that sexual-selection theory predicted male-biased sex differences in intrasex aggression, whereas social-role theory predicted male-biased sex differences in intersex aggression. Findings suggest the value of explaining sex differences separately for intra- and intersex aggression with a dual-theory framework covering both evolutionary and normative components. © The Author(s) 2015.
Games network and application to PAs system.
Chettaoui, C; Delaplace, F; Manceny, M; Malo, M
2007-02-01
In this article, we present a game theory based framework, named games network, for modeling biological interactions. After introducing the theory, we more precisely describe the methodology to model biological interactions. Then we apply it to the plasminogen activator system (PAs) which is a signal transduction pathway involved in cancer cell migration. The games network theory extends game theory by including the locality of interactions. Each game in a games network represents local interactions between biological agents. The PAs system is implicated in cytoskeleton modifications via regulation of actin and microtubules, which in turn favors cell migration. The games network model has enabled us a better understanding of the regulation involved in the PAs system.
Short Cuts and Extended Techniques: Rethinking Relations between Technology and Educational Theory
ERIC Educational Resources Information Center
Thumlert, Kurt; de Castell, Suzanne; Jenson, Jennifer
2015-01-01
Building upon a recent call to renew actor-network theory (ANT) for educational research, this article reconsiders relations between technology and educational theory. Taking cues from actor-network theorists, this discussion considers the technologically-mediated networks in which learning actors are situated, acted upon, and acting, and traces…
How Might Better Network Theories Support School Leadership Research?
ERIC Educational Resources Information Center
Hadfield, Mark; Jopling, Michael
2012-01-01
This article explores how recent research in education has applied different aspects of "network" theory to the study of school leadership. Constructs from different network theories are often used because of their perceived potential to clarify two perennial issues in leadership research. The first is the relative importance of formal and…
Proof of Concept in Disrupted Tactical Networking
2017-09-01
because of the risk of detection. In this study , we design projectile-based mesh networking prototypes as one potential type of short-living network...to communicate because of the risk of detection. In this study , we design projectile-based mesh networking prototypes as one potential type of short...reader with a background in systems-theory. This study is designed using systems theory and uses systems theory as a lens through which to observe
Up the ANTe: Understanding Entrepreneurial Leadership Learning through Actor-Network Theory
ERIC Educational Resources Information Center
Smith, Sue; Kempster, Steve; Barnes, Stewart
2017-01-01
This article explores the role of educators in supporting the development of entrepreneurial leadership learning by creating peer learning networks of owner-managers of small businesses. Using actor-network theory, the authors think through the process of constructing and maintaining a peer learning network (conceived of as an actor-network) and…
Prediction and control of chaotic processes using nonlinear adaptive networks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jones, R.D.; Barnes, C.W.; Flake, G.W.
1990-01-01
We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We then present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series, tidal prediction in Venice lagoon, finite differencing, sonar transient detection, control of nonlinear processes, control of a negative ion source, balancing a double inverted pendulum and design advice for free electron lasers and laser fusion targets.
Automated observatory in Antarctica: real-time data transfer on constrained networks in practice
NASA Astrophysics Data System (ADS)
Bracke, Stephan; Gonsette, Alexandre; Rasson, Jean; Poncelet, Antoine; Hendrickx, Olivier
2017-08-01
In 2013 a project was started by the geophysical centre in Dourbes to install a fully automated magnetic observatory in Antarctica. This isolated place comes with specific requirements: unmanned station during 6 months, low temperatures with extreme values down to -50 °C, minimum power consumption and satellite bandwidth limited to 56 Kbit s-1. The ultimate aim is to transfer real-time magnetic data every second: vector data from a LEMI-25 vector magnetometer, absolute F measurements from a GEM Systems scalar proton magnetometer and absolute magnetic inclination-declination (DI) measurements (five times a day) with an automated DI-fluxgate magnetometer. Traditional file transfer protocols (for instance File Transfer Protocol (FTP), email, rsync) show severe limitations when it comes to real-time capability. After evaluation of pro and cons of the available real-time Internet of things (IoT) protocols and seismic software solutions, we chose to use Message Queuing Telemetry Transport (MQTT) and receive the 1 s data with a negligible latency cost and no loss of data. Each individual instrument sends the magnetic data immediately after capturing, and the data arrive approximately 300 ms after being sent, which corresponds with the normal satellite latency.
Optical burst switching for the next generation Optical Internet
NASA Astrophysics Data System (ADS)
Yoo, Myungsik
2000-11-01
In recent years, Internet Protocol (IP) over Wavelength Division Multiplexing (WDM) networks for the next generation Internet (or the so-called Optical Internet) have received enormous attention. There are two main drivers for an Optical Internet. One is the explosion of Internet traffic, which seems to keep growing exponentially. The other driver is the rapid advance in the WDM optical networking technology. In this study, key issues in the optical (WDM) layer will be investigated. As a novel switching paradigm for Optical Internet, Optical Burst Switching (OBS) is discussed. By leveraging the attractive properties of optical communications and at the same time, taking into account its limitations, OBS can combine the best of optical circuit-switching and packet/cell switching. The general concept of JET-based OBS protocol is described, including offset time and delayed reservation. In the next generation Optical Internet, one must address how to support Quality of Service (QoS) at the WDM layer since current IP provides only best effort services. The offset-time- based QoS scheme is proposed as a way of supporting QoS at the WDM layer. Unlike existing QoS schemes, offset- time-based QoS scheme does not mandate the use of buffer to differentiate services. For the bufferless WDM switch, the performance of offset- time-based QoS scheme is evaluated in term of blocking probability. In addition, the extra offset time required for class isolation is quantified and the theoretical bounds on blocking probability are analyzed. The offset-time-based scheme is applied to WDM switch with limited fiber delay line (FDL) buffer. We evaluate the effect of having a FDL buffer on the QoS performance of the offset-time-based scheme in terms of the loss probability and queuing delay of bursts. Finally, in order to dimension the network resources in Optical Internet backbone networks, the performance of the offset-time-based QoS scheme is evaluated for the multi-hop case. In particular, we consider very high performance Backbone Network Service (vBNS) backbone network. Various policies such as drop, retransmission, deflection routing and buffering are considered for performance evaluation. The performance results obtained under these policies are compared to decide the most efficient policy for the WDM backbone network.
Thinking on building the network cardiovasology of Chinese medicine.
Yu, Gui; Wang, Jie
2012-11-01
With advances in complex network theory, the thinking and methods regarding complex systems have changed revolutionarily. Network biology and network pharmacology were built by applying network-based approaches in biomedical research. The cardiovascular system may be regarded as a complex network, and cardiovascular diseases may be taken as the damage of structure and function of the cardiovascular network. Although Chinese medicine (CM) is effective in treating cardiovascular diseases, its mechanisms are still unclear. With the guidance of complex network theory, network biology and network pharmacology, network-based approaches could be used in the study of CM in preventing and treating cardiovascular diseases. A new discipline-network cardiovasology of CM was, therefore, developed. In this paper, complex network theory, network biology and network pharmacology were introduced and the connotation of "disease-syndrome-formula-herb" was illustrated from the network angle. Network biology could be used to analyze cardiovascular diseases and syndromes and network pharmacology could be used to analyze CM formulas and herbs. The "network-network"-based approaches could provide a new view for elucidating the mechanisms of CM treatment.
Can Cultural Worldviews Influence Network Composition?
ERIC Educational Resources Information Center
Vaisey, Stephen; Lizardo, Omar
2010-01-01
Most sociological research assumes that social network composition shapes individual beliefs. Network theory and research has not adequately considered that internalized cultural worldviews might affect network composition. Drawing on a synthetic, dual-process theory of culture and two waves of nationally-representative panel data, this article…
It is the Theory Which Decides What We Can Observe (Einstein)
NASA Astrophysics Data System (ADS)
Filk, Thomas
In this chapter I will give examples for three types of contextuality: theory as context, a theory of measurement as context, and environmental and internal conditions as context. In particular, I will argue that depending on which theory of measurements we attribute to Bohmian mechanics, this theory may be called a classical theory or a quantum theory. Furthermore, I will show that for neural networks one can define in a natural way two different theories of measurements which can be compared with scanner-type measurements on the one hand and psychological experiments on the other hand. The later theory of measurements for neural networks leads to non-commutativity and even quantum-like contextuality. It is shown that very simple neural networks can violate Bell-type inequalities.
Lansford, J E; Sherman, A M; Antonucci, T C
1998-12-01
This study examines L. L. Carstensen's (1993, 1995) socioemotional selectivity theory within and across three cohorts spanning 4 decades. Socioemotional selectivity theory predicts that as individuals age, they narrow their social networks to devote more emotional resources to fewer relationships with close friends and family. Data from 3 cohorts of nationally representative samples were analyzed to determine whether respondents' satisfaction with the size of their social networks differed by age, cohort, or both. Results support socioemotional selectivity theory: More older adults than younger adults were satisfied with the current size of their social networks rather than wanting larger networks. These findings are consistent across all cohorts. Results are discussed with respect to social relationships across the life course.
Information theory in systems biology. Part I: Gene regulatory and metabolic networks.
Mousavian, Zaynab; Kavousi, Kaveh; Masoudi-Nejad, Ali
2016-03-01
"A Mathematical Theory of Communication", was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein-protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory. Copyright © 2015 Elsevier Ltd. All rights reserved.
Renormalization group theory for percolation in time-varying networks.
Karschau, Jens; Zimmerling, Marco; Friedrich, Benjamin M
2018-05-22
Motivated by multi-hop communication in unreliable wireless networks, we present a percolation theory for time-varying networks. We develop a renormalization group theory for a prototypical network on a regular grid, where individual links switch stochastically between active and inactive states. The question whether a given source node can communicate with a destination node along paths of active links is equivalent to a percolation problem. Our theory maps the temporal existence of multi-hop paths on an effective two-state Markov process. We show analytically how this Markov process converges towards a memoryless Bernoulli process as the hop distance between source and destination node increases. Our work extends classical percolation theory to the dynamic case and elucidates temporal correlations of message losses. Quantification of temporal correlations has implications for the design of wireless communication and control protocols, e.g. in cyber-physical systems such as self-organized swarms of drones or smart traffic networks.
("Un")Doing Standards in Education with Actor-Network Theory
ERIC Educational Resources Information Center
Fenwick, Tara J.
2010-01-01
Recent critiques have drawn important attention to the depoliticized consensus and empty promises embedded in network discourses of educational policy. While acceding this critique, this discussion argues that some forms of network analysis--specifically those adopting actor-network theory (ANT) approaches--actually offer useful theoretical…
Modeling service time reliability in urban ferry system
NASA Astrophysics Data System (ADS)
Chen, Yifan; Luo, Sida; Zhang, Mengke; Shen, Hanxia; Xin, Feifei; Luo, Yujie
2017-09-01
The urban ferry system can carry a large number of travelers, which may alleviate the pressure on road traffic. As an indicator of its service quality, service time reliability (STR) plays an essential part in attracting travelers to the ferry system. A wide array of studies have been conducted to analyze the STR of land transportation. However, the STR of ferry systems has received little attention in the transportation literature. In this study, a model was established to obtain the STR in urban ferry systems. First, the probability density function (PDF) of the service time provided by ferry systems was constructed. Considering the deficiency of the queuing theory, this PDF was determined by Bayes’ theorem. Then, to validate the function, the results of the proposed model were compared with those of the Monte Carlo simulation. With the PDF, the reliability could be determined mathematically by integration. Results showed how the factors including the frequency, capacity, time schedule and ferry waiting time affected the STR under different degrees of congestion in ferry systems. Based on these results, some strategies for improving the STR were proposed. These findings are of great significance to increasing the share of ferries among various urban transport modes.
Advanced access: reducing waiting and delays in primary care.
Murray, Mark; Berwick, Donald M
2003-02-26
Delay of care is a persistent and undesirable feature of current health care systems. Although delay seems to be inevitable and linked to resource limitations, it often is neither. Rather, it is usually the result of unplanned, irrational scheduling and resource allocation. Application of queuing theory and principles of industrial engineering, adapted appropriately to clinical settings, can reduce delay substantially, even in small practices, without requiring additional resources. One model, sometimes referred to as advanced access, has increasingly been shown to reduce waiting times in primary care. The core principle of advanced access is that patients calling to schedule a physician visit are offered an appointment the same day. Advanced access is not sustainable if patient demand for appointments is permanently greater than physician capacity to offer appointments. Six elements of advanced access are important in its application balancing supply and demand, reducing backlog, reducing the variety of appointment types, developing contingency plans for unusual circumstances, working to adjust demand profiles, and increasing the availability of bottleneck resources. Although these principles are powerful, they are counter to deeply held beliefs and established practices in health care organizations. Adopting these principles requires strong leadership investment and support.
Social Network Theory and Educational Change
ERIC Educational Resources Information Center
Daly, Alan J., Ed.
2010-01-01
"Social Network Theory and Educational Change" offers a provocative and fascinating exploration of how social networks in schools can impede or facilitate the work of education reform. Drawing on the work of leading scholars, the book comprises a series of studies examining networks among teachers and school leaders, contrasting formal…
The Embedded Self: A Social Networks Approach to Identity Theory
ERIC Educational Resources Information Center
Walker, Mark H.; Lynn, Freda B.
2013-01-01
Despite the fact that key sociological theories of self and identity view the self as fundamentally rooted in networks of interpersonal relationships, empirical research investigating how personal network structure influences the self is conspicuously lacking. To address this gap, we examine links between network structure and role identity…
Graph theory findings in the pathophysiology of temporal lobe epilepsy
Chiang, Sharon; Haneef, Zulfi
2014-01-01
Temporal lobe epilepsy (TLE) is the most common form of adult epilepsy. Accumulating evidence has shown that TLE is a disorder of abnormal epileptogenic networks, rather than focal sources. Graph theory allows for a network-based representation of TLE brain networks, and has potential to illuminate characteristics of brain topology conducive to TLE pathophysiology, including seizure initiation and spread. We review basic concepts which we believe will prove helpful in interpreting results rapidly emerging from graph theory research in TLE. In addition, we summarize the current state of graph theory findings in TLE as they pertain its pathophysiology. Several common findings have emerged from the many modalities which have been used to study TLE using graph theory, including structural MRI, diffusion tensor imaging, surface EEG, intracranial EEG, magnetoencephalography, functional MRI, cell cultures, simulated models, and mouse models, involving increased regularity of the interictal network configuration, altered local segregation and global integration of the TLE network, and network reorganization of temporal lobe and limbic structures. As different modalities provide different views of the same phenomenon, future studies integrating data from multiple modalities are needed to clarify findings and contribute to the formation of a coherent theory on the pathophysiology of TLE. PMID:24831083
A social network model for the development of a 'Theory of Mind'
NASA Astrophysics Data System (ADS)
Harré, Michael S.
2013-02-01
A "Theory of Mind" is one of the most important skills we as humans have developed; It enables us to infer the mental states and intentions of others, build stable networks of relationships and it plays a central role in our psychological make-up and development. Findings published earlier this year have also shown that we as a species as well as each of us individually benefit from the enlargement of the underlying neuro-anatomical regions that support our social networks, mediated by our Theory of Mind that stabilises these networks. On the basis of such progress and that of earlier work, this paper draws together several different strands from psychology, behavioural economics and network theory in order to generate a novel theoretical representation of the development of our social-cognition and how subsequent larger social networks enables much of our cultural development but at the increased risk of mental disorders.
Prototype-Incorporated Emotional Neural Network.
Oyedotun, Oyebade K; Khashman, Adnan
2017-08-15
Artificial neural networks (ANNs) aim to simulate the biological neural activities. Interestingly, many ''engineering'' prospects in ANN have relied on motivations from cognition and psychology studies. So far, two important learning theories that have been subject of active research are the prototype and adaptive learning theories. The learning rules employed for ANNs can be related to adaptive learning theory, where several examples of the different classes in a task are supplied to the network for adjusting internal parameters. Conversely, the prototype-learning theory uses prototypes (representative examples); usually, one prototype per class of the different classes contained in the task. These prototypes are supplied for systematic matching with new examples so that class association can be achieved. In this paper, we propose and implement a novel neural network algorithm based on modifying the emotional neural network (EmNN) model to unify the prototype- and adaptive-learning theories. We refer to our new model as ``prototype-incorporated EmNN''. Furthermore, we apply the proposed model to two real-life challenging tasks, namely, static hand-gesture recognition and face recognition, and compare the result to those obtained using the popular back-propagation neural network (BPNN), emotional BPNN (EmNN), deep networks, an exemplar classification model, and k-nearest neighbor.
Valt, Christian; Klein, Christoph; Boehm, Stephan G
2015-08-01
Repetition priming is a prominent example of non-declarative memory, and it increases the accuracy and speed of responses to repeatedly processed stimuli. Major long-hold memory theories posit that repetition priming results from facilitation within perceptual and conceptual networks for stimulus recognition and categorization. Stimuli can also be bound to particular responses, and it has recently been suggested that this rapid response learning, not network facilitation, provides a sound theory of priming of object recognition. Here, we addressed the relevance of network facilitation and rapid response learning for priming of person recognition with a view to advance general theories of priming. In four experiments, participants performed conceptual decisions like occupation or nationality judgments for famous faces. The magnitude of rapid response learning varied across experiments, and rapid response learning co-occurred and interacted with facilitation in perceptual and conceptual networks. These findings indicate that rapid response learning and facilitation in perceptual and conceptual networks are complementary rather than competing theories of priming. Thus, future memory theories need to incorporate both rapid response learning and network facilitation as individual facets of priming. © 2014 The British Psychological Society.
A study of the spreading scheme for viral marketing based on a complex network model
NASA Astrophysics Data System (ADS)
Yang, Jianmei; Yao, Canzhong; Ma, Weicheng; Chen, Guanrong
2010-02-01
Buzzword-based viral marketing, known also as digital word-of-mouth marketing, is a marketing mode attached to some carriers on the Internet, which can rapidly copy marketing information at a low cost. Viral marketing actually uses a pre-existing social network where, however, the scale of the pre-existing network is believed to be so large and so random, so that its theoretical analysis is intractable and unmanageable. There are very few reports in the literature on how to design a spreading scheme for viral marketing on real social networks according to the traditional marketing theory or the relatively new network marketing theory. Complex network theory provides a new model for the study of large-scale complex systems, using the latest developments of graph theory and computing techniques. From this perspective, the present paper extends the complex network theory and modeling into the research of general viral marketing and develops a specific spreading scheme for viral marking and an approach to design the scheme based on a real complex network on the QQ instant messaging system. This approach is shown to be rather universal and can be further extended to the design of various spreading schemes for viral marketing based on different instant messaging systems.
NASA Astrophysics Data System (ADS)
Debnath, Lokenath
2010-09-01
This article is essentially devoted to a brief historical introduction to Euler's formula for polyhedra, topology, theory of graphs and networks with many examples from the real-world. Celebrated Königsberg seven-bridge problem and some of the basic properties of graphs and networks for some understanding of the macroscopic behaviour of real physical systems are included. We also mention some important and modern applications of graph theory or network problems from transportation to telecommunications. Graphs or networks are effectively used as powerful tools in industrial, electrical and civil engineering, communication networks in the planning of business and industry. Graph theory and combinatorics can be used to understand the changes that occur in many large and complex scientific, technical and medical systems. With the advent of fast large computers and the ubiquitous Internet consisting of a very large network of computers, large-scale complex optimization problems can be modelled in terms of graphs or networks and then solved by algorithms available in graph theory. Many large and more complex combinatorial problems dealing with the possible arrangements of situations of various kinds, and computing the number and properties of such arrangements can be formulated in terms of networks. The Knight's tour problem, Hamilton's tour problem, problem of magic squares, the Euler Graeco-Latin squares problem and their modern developments in the twentieth century are also included.
NASA Astrophysics Data System (ADS)
Lezon, Timothy R.; Shrivastava, Indira H.; Yang, Zheng; Bahar, Ivet
The following sections are included: * Introduction * Theory and Assumptions * Statistical mechanical foundations * Anisotropic network models * Gaussian network model * Rigid block models * Treatment of perturbations * Langevin dynamics * Applications * Membrane proteins * Viruses * Conclusion * References
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berg, D.; Black, D.; Slimmer, D.
1994-04-01
The DART Data Flow Manager (dfm) integrates a buffer manager with a requester/provider model for scheduling work on buffers. Buffer lists, representing built events or other data, are queued by service requesters to service providers. Buffers may be either internal (reside on the local node), or external (located elsewhere, e.g., dual ported memory). Internal buffers are managed locally. Wherever possible, dfm moves only addresses of buffers rather than buffers themselves.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berg, D.; Black, D.; Slimmer, D.
1994-12-31
The DART Data Flow Manager (dfm) integrates a buffer manager with a requester/provider model for scheduling work on buffers. Buffer lists, representing built events or other data, are queued by service requesters to service providers. Buffers may be either internal (reside on the local node), or external (located elsewhere, e.g., dual ported memory). Internal buffers are managed locally. Wherever possible, dfm moves only addresses of buffers rather than buffers themselves.
Actor-Network Theory and methodology: Just what does it mean to say that nonhumans have agency?
Sayes, Edwin
2014-02-01
Actor-Network Theory is a controversial social theory. In no respect is this more so than the role it 'gives' to nonhumans: nonhumans have agency, as Latour provocatively puts it. This article aims to interrogate the multiple layers of this declaration to understand what it means to assert with Actor-Network Theory that nonhumans exercise agency. The article surveys a wide corpus of statements by the position's leading figures and emphasizes the wider methodological framework in which these statements are embedded. With this work done, readers will then be better placed to reject or accept the Actor-Network position - understanding more precisely what exactly it is at stake in this decision.
Wilber 3: A Python-Django Web Application For Acquiring Large-scale Event-oriented Seismic Data
NASA Astrophysics Data System (ADS)
Newman, R. L.; Clark, A.; Trabant, C. M.; Karstens, R.; Hutko, A. R.; Casey, R. E.; Ahern, T. K.
2013-12-01
Since 2001, the IRIS Data Management Center (DMC) WILBER II system has provided a convenient web-based interface for locating seismic data related to a particular event, and requesting a subset of that data for download. Since its launch, both the scale of available data and the technology of web-based applications have developed significantly. Wilber 3 is a ground-up redesign that leverages a number of public and open-source projects to provide an event-oriented data request interface with a high level of interactivity and scalability for multiple data types. Wilber 3 uses the IRIS/Federation of Digital Seismic Networks (FDSN) web services for event data, metadata, and time-series data. Combining a carefully optimized Google Map with the highly scalable SlickGrid data API, the Wilber 3 client-side interface can load tens of thousands of events or networks/stations in a single request, and provide instantly responsive browsing, sorting, and filtering of event and meta data in the web browser, without further reliance on the data service. The server-side of Wilber 3 is a Python-Django application, one of over a dozen developed in the last year at IRIS, whose common framework, components, and administrative overhead represent a massive savings in developer resources. Requests for assembled datasets, which may include thousands of data channels and gigabytes of data, are queued and executed using the Celery distributed Python task scheduler, giving Wilber 3 the ability to operate in parallel across a large number of nodes.
Henry, Kevin; Wood, Nathan J.; Frazier, Tim G.
2017-01-01
Tsunami evacuation planning in coastal communities is typically focused on local events where at-risk individuals must move on foot in a matter of minutes to safety. Less attention has been placed on distant tsunamis, where evacuations unfold over several hours, are often dominated by vehicle use and are managed by public safety officials. Traditional traffic simulation models focus on estimating clearance times but often overlook the influence of varying population demand, alternative modes, background traffic, shadow evacuation, and traffic management alternatives. These factors are especially important for island communities with limited egress options to safety. We use the coastal community of Balboa Island, California (USA), as a case study to explore the range of potential clearance times prior to wave arrival for a distant tsunami scenario. We use a first-in–first-out queuing simulation environment to estimate variations in clearance times, given varying assumptions of the evacuating population (demand) and the road network over which they evacuate (supply). Results suggest clearance times are less than wave arrival times for a distant tsunami, except when we assume maximum vehicle usage for residents, employees, and tourists for a weekend scenario. A two-lane bridge to the mainland was the primary traffic bottleneck, thereby minimizing the effect of departure times, shadow evacuations, background traffic, boat-based evacuations, and traffic light timing on overall community clearance time. Reducing vehicular demand generally reduced clearance time, whereas improvements to road capacity had mixed results. Finally, failure to recognize non-residential employee and tourist populations in the vehicle demand substantially underestimated clearance time.
Complete characterization of the stability of cluster synchronization in complex dynamical networks.
Sorrentino, Francesco; Pecora, Louis M; Hagerstrom, Aaron M; Murphy, Thomas E; Roy, Rajarshi
2016-04-01
Synchronization is an important and prevalent phenomenon in natural and engineered systems. In many dynamical networks, the coupling is balanced or adjusted to admit global synchronization, a condition called Laplacian coupling. Many networks exhibit incomplete synchronization, where two or more clusters of synchronization persist, and computational group theory has recently proved to be valuable in discovering these cluster states based on the topology of the network. In the important case of Laplacian coupling, additional synchronization patterns can exist that would not be predicted from the group theory analysis alone. Understanding how and when clusters form, merge, and persist is essential for understanding collective dynamics, synchronization, and failure mechanisms of complex networks such as electric power grids, distributed control networks, and autonomous swarming vehicles. We describe a method to find and analyze all of the possible cluster synchronization patterns in a Laplacian-coupled network, by applying methods of computational group theory to dynamically equivalent networks. We present a general technique to evaluate the stability of each of the dynamically valid cluster synchronization patterns. Our results are validated in an optoelectronic experiment on a five-node network that confirms the synchronization patterns predicted by the theory.
Modifier constraint in alkali borophosphate glasses using topological constraint theory
NASA Astrophysics Data System (ADS)
Li, Xiang; Zeng, Huidan; Jiang, Qi; Zhao, Donghui; Chen, Guorong; Wang, Zhaofeng; Sun, Luyi; Chen, Jianding
2016-12-01
In recent years, composition-dependent properties of glasses have been successfully predicted using the topological constraint theory. The constraints of the glass network are derived from two main parts: network formers and network modifiers. The constraints of the network formers can be calculated on the basis of the topological structure of the glass. However, the latter cannot be accurately calculated in this way, because of the existing of ionic bonds. In this paper, the constraints of the modifier ions in phosphate glasses were thoroughly investigated using the topological constraint theory. The results show that the constraints of the modifier ions are gradually increased with the addition of alkali oxides. Furthermore, an improved topological constraint theory for borophosphate glasses is proposed by taking the composition-dependent constraints of the network modifiers into consideration. The proposed theory is subsequently evaluated by analyzing the composition dependence of the glass transition temperature in alkali borophosphate glasses. This method is supposed to be extended to other similar glass systems containing alkali ions.
