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Sample records for agent-based intrusion detection

  1. Intelligent Agent-Based Intrusion Detection System Using Enhanced Multiclass SVM

    PubMed Central

    Ganapathy, S.; Yogesh, P.; Kannan, A.

    2012-01-01

    Intrusion detection systems were used in the past along with various techniques to detect intrusions in networks effectively. However, most of these systems are able to detect the intruders only with high false alarm rate. In this paper, we propose a new intelligent agent-based intrusion detection model for mobile ad hoc networks using a combination of attribute selection, outlier detection, and enhanced multiclass SVM classification methods. For this purpose, an effective preprocessing technique is proposed that improves the detection accuracy and reduces the processing time. Moreover, two new algorithms, namely, an Intelligent Agent Weighted Distance Outlier Detection algorithm and an Intelligent Agent-based Enhanced Multiclass Support Vector Machine algorithm are proposed for detecting the intruders in a distributed database environment that uses intelligent agents for trust management and coordination in transaction processing. The experimental results of the proposed model show that this system detects anomalies with low false alarm rate and high-detection rate when tested with KDD Cup 99 data set. PMID:23056036

  2. Interior intrusion detection systems

    SciTech Connect

    Rodriguez, J.R.; Matter, J.C. ); Dry, B. )

    1991-10-01

    The purpose of this NUREG is to present technical information that should be useful to NRC licensees in designing interior intrusion detection systems. Interior intrusion sensors are discussed according to their primary application: boundary-penetration detection, volumetric detection, and point protection. Information necessary for implementation of an effective interior intrusion detection system is presented, including principles of operation, performance characteristics and guidelines for design, procurement, installation, testing, and maintenance. A glossary of sensor data terms is included. 36 figs., 6 tabs.

  3. Detecting Signs of Intrusion.

    DTIC Science & Technology

    1997-08-01

    your systems, you should investigate any warnings they sound. Although monitors are not fool- proof, they can be part of an effective early warning ...Carnegie Mellon University Software Engineering Institute Detecting Signs of Intrusion Robert Firth Gary Ford Barbara Fräser John Kochmar...1997 Detecting Signs of Intrusion Robert Firth Gary Ford Barbara Fräser John Kochmar Suresh Konda John Richael Derek Simmel Networked Systems

  4. Smell Detection Agent Based Optimization Algorithm

    NASA Astrophysics Data System (ADS)

    Vinod Chandra, S. S.

    2016-09-01

    In this paper, a novel nature-inspired optimization algorithm has been employed and the trained behaviour of dogs in detecting smell trails is adapted into computational agents for problem solving. The algorithm involves creation of a surface with smell trails and subsequent iteration of the agents in resolving a path. This algorithm can be applied in different computational constraints that incorporate path-based problems. Implementation of the algorithm can be treated as a shortest path problem for a variety of datasets. The simulated agents have been used to evolve the shortest path between two nodes in a graph. This algorithm is useful to solve NP-hard problems that are related to path discovery. This algorithm is also useful to solve many practical optimization problems. The extensive derivation of the algorithm can be enabled to solve shortest path problems.

  5. Intrusion detection using secure signatures

    DOEpatents

    Nelson, Trent Darnel; Haile, Jedediah

    2014-09-30

    A method and device for intrusion detection using secure signatures comprising capturing network data. A search hash value, value employing at least one one-way function, is generated from the captured network data using a first hash function. The presence of a search hash value match in a secure signature table comprising search hash values and an encrypted rule is determined. After determining a search hash value match, a decryption key is generated from the captured network data using a second hash function, a hash function different form the first hash function. One or more of the encrypted rules of the secure signatures table having a hash value equal to the generated search hash value are then decrypted using the generated decryption key. The one or more decrypted secure signature rules are then processed for a match and one or more user notifications are deployed if a match is identified.

  6. AIDE - Advanced Intrusion Detection Environment

    SciTech Connect

    Smith, Cathy L.

    2013-04-28

    Would you like to know when someone has dropped an undesirable executable binary on our system? What about something less malicious such as a software installation by a user? What about the user who decides to install a newer version of mod_perl or PHP on your web server without letting you know beforehand? Or even something as simple as when an undocumented config file change is made by another member of the admin group? Do you even want to know about all the changes that happen on a daily basis on your server? The purpose of an intrusion detection system (IDS) is to detect unauthorized, possibly malicious activity. The purpose of a host-based IDS, or file integrity checker, is check for unauthorized changes to key system files, binaries, libraries, and directories on the system. AIDE is an Open Source file and directory integrity checker. AIDE will let you know when a file or directory has been added, deleted, modified. It is included with the Red Hat Enterprise 6. It is available for other Linux distros. This is a case study describing the process of configuring AIDE on an out of the box RHEL6 installation. Its goal is to illustrate the thinking and the process by which a useful AIDE configuration is built.

  7. Adapting safety requirements analysis to intrusion detection

    NASA Technical Reports Server (NTRS)

    Lutz, R.

    2001-01-01

    Several requirements analysis techniques widely used in safety-critical systems are being adapted to support the analysis of secure systems. Perhaps the most relevant system safety techique for Intrusion Detection Systems is hazard analysis.

  8. A Radiating Cable Intrusion Detection System

    DTIC Science & Technology

    1980-06-01

    RtADC-Th40O1"ř June 1930 A RADIATING CABLE INTRUSION 0 DETECTION SYSTEM Northeastern University Spencer d. Rochefort Raimundas Sukys Norman C...J.7[ochefortF168R. Raimundas/ Sukys SADDROSSAMfELEMENT,.PROJECT. TASK Electronics Research Labe.*&tory 11. CONTROLLING OFFICE NAME AND ADDRESS Hanscom...stable threshold levels. -a- -22- REFERENCES 1. Rochefort, J.S., Sukys , R. and Poirier, N.C. (1978), "An Area Intrusion Detection and Alarm System

  9. A system for distributed intrusion detection

    SciTech Connect

    Snapp, S.R.; Brentano, J.; Dias, G.V.; Goan, T.L.; Heberlein, L.T.; Ho, Che-Lin; Levitt, K.N.; Mukherjee, B. . Div. of Computer Science); Grance, T. ); Mansur, D.L.; Pon, K.L. ); Smaha, S.E. )

    1991-01-01

    The study of providing security in computer networks is a rapidly growing area of interest because the network is the medium over which most attacks or intrusions on computer systems are launched. One approach to solving this problem is the intrusion-detection concept, whose basic premise is that not only abandoning the existing and huge infrastructure of possibly-insecure computer and network systems is impossible, but also replacing them by totally-secure systems may not be feasible or cost effective. Previous work on intrusion-detection systems were performed on stand-alone hosts and on a broadcast local area network (LAN) environment. The focus of our present research is to extend our network intrusion-detection concept from the LAN environment to arbitarily wider areas with the network topology being arbitrary as well. The generalized distributed environment is heterogeneous, i.e., the network nodes can be hosts or servers from different vendors, or some of them could be LAN managers, like our previous work, a network security monitor (NSM), as well. The proposed architecture for this distributed intrusion-detection system consists of the following components: a host manager in each host; a LAN manager for monitoring each LAN in the system; and a central manager which is placed at a single secure location and which receives reports from various host and LAN managers to process these reports, correlate them, and detect intrusions. 11 refs., 2 figs.

  10. Autonomous Rule Creation for Intrusion Detection

    SciTech Connect

    Todd Vollmer; Jim Alves-Foss; Milos Manic

    2011-04-01

    Many computational intelligence techniques for anomaly based network intrusion detection can be found in literature. Translating a newly discovered intrusion recognition criteria into a distributable rule can be a human intensive effort. This paper explores a multi-modal genetic algorithm solution for autonomous rule creation. This algorithm focuses on the process of creating rules once an intrusion has been identified, rather than the evolution of rules to provide a solution for intrusion detection. The algorithm was demonstrated on anomalous ICMP network packets (input) and Snort rules (output of the algorithm). Output rules were sorted according to a fitness value and any duplicates were removed. The experimental results on ten test cases demonstrated a 100 percent rule alert rate. Out of 33,804 test packets 3 produced false positives. Each test case produced a minimum of three rule variations that could be used as candidates for a production system.

  11. An automatically tuning intrusion detection system.

    PubMed

    Yu, Zhenwei; Tsai, Jeffrey J P; Weigert, Thomas

    2007-04-01

    An intrusion detection system (IDS) is a security layer used to detect ongoing intrusive activities in information systems. Traditionally, intrusion detection relies on extensive knowledge of security experts, in particular, on their familiarity with the computer system to be protected. To reduce this dependence, various data-mining and machine learning techniques have been deployed for intrusion detection. An IDS is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current systems depends on the system operators in working out the tuning solution and in integrating it into the detection model. In this paper, an automatically tuning IDS (ATIDS) is presented. The proposed system will automatically tune the detection model on-the-fly according to the feedback provided by the system operator when false predictions are encountered. The system is evaluated using the KDDCup'99 intrusion detection dataset. Experimental results show that the system achieves up to 35% improvement in terms of misclassification cost when compared with a system lacking the tuning feature. If only 10% false predictions are used to tune the model, the system still achieves about 30% improvement. Moreover, when tuning is not delayed too long, the system can achieve about 20% improvement, with only 1.3% of the false predictions used to tune the model. The results of the experiments show that a practical system can be built based on ATIDS: system operators can focus on verification of predictions with low confidence, as only those predictions determined to be false will be used to tune the detection model.

  12. An Adaptive Database Intrusion Detection System

    ERIC Educational Resources Information Center

    Barrios, Rita M.

    2011-01-01

    Intrusion detection is difficult to accomplish when attempting to employ current methodologies when considering the database and the authorized entity. It is a common understanding that current methodologies focus on the network architecture rather than the database, which is not an adequate solution when considering the insider threat. Recent…

  13. Dynamic immune intrusion detection system for IPv6

    NASA Astrophysics Data System (ADS)

    Yao, Li; Li, Zhi-tang; Hao, Tu

    2005-03-01

    We have set up a project aimed at developing a dynamical immune intrusion detection system for IPv6 and protecting the next generation Internet from intrusion. We focus on investigating immunelogical principles in designing a dynamic multi-agent system for intrusion detection in IPv6 environment, instead of attempting to describe all that is intrusion in the network try and describe what is normal use and define "non-self" as intrusion. The proposed intrusion detection system is designed as flexible, extendible, and adaptable in order to meet the needs and preferences of network administrators for IPv6 environment.

  14. Intrusion detection using rough set classification.

    PubMed

    Zhang, Lian-hua; Zhang, Guan-hua; Zhang, Jie; Bai, Ying-cai

    2004-09-01

    Recently machine learning-based intrusion detection approaches have been subjected to extensive researches because they can detect both misuse and anomaly. In this paper, rough set classification (RSC), a modern learning algorithm, is used to rank the features extracted for detecting intrusions and generate intrusion detection models. Feature ranking is a very critical step when building the model. RSC performs feature ranking before generating rules, and converts the feature ranking to minimal hitting set problem addressed by using genetic algorithm (GA). This is done in classical approaches using Support Vector Machine (SVM) by executing many iterations, each of which removes one useless feature. Compared with those methods, our method can avoid many iterations. In addition, a hybrid genetic algorithm is proposed to increase the convergence speed and decrease the training time of RSC. The models generated by RSC take the form of "IF-THEN" rules, which have the advantage of explication. Tests and comparison of RSC with SVM on DARPA benchmark data showed that for Probe and DoS attacks both RSC and SVM yielded highly accurate results (greater than 99% accuracy on testing set).

  15. A Survey on Intrusion Detection in MANETs.

    NASA Astrophysics Data System (ADS)

    BakeyaLakshmi, P.; Santhi, K.

    2012-10-01

    A mobile ad hoc network is an infrastructureless network that changes its links dynamically, which makes routing in MANET a difficult process. As Mobile Ad-Hoc Network (MANET) has become a very important technology, research concerning its security problem, especially, in intrusion detection has attracted many researchers. Feature selection methodology plays a vital role in the data analysis process. PCA is used to analyze the selected features. This is because, redundant and irrelevant features often reduce performance of the intrusion detection system. It performs better in increasing speed and predictive accuracy. This survey aims to select and analyze the network features using principal component analysis. While performing various experiments, normal and attack states are simulated and the results for the selected features are analyzed.

  16. In-situ trainable intrusion detection system

    DOEpatents

    Symons, Christopher T.; Beaver, Justin M.; Gillen, Rob; Potok, Thomas E.

    2016-11-15

    A computer implemented method detects intrusions using a computer by analyzing network traffic. The method includes a semi-supervised learning module connected to a network node. The learning module uses labeled and unlabeled data to train a semi-supervised machine learning sensor. The method records events that include a feature set made up of unauthorized intrusions and benign computer requests. The method identifies at least some of the benign computer requests that occur during the recording of the events while treating the remainder of the data as unlabeled. The method trains the semi-supervised learning module at the network node in-situ, such that the semi-supervised learning modules may identify malicious traffic without relying on specific rules, signatures, or anomaly detection.

  17. Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems

    NASA Astrophysics Data System (ADS)

    Shyu, Mei-Ling; Huang, Zifang; Luo, Hongli

    In recent years, pervasive computing infrastructures have greatly improved the interaction between human and system. As we put more reliance on these computing infrastructures, we also face threats of network intrusion and/or any new forms of undesirable IT-based activities. Hence, network security has become an extremely important issue, which is closely connected with homeland security, business transactions, and people's daily life. Accurate and efficient intrusion detection technologies are required to safeguard the network systems and the critical information transmitted in the network systems. In this chapter, a novel network intrusion detection framework for mining and detecting sequential intrusion patterns is proposed. The proposed framework consists of a Collateral Representative Subspace Projection Modeling (C-RSPM) component for supervised classification, and an inter-transactional association rule mining method based on Layer Divided Modeling (LDM) for temporal pattern analysis. Experiments on the KDD99 data set and the traffic data set generated by a private LAN testbed show promising results with high detection rates, low processing time, and low false alarm rates in mining and detecting sequential intrusion detections.

  18. Rapid detection of biothreat agents based on cellular machinery.

    SciTech Connect

    Lane, Todd W.; Gantt, Richard W.

    2004-12-01

    This research addresses rapid and sensitive identification of biological agents in a complex background. We attempted to devise a method by which the specificity of the cellular transcriptional machinery could be used to detect and identify bacterial bio-terror agents in a background of other organisms. Bacterial cells contain RNA polymerases and transcription factors that transcribe genes into mRNA for translation into proteins. RNA polymerases in conjunction with transcription factors recognize regulatory elements (promoters) upstream of the gene. These promoters are, in many cases, recognized by the polymerase and transcription factor combinations of one species only. We have engineered a plasmid, for Escherichia coli, containing the virA promoter from the target species Shigella flexneri. This promoter was fused to a reporter gene Green Fluorescent Protein (GFP). In theory the indicator strain (carrying the plasmid) is mixed with the target strain and the two are lysed. The cellular machinery from both cells mixes and the GFP is produced. This report details the results of testing this system.

  19. Detection of DoS attacks using intrusion detection sensors

    NASA Astrophysics Data System (ADS)

    Ramakrishna, Pathmenanthan; Maarof, Mohd A.

    2002-09-01

    Intrusion detection systems have usually been developed using large host-based components. These components impose an extra load on the system where they run (sometimes even requiring a dedicated system) and are subject to tampering or disabling by an intruder. Additionally, intrusion detection systems have usually obtained information about host behavior through indirect means, such as audit trails or network packet traces. This potentially allows intruders to modify the information before the intrusion detection system obtains it and slows down the detection and prevention of DoS attacks, making it possible for an intruder to hide his activities. In this paper we propose work that will attempt to show that it is possible to perform intrusion detection mechanism of DoS attacks using small sensors embedded in a computer system. These sensors will look for signs of specific intrusions. They will perform target monitoring by observing the behavior of the through an audit trail or other indirect means in real time while the Snort IDS running. Furthermore, by being built into the computer system it could provide a flexible alert sensor which may not impose a considerable extra load on the host they monitor.

  20. The architecture of a network level intrusion detection system

    SciTech Connect

    Heady, R.; Luger, G.; Maccabe, A.; Servilla, M.

    1990-08-15

    This paper presents the preliminary architecture of a network level intrusion detection system. The proposed system will monitor base level information in network packets (source, destination, packet size, and time), learning the normal patterns and announcing anomalies as they occur. The goal of this research is to determine the applicability of current intrusion detection technology to the detection of network level intrusions. In particular, the authors are investigating the possibility of using this technology to detect and react to worm programs.

  1. From Intrusion Detection to Self Protection

    SciTech Connect

    Frincke, Deb; Wespi, Andreas; Zamboni, Diego

    2007-04-11

    Modern computer systems have become so complex and interdependent that the traditional model of system defense, utilizing layers and including an intrusion detection system that provides alerts to a human who responds to them, is becoming unfeasible. Effective human-guided real-time responses are no longer a reasonable expectation for large scale systems--this is particularly troublesome because a failure to respond correctly and rapidly can have disastrous consequences. In an ideal world, our systems would automatically detect and respond to threats of all kinds, including but not limited to automated attacks, human-guided attacks, and the constant onslaught of unsolicited email (spam). Traditionally, these threats have been dealt with by separate communities--the anti-virus community, the intrusion-detection/firewall community, and the anti-spam community. Today however, we see an increasing need for integrating different technologies toward achieving a common goal. In this special issue, we surveyed the research community with the intent of identifying novel, multidisciplinary and integrated approaches to system defense that contribute towards development of true self-protecting and self-healing systems. The result is reflected in the articles we selected.

  2. Characterizing and Improving Distributed Intrusion Detection Systems.

    SciTech Connect

    Hurd, Steven A; Proebstel, Elliot P.

    2007-11-01

    Due to ever-increasing quantities of information traversing networks, network administrators are developing greater reliance upon statistically sampled packet information as the source for their intrusion detection systems (IDS). Our research is aimed at understanding IDS performance when statistical packet sampling is used. Using the Snort IDS and a variety of data sets, we compared IDS results when an entire data set is used to the results when a statistically sampled subset of the data set is used. Generally speaking, IDS performance with statistically sampled information was shown to drop considerably even under fairly high sampling rates (such as 1:5). Characterizing and Improving Distributed Intrusion Detection Systems4AcknowledgementsThe authors wish to extend our gratitude to Matt Bishop and Chen-Nee Chuah of UC Davis for their guidance and support on this work. Our thanks are also extended to Jianning Mai of UC Davis and Tao Ye of Sprint Advanced Technology Labs for their generous assistance.We would also like to acknowledge our dataset sources, CRAWDAD and CAIDA, without which this work would not have been possible. Support for OC48 data collection is provided by DARPA, NSF, DHS, Cisco and CAIDA members.

  3. Intrusion Detection With Quantum Mechanics: A Photonic Quantum Fence

    DTIC Science & Technology

    2008-12-01

    computing and quantum key distribution (QKD). Some of the most remarkable examples include quantum teleportation for the non-local transfer of...1 INTRUSION DETECTION WITH QUANTUM MECHANICS: A PHOTONIC QUANTUM FENCE T. S. Humble*, R. S. Bennink, and W. P. Grice Oak Ridge National...use of quantum -mechanically entangled photons for sensing intrusions across a physical perimeter. Our approach to intrusion detection uses the no

  4. APHID: Anomaly Processor in Hardware for Intrusion Detection

    DTIC Science & Technology

    2007-03-01

    APHID : Anomaly Processor in Hardware for Intrusion Detection THESIS Samuel Hart, Captain, USAF AFIT/GCE/ENG/07-04 DEPARTMENT OF THE AIR FORCE AIR...the United States Government. AFIT/GCE/ENG/07-04 APHID : Anomaly Processor in Hardware for Intrusion Detection THESIS Presented to the Faculty...Captain, USAF March 2007 APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. AFIT/GCE/ENG/07-04 APHID : Anomaly Processor in Hardware for Intrusion

  5. An improved unsupervised clustering-based intrusion detection method

    NASA Astrophysics Data System (ADS)

    Hai, Yong J.; Wu, Yu; Wang, Guo Y.

    2005-03-01

    Practical Intrusion Detection Systems (IDSs) based on data mining are facing two key problems, discovering intrusion knowledge from real-time network data, and automatically updating them when new intrusions appear. Most data mining algorithms work on labeled data. In order to set up basic data set for mining, huge volumes of network data need to be collected and labeled manually. In fact, it is rather difficult and impractical to label intrusions, which has been a big restrict for current IDSs and has led to limited ability of identifying all kinds of intrusion types. An improved unsupervised clustering-based intrusion model working on unlabeled training data is introduced. In this model, center of a cluster is defined and used as substitution of this cluster. Then all cluster centers are adopted to detect intrusions. Testing on data sets of KDDCUP"99, experimental results demonstrate that our method has good performance in detection rate. Furthermore, the incremental-learning method is adopted to detect those unknown-type intrusions and it decreases false positive rate.

  6. Intrusion Detection in Control Systems using Sequence Characteristics

    NASA Astrophysics Data System (ADS)

    Kiuchi, Mai; Onoda, Takashi

    Intrusion detection is considered effective in control systems. Sequences of the control application behavior observed in the communication, such as the order of the control device to be controlled, are important in control systems. However, most intrusion detection systems do not effectively reflect sequences in the application layer into the detection rules. In our previous work, we considered utilizing sequences for intrusion detection in control systems, and demonstrated the usefulness of sequences for intrusion detection. However, manually writing the detection rules for a large system can be difficult, so using machine learning methods becomes feasible. Also, in the case of control systems, there have been very few observed cyber attacks, so we have very little knowledge of the attack data that should be used to train the intrusion detection system. In this paper, we use an approach that combines CRF (Conditional Random Field) considering the sequence of the system, thus able to reflect the characteristics of control system sequences into the intrusion detection system, and also does not need the knowledge of attack data to construct the detection rules.

  7. An expert system application for network intrusion detection

    SciTech Connect

    Jackson, K.A.; Dubois, D.H.; Stallings, C.A.

    1991-01-01

    The paper describes the design of a prototype intrusion detection system for the Los Alamos National Laboratory's Integrated Computing Network (ICN). The Network Anomaly Detection and Intrusion Reporter (NADIR) differs in one respect from most intrusion detection systems. It tries to address the intrusion detection problem on a network, as opposed to a single operating system. NADIR design intent was to copy and improve the audit record review activities normally done by security auditors. We wished to replace the manual review of audit logs with a near realtime expert system. NADIR compares network activity, as summarized in user profiles, against expert rules that define network security policy, improper or suspicious network activities, and normal network and user activity. When it detects deviant (anomalous) behavior, NADIR alerts operators in near realtime, and provides tools to aid in the investigation of the anomalous event. 15 refs., 2 figs.

  8. Fusion of Heterogeneous Intrusion Detection Systems for Network Attack Detection

    PubMed Central

    Kaliappan, Jayakumar; Thiagarajan, Revathi; Sundararajan, Karpagam

    2015-01-01

    An intrusion detection system (IDS) helps to identify different types of attacks in general, and the detection rate will be higher for some specific category of attacks. This paper is designed on the idea that each IDS is efficient in detecting a specific type of attack. In proposed Multiple IDS Unit (MIU), there are five IDS units, and each IDS follows a unique algorithm to detect attacks. The feature selection is done with the help of genetic algorithm. The selected features of the input traffic are passed on to the MIU for processing. The decision from each IDS is termed as local decision. The fusion unit inside the MIU processes all the local decisions with the help of majority voting rule and makes the final decision. The proposed system shows a very good improvement in detection rate and reduces the false alarm rate. PMID:26295058

  9. Realistic computer network simulation for network intrusion detection dataset generation

    NASA Astrophysics Data System (ADS)

    Payer, Garrett

    2015-05-01

    The KDD-99 Cup dataset is dead. While it can continue to be used as a toy example, the age of this dataset makes it all but useless for intrusion detection research and data mining. Many of the attacks used within the dataset are obsolete and do not reflect the features important for intrusion detection in today's networks. Creating a new dataset encompassing a large cross section of the attacks found on the Internet today could be useful, but would eventually fall to the same problem as the KDD-99 Cup; its usefulness would diminish after a period of time. To continue research into intrusion detection, the generation of new datasets needs to be as dynamic and as quick as the attacker. Simply examining existing network traffic and using domain experts such as intrusion analysts to label traffic is inefficient, expensive, and not scalable. The only viable methodology is simulation using technologies including virtualization, attack-toolsets such as Metasploit and Armitage, and sophisticated emulation of threat and user behavior. Simulating actual user behavior and network intrusion events dynamically not only allows researchers to vary scenarios quickly, but enables online testing of intrusion detection mechanisms by interacting with data as it is generated. As new threat behaviors are identified, they can be added to the simulation to make quicker determinations as to the effectiveness of existing and ongoing network intrusion technology, methodology and models.

  10. Organizational coevolutionary classifiers with fuzzy logic used in intrusion detection

    NASA Astrophysics Data System (ADS)

    Chen, Zhenguo

    2009-07-01

    Intrusion detection is an important technique in the defense-in-depth network security framework and a hot topic in computer security in recent years. To solve the intrusion detection question, we introduce the fuzzy logic into Organization CoEvolutionary algorithm [1] and present the algorithm of Organization CoEvolutionary Classification with Fuzzy Logic. In this paper, we give an intrusion detection models based on Organization CoEvolutionary Classification with Fuzzy Logic. After illustrating our model with a representative dataset and applying it to the real-world network datasets KDD Cup 1999. The experimental result shown that the intrusion detection based on Organizational Coevolutionary Classifiers with Fuzzy Logic can give higher recognition accuracy than the general method.

  11. Configurable Middleware-Level Intrusion Detection for Embedded Systems

    SciTech Connect

    Naess, Eivind; Frincke, Deborah A.; McKinnon, A. D.; Bakken, David E.

    2005-06-20

    Embedded systems have become integral parts of a diverse range of systems from automobiles to critical infrastructure applications such as gas and electric power distribution. Unfortunately, research on computer security in general and intrusion detection in particular, has not kept pace. Furthermore, embedded systems, by their very nature, are application specific and therefore frameworks for developing application-specific intrusion detection systems for distributed embedded systems must be researched, designed, and implemented. In this paper, we present a configurable middleware-based intrusion detection framework. In particular, this paper presents a system model and a concrete implementation of a highly configurable intrusion detection framework that is integrated into MicroQoSCORBA, a highly configurable middleware framework developed for embedded systems. By exploiting the application-specific logic available to a middleware framework (e.g., object interfaces and method signatures), our integrated framework is able to autogenerate application-specific intrusion detection systems. Next, a set of configurable intrusion detection mechanisms suitable for embedded systems is presented. A performance evaluation of these mechanisms, run on two hardware platforms, is presented at the end of the paper.

  12. Developing a Cooperative Intrusion Detection System for Wireless Sensor Networks

    DTIC Science & Technology

    2010-11-01

    security measures out. AWISSENET (Ad-hoc personal area network & WIreless Sensor SEcure NETwork) is a project funded by the European Union...Information and Communication Technologies Program that is focused on security and resilience across ad-hoc personal area networks and wireless sensor networks...and provides a security toolbox for trusted route selection, secure service discovery and intrusion detection. This paper deals with intrusion

  13. Design of an Evolutionary Approach for Intrusion Detection

    PubMed Central

    2013-01-01

    A novel evolutionary approach is proposed for effective intrusion detection based on benchmark datasets. The proposed approach can generate a pool of noninferior individual solutions and ensemble solutions thereof. The generated ensembles can be used to detect the intrusions accurately. For intrusion detection problem, the proposed approach could consider conflicting objectives simultaneously like detection rate of each attack class, error rate, accuracy, diversity, and so forth. The proposed approach can generate a pool of noninferior solutions and ensembles thereof having optimized trade-offs values of multiple conflicting objectives. In this paper, a three-phase, approach is proposed to generate solutions to a simple chromosome design in the first phase. In the first phase, a Pareto front of noninferior individual solutions is approximated. In the second phase of the proposed approach, the entire solution set is further refined to determine effective ensemble solutions considering solution interaction. In this phase, another improved Pareto front of ensemble solutions over that of individual solutions is approximated. The ensemble solutions in improved Pareto front reported improved detection results based on benchmark datasets for intrusion detection. In the third phase, a combination method like majority voting method is used to fuse the predictions of individual solutions for determining prediction of ensemble solution. Benchmark datasets, namely, KDD cup 1999 and ISCX 2012 dataset, are used to demonstrate and validate the performance of the proposed approach for intrusion detection. The proposed approach can discover individual solutions and ensemble solutions thereof with a good support and a detection rate from benchmark datasets (in comparison with well-known ensemble methods like bagging and boosting). In addition, the proposed approach is a generalized classification approach that is applicable to the problem of any field having multiple conflicting

  14. Anomaly detection enhanced classification in computer intrusion detection

    SciTech Connect

    Fugate, M. L.; Gattiker, J. R.

    2002-01-01

    This report describes work with the goal of enhancing capabilities in computer intrusion detection. The work builds upon a study of classification performance, that compared various methods of classifying information derived from computer network packets into attack versus normal categories, based on a labeled training dataset. This previous work validates our classification methods, and clears the ground for studying whether and how anomaly detection can be used to enhance this performance, The DARPA project that initiated the dataset used here concluded that anomaly detection should be examined to boost the performance of machine learning in the computer intrusion detection task. This report investigates the data set for aspects that will be valuable for anomaly detection application, and supports these results with models constructed from the data. In this report, the term anomaly detection means learning a model from unlabeled data, and using this to make some inference about future data. Our data is a feature vector derived from network packets: an 'example' or 'sample'. On the other hand, classification means building a model from labeled data, and using that model to classify unlabeled (future) examples. There is some precedent in the literature for combining these methods. One approach is to stage the two techniques, using anomaly detection to segment data into two sets for classification. An interpretation of this is a method to combat nonstationarity in the data. In our previous work, we demonstrated that the data has substantial temporal nonstationarity. With classification methods that can be thought of as learning a decision surface between two statistical distributions, performance is expected to degrade significantly when classifying examples that are from regions not well represented in the training set. Anomaly detection can be seen as a problem of learning the density (landscape) or the support (boundary) of a statistical distribution so that

  15. Implementing a Patternless Intrusion Detection System; A Methodology for Zippo

    DTIC Science & Technology

    2005-09-01

    A methodology for the implementation of Zippo, a patternless intrusion detection system is presented in this thesis. This methodology approaches the...... based on those of Therminator and understanding the ideas of buckets and balls, thermal canyons and towers, decision trees, slidelength and windowlength

  16. Anomaly-based intrusion detection for SCADA systems

    SciTech Connect

    Yang, D.; Usynin, A.; Hines, J. W.

    2006-07-01

    Most critical infrastructure such as chemical processing plants, electrical generation and distribution networks, and gas distribution is monitored and controlled by Supervisory Control and Data Acquisition Systems (SCADA. These systems have been the focus of increased security and there are concerns that they could be the target of international terrorists. With the constantly growing number of internet related computer attacks, there is evidence that our critical infrastructure may also be vulnerable. Researchers estimate that malicious online actions may cause $75 billion at 2007. One of the interesting countermeasures for enhancing information system security is called intrusion detection. This paper will briefly discuss the history of research in intrusion detection techniques and introduce the two basic detection approaches: signature detection and anomaly detection. Finally, it presents the application of techniques developed for monitoring critical process systems, such as nuclear power plants, to anomaly intrusion detection. The method uses an auto-associative kernel regression (AAKR) model coupled with the statistical probability ratio test (SPRT) and applied to a simulated SCADA system. The results show that these methods can be generally used to detect a variety of common attacks. (authors)

  17. Data mining approach to web application intrusions detection

    NASA Astrophysics Data System (ADS)

    Kalicki, Arkadiusz

    2011-10-01

    Web applications became most popular medium in the Internet. Popularity, easiness of web application script languages and frameworks together with careless development results in high number of web application vulnerabilities and high number of attacks performed. There are several types of attacks possible because of improper input validation: SQL injection Cross-site scripting, Cross-Site Request Forgery (CSRF), web spam in blogs and others. In order to secure web applications intrusion detection (IDS) and intrusion prevention systems (IPS) are being used. Intrusion detection systems are divided in two groups: misuse detection (traditional IDS) and anomaly detection. This paper presents data mining based algorithm for anomaly detection. The principle of this method is the comparison of the incoming HTTP traffic with a previously built profile that contains a representation of the "normal" or expected web application usage sequence patterns. The frequent sequence patterns are found with GSP algorithm. Previously presented detection method was rewritten and improved. Some tests show that the software catches malicious requests, especially long attack sequences, results quite good with medium length sequences, for short length sequences must be complemented with other methods.

  18. Neural Network Based Intrusion Detection System for Critical Infrastructures

    SciTech Connect

    Todd Vollmer; Ondrej Linda; Milos Manic

    2009-07-01

    Resiliency and security in control systems such as SCADA and Nuclear plant’s in today’s world of hackers and malware are a relevant concern. Computer systems used within critical infrastructures to control physical functions are not immune to the threat of cyber attacks and may be potentially vulnerable. Tailoring an intrusion detection system to the specifics of critical infrastructures can significantly improve the security of such systems. The IDS-NNM – Intrusion Detection System using Neural Network based Modeling, is presented in this paper. The main contributions of this work are: 1) the use and analyses of real network data (data recorded from an existing critical infrastructure); 2) the development of a specific window based feature extraction technique; 3) the construction of training dataset using randomly generated intrusion vectors; 4) the use of a combination of two neural network learning algorithms – the Error-Back Propagation and Levenberg-Marquardt, for normal behavior modeling. The presented algorithm was evaluated on previously unseen network data. The IDS-NNM algorithm proved to be capable of capturing all intrusion attempts presented in the network communication while not generating any false alerts.

  19. Enterprise network intrusion detection and prevention system (ENIDPS)

    NASA Astrophysics Data System (ADS)

    Akujuobi, C. M.; Ampah, N. K.

    2007-04-01

    Securing enterprise networks comes under two broad topics: Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS). The right combination of selected algorithms/techniques under both topics produces better security for a given network. This approach leads to using layers of physical, administrative, electronic, and encrypted systems to protect valuable resources. So far, there is no algorithm, which guarantees absolute protection for a given network from intruders. Intrusion Prevention Systems like IPSec, Firewall, Sender ID, Domain Keys Identified Mail (DKIM) etc. do not guarantee absolute security just like existing Intrusion Detection Systems. Our approach focuses on developing an IDS, which will detect all intruders that bypass the IPS and at the same time will be used in updating the IPS, since the IPS fail to prevent some intruders from entering a given network. The new IDS will employ both signature-based detection and anomaly detection as its analysis strategy. It should therefore be able to detect known and unknown intruders or attacks and further isolate those sources of attack within the network. Both real-time and off-line IDS predictions will be applied under the analysis and response stages. The basic IDS architecture will involve both centralized and distributed/heterogeneous architecture to ensure effective detection. Pro-active responses and corrective responses will be employed. The new security system, which will be made up of both IDS and IPS, should be less expensive to implement compared to existing ones. Finally, limitations of existing security systems have to be eliminated with the introduction of the new security system.

  20. A Partially Distributed Intrusion Detection System for Wireless Sensor Networks

    PubMed Central

    Cho, Eung Jun; Hong, Choong Seon; Lee, Sungwon; Jeon, Seokhee

    2013-01-01

    The increasing use of wireless sensor networks, which normally comprise several very small sensor nodes, makes their security an increasingly important issue. They can be practically and efficiently secured using intrusion detection systems. Conventional security mechanisms are not usually applicable due to the sensor nodes having limitations of computational power, memory capacity, and battery power. Therefore, specific security systems should be designed to function under constraints of energy or memory. A partially distributed intrusion detection system with low memory and power demands is proposed here. It employs a Bloom filter, which allows reduced signature code size. Multiple Bloom filters can be combined to reduce the signature code for each Bloom filter array. The mechanism could then cope with potential denial of service attacks, unlike many previous detection systems with Bloom filters. The mechanism was evaluated and validated through analysis and simulation.

  1. AdaBoost-based algorithm for network intrusion detection.

    PubMed

    Hu, Weiming; Hu, Wei; Maybank, Steve

    2008-04-01

    Network intrusion detection aims at distinguishing the attacks on the Internet from normal use of the Internet. It is an indispensable part of the information security system. Due to the variety of network behaviors and the rapid development of attack fashions, it is necessary to develop fast machine-learning-based intrusion detection algorithms with high detection rates and low false-alarm rates. In this correspondence, we propose an intrusion detection algorithm based on the AdaBoost algorithm. In the algorithm, decision stumps are used as weak classifiers. The decision rules are provided for both categorical and continuous features. By combining the weak classifiers for continuous features and the weak classifiers for categorical features into a strong classifier, the relations between these two different types of features are handled naturally, without any forced conversions between continuous and categorical features. Adaptable initial weights and a simple strategy for avoiding overfitting are adopted to improve the performance of the algorithm. Experimental results show that our algorithm has low computational complexity and error rates, as compared with algorithms of higher computational complexity, as tested on the benchmark sample data.

  2. Dynamic Probing for Intrusion Detection under Resource Constraints

    DTIC Science & Technology

    2013-06-01

    performance measure of regret, defined as the performance loss compared to that of a genie who knows the entire attack processes a priori and probes...performance as that of the omniscient genie . Index Terms—Intrusion detection, dynamic probing, non- stochastic multi-armed bandit, regret. I...dynamic probing strategy under the performance measure of regret, de ned as the performance loss compared to that of a genie who knows the entire attack

  3. Thutmose - Investigation of Machine Learning-Based Intrusion Detection Systems

    DTIC Science & Technology

    2016-06-01

    goal of the experiment was to learn how susceptible an HMM is to a targeted causative integrity attack. In the first set of trials, the adversary...to a Targeted Causative attack against the Integrity of the learning system. In such an attack, an adversary chooses a specific anomalous point and...THUTMOSE – INVESTIGATION OF MACHINE LEARNING -BASED INTRUSION DETECTION SYSTEMS BAE SYSTEMS INFORMATION AND SECURITY JUNE 2016

  4. Application of a Hidden Bayes Naive Multiclass Classifier in Network Intrusion Detection

    ERIC Educational Resources Information Center

    Koc, Levent

    2013-01-01

    With increasing Internet connectivity and traffic volume, recent intrusion incidents have reemphasized the importance of network intrusion detection systems for combating increasingly sophisticated network attacks. Techniques such as pattern recognition and the data mining of network events are often used by intrusion detection systems to classify…

  5. Usefulness of DARPA dataset for intrusion detection system evaluation

    NASA Astrophysics Data System (ADS)

    Thomas, Ciza; Sharma, Vishwas; Balakrishnan, N.

    2008-03-01

    The MIT Lincoln Laboratory IDS evaluation methodology is a practical solution in terms of evaluating the performance of Intrusion Detection Systems, which has contributed tremendously to the research progress in that field. The DARPA IDS evaluation dataset has been criticized and considered by many as a very outdated dataset, unable to accommodate the latest trend in attacks. Then naturally the question arises as to whether the detection systems have improved beyond detecting these old level of attacks. If not, is it worth thinking of this dataset as obsolete? The paper presented here tries to provide supporting facts for the use of the DARPA IDS evaluation dataset. The two commonly used signature-based IDSs, Snort and Cisco IDS, and two anomaly detectors, the PHAD and the ALAD, are made use of for this evaluation purpose and the results support the usefulness of DARPA dataset for IDS evaluation.

  6. Detection of deep stratospheric intrusions by cosmogenic 35S

    PubMed Central

    Su, Lin; Shaheen, Robina; Fung, Jimmy C. H.; Thiemens, Mark H.

    2016-01-01

    The extent to which stratospheric intrusions on synoptic scales influence the tropospheric ozone (O3) levels remains poorly understood, because quantitative detection of stratospheric air has been challenging. Cosmogenic 35S mainly produced in the stratosphere has the potential to identify stratospheric air masses at ground level, but this approach has not yet been unambiguously shown. Here, we report unusually high 35S concentrations (7,390 atoms m−3; ∼16 times greater than annual average) in fine sulfate aerosols (aerodynamic diameter less than 0.95 µm) collected at a coastal site in southern California on May 3, 2014, when ground-level O3 mixing ratios at air quality monitoring stations across southern California (43 of 85) exceeded the recently revised US National Ambient Air Quality Standard (daily maximum 8-h average: 70 parts per billion by volume). The stratospheric origin of the significantly enhanced 35S level is supported by in situ measurements of air pollutants and meteorological variables, satellite observations, meteorological analysis, and box model calculations. The deep stratospheric intrusion event was driven by the coupling between midlatitude cyclones and Santa Ana winds, and it was responsible for the regional O3 pollution episode. These results provide direct field-based evidence that 35S is an additional sensitive and unambiguous tracer in detecting stratospheric air in the boundary layer and offer the potential for resolving the stratospheric influences on the tropospheric O3 level. PMID:27655890

  7. Visual behavior characterization for intrusion and misuse detection

    NASA Astrophysics Data System (ADS)

    Erbacher, Robert F.; Frincke, Deborah

    2001-05-01

    As computer and network intrusions become more and more of a concern, the need for better capabilities, to assist in the detection and analysis of intrusions also increase. System administrators typically rely on log files to analyze usage and detect misuse. However, as a consequence of the amount of data collected by each machine, multiplied by the tens or hundreds of machines under the system administrator's auspices, the entirety of the data available is neither collected nor analyzed. This is compounded by the need to analyze network traffic data as well. We propose a methodology for analyzing network and computer log information visually based on the analysis of the behavior of the users. Each user's behavior is the key to determining their intent and overriding activity, whether they attempt to hide their actions or not. Proficient hackers will attempt to hide their ultimate activities, which hinders the reliability of log file analysis. Visually analyzing the users''s behavior however, is much more adaptable and difficult to counteract.

  8. Detection of deep stratospheric intrusions by cosmogenic 35S.

    PubMed

    Lin, Mang; Su, Lin; Shaheen, Robina; Fung, Jimmy C H; Thiemens, Mark H

    2016-10-04

    The extent to which stratospheric intrusions on synoptic scales influence the tropospheric ozone (O3) levels remains poorly understood, because quantitative detection of stratospheric air has been challenging. Cosmogenic (35)S mainly produced in the stratosphere has the potential to identify stratospheric air masses at ground level, but this approach has not yet been unambiguously shown. Here, we report unusually high (35)S concentrations (7,390 atoms m(-3); ∼16 times greater than annual average) in fine sulfate aerosols (aerodynamic diameter less than 0.95 µm) collected at a coastal site in southern California on May 3, 2014, when ground-level O3 mixing ratios at air quality monitoring stations across southern California (43 of 85) exceeded the recently revised US National Ambient Air Quality Standard (daily maximum 8-h average: 70 parts per billion by volume). The stratospheric origin of the significantly enhanced (35)S level is supported by in situ measurements of air pollutants and meteorological variables, satellite observations, meteorological analysis, and box model calculations. The deep stratospheric intrusion event was driven by the coupling between midlatitude cyclones and Santa Ana winds, and it was responsible for the regional O3 pollution episode. These results provide direct field-based evidence that (35)S is an additional sensitive and unambiguous tracer in detecting stratospheric air in the boundary layer and offer the potential for resolving the stratospheric influences on the tropospheric O3 level.

  9. Detection of deep stratospheric intrusions by cosmogenic 35S

    NASA Astrophysics Data System (ADS)

    Lin, Mang; Su, Lin; Shaheen, Robina; Fung, Jimmy C. H.; Thiemens, Mark H.

    2016-10-01

    The extent to which stratospheric intrusions on synoptic scales influence the tropospheric ozone (O3) levels remains poorly understood, because quantitative detection of stratospheric air has been challenging. Cosmogenic 35S mainly produced in the stratosphere has the potential to identify stratospheric air masses at ground level, but this approach has not yet been unambiguously shown. Here, we report unusually high 35S concentrations (7,390 atoms m-3; ˜16 times greater than annual average) in fine sulfate aerosols (aerodynamic diameter less than 0.95 µm) collected at a coastal site in southern California on May 3, 2014, when ground-level O3 mixing ratios at air quality monitoring stations across southern California (43 of 85) exceeded the recently revised US National Ambient Air Quality Standard (daily maximum 8-h average: 70 parts per billion by volume). The stratospheric origin of the significantly enhanced 35S level is supported by in situ measurements of air pollutants and meteorological variables, satellite observations, meteorological analysis, and box model calculations. The deep stratospheric intrusion event was driven by the coupling between midlatitude cyclones and Santa Ana winds, and it was responsible for the regional O3 pollution episode. These results provide direct field-based evidence that 35S is an additional sensitive and unambiguous tracer in detecting stratospheric air in the boundary layer and offer the potential for resolving the stratospheric influences on the tropospheric O3 level.

  10. A Survey of Artificial Immune System Based Intrusion Detection

    PubMed Central

    Li, Tao; Hu, Xinlei; Wang, Feng; Zou, Yang

    2014-01-01

    In the area of computer security, Intrusion Detection (ID) is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS). The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs). This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted. PMID:24790549

  11. Optimization of detection sensitivity for a Fiber Optic Intrusion Detection System (FOIDS) using design of experiments.

    SciTech Connect

    Miller, Larry D.; Mack, Thomas Kimball; Mitchiner, Kim W.; Varoz, Carmella A.

    2010-06-01

    The Fiber Optic Intrusion Detection System (FOIDS)1 is a physical security sensor deployed on fence lines to detect climb or cut intrusions by adversaries. Calibration of detection sensitivity can be time consuming because, for example, the FiberSenSys FD-332 has 32 settings that can be adjusted independently to provide a balance between a high probability of detection and a low nuisance alarm rate. Therefore, an efficient method of calibrating the FOIDS in the field, other than by trial and error, was needed. This study was conducted to: x Identify the most significant settings for controlling detection x Develop a way of predicting detection sensitivity for given settings x Develop a set of optimal settings for validation The Design of Experiments (DoE) 2-4 methodology was used to generate small, planned test matrixes, which could be statistically analyzed to yield more information from the test data. Design of Experiments is a statistical methodology for quickly optimizing performance of systems with measurable input and output variables. DoE was used to design custom screening experiments based on 11 FOIDS settings believed to have the most affect on WKH types of fence perimeter intrusions were evaluated: simulated cut intrusions and actual climb intrusions. Two slightly different two-level randomized fractional factorial designed experiment matrixes consisting of 16 unique experiments were performed in the field for each type of intrusion. Three repetitions were conducted for every cut test; two repetitions were conducted for every climb test. Total number of cut tests analyzed was 51; the total number of climb tests was 38. This paper discusses the results and benefits of using Design of Experiments (DoE) to calibrate and optimize the settings for a FOIDS sensor

  12. Non-intrusive practitioner pupil detection for unmodified microscope oculars.

    PubMed

    Fuhl, Wolfgang; Santini, Thiago; Reichert, Carsten; Claus, Daniel; Herkommer, Alois; Bahmani, Hamed; Rifai, Katharina; Wahl, Siegfried; Kasneci, Enkelejda

    2016-12-01

    Modern microsurgery is a long and complex task requiring the surgeon to handle multiple microscope controls while performing the surgery. Eye tracking provides an additional means of interaction for the surgeon that could be used to alleviate this situation, diminishing surgeon fatigue and surgery time, thus decreasing risks of infection and human error. In this paper, we introduce a novel algorithm for pupil detection tailored for eye images acquired through an unmodified microscope ocular. The proposed approach, the Hough transform, and six state-of-the-art pupil detection algorithms were evaluated on over 4000 hand-labeled images acquired from a digital operating microscope with a non-intrusive monitoring system for the surgeon eyes integrated. Our results show that the proposed method reaches detection rates up to 71% for an error of ≈3% w.r.t the input image diagonal; none of the state-of-the-art pupil detection algorithms performed satisfactorily. The algorithm and hand-labeled data set can be downloaded at:: www.ti.uni-tuebingen.de/perception.

  13. An evaluation of fiber optic intrusion detection systems in interior applications

    SciTech Connect

    Vigil, J.T.

    1994-03-01

    This report discusses the testing and evaluation of four commercially available fiber optic intrusion detection systems. The systems were tested under carpet-type matting and in a vaulted ceiling application. This report will focus on nuisance alarm data and intrusion detection results. Tests were conducted in a mobile office building and in a bunker.

  14. Characterizing and Managing Intrusion Detection System (IDS) Alerts with Multi-Server/Multi-Priority Queuing Theory

    DTIC Science & Technology

    2014-12-26

    CHARACTERIZING AND MANAGING INTRUSION DETECTION SYSTEM (IDS) ALERTS WITH MULTI-SERVER/MULTI-PRIORITY...subject to copyright protection in the United States. AFIT-ENV-MS-14-D-24 CHARACTERIZING AND MANAGING INTRUSION DETECTION SYSTEM (IDS) ALERTS WITH...IDS) ALERTS WITH MULTI-SERVER/MULTI-PRIORITY QUEUING THEORY Christopher C. Olsen, BS Captain, USAF Approved

  15. Towards Reliable Evaluation of Anomaly-Based Intrusion Detection Performance

    NASA Technical Reports Server (NTRS)

    Viswanathan, Arun

    2012-01-01

    This report describes the results of research into the effects of environment-induced noise on the evaluation process for anomaly detectors in the cyber security domain. This research was conducted during a 10-week summer internship program from the 19th of August, 2012 to the 23rd of August, 2012 at the Jet Propulsion Laboratory in Pasadena, California. The research performed lies within the larger context of the Los Angeles Department of Water and Power (LADWP) Smart Grid cyber security project, a Department of Energy (DoE) funded effort involving the Jet Propulsion Laboratory, California Institute of Technology and the University of Southern California/ Information Sciences Institute. The results of the present effort constitute an important contribution towards building more rigorous evaluation paradigms for anomaly-based intrusion detectors in complex cyber physical systems such as the Smart Grid. Anomaly detection is a key strategy for cyber intrusion detection and operates by identifying deviations from profiles of nominal behavior and are thus conceptually appealing for detecting "novel" attacks. Evaluating the performance of such a detector requires assessing: (a) how well it captures the model of nominal behavior, and (b) how well it detects attacks (deviations from normality). Current evaluation methods produce results that give insufficient insight into the operation of a detector, inevitably resulting in a significantly poor characterization of a detectors performance. In this work, we first describe a preliminary taxonomy of key evaluation constructs that are necessary for establishing rigor in the evaluation regime of an anomaly detector. We then focus on clarifying the impact of the operational environment on the manifestation of attacks in monitored data. We show how dynamic and evolving environments can introduce high variability into the data stream perturbing detector performance. Prior research has focused on understanding the impact of this

  16. Detecting Aseismic Fault Slip and Magmatic Intrusion From Seismicity Data

    NASA Astrophysics Data System (ADS)

    Llenos, A. L.; McGuire, J. J.