Graph theory findings in the pathophysiology of temporal lobe epilepsy.
Chiang, Sharon; Haneef, Zulfi
2014-07-01
Temporal lobe epilepsy (TLE) is the most common form of adult epilepsy. Accumulating evidence has shown that TLE is a disorder of abnormal epileptogenic networks, rather than focal sources. Graph theory allows for a network-based representation of TLE brain networks, and has potential to illuminate characteristics of brain topology conducive to TLE pathophysiology, including seizure initiation and spread. We review basic concepts which we believe will prove helpful in interpreting results rapidly emerging from graph theory research in TLE. In addition, we summarize the current state of graph theory findings in TLE as they pertain its pathophysiology. Several common findings have emerged from the many modalities which have been used to study TLE using graph theory, including structural MRI, diffusion tensor imaging, surface EEG, intracranial EEG, magnetoencephalography, functional MRI, cell cultures, simulated models, and mouse models, involving increased regularity of the interictal network configuration, altered local segregation and global integration of the TLE network, and network reorganization of temporal lobe and limbic structures. As different modalities provide different views of the same phenomenon, future studies integrating data from multiple modalities are needed to clarify findings and contribute to the formation of a coherent theory on the pathophysiology of TLE. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks
Salim, Shelly; Moh, Sangman
2016-01-01
A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead. PMID:27376290
An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks.
Salim, Shelly; Moh, Sangman
2016-06-30
A cognitive radio sensor network (CRSN) is a wireless sensor network in which sensor nodes are equipped with cognitive radio. In this paper, we propose an energy-efficient game-theory-based spectrum decision (EGSD) scheme for CRSNs to prolong the network lifetime. Note that energy efficiency is the most important design consideration in CRSNs because it determines the network lifetime. The central part of the EGSD scheme consists of two spectrum selection algorithms: random selection and game-theory-based selection. The EGSD scheme also includes a clustering algorithm, spectrum characterization with a Markov chain, and cluster member coordination. Our performance study shows that EGSD outperforms the existing popular framework in terms of network lifetime and coordination overhead.
NASA Astrophysics Data System (ADS)
Cocco, Alex P.; Nakajo, Arata; Chiu, Wilson K. S.
2017-12-01
We present a fully analytical, heuristic model - the "Analytical Transport Network Model" - for steady-state, diffusive, potential flow through a 3-D network. Employing a combination of graph theory, linear algebra, and geometry, the model explicitly relates a microstructural network's topology and the morphology of its channels to an effective material transport coefficient (a general term meant to encompass, e.g., conductivity or diffusion coefficient). The model's transport coefficient predictions agree well with those from electrochemical fin (ECF) theory and finite element analysis (FEA), but are computed 0.5-1.5 and 5-6 orders of magnitude faster, respectively. In addition, the theory explicitly relates a number of morphological and topological parameters directly to the transport coefficient, whereby the distributions that characterize the structure are readily available for further analysis. Furthermore, ATN's explicit development provides insight into the nature of the tortuosity factor and offers the potential to apply theory from network science and to consider the optimization of a network's effective resistance in a mathematically rigorous manner. The ATN model's speed and relative ease-of-use offer the potential to aid in accelerating the design (with respect to transport), and thus reducing the cost, of energy materials.
Detection of network attacks based on adaptive resonance theory
NASA Astrophysics Data System (ADS)
Bukhanov, D. G.; Polyakov, V. M.
2018-05-01
The paper considers an approach to intrusion detection systems using a neural network of adaptive resonant theory. It suggests the structure of an intrusion detection system consisting of two types of program modules. The first module manages connections of user applications by preventing the undesirable ones. The second analyzes the incoming network traffic parameters to check potential network attacks. After attack detection, it notifies the required stations using a secure transmission channel. The paper describes the experiment on the detection and recognition of network attacks using the test selection. It also compares the obtained results with similar experiments carried out by other authors. It gives findings and conclusions on the sufficiency of the proposed approach. The obtained information confirms the sufficiency of applying the neural networks of adaptive resonant theory to analyze network traffic within the intrusion detection system.
Dynamical influence processes on networks: general theory and applications to social contagion.
Harris, Kameron Decker; Danforth, Christopher M; Dodds, Peter Sheridan
2013-08-01
We study binary state dynamics on a network where each node acts in response to the average state of its neighborhood. By allowing varying amounts of stochasticity in both the network and node responses, we find different outcomes in random and deterministic versions of the model. In the limit of a large, dense network, however, we show that these dynamics coincide. We construct a general mean-field theory for random networks and show this predicts that the dynamics on the network is a smoothed version of the average response function dynamics. Thus, the behavior of the system can range from steady state to chaotic depending on the response functions, network connectivity, and update synchronicity. As a specific example, we model the competing tendencies of imitation and nonconformity by incorporating an off-threshold into standard threshold models of social contagion. In this way, we attempt to capture important aspects of fashions and societal trends. We compare our theory to extensive simulations of this "limited imitation contagion" model on Poisson random graphs, finding agreement between the mean-field theory and stochastic simulations.
ERIC Educational Resources Information Center
Cook-Craig, Patricia G.
2010-01-01
This article examines the role that social network theory and social network analysis has played in assessing and developing effective primary prevention networks across a southeastern state. In 2004 the state began an effort to develop a strategic plan for the primary prevention of violence working with local communities across the state. The…
“Theory of Food” as a Neurocognitive Adaptation
Allen, John S.
2011-01-01
Human adult cognition emerges over the course of development via the interaction of multiple critical neurocognitive networks. These networks evolved in response to various selection pressures, many of which were modified or intensified by the intellectual, technological, and socio-cultural environments that arose in connection with the evolution of genus Homo. Networks related to language and theory of mind clearly play an important role in adult cognition. Given the critical importance of food to both basic survival and cultural interaction, a “theory of food” (analogous to theory of mind) may represent another complex network essential for normal cognition. I propose that theory of food evolved as an internal, cognitive representation of our diets in our minds. Like other complex cognitive abilities, it relies on complex and overlapping dedicated neural networks that develop in childhood under familial and cultural influences. Normative diets are analogous to first languages in that they are acquired without overt teaching; they are also difficult to change or modify once a critical period in development is passed. Theory of food suggests that cognitive activities related to food may be cognitive enhancers, which could have implications for maintaining healthy brain function in aging. PMID:22262561
"Theory of food" as a neurocognitive adaptation.
Allen, John S
2012-01-01
Human adult cognition emerges over the course of development via the interaction of multiple critical neurocognitive networks. These networks evolved in response to various selection pressures, many of which were modified or intensified by the intellectual, technological, and sociocultural environments that arose in connection with the evolution of genus Homo. Networks related to language and theory of mind clearly play an important role in adult cognition. Given the critical importance of food to both basic survival and cultural interaction, a "theory of food" (analogous to theory of mind) may represent another complex network essential for normal cognition. I propose that theory of food evolved as an internal, cognitive representation of our diets in our minds. Like other complex cognitive abilities, it relies on complex and overlapping dedicated neural networks that develop in childhood under familial and cultural influences. Normative diets are analogous to first languages in that they are acquired without overt teaching; they are also difficult to change or modify once a critical period in development is passed. Theory of food suggests that cognitive activities related to food may be cognitive enhancers, which could have implications for maintaining healthy brain function in aging. Copyright © 2012 Wiley Periodicals, Inc.
Wang, Xin; Wang, Ying; Sun, Hongbin
2016-01-01
In social media, trust and distrust among users are important factors in helping users make decisions, dissect information, and receive recommendations. However, the sparsity and imbalance of social relations bring great difficulties and challenges in predicting trust and distrust. Meanwhile, there are numerous inducing factors to determine trust and distrust relations. The relationship among inducing factors may be dependency, independence, and conflicting. Dempster-Shafer theory and neural network are effective and efficient strategies to deal with these difficulties and challenges. In this paper, we study trust and distrust prediction based on the combination of Dempster-Shafer theory and neural network. We firstly analyze the inducing factors about trust and distrust, namely, homophily, status theory, and emotion tendency. Then, we quantify inducing factors of trust and distrust, take these features as evidences, and construct evidence prototype as input nodes of multilayer neural network. Finally, we propose a framework of predicting trust and distrust which uses multilayer neural network to model the implementing process of Dempster-Shafer theory in different hidden layers, aiming to overcome the disadvantage of Dempster-Shafer theory without optimization method. Experimental results on a real-world dataset demonstrate the effectiveness of the proposed framework. PMID:27034651
Using food-web theory to conserve ecosystems
McDonald-Madden, E.; Sabbadin, R.; Game, E. T.; Baxter, P. W. J.; Chadès, I.; Possingham, H. P.
2016-01-01
Food-web theory can be a powerful guide to the management of complex ecosystems. However, we show that indices of species importance common in food-web and network theory can be a poor guide to ecosystem management, resulting in significantly more extinctions than necessary. We use Bayesian Networks and Constrained Combinatorial Optimization to find optimal management strategies for a wide range of real and hypothetical food webs. This Artificial Intelligence approach provides the ability to test the performance of any index for prioritizing species management in a network. While no single network theory index provides an appropriate guide to management for all food webs, a modified version of the Google PageRank algorithm reliably minimizes the chance and severity of negative outcomes. Our analysis shows that by prioritizing ecosystem management based on the network-wide impact of species protection rather than species loss, we can substantially improve conservation outcomes. PMID:26776253
Spectrally Queued Feature Selection for Robotic Visual Odometery
2010-11-23
in these systems has yet to be defined. 1. INTRODUCTION 1.1 Uses of Autonomous Vehicles Autonomous vehicles have a wide range of possible...applications. In military situations, autonomous vehicles are valued for their ability to keep Soldiers far away from danger. A robot can inspect and disarm...just a glimpse of what engineers are hoping for in the future. 1.2 Biological Influence Autonomous vehicles are becoming more of a possibility in
Multifractal Internet Traffic Model and Active Queue Management
2003-01-01
dropped by the Adaptive RED , ssthresh decreases from 64KB to 4KB and the new con- gestion window cwnd is decreased from 8KB to 1KB (Tahoe). The situation...method to predict the queuing behavior of FIFO and RED queues. In order to satisfy a given delay and jitter requirement for real time connections, and to...5.2 Vulnerability of Adaptive RED to Web-mice . . . . . . . . . . . . . 103 5.3 A Parallel Virtual Queues Structure
Connectivism and Information Literacy: Moving from Learning Theory to Pedagogical Practice
ERIC Educational Resources Information Center
Transue, Beth M.
2013-01-01
Connectivism is an emerging learning theory positing that knowledge comprises networked relationships and that learning comprises the ability to successfully navigate through these networks. Successful pedagogical strategies involve the instructor helping students to identify, navigate, and evaluate information from their learning networks. Many…
Network analysis applications in hydrology
NASA Astrophysics Data System (ADS)
Price, Katie
2017-04-01
Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain underexplored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five longterm USGS streamflow and water quality gages, allowing network application of longterm flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long term and eventbased hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwatersurface water interactions.
Cascading Failures and Recovery in Networks of Networks
NASA Astrophysics Data System (ADS)
Havlin, Shlomo
Network science have been focused on the properties of a single isolated network that does not interact or depends on other networks. In reality, many real-networks, such as power grids, transportation and communication infrastructures interact and depend on other networks. I will present a framework for studying the vulnerability and the recovery of networks of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes like certain locations play a role in two networks -multiplex. This may happen recursively and can lead to a cascade of failures and to a sudden fragmentation of the system. I will present analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. I will show, that the general theory has many novel features that are not present in the classical network theory. When recovery of components is possible global spontaneous recovery of the networks and hysteresis phenomena occur and the theory suggests an optimal repairing strategy of system of systems. I will also show that interdependent networks embedded in space are significantly more vulnerable compared to non embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences.Thus, analyzing data of real network of networks is highly required to understand the system vulnerability. DTRA, ONR, Israel Science Foundation.
Sociospatial Knowledge Networks: Appraising Community as Place.
ERIC Educational Resources Information Center
Skelly, Anne H.; Arcury, Thomas A.; Gesler, Wilbert M.; Cravey, Altha J.; Dougherty, Molly C.; Washburn, Sarah A.; Nash, Sally
2002-01-01
A new theory of geographical analysis--sociospatial knowledge networks--provides a framework for understanding the social and spatial locations of a community's health knowledge and beliefs. This theory is guiding an ethnographic study of health beliefs, knowledge, and knowledge networks in a diverse rural community at high risk for type-2…
Rubber elasticity for percolation network consisting of Gaussian chains.
Nishi, Kengo; Noguchi, Hiroshi; Sakai, Takamasa; Shibayama, Mitsuhiro
2015-11-14
A theory describing the elastic modulus for percolation networks of Gaussian chains on general lattices such as square and cubic lattices is proposed and its validity is examined with simulation and mechanical experiments on well-defined polymer networks. The theory was developed by generalizing the effective medium approximation (EMA) for Hookian spring network to Gaussian chain networks. From EMA theory, we found that the ratio of the elastic modulus at p, G to that at p = 1, G0, must be equal to G/G0 = (p - 2/f)/(1 - 2/f) if the position of sites can be determined so as to meet the force balance, where p is the degree of cross-linking reaction. However, the EMA prediction cannot be applicable near its percolation threshold because EMA is a mean field theory. Thus, we combine real-space renormalization and EMA and propose a theory called real-space renormalized EMA, i.e., REMA. The elastic modulus predicted by REMA is in excellent agreement with the results of simulations and experiments of near-ideal diamond lattice gels.
Rubber elasticity for percolation network consisting of Gaussian chains
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nishi, Kengo, E-mail: kengo.nishi@phys.uni-goettingen.de, E-mail: sakai@tetrapod.t.u-tokyo.ac.jp, E-mail: sibayama@issp.u-tokyo.ac.jp; Noguchi, Hiroshi; Shibayama, Mitsuhiro, E-mail: kengo.nishi@phys.uni-goettingen.de, E-mail: sakai@tetrapod.t.u-tokyo.ac.jp, E-mail: sibayama@issp.u-tokyo.ac.jp
2015-11-14
A theory describing the elastic modulus for percolation networks of Gaussian chains on general lattices such as square and cubic lattices is proposed and its validity is examined with simulation and mechanical experiments on well-defined polymer networks. The theory was developed by generalizing the effective medium approximation (EMA) for Hookian spring network to Gaussian chain networks. From EMA theory, we found that the ratio of the elastic modulus at p, G to that at p = 1, G{sub 0}, must be equal to G/G{sub 0} = (p − 2/f)/(1 − 2/f) if the position of sites can be determined somore » as to meet the force balance, where p is the degree of cross-linking reaction. However, the EMA prediction cannot be applicable near its percolation threshold because EMA is a mean field theory. Thus, we combine real-space renormalization and EMA and propose a theory called real-space renormalized EMA, i.e., REMA. The elastic modulus predicted by REMA is in excellent agreement with the results of simulations and experiments of near-ideal diamond lattice gels.« less
Xiong, Jie; Zhou, Tong
2012-01-01
An important problem in systems biology is to reconstruct gene regulatory networks (GRNs) from experimental data and other a priori information. The DREAM project offers some types of experimental data, such as knockout data, knockdown data, time series data, etc. Among them, multifactorial perturbation data are easier and less expensive to obtain than other types of experimental data and are thus more common in practice. In this article, a new algorithm is presented for the inference of GRNs using the DREAM4 multifactorial perturbation data. The GRN inference problem among [Formula: see text] genes is decomposed into [Formula: see text] different regression problems. In each of the regression problems, the expression level of a target gene is predicted solely from the expression level of a potential regulation gene. For different potential regulation genes, different weights for a specific target gene are constructed by using the sum of squared residuals and the Pearson correlation coefficient. Then these weights are normalized to reflect effort differences of regulating distinct genes. By appropriately choosing the parameters of the power law, we constructe a 0-1 integer programming problem. By solving this problem, direct regulation genes for an arbitrary gene can be estimated. And, the normalized weight of a gene is modified, on the basis of the estimation results about the existence of direct regulations to it. These normalized and modified weights are used in queuing the possibility of the existence of a corresponding direct regulation. Computation results with the DREAM4 In Silico Size 100 Multifactorial subchallenge show that estimation performances of the suggested algorithm can even outperform the best team. Using the real data provided by the DREAM5 Network Inference Challenge, estimation performances can be ranked third. Furthermore, the high precision of the obtained most reliable predictions shows the suggested algorithm may be helpful in guiding biological experiment designs.
Stochastic cycle selection in active flow networks.
Woodhouse, Francis G; Forrow, Aden; Fawcett, Joanna B; Dunkel, Jörn
2016-07-19
Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models.
Stochastic cycle selection in active flow networks
NASA Astrophysics Data System (ADS)
Woodhouse, Francis; Forrow, Aden; Fawcett, Joanna; Dunkel, Jorn
2016-11-01
Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such non-equilibrium networks. By connecting concepts from lattice field theory, graph theory and transition rate theory, we show how topology controls dynamics in a generic model for actively driven flow on a network. Through theoretical and numerical analysis we identify symmetry-based rules to classify and predict the selection statistics of complex flow cycles from the network topology. Our conceptual framework is applicable to a broad class of biological and non-biological far-from-equilibrium networks, including actively controlled information flows, and establishes a new correspondence between active flow networks and generalized ice-type models.
Stochastic cycle selection in active flow networks
Woodhouse, Francis G.; Forrow, Aden; Fawcett, Joanna B.; Dunkel, Jörn
2016-01-01
Active biological flow networks pervade nature and span a wide range of scales, from arterial blood vessels and bronchial mucus transport in humans to bacterial flow through porous media or plasmodial shuttle streaming in slime molds. Despite their ubiquity, little is known about the self-organization principles that govern flow statistics in such nonequilibrium networks. Here we connect concepts from lattice field theory, graph theory, and transition rate theory to understand how topology controls dynamics in a generic model for actively driven flow on a network. Our combined theoretical and numerical analysis identifies symmetry-based rules that make it possible to classify and predict the selection statistics of complex flow cycles from the network topology. The conceptual framework developed here is applicable to a broad class of biological and nonbiological far-from-equilibrium networks, including actively controlled information flows, and establishes a correspondence between active flow networks and generalized ice-type models. PMID:27382186
Social Capital Theory: Implications for Women's Networking and Learning
ERIC Educational Resources Information Center
Alfred, Mary V.
2009-01-01
This chapter describes social capital theory as a framework for exploring women's networking and social capital resources. It presents the foundational assumptions of the theory, the benefits and risks of social capital engagement, a feminist critique of social capital, and the role of social capital in adult learning.
Story-Telling and Narrative: A Neurophilosophical Perspective.
ERIC Educational Resources Information Center
Liston, Delores D.
Theories of neuroscience are presented to demonstrate the significance of storytelling and narrative to education by relating brain function to learning. A few key concepts are reviewed to establish a common working vocabulary with regard to neural networks. The tensor network theory and the neurognosis theory are described to provide…
Towards the Integration of Niche and Network Theories.
Godoy, Oscar; Bartomeus, Ignasi; Rohr, Rudolf P; Saavedra, Serguei
2018-04-01
The quest for understanding how species interactions modulate diversity has progressed by theoretical and empirical advances following niche and network theories. Yet, niche studies have been limited to describe coexistence within tropic levels despite incorporating information about multi-trophic interactions. Network approaches could address this limitation, but they have ignored the structure of species interactions within trophic levels. Here we call for the integration of niche and network theories to reach new frontiers of knowledge exploring how interactions within and across trophic levels promote species coexistence. This integration is possible due to the strong parallelisms in the historical development, ecological concepts, and associated mathematical tools of both theories. We provide a guideline to integrate this framework with observational and experimental studies. Copyright © 2018 Elsevier Ltd. All rights reserved.
Information theory in systems biology. Part II: protein-protein interaction and signaling networks.
Mousavian, Zaynab; Díaz, José; Masoudi-Nejad, Ali
2016-03-01
By the development of information theory in 1948 by Claude Shannon to address the problems in the field of data storage and data communication over (noisy) communication channel, it has been successfully applied in many other research areas such as bioinformatics and systems biology. In this manuscript, we attempt to review some of the existing literatures in systems biology, which are using the information theory measures in their calculations. As we have reviewed most of the existing information-theoretic methods in gene regulatory and metabolic networks in the first part of the review, so in the second part of our study, the application of information theory in other types of biological networks including protein-protein interaction and signaling networks will be surveyed. Copyright © 2015 Elsevier Ltd. All rights reserved.
Chang, H.-C.; Kopaska-Merkel, D. C.; Chen, H.-C.; Rocky, Durrans S.
2000-01-01
Lithofacies identification supplies qualitative information about rocks. Lithofacies represent rock textures and are important components of hydrocarbon reservoir description. Traditional techniques of lithofacies identification from core data are costly and different geologists may provide different interpretations. In this paper, we present a low-cost intelligent system consisting of three adaptive resonance theory neural networks and a rule-based expert system to consistently and objectively identify lithofacies from well-log data. The input data are altered into different forms representing different perspectives of observation of lithofacies. Each form of input is processed by a different adaptive resonance theory neural network. Among these three adaptive resonance theory neural networks, one neural network processes the raw continuous data, another processes categorial data, and the third processes fuzzy-set data. Outputs from these three networks are then combined by the expert system using fuzzy inference to determine to which facies the input data should be assigned. Rules are prioritized to emphasize the importance of firing order. This new approach combines the learning ability of neural networks, the adaptability of fuzzy logic, and the expertise of geologists to infer facies of the rocks. This approach is applied to the Appleton Field, an oil field located in Escambia County, Alabama. The hybrid intelligence system predicts lithofacies identity from log data with 87.6% accuracy. This prediction is more accurate than those of single adaptive resonance theory networks, 79.3%, 68.0% and 66.0%, using raw, fuzzy-set, and categorical data, respectively, and by an error-backpropagation neural network, 57.3%. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Christianson, D. S.; Beekwilder, N.; Chan, S.; Cheah, Y. W.; Chu, H.; Dengel, S.; O'Brien, F.; Pastorello, G.; Sandesh, M.; Torn, M. S.; Agarwal, D.
2017-12-01
AmeriFlux is a network of scientists who independently collect eddy covariance and related environmental observations at over 250 locations across the Americas. As part of the AmeriFlux Management Project, the AmeriFlux Data Team manages standardization, collection, quality assurance / quality control (QA/QC), and distribution of data submitted by network members. To generate data products that are timely, QA/QC'd, and repeatable, and have traceable provenance, we developed a semi-automated data processing pipeline. The new pipeline consists of semi-automated format and data QA/QC checks. Results are communicated via on-line reports as well as an issue-tracking system. Data processing time has been reduced from 2-3 days to a few hours of manual review time, resulting in faster data availability from the time of data submission. The pipeline is scalable to the network level and has the following key features. (1) On-line results of the format QA/QC checks are available immediately for data provider review. This enables data providers to correct and resubmit data quickly. (2) The format QA/QC assessment includes an automated attempt to fix minor format errors. Data submissions that are formatted in the new AmeriFlux FP-In standard can be queued for the data QA/QC assessment, often with minimal delay. (3) Automated data QA/QC checks identify and communicate potentially erroneous data via online, graphical quick views that highlight observations with unexpected values, incorrect units, time drifts, invalid multivariate correlations, and/or radiation shadows. (4) Progress through the pipeline is integrated with an issue-tracking system that facilitates communications between data providers and the data processing team in an organized and searchable fashion. Through development of these and other features of the pipeline, we present solutions to challenges that include optimizing automated with manual processing, bridging legacy data management infrastructure with various software tools, and working across interdisciplinary and international science cultures. Additionally, we discuss results from community member feedback that helped refine QA/QC communications for efficient data submission and revision.
Warren, David E; Denburg, Natalie L; Power, Jonathan D; Bruss, Joel; Waldron, Eric J; Sun, Haoxin; Petersen, Steve E; Tranel, Daniel
2017-02-01
Theories of brain-network organization based on neuroimaging data have burgeoned in recent years, but the predictive power of such theories for cognition and behavior has only rarely been examined. Here, predictions from clinical neuropsychologists about the cognitive profiles of patients with focal brain lesions were used to evaluate a brain-network theory (Warren et al., 2014). Neuropsychologists made predictions regarding the neuropsychological profiles of a neurological patient sample (N = 30) based on lesion location. The neuropsychologists then rated the congruence of their predictions with observed neuropsychological outcomes, in regard to the "severity" of neuropsychological deficits and the "focality" of neuropsychological deficits. Based on the network theory, two types of lesion locations were identified: "target" locations (putative hubs in a brain-wide network) and "control" locations (hypothesized to play limited roles in network function). We found that patients with lesions of target locations (N = 19) had deficits of greater than expected severity that were more widespread than expected, whereas patients with lesions of control locations (N = 11) showed milder, circumscribed deficits that were more congruent with expectations. The findings for the target brain locations suggest that prevailing views of brain-behavior relationships may be sharpened and refined by integrating recently proposed network-oriented perspectives. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Operationalizing Network Theory for Ecosystem Service Assessments.
Dee, Laura E; Allesina, Stefano; Bonn, Aletta; Eklöf, Anna; Gaines, Steven D; Hines, Jes; Jacob, Ute; McDonald-Madden, Eve; Possingham, Hugh; Schröter, Matthias; Thompson, Ross M
2017-02-01
Managing ecosystems to provide ecosystem services in the face of global change is a pressing challenge for policy and science. Predicting how alternative management actions and changing future conditions will alter services is complicated by interactions among components in ecological and socioeconomic systems. Failure to understand those interactions can lead to detrimental outcomes from management decisions. Network theory that integrates ecological and socioeconomic systems may provide a path to meeting this challenge. While network theory offers promising approaches to examine ecosystem services, few studies have identified how to operationalize networks for managing and assessing diverse ecosystem services. We propose a framework for how to use networks to assess how drivers and management actions will directly and indirectly alter ecosystem services. Copyright © 2016 Elsevier Ltd. All rights reserved.
Social networking for nurse education: Possibilities, perils and pitfalls.
Green, Janet; Wyllie, Aileen; Jackson, Debra
2014-01-01
Abstract In this paper, we consider the potential and implications of using social networking sites such as Facebook® in nurse education. The concept of social networking and the use of Facebook will be explored, as will the theoretical constructs specific to the use of online technology and Web 2.0 tools. Theories around Communities of Inquiry (Garrison, Anderson, & Archer, 2000), Communities of Practice (Wenger, 1998), Activity Theory (Daniels, Cole, & Wertsch, 2007) and Actor-Network theory (Latour, 1997) will be briefly explored, as will the work of Vygotsky (1978), as applies to the social aspects of learning. Boundary issues, such as if and how faculty and students should or could be connected via social networking sites will also be explored.
The use of network theory to model disparate ship design information
NASA Astrophysics Data System (ADS)
Rigterink, Douglas; Piks, Rebecca; Singer, David J.
2014-06-01
This paper introduces the use of network theory to model and analyze disparate ship design information. This work will focus on a ship's distributed systems and their intra- and intersystem structures and interactions. The three system to be analyzed are: a passageway system, an electrical system, and a fire fighting system. These systems will be analyzed individually using common network metrics to glean information regarding their structures and attributes. The systems will also be subjected to community detection algorithms both separately and as a multiplex network to compare their similarities, differences, and interactions. Network theory will be shown to be useful in the early design stage due to its simplicity and ability to model any shipboard system.
Artificial intelligence based decision support for trumpeter swan management
Sojda, Richard S.
2002-01-01
The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988-2000. Applying the Matched Pairs Multivariate Permutation Test as a statistical tool was a new approach for comparing flyway distributions of waterfowl over time that seemed to work well. Based on this approach, the empirical evidence that I gathered led me to conclude that the base queuing model does accurately simulate swan distributions in the flyway. The system was insensitive to almost all model parameters tested. That remains perplexing, but might result from the base queuing model, itself, being particularly effective at representing the actual ecological diversity in the world of Rocky Mountain trumpeter swans, both spatial and temporally.
Lee, Haeok; Fawcett, Jacqueline; Yang, Jin Hyang; Hann, Hie-Won
2012-12-01
The purpose of this article is to explain the evolution of a situation-specific theory developed to enhance understanding of health-related behaviors of Korean Americans (KAs) who have or are at risk for a chronic hepatitis B virus (HBV) infection. The situation-specific theory evolved from an integration of the Network Episode Model, studies of health-related behaviors of people with HBV infection, and our studies of and practice experiences with Asian American individuals with HBV infection. The major concepts of the theory are sociocultural context, social network, individual-level factors, illness experience, and health-related behaviors. The major propositions of the theory are that sociocultural context, social network, and individual-level factors influence the illness experience, and that sociocultural context, social network, individual-level factors, and the illness experience influence health-related behaviors of KAs who have or are at risk for HBV infection. This situation-specific theory represents a translation of abstract concepts into clinical reality. The theory is an explanation of correlates of health-related HBV behaviors of KAs. The next step is to develop and test the effectiveness of a nursing intervention designed to promote behaviors that will enhance the health of KAs who have or are at risk for HBV infection, and that takes into account sociocultural context, social network, individual-level factors, and illness experience. © 2012 Sigma Theta Tau International.
Cresswell, Kathrin M; Worth, Allison; Sheikh, Aziz
2010-11-01
Actor-Network Theory (ANT) is an increasingly influential, but still deeply contested, approach to understand humans and their interactions with inanimate objects. We argue that health services research, and in particular evaluations of complex IT systems in health service organisations, may benefit from being informed by Actor-Network Theory perspectives. Despite some limitations, an Actor-Network Theory-based approach is conceptually useful in helping to appreciate the complexity of reality (including the complexity of organisations) and the active role of technology in this context. This can prove helpful in understanding how social effects are generated as a result of associations between different actors in a network. Of central importance in this respect is that Actor-Network Theory provides a lens through which to view the role of technology in shaping social processes. Attention to this shaping role can contribute to a more holistic appreciation of the complexity of technology introduction in healthcare settings. It can also prove practically useful in providing a theoretically informed approach to sampling (by drawing on informants that are related to the technology in question) and analysis (by providing a conceptual tool and vocabulary that can form the basis for interpretations). We draw on existing empirical work in this area and our ongoing work investigating the integration of electronic health record systems introduced as part of England's National Programme for Information Technology to illustrate salient points. Actor-Network Theory needs to be used pragmatically with an appreciation of its shortcomings. Our experiences suggest it can be helpful in investigating technology implementations in healthcare settings.
Controllability of Surface Water Networks
NASA Astrophysics Data System (ADS)
Riasi, M. Sadegh; Yeghiazarian, Lilit
2017-12-01
To sustainably manage water resources, we must understand how to control complex networked systems. In this paper, we study surface water networks from the perspective of structural controllability, a concept that integrates classical control theory with graph-theoretic formalism. We present structural controllability theory and compute four metrics: full and target controllability, control centrality and control profile (FTCP) that collectively determine the structural boundaries of the system's control space. We use these metrics to answer the following questions: How does the structure of a surface water network affect its controllability? How to efficiently control a preselected subset of the network? Which nodes have the highest control power? What types of topological structures dominate controllability? Finally, we demonstrate the structural controllability theory in the analysis of a wide range of surface water networks, such as tributary, deltaic, and braided river systems.
Decorated tensor network renormalization for lattice gauge theories and spin foam models
NASA Astrophysics Data System (ADS)
Dittrich, Bianca; Mizera, Sebastian; Steinhaus, Sebastian
2016-05-01
Tensor network techniques have proved to be powerful tools that can be employed to explore the large scale dynamics of lattice systems. Nonetheless, the redundancy of degrees of freedom in lattice gauge theories (and related models) poses a challenge for standard tensor network algorithms. We accommodate for such systems by introducing an additional structure decorating the tensor network. This allows to explicitly preserve the gauge symmetry of the system under coarse graining and straightforwardly interpret the fixed point tensors. We propose and test (for models with finite Abelian groups) a coarse graining algorithm for lattice gauge theories based on decorated tensor networks. We also point out that decorated tensor networks are applicable to other models as well, where they provide the advantage to give immediate access to certain expectation values and correlation functions.
A bottom-up strategy for establishment of EER in three Nordic countries - the role of networks
NASA Astrophysics Data System (ADS)
Edström, Kristina; Kolmos, Anette; Malmi, Lauri; Bernhard, Jonte; Andersson, Pernille
2018-03-01
This paper investigates the emergence of an engineering education research (EER) community in three Nordic countries: Denmark, Finland and Sweden. First, an overview of the current state of Nordic EER authorship is produced through statistics on international publication. Then, the history of EER and its precursor activities is described in three national narratives. These national storylines are tied together in a description of recent networking activities, aiming to strengthen the EER communities on the Nordic level. Taking these three perspectives together, and drawing on concepts from community of practice theory, network theory and learning network theory, we discuss factors behind the differences in the countries, and draw some conclusions about implications for networking activities in a heterogeneous community. Further, we discuss the role of networks for affording a joint identity.
A game theory-based trust measurement model for social networks.
Wang, Yingjie; Cai, Zhipeng; Yin, Guisheng; Gao, Yang; Tong, Xiangrong; Han, Qilong
2016-01-01
In social networks, trust is a complex social network. Participants in online social networks want to share information and experiences with as many reliable users as possible. However, the modeling of trust is complicated and application dependent. Modeling trust needs to consider interaction history, recommendation, user behaviors and so on. Therefore, modeling trust is an important focus for online social networks. We propose a game theory-based trust measurement model for social networks. The trust degree is calculated from three aspects, service reliability, feedback effectiveness, recommendation credibility, to get more accurate result. In addition, to alleviate the free-riding problem, we propose a game theory-based punishment mechanism for specific trust and global trust, respectively. We prove that the proposed trust measurement model is effective. The free-riding problem can be resolved effectively through adding the proposed punishment mechanism.
Radio and Optical Telescopes for School Students and Professional Astronomers
NASA Astrophysics Data System (ADS)
Hosmer, Laura; Langston, G.; Heatherly, S.; Towner, A. P.; Ford, J.; Simon, R. S.; White, S.; O'Neil, K. L.; Haipslip, J.; Reichart, D.
2013-01-01
The NRAO 20m telescope is now on-line as a part of UNC's Skynet worldwide telescope network. The NRAO is completing integration of radio astronomy tools with the Skynet web interface. We present the web interface and astronomy projects that allow students and astronomers from all over the country to become Radio Astronomers. The 20 meter radio telescope at NRAO in Green Bank, WV is dedicated to public education and also is part of an experiment in public funding for astronomy. The telescope has a fantastic new web-based interface, with priority queuing, accommodating priority for paying customers and enabling free use of otherwise unused time. This revival included many software and hardware improvements including automatic calibration and improved time integration resulting in improved data processing, and a new ultra high resolution spectrometer. This new spectrometer is optimized for very narrow spectral lines, which will allow astronomers to study complex molecules and very cold regions of space in remarkable detail. In accordance with focusing on broader impacts, many public outreach and high school education activities have been completed with many confirmed future activities. The 20 meter is now a fully automated, powerful tool capable of professional grade results available to anyone in the world. Drop by our poster and try out real-time telescope control!
ERIC Educational Resources Information Center
Wilks, Clarissa; Meara, Paul
2002-01-01
Examines the implications of the metaphor of the vocabulary network. Takes a formal approach to the exploration of this metaphor by applying the principles of graph theory to word association data to compare the relative densities of the first language and second language lexical networks. (Author/VWL)
Graph Theory-Based Pinning Synchronization of Stochastic Complex Dynamical Networks.
Li, Xiao-Jian; Yang, Guang-Hong
2017-02-01
This paper is concerned with the adaptive pinning synchronization problem of stochastic complex dynamical networks (CDNs). Based on algebraic graph theory and Lyapunov theory, pinning controller design conditions are derived, and the rigorous convergence analysis of synchronization errors in the probability sense is also conducted. Compared with the existing results, the topology structures of stochastic CDN are allowed to be unknown due to the use of graph theory. In particular, it is shown that the selection of nodes for pinning depends on the unknown lower bounds of coupling strengths. Finally, an example on a Chua's circuit network is given to validate the effectiveness of the theoretical results.
Experimental Observation of Two Features Unexpected from the Classical Theories of Rubber Elasticity
NASA Astrophysics Data System (ADS)
Nishi, Kengo; Fujii, Kenta; Chung, Ung-il; Shibayama, Mitsuhiro; Sakai, Takamasa
2017-12-01
Although the elastic modulus of a Gaussian chain network is thought to be successfully described by classical theories of rubber elasticity, such as the affine and phantom models, verification experiments are largely lacking owing to difficulties in precisely controlling of the network structure. We prepared well-defined model polymer networks experimentally, and measured the elastic modulus G for a broad range of polymer concentrations and connectivity probabilities, p . In our experiment, we observed two features that were distinct from those predicted by classical theories. First, we observed the critical behavior G ˜|p -pc|1.95 near the sol-gel transition. This scaling law is different from the prediction of classical theories, but can be explained by analogy between the electric conductivity of resistor networks and the elasticity of polymer networks. Here, pc is the sol-gel transition point. Furthermore, we found that the experimental G -p relations in the region above C* did not follow the affine or phantom theories. Instead, all the G /G0-p curves fell onto a single master curve when G was normalized by the elastic modulus at p =1 , G0. We show that the effective medium approximation for Gaussian chain networks explains this master curve.
Research Activities of the Northwest Laboratory for Integrated Systems
1987-04-06
table, and composite table (to assist evaluation of objects) are each built. The parse tree is also checked to make sure there are no meaningless...Stan- ford) as well as the Apollo DN series. All of these implementations require eight bit planes for effective use of color. Also supported are AED...time of intersection had not yet passed the queuing of the segment was delayed until that time. This algorithm had the effect of preserving the slope of
2006-09-27
Information Sciences Department, JHU/Applied Physics Laboratory, 12000 Johns Hopkins Road., Laurel, Maryland. 22104 ( PHB ) to meet the QoS requirements of...applications, e.g., (Keshav, 1997). However, to date, no work ex- ists to design and investigate PHB algorithms which simultaneously deliver QoS to...techniques to handle P&P requirements and rely upon standard, well studied QoS PHB , e.g., Weighted Round Robin, Class-Based Fair Queuing, etc., for han
Optimising resource management in neurorehabilitation.
Wood, Richard M; Griffiths, Jeff D; Williams, Janet E; Brouwers, Jakko
2014-01-01
To date, little research has been published regarding the effective and efficient management of resources (beds and staff) in neurorehabilitation, despite being an expensive service in limited supply. To demonstrate how mathematical modelling can be used to optimise service delivery, by way of a case study at a major 21 bed neurorehabilitation unit in the UK. An automated computer program for assigning weekly treatment sessions is developed. Queue modelling is used to construct a mathematical model of the hospital in terms of referral submissions to a waiting list, admission and treatment, and ultimately discharge. This is used to analyse the impact of hypothetical strategic decisions on a variety of performance measures and costs. The project culminates in a hybridised model of these two approaches, since a relationship is found between the number of therapy hours received each week (scheduling output) and length of stay (queuing model input). The introduction of the treatment scheduling program has substantially improved timetable quality (meaning a better and fairer service to patients) and has reduced employee time expended in its creation by approximately six hours each week (freeing up time for clinical work). The queuing model has been used to assess the effect of potential strategies, such as increasing the number of beds or employing more therapists. The use of mathematical modelling has not only optimised resources in the short term, but has allowed the optimality of longer term strategic decisions to be assessed.
Wang, Jinghong; Lo, Siuming; Wang, Qingsong; Sun, Jinhua; Mu, Honglin
2013-08-01
Crowd density is a key factor that influences the moving characteristics of a large group of people during a large-scale evacuation. In this article, the macro features of crowd flow and subsequent rescue strategies were considered, and a series of characteristic crowd densities that affect large-scale people movement, as well as the maximum bearing density when the crowd is extremely congested, were analyzed. On the basis of characteristic crowd densities, the queuing theory was applied to simulate crowd movement. Accordingly, the moving characteristics of the crowd and the effects of typical crowd density-which is viewed as the representation of the crowd's arrival intensity in front of the evacuation passageways-on rescue strategies was studied. Furthermore, a "risk axle of crowd density" is proposed to determine the efficiency of rescue strategies in a large-scale evacuation, i.e., whether the rescue strategies are able to effectively maintain or improve evacuation efficiency. Finally, through some rational hypotheses for the value of evacuation risk, a three-dimensional distribution of the evacuation risk is established to illustrate the risk axle of crowd density. This work aims to make some macro, but original, analysis on the risk of large-scale crowd evacuation from the perspective of the efficiency of rescue strategies. © 2012 Society for Risk Analysis.
Liu, Hongjie
2017-12-01
The epidemic of HIV/AIDS continues to spread among older adults and mid-age female sex workers (FSWs) over 35 years old. We used egocentric network data collected from three study sites in China to examine the applicability of Burt's Theory of Social Holes to study social support among mid-age FSWs. Using respondent-driven sampling, 1245 eligible mid-age FSWs were interviewed. Network structural holes were measured by network constraint and effective size. Three types of social networks were identified: family networks, workplace networks, and non-FSW networks. A larger effective size was significantly associated with a higher level of social support [regression coefficient (β) 5.43-10.59] across the three study samples. In contrast, a greater constraint was significantly associated with a lower level of social support (β -9.33 to -66.76). This study documents the applicability of the Theory of Structural Holes in studying network support among marginalized populations, such as FSWs.
PhD Thesis: String theory in the early universe
NASA Astrophysics Data System (ADS)
Gwyn, Rhiannon
2009-11-01
The intersection of string theory with cosmology is unavoidable in the early universe, and its exploration may shine light on both fields. In this thesis, three papers at this intersection are presented and reviewed, with the aim of providing a thorough and pedagogical guide to their results. First, we address the longstanding problem of finding a string theory realisation of the axion. Using warped compactifications in heterotic string theory, we show that the axion decay constant can be lowered to acceptable values by the warp factor. Next, we move to the subject of cosmic strings, whose network evolution could have important consequences for astrophysics and cosmology. In particular, there are quantitative differences between cosmic superstring networks and GUT cosmic string networks. We investigate the properties of cosmic superstring networks in warped backgrounds, giving the tension and properties of three-string junctions in these backgrounds. Finally, we examine the possibility that cosmic strings in heterotic string theory could be responsible for generating the galactic magnetic fields that seeded those observed today.
Choe, Eugenie; Lee, Tae Young; Kim, Minah; Hur, Ji-Won; Yoon, Youngwoo Bryan; Cho, Kang-Ik K; Kwon, Jun Soo
2018-03-26
It has been suggested that the mentalizing network and the mirror neuron system network support important social cognitive processes that are impaired in schizophrenia. However, the integrity and interaction of these two networks have not been sufficiently studied, and their effects on social cognition in schizophrenia remain unclear. Our study included 26 first-episode psychosis (FEP) patients and 26 healthy controls. We utilized resting-state functional connectivity to examine the a priori-defined mirror neuron system network and the mentalizing network and to assess the within- and between-network connectivities of the networks in FEP patients. We also assessed the correlation between resting-state functional connectivity measures and theory of mind performance. FEP patients showed altered within-network connectivity of the mirror neuron system network, and aberrant between-network connectivity between the mirror neuron system network and the mentalizing network. The within-network connectivity of the mirror neuron system network was noticeably correlated with theory of mind task performance in FEP patients. The integrity and interaction of the mirror neuron system network and the mentalizing network may be altered during the early stages of psychosis. Additionally, this study suggests that alterations in the integrity of the mirror neuron system network are highly related to deficient theory of mind in schizophrenia, and this problem would be present from the early stage of psychosis. Copyright © 2018 Elsevier B.V. All rights reserved.
Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach.
Alaerts, Kaat; Geerlings, Franca; Herremans, Lynn; Swinnen, Stephan P; Verhoeven, Judith; Sunaert, Stefan; Wenderoth, Nicole
2015-01-01
The ability to recognize, understand and interpret other's actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network. Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC). Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD. While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON.
Ding, Xiao Pan; Wu, Si Jia; Liu, Jiangang; Fu, Genyue; Lee, Kang
2017-09-21
The present study examined how different brain regions interact with each other during spontaneous honest vs. dishonest communication. More specifically, we took a complex network approach based on the graph-theory to analyze neural response data when children are spontaneously engaged in honest or dishonest acts. Fifty-nine right-handed children between 7 and 12 years of age participated in the study. They lied or told the truth out of their own volition. We found that lying decreased both the global and local efficiencies of children's functional neural network. This finding, for the first time, suggests that lying disrupts the efficiency of children's cortical network functioning. Further, it suggests that the graph theory based network analysis is a viable approach to study the neural development of deception.
NASA Technical Reports Server (NTRS)
Miller, M. Meghan
1998-01-01
Accomplishments: (1) Continues GPS monitoring of surface change during and following the fortuitous occurrence of the M(sub w) = 7.3 Landers earthquake in our network, in order to characterize earthquake dynamics and accelerated activity of related faults as far as 100's of kilometers along strike. (2) Integrates the geodetic constraints into consistent kinematic descriptions of the deformation field that can in turn be used to characterize the processes that drive geodynamics, including seismic cycle dynamics. In 1991, we installed and occupied a high precision GPS geodetic network to measure transform-related deformation that is partitioned from the Pacific - North America plate boundary northeastward through the Mojave Desert, via the Eastern California shear zone to the Walker Lane. The onset of the M(sub w) = 7.3 June 28, 1992, Landers, California, earthquake sequence within this network poses unique opportunities for continued monitoring of regional surface deformation related to the culmination of a major seismic cycle, characterization of the dynamic behavior of continental lithosphere during the seismic sequence, and post-seismic transient deformation. During the last year, we have reprocessed all three previous epochs for which JPL fiducial free point positioning products available and are queued for the remaining needed products, completed two field campaigns monitoring approx. 20 sites (October 1995 and September 1996), begun modeling by development of a finite element mesh based on network station locations, and developed manuscripts dealing with both the Landers-related transient deformation at the latitude of Lone Pine and the velocity field of the whole experiment. We are currently deploying a 1997 observation campaign (June 1997). We use GPS geodetic studies to characterize deformation in the Mojave Desert region and related structural domains to the north, and geophysical modeling of lithospheric behavior. The modeling is constrained by our existing and continued GPS measurements, which will provide much needed data on far-field strain accumulation across the region and on the deformational response of continental lithosphere during and following a large earthquake, forming the basis for kinematic and dynamic modeling of secular and seismic-cycle deformation. GPS geodesy affords both regional coverage and high precision that uniquely bear on these problems.
Valente, Thomas W; Pitts, Stephanie R
2017-03-20
The use of social network theory and analysis methods as applied to public health has expanded greatly in the past decade, yielding a significant academic literature that spans almost every conceivable health issue. This review identifies several important theoretical challenges that confront the field but also provides opportunities for new research. These challenges include (a) measuring network influences, (b) identifying appropriate influence mechanisms, (c) the impact of social media and computerized communications, (d) the role of networks in evaluating public health interventions, and (e) ethics. Next steps for the field are outlined and the need for funding is emphasized. Recently developed network analysis techniques, technological innovations in communication, and changes in theoretical perspectives to include a focus on social and environmental behavioral influences have created opportunities for new theory and ever broader application of social networks to public health topics.
ERIC Educational Resources Information Center
Debnath, Lokenath
2010-01-01
This article is essentially devoted to a brief historical introduction to Euler's formula for polyhedra, topology, theory of graphs and networks with many examples from the real-world. Celebrated Konigsberg seven-bridge problem and some of the basic properties of graphs and networks for some understanding of the macroscopic behaviour of real…
Statistical Inference for Cultural Consensus Theory
2014-02-24
Social Network Conference XXXII , Redondo Beach, California, March 2012. Agrawal, K. (Presenter), and Batchelder, W. H. Cultural Consensus Theory...Aggregating Complete Signed Graphs Under a Balance Constraint -- Part 2. International Sunbelt Social Network Conference XXXII , Redondo Beach
ERIC Educational Resources Information Center
Schindler, Maike; Rott, Benjamin
2017-01-01
Giftedness is an increasingly important research topic in educational sciences and mathematics education in particular. In this paper, we contribute to further theorizing mathematical giftedness through illustrating how networking processes can be conducted and illustrating their potential benefits. The paper focuses on two theories: Renzulli's…
2008-12-01
1979; Wasserman and Faust, 1994). SNA thus relies heavily on graph theory to make predictions about network structure and thus social behavior...becomes a tool for increasing the specificity of theory , thinking through the theoretical implications, and generating testable predictions. In...to summarize Construct and its roots in constructural sociological theory . We discover that the (LPM) provides a mathematical bridge between
Koch, Ina; Junker, Björn H; Heiner, Monika
2005-04-01
Because of the complexity of metabolic networks and their regulation, formal modelling is a useful method to improve the understanding of these systems. An essential step in network modelling is to validate the network model. Petri net theory provides algorithms and methods, which can be applied directly to metabolic network modelling and analysis in order to validate the model. The metabolism between sucrose and starch in the potato tuber is of great research interest. Even if the metabolism is one of the best studied in sink organs, it is not yet fully understood. We provide an approach for model validation of metabolic networks using Petri net theory, which we demonstrate for the sucrose breakdown pathway in the potato tuber. We start with hierarchical modelling of the metabolic network as a Petri net and continue with the analysis of qualitative properties of the network. The results characterize the net structure and give insights into the complex net behaviour.
Identity theory and personality theory: mutual relevance.
Stryker, Sheldon
2007-12-01
Some personality psychologists have found a structural symbolic interactionist frame and identity theory relevant to their work. This frame and theory, developed in sociology, are first reviewed. Emphasized in the review are a multiple identity conception of self, identities as internalized expectations derived from roles embedded in organized networks of social interaction, and a view of social structures as facilitators in bringing people into networks or constraints in keeping them out, subsequently, attention turns to a discussion of the mutual relevance of structural symbolic interactionism/identity theory and personality theory, looking to extensions of the current literature on these topics.
Psychology and social networks: a dynamic network theory perspective.
Westaby, James D; Pfaff, Danielle L; Redding, Nicholas
2014-04-01
Research on social networks has grown exponentially in recent years. However, despite its relevance, the field of psychology has been relatively slow to explain the underlying goal pursuit and resistance processes influencing social networks in the first place. In this vein, this article aims to demonstrate how a dynamic network theory perspective explains the way in which social networks influence these processes and related outcomes, such as goal achievement, performance, learning, and emotional contagion at the interpersonal level of analysis. The theory integrates goal pursuit, motivation, and conflict conceptualizations from psychology with social network concepts from sociology and organizational science to provide a taxonomy of social network role behaviors, such as goal striving, system supporting, goal preventing, system negating, and observing. This theoretical perspective provides psychologists with new tools to map social networks (e.g., dynamic network charts), which can help inform the development of change interventions. Implications for social, industrial-organizational, and counseling psychology as well as conflict resolution are discussed, and new opportunities for research are highlighted, such as those related to dynamic network intelligence (also known as cognitive accuracy), levels of analysis, methodological/ethical issues, and the need to theoretically broaden the study of social networking and social media behavior. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
Peer network influence on intimate partner violence perpetration among urban Tanzanian men.
Mulawa, Marta I; Kajula, Lusajo J; Maman, Suzanne
2018-04-01
Male perpetration of intimate partner violence (IPV) against women in Tanzania is widespread. Theory and empirical evidence suggest peer networks may play an important role in shaping IPV perpetration, although research on this topic in sub-Saharan Africa is limited. Grounded in social learning theory, social influence theory, and the theory of gender and power, the purpose of this study was to examine whether and how peer networks influence men's perpetration of IPV in Dar es Salaam, Tanzania. We conducted in-depth interviews (n = 40) with a sub-sample of 20 men enrolled in the control condition of an ongoing cluster-randomised controlled trial. We purposively sampled participants who previously reported perpetrating physical IPV. To analyse the data, we generated narrative summaries and conducted thematic and interpretative coding. We saw no evidence that men self-selected into peer networks with certain values or behaviours. Rather, men described several mechanisms through which their peers influenced the perpetration of IPV, including: (1) the internalisation of peer network norms, (2) pressure to conform to peer network norms and (3) the direct involvement of peers in shaping couple power dynamics. Our findings suggest that peer networks influence men's perpetration of IPV and should be targeted in future programmes and interventions.
Intrinsic connectivity in the human brain does not reveal networks for ‘basic’ emotions
Lindquist, Kristen A.; Dickerson, Bradford C.; Barrett, Lisa Feldman
2015-01-01
We tested two competing models for the brain basis of emotion, the basic emotion theory and the conceptual act theory of emotion, using resting-state functional connectivity magnetic resonance imaging (rs-fcMRI). The basic emotion view hypothesizes that anger, sadness, fear, disgust and happiness each arise from a brain network that is innate, anatomically constrained and homologous in other animals. The conceptual act theory of emotion hypothesizes that an instance of emotion is a brain state constructed from the interaction of domain-general, core systems within the brain such as the salience, default mode and frontoparietal control networks. Using peak coordinates derived from a meta-analysis of task-evoked emotion fMRI studies, we generated a set of whole-brain rs-fcMRI ‘discovery’ maps for each emotion category and examined the spatial overlap in their conjunctions. Instead of discovering a specific network for each emotion category, variance in the discovery maps was accounted for by the known domain-general network. Furthermore, the salience network is observed as part of every emotion category. These results indicate that specific networks for each emotion do not exist within the intrinsic architecture of the human brain and instead support the conceptual act theory of emotion. PMID:25680990
Graph theory network function in Parkinson's disease assessed with electroencephalography.