    2007-12-01

    Seismicity triggered by aseismic deformation, such as magmatic intrusions or afterslip, can be used to detect the occurrence of these otherwise difficult to observe processes. Recent studies suggest that aseismic deformation can trigger large amounts of seismicity in a variety of plate tectonic settings. We have developed a new technique that takes advantage of this triggered seismicity to estimate the time-history of aseismic stressing rate on a fault- zone by combining the rate and state dependent friction and the Epidemic Type Aftershock Sequence (ETAS) models of seismicity-rate [ Dieterich, 1994; Ogata, 1988]. In the rate-state model, the integration of an observed seismicity rate results in an estimate of the stress rate acting in a given space-time window. However, the seismicity rate observed in any catalog comes from 3 primary sources: coseismically-triggered seismicity (aftershocks), tectonically-triggered seismicity (i.e., from long-term tectonic loading), and aseismically-triggered seismicity (e.g., from dike intrusion, aseismic slip transients, or fluid migration). In catalogs dominated by directly triggered aftershocks (i.e., ETAS branching ratios >~0.7), the coseismically-triggered seismicity rate will be much larger than the aseismically-triggered rate and will dominate the estimate of stressing-rate, obscuring the aseismic transient of interest if the rate-state method is applied directly. The challenge therefore lies in isolating the aseismically-triggered seismicity rate from the coseismically-triggered seismicity rate. The ETAS model [ Ogata, 1988] provides a natural way to separate the aseismic and coseismic seismicity rates, as the ETAS parameter μ essentially reflects the aseismically-triggered rate (as well as the background tectonically-triggered rate). To develop a method that can resolve the magnitude and time history of aseismic stress transients even in high branching ratio regions, we combine the rate-state and ETAS models into a

  17. An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks

    PubMed Central

    Butun, Ismail; Ra, In-Ho; Sankar, Ravi

    2015-01-01

    In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) “upward-IDS (U-IDS)” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. PMID:26593915

  18. Efficient pattern matching on GPUs for intrusion detection systems

    SciTech Connect

    Villa, Oreste; Tumeo, Antonino; Sciuto, Donatella

    2010-05-17

    Pattern matching is at the core of many security applications, like Network Intrusion Detection Systems (NIDS), spam filters and virus scanner. The always growing traffic on networks requires the ability to recognize potentially malicious signatures effectively, fastly and possibly in real time, without afftecting the performance and the latencies of the connections. Unfortunately, pattern matching is a computationally intensive procedure which poses significant challenges on current software and hardware implementations. Graphic Processing Units (GPU) have become an interesting target for such high-througput applications, but the algorithms and the data structures need to be redesigned to be parallelized and adapted to the underlining hardware, coping with the limitations imposed by these architectures. In this paper we present an efficient implementation of the Aho-Corasick pattern matching algorithm on GPU, showing how we progressively redesigned the algorithm and the data structures to fit on the architecture and comparing it with equivalent implementations on the CPU and with previous work. We show that with realistic TCP-IP workloads and signatures, our implementation obtains a speedup of 6.5 with respect to CPU implementations and of two times when compared to previous GPU solutions.

  19. An ethernet/IP security review with intrusion detection applications

    SciTech Connect

    Laughter, S. A.; Williams, R. D.

    2006-07-01

    Supervisory Control and Data Acquisition (SCADA) and automation networks, used throughout utility and manufacturing applications, have their own specific set of operational and security requirements when compared to corporate networks. The modern climate of heightened national security and awareness of terrorist threats has made the security of these systems of prime concern. There is a need to understand the vulnerabilities of these systems and how to monitor and protect them. Ethernet/IP is a member of a family of protocols based on the Control and Information Protocol (CIP). Ethernet/IP allows automation systems to be utilized on and integrated with traditional TCP/IP networks, facilitating integration of these networks with corporate systems and even the Internet. A review of the CIP protocol and the additions Ethernet/IP makes to it has been done to reveal the kind of attacks made possible through the protocol. A set of rules for the SNORT Intrusion Detection software is developed based on the results of the security review. These can be used to monitor, and possibly actively protect, a SCADA or automation network that utilizes Ethernet/IP in its infrastructure. (authors)

  20. Intrusion Prevention and Detection in Grid Computing - The ALICE Case

    NASA Astrophysics Data System (ADS)

    Gomez, Andres; Lara, Camilo; Kebschull, Udo

    2015-12-01

    Grids allow users flexible on-demand usage of computing resources through remote communication networks. A remarkable example of a Grid in High Energy Physics (HEP) research is used in the ALICE experiment at European Organization for Nuclear Research CERN. Physicists can submit jobs used to process the huge amount of particle collision data produced by the Large Hadron Collider (LHC). Grids face complex security challenges. They are interesting targets for attackers seeking for huge computational resources. Since users can execute arbitrary code in the worker nodes on the Grid sites, special care should be put in this environment. Automatic tools to harden and monitor this scenario are required. Currently, there is no integrated solution for such requirement. This paper describes a new security framework to allow execution of job payloads in a sandboxed context. It also allows process behavior monitoring to detect intrusions, even when new attack methods or zero day vulnerabilities are exploited, by a Machine Learning approach. We plan to implement the proposed framework as a software prototype that will be tested as a component of the ALICE Grid middleware.

  1. An armored-cable-based fiber Bragg grating sensor array for perimeter fence intrusion detection

    NASA Astrophysics Data System (ADS)

    Hao, Jianzhong; Dong, Bo; Varghese, Paulose; Phua, Jiliang; Foo, Siang Fook

    2011-11-01

    In this paper, an armored-cable-based optical fiber Bragg grating (FBG) sensor array, for perimeter fence intrusion detection, is demonstrated and some of the field trial results are reported. The field trial was conducted at a critical local installation in Singapore in December 2010. The sensor array was put through a series of both simulated and live intrusion scenarios to test the stability and suitability of operation in the local environmental conditions and to determine its capabilities in detecting and reporting these intrusions accurately to the control station. Such a sensor array can provide perimeter intrusion detection with fine granularity and preset pin-pointing accuracy. The various types of intrusions included aided or unaided climbs, tampering and cutting of the fence, etc. The unique sensor packaging structure provides high sensitivity, crush resistance and protection against rodents. It is also capable of resolving nuisance events such as rain, birds sitting on the fence or seismic vibrations. These sensors are extremely sensitive with a response time of a few seconds. They can be customized for a desired spatial resolution and pre-determined sensitivity. Furthermore, it is easy to cascade a series of such sensors to monitor and detect intrusion events over a long stretch of fence line. Such sensors can be applied to real-time intrusion detection for perimeter security, pipeline security and communications link security.

  2. An armored-cable-based fiber Bragg grating sensor array for perimeter fence intrusion detection

    NASA Astrophysics Data System (ADS)

    Hao, Jianzhong; Dong, Bo; Varghese, Paulose; Phua, Jiliang; Foo, Siang Fook

    2012-01-01

    In this paper, an armored-cable-based optical fiber Bragg grating (FBG) sensor array, for perimeter fence intrusion detection, is demonstrated and some of the field trial results are reported. The field trial was conducted at a critical local installation in Singapore in December 2010. The sensor array was put through a series of both simulated and live intrusion scenarios to test the stability and suitability of operation in the local environmental conditions and to determine its capabilities in detecting and reporting these intrusions accurately to the control station. Such a sensor array can provide perimeter intrusion detection with fine granularity and preset pin-pointing accuracy. The various types of intrusions included aided or unaided climbs, tampering and cutting of the fence, etc. The unique sensor packaging structure provides high sensitivity, crush resistance and protection against rodents. It is also capable of resolving nuisance events such as rain, birds sitting on the fence or seismic vibrations. These sensors are extremely sensitive with a response time of a few seconds. They can be customized for a desired spatial resolution and pre-determined sensitivity. Furthermore, it is easy to cascade a series of such sensors to monitor and detect intrusion events over a long stretch of fence line. Such sensors can be applied to real-time intrusion detection for perimeter security, pipeline security and communications link security.

  3. Research on artificial neural network intrusion detection photochemistry based on the improved wavelet analysis and transformation

    NASA Astrophysics Data System (ADS)

    Li, Hong; Ding, Xue

    2017-03-01

    This paper combines wavelet analysis and wavelet transform theory with artificial neural network, through the pretreatment on point feature attributes before in intrusion detection, to make them suitable for improvement of wavelet neural network. The whole intrusion classification model gets the better adaptability, self-learning ability, greatly enhances the wavelet neural network for solving the problem of field detection invasion, reduces storage space, contributes to improve the performance of the constructed neural network, and reduces the training time. Finally the results of the KDDCup99 data set simulation experiment shows that, this method reduces the complexity of constructing wavelet neural network, but also ensures the accuracy of the intrusion classification.

  4. Network intrusion detection by the coevolutionary immune algorithm of artificial immune systems with clonal selection

    NASA Astrophysics Data System (ADS)

    Salamatova, T.; Zhukov, V.

    2017-02-01

    The paper presents the application of the artificial immune systems apparatus as a heuristic method of network intrusion detection for algorithmic provision of intrusion detection systems. The coevolutionary immune algorithm of artificial immune systems with clonal selection was elaborated. In testing different datasets the empirical results of evaluation of the algorithm effectiveness were achieved. To identify the degree of efficiency the algorithm was compared with analogs. The fundamental rules based of solutions generated by this algorithm are described in the article.

  5. A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation

    DTIC Science & Technology

    2011-03-01

    for a new, self-organized, multi agent, flow-based intrusion detection system; and 2 ) a network simulation envi- ronment suitable for evaluating an...six years of service in the Air Force, and I am indebted to him for his efforts. I also thank Dr. Gilbert Peterson and Dr. Barry Mullins for valuable...1 1.1 The Generic Intrusion Detection Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.2 Scope of Investigative Domain

  6. A Distributed Signature Detection Method for Detecting Intrusions in Sensor Systems

    PubMed Central

    Kim, Ilkyu; Oh, Doohwan; Yoon, Myung Kuk; Yi, Kyueun; Ro, Won Woo

    2013-01-01

    Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on the Wu–Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors. PMID:23529146

  7. A distributed signature detection method for detecting intrusions in sensor systems.

    PubMed

    Kim, Ilkyu; Oh, Doohwan; Yoon, Myung Kuk; Yi, Kyueun; Ro, Won Woo

    2013-03-25

    Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on the Wu-Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors.

  8. A prototype implementation of a network-level intrusion detection system. Technical report number CS91-11

    SciTech Connect

    Heady, R.; Luger, G.F.; Maccabe, A.B.; Servilla, M.; Sturtevant, J.

    1991-05-15

    This paper presents the implementation of a prototype network level intrusion detection system. The prototype system monitors base level information in network packets (source, destination, packet size, time, and network protocol), learning the normal patterns and announcing anomalies as they occur. The goal of this research is to determine the applicability of current intrusion detection technology to the detection of network level intrusions. In particular, the authors are investigating the possibility of using this technology to detect and react to worm programs.

  9. Studying bio-inspired coalition formation of robots for detecting intrusions using game theory.

    PubMed

    Liang, Xiannuan; Xiao, Yang

    2010-06-01

    In this paper, inspired by the society of animals, we study the coalition formation of robots for detecting intrusions using game theory. We consider coalition formation in a group of three robots that detect and capture intrusions in a closed curve loop. In our analytical model, individuals seek alliances if they think that their detect regions are too short to gain an intrusion capturing probability larger than their own. We assume that coalition seeking has an investment cost and that the formation of a coalition determines the outcomes of parities, with the detect length of a coalition simply being the sum of those of separate coalition members. We derive that, for any cost, always detecting alone is an evolutionarily stable strategy (ESS), and that, if the cost is below a threshold, always trying to form a coalition is an ESS (thus a three-way coalition arises).

  10. Implementation of an intrusion detection system based on wireless positioning

    NASA Astrophysics Data System (ADS)

    Akopian, David; Chen, Philip; Gunturu, Maheedhar; Sagiraju, Phani K.

    2008-04-01

    WLAN networks are widely deployed and can be used for testbed and application developments in academic environments. This paper presents wireless positioning testbed and a related application implementation methodology as a case study. Nowadays state-of-the-art WLAN positioning systems achieve high location estimation accuracy. In designated areas the signal profile map can be designed and used for such a positioning. Coverage of WLAN networks is typically wider than the authorized areas and there might be network intrusion attempts from the vicinity areas such as parking lots, cafeterias, etc. In addition to conventional verification and authorization methods, the network can locate the user, verify if his location is in the authorized area and apply additional checks to find the violators.

  11. Scheduling Randomly-Deployed Heterogeneous Video Sensor Nodes for Reduced Intrusion Detection Time

    NASA Astrophysics Data System (ADS)

    Pham, Congduc

    This paper proposes to use video sensor nodes to provide an efficient intrusion detection system. We use a scheduling mechanism that takes into account the criticality of the surveillance application and present a performance study of various cover set construction strategies that take into account cameras with heterogeneous angle of view and those with very small angle of view. We show by simulation how a dynamic criticality management scheme can provide fast event detection for mission-critical surveillance applications by increasing the network lifetime and providing low stealth time of intrusions.

  12. A Multilevel Secure Constrained Intrusion Detection System Prototype

    DTIC Science & Technology

    2010-12-01

    components consist of a packet classifier, an IP defragmenter and a TCP reassembler, a portscan processor and a detection engine [9]. The packet... portscan processor watches for portscans and the detection engine performs protocol normalization, rule matching, and other detection functions to

  13. Functional requirements with survey results for integrated intrusion detection and access control annunciator systems

    SciTech Connect

    Arakaki, L.H.; Monaco, F.M.

    1995-09-01

    This report contains the guidance Functional Requirements for an Integrated Intrusion Detection and Access Control Annunciator System, and survey results of selected commercial systems. The survey questions were based upon the functional requirements; therefore, the results reflect which and sometimes how the guidance recommendations were met.

  14. An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network

    PubMed Central

    Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

    2015-01-01

    Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish–Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection. PMID:26447696

  15. An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

    PubMed

    Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

    2015-01-01

    Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

  16. An Optimal Method for Detecting Internal and External Intrusion in MANET

    NASA Astrophysics Data System (ADS)

    Rafsanjani, Marjan Kuchaki; Aliahmadipour, Laya; Javidi, Mohammad M.

    Mobile Ad hoc Network (MANET) is formed by a set of mobile hosts which communicate among themselves through radio waves. The hosts establish infrastructure and cooperate to forward data in a multi-hop fashion without a central administration. Due to their communication type and resources constraint, MANETs are vulnerable to diverse types of attacks and intrusions. In this paper, we proposed a method for prevention internal intruder and detection external intruder by using game theory in mobile ad hoc network. One optimal solution for reducing the resource consumption of detection external intruder is to elect a leader for each cluster to provide intrusion service to other nodes in the its cluster, we call this mode moderate mode. Moderate mode is only suitable when the probability of attack is low. Once the probability of attack is high, victim nodes should launch their own IDS to detect and thwart intrusions and we call robust mode. In this paper leader should not be malicious or selfish node and must detect external intrusion in its cluster with minimum cost. Our proposed method has three steps: the first step building trust relationship between nodes and estimation trust value for each node to prevent internal intrusion. In the second step we propose an optimal method for leader election by using trust value; and in the third step, finding the threshold value for notifying the victim node to launch its IDS once the probability of attack exceeds that value. In first and third step we apply Bayesian game theory. Our method due to using game theory, trust value and honest leader can effectively improve the network security, performance and reduce resource consumption.

  17. Evaluating Machine Learning Classifiers for Hybrid Network Intrusion Detection Systems

    DTIC Science & Technology

    2015-03-26

    13 2.3.2 Anomaly-Based Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.3.3 Stateful Protocol Analysis...1 TCP Transmission Control Protocol ...3 IP Internet Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 VFT Value-Focused Thinking

  18. Design and implementation of an intrusion detection system based on IPv6 protocol

    NASA Astrophysics Data System (ADS)

    Liu, Bin; Li, Zhitang; Li, Yao; Li, Zhanchun

    2005-11-01

    Network intrusion detection systems (NIDS) are important parts of network security architecture. Although many NIDS have been proposed, there is little effort to expand the current set of NIDS to support IPv6 protocol. This paper presents the design and implementation of a Network-based Intrusion Detection System that supports both IPv6 protocol and IPv4 protocol. It characters rules based logging to perform content pattern matching and detect a variety of attacks and probes from IPv4 and IPv6.There are four primary subsystems to make it up: packet capture, packet decoder, detection engine, and logging and alerting subsystem. A new approach to packet capture that combined NAPI with MMAP is proposed in this paper. The test results show that the efficiency of packet capture can be improved significantly by this method. Several new attack tools for IPv6 have been developed for intrusion detection evaluation. Test shows that more than 20 kinds of IPv6 attacks can be detected by this system and it also has a good performance under heavy traffic load.

  19. Detection and Classification of Network Intrusions Using Hidden Markov Models

    DTIC Science & Technology

    2002-01-01

    system was able to detect buffer overflows, ftp-write attack, warez attack, guess telnet, guest and HTTPtunnel attacks. They claim that no false...already known attack that has been altered or a completely new attack. 95 Bibliography [1] Stuart McClure et. al “ Hacking Exposed: Network Security

  20. Detection of Dry Intrusion on Water Vapor Images Over Central Europe - June 2010 TO September 2011

    NASA Astrophysics Data System (ADS)

    Novotny, J.; Dejmal, K.; Hudec, F.; Kolar, P.

    2016-06-01

    The knowledge of evaluation of the intensity of cyclogenesis which could be connected with the weather having a significant impact on Earth's surface is quite useful. If, as one of the basic assumptions, the existence of connection between dry intrusions, dry bands, tropopause height and warm dark areas distribution on water vapor images (WV images) is considered, it is possible to set up a method of detecting dry intrusions on searching and tracking areas with higher brightness temperature compared with the surrounding environment. This paper covers the period between June 2010 and September 2011 over Central Europe. The ISIS method (Instrument de Suivi dans I'Imagerie satellitaire), originally developed for detection of cold cloud tops, was used as an initial ideological point. Subsequently, this method was modified by Michel and Bouttier for usage on WV images. Some of the applied criteria and parameters were chosen with reference to the results published by Michel and Bouttier as well as by Novotny. The procedure can be divided into two steps: detection of warm areas and their tracking. Cases of detection of areas not evidently connected with dry intrusions can be solved by filtering off based on the connection between detected warm areas to the cyclonic side of jet streams and significant lowering of the tropopause.

  1. A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks

    PubMed Central

    Ma, Tao; Wang, Fen; Cheng, Jianjun; Yu, Yang; Chen, Xiaoyun

    2016-01-01

    The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC) and deep neural network (DNN) algorithms. First, the dataset is divided into k subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN), support vector machine (SVM), random forest (RF) and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks. PMID:27754380

  2. A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks.

    PubMed

    Ma, Tao; Wang, Fen; Cheng, Jianjun; Yu, Yang; Chen, Xiaoyun

    2016-10-13

    The development of intrusion detection systems (IDS) that are adapted to allow routers and network defence systems to detect malicious network traffic disguised as network protocols or normal access is a critical challenge. This paper proposes a novel approach called SCDNN, which combines spectral clustering (SC) and deep neural network (DNN) algorithms. First, the dataset is divided into k subsets based on sample similarity using cluster centres, as in SC. Next, the distance between data points in a testing set and the training set is measured based on similarity features and is fed into the deep neural network algorithm for intrusion detection. Six KDD-Cup99 and NSL-KDD datasets and a sensor network dataset were employed to test the performance of the model. These experimental results indicate that the SCDNN classifier not only performs better than backpropagation neural network (BPNN), support vector machine (SVM), random forest (RF) and Bayes tree models in detection accuracy and the types of abnormal attacks found. It also provides an effective tool of study and analysis of intrusion detection in large networks.

  3. Components for Cooperative Intrusion Detection in Dynamic Coalition Environments

    DTIC Science & Technology

    2004-04-20

    IWS Before it is possible to design and build a robust and effective IWS for CE scenarios, several issues are to be solved. Some of these issues...during the measurement period. Those graphs can be partitioned into subgraphs using graph clustering algorithms. The clustering of the graph...reported as warning messages. The comparison measures used for anomaly detection in network traffic structures can be used in this domain as well. When

  4. How Intrusion Detection Can Improve Software Decoy Applications

    DTIC Science & Technology

    2003-03-01

    processes and uses a security kernel. Additionally, LIDS has a built-in portscan detector, which can be used to alert users to the warning signs of a...several useful ways, such as in IP defragmentation, TCP stream assembly, portscan detection, and web-traffic normalization. The preprocessor can...HIDS can see a portscan , but a NIDS can see the similar attacks on other sites that happened first. 22 SNORT LIDS NIDS AlarmsLog Files HIDS

  5. A Protocol Specification-Based Intrusion Detection System for VoIP and Its Evaluation

    NASA Astrophysics Data System (ADS)

    Phit, Thyda; Abe, Kôki

    We propose an architecture of Intrusion Detection System (IDS) for VoIP using a protocol specification-based detection method to monitor the network traffics and alert administrator for further analysis of and response to suspicious activities. The protocol behaviors and their interactions are described by state machines. Traffic that behaves differently from the standard specifications are considered to be suspicious. The IDS has been implemented and simulated using OPNET Modeler, and verified to detect attacks. It was found that our system can detect typical attacks within a reasonable amount of delay time.

  6. Windows NT Attacks for the Evaluation of Intrusion Detection Systems

    DTIC Science & Technology

    2000-06-01

    Neptune and Smurf. These attacks are fully documented in [10]. In addition, two denial-of-service attacks, CrashIIS and DoSNuke, were developed to...in the Netscape browser. NetBus and NetCat use trojan programs to establish back doors on the victim system. PPMacro inserts malicious macro code...detecting the attack. 51 7.2 Netbus R-s-U Description The attacker uses a trojan program to install and run the Netbus server, version 1.7, on

  7. Phase-sensitive optical time domain reflectometer for distributed fence-perimeter intrusion detection

    NASA Astrophysics Data System (ADS)

    Yu, Xuhui; Zhou, Deliang; Lu, Bin; Liu, Sufang; Pan, Ming

    2015-10-01

    In this paper, we demonstrate a distributed fence-perimeter intrusion detection system using a phase-sensitive optical time domain reflectometer (Φ-OTDR) with several advantages, such as high spatial resolution, large detection range, single-end measurement and immunity from electromagnetic interference. By the effort of generating a high-extinction-ratio optical pulse, optimizing the incident optical power and utilizing a differential algorithm, a home-made Φ-OTDR system, as a distributed vibration sensor, is implemented with a spatial resolution of 10 meter. Nowadays, a fence-perimeter intrusion detection system is desired for the security monitor. We set up a fence perimeter using a fiber cable containing only one fiber and a field experiment is carried out based on our Φ-OTDR system. Various vibration events are recorded and analyzed, including wind blowing, personal climbing and knocking. The experiment results reveal unique vibration characteristics of different events in the frequency domain and confirm the effectiveness of the homemade Φ-OTDR system in the application of the distributed fence-perimeter intrusion detection.

  8. Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection.

    PubMed

    Al-Jarrah, Omar Y; Alhussein, Omar; Yoo, Paul D; Muhaidat, Sami; Taha, Kamal; Kim, Kwangjo

    2016-08-01

    Botnets, which consist of remotely controlled compromised machines called bots, provide a distributed platform for several threats against cyber world entities and enterprises. Intrusion detection system (IDS) provides an efficient countermeasure against botnets. It continually monitors and analyzes network traffic for potential vulnerabilities and possible existence of active attacks. A payload-inspection-based IDS (PI-IDS) identifies active intrusion attempts by inspecting transmission control protocol and user datagram protocol packet's payload and comparing it with previously seen attacks signatures. However, the PI-IDS abilities to detect intrusions might be incapacitated by packet encryption. Traffic-based IDS (T-IDS) alleviates the shortcomings of PI-IDS, as it does not inspect packet payload; however, it analyzes packet header to identify intrusions. As the network's traffic grows rapidly, not only the detection-rate is critical, but also the efficiency and the scalability of IDS become more significant. In this paper, we propose a state-of-the-art T-IDS built on a novel randomized data partitioned learning model (RDPLM), relying on a compact network feature set and feature selection techniques, simplified subspacing and a multiple randomized meta-learning technique. The proposed model has achieved 99.984% accuracy and 21.38 s training time on a well-known benchmark botnet dataset. Experiment results demonstrate that the proposed methodology outperforms other well-known machine-learning models used in the same detection task, namely, sequential minimal optimization, deep neural network, C4.5, reduced error pruning tree, and randomTree.

  9. A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

    PubMed Central

    Amudha, P.; Karthik, S.; Sivakumari, S.

    2015-01-01

    Intrusion detection has become a main part of network security due to the huge number of attacks which affects the computers. This is due to the extensive growth of internet connectivity and accessibility to information systems worldwide. To deal with this problem, in this paper a hybrid algorithm is proposed to integrate Modified Artificial Bee Colony (MABC) with Enhanced Particle Swarm Optimization (EPSO) to predict the intrusion detection problem. The algorithms are combined together to find out better optimization results and the classification accuracies are obtained by 10-fold cross-validation method. The purpose of this paper is to select the most relevant features that can represent the pattern of the network traffic and test its effect on the success of the proposed hybrid classification algorithm. To investigate the performance of the proposed method, intrusion detection KDDCup'99 benchmark dataset from the UCI Machine Learning repository is used. The performance of the proposed method is compared with the other machine learning algorithms and found to be significantly different. PMID:26221625

  10. Idaho National Laboratory Supervisory Control and Data Acquisition Intrusion Detection System (SCADA IDS)

    SciTech Connect

    Jared Verba; Michael Milvich

    2008-05-01

    Current Intrusion Detection System (IDS) technology is not suited to be widely deployed inside a Supervisory, Control and Data Acquisition (SCADA) environment. Anomaly- and signature-based IDS technologies have developed methods to cover information technology-based networks activity and protocols effectively. However, these IDS technologies do not include the fine protocol granularity required to ensure network security inside an environment with weak protocols lacking authentication and encryption. By implementing a more specific and more intelligent packet inspection mechanism, tailored traffic flow analysis, and unique packet tampering detection, IDS technology developed specifically for SCADA environments can be deployed with confidence in detecting malicious activity.

  11. Scanning seismic intrusion detection method and apparatus. [monitoring unwanted subterranean entry and departure

    NASA Technical Reports Server (NTRS)

    Lee, R. D. (Inventor)

    1983-01-01

    An intrusion monitoring system includes an array of seismic sensors, such as geophones, arranged along a perimeter to be monitored for unauthorized intrusion as by surface movement or tunneling. Two wires lead from each sensor to a central monitoring station. The central monitoring station has three modes of operation. In a first mode of operation, the output of all of the seismic sensors is summed into a receiver for amplification and detection. When the amplitude of the summed signals exceeds a certain predetermined threshold value an alarm is sounded. In a second mode of operation, the individual output signals from the sensors are multiplexed into the receiver for sequentially interrogating each of the sensors.

  12. Attacks and intrusion detection in wireless sensor networks of industrial SCADA systems

    NASA Astrophysics Data System (ADS)

    Kamaev, V. A.; Finogeev, A. G.; Finogeev, A. A.; Parygin, D. S.

    2017-01-01

    The effectiveness of automated process control systems (APCS) and supervisory control and data acquisition systems (SCADA) information security depends on the applied protection technologies of transport environment data transmission components. This article investigates the problems of detecting attacks in wireless sensor networks (WSN) of SCADA systems. As a result of analytical studies, the authors developed the detailed classification of external attacks and intrusion detection in sensor networks and brought a detailed description of attacking impacts on components of SCADA systems in accordance with the selected directions of attacks.

  13. A research using hybrid RBF/Elman neural networks for intrusion detection system secure model

    NASA Astrophysics Data System (ADS)

    Tong, Xiaojun; Wang, Zhu; Yu, Haining

    2009-10-01

    A hybrid RBF/Elman neural network model that can be employed for both anomaly detection and misuse detection is presented in this paper. The IDSs using the hybrid neural network can detect temporally dispersed and collaborative attacks effectively because of its memory of past events. The RBF network is employed as a real-time pattern classification and the Elman network is employed to restore the memory of past events. The IDSs using the hybrid neural network are evaluated against the intrusion detection evaluation data sponsored by U.S. Defense Advanced Research Projects Agency (DARPA). Experimental results are presented in ROC curves. Experiments show that the IDSs using this hybrid neural network improve the detection rate and decrease the false positive rate effectively.

  14. Integration of Self-Organizing Map (SOM) and Kernel Density Estimation (KDE) for network intrusion detection

    NASA Astrophysics Data System (ADS)

    Cao, Yuan; He, Haibo; Man, Hong; Shen, Xiaoping

    2009-09-01

    This paper proposes an approach to integrate the self-organizing map (SOM) and kernel density estimation (KDE) techniques for the anomaly-based network intrusion detection (ABNID) system to monitor the network traffic and capture potential abnormal behaviors. With the continuous development of network technology, information security has become a major concern for the cyber system research. In the modern net-centric and tactical warfare networks, the situation is more critical to provide real-time protection for the availability, confidentiality, and integrity of the networked information. To this end, in this work we propose to explore the learning capabilities of SOM, and integrate it with KDE for the network intrusion detection. KDE is used to estimate the distributions of the observed random variables that describe the network system and determine whether the network traffic is normal or abnormal. Meanwhile, the learning and clustering capabilities of SOM are employed to obtain well-defined data clusters to reduce the computational cost of the KDE. The principle of learning in SOM is to self-organize the network of neurons to seek similar properties for certain input patterns. Therefore, SOM can form an approximation of the distribution of input space in a compact fashion, reduce the number of terms in a kernel density estimator, and thus improve the efficiency for the intrusion detection. We test the proposed algorithm over the real-world data sets obtained from the Integrated Network Based Ohio University's Network Detective Service (INBOUNDS) system to show the effectiveness and efficiency of this method.

  15. Agent Based Computing Machine

    DTIC Science & Technology

    2005-12-09

    coordinates as in cellular automata systems. But using biology as a model suggests that the most general systems must provide for partial, but constrained...17. SECURITY CLASSIFICATION OF 118. SECURITY CLASSIFICATION OF 19. SECURITY CLASSIFICATION OF 20. LIMITATION OF ABSTRA REPORT THIS PAGE ABSTRACT...system called an "agent based computing" machine (ABC Machine). The ABC Machine is motivated by cellular biochemistry and it is based upon a concept

  16. An Intrusion Detection System for the Protection of Railway Assets Using Fiber Bragg Grating Sensors

    PubMed Central

    Catalano, Angelo; Bruno, Francesco Antonio; Pisco, Marco; Cutolo, Antonello; Cusano, Andrea

    2014-01-01

    We demonstrate the ability of Fiber Bragg Gratings (FBGs) sensors to protect large areas from unauthorized activities in railway scenarios such as stations or tunnels. We report on the technological strategy adopted to protect a specific depot, representative of a common scenario for security applications in the railway environment. One of the concerns in the protection of a railway area centers on the presence of rail-tracks, which cannot be obstructed with physical barriers. We propose an integrated optical fiber system composed of FBG strain sensors that can detect human intrusion for protection of the perimeter combined with FBG accelerometer sensors for protection of rail-track access. Several trials were carried out in indoor and outdoor environments. The results demonstrate that FBG strain sensors bonded under a ribbed rubber mat enable the detection of intruder break-in via the pressure induced on the mat, whereas the FBG accelerometers installed under the rails enable the detection of intruders walking close to the railroad tracks via the acoustic surface waves generated by footsteps. Based on a single enabling technology, this integrated system represents a valuable intrusion detection system for railway security and could be integrated with other sensing functionalities in the railway field using fiber optic technology. PMID:25268920

  17. An intrusion detection system for the protection of railway assets using Fiber Bragg Grating sensors.

    PubMed

    Catalano, Angelo; Bruno, Francesco Antonio; Pisco, Marco; Cutolo, Antonello; Cusano, Andrea

    2014-09-29

    We demonstrate the ability of Fiber Bragg Gratings (FBGs) sensors to protect large areas from unauthorized activities in railway scenarios such as stations or tunnels. We report on the technological strategy adopted to protect a specific depot, representative of a common scenario for security applications in the railway environment. One of the concerns in the protection of a railway area centers on the presence of rail-tracks, which cannot be obstructed with physical barriers. We propose an integrated optical fiber system composed of FBG strain sensors that can detect human intrusion for protection of the perimeter combined with FBG accelerometer sensors for protection of rail-track access. Several trials were carried out in indoor and outdoor environments. The results demonstrate that FBG strain sensors bonded under a ribbed rubber mat enable the detection of intruder break-in via the pressure induced on the mat, whereas the FBG accelerometers installed under the rails enable the detection of intruders walking close to the railroad tracks via the acoustic surface waves generated by footsteps. Based on a single enabling technology, this integrated system represents a valuable intrusion detection system for railway security and could be integrated with other sensing functionalities in the railway field using fiber optic technology.

  18. A Multiagent-based Intrusion Detection System with the Support of Multi-Class Supervised Classification

    NASA Astrophysics Data System (ADS)

    Shyu, Mei-Ling; Sainani, Varsha

    The increasing number of network security related incidents have made it necessary for the organizations to actively protect their sensitive data with network intrusion detection systems (IDSs). IDSs are expected to analyze a large volume of data while not placing a significantly added load on the monitoring systems and networks. This requires good data mining strategies which take less time and give accurate results. In this study, a novel data mining assisted multiagent-based intrusion detection system (DMAS-IDS) is proposed, particularly with the support of multiclass supervised classification. These agents can detect and take predefined actions against malicious activities, and data mining techniques can help detect them. Our proposed DMAS-IDS shows superior performance compared to central sniffing IDS techniques, and saves network resources compared to other distributed IDS with mobile agents that activate too many sniffers causing bottlenecks in the network. This is one of the major motivations to use a distributed model based on multiagent platform along with a supervised classification technique.

  19. Probabilistic monitoring in intrusion detection module for energy efficiency in mobile ad hoc networks

    NASA Astrophysics Data System (ADS)

    De Rango, Floriano; Lupia, Andrea

    2016-05-01

    MANETs allow mobile nodes communicating to each other using the wireless medium. A key aspect of these kind of networks is the security, because their setup is done without an infrastructure, so external nodes could interfere in the communication. Mobile nodes could be compromised, misbehaving during the multi-hop transmission of data, or they could have a selfish behavior to save energy, which is another important constraint in MANETs. The detection of these behaviors need a framework that takes into account the latest interactions among nodes, so malicious or selfish nodes could be detected also if their behavior is changed over time. The monitoring activity increases the energy consumption, so our proposal takes into account this issue reducing the energy required by the monitoring system, keeping the effectiveness of the intrusion detection system. The results show an improvement in the saved energy, improving the detection performance too.

  20. Design of an Acoustic Target Intrusion Detection System Based on Small-Aperture Microphone Array.

    PubMed

    Zu, Xingshui; Guo, Feng; Huang, Jingchang; Zhao, Qin; Liu, Huawei; Li, Baoqing; Yuan, Xiaobing

    2017-03-04

    Automated surveillance of remote locations in a wireless sensor network is dominated by the detection algorithm because actual intrusions in such locations are a rare event. Therefore, a detection method with low power consumption is crucial for persistent surveillance to ensure longevity of the sensor networks. A simple and effective two-stage algorithm composed of energy detector (ED) and delay detector (DD) with all its operations in time-domain using small-aperture microphone array (SAMA) is proposed. The algorithm analyzes the quite different velocities between wind noise and sound waves to improve the detection capability of ED in the surveillance area. Experiments in four different fields with three types of vehicles show that the algorithm is robust to wind noise and the probability of detection and false alarm are 96.67% and 2.857%, respectively.

  1. Design of an Acoustic Target Intrusion Detection System Based on Small-Aperture Microphone Array

    PubMed Central

    Zu, Xingshui; Guo, Feng; Huang, Jingchang; Zhao, Qin; Liu, Huawei; Li, Baoqing; Yuan, Xiaobing

    2017-01-01

    Automated surveillance of remote locations in a wireless sensor network is dominated by the detection algorithm because actual intrusions in such locations are a rare event. Therefore, a detection method with low power consumption is crucial for persistent surveillance to ensure longevity of the sensor networks. A simple and effective two-stage algorithm composed of energy detector (ED) and delay detector (DD) with all its operations in time-domain using small-aperture microphone array (SAMA) is proposed. The algorithm analyzes the quite different velocities between wind noise and sound waves to improve the detection capability of ED in the surveillance area. Experiments in four different fields with three types of vehicles show that the algorithm is robust to wind noise and the probability of detection and false alarm are 96.67% and 2.857%, respectively. PMID:28273838

  2. Hybrid TDM/WDM based fiber-optic sensor network for perimeter intrusion detection

    NASA Astrophysics Data System (ADS)

    Li, Xiaolei; Sun, Qizhen; Sun, Zhifeng; Wo, Jianghai; Zhang, Manliang; Liu, Deming

    2011-05-01

    A distributed fiber-optic sensor system is proposed and demonstrated for long-distance intrusion-detection, which employs the hybrid time/wavelength division multiplexing (TDM/WDM) architecture. By utilizing 20 time zones and 6 wavelengths, the system contains up to 120 fiber sensing units (OSU), of which the distributed sensing distance is from 0 to 500m. So the whole sensing distance of this system could reach 60 km. The system has been demonstrated to run stably exceed six months with the false alarm rate of less than 4%.

  3. The NIDS Cluster: Scalable, Stateful Network Intrusion Detection on Commodity Hardware

    SciTech Connect

    Tierney, Brian L; Vallentin, Matthias; Sommer, Robin; Lee, Jason; Leres, Craig; Paxson, Vern; Tierney, Brian

    2007-09-19

    In this work we present a NIDS cluster as a scalable solution for realizing high-performance, stateful network intrusion detection on commodity hardware. The design addresses three challenges: (i) distributing traffic evenly across an extensible set of analysis nodes in a fashion that minimizes the communication required for coordination, (ii) adapting the NIDS's operation to support coordinating its low-level analysis rather than just aggregating alerts; and (iii) validating that the cluster produces sound results. Prototypes of our NIDS cluster now operate at the Lawrence Berkeley National Laboratory and the University of California at Berkeley. In both environments the clusters greatly enhance the power of the network security monitoring.

  4. HPNAIDM: The High-Performance Network Anomaly/Intrusion Detection and Mitigation System

    SciTech Connect

    Chen, Yan

    2013-12-05

    Identifying traffic anomalies and attacks rapidly and accurately is critical for large network operators. With the rapid growth of network bandwidth, such as the next generation DOE UltraScience Network, and fast emergence of new attacks/virus/worms, existing network intrusion detection systems (IDS) are insufficient because they: • Are mostly host-based and not scalable to high-performance networks; • Are mostly signature-based and unable to adaptively recognize flow-level unknown attacks; • Cannot differentiate malicious events from the unintentional anomalies. To address these challenges, we proposed and developed a new paradigm called high-performance network anomaly/intrustion detection and mitigation (HPNAIDM) system. The new paradigm is significantly different from existing IDSes with the following features (research thrusts). • Online traffic recording and analysis on high-speed networks; • Online adaptive flow-level anomaly/intrusion detection and mitigation; • Integrated approach for false positive reduction. Our research prototype and evaluation demonstrate that the HPNAIDM system is highly effective and economically feasible. Beyond satisfying the pre-set goals, we even exceed that significantly (see more details in the next section). Overall, our project harvested 23 publications (2 book chapters, 6 journal papers and 15 peer-reviewed conference/workshop papers). Besides, we built a website for technique dissemination, which hosts two system prototype release to the research community. We also filed a patent application and developed strong international and domestic collaborations which span both academia and industry.

  5. A Hypergraph and Arithmetic Residue-based Probabilistic Neural Network for classification in Intrusion Detection Systems.

    PubMed

    Raman, M R Gauthama; Somu, Nivethitha; Kirthivasan, Kannan; Sriram, V S Shankar

    2017-02-17

    Over the past few decades, the design of an intelligent Intrusion Detection System (IDS) remains an open challenge to the research community. Continuous efforts by the researchers have resulted in the development of several learning models based on Artificial Neural Network (ANN) to improve the performance of the IDSs. However, there exists a tradeoff with respect to the stability of ANN architecture and the detection rate for less frequent attacks. This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS. The Helly property of Hypergraph was exploited for the identification of the optimal feature subset and the arithmetic residue of the optimal feature subset was used to train the PNN. The performance of HG AR-PNN was evaluated using KDD CUP 1999 intrusion dataset. Experimental results prove the dominance of HG AR-PNN classifier over the existing classifiers with respect to the stability and improved detection rate for less frequent attacks.

  6. Evolving optimised decision rules for intrusion detection using particle swarm paradigm

    NASA Astrophysics Data System (ADS)

    Sivatha Sindhu, Siva S.; Geetha, S.; Kannan, A.

    2012-12-01

    The aim of this article is to construct a practical intrusion detection system (IDS) that properly analyses the statistics of network traffic pattern and classify them as normal or anomalous class. The objective of this article is to prove that the choice of effective network traffic features and a proficient machine-learning paradigm enhances the detection accuracy of IDS. In this article, a rule-based approach with a family of six decision tree classifiers, namely Decision Stump, C4.5, Naive Baye's Tree, Random Forest, Random Tree and Representative Tree model to perform the detection of anomalous network pattern is introduced. In particular, the proposed swarm optimisation-based approach selects instances that compose training set and optimised decision tree operate over this trained set producing classification rules with improved coverage, classification capability and generalisation ability. Experiment with the Knowledge Discovery and Data mining (KDD) data set which have information on traffic pattern, during normal and intrusive behaviour shows that the proposed algorithm produces optimised decision rules and outperforms other machine-learning algorithm.

  7. A harmful-intrusion detection method based on background reconstruction and two-dimensional K-S test in an optical fiber pre-warning system

    NASA Astrophysics Data System (ADS)

    Bi, Fukun; Zheng, Tong; Qu, Hongquan; Pang, Liping

    2016-06-01

    The key technology and main difficulty for optical fiber intrusion pre-warning systems (OFIPS) is the extraction of harmful-intrusion signals. After being processed by a phase-sensitive optical time-domain reflectometer (Φ-OTDR), vibration signals can be preliminarily extracted. Generally, these include noises and intrusions. Here, intrusions can be divided into harmful and harmless intrusions. With respect to the close study of signal characteristics, an effective extraction method of harmful intrusion is proposed in the paper. Firstly, in the part of the background reconstruction, all intrusion signals are first detected by a constant false alarm rate (CFAR). We then reconstruct the backgrounds by extracting two-part information of alarm points, time and amplitude. This ensures that the detection background consists of intrusion signals. Secondly, in the part of the two-dimensional Kolmogorov-Smirnov (K-S) test, in order to extract harmful ones from all extracted intrusions, we design a separation method. It is based on the signal characteristics of harmful intrusion, which are shorter time interval and higher amplitude. In the actual OFIPS, the detection method is used in some typical scenes, which includes a lot of harmless intrusions, for example construction sites and busy roads. Results show that we can effectively extract harmful intrusions.

  8. Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security

    PubMed Central

    Kang, Min-Joo

    2016-01-01

    A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN), therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN) bus. PMID:27271802

  9. Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.

    PubMed

    Kang, Min-Joo; Kang, Je-Won

    2016-01-01

    A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to enhance the security of in-vehicular network. The parameters building the DNN structure are trained with probability-based feature vectors that are extracted from the in-vehicular network packets. For a given packet, the DNN provides the probability of each class discriminating normal and attack packets, and, thus the sensor can identify any malicious attack to the vehicle. As compared to the traditional artificial neural network applied to the IDS, the proposed technique adopts recent advances in deep learning studies such as initializing the parameters through the unsupervised pre-training of deep belief networks (DBN), therefore improving the detection accuracy. It is demonstrated with experimental results that the proposed technique can provide a real-time response to the attack with a significantly improved detection ratio in controller area network (CAN) bus.

  10. Evaluation and analysis of non-intrusive techniques for detecting illicit substances

    SciTech Connect

    Micklich, B.J.; Roche, C.T.; Fink, C.L.; Yule, T.J.; Demirgian, J.C.; Kunz, T.D.; Ulvick, S.J.; Cui, J.

    1995-12-31

    Argonne National Laboratory (ANL) and the Houston Advanced Research Center (HARC) have been tasked by the Counterdrug Technology Assessment Center of the Office of National Drug Control Policy to conduct evaluations and analyses of technologies for the non-intrusive inspection of containers for illicit substances. These technologies span the range of nuclear, X-ray, and chemical techniques used in nondestructive sample analysis. ANL has performed assessments of nuclear and X-ray inspection concepts and undertaken site visits with developers to understand the capabilities and the range of applicability of candidate systems. ANL and HARC have provided support to law enforcement agencies (LEAs), including participation in numerous field studies. Both labs have provided staff to assist in the Narcotics Detection Technology Assessment (NDTA) program for evaluating drug detection systems. Also, the two labs are performing studies of drug contamination of currency. HARC has directed technical evaluations of automated ballistics imaging and identification systems under consideration by law enforcement agencies. ANL and HARC have sponsored workshops and a symposium, and are participating in a Non-Intrusive Inspection Study being led by Dynamics Technology, Incorporated.

  11. Long-distance fiber optic sensing solutions for pipeline leakage, intrusion, and ground movement detection

    NASA Astrophysics Data System (ADS)

    Nikles, Marc

    2009-05-01

    An increasing number of pipelines are constructed in remote regions affected by harsh environmental conditions where pipeline routes often cross mountain areas which are characterized by unstable grounds and where soil texture changes between winter and summer increase the probability of hazards. Third party intentional interference or accidental intrusions are a major cause of pipeline failures leading to large leaks or even explosions. Due to the long distances to be monitored and the linear nature of pipelines, distributed fiber optic sensing techniques offer significant advantages and the capability to detect and localize pipeline disturbance with great precision. Furthermore pipeline owner/operators lay fiber optic cable parallel to transmission pipelines for telecommunication purposes and at minimum additional cost monitoring capabilities can be added to the communication system. The Brillouin-based Omnisens DITEST monitoring system has been used in several long distance pipeline projects. The technique is capable of measuring strain and temperature over 100's kilometers with meter spatial resolution. Dedicated fiber optic cables have been developed for continuous strain and temperature monitoring and their deployment along the pipeline has enabled permanent and continuous pipeline ground movement, intrusion and leak detection. This paper presents a description of the fiber optic Brillouin-based DITEST sensing technique, its measurement performance and limits, while addressing future perspectives for pipeline monitoring. The description is supported by case studies and illustrated by field data.

  12. Weighted link graphs: a distributed IDS for secondary intrusion detection and defense

    NASA Astrophysics Data System (ADS)

    Zhou, Mian; Lang, Sheau-Dong

    2005-03-01

    While a firewall installed at the perimeter of a local network provides the first line of defense against the hackers, many intrusion incidents are the results of successful penetration of the firewalls. One computer"s compromise often put the entire network at risk. In this paper, we propose an IDS that provides a finer control over the internal network. The system focuses on the variations of connection-based behavior of each single computer, and uses a weighted link graph to visualize the overall traffic abnormalities. The functionality of our system is of a distributed personal IDS system that also provides a centralized traffic analysis by graphical visualization. We use a novel weight assignment schema for the local detection within each end agent. The local abnormalities are quantitatively carried out by the node weight and link weight and further sent to the central analyzer to build the weighted link graph. Thus, we distribute the burden of traffic processing and visualization to each agent and make it more efficient for the overall intrusion detection. As the LANs are more vulnerable to inside attacks, our system is designed as a reinforcement to prevent corruption from the inside.

  13. TAD2: the first truly non-intrusive lie detection system deployed in real crime cases

    NASA Astrophysics Data System (ADS)

    Sumriddetchkajorn, Sarun; Somboonkaew, Armote

    2010-11-01

    Interrogation is an important step for seeking truth from the suspect. With the limit of the intrusive nature of the current polygraph, we show here a highly-sought-after non-intrusive lie detection system with a user-friendly interface called TAD2. The key idea behind our TAD2 is based on the analysis of far-infrared data obtained remotely from the periorbital and nostril areas of the suspect during the interrogation. In this way, measured change in skin temperature around two periorbital areas is converted to a relative blood flow velocity while a respiration pattern is simultaneously determined from the measured change in temperature around the nostril region. In addition, TAD2 is embedded with our automatic baseline assignment that is used for distinguishing the subject's response into normal or abnormal stage. In our TAD2, the officer can choose to perform one of the three standard lie detection tests, namely, a modified zone comparison test, a modified general question test, and an irrelevant & relevant test. Field test results from suspects in real crime cases are discussed.

  14. Non-intrusive gesture recognition system combining with face detection based on Hidden Markov Model

    NASA Astrophysics Data System (ADS)

    Jin, Jing; Wang, Yuanqing; Xu, Liujing; Cao, Liqun; Han, Lei; Zhou, Biye; Li, Minggao

    2014-11-01

    A non-intrusive gesture recognition human-machine interaction system is proposed in this paper. In order to solve the hand positioning problem which is a difficulty in current algorithms, face detection is used for the pre-processing to narrow the search area and find user's hand quickly and accurately. Hidden Markov Model (HMM) is used for gesture recognition. A certain number of basic gesture units are trained as HMM models. At the same time, an improved 8-direction feature vector is proposed and used to quantify characteristics in order to improve the detection accuracy. The proposed system can be applied in interaction equipments without special training for users, such as household interactive television

  15. Alerts Analysis and Visualization in Network-based Intrusion Detection Systems

    SciTech Connect

    Yang, Dr. Li

    2010-08-01

    The alerts produced by network-based intrusion detection systems, e.g. Snort, can be difficult for network administrators to efficiently review and respond to due to the enormous number of alerts generated in a short time frame. This work describes how the visualization of raw IDS alert data assists network administrators in understanding the current state of a network and quickens the process of reviewing and responding to intrusion attempts. The project presented in this work consists of three primary components. The first component provides a visual mapping of the network topology that allows the end-user to easily browse clustered alerts. The second component is based on the flocking behavior of birds such that birds tend to follow other birds with similar behaviors. This component allows the end-user to see the clustering process and provides an efficient means for reviewing alert data. The third component discovers and visualizes patterns of multistage attacks by profiling the attacker s behaviors.