Utianski, Rene L; Caviness, John N; van Straaten, Elisabeth C W; Beach, Thomas G; Dugger, Brittany N; Shill, Holly A; Driver-Dunckley, Erika D; Sabbagh, Marwan N; Mehta, Shyamal; Adler, Charles H; Hentz, Joseph G
2016-05-01
To determine what differences exist in graph theory network measures derived from electroencephalography (EEG), between Parkinson's disease (PD) patients who are cognitively normal (PD-CN) and matched healthy controls; and between PD-CN and PD dementia (PD-D). EEG recordings were analyzed via graph theory network analysis to quantify changes in global efficiency and local integration. This included minimal spanning tree analysis. T-tests and correlations were used to assess differences between groups and assess the relationship with cognitive performance. Network measures showed increased local integration across all frequency bands between control and PD-CN; in contrast, decreased local integration occurred in PD-D when compared to PD-CN in the alpha1 frequency band. Differences found in PD-MCI mirrored PD-D. Correlations were found between network measures and assessments of global cognitive performance in PD. Our results reveal distinct patterns of band and network measure type alteration and breakdown for PD, as well as with cognitive decline in PD. These patterns suggest specific ways that interaction between cortical areas becomes abnormal and contributes to PD symptoms at various stages. Graph theory analysis by EEG suggests that network alteration and breakdown are robust attributes of PD cortical dysfunction pathophysiology. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Potential Theory for Directed Networks
Zhang, Qian-Ming; Lü, Linyuan; Wang, Wen-Qiang; Zhou, Tao
2013-01-01
Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i) We propose a new mechanism for the local organization of directed networks; (ii) We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation. PMID:23408979
Group field theory and tensor networks: towards a Ryu–Takayanagi formula in full quantum gravity
NASA Astrophysics Data System (ADS)
Chirco, Goffredo; Oriti, Daniele; Zhang, Mingyi
2018-06-01
We establish a dictionary between group field theory (thus, spin networks and random tensors) states and generalized random tensor networks. Then, we use this dictionary to compute the Rényi entropy of such states and recover the Ryu–Takayanagi formula, in two different cases corresponding to two different truncations/approximations, suggested by the established correspondence.
An Attractor Network in the Hippocampus: Theory and Neurophysiology
ERIC Educational Resources Information Center
Rolls, Edmund T.
2007-01-01
A quantitative computational theory of the operation of the CA3 system as an attractor or autoassociation network is described. Based on the proposal that CA3-CA3 autoassociative networks are important for episodic or event memory in which space is a component (place in rodents and spatial view in primates), it has been shown behaviorally that the…
Productivity improvement through cycle time analysis
NASA Astrophysics Data System (ADS)
Bonal, Javier; Rios, Luis; Ortega, Carlos; Aparicio, Santiago; Fernandez, Manuel; Rosendo, Maria; Sanchez, Alejandro; Malvar, Sergio
1996-09-01
A cycle time (CT) reduction methodology has been developed in the Lucent Technology facility (former AT&T) in Madrid, Spain. It is based on a comparison of the contribution of each process step in each technology with a target generated by a cycle time model. These targeted cycle times are obtained using capacity data of the machines processing those steps, queuing theory and theory of constrains (TOC) principles (buffers to protect bottleneck and low cycle time/inventory everywhere else). Overall efficiency equipment (OEE) like analysis is done in the machine groups with major differences between their target cycle time and real values. Comparisons between the current value of the parameters that command their capacity (process times, availability, idles, reworks, etc.) and the engineering standards are done to detect the cause of exceeding their contribution to the cycle time. Several friendly and graphical tools have been developed to track and analyze those capacity parameters. Specially important have showed to be two tools: ASAP (analysis of scheduling, arrivals and performance) and performer which analyzes interrelation problems among machines procedures and direct labor. The performer is designed for a detailed and daily analysis of an isolate machine. The extensive use of this tool by the whole labor force has demonstrated impressive results in the elimination of multiple small inefficiencies with a direct positive implications on OEE. As for ASAP, it shows the lot in process/queue for different machines at the same time. ASAP is a powerful tool to analyze the product flow management and the assigned capacity for interdependent operations like the cleaning and the oxidation/diffusion. Additional tools have been developed to track, analyze and improve the process times and the availability.
Issues in Semantic Memory: A Response to Glass and Holyoak. Technical Report No. 101.
ERIC Educational Resources Information Center
Shoben, Edward J.; And Others
Glass and Holyoak (1975) have raised two issues related to the distinction between set-theoretic and network theories of semantic memory, contending that: (a) their version of a network theory, the Marker Search model, is conceptually and empirically superior to the Feature Comparison model version of a set-theoretic theory; and (b) the contrast…
Functional Organization of the Action Observation Network in Autism: A Graph Theory Approach
Alaerts, Kaat; Geerlings, Franca; Herremans, Lynn; Swinnen, Stephan P.; Verhoeven, Judith; Sunaert, Stefan; Wenderoth, Nicole
2015-01-01
Background The ability to recognize, understand and interpret other’s actions and emotions has been linked to the mirror system or action-observation-network (AON). Although variations in these abilities are prevalent in the neuro-typical population, persons diagnosed with autism spectrum disorders (ASD) have deficits in the social domain and exhibit alterations in this neural network. Method Here, we examined functional network properties of the AON using graph theory measures and region-to-region functional connectivity analyses of resting-state fMRI-data from adolescents and young adults with ASD and typical controls (TC). Results Overall, our graph theory analyses provided convergent evidence that the network integrity of the AON is altered in ASD, and that reductions in network efficiency relate to reductions in overall network density (i.e., decreased overall connection strength). Compared to TC, individuals with ASD showed significant reductions in network efficiency and increased shortest path lengths and centrality. Importantly, when adjusting for overall differences in network density between ASD and TC groups, participants with ASD continued to display reductions in network integrity, suggesting that also network-level organizational properties of the AON are altered in ASD. Conclusion While differences in empirical connectivity contributed to reductions in network integrity, graph theoretical analyses provided indications that also changes in the high-level network organization reduced integrity of the AON. PMID:26317222
Flory-Stockmayer analysis on reprocessable polymer networks
NASA Astrophysics Data System (ADS)
Li, Lingqiao; Chen, Xi; Jin, Kailong; Torkelson, John
Reprocessable polymer networks can undergo structure rearrangement through dynamic chemistries under proper conditions, making them a promising candidate for recyclable crosslinked materials, e.g. tires. This research field has been focusing on various chemistries. However, there has been lacking of an essential physical theory explaining the relationship between abundancy of dynamic linkages and reprocessability. Based on the classical Flory-Stockmayer analysis on network gelation, we developed a similar analysis on reprocessable polymer networks to quantitatively predict the critical condition for reprocessability. Our theory indicates that it is unnecessary for all bonds to be dynamic to make the resulting network reprocessable. As long as there is no percolated permanent network in the system, the material can fully rearrange. To experimentally validate our theory, we used a thiol-epoxy network model system with various dynamic linkage compositions. The stress relaxation behavior of resulting materials supports our theoretical prediction: only 50 % of linkages between crosslinks need to be dynamic for a tri-arm network to be reprocessable. Therefore, this analysis provides the first fundamental theoretical platform for designing and evaluating reprocessable polymer networks. We thank McCormick Research Catalyst Award Fund and ISEN cluster fellowship (L. L.) for funding support.
Reliability analysis in interdependent smart grid systems
NASA Astrophysics Data System (ADS)
Peng, Hao; Kan, Zhe; Zhao, Dandan; Han, Jianmin; Lu, Jianfeng; Hu, Zhaolong
2018-06-01
Complex network theory is a useful way to study many real complex systems. In this paper, a reliability analysis model based on complex network theory is introduced in interdependent smart grid systems. In this paper, we focus on understanding the structure of smart grid systems and studying the underlying network model, their interactions, and relationships and how cascading failures occur in the interdependent smart grid systems. We propose a practical model for interdependent smart grid systems using complex theory. Besides, based on percolation theory, we also study the effect of cascading failures effect and reveal detailed mathematical analysis of failure propagation in such systems. We analyze the reliability of our proposed model caused by random attacks or failures by calculating the size of giant functioning components in interdependent smart grid systems. Our simulation results also show that there exists a threshold for the proportion of faulty nodes, beyond which the smart grid systems collapse. Also we determine the critical values for different system parameters. In this way, the reliability analysis model based on complex network theory can be effectively utilized for anti-attack and protection purposes in interdependent smart grid systems.
The need for theory to guide concussion research.
Molfese, Dennis L
2015-01-01
Although research into concussion has greatly expanded over the past decade, progress in identifying the mechanisms and consequences of head injury and recovery are largely absent. Instead, data are accumulated without the guidance of a systematic theory to direct research questions or generate testable hypotheses. As part of this special issue on sports concussion, I advance a theory that emphasizes changes in spatial and temporal distributions of the brain's neural networks during normal learning and the disruptions of these networks following injury. Specific predictions are made regarding both the development of the network as well as its breakdown following injury.
ERIC Educational Resources Information Center
Karimi, Leila; Khodabandelou, Rouhollah; Ehsani, Maryam; Ahmad, Muhammad
2014-01-01
Drawing from the Uses and Gratifications Theory, this study examined the Gratification Sought and the Gratification Obtained from using Social Networking Sites among Iranian, Malaysian, British, and South African higher education students. This comparison allowed to drawing conclusions about how social networking sites fulfill users' needs with…
ERIC Educational Resources Information Center
Hung, Aaron Chia Yuan
2016-01-01
The paper uses actor-network theory (ANT) to analyze the sociotechnical networks of three groups of adolescents who played online games in different physical and social contexts. These include: an internet café, which allowed the players to be co-present; a personal laptop, which gave the player more control over how he played; and at home through…
Rethinking Traffic Management: Design of Optimizable Networks
2008-06-01
Though this paper used optimization theory to design and analyze DaVinci , op- timization theory is one of many possible tools to enable a grounded...dynamically allocate bandwidth shares. The distributed protocols can be implemented using DaVinci : Dynamically Adaptive VIrtual Networks for a Customized...Internet. In DaVinci , each virtual network runs traffic-management protocols optimized for a traffic class, and link bandwidth is dynamically allocated
Theory and Experimental and Chemical Instabilities
1989-01-31
Thresholds, Hysteresis, and Neuromodulation of Signal-to-Noise; and Statistical-Mechanical Theory of Many-body Effects in Reaction Rates. T Ic 2 UL3...submitted to the Journal of Physical Chemistry. 6. Noise in Neural Networks: Thresholds, Hysteresis, and Neuromodulation of Signal-to-Noise. We study a...neural-network model including Gaussian noise, higher-order neuronal interactions, and neuromodulation . For a first-order network, there is a
NASA Astrophysics Data System (ADS)
Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi
2012-10-01
In this Letter, we propose a framework to transform a complex network to a time series. The transformation from complex networks to time series is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic time series, small-world networks to noisy periodic time series, and random networks to random time series. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices.
The investigation of social networks based on multi-component random graphs
NASA Astrophysics Data System (ADS)
Zadorozhnyi, V. N.; Yudin, E. B.
2018-01-01
The methods of non-homogeneous random graphs calibration are developed for social networks simulation. The graphs are calibrated by the degree distributions of the vertices and the edges. The mathematical foundation of the methods is formed by the theory of random graphs with the nonlinear preferential attachment rule and the theory of Erdôs-Rényi random graphs. In fact, well-calibrated network graph models and computer experiments with these models would help developers (owners) of the networks to predict their development correctly and to choose effective strategies for controlling network projects.
Using Target Network Modelling to Increase Battlespace Agility
2013-06-01
Moffat, James. (2003) Complexity Theory and Network Centric Warfare. Washington DC: CCRP Moore, David T.. Sensemaking : A Structure for an Intelligence...Ted Hopf’s “Promise of Constructivism in International Relations Theory ” presented in International Security in 1998; and Adler 1998. 5 Look to...of warfighting within a doctrinal framework. Based on 10 years of research12 informed by social theory , experimentation, NATO doctrinal studies and
Linear network representation of multistate models of transport.
Sandblom, J; Ring, A; Eisenman, G
1982-01-01
By introducing external driving forces in rate-theory models of transport we show how the Eyring rate equations can be transformed into Ohm's law with potentials that obey Kirchhoff's second law. From such a formalism the state diagram of a multioccupancy multicomponent system can be directly converted into linear network with resistors connecting nodal (branch) points and with capacitances connecting each nodal point with a reference point. The external forces appear as emf or current generators in the network. This theory allows the algebraic methods of linear network theory to be used in solving the flux equations for multistate models and is particularly useful for making proper simplifying approximation in models of complex membrane structure. Some general properties of linear network representation are also deduced. It is shown, for instance, that Maxwell's reciprocity relationships of linear networks lead directly to Onsager's relationships in the near equilibrium region. Finally, as an example of the procedure, the equivalent circuit method is used to solve the equations for a few transport models. PMID:7093425
GTRF: a game theory approach for regulating node behavior in real-time wireless sensor networks.
Lin, Chi; Wu, Guowei; Pirozmand, Poria
2015-06-04
The selfish behaviors of nodes (or selfish nodes) cause packet loss, network congestion or even void regions in real-time wireless sensor networks, which greatly decrease the network performance. Previous methods have focused on detecting selfish nodes or avoiding selfish behavior, but little attention has been paid to regulating selfish behavior. In this paper, a Game Theory-based Real-time & Fault-tolerant (GTRF) routing protocol is proposed. GTRF is composed of two stages. In the first stage, a game theory model named VA is developed to regulate nodes' behaviors and meanwhile balance energy cost. In the second stage, a jumping transmission method is adopted, which ensures that real-time packets can be successfully delivered to the sink before a specific deadline. We prove that GTRF theoretically meets real-time requirements with low energy cost. Finally, extensive simulations are conducted to demonstrate the performance of our scheme. Simulation results show that GTRF not only balances the energy cost of the network, but also prolongs network lifetime.
He, Yongqun
2016-06-01
Compared with controlled terminologies ( e.g. , MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network ( i.e. , OneNet). A new "OneNet effectiveness" tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research.
SISL and SIRL: Two knowledge dissemination models with leader nodes on cooperative learning networks
NASA Astrophysics Data System (ADS)
Li, Jingjing; Zhang, Yumei; Man, Jiayu; Zhou, Yun; Wu, Xiaojun
2017-02-01
Cooperative learning is one of the most effective teaching methods, which has been widely used. Students' mutual contact forms a cooperative learning network in this process. Our previous research demonstrated that the cooperative learning network has complex characteristics. This study aims to investigating the dynamic spreading process of the knowledge in the cooperative learning network and the inspiration of leaders in this process. To this end, complex network transmission dynamics theory is utilized to construct the knowledge dissemination model of a cooperative learning network. Based on the existing epidemic models, we propose a new susceptible-infected-susceptible-leader (SISL) model that considers both students' forgetting and leaders' inspiration, and a susceptible-infected-removed-leader (SIRL) model that considers students' interest in spreading and leaders' inspiration. The spreading threshold λcand its impact factors are analyzed. Then, numerical simulation and analysis are delivered to reveal the dynamic transmission mechanism of knowledge and leaders' role. This work is of great significance to cooperative learning theory and teaching practice. It also enriches the theory of complex network transmission dynamics.
Cancer Theory from Systems Biology Point of View
NASA Astrophysics Data System (ADS)
Wang, Gaowei; Tang, Ying; Yuan, Ruoshi; Ao, Ping
In our previous work, we have proposed a novel cancer theory, endogenous network theory, to understand mechanism underlying cancer genesis and development. Recently, we apply this theory to hepatocellular carcinoma (HCC). A core endogenous network of hepatocyte was established by integrating the current understanding of hepatocyte at molecular level. Quantitative description of the endogenous network consisted of a set of stochastic differential equations which could generate many local attractors with obvious or non-obvious biological functions. By comparing with clinical observation and experimental data, the results showed that two robust attractors from the model reproduced the main known features of normal hepatocyte and cancerous hepatocyte respectively at both modular and molecular level. In light of our theory, the genesis and progression of cancer is viewed as transition from normal attractor to HCC attractor. A set of new insights on understanding cancer genesis and progression, and on strategies for cancer prevention, cure, and care were provided.
Best, Allan; Berland, Alex; Greenhalgh, Trisha; Bourgeault, Ivy L; Saul, Jessie E; Barker, Brittany
2018-03-19
Purpose The purpose of this paper is to present a case study of the World Health Organization's Global Healthcare Workforce Alliance (GHWA). Based on a commissioned evaluation of GHWA, it applies network theory and key concepts from systems thinking to explore network emergence, effectiveness, and evolution to over a ten-year period. The research was designed to provide high-level strategic guidance for further evolution of global governance in human resources for health (HRH). Design/methodology/approach Methods included a review of published literature on HRH governance and current practice in the field and an in-depth case study whose main data sources were relevant GHWA background documents and key informant interviews with GHWA leaders, staff, and stakeholders. Sampling was purposive and at a senior level, focusing on board members, executive directors, funders, and academics. Data were analyzed thematically with reference to systems theory and Shiffman's theory of network development. Findings Five key lessons emerged: effective management and leadership are critical; networks need to balance "tight" and "loose" approaches to their structure and processes; an active communication strategy is key to create and maintain support; the goals, priorities, and membership must be carefully focused; and the network needs to support shared measurement of progress on agreed-upon goals. Shiffman's middle-range network theory is a useful tool when guided by the principles of complex systems that illuminate dynamic situations and shifting interests as global alliances evolve. Research limitations/implications This study was implemented at the end of the ten-year funding cycle. A more continuous evaluation throughout the term would have provided richer understanding of issues. Experience and perspectives at the country level were not assessed. Practical implications Design and management of large, complex networks requires ongoing attention to key issues like leadership, and flexible structures and processes to accommodate the dynamic reality of these networks. Originality/value This case study builds on growing interest in the role of networks to foster large-scale change. The particular value rests on the longitudinal perspective on the evolution of a large, complex global network, and the use of theory to guide understanding.
Criticism of generally accepted fundamentals and methodologies of traffic and transportation theory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kerner, Boris S.
It is explained why the set of the fundamental empirical features of traffic breakdown (a transition from free flow to congested traffic) should be the empirical basis for any traffic and transportation theory that can be reliable used for control and optimization in traffic networks. It is shown that generally accepted fundamentals and methodologies of traffic and transportation theory are not consistent with the set of the fundamental empirical features of traffic breakdown at a highway bottleneck. To these fundamentals and methodologies of traffic and transportation theory belong (i) Lighthill-Whitham-Richards (LWR) theory, (ii) the General Motors (GM) model class (formore » example, Herman, Gazis et al. GM model, Gipps’s model, Payne’s model, Newell’s optimal velocity (OV) model, Wiedemann’s model, Bando et al. OV model, Treiber’s IDM, Krauß’s model), (iii) the understanding of highway capacity as a particular stochastic value, and (iv) principles for traffic and transportation network optimization and control (for example, Wardrop’s user equilibrium (UE) and system optimum (SO) principles). Alternatively to these generally accepted fundamentals and methodologies of traffic and transportation theory, we discuss three-phase traffic theory as the basis for traffic flow modeling as well as briefly consider the network breakdown minimization (BM) principle for the optimization of traffic and transportation networks with road bottlenecks.« less
A high performance hierarchical storage management system for the Canadian tier-1 centre at TRIUMF
NASA Astrophysics Data System (ADS)
Deatrich, D. C.; Liu, S. X.; Tafirout, R.
2010-04-01
We describe in this paper the design and implementation of Tapeguy, a high performance non-proprietary Hierarchical Storage Management (HSM) system which is interfaced to dCache for efficient tertiary storage operations. The system has been successfully implemented at the Canadian Tier-1 Centre at TRIUMF. The ATLAS experiment will collect a large amount of data (approximately 3.5 Petabytes each year). An efficient HSM system will play a crucial role in the success of the ATLAS Computing Model which is driven by intensive large-scale data analysis activities that will be performed on the Worldwide LHC Computing Grid infrastructure continuously. Tapeguy is Perl-based. It controls and manages data and tape libraries. Its architecture is scalable and includes Dataset Writing control, a Read-back Queuing mechanism and I/O tape drive load balancing as well as on-demand allocation of resources. A central MySQL database records metadata information for every file and transaction (for audit and performance evaluation), as well as an inventory of library elements. Tapeguy Dataset Writing was implemented to group files which are close in time and of similar type. Optional dataset path control dynamically allocates tape families and assign tapes to it. Tape flushing is based on various strategies: time, threshold or external callbacks mechanisms. Tapeguy Read-back Queuing reorders all read requests by using an elevator algorithm, avoiding unnecessary tape loading and unloading. Implementation of priorities will guarantee file delivery to all clients in a timely manner.
Complex Network Simulation of Forest Network Spatial Pattern in Pearl River Delta
NASA Astrophysics Data System (ADS)
Zeng, Y.
2017-09-01
Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network's power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network's degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network's main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.
Mears, David; Pollard, Harvey B
2016-06-01
Over the past 15 years, the emerging field of network science has revealed the key features of brain networks, which include small-world topology, the presence of highly connected hubs, and hierarchical modularity. The value of network studies of the brain is underscored by the range of network alterations that have been identified in neurological and psychiatric disorders, including epilepsy, depression, Alzheimer's disease, schizophrenia, and many others. Here we briefly summarize the concepts of graph theory that are used to quantify network properties and describe common experimental approaches for analysis of brain networks of structural and functional connectivity. These range from tract tracing to functional magnetic resonance imaging, diffusion tensor imaging, electroencephalography, and magnetoencephalography. We then summarize the major findings from the application of graph theory to nervous systems ranging from Caenorhabditis elegans to more complex primate brains, including man. Focusing, then, on studies involving the amygdala, a brain region that has attracted intense interest as a center for emotional processing, fear, and motivation, we discuss the features of the amygdala in brain networks for fear conditioning and emotional perception. Finally, to highlight the utility of graph theory for studying dysfunction of the amygdala in mental illness, we review data with regard to changes in the hub properties of the amygdala in brain networks of patients with depression. We suggest that network studies of the human brain may serve to focus attention on regions and connections that act as principal drivers and controllers of brain function in health and disease. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.
Networks in cognitive science.
Baronchelli, Andrea; Ferrer-i-Cancho, Ramon; Pastor-Satorras, Romualdo; Chater, Nick; Christiansen, Morten H
2013-07-01
Networks of interconnected nodes have long played a key role in Cognitive Science, from artificial neural networks to spreading activation models of semantic memory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions, and collaborations among scientists. Today, the inclusion of network theory into Cognitive Sciences, and the expansion of complex-systems science, promises to significantly change the way in which the organization and dynamics of cognitive and behavioral processes are understood. In this paper, we review recent contributions of network theory at different levels and domains within the Cognitive Sciences. Copyright © 2013 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Galey, Sarah; Youngs, Peter
2014-01-01
Scholars have developed a wide range of theories to explain both stability and change in policy subsystems. In recent years, a burgeoning literature has emerged that focuses on the application of network analysis in policy research, more formally known as Policy Network Analysis (PNA). This approach, while still developing, has great potential as…
A key heterogeneous structure of fractal networks based on inverse renormalization scheme
NASA Astrophysics Data System (ADS)
Bai, Yanan; Huang, Ning; Sun, Lina
2018-06-01
Self-similarity property of complex networks was found by the application of renormalization group theory. Based on this theory, network topologies can be classified into universality classes in the space of configurations. In return, through inverse renormalization scheme, a given primitive structure can grow into a pure fractal network, then adding different types of shortcuts, it exhibits different characteristics of complex networks. However, the effect of primitive structure on networks structural property has received less attention. In this paper, we introduce a degree variance index to measure the dispersion of nodes degree in the primitive structure, and investigate the effect of the primitive structure on network structural property quantified by network efficiency. Numerical simulations and theoretical analysis show a primitive structure is a key heterogeneous structure of generated networks based on inverse renormalization scheme, whether or not adding shortcuts, and the network efficiency is positively correlated with degree variance of the primitive structure.
Identifying Key Actors in Heterogeneous Networks
2017-11-29
analysis (SNA) and game theory (GT) to improve accuracy for detecting significant or “powerful” actors within a total actor space when both resource...coalesce in order to achieve a desired outcome. Cooperative game theory (CGT) models of coalition formation are based on two limiting assumptions: that...demonstration of a new approach for synthesizing social network analysis and game theory. The ultimate goal of this research agenda is to generalize
Conceptual Developments in Schema Theory.
ERIC Educational Resources Information Center
Bigenho, Frederick W., Jr.
The conceptual development of schema theory, the way an individual organizes knowledge, is discussed, reviewing a range of perspectives regarding schema. Schema has been defined as the interfacing of incoming information with prior knowledge, clustered in networks. These networks comprise a superordinate concept and supporting information. The…
Empiricism and theorizing in epidemiology and social network analysis.
Rothenberg, Richard; Costenbader, Elizabeth
2011-01-01
The connection between theory and data is an iterative one. In principle, each is informed by the other: data provide the basis for theory that in turn generates the need for new information. This circularity is reflected in the notion of abduction, a concept that focuses on the space between induction (generating theory from data) and deduction (testing theory with data). Einstein, in the 1920s, placed scientific creativity in that space. In the field of social network analysis, some remarkable theory has been developed, accompanied by sophisticated tools to develop, extend, and test the theory. At the same time, important empirical data have been generated that provide insight into transmission dynamics. Unfortunately, the connection between them is often tenuous and the iterative loop is frayed. This circumstance may arise both from data deficiencies and from the ease with which data can be created by simulation. But for whatever reason, theory and empirical data often occupy different orbits. Fortunately, the relationship, while frayed, is not broken, to which several recent analyses merging theory and extant data will attest. Their further rapprochement in the field of social network analysis could provide the field with a more creative approach to experimentation and inference.