  16. Multi-Centrality Graph Spectral Decompositions and Their Application to Cyber Intrusion Detection

    SciTech Connect

    Chen, Pin-Yu; Choudhury, Sutanay; Hero, Alfred

    2016-03-01

    Many modern datasets can be represented as graphs and hence spectral decompositions such as graph principal component analysis (PCA) can be useful. Distinct from previous graph decomposition approaches based on subspace projection of a single topological feature, e.g., the centered graph adjacency matrix (graph Laplacian), we propose spectral decomposition approaches to graph PCA and graph dictionary learning that integrate multiple features, including graph walk statistics, centrality measures and graph distances to reference nodes. In this paper we propose a new PCA method for single graph analysis, called multi-centrality graph PCA (MC-GPCA), and a new dictionary learning method for ensembles of graphs, called multi-centrality graph dictionary learning (MC-GDL), both based on spectral decomposition of multi-centrality matrices. As an application to cyber intrusion detection, MC-GPCA can be an effective indicator of anomalous connectivity pattern and MC-GDL can provide discriminative basis for attack classification.

  17. Time-resolved seismic tomography detects magma intrusions at Mount Etna.

    PubMed

    Patanè, D; Barberi, G; Cocina, O; De Gori, P; Chiarabba, C

    2006-08-11

    The continuous volcanic and seismic activity at Mount Etna makes this volcano an important laboratory for seismological and geophysical studies. We used repeated three-dimensional tomography to detect variations in elastic parameters during different volcanic cycles, before and during the October 2002-January 2003 flank eruption. Well-defined anomalous low P- to S-wave velocity ratio volumes were revealed. Absent during the pre-eruptive period, the anomalies trace the intrusion of volatile-rich (>/=4 weight percent) basaltic magma, most of which rose up only a few months before the onset of eruption. The observed time changes of velocity anomalies suggest that four-dimensional tomography provides a basis for more efficient volcano monitoring and short- and midterm eruption forecasting of explosive activity.

  18. Intrusion detection capabilities of smart video: Collaborative efforts to improve remote monitoring for safeguards surveillance

    SciTech Connect

    Kadner, S.P.; Ondrik, M.; Reisman, A.

    1996-12-31

    Collaborative efforts between the International Projects Division (IPD) of the Department of Advanced Technology at Brookhaven National Laboratory, Aquila Technologies Group, Inc. (Aquila), and the General Physics Institute (GPI) in Moscow have developed object recognition technologies to provide real-time intrusion detection capabilities for Aquila`s GEMINI Digital Surveillance System. The research, development and testing for integrating enhanced surveillance capabilities into Aquila`s GEMINI system will receive support from the US Industry Coalition (USIC), an initiative funded by the Initiatives for Proliferation Prevention (IPP), in the coming year. Oversight of the research and development effort is being provided by the IPD staff to ensure that the technical standards of safeguards systems for use by the International Atomic Energy Agency (IAEA) are met. The scientific expertise at GPI is providing breakthroughs in the realm of motion detection for surveillance. Aquila`s contribution to the project focuses on the integration of authenticated digital camera technology for front-end detection. This project illustrates how the application of technology can increase efficiency and reliability of remote monitoring, as well as the timely detection of Safeguards-significant events.

  19. Non-intrusive detection of methanol in gas phase using infrared degenerate four-wave mixing

    NASA Astrophysics Data System (ADS)

    Zhou, J.; Sahlberg, A. L.; Nilsson, H.; Lundgren, E.; Zetterberg, J.

    2015-11-01

    Sensitive and non-intrusive detection of gas-phase methanol with high spatial and temporal resolution has for the first time been reported using mid-infrared degenerate four-wave mixing (IR-DFWM). IR-DFWM spectra of methanol have been successfully recorded in nitrogen-diluted gas flows at room temperature and at 300 °C, by probing ro-vibrational transitions belonging to the fundamental C-H stretching modes, ν 2 and ν 9, and the O-H stretching mode, ν 1. The detection limit of methanol vapor at room temperature and atmospheric pressure is estimated to be 250 ppm with the present setup. Potential interference from CH4 and CO2 is discussed from recorded IR-DFWM spectra of CH4 and CO2, and it was found that detection of methanol free from CH4 and CO2 interference is possible. These results show the potential of the detection of methanol with IR-DFWM for applications in both combustion and catalytic environments, such as CO2 hydrogenation and CH4 oxidation.

  20. Multi-pattern string matching algorithms comparison for intrusion detection system

    NASA Astrophysics Data System (ADS)

    Hasan, Awsan A.; Rashid, Nur'Aini Abdul; Abdulrazzaq, Atheer A.

    2014-12-01

    Computer networks are developing exponentially and running at high speeds. With the increasing number of Internet users, computers have become the preferred target for complex attacks that require complex analyses to be detected. The Intrusion detection system (IDS) is created and turned into an important part of any modern network to protect the network from attacks. The IDS relies on string matching algorithms to identify network attacks, but these string matching algorithms consume a considerable amount of IDS processing time, thereby slows down the IDS performance. A new algorithm that can overcome the weakness of the IDS needs to be developed. Improving the multi-pattern matching algorithm ensure that an IDS can work properly and the limitations can be overcome. In this paper, we perform a comparison between our three multi-pattern matching algorithms; MP-KR, MPHQS and MPH-BMH with their corresponding original algorithms Kr, QS and BMH respectively. The experiments show that MPH-QS performs best among the proposed algorithms, followed by MPH-BMH, and MP-KR is the slowest. MPH-QS detects a large number of signature patterns in short time compared to other two algorithms. This finding can prove that the multi-pattern matching algorithms are more efficient in high-speed networks.

  1. Non-Intrusive Magneto-Optic Detecting System for Investigations of Air Switching Arcs

    NASA Astrophysics Data System (ADS)

    Zhang, Pengfei; Zhang, Guogang; Dong, Jinlong; Liu, Wanying; Geng, Yingsan

    2014-07-01

    In current investigations of electric arc plasmas, experiments based on modern testing technology play an important role. To enrich the testing methods and contribute to the understanding and grasping of the inherent mechanism of air switching arcs, in this paper, a non-intrusive detecting system is described that combines the magneto-optic imaging (MOI) technique with the solution to inverse electromagnetic problems. The detecting system works in a sequence of main steps as follows: MOI of the variation of the arc flux density over a plane, magnetic field information extracted from the magneto-optic (MO) images, arc current density distribution and spatial pattern reconstruction by inverting the resulting field data. Correspondingly, in the system, an MOI set-up is designed based on the Faraday effect and the polarization properties of light, and an intelligent inversion algorithm is proposed that involves simulated annealing (SA). Experiments were carried out for high current (2 kA RMS) discharge cases in a typical low-voltage switchgear. The results show that the MO detection system possesses the advantages of visualization, high resolution and response, and electrical insulation, which provides a novel diagnostics tool for further studies of the arc.

  2. Characterization of Extremely Lightweight Intrusion Detection (ELIDe) Power Utilization by Varying N-gram and Hash Length

    DTIC Science & Technology

    2015-09-01

    Contents List of Figures iv 1. Introduction 1 2. Setup 2 2.1 Mobile Device 2 2.2 Network 2 2.3 Software Configuration 3 2.4 Determining Power...Figures Fig. 1 Test- network setup ................................................................................... 3 Fig. 2 Power utilization of ELIDe...Signature detection is a very performance-intensive task in regard to network traffic.1 Extremely lightweight intrusion detection (ELIDe) was developed to

  3. FSM-F: Finite State Machine Based Framework for Denial of Service and Intrusion Detection in MANET.

    PubMed

    N Ahmed, Malik; Abdullah, Abdul Hanan; Kaiwartya, Omprakash

    2016-01-01

    Due to the continuous advancements in wireless communication in terms of quality of communication and affordability of the technology, the application area of Mobile Adhoc Networks (MANETs) significantly growing particularly in military and disaster management. Considering the sensitivity of the application areas, security in terms of detection of Denial of Service (DoS) and intrusion has become prime concern in research and development in the area. The security systems suggested in the past has state recognition problem where the system is not able to accurately identify the actual state of the network nodes due to the absence of clear definition of states of the nodes. In this context, this paper proposes a framework based on Finite State Machine (FSM) for denial of service and intrusion detection in MANETs. In particular, an Interruption Detection system for Adhoc On-demand Distance Vector (ID-AODV) protocol is presented based on finite state machine. The packet dropping and sequence number attacks are closely investigated and detection systems for both types of attacks are designed. The major functional modules of ID-AODV includes network monitoring system, finite state machine and attack detection model. Simulations are carried out in network simulator NS-2 to evaluate the performance of the proposed framework. A comparative evaluation of the performance is also performed with the state-of-the-art techniques: RIDAN and AODV. The performance evaluations attest the benefits of proposed framework in terms of providing better security for denial of service and intrusion detection attacks.

  4. Intrusion detection: a novel approach that combines boosting genetic fuzzy classifier and data mining techniques

    NASA Astrophysics Data System (ADS)

    Ozyer, Tansel; Alhajj, Reda; Barker, Ken

    2005-03-01

    This paper proposes an intelligent intrusion detection system (IDS) which is an integrated approach that employs fuzziness and two of the well-known data mining techniques: namely classification and association rule mining. By using these two techniques, we adopted the idea of using an iterative rule learning that extracts out rules from the data set. Our final intention is to predict different behaviors in networked computers. To achieve this, we propose to use a fuzzy rule based genetic classifier. Our approach has two main stages. First, fuzzy association rule mining is applied and a large number of candidate rules are generated for each class. Then the rules pass through pre-screening mechanism in order to reduce the fuzzy rule search space. Candidate rules obtained after pre-screening are used in genetic fuzzy classifier to generate rules for the specified classes. Classes are defined as Normal, PRB-probe, DOS-denial of service, U2R-user to root and R2L- remote to local. Second, an iterative rule learning mechanism is employed for each class to find its fuzzy rules required to classify data each time a fuzzy rule is extracted and included in the system. A Boosting mechanism evaluates the weight of each data item in order to help the rule extraction mechanism focus more on data having relatively higher weight. Finally, extracted fuzzy rules having the corresponding weight values are aggregated on class basis to find the vote of each class label for each data item.

  5. Non-intrusive detection of rotating stall in pump-turbines

    NASA Astrophysics Data System (ADS)

    Botero, F.; Hasmatuchi, V.; Roth, S.; Farhat, M.

    2014-10-01

    When operated far from their optimum conditions, pump-turbines may exhibit strong hydrodynamic instabilities, often called rotating stall, which lead to substantial increase of vibration and risk of mechanical failure. In the present study, we have investigated the flow filed in a model of radial pump-turbine with the help of tuft visualization, wall pressure measurement and structure-borne noise monitoring. As the rotation speed is increased, the machine is brought from its optimum operation to runaway with zero torque on the shaft. The runaway operation is characterized by a significant increase of pressure fluctuation at the rotor-stator interaction frequency. As the speed is further increased, the flow exhibits sub-synchronous instability, which rotates at 70% of the rotation frequency. Tuft visualization clearly shows that, as the instability evolves, the flow in a given distributor channel suddenly stalls and switches to reverse pumping mode in periodic way. We have also investigated the monitoring of the rotating stall with the help of vibration signals. A specific signal processing method, based on amplitude demodulation, was developed. The use of 2 accelerometers allows for the identification of the optimum carrier frequency by computing the cyclic coherence of vibration signals. This non-intrusive method is proved to be efficient in detecting the rotating stall instability and the number of stall cells. We strongly believe that it could be implemented in full scale pump-turbines.

  6. Optimal sensor placement for detecting organophosphate intrusions into water distribution systems.

    PubMed

    Ohar, Ziv; Lahav, Ori; Ostfeld, Avi

    2015-04-15

    Placement of water quality sensors in a water distribution system is a common approach for minimizing contamination intrusion risks. This study incorporates detailed chemistry of organophosphate contaminations into the problem of sensor placement and links quantitative measures of the affected population as a result of such intrusions. The suggested methodology utilizes the stoichiometry and kinetics of the reactions between organophosphate contaminants and free chlorine for predicting the number of affected consumers. This is accomplished through linking a multi-species water quality model and a statistical dose-response model. Three organophosphates (chlorpyrifos, malathion, and parathion) are tested as possible contaminants. Their corresponding by-products were modeled and accounted for in the affected consumers impact calculations. The methodology incorporates a series of randomly generated intrusion events linked to a genetic algorithm for minimizing the contaminants impact through a sensors system. Three example applications are explored for demonstrating the model capabilities through base runs and sensitivity analyses.

  7. Reduction of Motion Artifacts and Improvement of R Peak Detecting Accuracy Using Adjacent Non-Intrusive ECG Sensors

    PubMed Central

    Choi, Minho; Jeong, Jae Jin; Kim, Seung Hun; Kim, Sang Woo

    2016-01-01

    Non-intrusive electrocardiogram (ECG) monitoring has many advantages: easy to measure and apply in daily life. However, motion noise in the measured signal is the major problem of non-intrusive measurement. This paper proposes a method to reduce the noise and to detect the R peaks of ECG in a stable manner in a sitting arrangement using non-intrusive sensors. The method utilizes two capacitive ECG sensors (cECGs) to measure ECG, and another two cECGs located adjacent to the sensors for ECG are added to obtain the information on motion. Then, active noise cancellation technique and the motion information are used to reduce motion noise. To verify the proposed method, ECG was measured indoors and during driving, and the accuracy of the detected R peaks was compared. After applying the method, the sum of sensitivity and positive predictivity increased 8.39% on average and 26.26% maximally in the data. Based on the results, it was confirmed that the motion noise was reduced and that more reliable R peak positions could be obtained by the proposed method. The robustness of the new ECG measurement method will elicit benefits to various health care systems that require noninvasive heart rate or heart rate variability measurements. PMID:27196910

  8. Network Intrusion Detection Based on a General Regression Neural Network Optimized by an Improved Artificial Immune Algorithm

    PubMed Central

    Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

    2015-01-01

    To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data. PMID:25807466

  9. Network intrusion detection based on a general regression neural network optimized by an improved artificial immune algorithm.

    PubMed

    Wu, Jianfa; Peng, Dahao; Li, Zhuping; Zhao, Li; Ling, Huanzhang

    2015-01-01

    To effectively and accurately detect and classify network intrusion data, this paper introduces a general regression neural network (GRNN) based on the artificial immune algorithm with elitist strategies (AIAE). The elitist archive and elitist crossover were combined with the artificial immune algorithm (AIA) to produce the AIAE-GRNN algorithm, with the aim of improving its adaptivity and accuracy. In this paper, the mean square errors (MSEs) were considered the affinity function. The AIAE was used to optimize the smooth factors of the GRNN; then, the optimal smooth factor was solved and substituted into the trained GRNN. Thus, the intrusive data were classified. The paper selected a GRNN that was separately optimized using a genetic algorithm (GA), particle swarm optimization (PSO), and fuzzy C-mean clustering (FCM) to enable a comparison of these approaches. As shown in the results, the AIAE-GRNN achieves a higher classification accuracy than PSO-GRNN, but the running time of AIAE-GRNN is long, which was proved first. FCM and GA-GRNN were eliminated because of their deficiencies in terms of accuracy and convergence. To improve the running speed, the paper adopted principal component analysis (PCA) to reduce the dimensions of the intrusive data. With the reduction in dimensionality, the PCA-AIAE-GRNN decreases in accuracy less and has better convergence than the PCA-PSO-GRNN, and the running speed of the PCA-AIAE-GRNN was relatively improved. The experimental results show that the AIAE-GRNN has a higher robustness and accuracy than the other algorithms considered and can thus be used to classify the intrusive data.

  10. Report on the NS/EP Implications of Intrusion Detection Technology Research and Development

    DTIC Science & Technology

    1997-12-01

    component&ignaling System 7 ( SS7 ), Signal Transfer Points (STPs), and Synchronous Optical Network (SONET)-that if attacked or exploited could...potential use of electronic intrusion techniques to exploit , degrade, or deny service to key information systems. As a result of considering new terms of...As other critical infrastructures seek to exploit information technologies and migrate to more open systems, their control networks may be similarly

  11. Host-Based Multivariate Statistical Computer Operating Process Anomaly Intrusion Detection System (PAIDS)

    DTIC Science & Technology

    2009-03-01

    Jeffrey W. Humphries , Lt Col, PhD, USAF (Reader) Date iv AFIT/GOR/ENS/09-15 Abstract Most intrusion...Linear Discriminant Analysis (LDA) developed by Sir Ronald A. Fisher, in The Use of Multiple Measurements in Taxonomic Problems (1936) finds a...Agency. National Institue of Standards and Technology. Merkle, L. D., Carlisle, M. C., Humphries , J. W., & Lopez, D. W. (2002). EA-Based Approach for

  12. Intelligent detection and identification in fiber-optical perimeter intrusion monitoring system based on the FBG sensor network

    NASA Astrophysics Data System (ADS)

    Wu, Huijuan; Qian, Ya; Zhang, Wei; Li, Hanyu; Xie, Xin

    2015-12-01

    A real-time intelligent fiber-optic perimeter intrusion detection system (PIDS) based on the fiber Bragg grating (FBG) sensor network is presented in this paper. To distinguish the effects of different intrusion events, a novel real-time behavior impact classification method is proposed based on the essential statistical characteristics of signal's profile in the time domain. The features are extracted by the principal component analysis (PCA), which are then used to identify the event with a K-nearest neighbor classifier. Simulation and field tests are both carried out to validate its effectiveness. The average identification rate (IR) for five sample signals in the simulation test is as high as 96.67%, and the recognition rate for eight typical signals in the field test can also be achieved up to 96.52%, which includes both the fence-mounted and the ground-buried sensing signals. Besides, critically high detection rate (DR) and low false alarm rate (FAR) can be simultaneously obtained based on the autocorrelation characteristics analysis and a hierarchical detection and identification flow.

  13. Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems

    PubMed Central

    Laftah Al-Yaseen, Wathiq; Ali Othman, Zulaiha; Ahmad Nazri, Mohd Zakree

    2015-01-01

    Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy. PMID:26161437

  14. Agent-based forward analysis

    SciTech Connect

    Kerekes, Ryan A.; Jiao, Yu; Shankar, Mallikarjun; Potok, Thomas E.; Lusk, Rick M.

    2008-01-01

    We propose software agent-based "forward analysis" for efficient information retrieval in a network of sensing devices. In our approach, processing is pushed to the data at the edge of the network via intelligent software agents rather than pulling data to a central facility for processing. The agents are deployed with a specific query and perform varying levels of analysis of the data, communicating with each other and sending only relevant information back across the network. We demonstrate our concept in the context of face recognition using a wireless test bed comprised of PDA cell phones and laptops. We show that agent-based forward analysis can provide a significant increase in retrieval speed while decreasing bandwidth usage and information overload at the central facility. n

  15. Reactive and multiphase modelling for the identification of monitoring parameters to detect CO2 intrusion into freshwater aquifers

    NASA Astrophysics Data System (ADS)

    Fahrner, S.; Schaefer, D.; Wiegers, C.; Köber, R.; Dahmke, A.

    2011-12-01

    A monitoring at geological CO2 storage sites has to meet environmental, regulative, financial and public demands and thus has to enable the detection of CO2 leakages. Current monitoring concepts for the detection of CO2 intrusion into freshwater aquifers located above saline storage formations in course of leakage events lack the identification of monitoring parameters. Their response to CO2 intrusion still has to be enlightened. Scenario simulations of CO2 intrusion in virtual synthetic aquifers are performed using the simulators PhreeqC and TOUGH2 to reveal relevant CO2-water-mineral interactions and multiphase behaviour on potential monitoring parameters. The focus is set on pH, total dissolved inorganic carbon (TIC) and the hydroelectric conductivity (EC). The study aims at identifying at which conditions the parameters react rapidly, durable and in a measurable degree. The depth of the aquifer, the mineralogy, the intrusion rates, the sorption specification and capacities, and groundwater flow velocities are varied in the course of the scenario modelling. All three parameters have been found suited in most scenarios. However, in case of a lack of calcite combined with low saturation of the water with respect to CO2 and shallow conditions, changes are close to the measurement resolution. Predicted changes in EC result from the interplay between carbonic acid production and its dissociation, and pH buffering by mineral dissolution. The formation of a discrete gas phase in cases of full saturation of the groundwater in confined aquifers illustrates the potential bipartite resistivity response: An increased hydroelectric conductivity at locations with dissolved CO2, and a high resistivity where the gas phase dominates the pore volume occupation. Increased hydrostatic pressure with depth and enhanced groundwater flow velocities enforce gas dissolution and diminish the formation of a discrete gas phase. Based on the results, a monitoring strategy is proposed which

  16. A system for the non-intrusive detection of damage in underground power cables: Damage modeling and sensor system design

    NASA Astrophysics Data System (ADS)

    Gorgen, Marvin Alexander

    A system for non-intrusive sensing of underground power cable impedance is presented. The impedance sensor is used for the detection of damage to underground power cables. The system is capable of taking measurements without the need to interrupt power service. To isolate the impedance measurement from the effects of customer loading, a blocking unit is proposed which presents an open circuit to the impedance sensor in the transmission line at the point where the blocker is clamped onto the cable. Both of the proposed devices are prototyped and evaluated. The impedance sensor is demonstrated to be capable of accurate impedance measurements within a 2% error over a range from 50 to 1000 Ohms. The blocker is demonstrated to provide approximately 30 dB of attenuation over the designed ranged of measurement frequencies. The system can detect impedance changes resulting from corrosion or damage in underground power cables.

  17. A choline oxidase amperometric bioassay for the detection of mustard agents based on screen-printed electrodes modified with Prussian Blue nanoparticles.

    PubMed

    Arduini, Fabiana; Scognamiglio, Viviana; Covaia, Corrado; Amine, Aziz; Moscone, Danila; Palleschi, Giuseppe

    2015-02-13

    In this work a novel bioassay for mustard agent detection was proposed. The bioassay is based on the capability of these compounds to inhibit the enzyme choline oxidase. The enzymatic activity, which is correlated to the mustard agents, was electrochemically monitored measuring the enzymatic product, hydrogen peroxide, by means of a screen-printed electrode modified with Prussian Blue nanoparticles. Prussian Blue nanoparticles are able to electrocatalyse the hydrogen peroxide concentration reduction at low applied potential (-50 mV vs. Ag/AgCl), thus allowing the detection of the mustard agents with no electrochemical interferences. The suitability of this novel bioassay was tested with the nitrogen mustard simulant bis(2-chloroethyl)amine and the sulfur mustard simulants 2-chloroethyl ethyl sulfide and 2-chloroethyl phenyl sulfide. The bioassay proposed in this work allowed the detection of mustard agent simulants with good sensitivity and fast response, which are excellent premises for the development of a miniaturised sensor well suited for an alarm system in case of terrorist attacks.

  18. Vapor Intrusion

    EPA Pesticide Factsheets

    Vapor intrusion occurs when there is a migration of volatile chemicals from contaminated groundwater or soil into an overlying building. Volatile chemicals can emit vapors that may migrate through subsurface soils and into indoor air spaces.

  19. Non-intrusive tunable resonant microwave cavity for optical detected magnetic resonance of NV centres in nanodiamonds

    NASA Astrophysics Data System (ADS)

    Le Floch, Jean-Michel; Bradac, Carlo; Volz, Thomas; Tobar, Michael E.; Castelletto, Stefania

    2013-12-01

    Optically detected magnetic resonance (ODMR) in nanodiamond nitrogen-vacancy (NV) centres is usually achieved by applying a microwave field delivered by micron-size wires, strips or antennas directly positioned in very close proximity (~ μm) of the nanodiamond crystals. The microwave field couples evanescently with the ground state spin transition of the NV centre (2.87 GHz at zero magnetic field), which results in a reduction of the centre photoluminescence. We propose an alternative approach based on the construction of a dielectric resonator. We show that such a resonator allows for the efficient detection of NV spins in nanodiamonds without the constraints associated to the laborious positioning of the microwave antenna next to the nanodiamonds, providing therefore improved flexibility. The resonator is based on a tunable Transverse Electric Mode in a dielectric-loaded cavity, and we demonstrate that the resonator can detect single NV centre spins in nanodiamonds using less microwave power than alternative techniques in a non-intrusive manner. This method can achieve higher precision measurement of ODMR of paramagnetic defects spin transition in the micro to millimetre-wave frequency domain. Our approach would permit the tracking of NV centres in biological solutions rather than simply on the surface, which is desirable in light of the recently proposed applications of using nanodiamonds containing NV centres for spin labelling in biological systems with single spin and single particle resolution.

  20. iSSH v. Auditd: Intrusion Detection in High Performance Computing

    SciTech Connect

    Karns, David M.; Protin, Kathryn S.; Wolf, Justin G.

    2012-07-30

    The goal is to provide insight into intrusions in high performance computing, focusing on tracking intruders motions through the system. The current tools, such as pattern matching, do not provide sufficient tracking capabilities. We tested two tools: an instrumented version of SSH (iSSH) and Linux Auditing Framework (Auditd). First discussed is Instrumented Secure Shell (iSSH): a version of SSH developed at Lawrence Berkeley National Laboratory. The goal is to audit user activity within a computer system to increase security. Capabilities are: Keystroke logging, Records user names and authentication information, and Catching suspicious remote and local commands. Strengths for iSSH are: (1) Good for keystroke logging, making it easier to track malicious users by catching suspicious commands; (2) Works with Bro to send alerts; could be configured to send pages to systems administrators; and (3) Creates visibility into SSH sessions. Weaknesses are: (1) Relatively new, so not very well documented; and (2) No capabilities to see if files have been edited, moved, or copied within the system. Second we discuss Auditd, the user component of the Linux Auditing System. It creates logs of user behavior, and monitors systems calls and file accesses. Its goal is to improve system security by keeping track of users actions within the system. Strenghts of Auditd are: (1) Very thorough logs; (2) Wider variety of tracking abilities than iSSH; and (3) Older, so better documented. Weaknesses are: (1) Logs record everything, not just malicious behavior; (2) The size of the logs can lead to overflowing directories; and (3) This level of logging leads to a lot of false alarms. Auditd is better documented than iSSH, which would help administrators during set up and troubleshooting. iSSH has a cleaner notification system, but the logs are not as detailed as Auditd. From our performance testing: (1) File transfer speed using SCP is increased when using iSSH; and (2) Network benchmarks

  1. Using Hybrid Algorithm to Improve Intrusion Detection in Multi Layer Feed Forward Neural Networks

    ERIC Educational Resources Information Center

    Ray, Loye Lynn

    2014-01-01

    The need for detecting malicious behavior on a computer networks continued to be important to maintaining a safe and secure environment. The purpose of this study was to determine the relationship of multilayer feed forward neural network architecture to the ability of detecting abnormal behavior in networks. This involved building, training, and…

  2. Future Volcanism at Yucca Mountain - Statistical Insights from the Non-Detection of Basalt Intrusions in the Potential Repository

    NASA Astrophysics Data System (ADS)

    Coleman, N.; Abramson, L.

    2004-05-01

    Yucca Mt. (YM) is a potential repository site for high-level radioactive waste and spent fuel. One issue is the potential for future igneous activity to intersect the repository. If the event probability is <1E-8/yr, it need not be considered in licensing. Plio-Quaternary volcanos and older basalts occur near YM. Connor et al (JGR, 2000) estimate a probability of 1E-8/yr to 1E-7/yr for a basaltic dike to intersect the potential repository. Based on aeromagnetic data, Hill and Stamatakos (CNWRA, 2002) propose that additional volcanos may lie buried in nearby basins. They suggest if these volcanos are part of temporal-clustered volcanic activity, the probability of an intrusion may be as high as 1E-6/yr. We examine whether recurrence probabilities >2E-7/yr are realistic given that no dikes have been found in or above the 1.3E7 yr-old potential repository block. For 2E-7/yr (or 1E-6/yr), the expected number of penetrating dikes is 2.6 (respectively, 13), and the probability of at least one penetration is 0.93 (0.999). These results are not consistent with the exploration evidence. YM is one of the most intensively studied places on Earth. Over 20 yrs of studies have included surface and subsurface mapping, geophysical surveys, construction of 10+ km of tunnels in the mountain, drilling of many boreholes, and construction of many pits (DOE, Site Recommendation, 2002). It seems unlikely that multiple dikes could exist within the proposed repository footprint and escape detection. A dike complex dated 11.7 Ma (Smith et al, UNLV, 1997) or 10 Ma (Carr and Parrish, 1985) does exist NW of YM and west of the main Solitario Canyon Fault. These basalts intruded the Tiva Canyon Tuff (12.7 Ma) in an epoch of caldera-forming pyroclastic eruptions that ended millions of yrs ago. We would conclude that basaltic volcanism related to Miocene silicic volcanism may also have ended. Given the nondetection of dikes in the potential repository, we can use a Poisson model to estimate an

  3. Cold Regions Performance of Optical-Fiber and Pulsed Near-Infrared Intrusion Detection Systems

    DTIC Science & Technology

    1994-05-01

    8 Doc 1992 were a direct consequence of (29 Jun). flu P011)6 reliably detected a Fperonr cross- the gravel layer being harri -furozn Once the ice ing...was the poter - FOLDS alarms is wind-induced motion of the ply- tial for twice as many alarms to occur as were re- wood panel to which the enclosure

  4. Using Relational Schemata in a Computer Immune System to Detect Multiple-Packet Network Intrusions

    DTIC Science & Technology

    2002-03-01

    used to perform portscans on between one and ten computers using SYN scanning, FIN scanning, and UDP scanning of victim machines. Both sequential and...for Computing Machinery, 1997. [Stan00] Staniford, Stuart, et al. “Practical Automated Detection of Stealthy Portscans .” Proceedings of the 7th ACM

  5. Network Intrusion Detection and Visualization using Aggregations in a Cyber Security Data Warehouse

    SciTech Connect

    Czejdo, Bogdan; Ferragut, Erik M; Goodall, John R; Laska, Jason A

    2012-01-01

    The challenge of achieving situational understanding is a limiting factor in effective, timely, and adaptive cyber-security analysis. Anomaly detection fills a critical role in network assessment and trend analysis, both of which underlie the establishment of comprehensive situational understanding. To that end, we propose a cyber security data warehouse implemented as a hierarchical graph of aggregations that captures anomalies at multiple scales. Each node of our pro-posed graph is a summarization table of cyber event aggregations, and the edges are aggregation operators. The cyber security data warehouse enables domain experts to quickly traverse a multi-scale aggregation space systematically. We describe the architecture of a test bed system and a summary of results on the IEEE VAST 2012 Cyber Forensics data.

  6. An agent based model of genotype editing

    SciTech Connect

    Rocha, L. M.; Huang, C. F.

    2004-01-01

    This paper presents our investigation on an agent-based model of Genotype Editing. This model is based on several characteristics that are gleaned from the RNA editing system as observed in several organisms. The incorporation of editing mechanisms in an evolutionary agent-based model provides a means for evolving agents with heterogenous post-transcriptional processes. The study of this agent-based genotype-editing model has shed some light into the evolutionary implications of RNA editing as well as established an advantageous evolutionary computation algorithm for machine learning. We expect that our proposed model may both facilitate determining the evolutionary role of RNA editing in biology, and advance the current state of research in agent-based optimization.

  7. Subsurface Intrusion Detection System

    DTIC Science & Technology

    2014-02-25

    vibrations with a first sensor positioned at a first depth relative to a surface of the earth to generate a first signal and receiving vibrations...with a second sensor positioned at a second depth relative to the surface of the earth to generate a second signal. The second depth is greater than...to measure vibrations of the earth . The plurality of vibration sensors comprise at least an upper sensor and lower sensor at a location. Each signal

  8. Acoustic emission intrusion detector

    DOEpatents

    Carver, Donald W.; Whittaker, Jerry W.

    1980-01-01

    An intrusion detector is provided for detecting a forcible entry into a secured structure while minimizing false alarms. The detector uses a piezoelectric crystal transducer to sense acoustic emissions. The transducer output is amplified by a selectable gain amplifier to control the sensitivity. The rectified output of the amplifier is applied to a Schmitt trigger circuit having a preselected threshold level to provide amplitude discrimination. Timing circuitry is provided which is activated by successive pulses from the Schmitt trigger which lie within a selected time frame for frequency discrimination. Detected signals having proper amplitude and frequency trigger an alarm within the first complete cycle time of a detected acoustical disturbance signal.

  9. Superfund Vapor Intrusion

    EPA Pesticide Factsheets

    In addition to basic information about vapor intrusion, the site contains technical and policy documents, tools and other resources to support vapor intrusion environmental investigations and mitigation activities.

  10. Agent Based Modeling Applications for Geosciences

    NASA Astrophysics Data System (ADS)

    Stein, J. S.

    2004-12-01

    Agent-based modeling techniques have successfully been applied to systems in which complex behaviors or outcomes arise from varied interactions between individuals in the system. Each individual interacts with its environment, as well as with other individuals, by following a set of relatively simple rules. Traditionally this "bottom-up" modeling approach has been applied to problems in the fields of economics and sociology, but more recently has been introduced to various disciplines in the geosciences. This technique can help explain the origin of complex processes from a relatively simple set of rules, incorporate large and detailed datasets when they exist, and simulate the effects of extreme events on system-wide behavior. Some of the challenges associated with this modeling method include: significant computational requirements in order to keep track of thousands to millions of agents, methods and strategies of model validation are lacking, as is a formal methodology for evaluating model uncertainty. Challenges specific to the geosciences, include how to define agents that control water, contaminant fluxes, climate forcing and other physical processes and how to link these "geo-agents" into larger agent-based simulations that include social systems such as demographics economics and regulations. Effective management of limited natural resources (such as water, hydrocarbons, or land) requires an understanding of what factors influence the demand for these resources on a regional and temporal scale. Agent-based models can be used to simulate this demand across a variety of sectors under a range of conditions and determine effective and robust management policies and monitoring strategies. The recent focus on the role of biological processes in the geosciences is another example of an area that could benefit from agent-based applications. A typical approach to modeling the effect of biological processes in geologic media has been to represent these processes in

  11. Agent-based modelling in synthetic biology

    PubMed Central

    2016-01-01

    Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions. PMID:27903820

  12. Agent-Based Modeling in Systems Pharmacology.

    PubMed

    Cosgrove, J; Butler, J; Alden, K; Read, M; Kumar, V; Cucurull-Sanchez, L; Timmis, J; Coles, M

    2015-11-01

    Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent-based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM-specific strengths have yielded success in the area of preclinical mechanistic modeling.

  13. Multiscale agent-based consumer market modeling.

    SciTech Connect

    North, M. J.; Macal, C. M.; St. Aubin, J.; Thimmapuram, P.; Bragen, M.; Hahn, J.; Karr, J.; Brigham, N.; Lacy, M. E.; Hampton, D.; Decision and Information Sciences; Procter & Gamble Co.

    2010-05-01

    Consumer markets have been studied in great depth, and many techniques have been used to represent them. These have included regression-based models, logit models, and theoretical market-level models, such as the NBD-Dirichlet approach. Although many important contributions and insights have resulted from studies that relied on these models, there is still a need for a model that could more holistically represent the interdependencies of the decisions made by consumers, retailers, and manufacturers. When the need is for a model that could be used repeatedly over time to support decisions in an industrial setting, it is particularly critical. Although some existing methods can, in principle, represent such complex interdependencies, their capabilities might be outstripped if they had to be used for industrial applications, because of the details this type of modeling requires. However, a complementary method - agent-based modeling - shows promise for addressing these issues. Agent-based models use business-driven rules for individuals (e.g., individual consumer rules for buying items, individual retailer rules for stocking items, or individual firm rules for advertizing items) to determine holistic, system-level outcomes (e.g., to determine if brand X's market share is increasing). We applied agent-based modeling to develop a multi-scale consumer market model. We then conducted calibration, verification, and validation tests of this model. The model was successfully applied by Procter & Gamble to several challenging business problems. In these situations, it directly influenced managerial decision making and produced substantial cost savings.

  14. Assurance in Agent-Based Systems

    SciTech Connect

    Gilliom, Laura R.; Goldsmith, Steven Y.

    1999-05-10

    Our vision of the future of information systems is one that includes engineered collectives of software agents which are situated in an environment over years and which increasingly improve the performance of the overall system of which they are a part. At a minimum, the movement of agent and multi-agent technology into National Security applications, including their use in information assurance, is apparent today. The use of deliberative, autonomous agents in high-consequence/high-security applications will require a commensurate level of protection and confidence in the predictability of system-level behavior. At Sandia National Laboratories, we have defined and are addressing a research agenda that integrates the surety (safety, security, and reliability) into agent-based systems at a deep level. Surety is addressed at multiple levels: The integrity of individual agents must be protected by addressing potential failure modes and vulnerabilities to malevolent threats. Providing for the surety of the collective requires attention to communications surety issues and mechanisms for identifying and working with trusted collaborators. At the highest level, using agent-based collectives within a large-scale distributed system requires the development of principled design methods to deliver the desired emergent performance or surety characteristics. This position paper will outline the research directions underway at Sandia, will discuss relevant work being performed elsewhere, and will report progress to date toward assurance in agent-based systems.

  15. Improving Agent Based Models and Validation through Data Fusion

    PubMed Central

    Laskowski, Marek; Demianyk, Bryan C.P.; Friesen, Marcia R.; McLeod, Robert D.; Mukhi, Shamir N.

    2011-01-01

    This work is contextualized in research in modeling and simulation of infection spread within a community or population, with the objective to provide a public health and policy tool in assessing the dynamics of infection spread and the qualitative impacts of public health interventions. This work uses the integration of real data sources into an Agent Based Model (ABM) to simulate respiratory infection spread within a small municipality. Novelty is derived in that the data sources are not necessarily obvious within ABM infection spread models. The ABM is a spatial-temporal model inclusive of behavioral and interaction patterns between individual agents on a real topography. The agent behaviours (movements and interactions) are fed by census / demographic data, integrated with real data from a telecommunication service provider (cellular records) and person-person contact data obtained via a custom 3G Smartphone application that logs Bluetooth connectivity between devices. Each source provides data of varying type and granularity, thereby enhancing the robustness of the model. The work demonstrates opportunities in data mining and fusion that can be used by policy and decision makers. The data become real-world inputs into individual SIR disease spread models and variants, thereby building credible and non-intrusive models to qualitatively simulate and assess public health interventions at the population level. PMID:23569606

  16. Petroleum Vapor Intrusion

    EPA Pesticide Factsheets

    One type of vapor intrusion is PVI, in which vapors from petroleum hydrocarbons such as gasoline, diesel, or jet fuel enter a building. Intrusion of contaminant vapors into indoor spaces is of concern.

  17. Agent based modeling in tactical wargaming

    NASA Astrophysics Data System (ADS)

    James, Alex; Hanratty, Timothy P.; Tuttle, Daniel C.; Coles, John B.

    2016-05-01

    Army staffs at division, brigade, and battalion levels often plan for contingency operations. As such, analysts consider the impact and potential consequences of actions taken. The Army Military Decision-Making Process (MDMP) dictates identification and evaluation of possible enemy courses of action; however, non-state actors often do not exhibit the same level and consistency of planned actions that the MDMP was originally designed to anticipate. The fourth MDMP step is a particular challenge, wargaming courses of action within the context of complex social-cultural behaviors. Agent-based Modeling (ABM) and its resulting emergent behavior is a potential solution to model terrain in terms of the human domain and improve the results and rigor of the traditional wargaming process.

  18. Validating agent based models through virtual worlds.

    SciTech Connect

    Lakkaraju, Kiran; Whetzel, Jonathan H.; Lee, Jina; Bier, Asmeret Brooke; Cardona-Rivera, Rogelio E.; Bernstein, Jeremy Ray Rhythm

    2014-01-01

    As the US continues its vigilance against distributed, embedded threats, understanding the political and social structure of these groups becomes paramount for predicting and dis- rupting their attacks. Agent-based models (ABMs) serve as a powerful tool to study these groups. While the popularity of social network tools (e.g., Facebook, Twitter) has provided extensive communication data, there is a lack of ne-grained behavioral data with which to inform and validate existing ABMs. Virtual worlds, in particular massively multiplayer online games (MMOG), where large numbers of people interact within a complex environ- ment for long periods of time provide an alternative source of data. These environments provide a rich social environment where players engage in a variety of activities observed between real-world groups: collaborating and/or competing with other groups, conducting battles for scarce resources, and trading in a market economy. Strategies employed by player groups surprisingly re ect those seen in present-day con icts, where players use diplomacy or espionage as their means for accomplishing their goals. In this project, we propose to address the need for ne-grained behavioral data by acquiring and analyzing game data a commercial MMOG, referred to within this report as Game X. The goals of this research were: (1) devising toolsets for analyzing virtual world data to better inform the rules that govern a social ABM and (2) exploring how virtual worlds could serve as a source of data to validate ABMs established for analogous real-world phenomena. During this research, we studied certain patterns of group behavior to compliment social modeling e orts where a signi cant lack of detailed examples of observed phenomena exists. This report outlines our work examining group behaviors that underly what we have termed the Expression-To-Action (E2A) problem: determining the changes in social contact that lead individuals/groups to engage in a particular behavior

  19. SUPPLEMENT TO EPA COMPENDIUM METHOD TO-15 - REDUCTION OF METHOD DETECTION LIMITS TO MEET VAPOR INTRUSION MONITORING NEEDS

    EPA Science Inventory

    The Supplement to EPA Compendium Method TO-15 provides guidance for reducing the method detection limit (MDL) for the compound 1,1- dichloroethene (1,1-DCE) and for other volatile organic compounds (VOCs) from 0.5 ppbv, as cited in Method TO-15, to much lower concentrations. R...

  20. SUPPLEMENT TO EPA COMPENDIUM METHOD TO-15 - REDUCTION OF METHOD DETECTION LIMITS TO MEET VAPOR INTRUSION MONITORING NEEDS

    EPA Science Inventory

    The Supplement to EPA Compendium Method TO-15 provides guidance for reducing the method detection limit (MDL) for the compound 1,1-dichloroethene (1,1-DCE) and for other volatile organic compounds (VOCs) from 0.5 parts per billion by volume (ppbv), as cited in Method TO-15, to ...

  1. Agent-based modeling in ecological economics.

    PubMed

    Heckbert, Scott; Baynes, Tim; Reeson, Andrew

    2010-01-01

    Interconnected social and environmental systems are the domain of ecological economics, and models can be used to explore feedbacks and adaptations inherent in these systems. Agent-based modeling (ABM) represents autonomous entities, each with dynamic behavior and heterogeneous characteristics. Agents interact with each other and their environment, resulting in emergent outcomes at the macroscale that can be used to quantitatively analyze complex systems. ABM is contributing to research questions in ecological economics in the areas of natural resource management and land-use change, urban systems modeling, market dynamics, changes in consumer attitudes, innovation, and diffusion of technology and management practices, commons dilemmas and self-governance, and psychological aspects to human decision making and behavior change. Frontiers for ABM research in ecological economics involve advancing the empirical calibration and validation of models through mixed methods, including surveys, interviews, participatory modeling, and, notably, experimental economics to test specific decision-making hypotheses. Linking ABM with other modeling techniques at the level of emergent properties will further advance efforts to understand dynamics of social-environmental systems.

  2. Agent Based Model of Livestock Movements

    NASA Astrophysics Data System (ADS)

    Miron, D. J.; Emelyanova, I. V.; Donald, G. E.; Garner, G. M.

    The modelling of livestock movements within Australia is of national importance for the purposes of the management and control of exotic disease spread, infrastructure development and the economic forecasting of livestock markets. In this paper an agent based model for the forecasting of livestock movements is presented. This models livestock movements from farm to farm through a saleyard. The decision of farmers to sell or buy cattle is often complex and involves many factors such as climate forecast, commodity prices, the type of farm enterprise, the number of animals available and associated off-shore effects. In this model the farm agent's intelligence is implemented using a fuzzy decision tree that utilises two of these factors. These two factors are the livestock price fetched at the last sale and the number of stock on the farm. On each iteration of the model farms choose either to buy, sell or abstain from the market thus creating an artificial supply and demand. The buyers and sellers then congregate at the saleyard where livestock are auctioned using a second price sealed bid. The price time series output by the model exhibits properties similar to those found in real livestock markets.

  3. Lunar igneous intrusions.

    PubMed

    El-Baz, F

    1970-01-02

    Photographs taken from Apollo 10 and 11 reveal a number of probable igneous intrusions, including three probable dikes that crosscut the wall and floor of an unnamed 75-kilometer crater on the lunar farside. These intrusions are distinguished by their setting, textures, structures, and brightness relative to the surrounding materials. Recognition of these probable igneous intrusions in the lunar highlands slupports the indications of the heterogeneity of lunar materials and the plausibility of intrusive igneous activity, in addition to extrusive volcanism, on the moon.

  4. Real-Time, Non-Intrusive Detection of Liquid Nitrogen in Liquid Oxygen at High Pressure and High Flow

    NASA Technical Reports Server (NTRS)

    Singh, Jagdish P.; Yueh, Fang-Yu; Kalluru, Rajamohan R.; Harrison, Louie

    2012-01-01

    An integrated fiber-optic Raman sensor has been designed for real-time, nonintrusive detection of liquid nitrogen in liquid oxygen (LOX) at high pressures and high flow rates in order to monitor the quality of LOX used during rocket engine ground testing. The integrated sensor employs a high-power (3-W) Melles Griot diode-pumped, solid-state (DPSS), frequency-doubled Nd:YAG 532- nm laser; a modified Raman probe that has built-in Raman signal filter optics; two high-resolution spectrometers; and photomultiplier tubes (PMTs) with selected bandpass filters to collect both N2 and O2 Raman signals. The PMT detection units are interfaced with National Instruments Lab- VIEW for fast data acquisition. Studies of sensor performance with different detection systems (i.e., spectrometer and PMT) were carried out. The concentration ratio of N2 and O2 can be inferred by comparing the intensities of the N2 and O2 Raman signals. The final system was fabricated to measure N2 and O2 gas mixtures as well as mixtures of liquid N2 and LOX

  5. Agent-based models of financial markets

    NASA Astrophysics Data System (ADS)

    Samanidou, E.; Zschischang, E.; Stauffer, D.; Lux, T.

    2007-03-01

    This review deals with several microscopic ('agent-based') models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, Cont-Bouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the Donangelo-Sneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics (e.g. moving from the notion of fat tails to the more concrete one of a power law with index around three), it became clear that financial market dynamics give rise to some kind of universal scaling law. Showing similarities with scaling laws for other systems with many interacting sub-units, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic has been pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavours of multi-agent models that have appeared up to now, we discuss the Cont

  6. An Active Learning Exercise for Introducing Agent-Based Modeling

    ERIC Educational Resources Information Center

    Pinder, Jonathan P.

    2013-01-01

    Recent developments in agent-based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent-based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent-based…

  7. An Agent-Based Cockpit Task Management System

    NASA Technical Reports Server (NTRS)

    Funk, Ken

    1997-01-01

    An agent-based program to facilitate Cockpit Task Management (CTM) in commercial transport aircraft is developed and evaluated. The agent-based program called the AgendaManager (AMgr) is described and evaluated in a part-task simulator study using airline pilots.

  8. Extremely Lightweight Intrusion Detection (ELIDe)

    DTIC Science & Technology

    2013-12-01

    conventional computing platform (Dell Inspiron 15N laptop running Mint Maya as the operating system, dual-core Core i5 CPU, 8 GB RAM ), Snort exhibited a peak... RAM usage of approximately 1.2 GB as measured by the Massif memory profiler within the Valgrind suite (3). While this is very reasonable for...equipped with only 512 MB of RAM and would, therefore, be overwhelmed by the runtime demands of Snort. Consequently, any packet analysis solution in the

  9. Computer Intrusions and Attacks.

    ERIC Educational Resources Information Center

    Falk, Howard

    1999-01-01

    Examines some frequently encountered unsolicited computer intrusions, including computer viruses, worms, Java applications, trojan horses or vandals, e-mail spamming, hoaxes, and cookies. Also discusses virus-protection software, both for networks and for individual users. (LRW)

  10. Agent-Based Target Detection in 3-Dimensional Environments

    DTIC Science & Technology

    2005-03-01

    thesis along this line is discussed in Chapter 11. 2 D. THESIS ORGANIZATION The remainder of this thesis is organized into 4 chapters as follows : 1...Vertex and fragment shader programs are used to make comparisons of the stored images. All the renders and calculations are performed on the Graphics...not implemented in the demonstration program. Once the two images are generated they are further processed as follows : 1. The Line of Sight Check At

  11. Agent-Based Automated Algorithm Generator

    DTIC Science & Technology

    2010-01-12

    Detection and Isolation Agent (FDIA), Prognostic Agent (PA), Fusion Agent (FA), and Maintenance Mining Agent (MMA). FDI agents perform diagnostics...manner and loosely coupled). The library of D/P algorithms will be hosted in server-side agents, consisting of four types of major agents: Fault

  12. Computationally Efficient Neural Network Intrusion Security Awareness

    SciTech Connect

    Todd Vollmer; Milos Manic

    2009-08-01

    An enhanced version of an algorithm to provide anomaly based intrusion detection alerts for cyber security state awareness is detailed. A unique aspect is the training of an error back-propagation neural network with intrusion detection rule features to provide a recognition basis. Network packet details are subsequently provided to the trained network to produce a classification. This leverages rule knowledge sets to produce classifications for anomaly based systems. Several test cases executed on ICMP protocol revealed a 60% identification rate of true positives. This rate matched the previous work, but 70% less memory was used and the run time was reduced to less than 1 second from 37 seconds.

  13. Agent-Based Modeling of Growth Processes

    ERIC Educational Resources Information Center

    Abraham, Ralph

    2014-01-01

    Growth processes abound in nature, and are frequently the target of modeling exercises in the sciences. In this article we illustrate an agent-based approach to modeling, in the case of a single example from the social sciences: bullying.

  14. AGENT-BASED MODELS IN EMPIRICAL SOCIAL RESEARCH*

    PubMed Central

    Bruch, Elizabeth; Atwell, Jon

    2014-01-01

    Agent-based modeling has become increasingly popular in recent years, but there is still no codified set of recommendations or practices for how to use these models within a program of empirical research. This article provides ideas and practical guidelines drawn from sociology, biology, computer science, epidemiology, and statistics. We first discuss the motivations for using agent-based models in both basic science and policy-oriented social research. Next, we provide an overview of methods and strategies for incorporating data on behavior and populations into agent-based models, and review techniques for validating and testing the sensitivity of agent-based models. We close with suggested directions for future research. PMID:25983351

  15. Agent-based modeling to simulate the dengue spread

    NASA Astrophysics Data System (ADS)

    Deng, Chengbin; Tao, Haiyan; Ye, Zhiwei

    2008-10-01

    In this paper, we introduce a novel method ABM in simulating the unique process for the dengue spread. Dengue is an acute infectious disease with a long history of over 200 years. Unlike the diseases that can be transmitted directly from person to person, dengue spreads through a must vector of mosquitoes. There is still no any special effective medicine and vaccine for dengue up till now. The best way to prevent dengue spread is to take precautions beforehand. Thus, it is crucial to detect and study the dynamic process of dengue spread that closely relates to human-environment interactions where Agent-Based Modeling (ABM) effectively works. The model attempts to simulate the dengue spread in a more realistic way in the bottom-up way, and to overcome the limitation of ABM, namely overlooking the influence of geographic and environmental factors. Considering the influence of environment, Aedes aegypti ecology and other epidemiological characteristics of dengue spread, ABM can be regarded as a useful way to simulate the whole process so as to disclose the essence of the evolution of dengue spread.

  16. A Large Scale, High Resolution Agent-Based Insurgency Model

    DTIC Science & Technology

    2013-09-30

    for understanding and analyzing human behavior in a civil violence paradigm. This model employed two types of agents: an agent that can become...cognitions and behaviors. Unlike previous agent-based models of civil violence , this work includes the use of a hidden Markov process for simulating...these models can portray real insurgent environments. Keywords simulation · agent based model · insurgency · civil violence · graphics processing

  17. Enhanced situational awareness in the maritime domain: an agent-based approach for situation management

    NASA Astrophysics Data System (ADS)

    Brax, Christoffer; Niklasson, Lars

    2009-05-01

    Maritime Domain Awareness is important for both civilian and military applications. An important part of MDA is detection of unusual vessel activities such as piracy, smuggling, poaching, collisions, etc. Today's interconnected sensorsystems provide us with huge amounts of information over large geographical areas which can make the operators reach their cognitive capacity and start to miss important events. We propose and agent-based situation management system that automatically analyse sensor information to detect unusual activity and anomalies. The system combines knowledge-based detection with data-driven anomaly detection. The system is evaluated using information from both radar and AIS sensors.

  18. A hybrid agent-based approach for modeling microbiological systems.

    PubMed

    Guo, Zaiyi; Sloot, Peter M A; Tay, Joc Cing

    2008-11-21

    Models for systems biology commonly adopt Differential Equations or Agent-Based modeling approaches for simulating the processes as a whole. Models based on differential equations presuppose phenomenological intracellular behavioral mechanisms, while models based on Multi-Agent approach often use directly translated, and quantitatively less precise if-then logical rule constructs. We propose an extendible systems model based on a hybrid agent-based approach where biological cells are modeled as individuals (agents) while molecules are represented by quantities. This hybridization in entity representation entails a combined modeling strategy with agent-based behavioral rules and differential equations, thereby balancing the requirements of extendible model granularity with computational tractability. We demonstrate the efficacy of this approach with models of chemotaxis involving an assay of 10(3) cells and 1.2x10(6) molecules. The model produces cell migration patterns that are comparable to laboratory observations.

  19. Diversity and Community: The Role of Agent-Based Modeling.

    PubMed

    Stivala, Alex

    2017-03-13

    Community psychology involves several dialectics between potentially opposing ideals, such as theory and practice, rights and needs, and respect for human diversity and sense of community. Some recent papers in the American Journal of Community Psychology have examined the diversity-community dialectic, some with the aid of agent-based modeling and concepts from network science. This paper further elucidates these concepts and suggests that research in community psychology can benefit from a useful dialectic between agent-based modeling and the real-world concerns of community psychology.

  20. An Agent-Based Interface to Terrestrial Ecological Forecasting

    NASA Technical Reports Server (NTRS)

    Golden, Keith; Nemani, Ramakrishna; Pang, Wan-Lin; Votava, Petr; Etzioni, Oren

    2004-01-01

    This paper describes a flexible agent-based ecological forecasting system that combines multiple distributed data sources and models to provide near-real-time answers to questions about the state of the Earth system We build on novel techniques in automated constraint-based planning and natural language interfaces to automatically generate data products based on descriptions of the desired data products.

  1. The Uniframe Mobile Agent Based Resource Discovery Service

    DTIC Science & Technology

    2004-06-28

    ABSTRACT see report 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18 . NUMBER OF PAGES 251...Prescribed by ANSI Std Z39- 18 THE UNIFRAME MOBILE AGENT BASED RESOURCE DISCOVERY SERVICE A Technical Report Report Number TR-CIS... 18 2.1.2.3 The UniFrame System Level Generative Programming Framework (USGPF

  2. An Agent-based Framework for Web Query Answering.

    ERIC Educational Resources Information Center

    Wang, Huaiqing; Liao, Stephen; Liao, Lejian

    2000-01-01

    Discusses discrepancies between user queries on the Web and the answers provided by information sources; proposes an agent-based framework for Web mining tasks; introduces an object-oriented deductive data model and a flexible query language; and presents a cooperative mechanism for query answering. (Author/LRW)

  3. Agent-based services for B2B electronic commerce

    NASA Astrophysics Data System (ADS)

    Fong, Elizabeth; Ivezic, Nenad; Rhodes, Tom; Peng, Yun

    2000-12-01

    The potential of agent-based systems has not been realized yet, in part, because of the lack of understanding of how the agent technology supports industrial needs and emerging standards. The area of business-to-business electronic commerce (b2b e-commerce) is one of the most rapidly developing sectors of industry with huge impact on manufacturing practices. In this paper, we investigate the current state of agent technology and the feasibility of applying agent-based computing to b2b e-commerce in the circuit board manufacturing sector. We identify critical tasks and opportunities in the b2b e-commerce area where agent-based services can best be deployed. We describe an implemented agent-based prototype system to facilitate the bidding process for printed circuit board manufacturing and assembly. These activities are taking place within the Internet Commerce for Manufacturing (ICM) project, the NIST- sponsored project working with industry to create an environment where small manufacturers of mechanical and electronic components may participate competitively in virtual enterprises that manufacture printed circuit assemblies.

  4. Simulating cancer growth with multiscale agent-based modeling.

    PubMed

    Wang, Zhihui; Butner, Joseph D; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S

    2015-02-01

    There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models.

  5. Modeling civil violence: An agent-based computational approach

    PubMed Central

    Epstein, Joshua M.

    2002-01-01

    This article presents an agent-based computational model of civil violence. Two variants of the civil violence model are presented. In the first a central authority seeks to suppress decentralized rebellion. In the second a central authority seeks to suppress communal violence between two warring ethnic groups. PMID:11997450

  6. Agent-based Approaches to Dynamic Team Simulation

    DTIC Science & Technology

    2008-09-01

    behavior. The second section reviews agent-based models of teamwork describing work involving both teamwork approaches to design of multiagent systems...there is less direct evidence for teams. Hough (1992), for example, found that ratings on conscientiousness, emotional stability, and agreeableness...Peeters, Rutte, Tuijl, and Reymen (2006) who found agreeableness and emotional stability positively related to satisfaction with the team make

  7. Solution of partial differential equations by agent-based simulation

    NASA Astrophysics Data System (ADS)

    Szilagyi, Miklos N.

    2014-01-01

    The purpose of this short note is to demonstrate that partial differential equations can be quickly solved by agent-based simulation with high accuracy. There is no need for the solution of large systems of algebraic equations. This method is especially useful for quick determination of potential distributions and demonstration purposes in teaching electromagnetism.

  8. Adding ecosystem function to agent-based land use models

    PubMed Central

    Yadav, V.; Del Grosso, S.J.; Parton, W.J.; Malanson, G.P.

    2015-01-01

    The objective of this paper is to examine issues in the inclusion of simulations of ecosystem functions in agent-based models of land use decision-making. The reasons for incorporating these simulations include local interests in land fertility and global interests in carbon sequestration. Biogeochemical models are needed in order to calculate such fluxes. The Century model is described with particular attention to the land use choices that it can encompass. When Century is applied to a land use problem the combinatorial choices lead to a potentially unmanageable number of simulation runs. Century is also parameter-intensive. Three ways of including Century output in agent-based models, ranging from separately calculated look-up tables to agents running Century within the simulation, are presented. The latter may be most efficient, but it moves the computing costs to where they are most problematic. Concern for computing costs should not be a roadblock. PMID:26191077

  9. Agent-based models in translational systems biology

    PubMed Central

    An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

    2013-01-01

    Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

  10. Investigating biocomplexity through the agent-based paradigm

    PubMed Central

    Kaul, Himanshu

    2015-01-01

    Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines—or agents—to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex. PMID:24227161

  11. Agent-based Modeling with MATSim for Hazards Evacuation Planning

    NASA Astrophysics Data System (ADS)

    Jones, J. M.; Ng, P.; Henry, K.; Peters, J.; Wood, N. J.

    2015-12-01

    Hazard evacuation planning requires robust modeling tools and techniques, such as least cost distance or agent-based modeling, to gain an understanding of a community's potential to reach safety before event (e.g. tsunami) arrival. Least cost distance modeling provides a static view of the evacuation landscape with an estimate of travel times to safety from each location in the hazard space. With this information, practitioners can assess a community's overall ability for timely evacuation. More information may be needed if evacuee congestion creates bottlenecks in the flow patterns. Dynamic movement patterns are best explored with agent-based models that simulate movement of and interaction between individual agents as evacuees through the hazard space, reacting to potential congestion areas along the evacuation route. The multi-agent transport simulation model MATSim is an agent-based modeling framework that can be applied to hazard evacuation planning. Developed jointly by universities in Switzerland and Germany, MATSim is open-source software written in Java and freely available for modification or enhancement. We successfully used MATSim to illustrate tsunami evacuation challenges in two island communities in California, USA, that are impacted by limited escape routes. However, working with MATSim's data preparation, simulation, and visualization modules in an integrated development environment requires a significant investment of time to develop the software expertise to link the modules and run a simulation. To facilitate our evacuation research, we packaged the MATSim modules into a single application tailored to the needs of the hazards community. By exposing the modeling parameters of interest to researchers in an intuitive user interface and hiding the software complexities, we bring agent-based modeling closer to practitioners and provide access to the powerful visual and analytic information that this modeling can provide.

  12. The fractional volatility model: An agent-based interpretation

    NASA Astrophysics Data System (ADS)

    Vilela Mendes, R.

    2008-06-01

    Based on the criteria of mathematical simplicity and consistency with empirical market data, a model with volatility driven by fractional noise has been constructed which provides a fairly accurate mathematical parametrization of the data. Here, some features of the model are reviewed and extended to account for leverage effects. Using agent-based models, one tries to find which agent strategies and (or) properties of the financial institutions might be responsible for the features of the fractional volatility model.

  13. Cognitive Modeling for Agent-Based Simulation of Child Maltreatment

    NASA Astrophysics Data System (ADS)

    Hu, Xiaolin; Puddy, Richard

    This paper extends previous work to develop cognitive modeling for agent-based simulation of child maltreatment (CM). The developed model is inspired from parental efficacy, parenting stress, and the theory of planned behavior. It provides an explanatory, process-oriented model of CM and incorporates causality relationship and feedback loops from different factors in the social ecology in order for simulating the dynamics of CM. We describe the model and present simulation results to demonstrate the features of this model.

  14. Scalable, distributed data mining using an agent based architecture

    SciTech Connect

    Kargupta, H.; Hamzaoglu, I.; Stafford, B.

    1997-05-01

    Algorithm scalability and the distributed nature of both data and computation deserve serious attention in the context of data mining. This paper presents PADMA (PArallel Data Mining Agents), a parallel agent based system, that makes an effort to address these issues. PADMA contains modules for (1) parallel data accessing operations, (2) parallel hierarchical clustering, and (3) web-based data visualization. This paper describes the general architecture of PADMA and experimental results.

  15. IRA: Intrusion - Reaction - Appats

    DTIC Science & Technology

    2004-11-01

    méthodes d ’attaques Détection d ’intrusion Cas particulier des Canaux Cachés Notion d ’appât (Honey Pot & Honey Net) Protection entre environnements de...aspects suivants : La notion de « Pot de miel » peut s ’étendre d ’un simple leurre (mot de passe constructeur conservé) à des environnement dédié...d’Attaques Logiques .........................................................................7-10 2.3 Environnement Technique étudié

  16. Evolutionary game theory using agent-based methods.

    PubMed

    Adami, Christoph; Schossau, Jory; Hintze, Arend

    2016-12-01

    Evolutionary game theory is a successful mathematical framework geared towards understanding the selective pressures that affect the evolution of the strategies of agents engaged in interactions with potential conflicts. While a mathematical treatment of the costs and benefits of decisions can predict the optimal strategy in simple settings, more realistic settings such as finite populations, non-vanishing mutations rates, stochastic decisions, communication between agents, and spatial interactions, require agent-based methods where each agent is modeled as an individual, carries its own genes that determine its decisions, and where the evolutionary outcome can only be ascertained by evolving the population of agents forward in time. While highlighting standard mathematical results, we compare those to agent-based methods that can go beyond the limitations of equations and simulate the complexity of heterogeneous populations and an ever-changing set of interactors. We conclude that agent-based methods can predict evolutionary outcomes where purely mathematical treatments cannot tread (for example in the weak selection-strong mutation limit), but that mathematics is crucial to validate the computational simulations.

  17. Who's your neighbor? neighbor identification for agent-based modeling.

    SciTech Connect

    Macal, C. M.; Howe, T. R.; Decision and Information Sciences; Univ. of Chicago

    2006-01-01

    Agent-based modeling and simulation, based on the cellular automata paradigm, is an approach to modeling complex systems comprised of interacting autonomous agents. Open questions in agent-based simulation focus on scale-up issues encountered in simulating large numbers of agents. Specifically, how many agents can be included in a workable agent-based simulation? One of the basic tenets of agent-based modeling and simulation is that agents only interact and exchange locally available information with other agents located in their immediate proximity or neighborhood of the space in which the agents are situated. Generally, an agent's set of neighbors changes rapidly as a simulation proceeds through time and as the agents move through space. Depending on the topology defined for agent interactions, proximity may be defined by spatial distance for continuous space, adjacency for grid cells (as in cellular automata), or by connectivity in social networks. Identifying an agent's neighbors is a particularly time-consuming computational task and can dominate the computational effort in a simulation. Two challenges in agent simulation are (1) efficiently representing an agent's neighborhood and the neighbors in it and (2) efficiently identifying an agent's neighbors at any time in the simulation. These problems are addressed differently for different agent interaction topologies. While efficient approaches have been identified for agent neighborhood representation and neighbor identification for agents on a lattice with general neighborhood configurations, other techniques must be used when agents are able to move freely in space. Techniques for the analysis and representation of spatial data are applicable to the agent neighbor identification problem. This paper extends agent neighborhood simulation techniques from the lattice topology to continuous space, specifically R2. Algorithms based on hierarchical (quad trees) or non-hierarchical data structures (grid cells) are

  18. Non-intrusive appliance monitor apparatus

    DOEpatents

    Hart, George W.; Kern, Jr., Edward C.; Schweppe, Fred C.

    1989-08-15

    A non-intrusive monitor of energy consumption of residential appliances is described in which sensors, coupled to the power circuits entering a residence, supply analog voltage and current signals which are converted to digital format and processed to detect changes in certain residential load parameters, i.e., admittance. Cluster analysis techniques are employed to group change measurements into certain categories, and logic is applied to identify individual appliances and the energy consumed by each.

  19. Non-intrusive appliance monitor apparatus

    DOEpatents

    Hart, G.W.; Kern, E.C. Jr.; Schweppe, F.C.

    1989-08-15

    A non-intrusive monitor of energy consumption of residential appliances is described in which sensors, coupled to the power circuits entering a residence, supply analog voltage and current signals which are converted to digital format and processed to detect changes in certain residential load parameters, i.e., admittance. Cluster analysis techniques are employed to group change measurements into certain categories, and logic is applied to identify individual appliances and the energy consumed by each. 9 figs.

  20. An adaptive neural swarm approach for intrusion defense in ad hoc networks

    NASA Astrophysics Data System (ADS)

    Cannady, James

    2011-06-01

    Wireless sensor networks (WSN) and mobile ad hoc networks (MANET) are being increasingly deployed in critical applications due to the flexibility and extensibility of the technology. While these networks possess numerous advantages over traditional wireless systems in dynamic environments they are still vulnerable to many of the same types of host-based and distributed attacks common to those systems. Unfortunately, the limited power and bandwidth available in WSNs and MANETs, combined with the dynamic connectivity that is a defining characteristic of the technology, makes it extremely difficult to utilize traditional intrusion detection techniques. This paper describes an approach to accurately and efficiently detect potentially damaging activity in WSNs and MANETs. It enables the network as a whole to recognize attacks, anomalies, and potential vulnerabilities in a distributive manner that reflects the autonomic processes of biological systems. Each component of the network recognizes activity in its local environment and then contributes to the overall situational awareness of the entire system. The approach utilizes agent-based swarm intelligence to adaptively identify potential data sources on each node and on adjacent nodes throughout the network. The swarm agents then self-organize into modular neural networks that utilize a reinforcement learning algorithm to identify relevant behavior patterns in the data without supervision. Once the modular neural networks have established interconnectivity both locally and with neighboring nodes the analysis of events within the network can be conducted collectively in real-time. The approach has been shown to be extremely effective in identifying distributed network attacks.

  1. Solvents and vapor intrusion pathways.

    PubMed

    Phillips, Scott D; Krieger, Gary R; Palmer, Robert B; Waksman, Javier C

    2004-08-01

    Vapor intrusion must be recognized appropriately as a separate pathway of contamination. Although many issues resemble those of other forms of contamination (particularly its entryway, which is similar to that of radon seepage), vapor intrusion stands apart as a unique risk requiring case-specific action. This article addresses these issues and the current understanding of the most appropriate and successful remedial actions.

  2. Agent-based modeling: case study in cleavage furrow models.

    PubMed

    Mogilner, Alex; Manhart, Angelika

    2016-11-07

    The number of studies in cell biology in which quantitative models accompany experiments has been growing steadily. Roughly, mathematical and computational techniques of these models can be classified as "differential equation based" (DE) or "agent based" (AB). Recently AB models have started to outnumber DE models, but understanding of AB philosophy and methodology is much less widespread than familiarity with DE techniques. Here we use the history of modeling a fundamental biological problem-positioning of the cleavage furrow in dividing cells-to explain how and why DE and AB models are used. We discuss differences, advantages, and shortcomings of these two approaches.

  3. Agent-Based Distributed Data Mining: A Survey

    NASA Astrophysics Data System (ADS)

    Moemeng, Chayapol; Gorodetsky, Vladimir; Zuo, Ziye; Yang, Yong; Zhang, Chengqi

    Distributed data mining is originated from the need of mining over decentralised data sources. Data mining techniques involving in such complex environment must encounter great dynamics due to changes in the system can affect the overall performance of the system. Agent computing whose aim is to deal with complex systems has revealed opportunities to improve distributed data mining systems in a number of ways. This paper surveys the integration of multi-agent system and distributed data mining, also known as agent-based distributed data mining, in terms of significance, system overview, existing systems, and research trends.

  4. An Agent Based Model for Social Class Emergence

    NASA Astrophysics Data System (ADS)

    Yang, Xiaoxiang; Rodriguez Segura, Daniel; Lin, Fei; Mazilu, Irina

    We present an open system agent-based model to analyze the effects of education and the society-specific wealth transactions on the emergence of social classes. Building on previous studies, we use realistic functions to model how years of education affect the income level. Numerical simulations show that the fraction of an individual's total transactions that is invested rather than consumed can cause wealth gaps between different income brackets in the long run. In an attempt to incorporate the network effects, we also explore how the probability of interactions among agents depending on the spread of their income brackets affects wealth distribution.

  5. Distributed fiber optic moisture intrusion sensing system

    DOEpatents

    Weiss, Jonathan D.

    2003-06-24

    Method and system for monitoring and identifying moisture intrusion in soil such as is contained in landfills housing radioactive and/or hazardous waste. The invention utilizes the principle that moist or wet soil has a higher thermal conductance than dry soil. The invention employs optical time delay reflectometry in connection with a distributed temperature sensing system together with heating means in order to identify discrete areas within a volume of soil wherein temperature is lower. According to the invention an optical element and, optionally, a heating element may be included in a cable or other similar structure and arranged in a serpentine fashion within a volume of soil to achieve efficient temperature detection across a large area or three dimensional volume of soil. Remediation, moisture countermeasures, or other responsive action may then be coordinated based on the assumption that cooler regions within a soil volume may signal moisture intrusion where those regions are located.

  6. An agent-based approach to financial stylized facts

    NASA Astrophysics Data System (ADS)

    Shimokawa, Tetsuya; Suzuki, Kyoko; Misawa, Tadanobu

    2007-06-01

    An important challenge of the financial theory in recent years is to construct more sophisticated models which have consistencies with as many financial stylized facts that cannot be explained by traditional models. Recently, psychological studies on decision making under uncertainty which originate in Kahneman and Tversky's research attract a lot of interest as key factors which figure out the financial stylized facts. These psychological results have been applied to the theory of investor's decision making and financial equilibrium modeling. This paper, following these behavioral financial studies, would like to propose an agent-based equilibrium model with prospect theoretical features of investors. Our goal is to point out a possibility that loss-averse feature of investors explains vast number of financial stylized facts and plays a crucial role in price formations of financial markets. Price process which is endogenously generated through our model has consistencies with, not only the equity premium puzzle and the volatility puzzle, but great kurtosis, asymmetry of return distribution, auto-correlation of return volatility, cross-correlation between return volatility and trading volume. Moreover, by using agent-based simulations, the paper also provides a rigorous explanation from the viewpoint of a lack of market liquidity to the size effect, which means that small-sized stocks enjoy excess returns compared to large-sized stocks.

  7. Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis.

    PubMed

    Kurhekar, Manish; Deshpande, Umesh

    2016-01-01

    Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website.

  8. Agent-Based Deterministic Modeling of the Bone Marrow Homeostasis

    PubMed Central

    2016-01-01

    Modeling of stem cells not only describes but also predicts how a stem cell's environment can control its fate. The first stem cell populations discovered were hematopoietic stem cells (HSCs). In this paper, we present a deterministic model of bone marrow (that hosts HSCs) that is consistent with several of the qualitative biological observations. This model incorporates stem cell death (apoptosis) after a certain number of cell divisions and also demonstrates that a single HSC can potentially populate the entire bone marrow. It also demonstrates that there is a production of sufficient number of differentiated cells (RBCs, WBCs, etc.). We prove that our model of bone marrow is biologically consistent and it overcomes the biological feasibility limitations of previously reported models. The major contribution of our model is the flexibility it allows in choosing model parameters which permits several different simulations to be carried out in silico without affecting the homeostatic properties of the model. We have also performed agent-based simulation of the model of bone marrow system proposed in this paper. We have also included parameter details and the results obtained from the simulation. The program of the agent-based simulation of the proposed model is made available on a publicly accessible website. PMID:27340402

  9. Modelling of robotic work cells using agent based-approach

    NASA Astrophysics Data System (ADS)

    Sękala, A.; Banaś, W.; Gwiazda, A.; Monica, Z.; Kost, G.; Hryniewicz, P.

    2016-08-01

    In the case of modern manufacturing systems the requirements, both according the scope and according characteristics of technical procedures are dynamically changing. This results in production system organization inability to keep up with changes in a market demand. Accordingly, there is a need for new design methods, characterized, on the one hand with a high efficiency and on the other with the adequate level of the generated organizational solutions. One of the tools that could be used for this purpose is the concept of agent systems. These systems are the tools of artificial intelligence. They allow assigning to agents the proper domains of procedures and knowledge so that they represent in a self-organizing system of an agent environment, components of a real system. The agent-based system for modelling robotic work cell should be designed taking into consideration many limitations considered with the characteristic of this production unit. It is possible to distinguish some grouped of structural components that constitute such a system. This confirms the structural complexity of a work cell as a specific production system. So it is necessary to develop agents depicting various aspects of the work cell structure. The main groups of agents that are used to model a robotic work cell should at least include next pattern representatives: machine tool agents, auxiliary equipment agents, robots agents, transport equipment agents, organizational agents as well as data and knowledge bases agents. In this way it is possible to create the holarchy of the agent-based system.

  10. An agent-based microsimulation of critical infrastructure systems

    SciTech Connect

    BARTON,DIANNE C.; STAMBER,KEVIN L.

    2000-03-29

    US infrastructures provide essential services that support the economic prosperity and quality of life. Today, the latest threat to these infrastructures is the increasing complexity and interconnectedness of the system. On balance, added connectivity will improve economic efficiency; however, increased coupling could also result in situations where a disturbance in an isolated infrastructure unexpectedly cascades across diverse infrastructures. An understanding of the behavior of complex systems can be critical to understanding and predicting infrastructure responses to unexpected perturbation. Sandia National Laboratories has developed an agent-based model of critical US infrastructures using time-dependent Monte Carlo methods and a genetic algorithm learning classifier system to control decision making. The model is currently under development and contains agents that represent the several areas within the interconnected infrastructures, including electric power and fuel supply. Previous work shows that agent-based simulations models have the potential to improve the accuracy of complex system forecasting and to provide new insights into the factors that are the primary drivers of emergent behaviors in interdependent systems. Simulation results can be examined both computationally and analytically, offering new ways of theorizing about the impact of perturbations to an infrastructure network.

  11. Influence of seawater intrusion on microbial communities in groundwater.

    PubMed

    Unno, Tatsuya; Kim, Jungman; Kim, Yumi; Nguyen, Son G; Guevarra, Robin B; Kim, Gee Pyo; Lee, Ji-Hoon; Sadowsky, Michael J

    2015-11-01

    Groundwater is the sole source of potable water on Jeju Island in the Republic of (South) Korea. Groundwater is also used for irrigation and industrial purposes, and it is severely impacted by seawater intrusion in coastal areas. Consequently, monitoring the intrusion of seawater into groundwater on Jeju is very important for health and environmental reasons. A number of studies have used hydrological models to predict the deterioration of groundwater quality caused by seawater intrusion. However, there is conflicting evidence of intrusion due to complicated environmental influences on groundwater quality. Here we investigated the use of next generation sequencing (NGS)-based microbial community analysis as a way to monitor groundwater quality and detect seawater intrusion. Pristine groundwater, groundwater from three coastal areas, and seawater were compared. Analysis of the distribution of bacterial species clearly indicated that the high and low salinity groundwater differed significantly with respect to microbial composition. While members of the family Parvularculaceae were only identified in high salinity water samples, a greater percentage of the phylum Actinobacteria was predominantly observed in pristine groundwater. In addition, we identified 48 shared operational taxonomic units (OTUs) with seawater, among which the high salinity groundwater sample shared a greater number of bacterial species with seawater (6.7%). In contrast, other groundwater samples shared less than 0.5%. Our results suggest that NGS-based microbial community analysis of groundwater may be a useful tool for monitoring groundwater quality and detect seawater intrusion. This technology may also provide additional insights in understanding hydrological dynamics.

  12. WiFi Miner: An Online Apriori-Infrequent Based Wireless Intrusion System

    NASA Astrophysics Data System (ADS)

    Rahman, Ahmedur; Ezeife, C. I.; Aggarwal, A. K.

    Intrusion detection in wireless networks has become a vital part in wireless network security systems with wide spread use of Wireless Local Area Networks (WLAN). Currently, almost all devices are Wi-Fi (Wireless Fidelity) capable and can access WLAN. This paper proposes an Intrusion Detection System, WiFi Miner, which applies an infrequent pattern association rule mining Apriori technique to wireless network packets captured through hardware sensors for purposes of real time detection of intrusive or anomalous packets. Contributions of the proposed system includes effectively adapting an efficient data mining association rule technique to important problem of intrusion detection in a wireless network environment using hardware sensors, providing a solution that eliminates the need for hard-to-obtain training data in this environment, providing increased intrusion detection rate and reduction of false alarms.

  13. DETECTION OF HISTORICAL PIPELINE LEAK PLUMES USING NON-INTRUSIVE SURFACE-BASED GEOPHYSICAL TECHNIQUES AT THE HANFORD NUCLEAR SITE WASHINGTON USA

    SciTech Connect

    SKORSKA MB; FINK JB; RUCKER DF; LEVITT MT

    2010-12-02

    Historical records from the Department of Energy Hanford Nuclear Reservation (in eastern WA) indicate that ruptures in buried waste transfer pipelines were common between the 1940s and 1980s, which resulted in unplanned releases (UPRs) of tank: waste at numerous locations. A number of methods are commercially available for the detection of active or recent leaks, however, there are no methods available for the detection of leaks that occurred many years ago. Over the decades, leaks from the Hanford pipelines were detected by visual observation of fluid on the surface, mass balance calculations (where flow volumes were monitored), and incidental encounters with waste during excavation or drilling. Since these detection methods for historic leaks are so limited in resolution and effectiveness, it is likely that a significant number of pipeline leaks have not been detected. Therefore, a technology was needed to detect the specific location of unknown pipeline leaks so that characterization technologies can be used to identify any risks to groundwater caused by waste released into the vadose zone. A proof-of-concept electromagnetic geophysical survey was conducted at an UPR in order to image a historical leak from a waste transfer pipeline. The survey was designed to test an innovative electromagnetic geophysical technique that could be used to rapidly map the extent of historical leaks from pipelines within the Hanford Site complex. This proof-of-concept test included comprehensive testing and analysis of the transient electromagnetic method (TEM) and made use of supporting and confirmatory geophysical methods including ground penetrating radar, magnetics, and electrical resistivity characterization (ERC). The results for this initial proof-of-concept test were successful and greatly exceeded the expectations of the project team by providing excellent discrimination of soils contaminated with leaked waste despite the interference from an electrically conductive pipe.

  14. Engineering large-scale agent-based systems with consensus

    NASA Technical Reports Server (NTRS)

    Bokma, A.; Slade, A.; Kerridge, S.; Johnson, K.

    1994-01-01

    The paper presents the consensus method for the development of large-scale agent-based systems. Systems can be developed as networks of knowledge based agents (KBA) which engage in a collaborative problem solving effort. The method provides a comprehensive and integrated approach to the development of this type of system. This includes a systematic analysis of user requirements as well as a structured approach to generating a system design which exhibits the desired functionality. There is a direct correspondence between system requirements and design components. The benefits of this approach are that requirements are traceable into design components and code thus facilitating verification. The use of the consensus method with two major test applications showed it to be successful and also provided valuable insight into problems typically associated with the development of large systems.

  15. Agent-based model to rural urban migration analysis

    NASA Astrophysics Data System (ADS)

    Silveira, Jaylson J.; Espíndola, Aquino L.; Penna, T. J. P.

    2006-05-01

    In this paper, we analyze the rural-urban migration phenomenon as it is usually observed in economies which are in the early stages of industrialization. The analysis is conducted by means of a statistical mechanics approach which builds a computational agent-based model. Agents are placed on a lattice and the connections among them are described via an Ising-like model. Simulations on this computational model show some emergent properties that are common in developing economies, such as a transitional dynamics characterized by continuous growth of urban population, followed by the equalization of expected wages between rural and urban sectors (Harris-Todaro equilibrium condition), urban concentration and increasing of per capita income.

  16. Agent-based simulation of a financial market

    NASA Astrophysics Data System (ADS)

    Raberto, Marco; Cincotti, Silvano; Focardi, Sergio M.; Marchesi, Michele

    2001-10-01

    This paper introduces an agent-based artificial financial market in which heterogeneous agents trade one single asset through a realistic trading mechanism for price formation. Agents are initially endowed with a finite amount of cash and a given finite portfolio of assets. There is no money-creation process; the total available cash is conserved in time. In each period, agents make random buy and sell decisions that are constrained by available resources, subject to clustering, and dependent on the volatility of previous periods. The model proposed herein is able to reproduce the leptokurtic shape of the probability density of log price returns and the clustering of volatility. Implemented using extreme programming and object-oriented technology, the simulator is a flexible computational experimental facility that can find applications in both academic and industrial research projects.

  17. Using Agent Based Modeling (ABM) to Develop Cultural Interaction Simulations

    NASA Technical Reports Server (NTRS)

    Drucker, Nick; Jones, Phillip N.

    2012-01-01

    Today, most cultural training is based on or built around "cultural engagements" or discrete interactions between the individual learner and one or more cultural "others". Often, success in the engagement is the end or the objective. In reality, these interactions usually involve secondary and tertiary effects with potentially wide ranging consequences. The concern is that learning culture within a strict engagement context might lead to "checklist" cultural thinking that will not empower learners to understand the full consequence of their actions. We propose the use of agent based modeling (ABM) to collect, store, and, simulating the effects of social networks, promulgate engagement effects over time, distance, and consequence. The ABM development allows for rapid modification to re-create any number of population types, extending the applicability of the model to any requirement for social modeling.

  18. On agent-based modeling and computational social science

    PubMed Central

    Conte, Rosaria; Paolucci, Mario

    2014-01-01

    In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS. PMID:25071642

  19. On agent-based modeling and computational social science.

    PubMed

    Conte, Rosaria; Paolucci, Mario

    2014-01-01

    In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS.

  20. Climate Shocks and Migration: An Agent-Based Modeling Approach.

    PubMed

    Entwisle, Barbara; Williams, Nathalie E; Verdery, Ashton M; Rindfuss, Ronald R; Walsh, Stephen J; Malanson, George P; Mucha, Peter J; Frizzelle, Brian G; McDaniel, Philip M; Yao, Xiaozheng; Heumann, Benjamin W; Prasartkul, Pramote; Sawangdee, Yothin; Jampaklay, Aree

    2016-09-01

    This is a study of migration responses to climate shocks. We construct an agent-based model that incorporates dynamic linkages between demographic behaviors, such as migration, marriage, and births, and agriculture and land use, which depend on rainfall patterns. The rules and parameterization of our model are empirically derived from qualitative and quantitative analyses of a well-studied demographic field site, Nang Rong district, Northeast Thailand. With this model, we simulate patterns of migration under four weather regimes in a rice economy: 1) a reference, 'normal' scenario; 2) seven years of unusually wet weather; 3) seven years of unusually dry weather; and 4) seven years of extremely variable weather. Results show relatively small impacts on migration. Experiments with the model show that existing high migration rates and strong selection factors, which are unaffected by climate change, are likely responsible for the weak migration response.

  1. Agent-based modeling of noncommunicable diseases: a systematic review.

    PubMed

    Nianogo, Roch A; Arah, Onyebuchi A

    2015-03-01

    We reviewed the use of agent-based modeling (ABM), a systems science method, in understanding noncommunicable diseases (NCDs) and their public health risk factors. We systematically reviewed studies in PubMed, ScienceDirect, and Web of Sciences published from January 2003 to July 2014. We retrieved 22 relevant articles; each had an observational or interventional design. Physical activity and diet were the most-studied outcomes. Often, single agent types were modeled, and the environment was usually irrelevant to the studied outcome. Predictive validation and sensitivity analyses were most used to validate models. Although increasingly used to study NCDs, ABM remains underutilized and, where used, is suboptimally reported in public health studies. Its use in studying NCDs will benefit from clarified best practices and improved rigor to establish its usefulness and facilitate replication, interpretation, and application.

  2. Techniques and Issues in Agent-Based Modeling Validation

    SciTech Connect

    Pullum, Laura L; Cui, Xiaohui

    2012-01-01

    Validation of simulation models is extremely important. It ensures that the right model has been built and lends confidence to the use of that model to inform critical decisions. Agent-based models (ABM) have been widely deployed in different fields for studying the collective behavior of large numbers of interacting agents. However, researchers have only recently started to consider the issues of validation. Compared to other simulation models, ABM has many differences in model development, usage and validation. An ABM is inherently easier to build than a classical simulation, but more difficult to describe formally since they are closer to human cognition. Using multi-agent models to study complex systems has attracted criticisms because of the challenges involved in their validation [1]. In this report, we describe the challenge of ABM validation and present a novel approach we recently developed for an ABM system.

  3. Agent-Based Modeling of Noncommunicable Diseases: A Systematic Review

    PubMed Central

    Arah, Onyebuchi A.

    2015-01-01

    We reviewed the use of agent-based modeling (ABM), a systems science method, in understanding noncommunicable diseases (NCDs) and their public health risk factors. We systematically reviewed studies in PubMed, ScienceDirect, and Web of Sciences published from January 2003 to July 2014. We retrieved 22 relevant articles; each had an observational or interventional design. Physical activity and diet were the most-studied outcomes. Often, single agent types were modeled, and the environment was usually irrelevant to the studied outcome. Predictive validation and sensitivity analyses were most used to validate models. Although increasingly used to study NCDs, ABM remains underutilized and, where used, is suboptimally reported in public health studies. Its use in studying NCDs will benefit from clarified best practices and improved rigor to establish its usefulness and facilitate replication, interpretation, and application. PMID:25602871

  4. Statistical Agent Based Modelization of the Phenomenon of Drug Abuse

    NASA Astrophysics Data System (ADS)

    di Clemente, Riccardo; Pietronero, Luciano

    2012-07-01

    We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.

  5. Protection of autonomous microgrids using agent-based distributed communication

    SciTech Connect

    Cintuglu, Mehmet H.; Ma, Tan; Mohammed, Osama A.

    2016-04-06

    This study presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large scale distribution net-works due to the presence of power converters and relatively low inertia. In this work, we introduce a practical overcurrent and a frequency selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme (RAS) of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency selectivity approach is proposed to avoid pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the pro-posed schemes using a laboratory based microgrid. The setup was composed of actual generation units and IEDs using IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme.

  6. Agent-Based Computational Modeling of Cell Culture ...

    EPA Pesticide Factsheets

    Quantitative characterization of cellular dose in vitro is needed for alignment of doses in vitro and in vivo. We used the agent-based software, CompuCell3D (CC3D), to provide a stochastic description of cell growth in culture. The model was configured so that isolated cells assumed a “fried egg shape” but became increasingly cuboidal with increasing confluency. The surface area presented by each cell to the overlying medium varies from cell-to-cell and is a determinant of diffusional flux of toxicant from the medium into the cell. Thus, dose varies among cells for a given concentration of toxicant in the medium. Computer code describing diffusion of H2O2 from medium into each cell and clearance of H2O2 was calibrated against H2O2 time-course data (25, 50, or 75 uM H2O2 for 60 min) obtained with the Amplex Red assay for the medium and the H2O2-sensitive fluorescent reporter, HyPer, for cytosol. Cellular H2O2 concentrations peaked at about 5 min and were near baseline by 10 min. The model predicted a skewed distribution of surface areas, with between cell variation usually 2 fold or less. Predicted variability in cellular dose was in rough agreement with the variation in the HyPer data. These results are preliminary, as the model was not calibrated to the morphology of a specific cell type. Future work will involve morphology model calibration against human bronchial epithelial (BEAS-2B) cells. Our results show, however, the potential of agent-based modeling

  7. Gas intrusion into SPR caverns

    SciTech Connect

    Hinkebein, T.E.; Bauer, S.J.; Ehgartner, B.L.; Linn, J.K.; Neal, J.T.; Todd, J.L.; Kuhlman, P.S.; Gniady, C.T.; Giles, H.N.

    1995-12-01

    The conditions and occurrence of gas in crude oil stored in Strategic Petroleum Reserve, SPR, caverns is characterized in this report. Many caverns in the SPR show that gas has intruded into the oil from the surrounding salt dome. Historical evidence and the analyses presented here suggest that gas will continue to intrude into many SPR caverns in the future. In considering why only some caverns contain gas, it is concluded that the naturally occurring spatial variability in salt permeability can explain the range of gas content measured in SPR caverns. Further, it is not possible to make a one-to-one correlation between specific geologic phenomena and the occurrence of gas in salt caverns. However, gas is concluded to be petrogenic in origin. Consequently, attempts have been made to associate the occurrence of gas with salt inhomogeneities including anomalies and other structural features. Two scenarios for actual gas intrusion into caverns were investigated for consistency with existing information. These scenarios are gas release during leaching and gas permeation through salt. Of these mechanisms, the greater consistency comes from the belief that gas permeates to caverns through the salt. A review of historical operating data for five Bryan Mound caverns loosely supports the hypothesis that higher operating pressures reduce gas intrusion into caverns. This conclusion supports a permeability intrusion mechanism. Further, it provides justification for operating the caverns near maximum operating pressure to minimize gas intrusion. Historical gas intrusion rates and estimates of future gas intrusion are given for all caverns.

  8. Biochemical and Clinical Assessments of Segmental Maxillary Posterior Tooth Intrusion

    PubMed Central

    Tasanapanont, Jintana; Wattanachai, Tanapan; Apisariyakul, Janya; Pothacharoen, Peraphan; Kongtawelert, Prachya; Midtbø, Marit

    2017-01-01

    Objective. To compare chondroitin sulphate (CS) levels around maxillary second premolars, first molars, and second molars between the unloaded and the loaded periods and to measure the rates of intrusion of maxillary posterior teeth during segmental posterior tooth intrusion. Materials and Methods. In this prospective clinical study, 105 teeth (from 15 patients exhibiting anterior open bite and requiring maxillary posterior tooth intrusion) were studied. Competitive ELISA was used to detect CS levels. Dental casts (during the unloaded and loaded periods) were scanned, and posterior tooth intrusion distances were measured. Results. During the unloaded period, the median CS levels around maxillary second premolars, first molars, second molars (experimental teeth), and mandibular first molars (negative control) were 0.006, 0.055, 0.056, and 0.012 and during the loaded period were 2.592, 5.738, 4.727, and 0.163 ng/μg of total protein, respectively. The median CS levels around experimental teeth were significantly elevated during the loaded period. The mean rates of maxillary second premolar and first and second molar intrusion were 0.72, 0.58, and 0.40 mm/12 weeks, respectively. Conclusions. Biochemical and clinical assessments suggested that the segmental posterior tooth intrusion treatment modality with 50 g of vertical force per side was sufficient. Trial Registration. The study is registered as TCTR20170206006. PMID:28321256

  9. Recent advances in vapor intrusion site investigations.

    PubMed

    McHugh, Thomas; Loll, Per; Eklund, Bart

    2017-02-22

    Our understanding of vapor intrusion has evolved rapidly since the discovery of the first high profile vapor intrusion sites in the late 1990s and early 2000s. Research efforts and field investigations have improved our understanding of vapor intrusion processes including the role of preferential pathways and natural barriers to vapor intrusion. This review paper addresses recent developments in the regulatory framework and conceptual model for vapor intrusion. In addition, a number of innovative investigation methods are discussed.

  10. Network intrusion detector: NID user`s guide V 1.0

    SciTech Connect

    Palasek, R.

    1994-04-01

    The NID suite of software tools was developed to help detect and analyze intrusive behavior over networks. NID combines and uses three techniques of intrusion detection: attack signature recognition, anomaly detection, and a vulnerability risk model. The authors have found from experience that the signature recognition component has been the most effective in detecting network based attacks. The underlying assumption of NID is that there is a security domain that you are interested in protecting. NID monitors traffic that crosses the boundary of that domain, looking for signs of intrusion and abnormal activity.

  11. Serious games experiment toward agent-based simulation

    USGS Publications Warehouse

    Wein, Anne; Labiosa, William

    2013-01-01

    We evaluate the potential for serious games to be used as a scientifically based decision-support product that supports the United States Geological Survey’s (USGS) mission--to provide integrated, unbiased scientific information that can make a substantial contribution to societal well-being for a wide variety of complex environmental challenges. Serious or pedagogical games are an engaging way to educate decisionmakers and stakeholders about environmental challenges that are usefully informed by natural and social scientific information and knowledge and can be designed to promote interactive learning and exploration in the face of large uncertainties, divergent values, and complex situations. We developed two serious games that use challenging environmental-planning issues to demonstrate and investigate the potential contributions of serious games to inform regional-planning decisions. Delta Skelta is a game emulating long-term integrated environmental planning in the Sacramento-San Joaquin Delta, California, that incorporates natural hazards (flooding and earthquakes) and consequences for California water supplies amidst conflicting water interests. Age of Ecology is a game that simulates interactions between economic and ecologic processes, as well as natural hazards while implementing agent-based modeling. The content of these games spans the USGS science mission areas related to water, ecosystems, natural hazards, land use, and climate change. We describe the games, reflect on design and informational aspects, and comment on their potential usefulness. During the process of developing these games, we identified various design trade-offs involving factual information, strategic thinking, game-winning criteria, elements of fun, number and type of players, time horizon, and uncertainty. We evaluate the two games in terms of accomplishments and limitations. Overall, we demonstrated the potential for these games to usefully represent scientific information

  12. Evaluating Water Demand Using Agent-Based Modeling

    NASA Astrophysics Data System (ADS)

    Lowry, T. S.

    2004-12-01

    The supply and demand of water resources are functions of complex, inter-related systems including hydrology, climate, demographics, economics, and policy. To assess the safety and sustainability of water resources, planners often rely on complex numerical models that relate some or all of these systems using mathematical abstractions. The accuracy of these models relies on how well the abstractions capture the true nature of the systems interactions. Typically, these abstractions are based on analyses of observations and/or experiments that account only for the statistical mean behavior of each system. This limits the approach in two important ways: 1) It cannot capture cross-system disruptive events, such as major drought, significant policy change, or terrorist attack, and 2) it cannot resolve sub-system level responses. To overcome these limitations, we are developing an agent-based water resources model that includes the systems of hydrology, climate, demographics, economics, and policy, to examine water demand during normal and extraordinary conditions. Agent-based modeling (ABM) develops functional relationships between systems by modeling the interaction between individuals (agents), who behave according to a probabilistic set of rules. ABM is a "bottom-up" modeling approach in that it defines macro-system behavior by modeling the micro-behavior of individual agents. While each agent's behavior is often simple and predictable, the aggregate behavior of all agents in each system can be complex, unpredictable, and different than behaviors observed in mean-behavior models. Furthermore, the ABM approach creates a virtual laboratory where the effects of policy changes and/or extraordinary events can be simulated. Our model, which is based on the demographics and hydrology of the Middle Rio Grande Basin in the state of New Mexico, includes agent groups of residential, agricultural, and industrial users. Each agent within each group determines its water usage

  13. Dynamic calibration of agent-based models using data assimilation.

    PubMed

    Ward, Jonathan A; Evans, Andrew J; Malleson, Nicolas S

    2016-04-01

    A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds.

  14. Agent-Based Mapping of Credit Risk for Sustainable Microfinance

    PubMed Central

    Lee, Joung-Hun; Jusup, Marko; Podobnik, Boris; Iwasa, Yoh

    2015-01-01

    By drawing analogies with independent research areas, we propose an unorthodox framework for mapping microfinance credit risk---a major obstacle to the sustainability of lenders outreaching to the poor. Specifically, using the elements of network theory, we constructed an agent-based model that obeys the stylized rules of microfinance industry. We found that in a deteriorating economic environment confounded with adverse selection, a form of latent moral hazard may cause a regime shift from a high to a low loan payment probability. An after-the-fact recovery, when possible, required the economic environment to improve beyond that which led to the shift in the first place. These findings suggest a small set of measurable quantities for mapping microfinance credit risk and, consequently, for balancing the requirements to reasonably price loans and to operate on a fully self-financed basis. We illustrate how the proposed mapping works using a 10-year monthly data set from one of the best-known microfinance representatives, Grameen Bank in Bangladesh. Finally, we discuss an entirely new perspective for managing microfinance credit risk based on enticing spontaneous cooperation by building social capital. PMID:25945790

  15. Agent-based mapping of credit risk for sustainable microfinance.

    PubMed

    Lee, Joung-Hun; Jusup, Marko; Podobnik, Boris; Iwasa, Yoh

    2015-01-01

    By drawing analogies with independent research areas, we propose an unorthodox framework for mapping microfinance credit risk--a major obstacle to the sustainability of lenders outreaching to the poor. Specifically, using the elements of network theory, we constructed an agent-based model that obeys the stylized rules of microfinance industry. We found that in a deteriorating economic environment confounded with adverse selection, a form of latent moral hazard may cause a regime shift from a high to a low loan payment probability. An after-the-fact recovery, when possible, required the economic environment to improve beyond that which led to the shift in the first place. These findings suggest a small set of measurable quantities for mapping microfinance credit risk and, consequently, for balancing the requirements to reasonably price loans and to operate on a fully self-financed basis. We illustrate how the proposed mapping works using a 10-year monthly data set from one of the best-known microfinance representatives, Grameen Bank in Bangladesh. Finally, we discuss an entirely new perspective for managing microfinance credit risk based on enticing spontaneous cooperation by building social capital.