Empiricism and Theorizing in Epidemiology and Social Network Analysis
Rothenberg, Richard; Costenbader, Elizabeth
2011-01-01
The connection between theory and data is an iterative one. In principle, each is informed by the other: data provide the basis for theory that in turn generates the need for new information. This circularity is reflected in the notion of abduction, a concept that focuses on the space between induction (generating theory from data) and deduction (testing theory with data). Einstein, in the 1920s, placed scientific creativity in that space. In the field of social network analysis, some remarkable theory has been developed, accompanied by sophisticated tools to develop, extend, and test the theory. At the same time, important empirical data have been generated that provide insight into transmission dynamics. Unfortunately, the connection between them is often tenuous and the iterative loop is frayed. This circumstance may arise both from data deficiencies and from the ease with which data can be created by simulation. But for whatever reason, theory and empirical data often occupy different orbits. Fortunately, the relationship, while frayed, is not broken, to which several recent analyses merging theory and extant data will attest. Their further rapprochement in the field of social network analysis could provide the field with a more creative approach to experimentation and inference. PMID:21127746
Theorising big IT programmes in healthcare: strong structuration theory meets actor-network theory.
Greenhalgh, Trisha; Stones, Rob
2010-05-01
The UK National Health Service is grappling with various large and controversial IT programmes. We sought to develop a sharper theoretical perspective on the question "What happens - at macro-, meso- and micro-level - when government tries to modernise a health service with the help of big IT?" Using examples from data fragments at the micro-level of clinical work, we considered how structuration theory and actor-network theory (ANT) might be combined to inform empirical investigation. Giddens (1984) argued that social structures and human agency are recursively linked and co-evolve. ANT studies the relationships that link people and technologies in dynamic networks. It considers how discourses become inscribed in data structures and decision models of software, making certain network relations irreversible. Stones' (2005) strong structuration theory (SST) is a refinement of Giddens' work, systematically concerned with empirical research. It views human agents as linked in dynamic networks of position-practices. A quadripartite approcach considers [a] external social structures (conditions for action); [b] internal social structures (agents' capabilities and what they 'know' about the social world); [c] active agency and actions and [d] outcomes as they feed back on the position-practice network. In contrast to early structuration theory and ANT, SST insists on disciplined conceptual methodology and linking this with empirical evidence. In this paper, we adapt SST for the study of technology programmes, integrating elements from material interactionism and ANT. We argue, for example, that the position-practice network can be a socio-technical one in which technologies in conjunction with humans can be studied as 'actants'. Human agents, with their complex socio-cultural frames, are required to instantiate technology in social practices. Structurally relevant properties inscribed and embedded in technological artefacts constrain and enable human agency. The fortunes of healthcare IT programmes might be studied in terms of the interplay between these factors. Copyright 2010 Elsevier Ltd. All rights reserved.
1990-05-25
INCLUDING ORIENTATIONAL INTERACTIONS BETWEEN CHAIN SEGMENTS B. Deloche, E.T. Samulski (France, USA) CHAIN SEGMENT ORDERING IN STRAINED BIMODAL P-2 PDMS...theory of elastomers is difficult because it requires a detailed study of many body interactions . A theory of elasticity must address the following: (1...a Kirchhoff matrix which describes the connectivity of the network (Kc) or the linear chains (Ku). The nonbonded interactions are handled with the
Exploring 3D optimal channel networks by multiple organizing principles
NASA Astrophysics Data System (ADS)
Mason, Emanuele; Bizzi, Simone; Cominola, Andrea; Castelletti, Andrea; Paik, Kyungrock
2017-04-01
Catchment topography and flow networks are shaped by the interactions of water and sediment across various spatial and temporal scales. The complexity of these processes hinders the development of models able to assess the validity of general principles governing such phenomena. The theory of Optimal Channel Networks (OCNs) proved that it is possible to generate drainage networks statistically comparable to those observed in nature by minimizing the energy spent by the water flowing through them. So far, the OCN theory has been developed for planar 2D domains, assuming equal energy expenditure per unit area of channel and, correspondingly, a constant slope-discharge relationship. In this work, we apply the OCN theory to 3D problems by introducing a multi-principle minimization starting from an artificial digital elevation model of pyramidal shape. The OCN theory assumption of constant slope-area relationship is relaxed and embedded into a second-order principle. The modelled 3D channel networks achieve lower total energy expenditure corresponding to 2D sub-optimal OCNs bound to specific slope-area relationships. This is the first time we are able to explore accessible 3D OCNs starting from a general DEM. By contrasting the modelled 3D OCNs and natural river networks, we found statistical similarities of two indexes, namely the area exponent index and the profile concavity index. Among the wide range of alternative and sub-optimal river networks, a minimum degree of 3D network organization is found to guarantee the indexes values within the natural range. These networks simultaneously possess topological and topographic properties of real river networks. We found a pivotal functional link between slope-area relationship and accessible sub-optimal 2D river network paths, which suggests that geological and climate conditions producing slope-area relationships in natural basins co-determine the degree of optimality of accessible network paths.
Understanding Knowledge Network, Learning and Connectivism
ERIC Educational Resources Information Center
AlDahdouh, Alaa A.; Osório, António J.; Caires, Susana
2015-01-01
Behaviorism, Cognitivism, Constructivism and other growing theories such as Actor-Network and Connectivism are circulating in the educational field. For each, there are allies who stand behind research evidence and consistency of observation. Meantime, those existing theories dominate the field until the background is changed or new concrete…
Co-Operative Learning and Development Networks.
ERIC Educational Resources Information Center
Hodgson, V.; McConnell, D.
1995-01-01
Discusses the theory, nature, and benefits of cooperative learning. Considers the Cooperative Learning and Development Network (CLDN) trial in the JITOL (Just in Time Open Learning) project and examines the relationship between theories about cooperative learning and the reality of a group of professionals participating in a virtual cooperative…
Arguel, Amaël; Perez-Concha, Oscar; Li, Simon Y W; Lau, Annie Y S
2018-02-01
The aim of this review was to identify general theoretical frameworks used in online social network interventions for behavioral change. To address this research question, a PRISMA-compliant systematic review was conducted. A systematic review (PROSPERO registration number CRD42014007555) was conducted using 3 electronic databases (PsycINFO, Pubmed, and Embase). Four reviewers screened 1788 abstracts. 15 studies were selected according to the eligibility criteria. Randomized controlled trials and controlled studies were assessed using Cochrane Collaboration's "risk-of-bias" tool, and narrative synthesis. Five eligible articles used the social cognitive theory as a framework to develop interventions targeting behavioral change. Other theoretical frameworks were related to the dynamics of social networks, intention models, and community engagement theories. Only one of the studies selected in the review mentioned a well-known theory from the field of health psychology. Conclusions were that guidelines are lacking in the design of online social network interventions for behavioral change. Existing theories and models from health psychology that are traditionally used for in situ behavioral change should be considered when designing online social network interventions in a health care setting. © 2016 John Wiley & Sons, Ltd.
Jan, Hengtai; Chao, Yi-Ping; Cho, Kuan-Hung; Kuo, Li-Wei
2013-01-01
Investigating the brain connective network using the modern graph theory has been widely applied in cognitive and clinical neuroscience research. In this study, we aimed to investigate the effects of streamline-based fiber tractography on the change of network properties and established a systematic framework to understand how an adequate network matrix scaling can be determined. The network properties, including degree, efficiency and betweenness centrality, show similar tendency in both left and right hemispheres. By employing the curve-fitting process with exponential law and measuring the residuals, the association between changes of network properties and threshold of track numbers is found and an adequate range of investigating the lateralization of brain network is suggested. The proposed approach can be further applied in clinical applications to improve the diagnostic sensitivity using network analysis with graph theory.
Network Security Validation Using Game Theory
NASA Astrophysics Data System (ADS)
Papadopoulou, Vicky; Gregoriades, Andreas
Non-functional requirements (NFR) such as network security recently gained widespread attention in distributed information systems. Despite their importance however, there is no systematic approach to validate these requirements given the complexity and uncertainty characterizing modern networks. Traditionally, network security requirements specification has been the results of a reactive process. This however, limited the immunity property of the distributed systems that depended on these networks. Security requirements specification need a proactive approach. Networks' infrastructure is constantly under attack by hackers and malicious software that aim to break into computers. To combat these threats, network designers need sophisticated security validation techniques that will guarantee the minimum level of security for their future networks. This paper presents a game-theoretic approach to security requirements validation. An introduction to game theory is presented along with an example that demonstrates the application of the approach.
Framework based on communicability and flow to analyze complex network dynamics
NASA Astrophysics Data System (ADS)
Gilson, M.; Kouvaris, N. E.; Deco, G.; Zamora-López, G.
2018-05-01
Graph theory constitutes a widely used and established field providing powerful tools for the characterization of complex networks. The intricate topology of networks can also be investigated by means of the collective dynamics observed in the interactions of self-sustained oscillations (synchronization patterns) or propagationlike processes such as random walks. However, networks are often inferred from real-data-forming dynamic systems, which are different from those employed to reveal their topological characteristics. This stresses the necessity for a theoretical framework dedicated to the mutual relationship between the structure and dynamics in complex networks, as the two sides of the same coin. Here we propose a rigorous framework based on the network response over time (i.e., Green function) to study interactions between nodes across time. For this purpose we define the flow that describes the interplay between the network connectivity and external inputs. This multivariate measure relates to the concepts of graph communicability and the map equation. We illustrate our theory using the multivariate Ornstein-Uhlenbeck process, which describes stable and non-conservative dynamics, but the formalism can be adapted to other local dynamics for which the Green function is known. We provide applications to classical network examples, such as small-world ring and hierarchical networks. Our theory defines a comprehensive framework that is canonically related to directed and weighted networks, thus paving a way to revise the standards for network analysis, from the pairwise interactions between nodes to the global properties of networks including community detection.
Chang, Xiao; Wang, Zhuo; Hao, Pei; Li, Yuan-Yuan; Li, Yi-Xue
2010-06-01
The endosymbiotic theory proposed that mitochondrial genomes are derived from an alpha-proteobacterium-like endosymbiont, which was concluded from sequence analysis. We rebuilt the metabolic networks of mitochondria and 22 relative species, and studied the evolution of mitochondrial metabolism at the level of enzyme content and network topology. Our phylogenetic results based on network alignment and motif identification supported the endosymbiotic theory from the point of view of systems biology for the first time. It was found that the mitochondrial metabolic network were much more compact than the relative species, probably related to the higher efficiency of oxidative phosphorylation of the specialized organelle, and the network is highly clustered around the TCA cycle. Moreover, the mitochondrial metabolic network exhibited high functional specificity to the modules. This work provided insight to the understanding of mitochondria evolution, and the organization principle of mitochondrial metabolic network at the network level. Copyright 2010 Elsevier Inc. All rights reserved.
VizieR Online Data Catalog: UBVR photometry of the T Tauri binary DQ Tau (Tofflemire+, 2017)
NASA Astrophysics Data System (ADS)
Tofflemire, B. M.; Mathieu, R. D.; Ardila, D. R.; Akeson, R. L.; Ciardi, D. R.; Johns-Krull, C.; Herczeg, G. J.; Quijano-Vodniza, A.
2017-08-01
The Las Cumbres Observatories Global Telescope (LCOGT) 1m network consists of nine 1m telescopes spread across four international sites: McDonald Observatory (USA), CTIO (Chile), SAAO (South Africa), and Siding Springs Observatory (Australia). Over the 2014-2015 winter observing season, our program requested queued "visits" of DQ Tau 20 times per orbital cycle for 10 continuous orbital periods. Given the orbital period of DQ Tau, the visit cadence corresponded to ~20hr. Each visit consisted of three observations in each of the broadband UBVRIY and narrowband Hα and Hβ filters, requiring ~20 minutes. In this work we present only the UBVR observations, which overlap with our high-cadence observations. Indeed, two eight-night observing runs centered on separate periastron passages of DQ Tau (orbital cycles 3 and 5 in Figure 1) were obtained from the WIYN 0.9m telescope located at the Kitt Peak National Observatory. In addition to our two eight-night observing runs, a synoptic observation program was also in place at the WIYN 0.9m that provided approximately weekly observations of DQ Tau in UBVR during the 2014-B semester. Also, using Apache Point Observatory's ARCSAT 0.5m telescope, we performed observing runs of seven and ten nights centered on two separate periastron passaged of DQ Tau (orbital cycles 2 and 7 in Figure 1). (1 data file).
2003-04-01
gener- ally considered to be passive data . Instead the genetic material should be capable of being algorith - mic information, that is, program code or...information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and...maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate or any other
Low Emission Development Strategies: The Role of Networks and Knowledge Platforms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Benioff, Ron; Bazilian, Morgan; Cox, Sadie
2013-09-01
Considerable effort has been made to address the transition to low-carbon economy. A key focus of these efforts has been on the development of national low-emissions developments strategies (LEDS). One enabler of these plans is the existence of well-functioning national, regional and international low-emission development networks and knowledge platforms. To better understand the role of LEDS, weexamine this area in relation to network theory. We present a review of strengths and weaknesses of existing LEDS networks that builds on the findings of a study conducted by the Coordinated Low Emission Assistance Network (CLEAN). Based on the insights from theory andmore » a mapping of the climate-related network space, we identify opportunities for further refinement of LEDS networks.« less
Parallel Distributed Processing Theory in the Age of Deep Networks.
Bowers, Jeffrey S
2017-12-01
Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory. Copyright © 2017. Published by Elsevier Ltd.
Optimal Mass Transport for Statistical Estimation, Image Analysis, Information Geometry, and Control
2017-01-10
Metric Uncertainty for Spectral Estimation based on Nevanlinna-Pick Interpolation, (with J. Karlsson) Intern. Symp. on the Math . Theory of Networks and...Systems, Melbourne 2012. 22. Geometric tools for the estimation of structured covariances, (with L. Ning, X. Jiang) Intern. Symposium on the Math . Theory...estimation and the reversibility of stochastic processes, (with Y. Chen, J. Karlsson) Proc. Int. Symp. on Math . Theory of Networks and Syst., July
Multidimensional Analysis of Linguistic Networks
NASA Astrophysics Data System (ADS)
Araújo, Tanya; Banisch, Sven
Network-based approaches play an increasingly important role in the analysis of data even in systems in which a network representation is not immediately apparent. This is particularly true for linguistic networks, which use to be induced from a linguistic data set for which a network perspective is only one out of several options for representation. Here we introduce a multidimensional framework for network construction and analysis with special focus on linguistic networks. Such a framework is used to show that the higher is the abstraction level of network induction, the harder is the interpretation of the topological indicators used in network analysis. Several examples are provided allowing for the comparison of different linguistic networks as well as to networks in other fields of application of network theory. The computation and the intelligibility of some statistical indicators frequently used in linguistic networks are discussed. It suggests that the field of linguistic networks, by applying statistical tools inspired by network studies in other domains, may, in its current state, have only a limited contribution to the development of linguistic theory.
Toddi A. Steelman; Branda Nowell; Deena Bayoumi; Sarah McCaffrey
2014-01-01
We leverage economic theory, network theory, and social network analytical techniques to bring greater conceptual and methodological rigor to understand how information is exchanged during disasters. We ask, "How can information relationships be evaluated more systematically during a disaster response?" "Infocentric analysis"a term and...
Faculty Social Networking Interactions: Using Social Domain Theory to Assess Student Views
ERIC Educational Resources Information Center
Nemetz, Patricia L.
2012-01-01
As educators consider using social networking sites, like Facebook, for educational innovations, they must be aware of possible vulnerabilities associated with the blurring of social and professional boundaries. This research uses social domain theory to examine how students rate the appropriateness of various faculty postings, behaviors, and…
Extending unified-theory-of-reinforcement neural networks to steady-state operant behavior.
Calvin, Olivia L; McDowell, J J
2016-06-01
The unified theory of reinforcement has been used to develop models of behavior over the last 20 years (Donahoe et al., 1993). Previous research has focused on the theory's concordance with the respondent behavior of humans and animals. In this experiment, neural networks were developed from the theory to extend the unified theory of reinforcement to operant behavior on single-alternative variable-interval schedules. This area of operant research was selected because previously developed neural networks could be applied to it without significant alteration. Previous research with humans and animals indicates that the pattern of their steady-state behavior is hyperbolic when plotted against the obtained rate of reinforcement (Herrnstein, 1970). A genetic algorithm was used in the first part of the experiment to determine parameter values for the neural networks, because values that were used in previous research did not result in a hyperbolic pattern of behavior. After finding these parameters, hyperbolic and other similar functions were fitted to the behavior produced by the neural networks. The form of the neural network's behavior was best described by an exponentiated hyperbola (McDowell, 1986; McLean and White, 1983; Wearden, 1981), which was derived from the generalized matching law (Baum, 1974). In post-hoc analyses the addition of a baseline rate of behavior significantly improved the fit of the exponentiated hyperbola and removed systematic residuals. The form of this function was consistent with human and animal behavior, but the estimated parameter values were not. Copyright © 2016 Elsevier B.V. All rights reserved.
Perturbation analysis of queueing systems with a time-varying arrival rate
NASA Technical Reports Server (NTRS)
Cassandras, Christos G.; Pan, Jie
1991-01-01
The authors consider an M/G/1 queuing with a time-varying arrival rate. The objective is to obtain infinitesimal perturbation analysis (IPA) gradient estimates for various performance measures of interest with respect to certain system parameters. In particular, the authors consider the mean system time over n arrivals and an arrival rate alternating between two values. By choosing a convenient sample path representation of this system, they derive an unbiased IPA gradient estimator which, however, is not consistent, and investigate the nature of this problem.
Potential energy surface interpolation with neural networks for instanton rate calculations
NASA Astrophysics Data System (ADS)
Cooper, April M.; Hallmen, Philipp P.; Kästner, Johannes
2018-03-01
Artificial neural networks are used to fit a potential energy surface (PES). We demonstrate the benefits of using not only energies but also their first and second derivatives as training data for the neural network. This ensures smooth and accurate Hessian surfaces, which are required for rate constant calculations using instanton theory. Our aim was a local, accurate fit rather than a global PES because instanton theory requires information on the potential only in the close vicinity of the main tunneling path. Elongations along vibrational normal modes at the transition state are used as coordinates for the neural network. The method is applied to the hydrogen abstraction reaction from methanol, calculated on a coupled-cluster level of theory. The reaction is essential in astrochemistry to explain the deuteration of methanol in the interstellar medium.
Theory of correlation in a network with synaptic depression
NASA Astrophysics Data System (ADS)
Igarashi, Yasuhiko; Oizumi, Masafumi; Okada, Masato
2012-01-01
Synaptic depression affects not only the mean responses of neurons but also the correlation of response variability in neural populations. Although previous studies have constructed a theory of correlation in a spiking neuron model by using the mean-field theory framework, synaptic depression has not been taken into consideration. We expanded the previous theoretical framework in this study to spiking neuron models with short-term synaptic depression. On the basis of this theory we analytically calculated neural correlations in a ring attractor network with Mexican-hat-type connectivity, which was used as a model of the primary visual cortex. The results revealed that synaptic depression reduces neural correlation, which could be beneficial for sensory coding. Furthermore, our study opens the way for theoretical studies on the effect of interaction change on the linear response function in large stochastic networks.
Meyer-Bäse, Anke; Roberts, Rodney G.; Illan, Ignacio A.; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja
2017-01-01
Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts. PMID:29051730
Meyer-Bäse, Anke; Roberts, Rodney G; Illan, Ignacio A; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja
2017-01-01
Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts.
Earthworks logistics in the high density urban development conditions - case study
NASA Astrophysics Data System (ADS)
Sobotka, A.; Blajer, M.
2017-10-01
Realisation of the construction projects on highly urbanised areas carries many difficulties and logistic problems. Earthworks conducted in such conditions constitute a good example of how important it is to properly plan the works and use the technical means of the logistics infrastructure. The construction processes on the observed construction site, in combination with their external logistics service are a complex system, difficult for mathematical modelling and achievement of appropriate data for planning the works. The paper shows describe and analysis of earthworks during construction of the Centre of Power Engineering of AGH in Krakow for two stages of a construction project. At the planning stage in the preparatory phase (before realization) and in the implementation phase of construction works (foundation). In the first case, an example of the use of queuing theory for prediction of excavation time under random work conditions of the excavator and the associated trucks is provided. In the second case there is a change of foundation works technology resulting as a consequence of changes in logistics earthworks. Observation of the construction has confirmed that the use of appropriate methods of construction works management, and in this case agile management, the time and cost of the project have not been exceeded. The success of a project depends on the ability of the contractor to react quickly when changes occur in the design, technology, environment, etc.
Network Access Control List Situation Awareness
ERIC Educational Resources Information Center
Reifers, Andrew
2010-01-01
Network security is a large and complex problem being addressed by multiple communities. Nevertheless, current theories in networking security appear to overestimate network administrators' ability to understand network access control lists (NACLs), providing few context specific user analyses. Consequently, the current research generally seems to…
He, Yongqun
2016-01-01
Compared with controlled terminologies (e.g., MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network (i.e., OneNet). A new “OneNet effectiveness” tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research. PMID:27458549
A graph-theory framework for evaluating landscape connectivity and conservation planning.
Minor, Emily S; Urban, Dean L
2008-04-01
Connectivity of habitat patches is thought to be important for movement of genes, individuals, populations, and species over multiple temporal and spatial scales. We used graph theory to characterize multiple aspects of landscape connectivity in a habitat network in the North Carolina Piedmont (U.S.A). We compared this landscape with simulated networks with known topology, resistance to disturbance, and rate of movement. We introduced graph measures such as compartmentalization and clustering, which can be used to identify locations on the landscape that may be especially resilient to human development or areas that may be most suitable for conservation. Our analyses indicated that for songbirds the Piedmont habitat network was well connected. Furthermore, the habitat network had commonalities with planar networks, which exhibit slow movement, and scale-free networks, which are resistant to random disturbances. These results suggest that connectivity in the habitat network was high enough to prevent the negative consequences of isolation but not so high as to allow rapid spread of disease. Our graph-theory framework provided insight into regional and emergent global network properties in an intuitive and visual way and allowed us to make inferences about rates and paths of species movements and vulnerability to disturbance. This approach can be applied easily to assessing habitat connectivity in any fragmented or patchy landscape.
Network Theory: A Primer and Questions for Air Transportation Systems Applications
NASA Technical Reports Server (NTRS)
Holmes, Bruce J.
2004-01-01
A new understanding (with potential applications to air transportation systems) has emerged in the past five years in the scientific field of networks. This development emerges in large part because we now have a new laboratory for developing theories about complex networks: The Internet. The premise of this new understanding is that most complex networks of interest, both of nature and of human contrivance, exhibit a fundamentally different behavior than thought for over two hundred years under classical graph theory. Classical theory held that networks exhibited random behavior, characterized by normal, (e.g., Gaussian or Poisson) degree distributions of the connectivity between nodes by links. The new understanding turns this idea on its head: networks of interest exhibit scale-free (or small world) degree distributions of connectivity, characterized by power law distributions. The implications of scale-free behavior for air transportation systems include the potential that some behaviors of complex system architectures might be analyzed through relatively simple approximations of local elements of the system. For air transportation applications, this presentation proposes a framework for constructing topologies (architectures) that represent the relationships between mobility, flight operations, aircraft requirements, and airspace capacity, and the related externalities in airspace procedures and architectures. The proposed architectures or topologies may serve as a framework for posing comparative and combinative analyses of performance, cost, security, environmental, and related metrics.
Meng, Jingbo; Martinez, Lourdes; Holmstrom, Amanda; Chung, Minwoong; Cox, Jeff
2017-01-01
The article presents a narrative review of scholarship on social support through social networking sites (SNSs) published from 2004 to 2015. By searching keywords related to social support and SNSs in major databases for social sciences, we identified and content analyzed directly relevant articles (N = 88). The article summarizes the prevalence of theory usage; the function of theory usage (e.g., testing a theory, developing a theory); major theories referenced; and methodologies, including research designs, measurement, and the roles of social support and SNS examined in this literature. It also reports four themes identified across the studies, indicating the trends in the current research. Based on the review, the article presents a discussion about study sites, conceptualization of social support, theoretical coherence, the role of social networks, and the dynamic relationships between SNS use and social support, which points out potential avenues for shaping a future research agenda.
Wei, Ruoyu; Cao, Jinde; Alsaedi, Ahmed
2018-02-01
This paper investigates the finite-time synchronization and fixed-time synchronization problems of inertial memristive neural networks with time-varying delays. By utilizing the Filippov discontinuous theory and Lyapunov stability theory, several sufficient conditions are derived to ensure finite-time synchronization of inertial memristive neural networks. Then, for the purpose of making the setting time independent of initial condition, we consider the fixed-time synchronization. A novel criterion guaranteeing the fixed-time synchronization of inertial memristive neural networks is derived. Finally, three examples are provided to demonstrate the effectiveness of our main results.
NASA Astrophysics Data System (ADS)
Wang, Weiping; Yuan, Manman; Luo, Xiong; Liu, Linlin; Zhang, Yao
2018-01-01
Proportional delay is a class of unbounded time-varying delay. A class of bidirectional associative memory (BAM) memristive neural networks with multiple proportional delays is concerned in this paper. First, we propose the model of BAM memristive neural networks with multiple proportional delays and stochastic perturbations. Furthermore, by choosing suitable nonlinear variable transformations, the BAM memristive neural networks with multiple proportional delays can be transformed into the BAM memristive neural networks with constant delays. Based on the drive-response system concept, differential inclusions theory and Lyapunov stability theory, some anti-synchronization criteria are obtained. Finally, the effectiveness of proposed criteria are demonstrated through numerical examples.
Analyzing complex networks evolution through Information Theory quantifiers
NASA Astrophysics Data System (ADS)
Carpi, Laura C.; Rosso, Osvaldo A.; Saco, Patricia M.; Ravetti, Martín Gómez
2011-01-01
A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Niño/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.
Theory of nonstationary Hawkes processes
NASA Astrophysics Data System (ADS)
Tannenbaum, Neta Ravid; Burak, Yoram
2017-12-01
We expand the theory of Hawkes processes to the nonstationary case, in which the mutually exciting point processes receive time-dependent inputs. We derive an analytical expression for the time-dependent correlations, which can be applied to networks with arbitrary connectivity, and inputs with arbitrary statistics. The expression shows how the network correlations are determined by the interplay between the network topology, the transfer functions relating units within the network, and the pattern and statistics of the external inputs. We illustrate the correlation structure using several examples in which neural network dynamics are modeled as a Hawkes process. In particular, we focus on the interplay between internally and externally generated oscillations and their signatures in the spike and rate correlation functions.