  16. Agent-based reasoning for distributed multi-INT analysis

    NASA Astrophysics Data System (ADS)

    Inchiosa, Mario E.; Parker, Miles T.; Perline, Richard

    2006-05-01

    Fully exploiting the intelligence community's exponentially growing data resources will require computational approaches differing radically from those currently available. Intelligence data is massive, distributed, and heterogeneous. Conventional approaches requiring highly structured and centralized data will not meet this challenge. We report on a new approach, Agent-Based Reasoning (ABR). In NIST evaluations, the use of ABR software tripled analysts' solution speed, doubled accuracy, and halved perceived difficulty. ABR makes use of populations of fine-grained, locally interacting agents that collectively reason about intelligence scenarios in a self-organizing, "bottom-up" process akin to those found in biological and other complex systems. Reproduction rules allow agents to make inferences from multi-INT data, while movement rules organize information and optimize reasoning. Complementary deterministic and stochastic agent behaviors enhance reasoning power and flexibility. Agent interaction via small-world networks - such as are found in nervous systems, social networks, and power distribution grids - dramatically increases the rate of discovering intelligence fragments that usefully connect to yield new inferences. Small-world networks also support the distributed processing necessary to address intelligence community data challenges. In addition, we have found that ABR pre-processing can boost the performance of commercial text clustering software. Finally, we have demonstrated interoperability with Knowledge Engineering systems and seen that reasoning across diverse data sources can be a rich source of inferences.

  17. Domination and evolution in agent based model of an economy

    NASA Astrophysics Data System (ADS)

    Kazmi, Syed S.

    We introduce Agent Based Model of a pure exchange economy and a simple economy that includes production, consumption and distributions. Markets are described by Edgeworth Exchange in both models. Trades are binary bilateral trades at prices that are set in each trade. We found that the prices converge over time to a value that is not the standard Equilibrium value given by the Walrasian Tattonement fiction. The average price, and the distributions of Wealth, depends on the degree of Domination (persuasive power) we introduced based on differentials in trading "leverage" due to wealth differences. The full economy model is allowed to evolve by replacement of agents that do not survive with agents having random properties. We found that, depending upon the average productivity compared to the average consumption, very different kinds of behavior emerged. The Economy as a whole reaches a steady state by the population adapting to the conditions of productivity and consumption. Correlations develop in a population between what would be for each individual a random assignment of Productivity, Labor power, Wealth, and Preferences. The population adapts to the economic environment by development of these Correlations and without any learning process. We see signs of emerging social structure as a result of necessity of survival.

  18. Measure of Landscape Heterogeneity by Agent-Based Methodology

    NASA Astrophysics Data System (ADS)

    Wirth, E.; Szabó, Gy.; Czinkóczky, A.

    2016-06-01

    With the rapid increase of the world's population, the efficient food production is one of the key factors of the human survival. Since biodiversity and heterogeneity is the basis of the sustainable agriculture, the authors tried to measure the heterogeneity of a chosen landscape. The EU farming and subsidizing policies (EEA, 2014) support landscape heterogeneity and diversity, nevertheless exact measurements and calculations apart from statistical parameters (standard deviation, mean), do not really exist. In the present paper the authors' goal is to find an objective, dynamic method that measures landscape heterogeneity. It is achieved with the so called agent-based modelling, where randomly dispatched dynamic scouts record the observed land cover parameters and sum up the features of a new type of land. During the simulation the agents collect a Monte Carlo integral as a diversity landscape potential which can be considered as the unit of the `greening' measure. As a final product of the ABM method, a landscape potential map is obtained that can serve as a tool for objective decision making to support agricultural diversity.

  19. E-laboratories : agent-based modeling of electricity markets.

    SciTech Connect

    North, M.; Conzelmann, G.; Koritarov, V.; Macal, C.; Thimmapuram, P.; Veselka, T.

    2002-05-03

    Electricity markets are complex adaptive systems that operate under a wide range of rules that span a variety of time scales. These rules are imposed both from above by society and below by physics. Many electricity markets are undergoing or are about to undergo a transition from centrally regulated systems to decentralized markets. Furthermore, several electricity markets have recently undergone this transition with extremely unsatisfactory results, most notably in California. These high stakes transitions require the introduction of largely untested regulatory structures. Suitable laboratories that can be used to test regulatory structures before they are applied to real systems are needed. Agent-based models can provide such electronic laboratories or ''e-laboratories.'' To better understand the requirements of an electricity market e-laboratory, a live electricity market simulation was created. This experience helped to shape the development of the Electricity Market Complex Adaptive Systems (EMCAS) model. To explore EMCAS' potential as an e-laboratory, several variations of the live simulation were created. These variations probed the possible effects of changing power plant outages and price setting rules on electricity market prices.

  20. Protection of autonomous microgrids using agent-based distributed communication

    DOE PAGES

    Cintuglu, Mehmet H.; Ma, Tan; Mohammed, Osama A.

    2016-04-06

    This study presents a real-time implementation of autonomous microgrid protection using agent-based distributed communication. Protection of an autonomous microgrid requires special considerations compared to large scale distribution net-works due to the presence of power converters and relatively low inertia. In this work, we introduce a practical overcurrent and a frequency selectivity method to overcome conventional limitations. The proposed overcurrent scheme defines a selectivity mechanism considering the remedial action scheme (RAS) of the microgrid after a fault instant based on feeder characteristics and the location of the intelligent electronic devices (IEDs). A synchrophasor-based online frequency selectivity approach is proposed to avoidmore » pulse loading effects in low inertia microgrids. Experimental results are presented for verification of the pro-posed schemes using a laboratory based microgrid. The setup was composed of actual generation units and IEDs using IEC 61850 protocol. The experimental results were in excellent agreement with the proposed protection scheme.« less

  1. Agent-based modelling of consumer energy choices

    NASA Astrophysics Data System (ADS)

    Rai, Varun; Henry, Adam Douglas

    2016-06-01

    Strategies to mitigate global climate change should be grounded in a rigorous understanding of energy systems, particularly the factors that drive energy demand. Agent-based modelling (ABM) is a powerful tool for representing the complexities of energy demand, such as social interactions and spatial constraints. Unlike other approaches for modelling energy demand, ABM is not limited to studying perfectly rational agents or to abstracting micro details into system-level equations. Instead, ABM provides the ability to represent behaviours of energy consumers -- such as individual households -- using a range of theories, and to examine how the interaction of heterogeneous agents at the micro-level produces macro outcomes of importance to the global climate, such as the adoption of low-carbon behaviours and technologies over space and time. We provide an overview of ABM work in the area of consumer energy choices, with a focus on identifying specific ways in which ABM can improve understanding of both fundamental scientific and applied aspects of the demand side of energy to aid the design of better policies and programmes. Future research needs for improving the practice of ABM to better understand energy demand are also discussed.

  2. Dynamic calibration of agent-based models using data assimilation

    PubMed Central

    Ward, Jonathan A.; Evans, Andrew J.; Malleson, Nicolas S.

    2016-01-01

    A widespread approach to investigating the dynamical behaviour of complex social systems is via agent-based models (ABMs). In this paper, we describe how such models can be dynamically calibrated using the ensemble Kalman filter (EnKF), a standard method of data assimilation. Our goal is twofold. First, we want to present the EnKF in a simple setting for the benefit of ABM practitioners who are unfamiliar with it. Second, we want to illustrate to data assimilation experts the value of using such methods in the context of ABMs of complex social systems and the new challenges these types of model present. We work towards these goals within the context of a simple question of practical value: how many people are there in Leeds (or any other major city) right now? We build a hierarchy of exemplar models that we use to demonstrate how to apply the EnKF and calibrate these using open data of footfall counts in Leeds. PMID:27152214

  3. Complexity and Multifractal of Volatility Duration for Agent-Based Financial Dynamics and Real Markets

    NASA Astrophysics Data System (ADS)

    Yang, Ge; Wang, Jun

    2016-11-01

    A random agent-based financial model is developed and investigated by the finite-range multitype contact dynamic system, in an attempt to reproduce and study the dynamics of financial markets. And an analysis method of detecting duration and intensity relationship in volatility series is introduced, called the volatility duration analysis. Then the auto-correlation analysis suggests that there exists evident volatility clustering feature in absolute volatility durations for the simulation data and the real data. Besides, the Lempel-Ziv complexity analysis is applied to study the complexity of the returns, the corresponding absolute returns and the volatility duration returns, which can reflect the fluctuation behaviors, the volatility behaviors and the volatility duration behaviors. At last, the multifractal phenomena of volatility durations of returns are comparatively studied for Shanghai Composite Index and the proposed model by multifractal detrended fluctuation analysis.

  4. Agent-based modeling of host–pathogen systems: The successes and challenges

    PubMed Central

    Bauer, Amy L.; Beauchemin, Catherine A.A.; Perelson, Alan S.

    2009-01-01

    Agent-based models have been employed to describe numerous processes in immunology. Simulations based on these types of models have been used to enhance our understanding of immunology and disease pathology. We review various agent-based models relevant to host–pathogen systems and discuss their contributions to our understanding of biological processes. We then point out some limitations and challenges of agent-based models and encourage efforts towards reproducibility and model validation. PMID:20161146

  5. Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations

    PubMed Central

    Shashkova, Tatiana; Popenko, Anna; Tyakht, Alexander; Peskov, Kirill; Kosinsky, Yuri; Bogolubsky, Lev; Raigorodskii, Andrei; Ischenko, Dmitry; Alexeev, Dmitry; Govorun, Vadim

    2016-01-01

    Background Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes. Methodology/Principal Findings In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery. Conclusion/Significance The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms

  6. Validation techniques of agent based modelling for geospatial simulations

    NASA Astrophysics Data System (ADS)

    Darvishi, M.; Ahmadi, G.

    2014-10-01

    One of the most interesting aspects of modelling and simulation study is to describe the real world phenomena that have specific properties; especially those that are in large scales and have dynamic and complex behaviours. Studying these phenomena in the laboratory is costly and in most cases it is impossible. Therefore, Miniaturization of world phenomena in the framework of a model in order to simulate the real phenomena is a reasonable and scientific approach to understand the world. Agent-based modelling and simulation (ABMS) is a new modelling method comprising of multiple interacting agent. They have been used in the different areas; for instance, geographic information system (GIS), biology, economics, social science and computer science. The emergence of ABM toolkits in GIS software libraries (e.g. ESRI's ArcGIS, OpenMap, GeoTools, etc) for geospatial modelling is an indication of the growing interest of users to use of special capabilities of ABMS. Since ABMS is inherently similar to human cognition, therefore it could be built easily and applicable to wide range applications than a traditional simulation. But a key challenge about ABMS is difficulty in their validation and verification. Because of frequent emergence patterns, strong dynamics in the system and the complex nature of ABMS, it is hard to validate and verify ABMS by conventional validation methods. Therefore, attempt to find appropriate validation techniques for ABM seems to be necessary. In this paper, after reviewing on Principles and Concepts of ABM for and its applications, the validation techniques and challenges of ABM validation are discussed.

  7. Final OSWER Vapor Intrusion Guidance

    EPA Science Inventory

    EPA is preparing to finalize its guidance on assessing and addressing vapor intrusion, which is defined as migration of volatile constituents from contaminated media in the subsurface (soil or groundwater) into the indoor environment. In November 2002, EPA issued draft guidance o...

  8. Appliance of Independent Component Analysis to System Intrusion Analysis

    NASA Astrophysics Data System (ADS)

    Ishii, Yoshikazu; Takagi, Tarou; Nakai, Kouji

    In order to analyze the output of the intrusion detection system and the firewall, we evaluated the applicability of ICA(independent component analysis). We developed a simulator for evaluation of intrusion analysis method. The simulator consists of the network model of an information system, the service model and the vulnerability model of each server, and the action model performed on client and intruder. We applied the ICA for analyzing the audit trail of simulated information system. We report the evaluation result of the ICA on intrusion analysis. In the simulated case, ICA separated two attacks correctly, and related an attack and the abnormalities of the normal application produced under the influence of the attach.

  9. Cloud Intrusion Detection and Repair (CIDAR)

    DTIC Science & Technology

    2016-02-01

    input formats of these applications include three im- age types (PNG, TIFF, JPEG), wave sound (WAV) and Shockwave flash video (SWF). We evaluate the...Errors: We use SOAP to rectify inputs for five applications: Swfdec 0.5.5 (a shockwave player) [18], Dillo 2.1 (a lightweight browser) [4], 23...incorrectly allocate memory or perform an invalid memory access. The input file formats for these errors are the SWF Shockwave Flash format; the PNG

  10. Intrusion detection and monitoring for wireless networks.

    SciTech Connect

    Thomas, Eric D.; Van Randwyk, Jamie A.; Lee, Erik J.; Stephano, Amanda; Tabriz, Parisa; Pelon, Kristen; McCoy, Damon (University of Colorado, Boulder); Lodato, Mark; Hemingway, Franklin; Custer, Ryan P.; Averin, Dimitry; Franklin, Jason; Kilman, Dominique Marie

    2005-11-01

    Wireless computer networks are increasing exponentially around the world. They are being implemented in both the unlicensed radio frequency (RF) spectrum (IEEE 802.11a/b/g) and the licensed spectrum (e.g., Firetide [1] and Motorola Canopy [2]). Wireless networks operating in the unlicensed spectrum are by far the most popular wireless computer networks in existence. The open (i.e., proprietary) nature of the IEEE 802.11 protocols and the availability of ''free'' RF spectrum have encouraged many producers of enterprise and common off-the-shelf (COTS) computer networking equipment to jump into the wireless arena. Competition between these companies has driven down the price of 802.11 wireless networking equipment and has improved user experiences with such equipment. The end result has been an increased adoption of the equipment by businesses and consumers, the establishment of the Wi-Fi Alliance [3], and widespread use of the Alliance's ''Wi-Fi'' moniker to describe these networks. Consumers use 802.11 equipment at home to reduce the burden of running wires in existing construction, facilitate the sharing of broadband Internet services with roommates or neighbors, and increase their range of ''connectedness''. Private businesses and government entities (at all levels) are deploying wireless networks to reduce wiring costs, increase employee mobility, enable non-employees to access the Internet, and create an added revenue stream to their existing business models (coffee houses, airports, hotels, etc.). Municipalities (Philadelphia; San Francisco; Grand Haven, MI) are deploying wireless networks so they can bring broadband Internet access to places lacking such access; offer limited-speed broadband access to impoverished communities; offer broadband in places, such as marinas and state parks, that are passed over by traditional broadband providers; and provide themselves with higher quality, more complete network coverage for use by emergency responders and other municipal agencies. In short, these Wi-Fi networks are being deployed everywhere. Much thought has been and is being put into evaluating cost-benefit analyses of wired vs. wireless networks and issues such as how to effectively cover an office building or municipality, how to efficiently manage a large network of wireless access points (APs), and how to save money by replacing an Internet service provider (ISP) with 802.11 technology. In comparison, very little thought and money are being focused on wireless security and monitoring for security purposes.

  11. Data Mining Approaches for Intrusion Detection

    DTIC Science & Technology

    2007-11-02

    a trace. We applied RIPPER [Coh95], a rule learning program, to our training data. The following learning tasks were formulated to induce the rule...remote attack The testing data includes both normal and abnormal traces not used in the training data. RIPPER outputs a set of if-then rules for the...minority” classes, and a default “true” rule for the remaining class. The following exemplar RIPPER rules were generated from the system call data

  12. Software Decoys: Intrusion Detection and Countermeasures

    DTIC Science & Technology

    2002-06-01

    TCP is a fre- quently called component and known to be susceptible to certain types of attacks, such as that of the “ Cheese ” worm [7] that attempts...calls resulting from the shell commands, the events at other components may need to be instrumented; this is the case for the Cheese worm . Some of...haviors of components of the Unix operating system with the Morris Internet worm . More recent worms , such as “Code Red” and “ Cheese ,” are variants of the

  13. Identifying Evacuees' Demand of Tsunami Shelters using Agent Based Simulation

    NASA Astrophysics Data System (ADS)

    Mas, E.; Adriano, B.; Koshimura, S.; Imamura, F.; Kuroiwa, J.; Yamazaki, F.; Zavala, C.; Estrada, M.

    2012-12-01

    Amongst the lessons learned in tsunami events such as the 2004 Indian Ocean and 2011 Great Tohoku Japan earthquake is that sometimes nature exceeds structural countermeasures like seawalls, breakwaters or tsunami gates. In such situations it is a challenging task for people in plain areas to find sheltering places. The vertical evacuation to multistory buildings is one alternative to provide areas for sheltering in a complex environment of evacuation. However, if the spatial distribution and the available capacity of these structures are not well displayed, conditions of evacuee over-demand or under-demand might be observed in several structures. In this study, we present the integration of the tsunami numerical modeling and the agent based simulation of evacuation as the method to estimate the sheltering demand of evacuees in an emergent behavior approach. The case study is set in La Punta district in Peru. Here, we used in the tsunami simulation a seismic source of slip distribution model (Pulido et.al. ,2011; Chlieh et.al, 2011) for a possible future tsunami scenario in the central Andes. We modeled three alternatives of evacuation. First, the horizontal evacuation scenario was analyzed to support the necessity of the sheltering-in-place option for the district. Second, the vertical evacuation scenario and third, the combination of vertical and horizontal evacuation scenarios of pedestrians and vehicles were conducted. In the last two alternatives, the demand of evacuees were measured at each official tsunami evacuation building and compared to the sheltering capacity of the structure. Results showed that out of twenty tsunami evacuation buildings, thirteen resulted with over-demands and seven were still with available space. Also it is confirmed that in this case the horizontal evacuation might lead to a high number of casualties due to the traffic congestion at the neck of the district. Finally the vertical evacuation would be a suitable solution for this area

  14. How Saccade Intrusions Affect Subsequent Motor and Oculomotor Actions

    PubMed Central

    Terao, Yasuo; Fukuda, Hideki; Tokushige, Shin-ichi; Inomata-Terada, Satomi; Ugawa, Yoshikazu

    2017-01-01

    In daily activities, there is a close spatial and temporal coupling between eye and hand movements that enables human beings to perform actions smoothly and accurately. If this coupling is disrupted by inadvertent saccade intrusions, subsequent motor actions suffer from delays, and lack of coordination. To examine how saccade intrusions affect subsequent voluntary actions, we used two tasks that require subjects to make motor/oculomotor actions in response to a visual cue. One was the memory guided saccade (MGS) task, and the other the hand reaction time (RT) task. The MGS task required subjects to initiate a voluntary saccade to a memorized target location, which is indicated shortly before by a briefly presented cue. The RT task required subjects to release a button on detection of a visual target, while foveating on a central fixation point. In normal subjects of various ages, inadvertent saccade intrusions delayed subsequent voluntary motor, and oculomotor actions. We also studied patients with Parkinson's disease (PD), who are impaired not only in initiating voluntary saccades but also in suppressing unwanted reflexive saccades. Saccade intrusions also delayed hand RT in PD patients. However, MGS was affected by the saccade intrusion differently. Saccade intrusion did not delay MGS latency in PD patients who could perform MGS with a relatively normal latency. In contrast, in PD patients who were unable to initiate MGS within the normal time range, we observed slightly decreased MGS latency after saccade intrusions. What explains this paradoxical phenomenon? It is known that motor actions slow down when switching between controlled and automatic behavior. We discuss how the effect of saccade intrusions on subsequent voluntary motor/oculomotor actions may reflect a similar switching cost between automatic and controlled behavior and a cost for switching between different motor effectors. In contrast, PD patients were unable to initiate internally guided MGS in

  15. How Saccade Intrusions Affect Subsequent Motor and Oculomotor Actions.

    PubMed

    Terao, Yasuo; Fukuda, Hideki; Tokushige, Shin-Ichi; Inomata-Terada, Satomi; Ugawa, Yoshikazu

    2016-01-01

    In daily activities, there is a close spatial and temporal coupling between eye and hand movements that enables human beings to perform actions smoothly and accurately. If this coupling is disrupted by inadvertent saccade intrusions, subsequent motor actions suffer from delays, and lack of coordination. To examine how saccade intrusions affect subsequent voluntary actions, we used two tasks that require subjects to make motor/oculomotor actions in response to a visual cue. One was the memory guided saccade (MGS) task, and the other the hand reaction time (RT) task. The MGS task required subjects to initiate a voluntary saccade to a memorized target location, which is indicated shortly before by a briefly presented cue. The RT task required subjects to release a button on detection of a visual target, while foveating on a central fixation point. In normal subjects of various ages, inadvertent saccade intrusions delayed subsequent voluntary motor, and oculomotor actions. We also studied patients with Parkinson's disease (PD), who are impaired not only in initiating voluntary saccades but also in suppressing unwanted reflexive saccades. Saccade intrusions also delayed hand RT in PD patients. However, MGS was affected by the saccade intrusion differently. Saccade intrusion did not delay MGS latency in PD patients who could perform MGS with a relatively normal latency. In contrast, in PD patients who were unable to initiate MGS within the normal time range, we observed slightly decreased MGS latency after saccade intrusions. What explains this paradoxical phenomenon? It is known that motor actions slow down when switching between controlled and automatic behavior. We discuss how the effect of saccade intrusions on subsequent voluntary motor/oculomotor actions may reflect a similar switching cost between automatic and controlled behavior and a cost for switching between different motor effectors. In contrast, PD patients were unable to initiate internally guided MGS in

  16. From Agents to Continuous Change via Aesthetics: Learning Mechanics with Visual Agent-Based Computational Modeling

    ERIC Educational Resources Information Center

    Sengupta, Pratim; Farris, Amy Voss; Wright, Mason

    2012-01-01

    Novice learners find motion as a continuous process of change challenging to understand. In this paper, we present a pedagogical approach based on agent-based, visual programming to address this issue. Integrating agent-based programming, in particular, Logo programming, with curricular science has been shown to be challenging in previous research…

  17. The Agent-based Approach: A New Direction for Computational Models of Development.

    ERIC Educational Resources Information Center

    Schlesinger, Matthew; Parisi, Domenico

    2001-01-01

    Introduces the concepts of online and offline sampling and highlights the role of online sampling in agent-based models of learning and development. Compares the strengths of each approach for modeling particular developmental phenomena and research questions. Describes a recent agent-based model of infant causal perception. Discusses limitations…

  18. A Systematic Review of Agent-Based Modelling and Simulation Applications in the Higher Education Domain

    ERIC Educational Resources Information Center

    Gu, X.; Blackmore, K. L.

    2015-01-01

    This paper presents the results of a systematic review of agent-based modelling and simulation (ABMS) applications in the higher education (HE) domain. Agent-based modelling is a "bottom-up" modelling paradigm in which system-level behaviour (macro) is modelled through the behaviour of individual local-level agent interactions (micro).…

  19. Applications of Agent Based Approaches in Business (A Three Essay Dissertation)

    ERIC Educational Resources Information Center

    Prawesh, Shankar

    2013-01-01

    The goal of this dissertation is to investigate the enabling role that agent based simulation plays in business and policy. The aforementioned issue has been addressed in this dissertation through three distinct, but related essays. The first essay is a literature review of different research applications of agent based simulation in various…

  20. Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions

    PubMed Central

    Lawley, Mark A.; Siscovick, David S.; Zhang, Donglan; Pagán, José A.

    2016-01-01

    The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions. PMID:27236380

  1. Agent-Based Modeling of Chronic Diseases: A Narrative Review and Future Research Directions.

    PubMed

    Li, Yan; Lawley, Mark A; Siscovick, David S; Zhang, Donglan; Pagán, José A

    2016-05-26

    The United States is experiencing an epidemic of chronic disease. As the US population ages, health care providers and policy makers urgently need decision models that provide systematic, credible prediction regarding the prevention and treatment of chronic diseases to improve population health management and medical decision-making. Agent-based modeling is a promising systems science approach that can model complex interactions and processes related to chronic health conditions, such as adaptive behaviors, feedback loops, and contextual effects. This article introduces agent-based modeling by providing a narrative review of agent-based models of chronic disease and identifying the characteristics of various chronic health conditions that must be taken into account to build effective clinical- and policy-relevant models. We also identify barriers to adopting agent-based models to study chronic diseases. Finally, we discuss future research directions of agent-based modeling applied to problems related to specific chronic health conditions.

  2. Zircon Recycling in Arc Intrusions

    NASA Astrophysics Data System (ADS)

    Miller, J.; Barth, A.; Matzel, J.; Wooden, J.; Burgess, S.

    2008-12-01

    Recycling of zircon has been well established in arc intrusions and arc volcanoes, but a better understanding of where and how zircons are recycled can help illuminate how arc magma systems are constructed. To that end, we are conducting age, trace element (including Ti-in-zircon temperatures; TzrnTi) and isotopic studies of zircons from the Late Cretaceous (95-85 Ma) Tuolumne Intrusive Suite (TIS) in the Sierra Nevada Batholith (CA). Within the TIS zircons inherited from ancient basement sources and/or distinctly older host rocks are uncommon, but recycled zircon antecrysts from earlier periods of TIS-related magmatism are common and conspicuous in the inner and two most voluminous units of the TIS, the Half Dome and Cathedral Peak Granodiorites. All TIS units have low bulk Zr ([Zr]<150 ppm) and thus low calculated zircon saturation temperatures (Tzrnsat). Within the Half Dome and Cathedral Peak, TzrnTi values are predominantly at or below average Tzrnsat, and there is no apparent correlation between age and TzrnTi. At temperatures appropriate for granodiorite/tonalite melt generation (at or above biotite dehydration; >825°C), [Zr] in the TIS is a factor of 2 to 3 lower than saturation values. Low [Zr] in TIS rocks might be attributed to a very limited supply of zircon in the source, by disequilibrium melting and rapid melt extraction [1], by melting reactions involving formation of other phases that can incorporate appreciable Zr [2], or by removal of zircon at an earlier stage of magma evolution. Based on a preliminary compilation of literature data, low [Zr] is common to Late Cretaceous N.A. Cordilleran granodioritic/tonalitic intrusions (typically <200 ppm and frequently 100-150 ppm for individual large intrusions or intrusive suites). We infer from this that [Zr] in anatectic melts is probably not limited by zircon supply and is primarily controlled by melting parameters. Comparison of the data from TIS with one of these intrusions, the smaller but otherwise

  3. Evaluation of intrusion sensors and video assessment in areas of restricted passage

    SciTech Connect

    Hoover, C.E.; Ringler, C.E.

    1996-04-01

    This report discusses an evaluation of intrusion sensors and video assessment in areas of restricted passage. The discussion focuses on applications of sensors and video assessment in suspended ceilings and air ducts. It also includes current and proposed requirements for intrusion detection and assessment. Detection and nuisance alarm characteristics of selected sensors as well as assessment capabilities of low-cost board cameras were included in the evaluation.

  4. Brief introductory guide to agent-based modeling and an illustration from urban health research.

    PubMed

    Auchincloss, Amy H; Garcia, Leandro Martin Totaro

    2015-11-01

    There is growing interest among urban health researchers in addressing complex problems using conceptual and computation models from the field of complex systems. Agent-based modeling (ABM) is one computational modeling tool that has received a lot of interest. However, many researchers remain unfamiliar with developing and carrying out an ABM, hindering the understanding and application of it. This paper first presents a brief introductory guide to carrying out a simple agent-based model. Then, the method is illustrated by discussing a previously developed agent-based model, which explored inequalities in diet in the context of urban residential segregation.

  5. A Hybrid Sensitivity Analysis Approach for Agent-based Disease Spread Models

    SciTech Connect

    Pullum, Laura L; Cui, Xiaohui

    2012-01-01

    Agent-based models (ABM) have been widely deployed in different fields for studying the collective behavior of large numbers of interacting agents. Of particular interest lately is the application of agent-based and hybrid models to epidemiology, specifically Agent-based Disease Spread Models (ABDSM). Validation (one aspect of the means to achieve dependability) of ABDSM simulation models is extremely important. It ensures that the right model has been built and lends confidence to the use of that model to inform critical decisions. In this report, we describe our preliminary efforts in ABDSM validation by using hybrid model fusion technology.

  6. Mafic intrusions triggering eruptions in Iceland

    NASA Astrophysics Data System (ADS)

    Sigmarsson, O.

    2012-04-01

    The last two eruptions in Iceland, Eyjafjallajökull 2010 and Grímsvötn 2011, were both provoked by an intrusion of more mafic magma into pre-existing magmatic system. Injection into the latter volcano, which is located in the main rift-zone of the island, above the presumed centre of the mantle plume and is the most active volcano of Iceland, has been gradual since the last eruption in 2004. In contrast, at Eyjafjallajökull volcano, one of the least active volcano in Iceland and located at the southern part of a propagating rift-zone where extensional tectonics are poorly developed, mafic magma intrusion occurred over less than a year. Beneath Eyjafjallajökull, a silicic intrusion at approximately 6 km depth was recharged with mantle derived alkali basalt that was injected into residual rhyolite from the penultimate eruption in the years 1821-23. The resulting magma mingIing process was highly complex, but careful sampling of tephra during the entire eruption allows the dynamics of the mingling process to be unravelled. Short-lived disequilibria between the gaseous nuclide 210Po and the much less volatile nuclide 210Pb, suggest that basalt accumulated beneath the silicic intrusion over approximately 100 days, or from early January 2010 until the onset of the explosive summit eruption on 14 April. Due to the degassing, crystal fractionation modified the composition of the injected mafic magma producing evolved Fe-and Ti-rich basalt, similar in composition to that of the nearby Katla volcano. This evolved basalt was intruded into the liquid part of the silicic intrusion only a few hours before the onset of the explosive summit eruption. The short time between intrusion and eruption led to the production of very heterogeneous (of basaltic, intermediate and silicic composition) and fine-grained tephra during the first days of explosive eruption. The fine grained tephra resulted from combined effects of magma fragmentation due to degassing of stiff magma rich in

  7. Deciphering chemokine properties by a hybrid agent-based model of Aspergillus fumigatus infection in human alveoli

    PubMed Central

    Pollmächer, Johannes; Figge, Marc Thilo

    2015-01-01

    The ubiquitous airborne fungal pathogen Aspergillus fumigatus is inhaled by humans every day. In the lung, it is able to quickly adapt to the humid environment and, if not removed within a time frame of 4–8 h, the pathogen may cause damage by germination and invasive growth. Applying a to-scale agent-based model of human alveoli to simulate early A. fumigatus infection under physiological conditions, we recently demonstrated that alveolar macrophages require chemotactic cues to accomplish the task of pathogen detection within the aforementioned time frame. The objective of this study is to specify our general prediction on the as yet unidentified chemokine by a quantitative analysis of its expected properties, such as the diffusion coefficient and the rates of secretion and degradation. To this end, the rule-based implementation of chemokine diffusion in the initial agent-based model is revised by numerically solving the spatio-temporal reaction-diffusion equation in the complex structure of the alveolus. In this hybrid agent-based model, alveolar macrophages are represented as migrating agents that are coupled to the interactive layer of diffusing molecule concentrations by the kinetics of chemokine receptor binding, internalization and re-expression. Performing simulations for more than a million virtual infection scenarios, we find that the ratio of secretion rate to the diffusion coefficient is the main indicator for the success of pathogen detection. Moreover, a subdivision of the parameter space into regimes of successful and unsuccessful parameter combination by this ratio is specific for values of the migration speed and the directional persistence time of alveolar macrophages, but depends only weakly on chemokine degradation rates. PMID:26074897

  8. Sea Water Intrusion in Kaligawe Semarang Based on Resistivity Data

    NASA Astrophysics Data System (ADS)

    Setyawan, Agus; Najib; Aribowo, Yoga; Trihadini, Agnis; Hastuti, Dhana; Ramdhani, Fitra; Waskito, Fajar; Febrika, Ganap; Virgiawan, Galang

    2017-02-01

    Semarang is a city on the north coast of the island of Java, Indonesia and it is lowland areas have experienced sea water intrusion. One of interesting area is Kaligawe which located at Eastern part of Semarang. Kaligawe has big population and industrial and it need water consumption. Excessive extraction of groundwater will be resulting height difference surface ground water to the surface of the sea water due to sea water intrusion. Electric resistivity method was used to detect for salt water intrusion. Dipole-dipole configuration was applied with 3 lines to get current, potential difference, and apparent resistivity from the field. 2D model has presented using Res2Dinv to get the true resistivity and the depth of each layer. A calibration of the model was conducted based on geological information. Result showed the subsurface area has 4 layers: sandstone, sandsilt, siltstone and clay. Moreover the sea water intrusion occurs in the Northwest, East and Southern part of the study area

  9. Absorptivity of molded soil-improving agents based on brown coals and zeolites

    SciTech Connect

    Aleksandrov, I.V.; Kossov, I.I.

    1993-12-31

    The objective of this work was to create a new technique for producing molded soil-improving agents based on brown coal from the Adunchulun deposit, and to determine the soil-improving properties of the obtained compositions.

  10. An international perspective on Facebook intrusion.

    PubMed

    Błachnio, Agata; Przepiorka, Aneta; Benvenuti, Martina; Cannata, Davide; Ciobanu, Adela Magdalena; Senol-Durak, Emre; Durak, Mithat; Giannakos, Michail N; Mazzoni, Elvis; Pappas, Ilias O; Popa, Camelia; Seidman, Gwendolyn; Yu, Shu; Wu, Anise M S; Ben-Ezra, Menachem

    2016-08-30

    Facebook has become one of the most popular social networking websites in the world. The main aim of the study was to present an international comparison of Facebook intrusion and Internet penetration while examining possible gender differences. The study consisted of 2589 participants from eight countries: China, Greece, Israel, Italy, Poland, Romania, Turkey, USA. Facebook intrusion and Internet penetration were taken into consideration. In this study the relationship between Facebook intrusion and Internet penetration was demonstrated. Facebook intrusion was slightly negatively related to Internet penetration in each country.

  11. Friendship Network and Dental Brushing Behavior among Middle School Students: An Agent Based Modeling Approach

    PubMed Central

    Sadeghipour, Maryam; Khoshnevisan, Mohammad Hossein; Jafari, Afshin; Shariatpanahi, Seyed Peyman

    2017-01-01

    By using a standard questionnaire, the level of dental brushing frequency was assessed among 201 adolescent female middle school students in Tehran. The initial assessment was repeated after 5 months, in order to observe the dynamics in dental health behavior level. Logistic Regression model was used to evaluate the correlation among individuals’ dental health behavior in their social network. A significant correlation on dental brushing habits was detected among groups of friends. This correlation was further spread over the network within the 5 months period. Moreover, it was identified that the average brushing level was improved within the 5 months period. Given that there was a significant correlation between social network’s nodes’ in-degree value, and brushing level, it was suggested that the observed improvement was partially due to more popularity of individuals with better tooth brushing habit. Agent Based Modeling (ABM) was used to demonstrate the dynamics of dental brushing frequency within a sample of friendship network. Two models with static and dynamic assumptions for the network structure were proposed. The model with dynamic network structure successfully described the dynamics of dental health behavior. Based on this model, on average, every 43 weeks a student changes her brushing habit due to learning from her friends. Finally, three training scenarios were tested by these models in order to evaluate their effectiveness. When training more popular students, considerable improvement in total students’ brushing frequency was demonstrated by simulation results. PMID:28103260

  12. Friendship Network and Dental Brushing Behavior among Middle School Students: An Agent Based Modeling Approach.

    PubMed

    Sadeghipour, Maryam; Khoshnevisan, Mohammad Hossein; Jafari, Afshin; Shariatpanahi, Seyed Peyman

    2017-01-01

    By using a standard questionnaire, the level of dental brushing frequency was assessed among 201 adolescent female middle school students in Tehran. The initial assessment was repeated after 5 months, in order to observe the dynamics in dental health behavior level. Logistic Regression model was used to evaluate the correlation among individuals' dental health behavior in their social network. A significant correlation on dental brushing habits was detected among groups of friends. This correlation was further spread over the network within the 5 months period. Moreover, it was identified that the average brushing level was improved within the 5 months period. Given that there was a significant correlation between social network's nodes' in-degree value, and brushing level, it was suggested that the observed improvement was partially due to more popularity of individuals with better tooth brushing habit. Agent Based Modeling (ABM) was used to demonstrate the dynamics of dental brushing frequency within a sample of friendship network. Two models with static and dynamic assumptions for the network structure were proposed. The model with dynamic network structure successfully described the dynamics of dental health behavior. Based on this model, on average, every 43 weeks a student changes her brushing habit due to learning from her friends. Finally, three training scenarios were tested by these models in order to evaluate their effectiveness. When training more popular students, considerable improvement in total students' brushing frequency was demonstrated by simulation results.

  13. Temporal asymmetries in Interbank Market: an empirically grounded Agent-Based Model

    NASA Astrophysics Data System (ADS)

    Zlatic, Vinko; Popovic, Marko; Abraham, Hrvoje; Caldarelli, Guido; Iori, Giulia

    2014-03-01

    We analyse the changes in the topology of the structure of the E-mid interbank market in the period from September 1st 1999 to September 1st 2009. We uncover a type of temporal irreversibility in the growth of the largest component of the interbank trading network, which is not common to any of the usual network growth models. Such asymmetry, which is also detected on the growth of the clustering and reciprocity coefficient, reveals that the trading mechanism is driven by different dynamics at the beginning and at the end of the day. We are able to recover the complexity of the system by means of a simple Agent Based Model in which the probability of matching between counter parties depends on a time varying vertex fitness (or attractiveness) describing banks liquidity needs. We show that temporal irreversibility is associated with heterogeneity in the banking system and emerges when the distribution of liquidity shocks across banks is broad. We acknowledge support from FET project FOC-II.

  14. Developing a Conceptual Architecture for a Generalized Agent-based Modeling Environment (GAME)

    DTIC Science & Technology

    2008-03-01

    possible. A conceptual architecture for a generalized agent- based modeling environment (GAME) based upon design principles from OR/MS systems was created...conceptual architecture for a generalized agent-based modeling environment (GAME) based upon design principles from OR/MS systems was created that...handle the event, and subsequently form the relevant plans. One of these plans will be selected, and either pushed to the top of the current

  15. Agent-based modeling: Methods and techniques for simulating human systems

    PubMed Central

    Bonabeau, Eric

    2002-01-01

    Agent-based modeling is a powerful simulation modeling technique that has seen a number of applications in the last few years, including applications to real-world business problems. After the basic principles of agent-based simulation are briefly introduced, its four areas of application are discussed by using real-world applications: flow simulation, organizational simulation, market simulation, and diffusion simulation. For each category, one or several business applications are described and analyzed. PMID:12011407

  16. Context-Driven Decision Making in Network-Centric Operations: Agent-Based Intelligent Support

    DTIC Science & Technology

    2006-01-01

    SPIIRAS CKM Workshop (MIT, Cambridge, MA; January 24, 2006 Context-Driven Decision Making in Network-Centric Operations: Agent- Based Intelligent...Operations: Agent- Based Intelligent Support 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK...Enterprise and Multi-Agent Systems (Engineering and Physical Sciences Research Council, UK, 2003-2005) Ontology- Based New Order Code Generation for

  17. Agent based reasoning for the non-linear stochastic models of long-range memory

    NASA Astrophysics Data System (ADS)

    Kononovicius, A.; Gontis, V.

    2012-02-01

    We extend Kirman's model by introducing variable event time scale. The proposed flexible time scale is equivalent to the variable trading activity observed in financial markets. Stochastic version of the extended Kirman's agent based model is compared to the non-linear stochastic models of long-range memory in financial markets. The agent based model providing matching macroscopic description serves as a microscopic reasoning of the earlier proposed stochastic model exhibiting power law statistics.

  18. Agents Based e-Commerce and Securing Exchanged Information

    NASA Astrophysics Data System (ADS)

    Al-Jaljouli, Raja; Abawajy, Jemal

    Mobile agents have been implemented in e-Commerce to search and filter information of interest from electronic markets. When the information is very sensitive and critical, it is important to develop a novel security protocol that can efficiently protect the information from malicious tampering as well as unauthorized disclosure or at least detect any malicious act of intruders. In this chapter, we describe robust security techniques that ensure a sound security of information gathered throughout agent’s itinerary against various security attacks, as well as truncation attacks. A sound security protocol is described, which implements the various security techniques that would jointly prevent or at least detect any malicious act of intruders. We reason about the soundness of the protocol usingSymbolic Trace Analyzer (STA), a formal verification tool that is based on symbolic techniques. We analyze the protocol in key configurations and show that it is free of flaws. We also show that the protocol fulfils the various security requirements of exchanged information in MAS, including data-integrity, data-confidentiality, data-authenticity, origin confidentiality and data non-repudiability.

  19. Non-intrusive speed sensor

    NASA Technical Reports Server (NTRS)

    Wyett, L.

    1986-01-01

    In Phase I of the Non-Intrusive Speed Sensor program, a computerized literature search was performed to identify candidate technologies for remote, non-intrusive speed sensing applications in Space Shuttle Main Engine (SSME) turbopumps. The three most promising technologies were subjected to experimental evaluation to quantify their performance characteristics under the harsh environmental requirements within the turbopumps. Although the infrared and microwave approaches demonstrated excellent cavitation immunity in laboratory tests, the variable-source magnetic speed sensor emerged as the most viable approach. Preliminary design of this speed sensor encountered no technical obstacles and resulted in viable and feasible speed nut, sensor housing, and sensor coil designs. Phase II of this program developed the variable-source magnetic speed sensor through the detailed design task and guided the design into breadboard fabrication. The speed sensor and its integral speed nut were evaluated at both unit and system level testing. The final room-temperature and cryogenic spin testing of the hardware demonstrated that the sensor was capable of generating sufficient output signal to enable remote speed sensing from 1500 to 40000 rpm over a speed nut/sensor separation of 3.5 inches.

  20. Intrusive Images in Psychological Disorders

    PubMed Central

    Brewin, Chris R.; Gregory, James D.; Lipton, Michelle; Burgess, Neil

    2010-01-01

    Involuntary images and visual memories are prominent in many types of psychopathology. Patients with posttraumatic stress disorder, other anxiety disorders, depression, eating disorders, and psychosis frequently report repeated visual intrusions corresponding to a small number of real or imaginary events, usually extremely vivid, detailed, and with highly distressing content. Both memory and imagery appear to rely on common networks involving medial prefrontal regions, posterior regions in the medial and lateral parietal cortices, the lateral temporal cortex, and the medial temporal lobe. Evidence from cognitive psychology and neuroscience implies distinct neural bases to abstract, flexible, contextualized representations (C-reps) and to inflexible, sensory-bound representations (S-reps). We revise our previous dual representation theory of posttraumatic stress disorder to place it within a neural systems model of healthy memory and imagery. The revised model is used to explain how the different types of distressing visual intrusions associated with clinical disorders arise, in terms of the need for correct interaction between the neural systems supporting S-reps and C-reps via visuospatial working memory. Finally, we discuss the treatment implications of the new model and relate it to existing forms of psychological therapy. PMID:20063969

  1. A Conceptual Framework for Representing Human Behavior Characteristics in a System of Systems Agent-Based Survivability Simulation

    DTIC Science & Technology

    2010-11-22

    distribution is unlimited. A CONCEPTUAL FRAMEWORK FOR REPRESENTING HUMAN BEHAVIOR CHARACTERISTICS IN A SYSTEM OF SYSTEMS AGENT-BASED SURVIVABILITY...27411 -0001 ABSTRACT A CONCEPTUAL FRAMEWORK FOR REPRESENTING HUMAN BEHAVIOR CHARACTERISTICS IN A SYSTEM OF SYSTEMS AGENT-BASED SURVIVABILITY SIMULATION...TITLE AND SUBTITLE A CONCEPTUAL FRAMEWORK FOR REPRESENTING HUMAN BEHAVIOR CHARACTERISTICS IN A SYSTEM OF SYSTEMS AGENT-BASED SURVIVABILITY

  2. Legal Vs. Psychological Aspects of Intrusiveness.

    ERIC Educational Resources Information Center

    Binder, Virginia L.

    Court decisions stressing the rights of mental patients have necessitated a radical revision in the management of behavioral treatment programs. The client's rights to the least intrusive procedures to achieve treatment goals have become important in case law. Factors which identify intrusiveness include: (1) the extent to which the "new…

  3. A Teacher's Checklist for Evaluating Treatment Intrusiveness

    ERIC Educational Resources Information Center

    Carter, Stacy L.; Mayton, Michael R.; Wheeler, John J.

    2011-01-01

    Teachers are frequently involved in developing and evaluating treatments for problematic behaviors. Along with other members of the interdisciplinary team, they must determine the level of intrusiveness that a treatment may have on a student. Several factors that influence the intrusiveness of treatment procedures are described. These factors were…

  4. Vapour Intrusion into Buildings - A Literature Review

    EPA Science Inventory

    This chapter provides a review of recent research on vapour intrusion of volatile organic compounds (VOCs) into buildings. The chapter builds on a report from Tillman and Weaver (2005) which reviewed the literature on vapour intrusion through 2005. Firstly, the term ‘vapour intru...

  5. Real Time Intrusion Detection (la detection des intrusions en temps reel)

    DTIC Science & Technology

    2003-06-01

    modelled by extended finite state machines . They examined the performance of these techniques, for real-time monitoring of communication networks, from both...widely used to avoid side -effect “Denial Of Service” attacks. The third presentation (Massicotte, Whalen and Bilodeau) was on a prototype network... machines , indicates the state and shows configuration information about the hosts and their connectivity. To query network components, the tool uses

  6. Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

    PubMed

    Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

    2015-09-01

    This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach.

  7. SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

    PubMed

    Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

    2010-01-01

    Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

  8. An extensible simulation environment and movement metrics for testing walking behavior in agent-based models

    SciTech Connect

    Paul M. Torrens; Atsushi Nara; Xun Li; Haojie Zhu; William A. Griffin; Scott B. Brown

    2012-01-01

    Human movement is a significant ingredient of many social, environmental, and technical systems, yet the importance of movement is often discounted in considering systems complexity. Movement is commonly abstracted in agent-based modeling (which is perhaps the methodological vehicle for modeling complex systems), despite the influence of movement upon information exchange and adaptation in a system. In particular, agent-based models of urban pedestrians often treat movement in proxy form at the expense of faithfully treating movement behavior with realistic agency. There exists little consensus about which method is appropriate for representing movement in agent-based schemes. In this paper, we examine popularly-used methods to drive movement in agent-based models, first by introducing a methodology that can flexibly handle many representations of movement at many different scales and second, introducing a suite of tools to benchmark agent movement between models and against real-world trajectory data. We find that most popular movement schemes do a relatively poor job of representing movement, but that some schemes may well be 'good enough' for some applications. We also discuss potential avenues for improving the representation of movement in agent-based frameworks.

  9. Going beyond the unitary curve: incorporating richer cognition into agent-based water resources models

    NASA Astrophysics Data System (ADS)

    Kock, B. E.

    2008-12-01

    The increased availability and understanding of agent-based modeling technology and techniques provides a unique opportunity for water resources modelers, allowing them to go beyond traditional behavioral approaches from neoclassical economics, and add rich cognition to social-hydrological models. Agent-based models provide for an individual focus, and the easier and more realistic incorporation of learning, memory and other mechanisms for increased cognitive sophistication. We are in an age of global change impacting complex water resources systems, and social responses are increasingly recognized as fundamentally adaptive and emergent. In consideration of this, water resources models and modelers need to better address social dynamics in a manner beyond the capabilities of neoclassical economics theory and practice. However, going beyond the unitary curve requires unique levels of engagement with stakeholders, both to elicit the richer knowledge necessary for structuring and parameterizing agent-based models, but also to make sure such models are appropriately used. With the aim of encouraging epistemological and methodological convergence in the agent-based modeling of water resources, we have developed a water resources-specific cognitive model and an associated collaborative modeling process. Our cognitive model emphasizes efficiency in architecture and operation, and capacity to adapt to different application contexts. We describe a current application of this cognitive model and modeling process in the Arkansas Basin of Colorado. In particular, we highlight the potential benefits of, and challenges to, using more sophisticated cognitive models in agent-based water resources models.

  10. Automated multi-objective calibration of biological agent-based simulations.

    PubMed

    Read, Mark N; Alden, Kieran; Rose, Louis M; Timmis, Jon

    2016-09-01

    Computational agent-based simulation (ABS) is increasingly used to complement laboratory techniques in advancing our understanding of biological systems. Calibration, the identification of parameter values that align simulation with biological behaviours, becomes challenging as increasingly complex biological domains are simulated. Complex domains cannot be characterized by single metrics alone, rendering simulation calibration a fundamentally multi-metric optimization problem that typical calibration techniques cannot handle. Yet calibration is an essential activity in simulation-based science; the baseline calibration forms a control for subsequent experimentation and hence is fundamental in the interpretation of results. Here, we develop and showcase a method, built around multi-objective optimization, for calibrating ABSs against complex target behaviours requiring several metrics (termed objectives) to characterize. Multi-objective calibration (MOC) delivers those sets of parameter values representing optimal trade-offs in simulation performance against each metric, in the form of a Pareto front. We use MOC to calibrate a well-understood immunological simulation against both established a priori and previously unestablished target behaviours. Furthermore, we show that simulation-borne conclusions are broadly, but not entirely, robust to adopting baseline parameter values from different extremes of the Pareto front, highlighting the importance of MOC's identification of numerous calibration solutions. We devise a method for detecting overfitting in a multi-objective context, not previously possible, used to save computational effort by terminating MOC when no improved solutions will be found. MOC can significantly impact biological simulation, adding rigour to and speeding up an otherwise time-consuming calibration process and highlighting inappropriate biological capture by simulations that cannot be well calibrated. As such, it produces more accurate

  11. Equation-free analysis of agent-based models and systematic parameter determination

    NASA Astrophysics Data System (ADS)

    Thomas, Spencer A.; Lloyd, David J. B.; Skeldon, Anne C.

    2016-12-01

    Agent based models (ABM)s are increasingly used in social science, economics, mathematics, biology and computer science to describe time dependent systems in circumstances where a description in terms of equations is difficult. Yet few tools are currently available for the systematic analysis of ABM behaviour. Numerical continuation and bifurcation analysis is a well-established tool for the study of deterministic systems. Recently, equation-free (EF) methods have been developed to extend numerical continuation techniques to systems where the dynamics are described at a microscopic scale and continuation of a macroscopic property of the system is considered. To date, the practical use of EF methods has been limited by; (1) the over-head of application-specific implementation; (2) the laborious configuration of problem-specific parameters; and (3) large ensemble sizes (potentially) leading to computationally restrictive run-times. In this paper we address these issues with our tool for the EF continuation of stochastic systems, which includes algorithms to systematically configuration problem specific parameters and enhance robustness to noise. Our tool is generic and can be applied to any 'black-box' simulator and determines the essential EF parameters prior to EF analysis. Robustness is significantly improved using our convergence-constraint with a corrector-repeat (C3R) method. This algorithm automatically detects outliers based on the dynamics of the underlying system enabling both an order of magnitude reduction in ensemble size and continuation of systems at much higher levels of noise than classical approaches. We demonstrate our method with application to several ABM models, revealing parameter dependence, bifurcation and stability analysis of these complex systems giving a deep understanding of the dynamical behaviour of the models in a way that is not otherwise easily obtainable. In each case we demonstrate our systematic parameter determination stage for

  12. Pattern-oriented modeling of agent-based complex systems: Lessons from ecology

    USGS Publications Warehouse

    Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M.; Railsback, Steven F.; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L.

    2005-01-01

    Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

  13. Examining the Impact of the Walking School Bus With an Agent-Based Model

    PubMed Central

    Diez-Roux, Ana; Evenson, Kelly R.; Colabianchi, Natalie

    2014-01-01

    We used an agent-based model to examine the impact of the walking school bus (WSB) on children’s active travel to school. We identified a synergistic effect of the WSB with other intervention components such as an educational campaign designed to improve attitudes toward active travel to school. Results suggest that to maximize active travel to school, children should arrive on time at “bus stops” to allow faster WSB walking speeds. We also illustrate how an agent-based model can be used to identify the location of routes maximizing the effects of the WSB on active travel. Agent-based models can be used to examine plausible effects of the WSB on active travel to school under various conditions and to identify ways of implementing the WSB that maximize its effectiveness. PMID:24832410

  14. Demeter, persephone, and the search for emergence in agent-based models.

    SciTech Connect

    North, M. J.; Howe, T. R.; Collier, N. T.; Vos, J. R.; Decision and Information Sciences; Univ. of Chicago; PantaRei Corp.; Univ. of Illinois

    2006-01-01

    In Greek mythology, the earth goddess Demeter was unable to find her daughter Persephone after Persephone was abducted by Hades, the god of the underworld. Demeter is said to have embarked on a long and frustrating, but ultimately successful, search to find her daughter. Unfortunately, long and frustrating searches are not confined to Greek mythology. In modern times, agent-based modelers often face similar troubles when searching for agents that are to be to be connected to one another and when seeking appropriate target agents while defining agent behaviors. The result is a 'search for emergence' in that many emergent or potentially emergent behaviors in agent-based models of complex adaptive systems either implicitly or explicitly require search functions. This paper considers a new nested querying approach to simplifying such agent-based modeling and multi-agent simulation search problems.

  15. Pattern-oriented modeling of agent-based complex systems: lessons from ecology.

    PubMed

    Grimm, Volker; Revilla, Eloy; Berger, Uta; Jeltsch, Florian; Mooij, Wolf M; Railsback, Steven F; Thulke, Hans-Hermann; Weiner, Jacob; Wiegand, Thorsten; DeAngelis, Donald L

    2005-11-11

    Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity.

  16. The role of estrogen in intrusive memories.

    PubMed

    Cheung, Jessica; Chervonsky, Liza; Felmingham, Kim L; Bryant, Richard A

    2013-11-01

    Intrusive memories are highly vivid, emotional and involuntary recollections which cause significant distress across psychological disorders including posttraumatic disorder (PTSD). Recent evidence has potentially extended our understanding of the development of intrusive memories by identifying biological factors which significantly impact on memories for emotionally arousing stimuli. This study investigated the role of stress on the development of intrusions for negative and neutral images, and indexed the potential contributions of sex (estrogen and progesterone) and stress (noradrenaline and cortisol) hormones. Whilst viewing the images, half the participants underwent a cold pressor stress (CPS) procedure to induce stress while the control participants immersed their hands in warm water. Saliva samples were collected to index estrogen, progesterone and noradrenergic and cortisol response. Participants (55 university students, 26 men, 29 women) viewed a series of negatively arousing and neutral images. Participants completed recall and intrusions measures 2 days later. Negative images resulted in greater recall and more intrusions than neutral images. In the cold water condition females recalled fewer neutral memories than males. Cortisol increase predicted decreased recall of negative memories in males, and estrogen predicted increased intrusions of negative images in women. These findings are consistent with evidence that circulating levels of ovarian hormones influence memory for emotionally arousing events, and provides the first evidence of the influence of sex hormones on intrusive memories. These results provide one possible explanation for the higher incidence of anxiety disorders in women.

  17. Consentaneous Agent-Based and Stochastic Model of the Financial Markets

    PubMed Central

    Gontis, Vygintas; Kononovicius, Aleksejus

    2014-01-01

    We are looking for the agent-based treatment of the financial markets considering necessity to build bridges between microscopic, agent based, and macroscopic, phenomenological modeling. The acknowledgment that agent-based modeling framework, which may provide qualitative and quantitative understanding of the financial markets, is very ambiguous emphasizes the exceptional value of well defined analytically tractable agent systems. Herding as one of the behavior peculiarities considered in the behavioral finance is the main property of the agent interactions we deal with in this contribution. Looking for the consentaneous agent-based and macroscopic approach we combine two origins of the noise: exogenous one, related to the information flow, and endogenous one, arising form the complex stochastic dynamics of agents. As a result we propose a three state agent-based herding model of the financial markets. From this agent-based model we derive a set of stochastic differential equations, which describes underlying macroscopic dynamics of agent population and log price in the financial markets. The obtained solution is then subjected to the exogenous noise, which shapes instantaneous return fluctuations. We test both Gaussian and q-Gaussian noise as a source of the short term fluctuations. The resulting model of the return in the financial markets with the same set of parameters reproduces empirical probability and spectral densities of absolute return observed in New York, Warsaw and NASDAQ OMX Vilnius Stock Exchanges. Our result confirms the prevalent idea in behavioral finance that herding interactions may be dominant over agent rationality and contribute towards bubble formation. PMID:25029364

  18. Consentaneous agent-based and stochastic model of the financial markets.

    PubMed

    Gontis, Vygintas; Kononovicius, Aleksejus

    2014-01-01

    We are looking for the agent-based treatment of the financial markets considering necessity to build bridges between microscopic, agent based, and macroscopic, phenomenological modeling. The acknowledgment that agent-based modeling framework, which may provide qualitative and quantitative understanding of the financial markets, is very ambiguous emphasizes the exceptional value of well defined analytically tractable agent systems. Herding as one of the behavior peculiarities considered in the behavioral finance is the main property of the agent interactions we deal with in this contribution. Looking for the consentaneous agent-based and macroscopic approach we combine two origins of the noise: exogenous one, related to the information flow, and endogenous one, arising form the complex stochastic dynamics of agents. As a result we propose a three state agent-based herding model of the financial markets. From this agent-based model we derive a set of stochastic differential equations, which describes underlying macroscopic dynamics of agent population and log price in the financial markets. The obtained solution is then subjected to the exogenous noise, which shapes instantaneous return fluctuations. We test both Gaussian and q-Gaussian noise as a source of the short term fluctuations. The resulting model of the return in the financial markets with the same set of parameters reproduces empirical probability and spectral densities of absolute return observed in New York, Warsaw and NASDAQ OMX Vilnius Stock Exchanges. Our result confirms the prevalent idea in behavioral finance that herding interactions may be dominant over agent rationality and contribute towards bubble formation.

  19. Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

    NASA Technical Reports Server (NTRS)

    Shameldin, Ramez Ahmed; Bowling, Shannon R.

    2010-01-01

    The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

  20. Agent-Based Modeling of Cancer Stem Cell Driven Solid Tumor Growth.

    PubMed

    Poleszczuk, Jan; Macklin, Paul; Enderling, Heiko

    2016-01-01

    Computational modeling of tumor growth has become an invaluable tool to simulate complex cell-cell interactions and emerging population-level dynamics. Agent-based models are commonly used to describe the behavior and interaction of individual cells in different environments. Behavioral rules can be informed and calibrated by in vitro assays, and emerging population-level dynamics may be validated with both in vitro and in vivo experiments. Here, we describe the design and implementation of a lattice-based agent-based model of cancer stem cell driven tumor growth.

  1. A Distributed Platform for Global-Scale Agent-Based Models of Disease Transmission

    PubMed Central

    Parker, Jon; Epstein, Joshua M.

    2013-01-01

    The Global-Scale Agent Model (GSAM) is presented. The GSAM is a high-performance distributed platform for agent-based epidemic modeling capable of simulating a disease outbreak in a population of several billion agents. It is unprecedented in its scale, its speed, and its use of Java. Solutions to multiple challenges inherent in distributing massive agent-based models are presented. Communication, synchronization, and memory usage are among the topics covered in detail. The memory usage discussion is Java specific. However, the communication and synchronization discussions apply broadly. We provide benchmarks illustrating the GSAM’s speed and scalability. PMID:24465120

  2. Spatial process and data models : toward integration of agent-based models and GIS.

    SciTech Connect

    Brown, D. G.; North, M. J.; Robinson, D. T.; Riolo, R.; Rand, W.; Decision and Information Sciences; Univ. of Michigan

    2007-10-01

    The use of object-orientation for both spatial data and spatial process models facilitates their integration, which can allow exploration and explanation of spatial-temporal phenomena. In order to better understand how tight coupling might proceed and to evaluate the possible functional and efficiency gains from such a tight coupling, we identify four key relationships affecting how geographic data (fields and objects) and agent-based process models can interact: identity, causal, temporal and topological. We discuss approaches to implementing tight integration, focusing on a middleware approach that links existing GIS and ABM development platforms, and illustrate the need and approaches with example agent-based models.

  3. An agent-based computational model for tuberculosis spreading on age-structured populations

    NASA Astrophysics Data System (ADS)

    Graciani Rodrigues, C. C.; Espíndola, Aquino L.; Penna, T. J. P.

    2015-06-01

    In this work we present an agent-based computational model to study the spreading of the tuberculosis (TB) disease on age-structured populations. The model proposed is a merge of two previous models: an agent-based computational model for the spreading of tuberculosis and a bit-string model for biological aging. The combination of TB with the population aging, reproduces the coexistence of health states, as seen in real populations. In addition, the universal exponential behavior of mortalities curves is still preserved. Finally, the population distribution as function of age shows the prevalence of TB mostly in elders, for high efficacy treatments.

  4. UAV Swarm Tactics: An Agent-Based Simulation and Markov Process Analysis

    DTIC Science & Technology

    2013-06-01

    NPS NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS UAV SWARM TACTICS: AN AGENT-BASED SIM ULATION AND MARKOV PROCESS ANALYSIS Thesis...inina; tho d ... _ . aod oompiotinl and ~_i .. tho roIloction of .. form. tion. Sond oommonu fQPrdina; thi!; burdon Mlim. m 0< a ny <>tho< ...,oct...TACTICS : AN AGENT-BASED SIMULATION AND MARKOV PROCESS ANALYSIS 1 So. " NUMBER ’. AU 1 Sd. PROJECT Uwe Gaertner 1 s.. TASK NUMBER 1 sr. WORK UNIT

  5. An Agent-Based Model for Studying Child Maltreatment and Child Maltreatment Prevention

    NASA Astrophysics Data System (ADS)

    Hu, Xiaolin; Puddy, Richard W.

    This paper presents an agent-based model that simulates the dynamics of child maltreatment and child maltreatment prevention. The developed model follows the principles of complex systems science and explicitly models a community and its families with multi-level factors and interconnections across the social ecology. This makes it possible to experiment how different factors and prevention strategies can affect the rate of child maltreatment. We present the background of this work and give an overview of the agent-based model and show some simulation results.

  6. Detection and Tracking Based on a Dynamical Hierarchical Occupancy Map in Agent-Based Simulations

    DTIC Science & Technology

    2008-09-01

    called pold . The new p(v) is the sum of the new incoming probability and the outgoing probability to the next nodes. Each edge from one node to...Output: Graph G’ For every active vertex v of G’ Copy p(v) in pold (v) For every edge E outgoing Get target node v’ p(v’) = p(v’) + (1...cost of E)* pold (v) p(v) = p(v) – (1/cost of E)* pold (v) 36 values are too small to make a reasonable search process. Therefore, there must be

  7. Frequency analysis of tick quotes on the foreign exchange market and agent-based modeling: A spectral distance approach

    NASA Astrophysics Data System (ADS)

    Sato, Aki-Hiro

    2007-08-01

    High-frequency financial data of the foreign exchange market (EUR/CHF, EUR/GBP, EUR/JPY, EUR/NOK, EUR/SEK, EUR/USD, NZD/USD, USD/CAD, USD/CHF, USD/JPY, USD/NOK, and USD/SEK) are analyzed by utilizing the Kullback-Leibler divergence between two normalized spectrograms of the tick frequency and the generalized Jensen-Shannon divergence among them. The temporal structure variations of the similarity between currency pairs is detected and characterized. A simple agent-based model in which N market participants exchange M currency pairs is proposed. The equation for the tick frequency is approximately derived theoretically. Based on the analysis of this model, the spectral distance of the tick frequency is associated with the similarity of the behavior (perception and decision) of the market participants in exchanging these currency pairs.

  8. Indoor Air Vapor Intrusion Mitigation Approaches

    EPA Pesticide Factsheets

    The National Risk Management Research Laboratory has developed a technology transfer document regarding management and treatment of vapor intrusion into building structures. This document describes the range of mitigation technologies available.

  9. A Citizen's Guide to Vapor Intrusion Mitigation

    EPA Pesticide Factsheets

    This guide describes how vapor intrusion is the movement of chemical vapors from contaminated soil and groundwater into nearby buildings.Vapors primarily enter through openings in the building foundation or basement walls.

  10. 10 CFR 63.322 - Human intrusion scenario.

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 2 2011-01-01 2011-01-01 false Human intrusion scenario. 63.322 Section 63.322 Energy... REPOSITORY AT YUCCA MOUNTAIN, NEVADA Postclosure Public Health and Environmental Standards Human Intrusion Standard § 63.322 Human intrusion scenario. For the purposes of the analysis of human intrusion, DOE...

  11. 10 CFR 63.322 - Human intrusion scenario.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 2 2010-01-01 2010-01-01 false Human intrusion scenario. 63.322 Section 63.322 Energy... REPOSITORY AT YUCCA MOUNTAIN, NEVADA Postclosure Public Health and Environmental Standards Human Intrusion Standard § 63.322 Human intrusion scenario. For the purposes of the analysis of human intrusion, DOE...

  12. A General Model for Shallow Magmatic Intrusions

    NASA Astrophysics Data System (ADS)

    Thorey, C.; Michaut, C.

    2015-12-01

    Shallow magmatic intrusions make room for themselves by upward bending of the elastic overburden. Previous studies have shown that the bending of the overlying layer first controls the dynamics. Then, when the radius reaches a few times the flexural wavelength of the overburden, it transitions to a gravity current regime. This model predicts the appropriate geometry for both terrestrial laccoliths and large mafic sills. However, it underestimates the absolute dimensions of these magmatic intrusions; in particular, it requires abnormally high viscosity to reconcile both observations and predictions. To get some insights into the effective flow viscosity, we develop a model that account for the cooling of such elastic-plated gravity currents. We show that the coupling between the temperature field and the flow itself leads to the formation of a highly viscous region at the tip that slows down the spreading in both regimes. The intrusions are predicted to be thicker and their dimensions, especially in the bending regime, are now consistent with observations. By introducing the potentially complex structure of the overburden, we also show that the topography largely contributes to constrain the final intrusion morphology. For instance, in the case of an intrusion centered below a circular depression, the model predicts that the lithostatic increase at the crater rim prevents the magma from spreading laterally and enhances the thickening of the intrusion. This model has already proven successful in reproducing the deformations observed on potential intrusion centered below lunar impact craters. Caldera complexes often exhibit ground deformations that might be associated to the formation of shallow magmatic intrusions. InSAR imaging and GPS measurements now provide efficient tools to monitor these deformations. We conclude this study by examining the ability of the model to reproduce the deformation observed in several caldera complexes.

  13. Preventing Point-of-Sale System Intrusions

    DTIC Science & Technology

    2014-06-01

    month Crimina l intent may be more focused on identity theft than payme nt card fraud 37 Unknown Zero day or custom keylogger TBD TBD 4...Several major United States retailers have suffered large-scale thefts of payment card information as the result of intrusions against point-of-sale...ABSTRACT Several major United States retailers have suffered large-scale thefts of payment card information as the result of intrusions against point

  14. Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

    ERIC Educational Resources Information Center

    Dickes, Amanda Catherine; Sengupta, Pratim

    2013-01-01

    In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…

  15. Formalizing the role of agent-based modeling in causal inference and epidemiology.

    PubMed

    Marshall, Brandon D L; Galea, Sandro

    2015-01-15

    Calls for the adoption of complex systems approaches, including agent-based modeling, in the field of epidemiology have largely centered on the potential for such methods to examine complex disease etiologies, which are characterized by feedback behavior, interference, threshold dynamics, and multiple interacting causal effects. However, considerable theoretical and practical issues impede the capacity of agent-based methods to examine and evaluate causal effects and thus illuminate new areas for intervention. We build on this work by describing how agent-based models can be used to simulate counterfactual outcomes in the presence of complexity. We show that these models are of particular utility when the hypothesized causal mechanisms exhibit a high degree of interdependence between multiple causal effects and when interference (i.e., one person's exposure affects the outcome of others) is present and of intrinsic scientific interest. Although not without challenges, agent-based modeling (and complex systems methods broadly) represent a promising novel approach to identify and evaluate complex causal effects, and they are thus well suited to complement other modern epidemiologic methods of etiologic inquiry.

  16. Lapse of time effects on tax evasion in an agent-based econophysics model

    NASA Astrophysics Data System (ADS)

    Seibold, Götz; Pickhardt, Michael

    2013-05-01

    We investigate an inhomogeneous Ising model in the context of tax evasion dynamics where different types of agents are parameterized via local temperatures and magnetic fields. In particular, we analyze the impact of lapse of time effects (i.e. backauditing) and endogenously determined penalty rates on tax compliance. Both features contribute to a microfoundation of agent-based econophysics models of tax evasion.

  17. Data-driven agent-based modeling, with application to rooftop solar adoption

    DOE PAGES

    Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua; ...

    2016-01-25

    Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends andmore » provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.« less

  18. Ensuring congruency in multiscale modeling: towards linking agent based and continuum biomechanical models of arterial adaptation.

    PubMed

    Hayenga, Heather N; Thorne, Bryan C; Peirce, Shayn M; Humphrey, Jay D

    2011-11-01

    There is a need to develop multiscale models of vascular adaptations to understand tissue-level manifestations of cellular level mechanisms. Continuum-based biomechanical models are well suited for relating blood pressures and flows to stress-mediated changes in geometry and properties, but less so for describing underlying mechanobiological processes. Discrete stochastic agent-based models are well suited for representing biological processes at a cellular level, but not for describing tissue-level mechanical changes. We present here a conceptually new approach to facilitate the coupling of continuum and agent-based models. Because of ubiquitous limitations in both the tissue- and cell-level data from which one derives constitutive relations for continuum models and rule-sets for agent-based models, we suggest that model verification should enforce congruency across scales. That is, multiscale model parameters initially determined from data sets representing different scales should be refined, when possible, to ensure that common outputs are consistent. Potential advantages of this approach are illustrated by comparing simulated aortic responses to a sustained increase in blood pressure predicted by continuum and agent-based models both before and after instituting a genetic algorithm to refine 16 objectively bounded model parameters. We show that congruency-based parameter refinement not only yielded increased consistency across scales, it also yielded predictions that are closer to in vivo observations.

  19. Using Agent-Based Technologies to Enhance Learning in Educational Games

    ERIC Educational Resources Information Center

    Tumenayu, Ogar Ofut; Shabalina, Olga; Kamaev, Valeriy; Davtyan, Alexander

    2014-01-01

    Recent research has shown that educational games positively motivate learning. However, there is a little evidence that they can trigger learning to a large extent if the game-play is supported by additional activities. We aim to support educational games development with an Agent-Based Technology (ABT) by using intelligent pedagogical agents that…

  20. The Impact of a Peer-Learning Agent Based on Pair Programming in a Programming Course

    ERIC Educational Resources Information Center

    Han, Keun-Woo; Lee, EunKyoung; Lee, YoungJun

    2010-01-01

    This paper analyzes the educational effects of a peer-learning agent based on pair programming in programming courses. A peer-learning agent system was developed to facilitate the learning of a programming language through the use of pair programming strategies. This system is based on the role of a peer-learning agent from pedagogical and…

  1. Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

    NASA Technical Reports Server (NTRS)

    Campbell, Kenyth

    2012-01-01

    The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

  2. Developing an Argument Learning Environment Using Agent-Based ITS (ALES)

    ERIC Educational Resources Information Center

    Abbas, Safia; Sawamura, Hajime

    2009-01-01

    This paper presents an agent-based educational environment to teach argument analysis (ALES). The idea is based on the Argumentation Interchange Format Ontology (AIF)using "Walton Theory". ALES uses different mining techniques to manage a highly structured arguments repertoire. This repertoire was designed, developed and implemented by us. Our aim…

  3. Synthesized Population Databases: A US Geospatial Database for Agent-Based Models.

    PubMed

    Wheaton, William D; Cajka, James C; Chasteen, Bernadette M; Wagener, Diane K; Cooley, Philip C; Ganapathi, Laxminarayana; Roberts, Douglas J; Allpress, Justine L

    2009-05-01

    Agent-based models simulate large-scale social systems. They assign behaviors and activities to "agents" (individuals) within the population being modeled and then allow the agents to interact with the environment and each other in complex simulations. Agent-based models are frequently used to simulate infectious disease outbreaks, among other uses.RTI used and extended an iterative proportional fitting method to generate a synthesized, geospatially explicit, human agent database that represents the US population in the 50 states and the District of Columbia in the year 2000. Each agent is assigned to a household; other agents make up the household occupants.For this database, RTI developed the methods for generating synthesized households and personsassigning agents to schools and workplaces so that complex interactions among agents as they go about their daily activities can be taken into accountgenerating synthesized human agents who occupy group quarters (military bases, college dormitories, prisons, nursing homes).In this report, we describe both the methods used to generate the synthesized population database and the final data structure and data content of the database. This information will provide researchers with the information they need to use the database in developing agent-based models.Portions of the synthesized agent database are available to any user upon request. RTI will extract a portion (a county, region, or state) of the database for users who wish to use this database in their own agent-based models.

  4. An agent-based simulation of extirpation of Ceratitis capitata applied to invasions in California

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We describe and validate an Agent-Based Simulation(ABS) of invasive insects and use it to investigate the time to extirpation of Ceratitis capitata using data from seven outbreaks that occurred in California from 2008-2010. Results are compared with the length of intervention and quarantine imposed ...

  5. Numerical Problems and Agent-Based Models for a Mass Transfer Course

    ERIC Educational Resources Information Center

    Murthi, Manohar; Shea, Lonnie D.; Snurr, Randall Q.

    2009-01-01

    Problems requiring numerical solutions of differential equations or the use of agent-based modeling are presented for use in a course on mass transfer. These problems were solved using the popular technical computing language MATLABTM. Students were introduced to MATLAB via a problem with an analytical solution. A more complex problem to which no…

  6. Agent-Based Learning Environments as a Research Tool for Investigating Teaching and Learning.

    ERIC Educational Resources Information Center

    Baylor, Amy L.

    2002-01-01

    Discusses intelligent learning environments for computer-based learning, such as agent-based learning environments, and their advantages over human-based instruction. Considers the effects of multiple agents; agents and research design; the use of Multiple Intelligent Mentors Instructing Collaboratively (MIMIC) for instructional design for…

  7. High performance computing for three-dimensional agent-based molecular models.

    PubMed

    Pérez-Rodríguez, G; Pérez-Pérez, M; Fdez-Riverola, F; Lourenço, A

    2016-07-01

    Agent-based simulations are increasingly popular in exploring and understanding cellular systems, but the natural complexity of these systems and the desire to grasp different modelling levels demand cost-effective simulation strategies and tools. In this context, the present paper introduces novel sequential and distributed approaches for the three-dimensional agent-based simulation of individual molecules in cellular events. These approaches are able to describe the dimensions and position of the molecules with high accuracy and thus, study the critical effect of spatial distribution on cellular events. Moreover, two of the approaches allow multi-thread high performance simulations, distributing the three-dimensional model in a platform independent and computationally efficient way. Evaluation addressed the reproduction of molecular scenarios and different scalability aspects of agent creation and agent interaction. The three approaches simulate common biophysical and biochemical laws faithfully. The distributed approaches show improved performance when dealing with large agent populations while the sequential approach is better suited for small to medium size agent populations. Overall, the main new contribution of the approaches is the ability to simulate three-dimensional agent-based models at the molecular level with reduced implementation effort and moderate-level computational capacity. Since these approaches have a generic design, they have the major potential of being used in any event-driven agent-based tool.

  8. Research on monocentric model of urbanization by agent-based simulation

    NASA Astrophysics Data System (ADS)

    Xue, Ling; Yang, Kaizhong

    2008-10-01

    Over the past years, GIS have been widely used for modeling urbanization from a variety of perspectives such as digital terrain representation and overlay analysis using cell-based data platform. Similarly, simulation of urban dynamics has been achieved with the use of Cellular Automata. In contrast to these approaches, agent-based simulation provides a much more powerful set of tools. This allows researchers to set up a counterpart for real environmental and urban systems in computer for experimentation and scenario analysis. This Paper basically reviews the research on the economic mechanism of urbanization and an agent-based monocentric model is setup for further understanding the urbanization process and mechanism in China. We build an endogenous growth model with dynamic interactions between spatial agglomeration and urban development by using agent-based simulation. It simulates the migration decisions of two main types of agents, namely rural and urban households between rural and urban area. The model contains multiple economic interactions that are crucial in understanding urbanization and industrial process in China. These adaptive agents can adjust their supply and demand according to the market situation by a learning algorithm. The simulation result shows this agent-based urban model is able to perform the regeneration and to produce likely-to-occur projections of reality.

  9. Data-driven agent-based modeling, with application to rooftop solar adoption

    SciTech Connect

    Zhang, Haifeng; Vorobeychik, Yevgeniy; Letchford, Joshua; Lakkaraju, Kiran

    2016-01-25

    Agent-based modeling is commonly used for studying complex system properties emergent from interactions among many agents. We present a novel data-driven agent-based modeling framework applied to forecasting individual and aggregate residential rooftop solar adoption in San Diego county. Our first step is to learn a model of individual agent behavior from combined data of individual adoption characteristics and property assessment. We then construct an agent-based simulation with the learned model embedded in artificial agents, and proceed to validate it using a holdout sequence of collective adoption decisions. We demonstrate that the resulting agent-based model successfully forecasts solar adoption trends and provides a meaningful quantification of uncertainty about its predictions. We utilize our model to optimize two classes of policies aimed at spurring solar adoption: one that subsidizes the cost of adoption, and another that gives away free systems to low-income house- holds. We find that the optimal policies derived for the latter class are significantly more efficacious, whereas the policies similar to the current California Solar Initiative incentive scheme appear to have a limited impact on overall adoption trends.

  10. Permutations of Control: Cognitive Considerations for Agent-Based Learning Environments

    ERIC Educational Resources Information Center

    Baylor, Amy L.

    2004-01-01

    While there has been a significant amount of research on technical issues regarding the development of agent-based learning environments (e.g., see the special issue of Journal of "Interactive Learning Research," 10(3/4)), there is less information regarding cognitive foundations for these environments. The management of control is a prime issue…

  11. Permutations of Control: Cognitive Considerations for Agent-Based Learning Environments.

    ERIC Educational Resources Information Center

    Baylor, Amy L.

    2001-01-01

    Discussion of intelligent agents and their use in computer learning environments focuses on cognitive considerations. Presents four dimension of control that should be considered in designing agent-based learning environments: learner control, from constructivist to instructivist; feedback; relationship of learner to agent; and learner confidence…

  12. Tropospheric intrusions associated with the secondary tropopause

    NASA Astrophysics Data System (ADS)

    Pan, L. L.; Randel, W. J.; Gille, J. C.; Hall, W. D.; Nardi, B.; Massie, S.; Yudin, V.; Khosravi, R.; Konopka, P.; Tarasick, D.

    2009-05-01

    Deep intrusions of tropospheric air into the lower stratosphere above the subtropical jet are investigated using new observations and meteorological analyses. These intrusions are characterized by low ozone concentration and low static stability. The low-ozone layer is consistently observed from ozonesonde profiles and satellite remote sensing data from Aura/HIRDLS. The intruding layer occurs along and under the poleward extending tropical tropopause, which becomes the secondary tropopause in middle to high latitudes. The association of the ozone and the thermal structure provides evidence for the physical significance of the subtropical tropopause break and the secondary tropopause. The core of the intruding layer is typically between 370 and 400 K potential temperature (˜15 km), but the vertical extent of the intrusion can impact ozone above 400 K, the lower boundary of the overworld. Two intrusion events over the continental United States in the spring of 2007 are analyzed to show the spatial extent and the temporal evolution of the intruding air mass. These examples demonstrate the effectiveness of potential temperature lapse rate, i.e., static stability, as a diagnostic for the intrusion event. Comparison with the potential vorticity field is made to show the complementarity of the two dynamical fields. The static stability diagnostic provides a tool to map out the horizontal extent of the intruding layer and to investigate its evolution. Furthermore, the diagnostic makes it possible to forecast the intrusion event for field studies.

  13. Modeling sill intrusion in volcanic calderas

    NASA Astrophysics Data System (ADS)

    Macedonio, Giovanni; Giudicepietro, Flora; D'Auria, Luca; Martini, Marcello

    2015-04-01

    We present a numerical model for describing sill intrusion in volcanic calderas. The dynamics of volcanic calderas are often subject to long-term unrests, with remarkable ground deformation, seismicity, and geochemical changes, that do not culminate in an eruption. On the contrary, in some cases, unrests with minor geophysical changes are followed, in few months, by an eruption, as in the case of Rabaul Caldera in 1994 and Sierra Negra (Galapagos) in 2005. The main common features of calderas are the relevant ground deformations with intense uplift episodes, often followed by subsidence. We think that the process of sill intrusion can explain the common features observed on different calderas. In our model, the sill, fed by a deeper magma reservoir, intrudes below a horizontal elastic plate, representing the overlying rocks and expands radially. The model is based on the numerical solution of the equation for the elastic plate, coupled with a Navier-Stokes equation for simulating magma intrusion in the viscous regime. The numerical simulations show that during the feeding process, the ground is subject to uplift. When the feeding stops a subsidence occurs in the central zone. For very low flexural rigidity of the elastic plate, the subsidence can occur even during the intrusion of the sill. The stress field produced by the intrusion is mainly concentrated in a circular zone that follows the sill intrusion front.

  14. Efficacy and Safety of Novel Agent-Based Therapies for Multiple Myeloma: A Meta-Analysis

    PubMed Central

    Wang, Xiaoxue; Li, Yan; Yan, Xiaojing

    2016-01-01

    This study aimed at comparing bortezomib, thalidomide, and lenalidomide in patients with multiple myeloma (MM) for safety and efficacy using meta-analysis. This meta-analysis identified 17 randomized controlled trials (RCTs) including 6742 patients. These RCTs were separated according to the different agent-based regimens and to autologous stem-cell transplantation (ASCT). Complete response (CR), progression-free survival (PFS), overall survival (OS), and adverse events (AE) were combined. The total weighted risk ratio (RR) of CR was 3.29 [95% confidence interval (95% CI): 2.22–4.88] (P < 0.0001) for the novel agent-based regimens. These novel agent-based regimens showed greater benefit in terms of PFS of all subgroups irrespective of whether the patient received ASCT or not. The hazard ratio (HR) for PFS was 0.64 [95% CI: 0.60–0.69] (P < 0.00001). Improvements of OS could be found only in the bortezomib- and thalidomide-based regimens without ASCT. The pooled HRs were 0.74 [95% CI: 0.65–0.86] (P < 0.0001) and 0.80 [95% CI: 0.70–0.90] (P = 0.0004), respectively. Several AEs were shown more frequently in the novel agent-based regimens compared with controls such as hematologic events (neutropenia, anemia, and thrombocytopenia), gastrointestinal infection, peripheral neuropathy, thrombosis, and embolism events. In conclusion, in spite of the AEs, novel agent-based regimens are safe and effective for the treatment of MM. PMID:26949704

  15. Comparing stochastic differential equations and agent-based modelling and simulation for early-stage cancer.

    PubMed

    Figueredo, Grazziela P; Siebers, Peer-Olaf; Owen, Markus R; Reps, Jenna; Aickelin, Uwe

    2014-01-01

    There is great potential to be explored regarding the use of agent-based modelling and simulation as an alternative paradigm to investigate early-stage cancer interactions with the immune system. It does not suffer from some limitations of ordinary differential equation models, such as the lack of stochasticity, representation of individual behaviours rather than aggregates and individual memory. In this paper we investigate the potential contribution of agent-based modelling and simulation when contrasted with stochastic versions of ODE models using early-stage cancer examples. We seek answers to the following questions: (1) Does this new stochastic formulation produce similar results to the agent-based version? (2) Can these methods be used interchangeably? (3) Do agent-based models outcomes reveal any benefit when compared to the Gillespie results? To answer these research questions we investigate three well-established mathematical models describing interactions between tumour cells and immune elements. These case studies were re-conceptualised under an agent-based perspective and also converted to the Gillespie algorithm formulation. Our interest in this work, therefore, is to establish a methodological discussion regarding the usability of different simulation approaches, rather than provide further biological insights into the investigated case studies. Our results show that it is possible to obtain equivalent models that implement the same mechanisms; however, the incapacity of the Gillespie algorithm to retain individual memory of past events affects the similarity of some results. Furthermore, the emergent behaviour of ABMS produces extra patters of behaviour in the system, which was not obtained by the Gillespie algorithm.

  16. Sewer Gas: An Indoor Air Source of PCE to Consider During Vapor Intrusion Investigations.

    PubMed

    Pennell, Kelly G; Scammell, Madeleine Kangsen; McClean, Michael D; Ames, Jennifer; Weldon, Brittany; Friguglietti, Leigh; Suuberg, Eric M; Shen, Rui; Indeglia, Paul A; Heiger-Bernays, Wendy J

    2013-01-01

    The United States Environmental Protection Agency (USEPA) is finalizing its vapor intrusion guidelines. One of the important issues related to vapor intrusion is background concentrations of volatile organic chemicals (VOCs) in indoor air, typically attributed to consumer products and building materials. Background concentrations can exist even in the absence of vapor intrusion and are an important consideration when conducting site assessments. In addition, the development of accurate conceptual models that depict pathways for vapor entry into buildings is important during vapor intrusion site assessments. Sewer gas, either as a contributor to background concentrations or as part of the site conceptual model, is not routinely evaluated during vapor intrusion site assessments. The research described herein identifies an instance where vapors emanating directly from a sanitary sewer pipe within a residence were determined to be a source of tetrachloroethylene (PCE) detected in indoor air. Concentrations of PCE in the bathroom range from 2.1 to 190 ug/m(3) and exceed typical indoor air concentrations by orders of magnitude resulting in human health risk classified as an "Imminent Hazard" condition. The results suggest that infiltration of sewer gas resulted in PCE concentrations in indoor air that were nearly two-orders of magnitude higher as compared to when infiltration of sewer gas was not known to be occurring. This previously understudied pathway whereby sewers serve as sources of PCE (and potentially other VOC) vapors is highlighted. Implications for vapor intrusion investigations are also discussed.

  17. Sewer Gas: An Indoor Air Source of PCE to Consider During Vapor Intrusion Investigations

    PubMed Central

    Pennell, Kelly G.; Scammell, Madeleine Kangsen; McClean, Michael D.; Ames, Jennifer; Weldon, Brittany; Friguglietti, Leigh; Suuberg, Eric M.; Shen, Rui; Indeglia, Paul A.; Heiger-Bernays, Wendy J.

    2013-01-01

    The United States Environmental Protection Agency (USEPA) is finalizing its vapor intrusion guidelines. One of the important issues related to vapor intrusion is background concentrations of volatile organic chemicals (VOCs) in indoor air, typically attributed to consumer products and building materials. Background concentrations can exist even in the absence of vapor intrusion and are an important consideration when conducting site assessments. In addition, the development of accurate conceptual models that depict pathways for vapor entry into buildings is important during vapor intrusion site assessments. Sewer gas, either as a contributor to background concentrations or as part of the site conceptual model, is not routinely evaluated during vapor intrusion site assessments. The research described herein identifies an instance where vapors emanating directly from a sanitary sewer pipe within a residence were determined to be a source of tetrachloroethylene (PCE) detected in indoor air. Concentrations of PCE in the bathroom range from 2.1 to 190 ug/m3 and exceed typical indoor air concentrations by orders of magnitude resulting in human health risk classified as an “Imminent Hazard” condition. The results suggest that infiltration of sewer gas resulted in PCE concentrations in indoor air that were nearly two-orders of magnitude higher as compared to when infiltration of sewer gas was not known to be occurring. This previously understudied pathway whereby sewers serve as sources of PCE (and potentially other VOC) vapors is highlighted. Implications for vapor intrusion investigations are also discussed. PMID:23950637

  18. Agent-based evacuation simulation for spatial allocation assessment of urban shelters

    NASA Astrophysics Data System (ADS)

    Yu, Jia; Wen, Jiahong; Jiang, Yong

    2015-12-01

    The construction of urban shelters is one of the most important work in urban planning and disaster prevention. The spatial allocation assessment is a fundamental pre-step for spatial location-allocation of urban shelters. This paper introduces a new method which makes use of agent-based technology to implement evacuation simulation so as to conduct dynamic spatial allocation assessment of urban shelters. The method can not only accomplish traditional geospatial evaluation for urban shelters, but also simulate the evacuation process of the residents to shelters. The advantage of utilizing this method lies into three aspects: (1) the evacuation time of each citizen from a residential building to the shelter can be estimated more reasonably; (2) the total evacuation time of all the residents in a region is able to be obtained; (3) the road congestions in evacuation in sheltering can be detected so as to take precautionary measures to prevent potential risks. In this study, three types of agents are designed: shelter agents, government agents and resident agents. Shelter agents select specified land uses as shelter candidates for different disasters. Government agents delimitate the service area of each shelter, in other words, regulate which shelter a person should take, in accordance with the administrative boundaries and road distance between the person's position and the location of the shelter. Resident agents have a series of attributes, such as ages, positions, walking speeds, and so on. They also have several behaviors, such as reducing speed when walking in the crowd, helping old people and children, and so on. Integrating these three types of agents which are correlated with each other, evacuation procedures can be simulated and dynamic allocation assessment of shelters will be achieved. A case study in Jing'an District, Shanghai, China, was conducted to demonstrate the feasibility of the method. A scenario of earthquake disaster which occurs in nighttime

  19. Agent-Based Model of Human Alveoli Predicts Chemotactic Signaling by Epithelial Cells during Early Aspergillus fumigatus Infection

    PubMed Central

    Pollmächer, Johannes; Figge, Marc Thilo

    2014-01-01

    Aspergillus fumigatus is one of the most important human fungal pathogens, causing life-threatening diseases. Since humans inhale hundreds to thousands of fungal conidia every day, the lower respiratory tract is the primary site of infection. Current interaction networks of the innate immune response attribute fungal recognition and detection to alveolar macrophages, which are thought to be the first cells to get in contact with the fungus. At present, these networks are derived from in vitro or in situ assays, as the peculiar physiology of the human lung makes in vivo experiments, including imaging on the cell-level, hard to realize. We implemented a spatio-temporal agent-based model of a human alveolus in order to perform in silico experiments of a virtual infection scenario, for an alveolus infected with A. fumigatus under physiological conditions. The virtual analog captures the three-dimensional alveolar morphology consisting of the two major alveolar epithelial cell types and the pores of Kohn as well as the dynamic process of respiration. To the best of our knowledge this is the first agent-based model of a dynamic human alveolus in the presence of respiration. A key readout of our simulations is the first-passage-time of alveolar macrophages, which is the period of time that elapses until the first physical macrophage-conidium contact is established. We tested for random and chemotactic migration modes of alveolar macrophages and varied their corresponding parameter sets. The resulting first-passage-time distributions imply that randomly migrating macrophages fail to find the conidium before the start of germination, whereas guidance by chemotactic signals derived from the alveolar epithelial cell associated with the fungus enables a secure and successful discovery of the pathogen in time. PMID:25360787

  20. Smart container UWB sensor system for situational awareness of intrusion alarms

    DOEpatents

    Romero, Carlos E.; Haugen, Peter C.; Zumstein, James M.; Leach, Jr., Richard R.; Vigars, Mark L.

    2013-06-11

    An in-container monitoring sensor system is based on an UWB radar intrusion detector positioned in a container and having a range gate set to the farthest wall of the container from the detector. Multipath reflections within the container make every point on or in the container appear to be at the range gate, allowing intrusion detection anywhere in the container. The system also includes other sensors to provide false alarm discrimination, and may include other sensors to monitor other parameters, e.g. radiation. The sensor system also includes a control subsystem for controlling system operation. Communications and information extraction capability may also be included. A method of detecting intrusion into a container uses UWB radar, and may also include false alarm discrimination. A secure container has an UWB based monitoring system

  1. Nuclear-power-plant perimeter-intrusion alarm systems

    SciTech Connect

    Halsey, D.J.

    1982-04-01

    Timely intercept of an intruder requires the examination of perimeter barriers and sensors in terms of reliable detection, immediate assessment and prompt response provisions. Perimeter security equipment and operations must at the same time meet the requirements of the Code of Federal Regulations, 10 CFR 73.55 with some attention to the performance and testing figures of Nuclear Regulatory Guide 5.44, Revision 2, May 1980. A baseline system is defined which recommends a general approach to implementing perimeter security elements: barriers, lighting, intrusion detection, alarm assessment. The baseline approach emphasizes cost/effectiveness achieved by detector layering and logic processing of alarm signals to produce reliable alarms and low nuisance alarm rates. A cost benefit of layering along with video assessment is reduction in operating expense. The concept of layering is also shown to minimize testing costs where detectability performance as suggested by Regulatory Guide 5.44 is to be performed. Synthesis of the perimeter intrusion alarm system and limited testing of CCTV and Video Motion Detectors (VMD), were performed at E-Systems, Greenville Division, Greenville, Texas during 1981.

  2. Assessment of Mitigation Systems on Vapor Intrusion ...

    EPA Pesticide Factsheets

    Vapor intrusion is the migration of subsurface vapors, including radon and volatile organic compounds (VOCs), in soil gas from the subsurface to indoor air. Vapor intrusion happens because there are pressure and concentration differentials between indoor air and soil gas. Indoor environments are often negatively pressurized with respect to outdoor air and soil gas (for example, from exhaust fans or the stack effect), and this pressure difference allows soil gas containing subsurface vapors to flow into indoor air through advection. In addition, concentration differentials cause VOCs and radon to migrate from areas of higher to lower concentrations through diffusion, which is another cause of vapor intrusion. Current practice for evaluating the vapor intrusion pathway involves a multiple line of evidence approach based on direct measurements in groundwater, external soil gas, subslab soil gas, and/or indoor air. No single line of evidence is considered definitive, and direct measurements of vapor intrusion can be costly, especially where significant spatial and temporal variability require repeated measurements at multiple locations to accurately assess the chronic risks of long-term exposure to volatile organic compounds (VOCs) like chloroform, perchloroethylene (PCE), and trichloroethylene (TCE).

  3. Igneous intrusions in coal-bearing sequences

    SciTech Connect

    Gurevich, A.B.; Shishlov, S.B.

    1987-08-01

    Intrusions of various compositions, sizes, and shapes have been observed in 115 out of 620 coal basins or deposits on all the continents. They are mainly subvolcanic and hypabyssal, with depths of emplacement estimated as ranging from a few hundred meters to 6 km, but usually 3-4 km. Compositionally, 42% are basic, 31% intermediate, 23% acid, and 4% ultrabasic. Mafic (and related) rock types include dolerites, trachydolerites, gabbro-dolerites, gabbro-monzonites, monzonites, diabases, gabbrodiabases, and less often gabbros and basalts (subvolcanic bodies). These mafic intrusions occur in coal formations of various ages from Carboniferous through Neogene, but predominate in Paleozoic (47%) and Cenozoic beds (45%). They also occur in coal formations of all genetic types, apart from those on ancient stable platforms, where there are no signs of intrusive activity. The mafic intrusions are almost everywhere associated with comagmatic lavas and tuffs (mainly in the younger strata), and the coal beds themselves are to some extent enriched in pyroclastic material, particularly in the upper horizons. This paper gives a worldwide review of igneous intrusions in coal beds. 24 references.

  4. Proceedings 3rd NASA/IEEE Workshop on Formal Approaches to Agent-Based Systems (FAABS-III)

    NASA Technical Reports Server (NTRS)

    Hinchey, Michael (Editor); Rash, James (Editor); Truszkowski, Walt (Editor); Rouff, Christopher (Editor)

    2004-01-01

    These preceedings contain 18 papers and 4 poster presentation, covering topics such as: multi-agent systems, agent-based control, formalism, norms, as well as physical and biological models of agent-based systems. Some applications presented in the proceedings include systems analysis, software engineering, computer networks and robot control.

  5. Architectural considerations for agent-based national scale policy models : LDRD final report.

    SciTech Connect

    Backus, George A.; Strip, David R.

    2007-09-01

    The need to anticipate the consequences of policy decisions becomes ever more important as the magnitude of the potential consequences grows. The multiplicity of connections between the components of society and the economy makes intuitive assessments extremely unreliable. Agent-based modeling has the potential to be a powerful tool in modeling policy impacts. The direct mapping between agents and elements of society and the economy simplify the mapping of real world functions into the world of computation assessment. Our modeling initiative is motivated by the desire to facilitate informed public debate on alternative policies for how we, as a nation, provide healthcare to our population. We explore the implications of this motivation on the design and implementation of a model. We discuss the choice of an agent-based modeling approach and contrast it to micro-simulation and systems dynamics approaches.

  6. Semantic Extension of Agent-Based Control: The Packing Cell Case Study

    NASA Astrophysics Data System (ADS)

    Vrba, Pavel; Radakovič, Miloslav; Obitko, Marek; Mařík, Vladimír

    The paper reports on the latest R&D activities in the field of agent-based manufacturing control systems. It is documented that this area becomes strongly influenced by the advancements of semantic technologies like the Web Ontology Language. The application of ontologies provides the agents with much more effective means for handling, exchanging and reasoning about the knowledge. The ontology dedicated for semantic description of orders, production processes and material handling tasks in discrete manufacturing domain has been developed. In addition, the framework for integration of this ontology in distributed, agent-based control solutions is given. The Manufacturing Agent Simulation Tool (MAST) is used as a base for pilot implementation of the ontology-powered multiagent control system; the packing cell environment is selected as a case study.

  7. Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies: Preprint

    SciTech Connect

    Gallo, Giulia

    2015-10-07

    The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020. The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.

  8. Disaggregation and Refinement of System Dynamics Models via Agent-based Modeling

    SciTech Connect

    Nutaro, James J; Ozmen, Ozgur; Schryver, Jack C

    2014-01-01

    System dynamics models are usually used to investigate aggregate level behavior, but these models can be decomposed into agents that have more realistic individual behaviors. Here we develop a simple model of the STEM workforce to illuminate the impacts that arise from the disaggregation and refinement of system dynamics models via agent-based modeling. Particularly, alteration of Poisson assumptions, adding heterogeneity to decision-making processes of agents, and discrete-time formulation are investigated and their impacts are illustrated. The goal is to demonstrate both the promise and danger of agent-based modeling in the context of a relatively simple model and to delineate the importance of modeling decisions that are often overlooked.

  9. An Agent-Based Model of New Venture Creation: Conceptual Design for Simulating Entrepreneurship

    NASA Technical Reports Server (NTRS)

    Provance, Mike; Collins, Andrew; Carayannis, Elias

    2012-01-01

    There is a growing debate over the means by which regions can foster the growth of entrepreneurial activity in order to stimulate recovery and growth of their economies. On one side, agglomeration theory suggests the regions grow because of strong clusters that foster knowledge spillover locally; on the other side, the entrepreneurial action camp argues that innovative business models are generated by entrepreneurs with unique market perspectives who draw on knowledge from more distant domains. We will show you the design for a novel agent-based model of new venture creation that will demonstrate the relationship between agglomeration and action. The primary focus of this model is information exchange as the medium for these agent interactions. Our modeling and simulation study proposes to reveal interesting relationships in these perspectives, offer a foundation on which these disparate theories from economics and sociology can find common ground, and expand the use of agent-based modeling into entrepreneurship research.

  10. Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system.

    PubMed

    Lu, Yunfan; Wang, Jun; Niu, Hongli

    2015-10-01

    Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

  11. Nonlinear multi-analysis of agent-based financial market dynamics by epidemic system

    NASA Astrophysics Data System (ADS)

    Lu, Yunfan; Wang, Jun; Niu, Hongli

    2015-10-01

    Based on the epidemic dynamical system, we construct a new agent-based financial time series model. In order to check and testify its rationality, we compare the statistical properties of the time series model with the real stock market indices, Shanghai Stock Exchange Composite Index and Shenzhen Stock Exchange Component Index. For analyzing the statistical properties, we combine the multi-parameter analysis with the tail distribution analysis, the modified rescaled range analysis, and the multifractal detrended fluctuation analysis. For a better perspective, the three-dimensional diagrams are used to present the analysis results. The empirical research in this paper indicates that the long-range dependence property and the multifractal phenomenon exist in the real returns and the proposed model. Therefore, the new agent-based financial model can recurrence some important features of real stock markets.