Kazerounian, Sohrob; Grossberg, Stephen
2014-01-01
How are sequences of events that are temporarily stored in a cognitive working memory unitized, or chunked, through learning? Such sequential learning is needed by the brain in order to enable language, spatial understanding, and motor skills to develop. In particular, how does the brain learn categories, or list chunks, that become selectively tuned to different temporal sequences of items in lists of variable length as they are stored in working memory, and how does this learning process occur in real time? The present article introduces a neural model that simulates learning of such list chunks. In this model, sequences of items are temporarily stored in an Item-and-Order, or competitive queuing, working memory before learning categorizes them using a categorization network, called a Masking Field, which is a self-similar, multiple-scale, recurrent on-center off-surround network that can weigh the evidence for variable-length sequences of items as they are stored in the working memory through time. A Masking Field hereby activates the learned list chunks that represent the most predictive item groupings at any time, while suppressing less predictive chunks. In a network with a given number of input items, all possible ordered sets of these item sequences, up to a fixed length, can be learned with unsupervised or supervised learning. The self-similar multiple-scale properties of Masking Fields interacting with an Item-and-Order working memory provide a natural explanation of George Miller's Magical Number Seven and Nelson Cowan's Magical Number Four. The article explains why linguistic, spatial, and action event sequences may all be stored by Item-and-Order working memories that obey similar design principles, and thus how the current results may apply across modalities. Item-and-Order properties may readily be extended to Item-Order-Rank working memories in which the same item can be stored in multiple list positions, or ranks, as in the list ABADBD. Comparisons with other models, including TRACE, MERGE, and TISK, are made. PMID:25339918
Nguyen, Thanh-Son; Selinger, Jonathan V
2017-09-01
In liquid crystal elastomers and polymer networks, the orientational order of liquid crystals is coupled with elastic distortions of crosslinked polymers. Previous theoretical research has described these materials through two different approaches: a neoclassical theory based on the liquid crystal director and the deformation gradient tensor, and a geometric elasticity theory based on the difference between the actual metric tensor and a reference metric. Here, we connect those two approaches using a formalism based on differential geometry. Through this connection, we determine how both the director and the geometry respond to a change of temperature.
English, Tammy; Carstensen, Laura L
2014-03-01
Past research has documented age differences in the size and composition of social networks that suggest that networks grow smaller with age and include an increasingly greater proportion of well-known social partners. According to socioemotional selectivity theory, such changes in social network composition serve an antecedent emotion regulatory function that supports an age-related increase in the priority that people place on emotional well-being. The present study employed a longitudinal design with a sample that spanned the full adult age range to examine whether there is evidence of within-individual (developmental) change in social networks and whether the characteristics of relationships predict emotional experiences in daily life. Using growth curve analyses, social networks were found to increase in size in young adulthood and then decline steadily throughout later life. As postulated by socioemotional selectivity theory, reductions were observed primarily in the number of peripheral partners; the number of close partners was relatively stable over time. In addition, cross-sectional analyses revealed that older adults reported that social network members elicited less negative emotion and more positive emotion. The emotional tone of social networks, particularly when negative emotions were associated with network members, also predicted experienced emotion of participants. Overall, findings were robust after taking into account demographic variables and physical health. The implications of these findings are discussed in the context of socioemotional selectivity theory and related theoretical models.
Analysis of the enzyme network involved in cattle milk production using graph theory.
Ghorbani, Sholeh; Tahmoorespur, Mojtaba; Masoudi Nejad, Ali; Nasiri, Mohammad; Asgari, Yazdan
2015-06-01
Understanding cattle metabolism and its relationship with milk products is important in bovine breeding. A systemic view could lead to consequences that will result in a better understanding of existing concepts. Topological indices and quantitative characterizations mostly result from the application of graph theory on biological data. In the present work, the enzyme network involved in cattle milk production was reconstructed and analyzed based on available bovine genome information using several public datasets (NCBI, Uniprot, KEGG, and Brenda). The reconstructed network consisted of 3605 reactions named by KEGG compound numbers and 646 enzymes that catalyzed the corresponding reactions. The characteristics of the directed and undirected network were analyzed using Graph Theory. The mean path length was calculated to be4.39 and 5.41 for directed and undirected networks, respectively. The top 11 hub enzymes whose abnormality could harm bovine health and reduce milk production were determined. Therefore, the aim of constructing the enzyme centric network was twofold; first to find out whether such network followed the same properties of other biological networks, and second, to find the key enzymes. The results of the present study can improve our understanding of milk production in cattle. Also, analysis of the enzyme network can help improve the modeling and simulation of biological systems and help design desired phenotypes to increase milk production quality or quantity.
Power and Relation in the World Polity: The INGO Network Country Score, 1978-1998
ERIC Educational Resources Information Center
Hughes, Melanie M.; Peterson, Lindsey; Harrison, Jill Ann; Paxton, Pamela
2009-01-01
World polity theory is explicitly relational, implying a global network structure that exists outside of the nation-state. And world polity theory increasingly acknowledges power--that some states and regions are dominant in the international field. But current world polity measures of international non-governmental organizations do not…
Information Resources Usage in Project Management Digital Learning System
ERIC Educational Resources Information Center
Davidovitch, Nitza; Belichenko, Margarita; Kravchenko, Yurii
2017-01-01
The article combines a theoretical approach to structuring knowledge that is based on the integrated use of fuzzy semantic network theory predicates, Boolean functions, theory of complexity of network structures and some practical aspects to be considered in the distance learning at the university. The paper proposes a methodological approach that…
Evaluating Action Learning: A Critical Realist Complex Network Theory Approach
ERIC Educational Resources Information Center
Burgoyne, John G.
2010-01-01
This largely theoretical paper will argue the case for the usefulness of applying network and complex adaptive systems theory to an understanding of action learning and the challenge it is evaluating. This approach, it will be argued, is particularly helpful in the context of improving capability in dealing with wicked problems spread around…
ERIC Educational Resources Information Center
Bernburg, Jon Gunnar; Krohn, Marvin D.; Rivera, Craig J.
2006-01-01
This article examines the short-term impact of formal criminal labeling on involvement in deviant social networks and increased likelihood of subsequent delinquency. According to labeling theory, formal criminal intervention should affect the individual's immediate social networks. In many cases, the stigma of the criminal status may increase the…
The Design and Realization of Net Testing System on Campus Network
ERIC Educational Resources Information Center
Ren, Zhanying; Liu, Shijie
2005-01-01
According to the requirement of modern teaching theory and technology, based on software engineering, database theory, the technique of net information security and system integration, a net testing system on local network was designed and realized. The system benefits for dividing of testing & teaching and settles the problems of random…
Equilibria of perceptrons for simple contingency problems.
Dawson, Michael R W; Dupuis, Brian
2012-08-01
The contingency between cues and outcomes is fundamentally important to theories of causal reasoning and to theories of associative learning. Researchers have computed the equilibria of Rescorla-Wagner models for a variety of contingency problems, and have used these equilibria to identify situations in which the Rescorla-Wagner model is consistent, or inconsistent, with normative models of contingency. Mathematical analyses that directly compare artificial neural networks to contingency theory have not been performed, because of the assumed equivalence between the Rescorla-Wagner learning rule and the delta rule training of artificial neural networks. However, recent results indicate that this equivalence is not as straightforward as typically assumed, suggesting a strong need for mathematical accounts of how networks deal with contingency problems. One such analysis is presented here, where it is proven that the structure of the equilibrium for a simple network trained on a basic contingency problem is quite different from the structure of the equilibrium for a Rescorla-Wagner model faced with the same problem. However, these structural differences lead to functionally equivalent behavior. The implications of this result for the relationships between associative learning, contingency theory, and connectionism are discussed.
The 6th International Conference on Computer Science and Computational Mathematics (ICCSCM 2017)
NASA Astrophysics Data System (ADS)
2017-09-01
The ICCSCM 2017 (The 6th International Conference on Computer Science and Computational Mathematics) has aimed to provide a platform to discuss computer science and mathematics related issues including Algebraic Geometry, Algebraic Topology, Approximation Theory, Calculus of Variations, Category Theory; Homological Algebra, Coding Theory, Combinatorics, Control Theory, Cryptology, Geometry, Difference and Functional Equations, Discrete Mathematics, Dynamical Systems and Ergodic Theory, Field Theory and Polynomials, Fluid Mechanics and Solid Mechanics, Fourier Analysis, Functional Analysis, Functions of a Complex Variable, Fuzzy Mathematics, Game Theory, General Algebraic Systems, Graph Theory, Group Theory and Generalizations, Image Processing, Signal Processing and Tomography, Information Fusion, Integral Equations, Lattices, Algebraic Structures, Linear and Multilinear Algebra; Matrix Theory, Mathematical Biology and Other Natural Sciences, Mathematical Economics and Financial Mathematics, Mathematical Physics, Measure Theory and Integration, Neutrosophic Mathematics, Number Theory, Numerical Analysis, Operations Research, Optimization, Operator Theory, Ordinary and Partial Differential Equations, Potential Theory, Real Functions, Rings and Algebras, Statistical Mechanics, Structure Of Matter, Topological Groups, Wavelets and Wavelet Transforms, 3G/4G Network Evolutions, Ad-Hoc, Mobile, Wireless Networks and Mobile Computing, Agent Computing & Multi-Agents Systems, All topics related Image/Signal Processing, Any topics related Computer Networks, Any topics related ISO SC-27 and SC- 17 standards, Any topics related PKI(Public Key Intrastructures), Artifial Intelligences(A.I.) & Pattern/Image Recognitions, Authentication/Authorization Issues, Biometric authentication and algorithms, CDMA/GSM Communication Protocols, Combinatorics, Graph Theory, and Analysis of Algorithms, Cryptography and Foundation of Computer Security, Data Base(D.B.) Management & Information Retrievals, Data Mining, Web Image Mining, & Applications, Defining Spectrum Rights and Open Spectrum Solutions, E-Comerce, Ubiquitous, RFID, Applications, Fingerprint/Hand/Biometrics Recognitions and Technologies, Foundations of High-performance Computing, IC-card Security, OTP, and Key Management Issues, IDS/Firewall, Anti-Spam mail, Anti-virus issues, Mobile Computing for E-Commerce, Network Security Applications, Neural Networks and Biomedical Simulations, Quality of Services and Communication Protocols, Quantum Computing, Coding, and Error Controls, Satellite and Optical Communication Systems, Theory of Parallel Processing and Distributed Computing, Virtual Visions, 3-D Object Retrievals, & Virtual Simulations, Wireless Access Security, etc. The success of ICCSCM 2017 is reflected in the received papers from authors around the world from several countries which allows a highly multinational and multicultural idea and experience exchange. The accepted papers of ICCSCM 2017 are published in this Book. Please check http://www.iccscm.com for further news. A conference such as ICCSCM 2017 can only become successful using a team effort, so herewith we want to thank the International Technical Committee and the Reviewers for their efforts in the review process as well as their valuable advices. We are thankful to all those who contributed to the success of ICCSCM 2017. The Secretary
Network Leadership: An Emerging Practice
ERIC Educational Resources Information Center
Tremblay, Christopher W.
2012-01-01
Network leadership is an emerging approach that can have an impact on change in education and in society. According to Merriam-Webster (2011), a network is "an interconnected or interrelated chain, group, or system." Intentional interconnectedness is what separates network leadership from other leadership theories. Network leadership has the…
NASA Astrophysics Data System (ADS)
Donges, Jonathan F.; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V.; Marwan, Norbert; Dijkstra, Henk A.; Kurths, Jürgen
2015-11-01
We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.
NASA Astrophysics Data System (ADS)
Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke
2017-05-01
Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.
Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling
Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.
2011-01-01
Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571
Putting Gino's lesson to work: Actor-network theory, enacted humanity, and rehabilitation.
Abrams, Thomas; Gibson, Barbara E
2016-02-01
This article argues that rehabilitation enacts a particular understanding of "the human" throughout therapeutic assessment and treatment. Following Michel Callon and Vololona Rabeharisoa's "Gino's Lesson on Humanity," we suggest that this is not simply a top-down process, but is cultivated in the application and response to biomedical frameworks of human ability, competence, and responsibility. The emergence of the human is at once a materially contingent, moral, and interpersonal process. We begin the article by outlining the basics of the actor-network theory that underpins "Gino's Lesson on Humanity." Next, we elucidate its central thesis regarding how disabled personhood emerges through actor-network interactions. Section "Learning Gino's lesson" draws on two autobiographical examples, examining the emergence of humanity through rehabilitation, particularly assessment measures and the responses to them. We conclude by thinking about how rehabilitation and actor-network theory might take this lesson on humanity seriously. © The Author(s) 2016.
Brown, B.L.; Swan, C.M.; Auerbach, D.A.; Campbell, Grant E.H.; Hitt, N.P.; Maloney, K.O.; Patrick, C.
2011-01-01
Explaining the mechanisms underlying patterns of species diversity and composition in riverine networks is challenging. Historically, community ecologists have conceived of communities as largely isolated entities and have focused on local environmental factors and interspecific interactions as the major forces determining species composition. However, stream ecologists have long embraced a multiscale approach to studying riverine ecosystems and have studied both local factors and larger-scale regional factors, such as dispersal and disturbance. River networks exhibit a dendritic spatial structure that can constrain aquatic organisms when their dispersal is influenced by or confined to the river network. We contend that the principles of metacommunity theory would help stream ecologists to understand how the complex spatial structure of river networks mediates the relative influences of local and regional control on species composition. From a basic ecological perspective, the concept is attractive because new evidence suggests that the importance of regional processes (dispersal) depends on spatial structure of habitat and on connection to the regional species pool. The role of local factors relative to regional factors will vary with spatial position in a river network. From an applied perspective, the long-standing view in ecology that local community composition is an indicator of habitat quality may not be uniformly applicable across a river network, but the strength of such bioassessment approaches probably will depend on spatial position in the network. The principles of metacommunity theory are broadly applicable across taxa and systems but seem of particular consequence to stream ecology given the unique spatial structure of riverine systems. By explicitly embracing processes at multiple spatial scales, metacommunity theory provides a foundation on which to build a richer understanding of stream communities.
A Game Theory Based Solution for Security Challenges in CRNs
NASA Astrophysics Data System (ADS)
Poonam; Nagpal, Chander Kumar
2018-03-01
Cognitive radio networks (CRNs) are being envisioned to drive the next generation Ad hoc wireless networks due to their ability to provide communications resilience in continuously changing environments through the use of dynamic spectrum access. Conventionally CRNs are dependent upon the information gathered by other secondary users to ensure the accuracy of spectrum sensing making them vulnerable to security attacks leading to the need of security mechanisms like cryptography and trust. However, a typical cryptography based solution is not a viable security solution for CRNs owing to their limited resources. Effectiveness of trust based approaches has always been, in question, due to credibility of secondary trust resources. Game theory with its ability to optimize in an environment of conflicting interests can be quite a suitable tool to manage an ad hoc network in the presence of autonomous selfish/malevolent/malicious and attacker nodes. The literature contains several theoretical proposals for augmenting game theory in the ad hoc networks without explicit/detailed implementation. This paper implements a game theory based solution in MATLAB-2015 to secure the CRN environment and compares the obtained results with the traditional approaches of trust and cryptography. The simulation result indicates that as the time progresses the game theory performs much better with higher throughput, lower jitter and better identification of selfish/malicious nodes.
Numerical methods for solving moment equations in kinetic theory of neuronal network dynamics
NASA Astrophysics Data System (ADS)
Rangan, Aaditya V.; Cai, David; Tao, Louis
2007-02-01
Recently developed kinetic theory and related closures for neuronal network dynamics have been demonstrated to be a powerful theoretical framework for investigating coarse-grained dynamical properties of neuronal networks. The moment equations arising from the kinetic theory are a system of (1 + 1)-dimensional nonlinear partial differential equations (PDE) on a bounded domain with nonlinear boundary conditions. The PDEs themselves are self-consistently specified by parameters which are functions of the boundary values of the solution. The moment equations can be stiff in space and time. Numerical methods are presented here for efficiently and accurately solving these moment equations. The essential ingredients in our numerical methods include: (i) the system is discretized in time with an implicit Euler method within a spectral deferred correction framework, therefore, the PDEs of the kinetic theory are reduced to a sequence, in time, of boundary value problems (BVPs) with nonlinear boundary conditions; (ii) a set of auxiliary parameters is introduced to recast the original BVP with nonlinear boundary conditions as BVPs with linear boundary conditions - with additional algebraic constraints on the auxiliary parameters; (iii) a careful combination of two Newton's iterates for the nonlinear BVP with linear boundary condition, interlaced with a Newton's iterate for solving the associated algebraic constraints is constructed to achieve quadratic convergence for obtaining the solutions with self-consistent parameters. It is shown that a simple fixed-point iteration can only achieve a linear convergence for the self-consistent parameters. The practicability and efficiency of our numerical methods for solving the moment equations of the kinetic theory are illustrated with numerical examples. It is further demonstrated that the moment equations derived from the kinetic theory of neuronal network dynamics can very well capture the coarse-grained dynamical properties of integrate-and-fire neuronal networks.
BRAPH: A graph theory software for the analysis of brain connectivity
Mijalkov, Mite; Kakaei, Ehsan; Pereira, Joana B.; Westman, Eric; Volpe, Giovanni
2017-01-01
The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH–BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer’s disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson’s patients with mild cognitive impairment. PMID:28763447
BRAPH: A graph theory software for the analysis of brain connectivity.
Mijalkov, Mite; Kakaei, Ehsan; Pereira, Joana B; Westman, Eric; Volpe, Giovanni
2017-01-01
The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH-BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimer's disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinson's patients with mild cognitive impairment.
Flexible server-side processing of climate archives
NASA Astrophysics Data System (ADS)
Juckes, Martin; Stephens, Ag; Damasio da Costa, Eduardo
2014-05-01
The flexibility and interoperability of OGC Web Processing Services are combined with an extensive range of data processing operations supported by the Climate Data Operators (CDO) library to facilitate processing of the CMIP5 climate data archive. The challenges posed by this peta-scale archive allow us to test and develop systems which will help us to deal with approaching exa-scale challenges. The CEDA WPS package allows users to manipulate data in the archive and export the results without first downloading the data -- in some cases this can drastically reduce the data volumes which need to be transferred and greatly reduce the time needed for the scientists to get their results. Reductions in data transfer are achieved at the expense of an additional computational load imposed on the archive (or near-archive) infrastructure. This is managed with a load balancing system. Short jobs may be run in near real-time, longer jobs will be queued. When jobs are queued the user is provided with a web dashboard displaying job status. A clean split between the data manipulation software and the request management software is achieved by exploiting the extensive CDO library. This library has a long history of development to support the needs of the climate science community. Use of the library ensures that operations run on data by the system can be reproduced by users using the same operators installed on their own computers. Examples using the system deployed for the CMIP5 archive will be shown and issues which need to be addressed as archive volumes expand into the exa-scale will be discussed.
Flexible server-side processing of climate archives
NASA Astrophysics Data System (ADS)
Juckes, M. N.; Stephens, A.; da Costa, E. D.
2013-12-01
The flexibility and interoperability of OGC Web Processing Services are combined with an extensive range of data processing operations supported by the Climate Data Operators (CDO) library to facilitate processing of the CMIP5 climate data archive. The challenges posed by this peta-scale archive allow us to test and develop systems which will help us to deal with approaching exa-scale challenges. The CEDA WPS package allows users to manipulate data in the archive and export the results without first downloading the data -- in some cases this can drastically reduce the data volumes which need to be transferred and greatly reduce the time needed for the scientists to get their results. Reductions in data transfer are achieved at the expense of an additional computational load imposed on the archive (or near-archive) infrastructure. This is managed with a load balancing system. Short jobs may be run in near real-time, longer jobs will be queued. When jobs are queued the user is provided with a web dashboard displaying job status. A clean split between the data manipulation software and the request management software is achieved by exploiting the extensive CDO library. This library has a long history of development to support the needs of the climate science community. Use of the library ensures that operations run on data by the system can be reproduced by users using the same operators installed on their own computers. Examples using the system deployed for the CMIP5 archive will be shown and issues which need to be addressed as archive volumes expand into the exa-scale will be discussed.
Yip, Kenneth; Pang, Suk-King; Chan, Kui-Tim; Chan, Chi-Kuen; Lee, Tsz-Leung
2016-08-08
Purpose - The purpose of this paper is to present a simulation modeling application to reconfigure the outpatient phlebotomy service of an acute regional and teaching hospital in Hong Kong, with an aim to improve service efficiency, shorten patient queuing time and enhance workforce utilization. Design/methodology/approach - The system was modeled as an inhomogeneous Poisson process and a discrete-event simulation model was developed to simulate the current setting, and to evaluate how various performance metrics would change if switched from a decentralized to a centralized model. Variations were then made to the model to test different workforce arrangements for the centralized service, so that managers could decide on the service's final configuration via an evidence-based and data-driven approach. Findings - This paper provides empirical insights about the relationship between staffing arrangement and system performance via a detailed scenario analysis. One particular staffing scenario was chosen by manages as it was considered to strike the best balance between performance and workforce scheduled. The resulting centralized phlebotomy service was successfully commissioned. Practical implications - This paper demonstrates how analytics could be used for operational planning at the hospital level. The authors show that a transparent and evidence-based scenario analysis, made available through analytics and simulation, greatly facilitates management and clinical stakeholders to arrive at the ideal service configuration. Originality/value - The authors provide a robust method in evaluating the relationship between workforce investment, queuing reduction and workforce utilization, which is crucial for managers when deciding the delivery model for any outpatient-related service.
Modeling work of the dispatching service of high-rise building as queuing system
NASA Astrophysics Data System (ADS)
Dement'eva, Marina; Dement'eva, Anastasiya
2018-03-01
The article presents the results of calculating the performance indicators of the dispatcher service of a high-rise building as a queuing system with an unlimited queue. The calculation was carried out for three models: with a single control room and brigade of service, with a single control room and a specialized service, with several dispatch centers and specialized services. The aim of the work was to investigate the influence of the structural scheme of the organization of the dispatcher service of a high-rise building on the amount of operating costs and the time of processing and fulfilling applications. The problems of high-rise construction and their impact on the complication of exploitation are analyzed. The composition of exploitation activities of high-rise buildings is analyzed. The relevance of the study is justified by the need to review the role of dispatch services in the structure of management of the quality of buildings. Dispatching service from the lower level of management of individual engineering systems becomes the main link in the centralized automated management of the exploitation of high-rise buildings. With the transition to market relations, the criterion of profitability at the organization of the dispatching service becomes one of the main parameters of the effectiveness of its work. A mathematical model for assessing the efficiency of the dispatching service on a set of quality of service indicators is proposed. The structure of operating costs is presented. The algorithm of decision-making is given when choosing the optimal structural scheme of the dispatching service of a high-rise building.
Optimizing Endoscope Reprocessing Resources Via Process Flow Queuing Analysis.
Seelen, Mark T; Friend, Tynan H; Levine, Wilton C
2018-05-04
The Massachusetts General Hospital (MGH) is merging its older endoscope processing facilities into a single new facility that will enable high-level disinfection of endoscopes for both the ORs and Endoscopy Suite, leveraging economies of scale for improved patient care and optimal use of resources. Finalized resource planning was necessary for the merging of facilities to optimize staffing and make final equipment selections to support the nearly 33,000 annual endoscopy cases. To accomplish this, we employed operations management methodologies, analyzing the physical process flow of scopes throughout the existing Endoscopy Suite and ORs and mapping the future state capacity of the new reprocessing facility. Further, our analysis required the incorporation of historical case and reprocessing volumes in a multi-server queuing model to identify any potential wait times as a result of the new reprocessing cycle. We also performed sensitivity analysis to understand the impact of future case volume growth. We found that our future-state reprocessing facility, given planned capital expenditures for automated endoscope reprocessors (AERs) and pre-processing sinks, could easily accommodate current scope volume well within the necessary pre-cleaning-to-sink reprocessing time limit recommended by manufacturers. Further, in its current planned state, our model suggested that the future endoscope reprocessing suite at MGH could support an increase in volume of at least 90% over the next several years. Our work suggests that with simple mathematical analysis of historic case data, significant changes to a complex perioperative environment can be made with ease while keeping patient safety as the top priority.
Markov modeling and discrete event simulation in health care: a systematic comparison.
Standfield, Lachlan; Comans, Tracy; Scuffham, Paul
2014-04-01
The aim of this study was to assess if the use of Markov modeling (MM) or discrete event simulation (DES) for cost-effectiveness analysis (CEA) may alter healthcare resource allocation decisions. A systematic literature search and review of empirical and non-empirical studies comparing MM and DES techniques used in the CEA of healthcare technologies was conducted. Twenty-two pertinent publications were identified. Two publications compared MM and DES models empirically, one presented a conceptual DES and MM, two described a DES consensus guideline, and seventeen drew comparisons between MM and DES through the authors' experience. The primary advantages described for DES over MM were the ability to model queuing for limited resources, capture individual patient histories, accommodate complexity and uncertainty, represent time flexibly, model competing risks, and accommodate multiple events simultaneously. The disadvantages of DES over MM were the potential for model overspecification, increased data requirements, specialized expensive software, and increased model development, validation, and computational time. Where individual patient history is an important driver of future events an individual patient simulation technique like DES may be preferred over MM. Where supply shortages, subsequent queuing, and diversion of patients through other pathways in the healthcare system are likely to be drivers of cost-effectiveness, DES modeling methods may provide decision makers with more accurate information on which to base resource allocation decisions. Where these are not major features of the cost-effectiveness question, MM remains an efficient, easily validated, parsimonious, and accurate method of determining the cost-effectiveness of new healthcare interventions.
How Fast Can Networks Synchronize? A Random Matrix Theory Approach
NASA Astrophysics Data System (ADS)
Timme, Marc; Wolf, Fred; Geisel, Theo
2004-03-01
Pulse-coupled oscillators constitute a paradigmatic class of dynamical systems interacting on networks because they model a variety of biological systems including flashing fireflies and chirping crickets as well as pacemaker cells of the heart and neural networks. Synchronization is one of the most simple and most prevailing kinds of collective dynamics on such networks. Here we study collective synchronization [1] of pulse-coupled oscillators interacting on asymmetric random networks. Using random matrix theory we analytically determine the speed of synchronization in such networks in dependence on the dynamical and network parameters [2]. The speed of synchronization increases with increasing coupling strengths. Surprisingly, however, it stays finite even for infinitely strong interactions. The results indicate that the speed of synchronization is limited by the connectivity of the network. We discuss the relevance of our findings to general equilibration processes on complex networks. [5mm] [1] M. Timme, F. Wolf, T. Geisel, Phys. Rev. Lett. 89:258701 (2002). [2] M. Timme, F. Wolf, T. Geisel, cond-mat/0306512 (2003).
Graduate Employability: The Perspective of Social Network Learning
ERIC Educational Resources Information Center
Chen, Yong
2017-01-01
This study provides a conceptual framework for understanding how the graduate acquire employability through the social network in the Chinese context, using insights from the social network theory. This paper builds a conceptual model of the relationship among social network, social network learning and the graduate employability, and uses…
NASA Astrophysics Data System (ADS)
Donado-Garzon, L. D.; Pardo, Y.