  12. Towards strength and stability : agent-based modeling of infrastructure markets.

    SciTech Connect

    North, M. J.; Decision and Information Sciences

    2001-01-01

    Complex Adaptive Systems (CASs) can be applied to investigate complex infrastructures and infrastructure interdependencies. Agent-based modeling (ABM) is a new CAS-based approach to the construction of models. The CAS agents within the Spot Market Agent Research Tool (SMART) and Flexible Agent Simulation Toolkit (FAST) ABMs allow investigation of the electric power infrastructure, the natural gas infrastructure, and their interdependencies. The Swarm-based SMART models use sets of agents and interconnections to represent electric power and natural gas systems. A prototype virtual reality (VR) interface has also been constructed for a version of the SMART model. This tool is intended to explore the use of advanced interactive three-dimensional visualization in agent-based modeling. The Java-based FAST model is currently under construction. FAST is a complete redesign of the SMART models that includes improvements in the modeling environment, model detail, and representational fidelity. Developing ABMs is difficult but can be rewarding.

  13. An agent-based model of collective emotions in online communities

    NASA Astrophysics Data System (ADS)

    Schweitzer, F.; Garcia, D.

    2010-10-01

    We develop an agent-based framework to model the emergence of collective emotions, which is applied to online communities. Agent’s individual emotions are described by their valence and arousal. Using the concept of Brownian agents, these variables change according to a stochastic dynamics, which also considers the feedback from online communication. Agents generate emotional information, which is stored and distributed in a field modeling the online medium. This field affects the emotional states of agents in a non-linear manner. We derive conditions for the emergence of collective emotions, observable in a bimodal valence distribution. Dependent on a saturated or a superlinear feedback between the information field and the agent’s arousal, we further identify scenarios where collective emotions only appear once or in a repeated manner. The analytical results are illustrated by agent-based computer simulations. Our framework provides testable hypotheses about the emergence of collective emotions, which can be verified by data from online communities.

  14. Agent-Based vs. Equation-based Epidemiological Models:A Model Selection Case Study

    SciTech Connect

    Sukumar, Sreenivas R; Nutaro, James J

    2012-01-01

    This paper is motivated by the need to design model validation strategies for epidemiological disease-spread models. We consider both agent-based and equation-based models of pandemic disease spread and study the nuances and complexities one has to consider from the perspective of model validation. For this purpose, we instantiate an equation based model and an agent based model of the 1918 Spanish flu and we leverage data published in the literature for our case- study. We present our observations from the perspective of each implementation and discuss the application of model-selection criteria to compare the risk in choosing one modeling paradigm to another. We conclude with a discussion of our experience and document future ideas for a model validation framework.

  15. Fluctuation complexity of agent-based financial time series model by stochastic Potts system

    NASA Astrophysics Data System (ADS)

    Hong, Weijia; Wang, Jun

    2015-03-01

    Financial market is a complex evolved dynamic system with high volatilities and noises, and the modeling and analyzing of financial time series are regarded as the rather challenging tasks in financial research. In this work, by applying the Potts dynamic system, a random agent-based financial time series model is developed in an attempt to uncover the empirical laws in finance, where the Potts model is introduced to imitate the trading interactions among the investing agents. Based on the computer simulation in conjunction with the statistical analysis and the nonlinear analysis, we present numerical research to investigate the fluctuation behaviors of the proposed time series model. Furthermore, in order to get a robust conclusion, we consider the daily returns of Shanghai Composite Index and Shenzhen Component Index, and the comparison analysis of return behaviors between the simulation data and the actual data is exhibited.

  16. Using Model Replication to Improve the Reliability of Agent-Based Models

    NASA Astrophysics Data System (ADS)

    Zhong, Wei; Kim, Yushim

    The basic presupposition of model replication activities for a computational model such as an agent-based model (ABM) is that, as a robust and reliable tool, it must be replicable in other computing settings. This assumption has recently gained attention in the community of artificial society and simulation due to the challenges of model verification and validation. Illustrating the replication of an ABM representing fraudulent behavior in a public service delivery system originally developed in the Java-based MASON toolkit for NetLogo by a different author, this paper exemplifies how model replication exercises provide unique opportunities for model verification and validation process. At the same time, it helps accumulate best practices and patterns of model replication and contributes to the agenda of developing a standard methodological protocol for agent-based social simulation.

  17. Integrated Agent-Based and Production Cost Modeling Framework for Renewable Energy Studies

    SciTech Connect

    Gallo, Giulia

    2016-01-08

    The agent-based framework for renewable energy studies (ARES) is an integrated approach that adds an agent-based model of industry actors to PLEXOS and combines the strengths of the two to overcome their individual shortcomings. It can examine existing and novel wholesale electricity markets under high penetrations of renewables. ARES is demonstrated by studying how increasing levels of wind will impact the operations and the exercise of market power of generation companies that exploit an economic withholding strategy. The analysis is carried out on a test system that represents the Electric Reliability Council of Texas energy-only market in the year 2020. The results more realistically reproduce the operations of an energy market under different and increasing penetrations of wind, and ARES can be extended to address pressing issues in current and future wholesale electricity markets.

  18. Preclinical animal acute toxicity studies of new developed MRI contrast agent based on gadolinium

    NASA Astrophysics Data System (ADS)

    Nam, I. F.; Zhuk, V. V.

    2015-04-01

    Acute toxicity test of new developed MRI contrast agent based on disodium salt of gadopentetic acid complex were carried out on Mus musculus and Sprague Dawley rats according to guidelines of preclinical studies [1]. Groups of six animals each were selected for experiment. Death and clinical symptoms of animals were recorded during 14 days. As a result the maximum tolerated dose (MTD) for female mice is 2.8 mM/kg of body weight, male mice - 1.4 mM/kg, female rats - 2.8 mM/kg, male rats - 5.6 mM/kg of body weight. No Observed Adverse Effect Dose (NOAEL) for female mice is 1.4 mM/kg, male mice - 0.7 mM/kg, male and female rats - 0.7 mM/kg. According to experimental data new developed MRI contrast agent based on Gd-DTPA complex is low-toxic.

  19. Analysis of a SCADA System Anomaly Detection Model Based on Information Entropy

    DTIC Science & Technology

    2014-03-27

    20 Intrusion Detection...alarms ( Rem ). ............................................................................................................. 86 Figure 25. TP% for...literature concerning the focus areas of this research. The focus areas include SCADA vulnerabilities, information theory, and intrusion detection

  20. Agent-based model for rural-urban migration: A dynamic consideration

    NASA Astrophysics Data System (ADS)

    Cai, Ning; Ma, Hai-Ying; Khan, M. Junaid

    2015-10-01

    This paper develops a dynamic agent-based model for rural-urban migration, based on the previous relevant works. The model conforms to the typical dynamic linear multi-agent systems model concerned extensively in systems science, in which the communication network is formulated as a digraph. Simulations reveal that consensus of certain variable could be harmful to the overall stability and should be avoided.

  1. Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

    NASA Astrophysics Data System (ADS)

    Haer, Toon; Aerts, Jeroen

    2015-04-01

    Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

  2. Addressing the translational dilemma: dynamic knowledge representation of inflammation using agent-based modeling.

    PubMed

    An, Gary; Christley, Scott

    2012-01-01

    Given the panoply of system-level diseases that result from disordered inflammation, such as sepsis, atherosclerosis, cancer, and autoimmune disorders, understanding and characterizing the inflammatory response is a key target of biomedical research. Untangling the complex behavioral configurations associated with a process as ubiquitous as inflammation represents a prototype of the translational dilemma: the ability to translate mechanistic knowledge into effective therapeutics. A critical failure point in the current research environment is a throughput bottleneck at the level of evaluating hypotheses of mechanistic causality; these hypotheses represent the key step toward the application of knowledge for therapy development and design. Addressing the translational dilemma will require utilizing the ever-increasing power of computers and computational modeling to increase the efficiency of the scientific method in the identification and evaluation of hypotheses of mechanistic causality. More specifically, development needs to focus on facilitating the ability of non-computer trained biomedical researchers to utilize and instantiate their knowledge in dynamic computational models. This is termed "dynamic knowledge representation." Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation. Agent-based modeling has been used in the study of inflammation at multiple scales. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggest that this modeling framework is well suited for addressing the translational dilemma. This review describes agent-based modeling, gives examples of its applications in the study of inflammation, and introduces a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge

  3. Financial price dynamics and agent-based models as inspired by Benoit Mandelbrot

    NASA Astrophysics Data System (ADS)

    LeBaron, Blake

    2016-12-01

    This short note draws some connections between Mandelbrot‗s empirical legacy, and the interdisciplinary work that followed in finance. Much of this work is now labeled econophysics, but some has always been more in the realm of economics than physics. In a few areas the overlap is even becoming quite complete as in market microstructure. I will also give some ideas about the various successes and failures in this area, and some directions for the future of agent- based modeling in particular.

  4. Pain expressiveness and altruistic behavior: an exploration using agent-based modeling.

    PubMed

    de C Williams, Amanda C; Gallagher, Elizabeth; Fidalgo, Antonio R; Bentley, Peter J

    2016-03-01

    Predictions which invoke evolutionary mechanisms are hard to test. Agent-based modeling in artificial life offers a way to simulate behaviors and interactions in specific physical or social environments over many generations. The outcomes have implications for understanding adaptive value of behaviors in context. Pain-related behavior in animals is communicated to other animals that might protect or help, or might exploit or predate. An agent-based model simulated the effects of displaying or not displaying pain (expresser/nonexpresser strategies) when injured and of helping, ignoring, or exploiting another in pain (altruistic/nonaltruistic/selfish strategies). Agents modeled in MATLAB interacted at random while foraging (gaining energy); random injury interrupted foraging for a fixed time unless help from an altruistic agent, who paid an energy cost, speeded recovery. Environmental and social conditions also varied, and each model ran for 10,000 iterations. Findings were meaningful in that, in general, contingencies that evident from experimental work with a variety of mammals, over a few interactions, were replicated in the agent-based model after selection pressure over many generations. More energy-demanding expression of pain reduced its frequency in successive generations, and increasing injury frequency resulted in fewer expressers and altruists. Allowing exploitation of injured agents decreased expression of pain to near zero, but altruists remained. Decreasing costs or increasing benefits of helping hardly changed its frequency, whereas increasing interaction rate between injured agents and helpers diminished the benefits to both. Agent-based modeling allows simulation of complex behaviors and environmental pressures over evolutionary time.

  5. Graceful Failure and Societal Resilience Analysis Via Agent-Based Modeling and Simulation

    NASA Astrophysics Data System (ADS)

    Schopf, P. S.; Cioffi-Revilla, C.; Rogers, J. D.; Bassett, J.; Hailegiorgis, A. B.

    2014-12-01

    Agent-based social modeling is opening up new methodologies for the study of societal response to weather and climate hazards, and providing measures of resiliency that can be studied in many contexts, particularly in coupled human and natural-technological systems (CHANTS). Since CHANTS are complex adaptive systems, societal resiliency may or may not occur, depending on dynamics that lack closed form solutions. Agent-based modeling has been shown to provide a viable theoretical and methodological approach for analyzing and understanding disasters and societal resiliency in CHANTS. Our approach advances the science of societal resilience through computational modeling and simulation methods that complement earlier statistical and mathematical approaches. We present three case studies of social dynamics modeling that demonstrate the use of these agent based models. In Central Asia, we exmaine mutltiple ensemble simulations with varying climate statistics to see how droughts and zuds affect populations, transmission of wealth across generations, and the overall structure of the social system. In Eastern Africa, we explore how successive episodes of drought events affect the adaptive capacity of rural households. Human displacement, mainly, rural to urban migration, and livelihood transition particularly from pastoral to farming are observed as rural households interacting dynamically with the biophysical environment and continually adjust their behavior to accommodate changes in climate. In the far north case we demonstrate one of the first successful attempts to model the complete climate-permafrost-infrastructure-societal interaction network as a complex adaptive system/CHANTS implemented as a ``federated'' agent-based model using evolutionary computation. Analysis of population changes resulting from extreme weather across these and other cases provides evidence for the emergence of new steady states and shifting patterns of resilience.

  6. Electricity Market Games: How Agent-Based Modeling Can Help under High Penetrations of Variable Generation

    SciTech Connect

    Gallo, Giulia

    2016-03-01

    Integrating increasingly high levels of variable generation in U.S. electricity markets requires addressing not only power system and grid modeling challenges but also an understanding of how market participants react and adapt to them. Key elements of current and future wholesale power markets can be modeled using an agent-based approach, which may prove to be a useful paradigm for researchers studying and planning for power systems of the future.

  7. Intelligent Agent Feasibility Study. Volume 1: Agent-based System Technology

    DTIC Science & Technology

    1998-02-01

    ambitious in its scope. In OAA (Moran, Cheyer, Julia , Martin, 10 & Park, 1997), agents can operate on multiple platforms across a network, new agents can be...find the source and best price for a given item. This area of electronic commerce has been an active area for research in agent-based systems ( Chavez ...D. (1993). Towards a taxonomy of multi-agent systems. International Journal of Man-Machine Studies 36, 689-704. Chavez , A., Dreilinger, D., Guttman, R

  8. An Advanced Computational Approach to System of Systems Analysis & Architecting Using Agent-Based Behavioral Model

    DTIC Science & Technology

    2012-09-30

    The Wave Process Model provides a framework for an agent-based modeling methodology, which is used to abstract the non- utopian behavioral aspects...that SoS participants exhibit nominal behavior ( utopian behavior), but deviation from nominal motivation leads to complications and disturbances in... characteristics . Figure 2 outlines the agent architecture components and flow of information among components. Own Process Control (OPC) Cooperation

  9. Agent-based Systems Key Enabler for the Army’s Future Force

    DTIC Science & Technology

    2003-10-04

    application areas for intelligent be used to support the development of new, revolutionary agent technology that will enable the US Army to rapidly...defining and state of the art information technologies to interpret and implementing agent-based solutions for other echelons and understand the evolving...apply intelligent agent technology to assist in the "Zone of Intel". This reach back capability to data collected information processing, management and

  10. Agent Based Study of Surprise Attacks:. Roles of Surveillance, Prompt Reaction and Intelligence

    NASA Astrophysics Data System (ADS)

    Shanahan, Linda; Sen, Surajit

    Defending a confined territory from a surprise attack is seldom possible. We use molecular dynamics and statistical physics inspired agent-based simulations to explore the evolution and outcome of such attacks. The study suggests robust emergent behavior, which emphasizes the importance of accurate surveillance, automated and powerful attack response, building layout, and sheds light on the role of communication restrictions in defending such territories.

  11. Relationship between vapor intrusion and human exposure to trichloroethylene

    PubMed Central

    ARCHER, NATALIE P.; BRADFORD, CARRIE M.; VILLANACCI, JOHN F.; CRAIN, NEIL E.; CORSI, RICHARD L.; CHAMBERS, DAVID M.; BURK, TONIA; BLOUNT, BENJAMIN C.

    2015-01-01

    Trichloroethylene (TCE) in groundwater has the potential to volatilize through soil into indoor air where it can be inhaled. The purpose of this study was to determine whether individuals living above TCE-contaminated groundwater are exposed to TCE through vapor intrusion. We examined associations between TCE concentrations in various environmental media and TCE concentrations in residents. For this assessment, indoor air, outdoor air, soil gas, and tap water samples were collected in and around 36 randomly selected homes; blood samples were collected from 63 residents of these homes. Additionally, a completed exposure survey was collected from each participant. Environmental and blood samples were analyzed for TCE. Mixed model multiple linear regression analyses were performed to determine associations between TCE in residents' blood and TCE in indoor air, outdoor air, and soil gas. Blood TCE concentrations were above the limit of quantitation (LOQ; ≥0.012 μg/L) in 17.5% of the blood samples. Of the 36 homes, 54.3%, 47.2%, and >84% had detectable concentrations of TCE in indoor air, outdoor air, and soil gas, respectively. Both indoor air and soil gas concentrations were statistically significantly positively associated with participants' blood concentrations (p=0.0002 and p=0.04, respectively). Geometric mean blood concentrations of residents from homes with indoor air concentrations of >1.6 μg/m3 were approximately 50 times higher than geometric mean blood TCE concentrations in participants from homes with no detectable TCE in indoor air (p<.0001; 95% CI 10.4 – 236.4). This study confirms the occurrence of vapor intrusion and demonstrates the magnitude of exposure from vapor intrusion of TCE in a residential setting. PMID:26259926

  12. Relationship between vapor intrusion and human exposure to trichloroethylene.

    PubMed

    Archer, Natalie P; Bradford, Carrie M; Villanacci, John F; Crain, Neil E; Corsi, Richard L; Chambers, David M; Burk, Tonia; Blount, Benjamin C

    2015-01-01

    Trichloroethylene (TCE) in groundwater has the potential to volatilize through soil into indoor air where it can be inhaled. The purpose of this study was to determine whether individuals living above TCE-contaminated groundwater are exposed to TCE through vapor intrusion. We examined associations between TCE concentrations in various environmental media and TCE concentrations in residents. For this assessment, indoor air, outdoor air, soil gas, and tap water samples were collected in and around 36 randomly selected homes; blood samples were collected from 63 residents of these homes. Additionally, a completed exposure survey was collected from each participant. Environmental and blood samples were analyzed for TCE. Mixed model multiple linear regression analyses were performed to determine associations between TCE in residents' blood and TCE in indoor air, outdoor air, and soil gas. Blood TCE concentrations were above the limit of quantitation (LOQ; ≥ 0.012 µg L(-1)) in 17.5% of the blood samples. Of the 36 homes, 54.3%, 47.2%, and >84% had detectable concentrations of TCE in indoor air, outdoor air, and soil gas, respectively. Both indoor air and soil gas concentrations were statistically significantly positively associated with participants' blood concentrations (P = 0.0002 and P = 0.04, respectively). Geometric mean blood concentrations of residents from homes with indoor air concentrations of >1.6 µg m(-3) were approximately 50 times higher than geometric mean blood TCE concentrations in participants from homes with no detectable TCE in indoor air (P < .0001; 95% CI 10.4-236.4). This study confirms the occurrence of vapor intrusion and demonstrates the magnitude of exposure from vapor intrusion of TCE in a residential setting.

  13. Deterministic Agent-Based Path Optimization by Mimicking the Spreading of Ripples.

    PubMed

    Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Di Paolo, Ezequiel A; Liu, Hao

    2016-01-01

    Inspirations from nature have contributed fundamentally to the development of evolutionary computation. Learning from the natural ripple-spreading phenomenon, this article proposes a novel ripple-spreading algorithm (RSA) for the path optimization problem (POP). In nature, a ripple spreads at a constant speed in all directions, and the node closest to the source is the first to be reached. This very simple principle forms the foundation of the proposed RSA. In contrast to most deterministic top-down centralized path optimization methods, such as Dijkstra's algorithm, the RSA is a bottom-up decentralized agent-based simulation model. Moreover, it is distinguished from other agent-based algorithms, such as genetic algorithms and ant colony optimization, by being a deterministic method that can always guarantee the global optimal solution with very good scalability. Here, the RSA is specifically applied to four different POPs. The comparative simulation results illustrate the advantages of the RSA in terms of effectiveness and efficiency. Thanks to the agent-based and deterministic features, the RSA opens new opportunities to attack some problems, such as calculating the exact complete Pareto front in multiobjective optimization and determining the kth shortest project time in project management, which are very difficult, if not impossible, for existing methods to resolve. The ripple-spreading optimization principle and the new distinguishing features and capacities of the RSA enrich the theoretical foundations of evolutionary computation.

  14. Model reduction for agent-based social simulation: coarse-graining a civil violence model.

    PubMed

    Zou, Yu; Fonoberov, Vladimir A; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G

    2012-06-01

    Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

  15. Agent-based power sharing scheme for active hybrid power sources

    NASA Astrophysics Data System (ADS)

    Jiang, Zhenhua

    The active hybridization technique provides an effective approach to combining the best properties of a heterogeneous set of power sources to achieve higher energy density, power density and fuel efficiency. Active hybrid power sources can be used to power hybrid electric vehicles with selected combinations of internal combustion engines, fuel cells, batteries, and/or supercapacitors. They can be deployed in all-electric ships to build a distributed electric power system. They can also be used in a bulk power system to construct an autonomous distributed energy system. An important aspect in designing an active hybrid power source is to find a suitable control strategy that can manage the active power sharing and take advantage of the inherent scalability and robustness benefits of the hybrid system. This paper presents an agent-based power sharing scheme for active hybrid power sources. To demonstrate the effectiveness of the proposed agent-based power sharing scheme, simulation studies are performed for a hybrid power source that can be used in a solar car as the main propulsion power module. Simulation results clearly indicate that the agent-based control framework is effective to coordinate the various energy sources and manage the power/voltage profiles.

  16. Using an agent-based model to simulate children’s active travel to school

    PubMed Central

    2013-01-01

    Background Despite the multiple advantages of active travel to school, only a small percentage of US children and adolescents walk or bicycle to school. Intervention studies are in a relatively early stage and evidence of their effectiveness over long periods is limited. The purpose of this study was to illustrate the utility of agent-based models in exploring how various policies may influence children’s active travel to school. Methods An agent-based model was developed to simulate children’s school travel behavior within a hypothetical city. The model was used to explore the plausible implications of policies targeting two established barriers to active school travel: long distance to school and traffic safety. The percent of children who walk to school was compared for various scenarios. Results To maximize the percent of children who walk to school the school locations should be evenly distributed over space and children should be assigned to the closest school. In the case of interventions to improve traffic safety, targeting a smaller area around the school with greater intensity may be more effective than targeting a larger area with less intensity. Conclusions Despite the challenges they present, agent based models are a useful complement to other analytical strategies in studying the plausible impact of various policies on active travel to school. PMID:23705953

  17. Model reduction for agent-based social simulation: Coarse-graining a civil violence model

    NASA Astrophysics Data System (ADS)

    Zou, Yu; Fonoberov, Vladimir A.; Fonoberova, Maria; Mezic, Igor; Kevrekidis, Ioannis G.

    2012-06-01

    Agent-based modeling (ABM) constitutes a powerful computational tool for the exploration of phenomena involving emergent dynamic behavior in the social sciences. This paper demonstrates a computer-assisted approach that bridges the significant gap between the single-agent microscopic level and the macroscopic (coarse-grained population) level, where fundamental questions must be rationally answered and policies guiding the emergent dynamics devised. Our approach will be illustrated through an agent-based model of civil violence. This spatiotemporally varying ABM incorporates interactions between a heterogeneous population of citizens [active (insurgent), inactive, or jailed] and a population of police officers. Detailed simulations exhibit an equilibrium punctuated by periods of social upheavals. We show how to effectively reduce the agent-based dynamics to a stochastic model with only two coarse-grained degrees of freedom: the number of jailed citizens and the number of active ones. The coarse-grained model captures the ABM dynamics while drastically reducing the computation time (by a factor of approximately 20).

  18. An agent-based model of signal transduction in bacterial chemotaxis.

    PubMed

    Miller, Jameson; Parker, Miles; Bourret, Robert B; Giddings, Morgan C

    2010-05-13

    We report the application of agent-based modeling to examine the signal transduction network and receptor arrays for chemotaxis in Escherichia coli, which are responsible for regulating swimming behavior in response to environmental stimuli. Agent-based modeling is a stochastic and bottom-up approach, where individual components of the modeled system are explicitly represented, and bulk properties emerge from their movement and interactions. We present the Chemoscape model: a collection of agents representing both fixed membrane-embedded and mobile cytoplasmic proteins, each governed by a set of rules representing knowledge or hypotheses about their function. When the agents were placed in a simulated cellular space and then allowed to move and interact stochastically, the model exhibited many properties similar to the biological system including adaptation, high signal gain, and wide dynamic range. We found the agent based modeling approach to be both powerful and intuitive for testing hypotheses about biological properties such as self-assembly, the non-linear dynamics that occur through cooperative protein interactions, and non-uniform distributions of proteins in the cell. We applied the model to explore the role of receptor type, geometry and cooperativity in the signal gain and dynamic range of the chemotactic response to environmental stimuli. The model provided substantial qualitative evidence that the dynamic range of chemotactic response can be traced to both the heterogeneity of receptor types present, and the modulation of their cooperativity by their methylation state.

  19. Non-Intrusive Cable Tester

    NASA Technical Reports Server (NTRS)

    Medelius, Pedro J. (Inventor); Simpson, Howard J. (Inventor)

    1999-01-01

    A cable tester is described for low frequency testing of a cable for faults. The tester allows for testing a cable beyond a point where a signal conditioner is installed, minimizing the number of connections which have to be disconnected. A magnetic pickup coil is described for detecting a test signal injected into the cable. A narrow bandpass filter is described for increasing detection of the test signal. The bandpass filter reduces noise so that a high gain amplifier provided for detecting a test signal is not completely saturate by noise. To further increase the accuracy of the cable tester, processing gain is achieved by comparing the signal from the amplifier with at least one reference signal emulating the low frequency input signal injected into the cable. Different processing techniques are described evaluating a detected signal.

  20. Monoclinal bending of strata over laccolithic intrusions

    USGS Publications Warehouse

    Koch, F.G.; Johnson, A.M.; Pollard, D.D.

    1981-01-01

    Sedimentary strata on top of some laccolithic intrusions are nearly horizontal and little deformed, but are bent into steeply dipping monoclinal flexures over the peripheries of these intrusions. This form of bending is not explained by previous theories of laccolithic intrusion, which predict either horizontal undeformed strata over the center and faulted strata around the periphery, or strata bent continuously into a dome. However, a slight generalization of these theories accomodates the observed form and contains the previous forms as special cases. A critical assumption is that the strength of contacts within a multilayered overburden is overcome locally by layer-parallel shear. If this strength is less than the strength of the layers themselves, then layers over the center remain bonded together and display negligible bending, whereas layers over the periphery slip over one another and are readily bent into a monoclinal flexure. ?? 1981.

  1. Magma rheology variation in sheet intrusions (Invited)

    NASA Astrophysics Data System (ADS)

    Magee, C.; O'Driscoll, B.; Petronis, M. S.; Stevenson, C.

    2013-12-01

    The rheology of magma fundamentally controls igneous intrusion style as well as the explosivity and type of volcanic eruptions. Importantly, the dynamic interplay between the viscosity of magma and other processes active during intrusion (e.g., crystallisation, magma mixing, assimilation of crystal mushes and/or xenolith entrainment) will likely bear an influence on the temporal variation of magma rheology. Constraining the timing of rheological changes during magma transit therefore plays an important role in understanding the nuances of volcanic systems. However, the rheological evolution of actively emplacing igneous intrusions cannot be directly studied. While significant advances have been made via experimental modelling and analysis of lava flows, how these findings relate to intruding magma remains unclear. This has led to an increasing number of studies that analyse various characteristics of fully crystallised intrusions in an attempt to ';back-out' the rheological conditions governing emplacement. For example, it has long been known that crystallinity affects the rheology and, consequently, the velocity of intruding magma. This means that quantitative textural analysis of crystal populations (e.g., crystal size distribution; CSD) used to elucidate crystallinity at different stages of emplacement can provide insights into magma rheology. Similarly, methods that measure flow-related fabrics (e.g., anisotropy of magnetic susceptibility; AMS) can be used to discern velocity profiles, a potential proxy for the magma rheology. To illustrate these ideas, we present an integrated AMS and petrological study of several sheet intrusions located within the Ardnamurchan Central Complex, NW Scotland. We focus on the entrainment and transport dynamics of gabbroic inclusions that were infiltrated by the host magma upon entrainment. Importantly, groundmass magnetic fabrics within and external to these inclusions are coaxial. This implies that a deviatoric stress was

  2. Convective, intrusive geothermal plays: what about tectonics?

    NASA Astrophysics Data System (ADS)

    Santilano, A.; Manzella, A.; Gianelli, G.; Donato, A.; Gola, G.; Nardini, I.; Trumpy, E.; Botteghi, S.

    2015-09-01

    We revised the concept of convective, intrusive geothermal plays, considering that the tectonic setting is not, in our opinion, a discriminant parameter suitable for a classification. We analysed and compared four case studies: (i) Larderello (Italy), (ii) Mt Amiata (Italy), (iii) The Geysers (USA) and (iv) Kizildere (Turkey). The tectonic settings of these geothermal systems are different and a matter of debate, so it is hard to use this parameter, and the results of classification are ambiguous. We suggest a classification based on the age and nature of the heat source and the related hydrothermal circulation. Finally we propose to distinguish the convective geothermal plays as volcanic, young intrusive and amagmatic.

  3. Brumalia Tholus: Magmatic Intrusion on Vesta?

    NASA Astrophysics Data System (ADS)

    Buczkowski, Debra L.; DeSanctis, M. Christina; Raymond, Carol A.; Ammannito, Eleonora; Frigeri, Alessandro; Wyrick, Danielle Y.; Williams, David; Russell, Christopher T.

    2013-04-01

    Geologic mapping of Vesta was based on Dawn spacecraft Framing Camera (FC) images and compositional data from the Visible & Infrared Spectrometer (VIR). Mapping reveals that while the equatorial region of Vesta displays numerous wide, flat-floored troughs [1], these troughs do not cut the Vestalia Terra plateau (VT) [2]. However, three large pit crater chains are observed on the VT surface [2,3]. Pit crater chains are hypothesized to form when dilational motion on buried normal faults causes overlying material to collapse into the opening portions of the buried fault [4]. The merged pits of the VT pit crater chains show signs of collapse but distinct fault faces can also be observed [3]. It has thus been suggested that the VT pit crater chains are representative of subsurface faulting of the plateau [2]. The pit crater chain Albalonga Catena phases from being a topographically low feature of merged pits into being the topographically high Brumalia Tholus, an elongate hill. If Albalonga Catena represents a buried normal fault, then the topographic high that emerges along its length could have been formed by a magmatic intrusion utilizing the subsurface fracture as a conduit to the surface. Brumalia Tholus should thus be comprised of diogenite, a plutonic vestan material. Teia crater impacts Brumalia Tholus and likely samples Brumalia's core material. FC data indicates that Teia ejecta have a smeared, flow-like texture and a distinct compostion. VIR analysis has shown that while background VT material is howarditic [5], these Teia ejecta are more diogenitic. VIR also detected small diogenite deposits on top of Brumalia Tholus. The identification of diogenite on the top of Brumalia Tholus and in the Teia ejecta is consistent with the hill being the surface representation of a magmatic intrusion. We present a possible sequence of events. Global equatorial fracturing and faulting occurred, resulting in sub-surface faulting of VT. The surface of VT was covered by

  4. Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling.

    PubMed

    Shin, Sangmi; Park, Seongha; Kim, Yongho; Matson, Eric T

    2016-04-22

    Recently, commercial unmanned aerial systems (UAS) have gained popularity. However, these UAS are potential threats to people in terms of safety in public places, such as public parks or stadiums. To reduce such threats, we consider a design, modeling, and evaluation of a cost-efficient sensor system that detects and tracks small UAS. In this research, we focus on discovering the best sensor deployments by simulating different types and numbers of sensors in a designated area, which provide reasonable detection rates at low costs. Also, the system should cover the crowded areas more thoroughly than vacant areas to reduce direct threats to people underneath. This research study utilized the Agent-Based Modeling (ABM) technique to model a system consisting of independent and heterogeneous agents that interact with each other. Our previous work presented the ability to apply ABM to analyze the sensor configurations with two types of radars in terms of cost-efficiency. The results from the ABM simulation provide a list of candidate configurations and deployments that can be referred to for applications in the real world environment.

  5. Design and Analysis of Cost-Efficient Sensor Deployment for Tracking Small UAS with Agent-Based Modeling

    PubMed Central

    Shin, Sangmi; Park, Seongha; Kim, Yongho; Matson, Eric T.

    2016-01-01

    Recently, commercial unmanned aerial systems (UAS) have gained popularity. However, these UAS are potential threats to people in terms of safety in public places, such as public parks or stadiums. To reduce such threats, we consider a design, modeling, and evaluation of a cost-efficient sensor system that detects and tracks small UAS. In this research, we focus on discovering the best sensor deployments by simulating different types and numbers of sensors in a designated area, which provide reasonable detection rates at low costs. Also, the system should cover the crowded areas more thoroughly than vacant areas to reduce direct threats to people underneath. This research study utilized the Agent-Based Modeling (ABM) technique to model a system consisting of independent and heterogeneous agents that interact with each other. Our previous work presented the ability to apply ABM to analyze the sensor configurations with two types of radars in terms of cost-efficiency. The results from the ABM simulation provide a list of candidate configurations and deployments that can be referred to for applications in the real world environment. PMID:27110790

  6. Impact of an intrusion by the Northern Current on the biogeochemistry in the eastern Gulf of Lion, NW Mediterranean

    NASA Astrophysics Data System (ADS)

    Ross, Oliver N.; Fraysse, Marion; Pinazo, Christel; Pairaud, Ivane

    2016-03-01

    We present the results from the RHOMA2011-LEG2 campaign that took place in the eastern Gulf of Lion from 7 to 17 Oct 2011 and combine them with remote sensing observations and results from a 3D coupled hydrodynamic-biogeochemical model to study an intrusion event of the Northern Current (NC) onto the continental shelf in the Gulf of Lion (NW Mediterranean). Our analysis shows that during the intrusion, the previously upwelled nutrient-rich water present on the shelf is replaced by warmer and mostly oligotrophic NC water within a matter of 2-3 days. This has a marked impact on the local biogeochemistry in the Gulf with pre-intrusion Chl-a concentrations in the surface layer of over 0.5 mg m-3 dropping to near the detection limit within less than 72 h. The intrusion event leads to a dramatic albeit short-lived regime shift in the limiting nutrient for primary production: prior to the intrusion most of production on the shelf is nitrogen limited while the intrusion induces a shift to phosphorous limitation. The relatively high frequency of occurrence of these intrusions in combination with their impact on the local ecosystem make them primary targets for future study.

  7. BTSC VAPOR INSTRUSION PRIMER "VAPOR INTRUSION CONSIDERATION FOR REDEVELOPMENT"

    EPA Science Inventory

    This primer is designed for brownfields stakeholders concerned about vapor intrusion, including property owners, real estate developers, and contractors performing environmental site investigations. It provides an overview of the vapor intrusion issue and how it can impact the ap...

  8. Vapor Intrusion Characterization Report (Revision 1.0)

    EPA Pesticide Factsheets

    Vapor Intrusion Characterization Report (Revision 1) - February 5, 2015: This report, which was approved by the EPA on February 18, 2015, documents the results from implementation of the Final Vapor Intrusion Characterization Work Plan.

  9. The Diamond Model of Intrusion Analysis

    DTIC Science & Technology

    2013-07-05

    Frederick. Intrusion Signatures and Analysis. New Riders Publishing, Indianapolis, IN, USA, 2001. [9] SANS. [ONLINE] http://www.sans.org. [10] Bernhard ...1):29–46, 1997. [29] John D. Howard and Thomas A. Longstaff. A common lanaguage for computer security incidents. Technical Report SAND98-8667, Sandia

  10. Chemical Observations of a Polar Vortex Intrusion

    NASA Technical Reports Server (NTRS)

    Schoeberl, M. R.; Kawa, S. R.; Douglass, A. R.; McGee, T. J.; Browell, E.; Waters, J.; Livesey, N.; Read, W.; Froidevaux, L.

    2006-01-01

    An intrusion of vortex edge air in D the interior of the Arctic polar vortex was observed on the January 31,2005 flight of the NASA DC-8 aircraft. This intrusion was identified as anomalously high values of ozone by the AROTAL and DIAL lidars. Our analysis shows that this intrusion formed when a blocking feature near Iceland collapsed, allowing edge air to sweep into the vortex interior. along the DC-8 flight track also shows the intrusion in both ozone and HNO3. Polar Stratospheric Clouds (PSCs) were observed by the DIAL lidar on the DC-8. The spatial variability of the PSCs can be explained using MLS HNO3 and H2O observations and meteorological analysis temperatures. We also estimate vortex denitrification using the relationship between N2O and HNO3. Reverse domain fill back trajectory calculations are used to focus on the features in the MLS data. The trajectory results improve the agreement between lidar measured ozone and MLS ozone and also improve the agreement between the HNO3 measurements PSC locations. The back trajectory calculations allow us to compute the local denitrification rate and reduction of HCl within the filament. We estimate a denitrification rate of about lO%/day after exposure to below PSC formation temperature. Analysis of Aura MLS observations made

  11. ON-LINE CALCULATOR: VAPOR INTRUSION MODELING

    EPA Science Inventory

    Migration of volatile chemicals from the subsurface into overlying buildings is called vapor intrusion (VI). Volatile organic chemicals in contaminated soils or groundwater can emit vapors, which may migrate through subsurface soils and may enter the indoor air of overlying build...

  12. Intrusion of Soil Water through Pipe Cracks

    EPA Science Inventory

    This report describes a series of experiments conducted at U.S. EPA’s Test and Evaluation Facility in 2013-2014 to study the intrusion of contaminated soil water into a pipe crack during simulated backflow events. A test rig was used consisting of a 3’ x 3’ x 3’ acrylic soil bo...

  13. Non-Intrusive Grammar in Writing.

    ERIC Educational Resources Information Center

    Roberts, Claudette M.; Boggase, Barbara A.

    Since introducing a grammar unit can be daunting and frustrating for both teachers and students, a collaborative unit for a 10th-grade class was planned that would satisfy an administrative requirement but also maintain the integrity of the writing program. The unit was planned by developing an approach of non-intrusive grammar instruction at the…

  14. How stratospheric are deep stratospheric intrusions?

    NASA Astrophysics Data System (ADS)

    Trickl, T.; Vogelmann, H.; Giehl, H.; Scheel, H.-E.; Sprenger, M.; Stohl, A.

    2014-06-01

    Preliminary attempts of quantifying the stratospheric ozone contribution in the observations at the Zugspitze summit (2962 m a.s.l.) next to Garmisch-Partenkirchen in the German Alps had yielded an approximate doubling of the stratospheric fraction of the Zugspitze ozone during the time period 1978 and 2004. These investigations had been based on data filtering by using low relative humidity and elevated 7Be as the criteria for selecting half-hour intervals of ozone data representative of stratospheric intrusion air. For quantifying the residual stratospheric component in stratospherically influenced air masses, however, the mixing of tropospheric air into the stratospheric intrusion layers must be taken into account. In fact, the dew-point-mirror instrument at the Zugspitze summit station rarely registers relative humidity (RH) values lower than 10% in stratospheric air intrusions. Since 2007 a programme of routine lidar sounding of ozone, water vapour and aerosol has been conducted in the Garmisch-Partenkirchen area. The lidar results demonstrate that the intrusion layers are dryer by roughly one order of magnitude than indicated in the in-situ measurements. Even in thin layers frequently RH values clearly below 1% have been observed. These thin, undiluted layers present an important challenge for atmospheric modelling. Although the ozone values never reach values typical of the lower-stratosphere it becomes, thus, obvious that, without strong wind shear or convective processes, mixing of stratospheric and tropospheric air must be very slow in most of the free troposphere. As a consequence, the analysis the Zugspitze data can be assumed to be more reliable than anticipated. Finally, the concentrations of Zugspitze carbon monoxide rarely drop inside intrusion layers and normally stay clearly above full stratospheric values. This indicates that most of the CO and, thus, the intrusion air mass originate in the shallow "mixing layer" around the thermal tropopause

  15. How stratospheric are deep stratospheric intrusions?

    NASA Astrophysics Data System (ADS)

    Trickl, T.; Vogelmann, H.; Giehl, H.; Scheel, H.-E.; Sprenger, M.; Stohl, A.

    2014-09-01

    Preliminary attempts of quantifying the stratospheric ozone contribution in the observations at the Zugspitze summit (2962 m a.s.l.) next to Garmisch-Partenkirchen in the German Alps had yielded an approximate doubling of the stratospheric fraction of the Zugspitze ozone during the time period 1978 to 2004. These investigations had been based on data filtering by using low relative humidity (RH) and elevated 7Be as the criteria for selecting half-hour intervals of ozone data representative of stratospheric intrusion air. To quantify the residual stratospheric component in stratospherically influenced air masses, however, the mixing of tropospheric air into the stratospheric intrusion layers must be taken into account. In fact, the dewpoint mirror instrument at the Zugspitze summit station rarely registers RH values lower than 10% in stratospheric air intrusions. Since 2007 a programme of routine lidar sounding of ozone, water vapour and aerosol has been conducted in the Garmisch-Partenkirchen area. The lidar results demonstrate that the intrusion layers are drier by roughly one order of magnitude than indicated in the in situ measurements. Even in thin layers RH values clearly below 1% have frequently been observed. These thin, undiluted layers present an important challenge for atmospheric modelling. Although the ozone values never reach values typical of the lower-stratosphere it becomes, thus, obvious that, without strong wind shear or convective processes, mixing of stratospheric and tropospheric air must be very slow in most of the free troposphere. As a consequence, the analysis the Zugspitze data can be assumed to be more reliable than anticipated. Finally, the concentrations of Zugspitze carbon monoxide rarely drop inside intrusion layers and normally stay clearly above full stratospheric values. This indicates that most of the CO, and thus the intrusion air mass, originates in the shallow "mixing layer" around the thermal tropopause. The CO mixing ratio in

  16. Intrusive Memories in Perpetrators of Violent Crime: Emotions and Cognitions

    ERIC Educational Resources Information Center

    Evans, Ceri; Ehlers, Anke; Mezey, Gillian; Clark, David M.

    2007-01-01

    The authors investigated factors that may determine whether perpetrators of violent crime develop intrusive memories of their offense. Of 105 young offenders who were convicted of killing or seriously harming others, 46% reported distressing intrusive memories, and 6% had posttraumatic stress disorder. Intrusions were associated with lower…

  17. A spatial web/agent-based model to support stakeholders' negotiation regarding land development.

    PubMed

    Pooyandeh, Majeed; Marceau, Danielle J

    2013-11-15

    Decision making in land management can be greatly enhanced if the perspectives of concerned stakeholders are taken into consideration. This often implies negotiation in order to reach an agreement based on the examination of multiple alternatives. This paper describes a spatial web/agent-based modeling system that was developed to support the negotiation process of stakeholders regarding land development in southern Alberta, Canada. This system integrates a fuzzy analytic hierarchy procedure within an agent-based model in an interactive visualization environment provided through a web interface to facilitate the learning and negotiation of the stakeholders. In the pre-negotiation phase, the stakeholders compare their evaluation criteria using linguistic expressions. Due to the uncertainty and fuzzy nature of such comparisons, a fuzzy Analytic Hierarchy Process is then used to prioritize the criteria. The negotiation starts by a development plan being submitted by a user (stakeholder) through the web interface. An agent called the proposer, which represents the proposer of the plan, receives this plan and starts negotiating with all other agents. The negotiation is conducted in a step-wise manner where the agents change their attitudes by assigning a new set of weights to their criteria. If an agreement is not achieved, a new location for development is proposed by the proposer agent. This process is repeated until a location is found that satisfies all agents to a certain predefined degree. To evaluate the performance of the model, the negotiation was simulated with four agents, one of which being the proposer agent, using two hypothetical development plans. The first plan was selected randomly; the other one was chosen in an area that is of high importance to one of the agents. While the agents managed to achieve an agreement about the location of the land development after three rounds of negotiation in the first scenario, seven rounds were required in the second

  18. A Novel Application of Agent-based Modeling: Projecting Water Access and Availability Using a Coupled Hydrologic Agent-based Model in the Nzoia Basin, Kenya

    NASA Astrophysics Data System (ADS)

    Le, A.; Pricope, N. G.

    2015-12-01

    Projections indicate that increasing population density, food production, and urbanization in conjunction with changing climate conditions will place stress on water resource availability. As a result, a holistic understanding of current and future water resource distribution is necessary for creating strategies to identify the most sustainable means of accessing this resource. Currently, most water resource management strategies rely on the application of global climate predictions to physically based hydrologic models to understand potential changes in water availability. However, the need to focus on understanding community-level social behaviors that determine individual water usage is becoming increasingly evident, as predictions derived only from hydrologic models cannot accurately represent the coevolution of basin hydrology and human water and land usage. Models that are better equipped to represent the complexity and heterogeneity of human systems and satellite-derived products in place of or in conjunction with historic data significantly improve preexisting hydrologic model accuracy and application outcomes. We used a novel agent-based sociotechnical model that combines the Soil and Water Assessment Tool (SWAT) and Agent Analyst and applied it in the Nzoia Basin, an area in western Kenya that is becoming rapidly urbanized and industrialized. Informed by a combination of satellite-derived products and over 150 household surveys, the combined sociotechnical model provided unique insight into how populations self-organize and make decisions based on water availability. In addition, the model depicted how population organization and current management alter water availability currently and in the future.

  19. Word of Mouth : An Agent-based Approach to Predictability of Stock Prices

    NASA Astrophysics Data System (ADS)

    Shimokawa, Tetsuya; Misawa, Tadanobu; Watanabe, Kyoko

    This paper addresses how communication processes among investors affect stock prices formation, especially emerging predictability of stock prices, in financial markets. An agent based model, called the word of mouth model, is introduced for analyzing the problem. This model provides a simple, but sufficiently versatile, description of informational diffusion process and is successful in making lucidly explanation for the predictability of small sized stocks, which is a stylized fact in financial markets but difficult to resolve by traditional models. Our model also provides a rigorous examination of the under reaction hypothesis to informational shocks.

  20. A Harris-Todaro Agent-Based Model to Rural-Urban Migration

    NASA Astrophysics Data System (ADS)

    Espíndola, Aquino L.; Silveira, Jaylson J.; Penna, T. J. P.

    2006-09-01

    The Harris-Todaro model of the rural-urban migration process is revisited under an agent-based approach. The migration of the workers is interpreted as a process of social learning by imitation, formalized by a computational model. By simulating this model, we observe a transitional dynamics with continuous growth of the urban fraction of overall population toward an equilibrium. Such an equilibrium is characterized by stabilization of rural-urban expected wages differential (generalized Harris-Todaro equilibrium condition), urban concentration and urban unemployment. These classic results obtained originally by Harris and Todaro are emergent properties of our model.

  1. Agent-Based Framework for Personalized Service Provisioning in Converged IP Networks

    NASA Astrophysics Data System (ADS)

    Podobnik, Vedran; Matijasevic, Maja; Lovrek, Ignac; Skorin-Kapov, Lea; Desic, Sasa

    In a global multi-service and multi-provider market, the Internet Service Providers will increasingly need to differentiate in the service quality they offer and base their operation on new, consumer-centric business models. In this paper, we propose an agent-based framework for the Business-to-Consumer (B2C) electronic market, comprising the Consumer Agents, Broker Agents and Content Agents, which enable Internet consumers to select a content provider in an automated manner. We also discuss how to dynamically allocate network resources to provide end-to-end Quality of Service (QoS) for a given consumer and content provider.

  2. Agent-based approach for generation of a money-centered star network

    NASA Astrophysics Data System (ADS)

    Yang, Jae-Suk; Kwon, Okyu; Jung, Woo-Sung; Kim, In-mook

    2008-09-01

    The history of trade is a progression from a pure barter system. A medium of exchange emerges autonomously in the market, a position currently occupied by money. We investigate an agent-based computational economics model consisting of interacting agents considering distinguishable properties of commodities which represent salability. We also analyze the properties of the commodity network using a spanning tree. We find that the “storage fee” is more crucial than “demand” in determining which commodity is used as a medium of exchange.

  3. Applications of agent-based simulation for human socio-cultural behavior modeling.

    PubMed

    Jiang, Hong; Karwowski, Waldemar; Ahram, Tareq Z

    2012-01-01

    Agent-based modeling and simulation (ABMS) has gained wide attention over the past few years. ABMS is a powerful simulation modeling technique that has a number of applications, including applications to real-world business problems [1]. This modeling technique has been used by scientists to analyze complex system-level behavior by simulating the system from the bottom up. The major application of ABMS includes social, political, biology, and economic sciences. This paper provides an overview of ABMS applications with the emphasis on modeling human socio-cultural behavior (HSCB).

  4. An Agent-Based Model of Centralized Institutions, Social Network Technology, and Revolution

    PubMed Central

    Makowsky, Michael D.; Rubin, Jared

    2013-01-01

    This paper sheds light on the general mechanisms underlying large-scale social and institutional change. We employ an agent-based model to test the impact of authority centralization and social network technology on preference falsification and institutional change. We find that preference falsification is increasing with centralization and decreasing with social network range. This leads to greater cascades of preference revelation and thus more institutional change in highly centralized societies and this effect is exacerbated at greater social network ranges. An empirical analysis confirms the connections that we find between institutional centralization, social radius, preference falsification, and institutional change. PMID:24278280

  5. Finding shared decisions in stakeholder networks: An agent-based approach

    NASA Astrophysics Data System (ADS)

    Le Pira, Michela; Inturri, Giuseppe; Ignaccolo, Matteo; Pluchino, Alessandro; Rapisarda, Andrea

    2017-01-01

    We address the problem of a participatory decision-making process where a shared priority list of alternatives has to be obtained while avoiding inconsistent decisions. An agent-based model (ABM) is proposed to mimic this process in different social networks of stakeholders who interact according to an opinion dynamics model. Simulations' results show the efficacy of interaction in finding a transitive and, above all, shared decision. These findings are in agreement with real participation experiences regarding transport planning decisions and can give useful suggestions on how to plan an effective participation process for sustainable policy-making based on opinion consensus.

  6. Genetic Algorithms for Agent-Based Infrastructure Interdependency Modeling and Analysis

    SciTech Connect

    May Permann

    2007-03-01

    Today’s society relies greatly upon an array of complex national and international infrastructure networks such as transportation, electric power, telecommunication, and financial networks. This paper describes initial research combining agent-based infrastructure modeling software and genetic algorithms (GAs) to help optimize infrastructure protection and restoration decisions. This research proposes to apply GAs to the problem of infrastructure modeling and analysis in order to determine the optimum assets to restore or protect from attack or other disaster. This research is just commencing and therefore the focus of this paper is the integration of a GA optimization method with a simulation through the simulation’s agents.