2013-12-01
Fractured media are very heterogeneous systems where occur complex physical and chemical processes to model. One of the possible approaches to conceptualize this type of massifs is the Discrete Fracture Network (DFN). Donado et al., modeled flow and transport in a granitic batholith based on this approach and found good fitting with hydraulic and tracer tests, but the computational cost was excessive due to a gigantic amount of elements to model. We present in this work a methodology based on percolation theory for reducing the number of elements and in consequence, to reduce the bandwidth of the conductance matrix and the execution time of each network. DFN poses as an excellent representation of all the set of fractures of the media, but not all the fractures of the media are part of the conductive network. Percolation theory is used to identify which nodes or fractures are not conductive, based on the occupation probability or percolation threshold. In a fractured system, connectivity determines the flow pattern in the fractured rock mass. This volume of fluid is driven through connection paths formed by the fractures, when the permeability of the rock is negligible compared to the fractures. In a population of distributed fractures, each of this that has no intersection with any connected fracture do not contribute to generate a flow field. This algorithm also permits us to erase these elements however they are water conducting and hence, refine even more the backbone of the network. We used 100 different generations of DFN that were optimized in this study using percolation theory. In each of the networks calibrate hydrodynamic parameters as hydraulic conductivity and specific storage coefficient, for each of the five families of fractures, yielding a total of 10 parameters to estimate, at each generation. Since the effects of the distribution of fault orientation changes the value of the percolation threshold, but not the universal laws of classical percolation theory, the latter is applicable to such networks. Under these conditions, percolation theory permit us to reduced the number of elements (90% in average) that form clusters of the 100 DFNs, preserving the so-called backbone. In this way the calibration runs in these networks changed from several hours to just a second obtaining much better results.
The Conundrum of Functional Brain Networks: Small-World Efficiency or Fractal Modularity
Gallos, Lazaros K.; Sigman, Mariano; Makse, Hernán A.
2012-01-01
The human brain has been studied at multiple scales, from neurons, circuits, areas with well-defined anatomical and functional boundaries, to large-scale functional networks which mediate coherent cognition. In a recent work, we addressed the problem of the hierarchical organization in the brain through network analysis. Our analysis identified functional brain modules of fractal structure that were inter-connected in a small-world topology. Here, we provide more details on the use of network science tools to elaborate on this behavior. We indicate the importance of using percolation theory to highlight the modular character of the functional brain network. These modules present a fractal, self-similar topology, identified through fractal network methods. When we lower the threshold of correlations to include weaker ties, the network as a whole assumes a small-world character. These weak ties are organized precisely as predicted by theory maximizing information transfer with minimal wiring costs. PMID:22586406
Stability and dynamical properties of material flow systems on random networks
NASA Astrophysics Data System (ADS)
Anand, K.; Galla, T.
2009-04-01
The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are characteristic of flow networks in economic, ecological and biological systems. Based on results from random matrix theory, we work out the phase diagram of such systems defined on extensively connected random graphs, and study in detail how the choice of control policies and the network structure affects stability. We also present results for more complex topologies of the underlying graph, focussing on finitely connected Erdös-Réyni graphs, Small-World Networks and Barabási-Albert scale-free networks. Results indicate that variability of input-output matrix elements, and random structures of the underlying graph tend to make the system less stable, while fast price dynamics or strong responsiveness to stock accumulation promote stability.
Topics on data transmission problem in software definition network
NASA Astrophysics Data System (ADS)
Gao, Wei; Liang, Li; Xu, Tianwei; Gan, Jianhou
2017-08-01
In normal computer networks, the data transmission between two sites go through the shortest path between two corresponding vertices. However, in the setting of software definition network (SDN), it should monitor the network traffic flow in each site and channel timely, and the data transmission path between two sites in SDN should consider the congestion in current networks. Hence, the difference of available data transmission theory between normal computer network and software definition network is that we should consider the prohibit graph structures in SDN, and these forbidden subgraphs represent the sites and channels in which data can't be passed by the serious congestion. Inspired by theoretical analysis of an available data transmission in SDN, we consider some computational problems from the perspective of the graph theory. Several results determined in the paper imply the sufficient conditions of data transmission in SDN in the various graph settings.
Critical behavior of the contact process on small-world networks
NASA Astrophysics Data System (ADS)
Ferreira, Ronan S.; Ferreira, Silvio C.
2013-11-01
We investigate the role of clustering on the critical behavior of the contact process (CP) on small-world networks using the Watts-Strogatz (WS) network model with an edge rewiring probability p. The critical point is well predicted by a homogeneous cluster-approximation for the limit of vanishing clustering ( p → 1). The critical exponents and dimensionless moment ratios of the CP are in agreement with those predicted by the mean-field theory for any p > 0. This independence on the network clustering shows that the small-world property is a sufficient condition for the mean-field theory to correctly predict the universality of the model. Moreover, we compare the CP dynamics on WS networks with rewiring probability p = 1 and random regular networks and show that the weak heterogeneity of the WS network slightly changes the critical point but does not alter other critical quantities of the model.
Self-Consistent Field Lattice Model for Polymer Networks.
Tito, Nicholas B; Storm, Cornelis; Ellenbroek, Wouter G
2017-12-26
A lattice model based on polymer self-consistent field theory is developed to predict the equilibrium statistics of arbitrary polymer networks. For a given network topology, our approach uses moment propagators on a lattice to self-consistently construct the ensemble of polymer conformations and cross-link spatial probability distributions. Remarkably, the calculation can be performed "in the dark", without any prior knowledge on preferred chain conformations or cross-link positions. Numerical results from the model for a test network exhibit close agreement with molecular dynamics simulations, including when the network is strongly sheared. Our model captures nonaffine deformation, mean-field monomer interactions, cross-link fluctuations, and finite extensibility of chains, yielding predictions that differ markedly from classical rubber elasticity theory for polymer networks. By examining polymer networks with different degrees of interconnectivity, we gain insight into cross-link entropy, an important quantity in the macroscopic behavior of gels and self-healing materials as they are deformed.
Some characteristics of supernetworks based on unified hybrid network theory framework
NASA Astrophysics Data System (ADS)
Liu, Qiang; Fang, Jin-Qing; Li, Yong
Comparing with single complex networks, supernetworks are more close to the real world in some ways, and have become the newest research hot spot in the network science recently. Some progresses have been made in the research of supernetworks, but the theoretical research method and complex network characteristics of supernetwork models are still needed to further explore. In this paper, we propose three kinds of supernetwork models with three layers based on the unified hybrid network theory framework (UHNTF), and introduce preferential and random linking, respectively, between the upper and lower layers. Then we compared the topological characteristics of the single networks with the supernetwork models. In order to analyze the influence of the interlayer edges on network characteristics, the cross-degree is defined as a new important parameter. Then some interesting new phenomena are found, the results imply this supernetwork model has reference value and application potential.
Eradicating catastrophic collapse in interdependent networks via reinforced nodes
Yuan, Xin; Hu, Yanqing; Havlin, Shlomo
2017-01-01
In interdependent networks, it is usually assumed, based on percolation theory, that nodes become nonfunctional if they lose connection to the network giant component. However, in reality, some nodes, equipped with alternative resources, together with their connected neighbors can still be functioning after disconnected from the giant component. Here, we propose and study a generalized percolation model that introduces a fraction of reinforced nodes in the interdependent networks that can function and support their neighborhood. We analyze, both analytically and via simulations, the order parameter—the functioning component—comprising both the giant component and smaller components that include at least one reinforced node. Remarkably, it is found that, for interdependent networks, we need to reinforce only a small fraction of nodes to prevent abrupt catastrophic collapses. Moreover, we find that the universal upper bound of this fraction is 0.1756 for two interdependent Erdős–Rényi (ER) networks: regular random (RR) networks and scale-free (SF) networks with large average degrees. We also generalize our theory to interdependent networks of networks (NONs). These findings might yield insight for designing resilient interdependent infrastructure networks. PMID:28289204
Hybrid modeling and empirical analysis of automobile supply chain network
NASA Astrophysics Data System (ADS)
Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying
2017-05-01
Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.
ERIC Educational Resources Information Center
Kretschmer, Hildrun
2002-01-01
Based on Gestalt theory, the author assumes the existence of a field-force equilibrium to explain how, according to the conciseness principle, mathematically precise gestalts could exist in coauthorship networks. Develops a mathematical function to describe these gestalts in scientific literature and discusses structural characteristics of…
ERIC Educational Resources Information Center
Mulcahy, Dianne; Perillo, Suzanne
2011-01-01
This article examines the significance of materiality for management and leadership in education using resources provided by actor-network theory (ANT). Espousing the idea that human interactions are mediated by material objects and that these objects participate in the production of practices, ANT affords thinking management and leadership in a…
Social Network Changes and Life Events across the Life Span: A Meta-Analysis
ERIC Educational Resources Information Center
Wrzus, Cornelia; Hanel, Martha; Wagner, Jenny; Neyer, Franz J.
2013-01-01
For researchers and practitioners interested in social relationships, the question remains as to how large social networks typically are, and how their size and composition change across adulthood. On the basis of predictions of socioemotional selectivity theory and social convoy theory, we conducted a meta-analysis on age-related social network…
Learning about a Fish from an ANT: Actor Network Theory and Science Education in the Postgenomic Era
ERIC Educational Resources Information Center
Pierce, Clayton
2015-01-01
This article uses actor network theory (ANT) to develop a more appropriate model of scientific literacy for students, teachers, and citizens in a society increasingly populated with biotechnological and bioscientific nonhumans. In so doing, I take the recent debate surrounding the first genetically engineered animal food product under review by…
Reading Educational Reform with Actor Network Theory: Fluid Spaces, Otherings, and Ambivalences
ERIC Educational Resources Information Center
Fenwick, Tara
2011-01-01
In considering two extended examples of educational reform efforts, this discussion traces relations that become visible through analytic approaches associated with actor-network theory (ANT). The strategy here is to present multiple readings of the two examples. The first reading adopts an ANT approach to follow ways that all actors--human and…
NASA Technical Reports Server (NTRS)
Beard, Daniel A.; Liang, Shou-Dan; Qian, Hong; Biegel, Bryan (Technical Monitor)
2001-01-01
Predicting behavior of large-scale biochemical metabolic networks represents one of the greatest challenges of bioinformatics and computational biology. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are perhaps the most promising tools for the analysis of large complex networks. As a step towards building a complete theory of biochemical circuit analysis, we introduce energy balance analysis (EBA), which compliments the FBA approach by introducing fundamental constraints based on the first and second laws of thermodynamics. Fluxes obtained with EBA are thermodynamically feasible and provide valuable insight into the activation and suppression of biochemical pathways.
A new delay-independent condition for global robust stability of neural networks with time delays.
Samli, Ruya
2015-06-01
This paper studies the problem of robust stability of dynamical neural networks with discrete time delays under the assumptions that the network parameters of the neural system are uncertain and norm-bounded, and the activation functions are slope-bounded. By employing the results of Lyapunov stability theory and matrix theory, new sufficient conditions for the existence, uniqueness and global asymptotic stability of the equilibrium point for delayed neural networks are presented. The results reported in this paper can be easily tested by checking some special properties of symmetric matrices associated with the parameter uncertainties of neural networks. We also present a numerical example to show the effectiveness of the proposed theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.
Distributed formation control of nonholonomic autonomous vehicle via RBF neural network
NASA Astrophysics Data System (ADS)
Yang, Shichun; Cao, Yaoguang; Peng, Zhaoxia; Wen, Guoguang; Guo, Konghui
2017-03-01
In this paper, RBF neural network consensus-based distributed control scheme is proposed for nonholonomic autonomous vehicles in a pre-defined formation along the specified reference trajectory. A variable transformation is first designed to convert the formation control problem into a state consensus problem. Then, the complete dynamics of the vehicles including inertia, Coriolis, friction model and unmodeled bounded disturbances are considered, which lead to the formation unstable when the distributed kinematic controllers are proposed based on the kinematics. RBF neural network torque controllers are derived to compensate for them. Some sufficient conditions are derived to accomplish the asymptotically stability of the systems based on algebraic graph theory, matrix theory, and Lyapunov theory. Finally, simulation examples illustrate the effectiveness of the proposed controllers.
Controlling extreme events on complex networks
NASA Astrophysics Data System (ADS)
Chen, Yu-Zhong; Huang, Zi-Gang; Lai, Ying-Cheng
2014-08-01
Extreme events, a type of collective behavior in complex networked dynamical systems, often can have catastrophic consequences. To develop effective strategies to control extreme events is of fundamental importance and practical interest. Utilizing transportation dynamics on complex networks as a prototypical setting, we find that making the network ``mobile'' can effectively suppress extreme events. A striking, resonance-like phenomenon is uncovered, where an optimal degree of mobility exists for which the probability of extreme events is minimized. We derive an analytic theory to understand the mechanism of control at a detailed and quantitative level, and validate the theory numerically. Implications of our finding to current areas such as cybersecurity are discussed.
Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay
NASA Astrophysics Data System (ADS)
Sun, Mei; Zeng, Chang-Yan; Tian, Li-Xin
2009-01-01
Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand-supply of energy resource in some regions of China.
Linear control theory for gene network modeling.
Shin, Yong-Jun; Bleris, Leonidas
2010-09-16
Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.
Cartographic generalization of urban street networks based on gravitational field theory
NASA Astrophysics Data System (ADS)
Liu, Gang; Li, Yongshu; Li, Zheng; Guo, Jiawei
2014-05-01
The automatic generalization of urban street networks is a constant and important aspect of geographical information science. Previous studies show that the dual graph for street-street relationships more accurately reflects the overall morphological properties and importance of streets than do other methods. In this study, we construct a dual graph to represent street-street relationship and propose an approach to generalize street networks based on gravitational field theory. We retain the global structural properties and topological connectivity of an original street network and borrow from gravitational field theory to define the gravitational force between nodes. The concept of multi-order neighbors is introduced and the gravitational force is taken as the measure of the importance contribution between nodes. The importance of a node is defined as the result of the interaction between a given node and its multi-order neighbors. Degree distribution is used to evaluate the level of maintaining the global structure and topological characteristics of a street network and to illustrate the efficiency of the suggested method. Experimental results indicate that the proposed approach can be used in generalizing street networks and retaining their density characteristics, connectivity and global structure.
Application and Exploration of Big Data Mining in Clinical Medicine.
Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling
2016-03-20
To review theories and technologies of big data mining and their application in clinical medicine. Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Big data mining has the potential to play an important role in clinical medicine.
Retinal Connectomics: Towards Complete, Accurate Networks
Marc, Robert E.; Jones, Bryan W.; Watt, Carl B.; Anderson, James R.; Sigulinsky, Crystal; Lauritzen, Scott
2013-01-01
Connectomics is a strategy for mapping complex neural networks based on high-speed automated electron optical imaging, computational assembly of neural data volumes, web-based navigational tools to explore 1012–1015 byte (terabyte to petabyte) image volumes, and annotation and markup tools to convert images into rich networks with cellular metadata. These collections of network data and associated metadata, analyzed using tools from graph theory and classification theory, can be merged with classical systems theory, giving a more completely parameterized view of how biologic information processing systems are implemented in retina and brain. Networks have two separable features: topology and connection attributes. The first findings from connectomics strongly validate the idea that the topologies complete retinal networks are far more complex than the simple schematics that emerged from classical anatomy. In particular, connectomics has permitted an aggressive refactoring of the retinal inner plexiform layer, demonstrating that network function cannot be simply inferred from stratification; exposing the complex geometric rules for inserting different cells into a shared network; revealing unexpected bidirectional signaling pathways between mammalian rod and cone systems; documenting selective feedforward systems, novel candidate signaling architectures, new coupling motifs, and the highly complex architecture of the mammalian AII amacrine cell. This is but the beginning, as the underlying principles of connectomics are readily transferrable to non-neural cell complexes and provide new contexts for assessing intercellular communication. PMID:24016532
Application of network methods for understanding evolutionary dynamics in discrete habitats.
Greenbaum, Gili; Fefferman, Nina H
2017-06-01
In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.
An Evolutionary Game Theory Model of Spontaneous Brain Functioning.
Madeo, Dario; Talarico, Agostino; Pascual-Leone, Alvaro; Mocenni, Chiara; Santarnecchi, Emiliano
2017-11-22
Our brain is a complex system of interconnected regions spontaneously organized into distinct networks. The integration of information between and within these networks is a continuous process that can be observed even when the brain is at rest, i.e. not engaged in any particular task. Moreover, such spontaneous dynamics show predictive value over individual cognitive profile and constitute a potential marker in neurological and psychiatric conditions, making its understanding of fundamental importance in modern neuroscience. Here we present a theoretical and mathematical model based on an extension of evolutionary game theory on networks (EGN), able to capture brain's interregional dynamics by balancing emulative and non-emulative attitudes among brain regions. This results in the net behavior of nodes composing resting-state networks identified using functional magnetic resonance imaging (fMRI), determining their moment-to-moment level of activation and inhibition as expressed by positive and negative shifts in BOLD fMRI signal. By spontaneously generating low-frequency oscillatory behaviors, the EGN model is able to mimic functional connectivity dynamics, approximate fMRI time series on the basis of initial subset of available data, as well as simulate the impact of network lesions and provide evidence of compensation mechanisms across networks. Results suggest evolutionary game theory on networks as a new potential framework for the understanding of human brain network dynamics.
How Neural Networks Learn from Experience.
ERIC Educational Resources Information Center
Hinton, Geoffrey E.
1992-01-01
Discusses computational studies of learning in artificial neural networks and findings that may provide insights into the learning abilities of the human brain. Describes efforts to test theories about brain information processing, using artificial neural networks. Vignettes include information concerning how a neural network represents…
On the origins of hierarchy in complex networks
Corominas-Murtra, Bernat; Goñi, Joaquín; Solé, Ricard V.; Rodríguez-Caso, Carlos
2013-01-01
Hierarchy seems to pervade complexity in both living and artificial systems. Despite its relevance, no general theory that captures all features of hierarchy and its origins has been proposed yet. Here we present a formal approach resulting from the convergence of theoretical morphology and network theory that allows constructing a 3D morphospace of hierarchies and hence comparing the hierarchical organization of ecological, cellular, technological, and social networks. Embedded within large voids in the morphospace of all possible hierarchies, four major groups are identified. Two of them match the expected from random networks with similar connectivity, thus suggesting that nonadaptive factors are at work. Ecological and gene networks define the other two, indicating that their topological order is the result of functional constraints. These results are consistent with an exploration of the morphospace, using in silico evolved networks. PMID:23898177
English, Tammy; Carstensen, Laura L.
2014-01-01
Past research has documented age differences in the size and composition of social networks that suggest that networks grow smaller with age and include an increasingly greater proportion of well-known social partners. According to socioemotional selectivity theory, such changes in social network composition serve an antecedent emotion regulatory function that supports an age-related increase in the priority that people place on emotional well-being. The present study employed a longitudinal design with a sample that spanned the full adult age range to examine whether there is evidence of within-individual (developmental) change in social networks and whether the characteristics of relationships predict emotional experiences in daily life. Using growth curve analyses, social networks were found to increase in size in young adulthood and then decline steadily throughout later life. As postulated by socioemotional selectivity theory, reductions were observed primarily in the number of peripheral partners; the number of close partners was relatively stable over time. In addition, cross-sectional analyses revealed that older adults reported that social network members elicited less negative emotion and more positive emotion. The emotional tone of social networks, particularly when negative emotions were associated with network members, also predicted experienced emotion of participants. Overall, findings were robust after taking into account demographic variables and physical health. The implications of these findings are discussed in the context of socioemotional selectivity theory and related theoretical models. PMID:24910483
NASA Astrophysics Data System (ADS)
Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo
2015-11-01
Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively implement neighbourhood-based link prediction entirely in the bipartite domain.
Analytical theory of polymer-network-mediated interaction between colloidal particles
Di Michele, Lorenzo; Zaccone, Alessio; Eiser, Erika
2012-01-01
Nanostructured materials based on colloidal particles embedded in a polymer network are used in a variety of applications ranging from nanocomposite rubbers to organic-inorganic hybrid solar cells. Further, polymer-network-mediated colloidal interactions are highly relevant to biological studies whereby polymer hydrogels are commonly employed to probe the mechanical response of living cells, which can determine their biological function in physiological environments. The performance of nanomaterials crucially relies upon the spatial organization of the colloidal particles within the polymer network that depends, in turn, on the effective interactions between the particles in the medium. Existing models based on nonlocal equilibrium thermodynamics fail to clarify the nature of these interactions, precluding the way toward the rational design of polymer-composite materials. In this article, we present a predictive analytical theory of these interactions based on a coarse-grained model for polymer networks. We apply the theory to the case of colloids partially embedded in cross-linked polymer substrates and clarify the origin of attractive interactions recently observed experimentally. Monte Carlo simulation results that quantitatively confirm the theoretical predictions are also presented. PMID:22679289
Hiraishi, Kunihiko
2014-01-01
One of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GRNs to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of GRNs, and gene expression is expressed by a binary value (ON or OFF). In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. For CS-PBNs, the verification problem and the optimal control problem are considered. For the verification problem, a solution method using the probabilistic model checker PRISM is proposed. For the optimal control problem, a solution method using polynomial optimization is proposed. Finally, a numerical example on the WNT5A network, which is related to melanoma, is presented. The proposed methods provide us useful tools in control theory of GRNs. PMID:24587766
Game Theory Meets Wireless Sensor Networks Security Requirements and Threats Mitigation: A Survey.
Abdalzaher, Mohamed S; Seddik, Karim; Elsabrouty, Maha; Muta, Osamu; Furukawa, Hiroshi; Abdel-Rahman, Adel
2016-06-29
We present a study of using game theory for protecting wireless sensor networks (WSNs) from selfish behavior or malicious nodes. Due to scalability, low complexity and disseminated nature of WSNs, malicious attacks can be modeled effectively using game theory. In this study, we survey the different game-theoretic defense strategies for WSNs. We present a taxonomy of the game theory approaches based on the nature of the attack, whether it is caused by an external attacker or it is the result of an internal node acting selfishly or maliciously. We also present a general trust model using game theory for decision making. We, finally, identify the significant role of evolutionary games for WSNs security against intelligent attacks; then, we list several prospect applications of game theory to enhance the data trustworthiness and node cooperation in different WSNs.
Understanding Social Networks: Theories, Concepts, and Findings
ERIC Educational Resources Information Center
Kadushin, Charles
2012-01-01
Despite the swift spread of social network concepts and their applications and the rising use of network analysis in social science, there is no book that provides a thorough general introduction for the serious reader. "Understanding Social Networks" fills that gap by explaining the big ideas that underlie the social network phenomenon.…
ERIC Educational Resources Information Center
Johnson, Katherine A.; Robertson, Ian H.; Barry, Edwina; Mulligan, Aisling; Daibhis, Aoife; Daly, Michael; Watchorn, Amy; Gill, Michael; Bellgrove, Mark A.
2008-01-01
Background: An important theory of attention suggests that there are three separate networks that execute discrete cognitive functions. The "alerting" network acquires and maintains an alert state, the "orienting" network selects information from sensory input and the "conflict" network resolves conflict that arises between potential responses.…
Relationship between microscopic dynamics in traffic flow and complexity in networks.
Li, Xin-Gang; Gao, Zi-You; Li, Ke-Ping; Zhao, Xiao-Mei
2007-07-01
Complex networks are constructed in the evolution process of traffic flow, and the states of traffic flow are represented by nodes in the network. The traffic dynamics can then be studied by investigating the statistical properties of those networks. According to Kerner's three-phase theory, there are two different phases in congested traffic, synchronized flow and wide moving jam. In the framework of this theory, we study different properties of synchronized flow and moving jam in relation to complex network. Scale-free network is constructed in stop-and-go traffic, i.e., a sequence of moving jams [Chin. Phys. Lett. 10, 2711 (2005)]. In this work, the networks generated in synchronized flow are investigated in detail. Simulation results show that the degree distribution of the networks constructed in synchronized flow has two power law regions, so the distinction in topological structure can really reflect the different dynamics in traffic flow. Furthermore, the real traffic data are investigated by this method, and the results are consistent with the simulations.
Software Defined Network Monitoring Scheme Using Spectral Graph Theory and Phantom Nodes
2014-09-01
networks is the emergence of software - defined networking ( SDN ) [1]. SDN has existed for the...Chapter III for network monitoring. A. SOFTWARE DEFINED NETWORKS SDNs provide a new and innovative method to simplify network hardware by logically...and R. Giladi, “Performance analysis of software - defined networking ( SDN ),” in Proc. of IEEE 21st International Symposium on Modeling, Analysis
A Methodology to Develop Entrepreneurial Networks: The Tech Ecosystem of Six African Cities
2014-11-01
Information Center. Greve, A. and Salaff, J. W. (2003), Social Networks and Entrepreneurship . Entrepreneurship Theory and Practice, 28: 1–22. doi...methodology enables us to accurately measure social capital and circumvents the massive effort of mapping an individual’s social network before...locating the social resources in it. 15. SUBJECT TERMS Network Analysis, Economic Networks, Network Topology, Network Classification 16. SECURITY
Immunologic Approach to the Identification and Development of Vaccines to Various Toxins
1994-08-01
network theory of the immune system Ann Immunol (Paris) 125C.373. 4. Nisonoff, A., and E. Lamoyi. 1981 Implications of the presence of an internal image...reagents to examine idiotype networks within antiviral immune responses. J. Virol. Methods. 25:123. 32. Benton BJ, Rivera, V.R., Hewetson J.F., and Chang F...vari’able (V) region of’ an antibody ( 1974). Jernie’s network theory states that in- (Ab) molecule. Anti-ld (or Ab2) are specific teractions between ld and
NASA Astrophysics Data System (ADS)
Xue, Jingxin
The article aims to completely, systematically and objectively analyze the current situation of Entrepreneurship Education in China with Ecological Systems Theory. From this perspective, the author discusses the structure, function and its basic features of higher education entrepreneur services network system, and puts forward the opinion that every entrepreneurship organization in higher education institution does not limited to only one platform. Different functional supporting platforms should be combined closed through composite functional organization to form an integrated network system, in which each unit would impels others' development.
Calculating degree-based topological indices of dominating David derived networks
NASA Astrophysics Data System (ADS)
Ahmad, Muhammad Saeed; Nazeer, Waqas; Kang, Shin Min; Imran, Muhammad; Gao, Wei
2017-12-01
An important area of applied mathematics is the Chemical reaction network theory. The behavior of real world problems can be modeled by using this theory. Due to applications in theoretical chemistry and biochemistry, it has attracted researchers since its foundation. It also attracts pure mathematicians because it involves interesting mathematical structures. In this report, we compute newly defined topological indices, namely, Arithmetic-Geometric index (AG1 index), SK index, SK1 index, and SK2 index of the dominating David derived networks [1, 2, 3, 4, 5].
Recent advances in coding theory for near error-free communications
NASA Technical Reports Server (NTRS)
Cheung, K.-M.; Deutsch, L. J.; Dolinar, S. J.; Mceliece, R. J.; Pollara, F.; Shahshahani, M.; Swanson, L.
1991-01-01
Channel and source coding theories are discussed. The following subject areas are covered: large constraint length convolutional codes (the Galileo code); decoder design (the big Viterbi decoder); Voyager's and Galileo's data compression scheme; current research in data compression for images; neural networks for soft decoding; neural networks for source decoding; finite-state codes; and fractals for data compression.
ERIC Educational Resources Information Center
Fung, Helene H.; Carstensen, Laura L.; Lang, Frieder, R.
2001-01-01
Tests socioemotional selectivity theory among African Americans and European Americans. Older people reported as many close partners but fewer peripheral partners as their younger counterparts, thus confirming the theory. A greater percentage of close social partners in social networks related to lower levels of happiness among the young age group…
ERIC Educational Resources Information Center
Moberg, Emilie
2018-01-01
This paper undertakes an investigation of the "life" of the curriculum concept of "children's interests" in a preschool practice. The concept of "children's interests" plays a vital role in the Swedish preschool curriculum text and in the preschool field. Strongly inspired by Actor-network theory readings, the paper…
ERIC Educational Resources Information Center
Blandy, Doug
2011-01-01
Art education is a systemic and extensive network within which children, youth, and adults make and learn about material culture. This lecture considers three sites of theory and practice that I see as ascendant in circulating through this network. These sites are sustainability, participatory culture, and performing democracy. I argue that…
ERIC Educational Resources Information Center
Heo, Gyeong Mi; Lee, Romee
2013-01-01
This paper uses an Activity Theory framework to explore adult user activities and informal learning processes as reflected in their blogs and social network sites (SNS). Using the assumption that a web-based space is an activity system in which learning occurs, typical features of the components were investigated and each activity system then…
ERIC Educational Resources Information Center
Waltz, Scott B.
2006-01-01
The aim of this paper is to call attention to the missing discourse of non-humans as social actors in the Social Foundations of Education. The paper outlines three common figuring metaphors that impede the adoption of such a theoretical discourse and shows how Actor-Network Theory (ANT), more recently developed in the nascent field of Science and…
A statistical mechanics approach to autopoietic immune networks
NASA Astrophysics Data System (ADS)
Barra, Adriano; Agliari, Elena
2010-07-01
In this work we aim to bridge theoretical immunology and disordered statistical mechanics. We introduce a model for the behavior of B-cells which naturally merges the clonal selection theory and the autopoietic network theory as a whole. From the analysis of its features we recover several basic phenomena such as low-dose tolerance, dynamical memory of antigens and self/non-self discrimination.
Analysis and Modeling of Ground Operations at Hub Airports
NASA Technical Reports Server (NTRS)
Atkins, Stephen (Technical Monitor); Andersson, Kari; Carr, Francis; Feron, Eric; Hall, William D.
2000-01-01
Building simple and accurate models of hub airports can considerably help one understand airport dynamics, and may provide quantitative estimates of operational airport improvements. In this paper, three models are proposed to capture the dynamics of busy hub airport operations. Two simple queuing models are introduced to capture the taxi-out and taxi-in processes. An integer programming model aimed at representing airline decision-making attempts to capture the dynamics of the aircraft turnaround process. These models can be applied for predictive purposes. They may also be used to evaluate control strategies for improving overall airport efficiency.
Research the simulation model of the passenger travel behavior in urban rail platform
NASA Astrophysics Data System (ADS)
Wang, Yujia; Yin, Xiangyong
2017-05-01
Based on the results of the research on the platform of the Beijing Chegongzhuang subway station in the line 2, the passenger travel behavior in urban rail platform is divided into 4 parts, which are the enter passenger walking, the passenger waiting distribution and queuing up before the door, passenger boarding and alighting and the alighting passengers walking, according to the social force model, simulation model was built based on Matlab software. Combined with the actual data of subway the Chegongzhuang subway station in the line 2, the simulation results show that the social force model is effective.
Optimal information transfer in enzymatic networks: A field theoretic formulation
NASA Astrophysics Data System (ADS)
Samanta, Himadri S.; Hinczewski, Michael; Thirumalai, D.
2017-07-01
Signaling in enzymatic networks is typically triggered by environmental fluctuations, resulting in a series of stochastic chemical reactions, leading to corruption of the signal by noise. For example, information flow is initiated by binding of extracellular ligands to receptors, which is transmitted through a cascade involving kinase-phosphatase stochastic chemical reactions. For a class of such networks, we develop a general field-theoretic approach to calculate the error in signal transmission as a function of an appropriate control variable. Application of the theory to a simple push-pull network, a module in the kinase-phosphatase cascade, recovers the exact results for error in signal transmission previously obtained using umbral calculus [Hinczewski and Thirumalai, Phys. Rev. X 4, 041017 (2014), 10.1103/PhysRevX.4.041017]. We illustrate the generality of the theory by studying the minimal errors in noise reduction in a reaction cascade with two connected push-pull modules. Such a cascade behaves as an effective three-species network with a pseudointermediate. In this case, optimal information transfer, resulting in the smallest square of the error between the input and output, occurs with a time delay, which is given by the inverse of the decay rate of the pseudointermediate. Surprisingly, in these examples the minimum error computed using simulations that take nonlinearities and discrete nature of molecules into account coincides with the predictions of a linear theory. In contrast, there are substantial deviations between simulations and predictions of the linear theory in error in signal propagation in an enzymatic push-pull network for a certain range of parameters. Inclusion of second-order perturbative corrections shows that differences between simulations and theoretical predictions are minimized. Our study establishes that a field theoretic formulation of stochastic biological signaling offers a systematic way to understand error propagation in networks of arbitrary complexity.
From Foucault to Freire through Facebook: Toward an Integrated Theory of mHealth
ERIC Educational Resources Information Center
Bull, Sheana; Ezeanochie, Nnamdi
2016-01-01
Objective: To document the integration of social science theory in literature on mHealth (mobile health) and consider opportunities for integration of classic theory, health communication theory, and social networking to generate a relevant theory for mHealth program design. Method: A secondary review of research syntheses and meta-analyses…
Topological entropy of catalytic sets: Hypercycles revisited
NASA Astrophysics Data System (ADS)
Sardanyés, Josep; Duarte, Jorge; Januário, Cristina; Martins, Nuno
2012-02-01
The dynamics of catalytic networks have been widely studied over the last decades because of their implications in several fields like prebiotic evolution, virology, neural networks, immunology or ecology. One of the most studied mathematical bodies for catalytic networks was initially formulated in the context of prebiotic evolution, by means of the hypercycle theory. The hypercycle is a set of self-replicating species able to catalyze other replicator species within a cyclic architecture. Hypercyclic organization might arise from a quasispecies as a way to increase the informational containt surpassing the so-called error threshold. The catalytic coupling between replicators makes all the species to behave like a single and coherent evolutionary multimolecular unit. The inherent nonlinearities of catalytic interactions are responsible for the emergence of several types of dynamics, among them, chaos. In this article we begin with a brief review of the hypercycle theory focusing on its evolutionary implications as well as on different dynamics associated to different types of small catalytic networks. Then we study the properties of chaotic hypercycles with error-prone replication with symbolic dynamics theory, characterizing, by means of the theory of topological Markov chains, the topological entropy and the periods of the orbits of unimodal-like iterated maps obtained from the strange attractor. We will focus our study on some key parameters responsible for the structure of the catalytic network: mutation rates, autocatalytic and cross-catalytic interactions.
Time-dependence of graph theory metrics in functional connectivity analysis
Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J.; Haneef, Zulfi; Stern, John M.
2016-01-01
Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. PMID:26518632
Time-dependence of graph theory metrics in functional connectivity analysis.
Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J; Haneef, Zulfi; Stern, John M
2016-01-15
Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. Copyright © 2015 Elsevier Inc. All rights reserved.
Critical exponents for diluted resistor networks
NASA Astrophysics Data System (ADS)
Stenull, O.; Janssen, H. K.; Oerding, K.
1999-05-01
An approach by Stephen [Phys. Rev. B 17, 4444 (1978)] is used to investigate the critical properties of randomly diluted resistor networks near the percolation threshold by means of renormalized field theory. We reformulate an existing field theory by Harris and Lubensky [Phys. Rev. B 35, 6964 (1987)]. By a decomposition of the principal Feynman diagrams, we obtain diagrams which again can be interpreted as resistor networks. This interpretation provides for an alternative way of evaluating the Feynman diagrams for random resistor networks. We calculate the resistance crossover exponent φ up to second order in ɛ=6-d, where d is the spatial dimension. Our result φ=1+ɛ/42+4ɛ2/3087 verifies a previous calculation by Lubensky and Wang, which itself was based on the Potts-model formulation of the random resistor network.
NASA Astrophysics Data System (ADS)
Gotoda, Hiroshi; Kinugawa, Hikaru; Tsujimoto, Ryosuke; Domen, Shohei; Okuno, Yuta
2017-04-01
Complex-network theory has attracted considerable attention for nearly a decade, and it enables us to encompass our understanding of nonlinear dynamics in complex systems in a wide range of fields, including applied physics and mechanical, chemical, and electrical engineering. We conduct an experimental study using a pragmatic online detection methodology based on complex-network theory to prevent a limiting unstable state such as blowout in a confined turbulent combustion system. This study introduces a modified version of the natural visibility algorithm based on the idea of a visibility limit to serve as a pragmatic online detector. The average degree of the modified version of the natural visibility graph allows us to detect the onset of blowout, resulting in online prevention.
Social patterns revealed through random matrix theory
NASA Astrophysics Data System (ADS)
Sarkar, Camellia; Jalan, Sarika
2014-11-01
Despite the tremendous advancements in the field of network theory, very few studies have taken weights in the interactions into consideration that emerge naturally in all real-world systems. Using random matrix analysis of a weighted social network, we demonstrate the profound impact of weights in interactions on emerging structural properties. The analysis reveals that randomness existing in particular time frame affects the decisions of individuals rendering them more freedom of choice in situations of financial security. While the structural organization of networks remains the same throughout all datasets, random matrix theory provides insight into the interaction pattern of individuals of the society in situations of crisis. It has also been contemplated that individual accountability in terms of weighted interactions remains as a key to success unless segregation of tasks comes into play.
NASA Astrophysics Data System (ADS)
Ren, Fengli; Cao, Jinde
2007-03-01
In this paper, several sufficient conditions are obtained ensuring existence, global attractivity and global asymptotic stability of the periodic solution for the higher-order bidirectional associative memory neural networks with periodic coefficients and delays by using the continuation theorem of Mawhin's coincidence degree theory, the Lyapunov functional and the non-singular M-matrix. Two examples are exploited to illustrate the effectiveness of the proposed criteria. These results are more effective than the ones in the literature for some neural networks, and can be applied to the design of globally attractive or globally asymptotically stable networks and thus have important significance in both theory and applications.
NASA Astrophysics Data System (ADS)
Malarz, K.; Szvetelszky, Z.; Szekf, B.; Kulakowski, K.
2006-11-01
We consider the average probability X of being informed on a gossip in a given social network. The network is modeled within the random graph theory of Erd{õ}s and Rényi. In this theory, a network is characterized by two parameters: the size N and the link probability p. Our experimental data suggest three levels of social inclusion of friendship. The critical value pc, for which half of agents are informed, scales with the system size as N-gamma with gamma approx 0.68. Computer simulations show that the probability X varies with p as a sigmoidal curve. Influence of the correlations between neighbors is also evaluated: with increasing clustering coefficient C, X decreases.
Recruitment dynamics in adaptive social networks
NASA Astrophysics Data System (ADS)
Shkarayev, Maxim; Shaw, Leah; Schwartz, Ira
2011-03-01
We model recruitment in social networks in the presence of birth and death processes. The recruitment is characterized by nodes changing their status to that of the recruiting class as a result of contact with recruiting nodes. The recruiting nodes may adapt their connections in order to improve recruitment capabilities, thus changing the network structure. We develop a mean-field theory describing the system dynamics. Using mean-field theory we characterize the dependence of the growth threshold of the recruiting class on the adaptation parameter. Furthermore, we investigate the effect of adaptation on the recruitment dynamics, as well as on network topology. The theoretical predictions are confirmed by the direct simulations of the full system.
Dawson, Michael R W; Dupuis, Brian; Spetch, Marcia L; Kelly, Debbie M
2009-08-01
The matching law (Herrnstein 1961) states that response rates become proportional to reinforcement rates; this is related to the empirical phenomenon called probability matching (Vulkan 2000). Here, we show that a simple artificial neural network generates responses consistent with probability matching. This behavior was then used to create an operant procedure for network learning. We use the multiarmed bandit (Gittins 1989), a classic problem of choice behavior, to illustrate that operant training balances exploiting the bandit arm expected to pay off most frequently with exploring other arms. Perceptrons provide a medium for relating results from neural networks, genetic algorithms, animal learning, contingency theory, reinforcement learning, and theories of choice.
Immunization of Epidemics in Multiplex Networks
Zhao, Dawei; Wang, Lianhai; Li, Shudong; Wang, Zhen; Wang, Lin; Gao, Bo
2014-01-01
Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted) immunization and layer node-based random (targeted) immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER) random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF) networks. PMID:25401755
Immunization of epidemics in multiplex networks.
Zhao, Dawei; Wang, Lianhai; Li, Shudong; Wang, Zhen; Wang, Lin; Gao, Bo
2014-01-01
Up to now, immunization of disease propagation has attracted great attention in both theoretical and experimental researches. However, vast majority of existing achievements are limited to the simple assumption of single layer networked population, which seems obviously inconsistent with recent development of complex network theory: each node could possess multiple roles in different topology connections. Inspired by this fact, we here propose the immunization strategies on multiplex networks, including multiplex node-based random (targeted) immunization and layer node-based random (targeted) immunization. With the theory of generating function, theoretical analysis is developed to calculate the immunization threshold, which is regarded as the most critical index for the effectiveness of addressed immunization strategies. Interestingly, both types of random immunization strategies show more efficiency in controlling disease spreading on multiplex Erdös-Rényi (ER) random networks; while targeted immunization strategies provide better protection on multiplex scale-free (SF) networks.
Margolis, Alvaro; Parboosingh, John
2015-01-01
Prior interpersonal relationships and interactivity among members of professional associations may impact the learning process in continuing medical education (CME). On the other hand, CME programs that encourage interactivity between participants may impact structures and behaviors in these professional associations. With the advent of information and communication technologies, new communication spaces have emerged that have the potential to enhance networked learning in national and international professional associations and increase the effectiveness of CME for health professionals. In this article, network science, based on the application of network theory and other theories, is proposed as an approach to better understand the contribution networking and interactivity between health professionals in professional communities make to their learning and adoption of new practices over time. © 2015 The Alliance for Continuing Education in the Health Professions, the Society for Academic Continuing Medical Education, and the Council on Continuing Medical Education, Association for Hospital Medical Education.
Finite state model and compatibility theory - New analysis tools for permutation networks
NASA Technical Reports Server (NTRS)
Huang, S.-T.; Tripathi, S. K.
1986-01-01
A simple model to describe the fundamental operation theory of shuffle-exchange-type permutation networks, the finite permutation machine (FPM), is described, and theorems which transform the control matrix result to a continuous compatible vector result are developed. It is found that only 2n-1 shuffle exchange passes are necessary, and that 3n-3 passes are sufficient, to realize all permutations, reducing the sufficient number of passes by two from previous results. The flexibility of the approach is demonstrated by the description of a stack permutation machine (SPM) which can realize all permutations, and by showing that the FPM corresponding to the Benes (1965) network belongs to the SPM. The FPM corresponding to the network with two cascaded reverse-exchange networks is found to realize all permutations, and a simple mechanism to verify several equivalence relationships of various permutation networks is discussed.
NASA Astrophysics Data System (ADS)
Yeghiazarian, L.; Riasi, M. S.
2016-12-01
Although controlling the level of contamination everywhere in the surface water network may not be feasible, it is vital to maintain safe water quality levels in specific areas, e.g. recreational waters. The question then is "what is the most efficient way to fully/partially control water quality in surface water networks?". This can be posed as a control problem where the goal is to efficiently drive the system to a desired state by manipulating few input variables. Such problems reduce to (1) finding the best control locations in the network to influence the state of the system; and (2) choosing the time-variant inputs at the control locations to achieve the desired state of the system with minimum effort. We demonstrate that the optimal solution to control the level of contamination in the network can be found through application of control theory concepts to transport in dendritic surface water networks.
NASA Astrophysics Data System (ADS)
Čech, Radek
2014-12-01
After a rapid and successful development of the theory of complex networks at the turn of the millennium [1,2], attempts to apply this theory to a language analysis emerged immediately [3,4]. The first results seemed to bring new insights to the functioning of language. Moreover, some authors assumed that this approach can even solve some fundamental problems concerning language evolution [5,6]. However, after a decade of the application of complex network theory to language analysis, the initial expectations have not been fulfilled, in my opinion, and the need for a deeper, linguistically based explanation of observed properties has been still more obvious. Cong and Liu's review [7] can be seen as a successful attempt to clarify the main aspects of this kind of research from the linguistics point of view. However, I see two problematic aspects in their study relating to the nature of the character of explanation.
Adaptive capacity of geographical clusters: Complexity science and network theory approach
NASA Astrophysics Data System (ADS)
Albino, Vito; Carbonara, Nunzia; Giannoccaro, Ilaria
This paper deals with the adaptive capacity of geographical clusters (GCs), that is a relevant topic in the literature. To address this topic, GC is considered as a complex adaptive system (CAS). Three theoretical propositions concerning the GC adaptive capacity are formulated by using complexity theory. First, we identify three main properties of CAS s that affect the adaptive capacity, namely the interconnectivity, the heterogeneity, and the level of control, and define how the value of these properties influence the adaptive capacity. Then, we associate these properties with specific GC characteristics so obtaining the key conditions of GCs that give them the adaptive capacity so assuring their competitive advantage. To test these theoretical propositions, a case study on two real GCs is carried out. The considered GCs are modeled as networks where firms are nodes and inter-firms relationships are links. Heterogeneity, interconnectivity, and level of control are considered as network properties and thus measured by using the methods of the network theory.
Steady states and stability in metabolic networks without regulation.
Ivanov, Oleksandr; van der Schaft, Arjan; Weissing, Franz J
2016-07-21
Metabolic networks are often extremely complex. Despite intensive efforts many details of these networks, e.g., exact kinetic rates and parameters of metabolic reactions, are not known, making it difficult to derive their properties. Considerable effort has been made to develop theory about properties of steady states in metabolic networks that are valid for any values of parameters. General results on uniqueness of steady states and their stability have been derived with specific assumptions on reaction kinetics, stoichiometry and network topology. For example, deep results have been obtained under the assumptions of mass-action reaction kinetics, continuous flow stirred tank reactors (CFSTR), concordant reaction networks and others. Nevertheless, a general theory about properties of steady states in metabolic networks is still missing. Here we make a step further in the quest for such a theory. Specifically, we study properties of steady states in metabolic networks with monotonic kinetics in relation to their stoichiometry (simple and general) and the number of metabolites participating in every reaction (single or many). Our approach is based on the investigation of properties of the Jacobian matrix. We show that stoichiometry, network topology, and the number of metabolites that participate in every reaction have a large influence on the number of steady states and their stability in metabolic networks. Specifically, metabolic networks with single-substrate-single-product reactions have disconnected steady states, whereas in metabolic networks with multiple-substrates-multiple-product reactions manifolds of steady states arise. Metabolic networks with simple stoichiometry have either a unique globally asymptotically stable steady state or asymptotically stable manifolds of steady states. In metabolic networks with general stoichiometry the steady states are not always stable and we provide conditions for their stability. In order to demonstrate the biological relevance we illustrate the results on the examples of the TCA cycle, the mevalonate pathway and the Calvin cycle. Copyright © 2016 Elsevier Ltd. All rights reserved.
Hemispheric asymmetry of electroencephalography-based functional brain networks.
Jalili, Mahdi
2014-11-12
Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically meaningful graph theory metrics: global and local efficiency measures. The global efficiency did not show any hemispheric asymmetry, whereas the local connectivity showed rightward asymmetry for a range of intermediate density values for the constructed networks. Furthermore, the age of the participants showed significant direct correlations with the global efficiency of the left hemisphere, but only in the right hemisphere, with local connectivity. These results suggest that only local connectivity of EEG-based functional networks is associated with brain hemispheres.
The Role of the Theory-of-Mind Cortical Network in the Comprehension of Narratives
Mason, Robert A.; Just, Marcel Adam
2009-01-01
Narrative comprehension rests on the ability to understand the intentions and perceptions of various agents in a story who interact with respect to some goal or problem. Reasoning about the state of mind of another person, real or fictional, has been referred to as Theory of Mind processing. While Theory of Mind Processing was first postulated prior to the existence of neuroimaging research, fMRI studies make it possible to characterize this processing in some detail. We propose that narrative comprehension makes use of some of the neural substrate of Theory of Mind reasoning, evoking what is referred to as a protagonist perspective network. The main cortical components of this protagonist-based network are the dorsomedial prefrontal cortex and the right temporo-parietal junction. The article discusses how these two cortical centers interact in narrative comprehension but still play distinguishable roles, and how the interaction between the two centers is disrupted in individuals with autism. PMID:19809575
Towards overcoming the Monte Carlo sign problem with tensor networks
NASA Astrophysics Data System (ADS)
Bañuls, Mari Carmen; Cichy, Krzysztof; Ignacio Cirac, J.; Jansen, Karl; Kühn, Stefan; Saito, Hana
2017-03-01
The study of lattice gauge theories with Monte Carlo simulations is hindered by the infamous sign problem that appears under certain circumstances, in particular at non-zero chemical potential. So far, there is no universal method to overcome this problem. However, recent years brought a new class of non-perturbative Hamiltonian techniques named tensor networks, where the sign problem is absent. In previous work, we have demonstrated that this approach, in particular matrix product states in 1+1 dimensions, can be used to perform precise calculations in a lattice gauge theory, the massless and massive Schwinger model. We have computed the mass spectrum of this theory, its thermal properties and real-time dynamics. In this work, we review these results and we extend our calculations to the case of two flavours and non-zero chemical potential. We are able to reliably reproduce known analytical results for this model, thus demonstrating that tensor networks can tackle the sign problem of a lattice gauge theory at finite density.
Student trajectories in physics: the need for analysis through a socio-cultural lens
NASA Astrophysics Data System (ADS)
Zapata, Mara
2010-09-01
An analysis of student connections through time and space relative to the core discipline of physics is attempted, as viewed through the lens of actor-network-theory, by Antonia Candela. Using lenses of cultural realities, networks, and perceived power in the discourse of one specific university in the capital city of Mexico and one undergraduate physics classroom, the trajectories and itineraries of students are analyzed, relative to a physics professor's pedagogical practices. This ethnographic study then yields comparisons between Mexican undergraduate students and students from the United States. Actor network theory recognizes that the symbiotic relationship existing between an actor and a continuum of space and time is defined by the symbiotic yet interdependent relationships and networks of practice (Lemke in Downward causation: Minds, bodies, and matter 2000). As part of this study and in line with actor-network-theory, human actors and non-human participants were viewed in relation to how subjects acted and were acted upon within networks of practice. Through this forum I reflect on this work with particular focus on the issues of situatedness of actors from a sociocultural perspective and how established networks viewed within this perspective frame and subsequently impact student trajectories and itineraries. In essence I argue for a need to look at a myriad of further complexities driving the symbiotic relationships being analyzed.
Gibson, Scott M; Ficklin, Stephen P; Isaacson, Sven; Luo, Feng; Feltus, Frank A; Smith, Melissa C
2013-01-01
The study of gene relationships and their effect on biological function and phenotype is a focal point in systems biology. Gene co-expression networks built using microarray expression profiles are one technique for discovering and interpreting gene relationships. A knowledge-independent thresholding technique, such as Random Matrix Theory (RMT), is useful for identifying meaningful relationships. Highly connected genes in the thresholded network are then grouped into modules that provide insight into their collective functionality. While it has been shown that co-expression networks are biologically relevant, it has not been determined to what extent any given network is functionally robust given perturbations in the input sample set. For such a test, hundreds of networks are needed and hence a tool to rapidly construct these networks. To examine functional robustness of networks with varying input, we enhanced an existing RMT implementation for improved scalability and tested functional robustness of human (Homo sapiens), rice (Oryza sativa) and budding yeast (Saccharomyces cerevisiae). We demonstrate dramatic decrease in network construction time and computational requirements and show that despite some variation in global properties between networks, functional similarity remains high. Moreover, the biological function captured by co-expression networks thresholded by RMT is highly robust.
Song, Kaida; Wang, Rui; Liu, Yi; Qian, Depei; Zhang, Han; Cai, Jihong
2015-01-01
Community networks, the distinguishing feature of which is membership admittance, appear on P2P networks, social networks, and conventional Web networks. Joining the network costs money, time or network bandwidth, but the individuals get access to special resources owned by the community in return. The prosperity and stability of the community are determined by both the policy of admittance and the attraction of the privileges gained by joining. However, some misbehaving users can get the dedicated resources with some illicit and low-cost approaches, which introduce instability into the community, a phenomenon that will destroy the membership policy. In this paper, we analyze on the stability using game theory on such a phenomenon. We propose a game-theoretical model of stability analysis in community networks and provide conditions for a stable community. We then extend the model to analyze the effectiveness of different incentive policies, which could be used when the community cannot maintain its members in certain situations. Then we verify those models through a simulation. Finally, we discuss several ways to promote community network's stability by adjusting the network's properties and give some proposal on the designs of these types of networks from the points of game theory and stability.
Composing Networks: Writing Practices on Mobile Devices
ERIC Educational Resources Information Center
Swarts, Jason
2016-01-01
This article is an investigation of composing practices through which people create networks with mobile phones. By looking through the lens of actor-network theory, the author portrays the networking activity of mobile phone users as translation, what Latour describes as an infralanguage to which different disciplinary perspectives can be…
Reinforce Networking Theory with OPNET Simulation
ERIC Educational Resources Information Center
Guo, Jinhua; Xiang, Weidong; Wang, Shengquan
2007-01-01
As networking systems have become more complex and expensive, hands-on experiments based on networking simulation have become essential for teaching the key computer networking topics to students. The simulation approach is the most cost effective and highly useful because it provides a virtual environment for an assortment of desirable features…