  7. Advancing complementary and alternative medicine through social network analysis and agent-based modeling.

    PubMed

    Frantz, Terrill L

    2012-01-01

    This paper introduces the contemporary perspectives and techniques of social network analysis (SNA) and agent-based modeling (ABM) and advocates applying them to advance various aspects of complementary and alternative medicine (CAM). SNA and ABM are invaluable methods for representing, analyzing and projecting complex, relational, social phenomena; they provide both an insightful vantage point and a set of analytic tools that can be useful in a wide range of contexts. Applying these methods in the CAM context can aid the ongoing advances in the CAM field, in both its scientific aspects and in developing broader acceptance in associated stakeholder communities.

  8. A Participatory Agent-Based Simulation for Indoor Evacuation Supported by Google Glass

    PubMed Central

    Sánchez, Jesús M.; Carrera, Álvaro; Iglesias, Carlos Á.; Serrano, Emilio

    2016-01-01

    Indoor evacuation systems are needed for rescue and safety management. One of the challenges is to provide users with personalized evacuation routes in real time. To this end, this project aims at exploring the possibilities of Google Glass technology for participatory multiagent indoor evacuation simulations. Participatory multiagent simulation combines scenario-guided agents and humans equipped with Google Glass that coexist in a shared virtual space and jointly perform simulations. The paper proposes an architecture for participatory multiagent simulation in order to combine devices (Google Glass and/or smartphones) with an agent-based social simulator and indoor tracking services. PMID:27563911

  9. Agent Based Modeling of Collaboration and Work Practices Onboard the International Space Station

    NASA Technical Reports Server (NTRS)

    Acquisti, Alessandro; Sierhuis, Maarten; Clancey, William J.; Bradshaw, Jeffrey M.; Shaffo, Mike (Technical Monitor)

    2002-01-01

    The International Space Station is one the most complex projects ever, with numerous interdependent constraints affecting productivity and crew safety. This requires planning years before crew expeditions, and the use of sophisticated scheduling tools. Human work practices, however, are difficult to study and represent within traditional planning tools. We present an agent-based model and simulation of the activities and work practices of astronauts onboard the ISS based on an agent-oriented approach. The model represents 'a day in the life' of the ISS crew and is developed in Brahms, an agent-oriented, activity-based language used to model knowledge in situated action and learning in human activities.

  10. ModelforAnalyzing Human Communication Network Based onAgent-Based Simulation

    NASA Astrophysics Data System (ADS)

    Matsuyama, Shinako; Terano, Takao

    This paper discusses dynamic properties of human communications networks, which appears as a result of informationexchanges among people. We propose agent-based simulation (ABS) to examine implicit mechanisms behind the dynamics. The ABS enables us to reveal the characteristics and the differences of the networks regarding the specific communicationgroups. We perform experiments on the ABS with activity data from questionnaires survey and with virtual data which isdifferent from the activity data. We compare the difference between them and show the effectiveness of the ABS through theexperiments.

  11. A Participatory Agent-Based Simulation for Indoor Evacuation Supported by Google Glass.

    PubMed

    Sánchez, Jesús M; Carrera, Álvaro; Iglesias, Carlos Á; Serrano, Emilio

    2016-08-24

    Indoor evacuation systems are needed for rescue and safety management. One of the challenges is to provide users with personalized evacuation routes in real time. To this end, this project aims at exploring the possibilities of Google Glass technology for participatory multiagent indoor evacuation simulations. Participatory multiagent simulation combines scenario-guided agents and humans equipped with Google Glass that coexist in a shared virtual space and jointly perform simulations. The paper proposes an architecture for participatory multiagent simulation in order to combine devices (Google Glass and/or smartphones) with an agent-based social simulator and indoor tracking services.

  12. Layered intrusions of the Duluth Complex, Minnesota, USA

    USGS Publications Warehouse

    Miller, J.D.; Ripley, E.M.; ,

    1996-01-01

    The Duluth Complex and associated subvolcanic intrusions comprise a large (5000 km2) intrusive complex in northeastern Minnesota that was emplaced into comagmatic volcanics during the development of the 1.1 Ga Midcontinent rift in North America. In addition to anorthositic and felsic intrusions, the Duluth Complex is composed of many individual mafic layered intrusions of tholeiitic affinity. The cumulate stratigraphies and cryptic variations of six of the better exposed and better studied intrusions are described here to demonstrate the variability in their cumulus mineral paragenesis.

  13. Agent-based model of angiogenesis simulates capillary sprout initiation in multicellular networks.

    PubMed

    Walpole, J; Chappell, J C; Cluceru, J G; Mac Gabhann, F; Bautch, V L; Peirce, S M

    2015-09-01

    Many biological processes are controlled by both deterministic and stochastic influences. However, efforts to model these systems often rely on either purely stochastic or purely rule-based methods. To better understand the balance between stochasticity and determinism in biological processes a computational approach that incorporates both influences may afford additional insight into underlying biological mechanisms that give rise to emergent system properties. We apply a combined approach to the simulation and study of angiogenesis, the growth of new blood vessels from existing networks. This complex multicellular process begins with selection of an initiating endothelial cell, or tip cell, which sprouts from the parent vessels in response to stimulation by exogenous cues. We have constructed an agent-based model of sprouting angiogenesis to evaluate endothelial cell sprout initiation frequency and location, and we have experimentally validated it using high-resolution time-lapse confocal microscopy. ABM simulations were then compared to a Monte Carlo model, revealing that purely stochastic simulations could not generate sprout locations as accurately as the rule-informed agent-based model. These findings support the use of rule-based approaches for modeling the complex mechanisms underlying sprouting angiogenesis over purely stochastic methods.

  14. Agent-based Model for the Coupled Human-Climate System

    NASA Astrophysics Data System (ADS)

    Zvoleff, A.; Werner, B.

    2006-12-01

    Integrated assessment models have been used to predict the outcome of coupled economic growth, resource use, greenhouse gas emissions and climate change, both for scientific and policy purposes. These models generally have employed significant simplifications that suppress nonlinearities and the possibility of multiple equilibria in both their economic (DeCanio, 2005) and climate (Schneider and Kuntz-Duriseti, 2002) components. As one step toward exploring general features of the nonlinear dynamics of the coupled system, we have developed a series of variations on the well studied RICE and DICE models, which employ different forms of agent-based market dynamics and "climate surprises." Markets are introduced through the replacement of the production function of the DICE/RICE models with an agent-based market modeling the interactions of producers, policymakers, and consumer agents. Technological change and population growth are treated endogenously. Climate surprises are representations of positive (for example, ice sheet collapse) or negative (for example, increased aerosols from desertification) feedbacks that are turned on with probability depending on warming. Initial results point toward the possibility of large amplitude instabilities in the coupled human-climate system owing to the mismatch between short outlook market dynamics and long term climate responses. Implications for predictability of future climate will be discussed. Supported by the Andrew W Mellon Foundation and the UC Academic Senate.

  15. Strategic directions for agent-based modeling: avoiding the YAAWN syndrome

    PubMed Central

    O’Sullivan, David; Evans, Tom; Manson, Steven; Metcalf, Sara; Ligmann-Zielinska, Arika; Bone, Chris

    2015-01-01

    In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances – in terms of model complexity, model evaluation, and model structure – can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from ‘yet another model’ to doing better science with models. PMID:27158257

  16. SAL: a language for developing an agent-based architecture for mobile robots

    NASA Astrophysics Data System (ADS)

    Lim, Willie Y.; Verzulli, Joe

    1993-05-01

    SAL (the SmartyCat Agent Language) is a language being developed for programming SmartyCat, our mobile robot. SmartyCat's underlying software architecture is agent-based. At the lowest level, the robot sensors and actuators are controlled by agents (viz., the sensing and acting agents, respectively). SAL provides the constructs for organizing these agents into many structures. In particular, SAL supports the subsumption architecture approach. At higher levels of abstraction, SAL can be used for writing programs based on Minsky's Society of Mind paradigm. Structurally, a SAL program is a graph, where the nodes are software modules called agents, and the arcs represent abstract communication links between agents. In SAL, an agent is a CLOS object with input and output ports. Input ports are used for presenting data from the outside world (i.e., other agents) to the agent. Data are presented to the outside world by the agent through its output ports. The main body of the SAL code for the agent specifies the computation or the action performed by the agent. This paper describes how SAL is being used for implementing the agent-based SmartyCat software architecture on a Cybermotion K2A platform.

  17. iCrowd: agent-based behavior modeling and crowd simulator

    NASA Astrophysics Data System (ADS)

    Kountouriotis, Vassilios I.; Paterakis, Manolis; Thomopoulos, Stelios C. A.

    2016-05-01

    Initially designed in the context of the TASS (Total Airport Security System) FP-7 project, the Crowd Simulation platform developed by the Integrated Systems Lab of the Institute of Informatics and Telecommunications at N.C.S.R. Demokritos, has evolved into a complete domain-independent agent-based behavior simulator with an emphasis on crowd behavior and building evacuation simulation. Under continuous development, it reflects an effort to implement a modern, multithreaded, data-oriented simulation engine employing latest state-of-the-art programming technologies and paradigms. It is based on an extensible architecture that separates core services from the individual layers of agent behavior, offering a concrete simulation kernel designed for high-performance and stability. Its primary goal is to deliver an abstract platform to facilitate implementation of several Agent-Based Simulation solutions with applicability in several domains of knowledge, such as: (i) Crowd behavior simulation during [in/out] door evacuation. (ii) Non-Player Character AI for Game-oriented applications and Gamification activities. (iii) Vessel traffic modeling and simulation for Maritime Security and Surveillance applications. (iv) Urban and Highway Traffic and Transportation Simulations. (v) Social Behavior Simulation and Modeling.

  18. Network Interventions on Physical Activity in an Afterschool Program: An Agent-Based Social Network Study

    PubMed Central

    Zhang, Jun; Shoham, David A.; Tesdahl, Eric

    2015-01-01

    Objectives. We studied simulated interventions that leveraged social networks to increase physical activity in children. Methods. We studied a real-world social network of 81 children (average age = 7.96 years) who lived in low socioeconomic status neighborhoods, and attended public schools and 1 of 2 structured afterschool programs. The sample was ethnically diverse, and 44% were overweight or obese. We used social network analysis and agent-based modeling simulations to test whether implementing a network intervention would increase children’s physical activity. We tested 3 intervention strategies. Results. The intervention that targeted opinion leaders was effective in increasing the average level of physical activity across the entire network. However, the intervention that targeted the most sedentary children was the best at increasing their physical activity levels. Conclusions. Which network intervention to implement depends on whether the goal is to shift the entire distribution of physical activity or to influence those most adversely affected by low physical activity. Agent-based modeling could be an important complement to traditional project planning tools, analogous to sample size and power analyses, to help researchers design more effective interventions for increasing children’s physical activity. PMID:25689202

  19. Linking agent-based models and stochastic models of financial markets.

    PubMed

    Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H Eugene

    2012-05-29

    It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that "fat" tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting.

  20. Group-Wise Herding Behavior in Financial Markets: An Agent-Based Modeling Approach

    PubMed Central

    Kim, Minsung; Kim, Minki

    2014-01-01

    In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy. PMID:24714635

  1. Combining agent-based modeling and life cycle assessment for the evaluation of mobility policies.

    PubMed

    Florent, Querini; Enrico, Benetto

    2015-02-03

    This article presents agent-based modeling (ABM) as a novel approach for consequential life cycle assessment (C-LCA) of large scale policies, more specifically mobility-related policies. The approach is validated at the Luxembourgish level (as a first case study). The agent-based model simulates the car market (sales, use, and dismantling) of the population of users in the period 2013-2020, following the implementation of different mobility policies and available electric vehicles. The resulting changes in the car fleet composition as well as the hourly uses of the vehicles are then used to derive consistent LCA results, representing the consequences of the policies. Policies will have significant environmental consequences: when using ReCiPe2008, we observe a decrease of global warming, fossil depletion, acidification, ozone depletion, and photochemical ozone formation and an increase of metal depletion, ionizing radiations, marine eutrophication, and particulate matter formation. The study clearly shows that the extrapolation of LCA results for the circulating fleet at national scale following the introduction of the policies from the LCAs of single vehicles by simple up-scaling (using hypothetical deployment scenarios) would be flawed. The inventory has to be directly conducted at full scale and to this aim, ABM is indeed a promising approach, as it allows identifying and quantifying emerging effects while modeling the Life Cycle Inventory of vehicles at microscale through the concept of agents.

  2. Agent-based modeling of the immune system: NetLogo, a promising framework.

    PubMed

    Chiacchio, Ferdinando; Pennisi, Marzio; Russo, Giulia; Motta, Santo; Pappalardo, Francesco

    2014-01-01

    Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms.

  3. Modeling the Information Age Combat Model: An Agent-Based Simulation of Network Centric Operations

    NASA Technical Reports Server (NTRS)

    Deller, Sean; Rabadi, Ghaith A.; Bell, Michael I.; Bowling, Shannon R.; Tolk, Andreas

    2010-01-01

    The Information Age Combat Model (IACM) was introduced by Cares in 2005 to contribute to the development of an understanding of the influence of connectivity on force effectiveness that can eventually lead to quantitative prediction and guidelines for design and employment. The structure of the IACM makes it clear that the Perron-Frobenius Eigenvalue is a quantifiable metric with which to measure the organization of a networked force. The results of recent experiments presented in Deller, et aI., (2009) indicate that the value of the Perron-Frobenius Eigenvalue is a significant measurement of the performance of an Information Age combat force. This was accomplished through the innovative use of an agent-based simulation to model the IACM and represents an initial contribution towards a new generation of combat models that are net-centric instead of using the current platform-centric approach. This paper describes the intent, challenges, design, and initial results of this agent-based simulation model.

  4. Strategic directions for agent-based modeling: avoiding the YAAWN syndrome.

    PubMed

    O'Sullivan, David; Evans, Tom; Manson, Steven; Metcalf, Sara; Ligmann-Zielinska, Arika; Bone, Chris

    In this short communication, we examine how agent-based modeling has become common in land change science and is increasingly used to develop case studies for particular times and places. There is a danger that the research community is missing a prime opportunity to learn broader lessons from the use of agent-based modeling (ABM), or at the very least not sharing these lessons more widely. How do we find an appropriate balance between empirically rich, realistic models and simpler theoretically grounded models? What are appropriate and effective approaches to model evaluation in light of uncertainties not only in model parameters but also in model structure? How can we best explore hybrid model structures that enable us to better understand the dynamics of the systems under study, recognizing that no single approach is best suited to this task? Under what circumstances - in terms of model complexity, model evaluation, and model structure - can ABMs be used most effectively to lead to new insight for stakeholders? We explore these questions in the hope of helping the growing community of land change scientists using models in their research to move from 'yet another model' to doing better science with models.

  5. Agent-based modeling of osteogenic differentiation of mesenchymal stem cells in porous biomaterials.

    PubMed

    Bayrak, Elif S; Mehdizadeh, Hamidreza; Akar, Banu; Somo, Sami I; Brey, Eric M; Cinar, Ali

    2014-01-01

    Mesenchymal stem cells (MSC) have shown promise in tissue engineering applications due to their potential for differentiating into mesenchymal tissues such as osteocytes, chondrocytes, and adipocytes and releasing proteins to promote tissue regeneration. One application involves seeding MSCs in biomaterial scaffolds to promote osteogenesis in the repair of bone defects following implantation. However, predicting in vivo survival and differentiation of MSCs in biomaterials is challenging. Rapid and stable vascularization of scaffolds is required to supply nutrients and oxygen that MSCs need to survive as well as to go through osteogenic differentiation. The objective of this study is to develop an agent-based model and simulator that can be used to investigate the effects of using gradient growth factors on survival and differentiation of MSCs seeded in scaffolds. An agent-based model is developed to simulate the MSC behavior. The effect of vascular endothelial growth factor (VEGF) and bone morphogenic protein-2 (BMP-2) on both survival and osteogenic differentiation is studied. Results showed that the survival ratio of MSCs can be enhanced by increasing VEGF concentration. BMP-2 caused a slight increase on survival ratio. Osteogenesis strongly depends on the VEGF concentration as well because of its effect on vascularization. BMP-2 increased the osteogenic differentiation of MSCs.

  6. Uses of Agent-Based Modeling for Health Communication: the TELL ME Case Study.

    PubMed

    Barbrook-Johnson, Peter; Badham, Jennifer; Gilbert, Nigel

    2016-07-19

    Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals' protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.

  7. Attribute Assignment to a Synthetic Population in Support of Agent-Based Disease Modeling.

    PubMed

    Cajka, James C; Cooley, Philip C; Wheaton, William D

    2010-09-01

    Communicable-disease transmission models are useful for the testing of prevention and intervention strategies. Agent-based models (ABMs) represent a new and important class of the many types of disease transmission models in use. Agent-based disease models benefit from their ability to assign disease transmission probabilities based on characteristics shared by individual agents. These shared characteristics allow ABMs to apply transmission probabilities when agents come together in geographic space. Modeling these types of social interactions requires data, and the results of the model largely depend on the quality of these input data. We initially generated a synthetic population for the United States, in support of the Models of Infectious Disease Agent Study. Subsequently, we created shared characteristics to use in ABMs. The specific goals for this task were to assign the appropriately aged populations to schools, workplaces, and public transit. Each goal presented its own challenges and problems; therefore, we used different techniques to create each type of shared characteristic. These shared characteristics have allowed disease models to more realistically predict the spread of disease, both spatially and temporally.

  8. Group-wise herding behavior in financial markets: an agent-based modeling approach.

    PubMed

    Kim, Minsung; Kim, Minki

    2014-01-01

    In this paper, we shed light on the dynamic characteristics of rational group behaviors and the relationship between monetary policy and economic units in the financial market by using an agent-based model (ABM), the Hurst exponent, and the Shannon entropy. First, an agent-based model is used to analyze the characteristics of the group behaviors at different levels of irrationality. Second, the Hurst exponent is applied to analyze the characteristics of the trend-following irrationality group. Third, the Shannon entropy is used to analyze the randomness and unpredictability of group behavior. We show that in a system that focuses on macro-monetary policy, steep fluctuations occur, meaning that the medium-level irrationality group has the highest Hurst exponent and Shannon entropy among all of the groups. However, in a system that focuses on micro-monetary policy, all group behaviors follow a stable trend, and the medium irrationality group thus remains stable, too. Likewise, in a system that focuses on both micro- and macro-monetary policies, all groups tend to be stable. Consequently, we find that group behavior varies across economic units at each irrationality level for micro- and macro-monetary policy in the financial market. Together, these findings offer key insights into monetary policy.

  9. Simulating the elimination of sleeping sickness with an agent-based model

    PubMed Central

    Grébaut, Pascal; Girardin, Killian; Fédérico, Valentine; Bousquet, François

    2016-01-01

    Although Human African Trypanosomiasis is largely considered to be in the process of extinction today, the persistence of human and animal reservoirs, as well as the vector, necessitates a laborious elimination process. In this context, modeling could be an effective tool to evaluate the ability of different public health interventions to control the disease. Using the Cormas® system, we developed HATSim, an agent-based model capable of simulating the possible endemic evolutions of sleeping sickness and the ability of National Control Programs to eliminate the disease. This model takes into account the analysis of epidemiological, entomological, and ecological data from field studies conducted during the last decade, making it possible to predict the evolution of the disease within this area over a 5-year span. In this article, we first present HATSim according to the Overview, Design concepts, and Details (ODD) protocol that is classically used to describe agent-based models, then, in a second part, we present predictive results concerning the evolution of Human African Trypanosomiasis in the village of Lambi (Cameroon), in order to illustrate the interest of such a tool. Our results are consistent with what was observed in the field by the Cameroonian National Control Program (CNCP). Our simulations also revealed that regular screening can be sufficient, although vector control applied to all areas with human activities could be significantly more efficient. Our results indicate that the current model can already help decision-makers in planning the elimination of the disease in foci. PMID:28008825

  10. A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

    SciTech Connect

    Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung; Kao, Shih-Chieh; Tuttle, Mark A; Bhaduri, Budhendra L

    2011-01-01

    The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

  11. Reaching unanimous agreements within agent-based negotiation teams with linear and monotonic utility functions.

    PubMed

    Sanchez-Anguix, Victor; Julian, Vicente; Botti, Vicente; García-Fornes, Ana

    2012-06-01

    In this article, an agent-based negotiation model for negotiation teams that negotiate a deal with an opponent is presented. Agent-based negotiation teams are groups of agents that join together as a single negotiation party because they share an interest that is related to the negotiation process. The model relies on a trusted mediator that coordinates and helps team members in the decisions that they have to take during the negotiation process: which offer is sent to the opponent, and whether the offers received from the opponent are accepted. The main strength of the proposed negotiation model is the fact that it guarantees unanimity within team decisions since decisions report a utility to team members that is greater than or equal to their aspiration levels at each negotiation round. This work analyzes how unanimous decisions are taken within the team and the robustness of the model against different types of manipulations. An empirical evaluation is also performed to study the impact of the different parameters of the model.

  12. An Agent-Based Epidemic Simulation of Social Behaviors Affecting HIV Transmission among Taiwanese Homosexuals

    PubMed Central

    2015-01-01

    Computational simulations are currently used to identify epidemic dynamics, to test potential prevention and intervention strategies, and to study the effects of social behaviors on HIV transmission. The author describes an agent-based epidemic simulation model of a network of individuals who participate in high-risk sexual practices, using number of partners, condom usage, and relationship length to distinguish between high- and low-risk populations. Two new concepts—free links and fixed links—are used to indicate tendencies among individuals who either have large numbers of short-term partners or stay in long-term monogamous relationships. An attempt was made to reproduce epidemic curves of reported HIV cases among male homosexuals in Taiwan prior to using the agent-based model to determine the effects of various policies on epidemic dynamics. Results suggest that when suitable adjustments are made based on available social survey statistics, the model accurately simulates real-world behaviors on a large scale. PMID:25815047

  13. Effectiveness of dynamic rescheduling in agent-based flexible manufacturing systems

    NASA Astrophysics Data System (ADS)

    Saad, Ashraf; Biswas, Gautam; Kawamura, Kazuhiko; Johnson, Eric M.

    1997-12-01

    This work has been developed within the framework of agent- based decentralized scheduling for flexible manufacturing systems. In this framework, all workcells comprising the manufacturing system, and the products to be generated, are modeled via intelligent software agents. These agents interact dynamically using a bidding production reservation (BPRS) scheme, based on the Contract Net Protocol, to devise the production schedule for each product unit. Simulation studies of a job shop have demonstrated the gains in performance achieved by this approach over heuristic dispatching rules commonly used in industry. Manufacturing environments are also prone to operational uncertainties such as variations in processing times and machine breakdowns. In order to cope with these uncertainties, the BPRS algorithm has been extended for dynamic rescheduling to also occur in a fully decentralized manner. The resulting multi-agent rescheduling scheme results in decentralized control of flexible manufacturing systems that are capable of responding dynamically to such operational uncertainties, thereby enhancing the robustness and fault tolerance of the proposed scheduling approach. This paper also presents the effects of the proposed agent-based decentralized scheduling approach on the performance of the underlying flexible manufacturing system under a variety of production and scheduling scenarios, including forward and backward scheduling. Future directions for this work include applying the proposed scheduling approach to other advanced manufacturing areas such as agile and holonic manufacturing.

  14. An agent-based model for domestic water management in Valladolid metropolitan area

    NASA Astrophysics Data System (ADS)

    GaláN, José M.; López-Paredes, Adolfo; Del Olmo, Ricardo

    2009-05-01

    In this work we demonstrate that the combination of agent-based modeling and simulation constitutes a useful methodological approach to dealing with the complexity derived from multiple factors with influence in the domestic water management in emergent metropolitan areas. In particular, we adapt and integrate different social submodels, models of urban dynamics, water consumption, and technological and opinion diffusion, in an agent-based model that is, in turn, linked with a geographic information system. The result is a computational environment that enables simulating and comparing various water demand scenarios. We have parameterized our general model for the metropolitan area of Valladolid (Spain).The model shows the influence of urban dynamics (e.g., intrapopulation movements, residence typology, and changes in the territorial model) and other socio-geographic effects (technological and opinion dynamics) in domestic water demand. The conclusions drawn in this way would have been difficult to obtain using other approaches, such as conventional forecasting methods, given the need to integrate different socioeconomic and geographic aspects in one single model. We illustrate that the described methodology can complement conventional approaches, providing descriptive and formal additional insights into domestic water demand management problems.

  15. Agent-Based Modeling of the Immune System: NetLogo, a Promising Framework

    PubMed Central

    Chiacchio, Ferdinando; Russo, Giulia; Pappalardo, Francesco

    2014-01-01

    Several components that interact with each other to evolve a complex, and, in some cases, unexpected behavior, represents one of the main and fascinating features of the mammalian immune system. Agent-based modeling and cellular automata belong to a class of discrete mathematical approaches in which entities (agents) sense local information and undertake actions over time according to predefined rules. The strength of this approach is characterized by the appearance of a global behavior that emerges from interactions among agents. This behavior is unpredictable, as it does not follow linear rules. There are a lot of works that investigates the immune system with agent-based modeling and cellular automata. They have shown the ability to see clearly and intuitively into the nature of immunological processes. NetLogo is a multiagent programming language and modeling environment for simulating complex phenomena. It is designed for both research and education and is used across a wide range of disciplines and education levels. In this paper, we summarize NetLogo applications to immunology and, particularly, how this framework can help in the development and formulation of hypotheses that might drive further experimental investigations of disease mechanisms. PMID:24864263

  16. Linking agent-based models and stochastic models of financial markets

    PubMed Central

    Feng, Ling; Li, Baowen; Podobnik, Boris; Preis, Tobias; Stanley, H. Eugene

    2012-01-01

    It is well-known that financial asset returns exhibit fat-tailed distributions and long-term memory. These empirical features are the main objectives of modeling efforts using (i) stochastic processes to quantitatively reproduce these features and (ii) agent-based simulations to understand the underlying microscopic interactions. After reviewing selected empirical and theoretical evidence documenting the behavior of traders, we construct an agent-based model to quantitatively demonstrate that “fat” tails in return distributions arise when traders share similar technical trading strategies and decisions. Extending our behavioral model to a stochastic model, we derive and explain a set of quantitative scaling relations of long-term memory from the empirical behavior of individual market participants. Our analysis provides a behavioral interpretation of the long-term memory of absolute and squared price returns: They are directly linked to the way investors evaluate their investments by applying technical strategies at different investment horizons, and this quantitative relationship is in agreement with empirical findings. Our approach provides a possible behavioral explanation for stochastic models for financial systems in general and provides a method to parameterize such models from market data rather than from statistical fitting. PMID:22586086

  17. An efficient communication strategy for mobile agent based distributed spatial data mining application

    NASA Astrophysics Data System (ADS)

    Han, Guodong; Wang, Jiazhen

    2005-11-01

    An efficient communication strategy is proposed in this paper, which aims to improve the response time and availability of mobile agent based distributed spatial data mining applications. When dealing with decomposed complex data mining tasks or On-Line Analytical Processing (OLAP), mobile agents authorized by the specified user need to coordinate and cooperate with each other by employing given communication method to fulfill the subtasks delegated to them. Agent interactive behavior, e.g. messages passing, intermediate results exchanging and final results merging, must happen after the specified path is determined by executing given routing selection algorithm. Most of algorithms exploited currently run in time that grows approximately quadratic with the size of the input nodes where mobile agents migrate between. In order to gain enhanced communication performance by reducing the execution time of the decision algorithm, we propose an approach to reduce the number of nodes involved in the computation. In practice, hosts in the system are reorganized into groups in terms of the bandwidth between adjacent nodes. Then, we find an optimal node for each group with high bandwidth and powerful computing resources, which is managed by an agent dispatched by agent home node. With that, the communication pattern can be implemented at a higher level of abstraction and contribute to improving the overall performance of mobile agent based distributed spatial data mining applications.

  18. Towards a framework for agent-based image analysis of remote-sensing data.

    PubMed

    Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

    2015-04-03

    Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects' properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA).

  19. Towards a framework for agent-based image analysis of remote-sensing data

    PubMed Central

    Hofmann, Peter; Lettmayer, Paul; Blaschke, Thomas; Belgiu, Mariana; Wegenkittl, Stefan; Graf, Roland; Lampoltshammer, Thomas Josef; Andrejchenko, Vera

    2015-01-01

    Object-based image analysis (OBIA) as a paradigm for analysing remotely sensed image data has in many cases led to spatially and thematically improved classification results in comparison to pixel-based approaches. Nevertheless, robust and transferable object-based solutions for automated image analysis capable of analysing sets of images or even large image archives without any human interaction are still rare. A major reason for this lack of robustness and transferability is the high complexity of image contents: Especially in very high resolution (VHR) remote-sensing data with varying imaging conditions or sensor characteristics, the variability of the objects’ properties in these varying images is hardly predictable. The work described in this article builds on so-called rule sets. While earlier work has demonstrated that OBIA rule sets bear a high potential of transferability, they need to be adapted manually, or classification results need to be adjusted manually in a post-processing step. In order to automate these adaptation and adjustment procedures, we investigate the coupling, extension and integration of OBIA with the agent-based paradigm, which is exhaustively investigated in software engineering. The aims of such integration are (a) autonomously adapting rule sets and (b) image objects that can adopt and adjust themselves according to different imaging conditions and sensor characteristics. This article focuses on self-adapting image objects and therefore introduces a framework for agent-based image analysis (ABIA). PMID:27721916

  20. A mathematical framework for agent based models of complex biological networks.

    PubMed

    Hinkelmann, Franziska; Murrugarra, David; Jarrah, Abdul Salam; Laubenbacher, Reinhard

    2011-07-01

    Agent-based modeling and simulation is a useful method to study biological phenomena in a wide range of fields, from molecular biology to ecology. Since there is currently no agreed-upon standard way to specify such models, it is not always easy to use published models. Also, since model descriptions are not usually given in mathematical terms, it is difficult to bring mathematical analysis tools to bear, so that models are typically studied through simulation. In order to address this issue, Grimm et al. proposed a protocol for model specification, the so-called ODD protocol, which provides a standard way to describe models. This paper proposes an addition to the ODD protocol which allows the description of an agent-based model as a dynamical system, which provides access to computational and theoretical tools for its analysis. The mathematical framework is that of algebraic models, that is, time-discrete dynamical systems with algebraic structure. It is shown by way of several examples how this mathematical specification can help with model analysis. This mathematical framework can also accommodate other model types such as Boolean networks and the more general logical models, as well as Petri nets.

  1. Modeling the Population Dynamics of Antibiotic-Resistant Bacteria:. AN Agent-Based Approach

    NASA Astrophysics Data System (ADS)

    Murphy, James T.; Walshe, Ray; Devocelle, Marc

    The response of bacterial populations to antibiotic treatment is often a function of a diverse range of interacting factors. In order to develop strategies to minimize the spread of antibiotic resistance in pathogenic bacteria, a sound theoretical understanding of the systems of interactions taking place within a colony must be developed. The agent-based approach to modeling bacterial populations is a useful tool for relating data obtained at the molecular and cellular level with the overall population dynamics. Here we demonstrate an agent-based model, called Micro-Gen, which has been developed to simulate the growth and development of bacterial colonies in culture. The model also incorporates biochemical rules and parameters describing the kinetic interactions of bacterial cells with antibiotic molecules. Simulations were carried out to replicate the development of methicillin-resistant S. aureus (MRSA) colonies growing in the presence of antibiotics. The model was explored to see how the properties of the system emerge from the interactions of the individual bacterial agents in order to achieve a better mechanistic understanding of the population dynamics taking place. Micro-Gen provides a good theoretical framework for investigating the effects of local environmental conditions and cellular properties on the response of bacterial populations to antibiotic exposure in the context of a simulated environment.

  2. An Agent-Based Model of Farmer Decision Making in Jordan

    NASA Astrophysics Data System (ADS)

    Selby, Philip; Medellin-Azuara, Josue; Harou, Julien; Klassert, Christian; Yoon, Jim

    2016-04-01

    We describe an agent based hydro-economic model of groundwater irrigated agriculture in the Jordan Highlands. The model employs a Multi-Agent-Simulation (MAS) framework and is designed to evaluate direct and indirect outcomes of climate change scenarios and policy interventions on farmer decision making, including annual land use, groundwater use for irrigation, and water sales to a water tanker market. Land use and water use decisions are simulated for groups of farms grouped by location and their behavioural and economic similarities. Decreasing groundwater levels, and the associated increase in pumping costs, are important drivers for change within Jordan'S agricultural sector. We describe how this is considered by coupling of agricultural and groundwater models. The agricultural production model employs Positive Mathematical Programming (PMP), a method for calibrating agricultural production functions to observed planted areas. PMP has successfully been used with disaggregate models for policy analysis. We adapt the PMP approach to allow explicit evaluation of the impact of pumping costs, groundwater purchase fees and a water tanker market. The work demonstrates the applicability of agent-based agricultural decision making assessment in the Jordan Highlands and its integration with agricultural model calibration methods. The proposed approach is designed and implemented with software such that it could be used to evaluate a variety of physical and human influences on decision making in agricultural water management.

  3. Psychological impact of illness intrusiveness in epilepsy - comparison of treatments.

    PubMed

    Poochikian-Sarkissian, Sonia; Sidani, Souraya; Wennberg, Richard A; Devins, Gerald M

    2008-03-01

    Chronic illnesses are associated with multiple stressors that compromise quality of life (QOL). Implicit in many of these is the concept of illness intrusiveness, the disruption of lifestyles and activities attributable to constraints imposed by chronic disease and its treatment. This study tested the illness intrusiveness theoretical framework in epilepsy and compared the impact of pharmacological and surgical treatments on illness intrusiveness and QOL. Cross-sectional data compared three epilepsy groups (N = 145): (a) 40 patients admitted for presurgical evaluation to an Epilepsy Monitoring Unit; (b) 52 patients treated pharmacologically; and (c) 53 post-surgical patients. Illness intrusiveness differed significantly across epilepsy patients with the differences primarily related to seizure control. Illness intrusiveness varied inversely with seizure control (p < .05). Seizure freedom, whether achieved by surgical or pharmacological treatments, was associated with maximal reduction of illness intrusiveness. Increased illness intrusiveness correlated significantly with decreased QOL and increased depressive symptoms. Perceived control over diverse life domains correlated positively with QOL and psychosocial outcomes. Path analysis supported the validity of the illness intrusiveness theoretical framework in epilepsy. Illness intrusiveness is an important determinant of the psychosocial impact of epilepsy and its treatment. Effective pharmacological or surgical treatment may reduce illness intrusiveness in epilepsy. Findings also offer encouragement that QOL in epilepsy, as in other chronic conditions, may be enhanced by multidisciplinary bio-psychosocial efforts. Health care providers should consider multifaceted interventions to reduce illness intrusiveness and, thereby, improve QOL.

  4. Non-intrusive refrigerant charge indicator

    DOEpatents

    Mei, Viung C.; Chen, Fang C.; Kweller, Esher

    2005-03-22

    A non-intrusive refrigerant charge level indicator includes a structure for measuring at least one temperature at an outside surface of a two-phase refrigerant line section. The measured temperature can be used to determine the refrigerant charge status of an HVAC system, and can be converted to a pressure of the refrigerant in the line section and compared to a recommended pressure range to determine whether the system is under-charged, properly charged or over-charged. A non-intrusive method for assessing the refrigerant charge level in a system containing a refrigerant fluid includes the step of measuring a temperature at least one outside surface of a two-phase region of a refrigerant containing refrigerant line, wherein the temperature measured can be converted to a refrigerant pressure within the line section.

  5. Increasing Intrusion Tolerance via Scalable Redundancy

    DTIC Science & Technology

    2006-07-01

    versioning can be used as a mechanism to aid the provision of strong concurrent semantics and intrusion tolerance in a very different way. To illustrate...need for services (e.g., namespace, key management, metadata, and LDAP ) and distributed data structures (e.g., b-trees, queues, and logs) to be...caption. Structures, enumerations and types used in the pseudo-code are given on lines 100-107. The definition of a Candidate includes the

  6. [The removal of organs and intrusion].

    PubMed

    Breynaert, Sophie; Tournier-Vervliet, Anne

    2015-04-01

    Approaching the family of a brain dead patient to enquire about the deceased's wishes with regard to the donation of their organs is a delicate matter. It is also a difficult time for the medical and paramedical teams, in intensive care as well as the operating theatre. Describing the phenomena of potential intrusions and the methods of guidance and support can help those involved adjust their practice to the specific situation of the families and professionals concerned.

  7. Non-intrusive electric field sensing

    NASA Astrophysics Data System (ADS)

    Schultz, S. M.; Selfridge, R.; Chadderdon, S.; Perry, D.; Stan, N.

    2014-04-01

    This paper presents an overview of non-intrusive electric field sensing. The non-intrusive nature is attained by creating a sensor that is entirely dielectric, has a small cross-sectional area, and has the interrogation electronics a long distance away from the system under test. One non-intrusive electric field sensing technology is the slab coupled optical fiber sensor (SCOS). The SCOS consists of an electro-optic crystal attached to the surface of a D-shaped optical fiber. It is entirely dielectric and has a cross-sectional area down to 0.3mm by 0.3mm. The SCOS device functions as an electric field sensor through use of resonant mode coupling between the crystal waveguide and the core of a D-shaped optical fiber. The resonant mode coupling of a SCOS device occurs at specific wavelengths whose spectral locations are determined in part by the effective refractive index of the modes in the slab. An electric field changes the refractive index of the slab causing a shift in the spectral position of the resonant modes. This paper describes an overview of the SCOS technology including the theory, fabrication, and operation. The effect of crystal orientation and crystal type are explained with respect to directional sensitivity and frequency response.

  8. Evaluating network analysis and agent based modeling for investigating the stability of commercial air carrier schedules

    NASA Astrophysics Data System (ADS)

    Conway, Sheila Ruth

    For a number of years, the United States Federal Government has been formulating the Next Generation Air Transportation System plans for National Airspace System improvement. These improvements attempt to address air transportation holistically, but often address individual improvements in one arena such as ground or in-flight equipment. In fact, air transportation system designers have had only limited success using traditional Operations Research and parametric modeling approaches in their analyses of innovative operations. They need a systemic methodology for modeling of safety-critical infrastructure that is comprehensive, objective, and sufficiently concrete, yet simple enough to be deployed with reasonable investment. The methodology must also be amenable to quantitative analysis so issues of system safety and stability can be rigorously addressed. The literature suggests that both agent-based models and network analysis techniques may be useful for complex system development and analysis. The purpose of this research is to evaluate these two techniques as applied to analysis of commercial air carrier schedule (route) stability in daily operations, an important component of air transportation. Airline-like routing strategies are used to educe essential elements of applying the method. Two main models are developed, one investigating the network properties of the route structure, the other an Agent-based approach. The two methods are used to predict system properties at a macro-level. These findings are compared to observed route network performance measured by adherence to a schedule to provide validation of the results. Those interested in complex system modeling are provided some indication as to when either or both of the techniques would be applicable. For aviation policy makers, the results point to a toolset capable of providing insight into the system behavior during the formative phases of development and transformation with relatively low investment

  9. Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective

    PubMed Central

    2013-01-01

    Many advances in research regarding immuno-interactions with cancer were developed with the help of ordinary differential equation (ODE) models. These models, however, are not effectively capable of representing problems involving individual localisation, memory and emerging properties, which are common characteristics of cells and molecules of the immune system. Agent-based modelling and simulation is an alternative paradigm to ODE models that overcomes these limitations. In this paper we investigate the potential contribution of agent-based modelling and simulation when compared to ODE modelling and simulation. We seek answers to the following questions: Is it possible to obtain an equivalent agent-based model from the ODE formulation? Do the outcomes differ? Are there any benefits of using one method compared to the other? To answer these questions, we have considered three case studies using established mathematical models of immune interactions with early-stage cancer. These case studies were re-conceptualised under an agent-based perspective and the simulation results were then compared with those from the ODE models. Our results show that it is possible to obtain equivalent agent-based models (i.e. implementing the same mechanisms); the simulation output of both types of models however might differ depending on the attributes of the system to be modelled. In some cases, additional insight from using agent-based modelling was obtained. Overall, we can confirm that agent-based modelling is a useful addition to the tool set of immunologists, as it has extra features that allow for simulations with characteristics that are closer to the biological phenomena. PMID:23734575

  10. Investigating mathematical models of immuno-interactions with early-stage cancer under an agent-based modelling perspective.

    PubMed

    Figueredo, Grazziela P; Siebers, Peer-Olaf; Aickelin, Uwe

    2013-01-01

    Many advances in research regarding immuno-interactions with cancer were developed with the help of ordinary differential equation (ODE) models. These models, however, are not effectively capable of representing problems involving individual localisation, memory and emerging properties, which are common characteristics of cells and molecules of the immune system. Agent-based modelling and simulation is an alternative paradigm to ODE models that overcomes these limitations. In this paper we investigate the potential contribution of agent-based modelling and simulation when compared to ODE modelling and simulation. We seek answers to the following questions: Is it possible to obtain an equivalent agent-based model from the ODE formulation? Do the outcomes differ? Are there any benefits of using one method compared to the other? To answer these questions, we have considered three case studies using established mathematical models of immune interactions with early-stage cancer. These case studies were re-conceptualised under an agent-based perspective and the simulation results were then compared with those from the ODE models. Our results show that it is possible to obtain equivalent agent-based models (i.e. implementing the same mechanisms); the simulation output of both types of models however might differ depending on the attributes of the system to be modelled. In some cases, additional insight from using agent-based modelling was obtained. Overall, we can confirm that agent-based modelling is a useful addition to the tool set of immunologists, as it has extra features that allow for simulations with characteristics that are closer to the biological phenomena.

  11. A three-dimensional multi-agent-based model for the evolution of Chagas' disease.

    PubMed

    Galvão, Viviane; Miranda, José Garcia Vivas

    2010-06-01

    A better understanding of Chagas' disease is important because the knowledge about the progression and the participation of the different types of cells in this disease are still lacking. To clarify this system, the kinetics of inflammatory cells and parasite nests was shown in an experiment. Using this experimental data, we have developed a three-dimensional multi-agent-based computational model for the evolution of Chagas' disease. Our model includes five different types of agents: inflammatory cell, fibrosis, cardiomyocyte, fibroblast, and Trypanosoma cruzi. Fibrosis is fixed and the other types of agents can move through the empty space. They move randomly by using the Moore neighborhood. This model reproduces the acute and chronic phases of Chagas' disease and the volume occupied by all different types of cells in the cardiac tissue.

  12. An adaptive scheduling model for a multi-agent based VEPR data collection actions.

    PubMed

    Vieira-Marques, Pedro; Jácome, Jorge; Hilário-Patriarca, José; Cruz-Correia, Ricardo

    2015-01-01

    With the purpose of improving the access to departmental legacy information systems, a multi agent based Virtual Electronic Patient Record (VEPR) was deployed at a major Portuguese Hospital. The agent module (MAID) is in charge of identifying new data produced (reports), collecting and making it available through an integrated web interface. The deployed MAID system uses a static interval for checking the existence of new data, however from the gathered data regarding each department data production it is observable a variable rate throughout the day. In order to address this variability an adaptive model was developed and tested in a simulated environment with real data. The model takes in consideration the past report production profiles for determining a variable query frequency in order to reduce the average time to make data available minimizing the number of departmental requests.

  13. Changing crops in response to climate: virtual Nang Rong, Thailand in an agent based simulation.

    PubMed

    Malanson, George P; Verdery, Ashton M; Walsh, Stephen J; Sawangdee, Yothin; Heumann, Benjamin W; McDaniel, Philip M; Frizzelle, Brian G; Williams, Nathalie E; Yao, Xiaozheng; Entwisle, Barbara; Rindfuss, Ronald R

    2014-09-01

    The effects of extended climatic variability on agricultural land use were explored for the type of system found in villages of northeastern Thailand. An agent based model developed for the Nang Rong district was used to simulate land allotted to jasmine rice, heavy rice, cassava, and sugar cane. The land use choices in the model depended on likely economic outcomes, but included elements of bounded rationality in dependence on household demography. The socioeconomic dynamics are endogenous in the system, and climate changes were added as exogenous drivers. Villages changed their agricultural effort in many different ways. Most villages reduced the amount of land under cultivation, primarily with reduction in jasmine rice, but others did not. The variation in responses to climate change indicates potential sensitivity to initial conditions and path dependence for this type of system. The differences between our virtual villages and the real villages of the region indicate effects of bounded rationality and limits on model applications.

  14. Determination of the periodicity and synchronization of anticipative agent based supply-demand model

    NASA Astrophysics Data System (ADS)

    Škraba, A.; Bren, M.; Kofjač, D.

    2017-02-01

    The paper presents the transformation of cobweb model by including the anticipation about the supply and demand. Developed transformation leads to oscillatory behaviour. The periodic conditions of the model have been analytically determined by the application of z-transform. Periodic solutions of the system are presented in the form of an inverse Farey tree, where the Golden Ratio path could be observed. The table of periodic conditions is given up to period 8. The agent-based system was developed in order to show the possibility of controlling the system by varying the key parameter, which determines the frequency response of agents and their interaction. A note on application in the stock market has been provided.

  15. An Agent-Based Labor Market Simulation with Endogenous Skill-Demand

    NASA Astrophysics Data System (ADS)

    Gemkow, S.

    This paper considers an agent-based labor market simulation to examine the influence of skills on wages and unemployment rates. Therefore less and highly skilled workers as well as less and highly productive vacancies are implemented. The skill distribution is exogenous whereas the distribution of the less and highly productive vacancies is endogenous. The different opportunities of the skill groups on the labor market are established by skill requirements. This means that a highly productive vacancy can only be filled by a highly skilled unemployed. Different skill distributions, which can also be interpreted as skill-biased technological change, are simulated by incrementing the skill level of highly skilled persons exogenously. This simulation also provides a microeconomic foundation of the matching function often used in theoretical approaches.

  16. Agent-based simulation as a tool for the built environment.

    PubMed

    Gaudiano, Paolo

    2013-08-01

    There is a growing need to increase the performance of the built environment through a combination of improved design, retrofitting of existing structures, and behavioral and policy change. Increased performance includes decreasing construction and operational costs, improving efficiency, reducing energy consumption and overall carbon footprint, and increasing the health, safety, and comfort of building occupants. Data collection and analysis are central to ongoing efforts in performance improvement. The growth of sensor and monitoring technologies, coupled with the proliferation of building automation systems, is quickly leading to an explosion in the amount, quality, and format of building performance data. What is needed are methodologies for extracting viable information from these data and using the results to effect meaningful change. Furthermore, occupant behavior and attitudes must be taken into account. This paper summarizes agent-based simulation and describes its potential as an approach to support analysis, design, and performance improvements in the built environment.

  17. An agent based model for simulating the spread of sexually transmitted infections.

    PubMed

    Rutherford, Grant; Friesen, Marcia R; McLeod, Robert D

    2012-01-01

    This work uses agent-based modelling (ABM) to simulate sexually transmitted infection (STIs) spread within a population of 1000 agents over a 10-year period, as a preliminary investigation of the suitability of ABM methodology to simulate STI spread. The work contrasts compartmentalized mathematical models that fail to account for individual agents, and ABMs commonly applied to simulate the spread of respiratory infections. The model was developed in C++ using the Boost 1.47.0 libraries for the normal distribution and OpenGL for visualization. Sixteen agent parameters interact individually and in combination to govern agent profiles and behaviours relative to infection probabilities. The simulation results provide qualitative comparisons of STI mitigation strategies, including the impact of condom use, promiscuity, the form of the friend network, and mandatory STI testing. Individual and population-wide impacts were explored, with individual risk being impacted much more dramatically by population-level behaviour changes as compared to individual behaviour changes.

  18. Agent-based model for the h-index - exact solution

    NASA Astrophysics Data System (ADS)

    Żogała-Siudem, Barbara; Siudem, Grzegorz; Cena, Anna; Gagolewski, Marek

    2016-01-01

    Hirsch's h-index is perhaps the most popular citation-based measure of scientific excellence. In 2013, Ionescu and Chopard proposed an agent-based model describing a process for generating publications and citations in an abstract scientific community [G. Ionescu, B. Chopard, Eur. Phys. J. B 86, 426 (2013)]. Within such a framework, one may simulate a scientist's activity, and - by extension - investigate the whole community of researchers. Even though the Ionescu and Chopard model predicts the h-index quite well, the authors provided a solution based solely on simulations. In this paper, we complete their results with exact, analytic formulas. What is more, by considering a simplified version of the Ionescu-Chopard model, we obtained a compact, easy to compute formula for the h-index. The derived approximate and exact solutions are investigated on a simulated and real-world data sets.

  19. Changing crops in response to climate: virtual Nang Rong, Thailand in an agent based simulation

    PubMed Central

    Malanson, George P.; Verdery, Ashton M.; Walsh, Stephen J.; Sawangdee, Yothin; Heumann, Benjamin W.; McDaniel, Philip M.; Frizzelle, Brian G.; Williams, Nathalie E.; Yao, Xiaozheng; Entwisle, Barbara; Rindfuss, Ronald R.

    2014-01-01

    The effects of extended climatic variability on agricultural land use were explored for the type of system found in villages of northeastern Thailand. An agent based model developed for the Nang Rong district was used to simulate land allotted to jasmine rice, heavy rice, cassava, and sugar cane. The land use choices in the model depended on likely economic outcomes, but included elements of bounded rationality in dependence on household demography. The socioeconomic dynamics are endogenous in the system, and climate changes were added as exogenous drivers. Villages changed their agricultural effort in many different ways. Most villages reduced the amount of land under cultivation, primarily with reduction in jasmine rice, but others did not. The variation in responses to climate change indicates potential sensitivity to initial conditions and path dependence for this type of system. The differences between our virtual villages and the real villages of the region indicate effects of bounded rationality and limits on model applications. PMID:25061240

  20. GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

    DOE PAGES

    Chassin, David P.; Fuller, Jason C.; Djilali, Ned

    2014-01-01

    Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control systemmore » design, and integration of wind power in a smart grid.« less

  1. Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery

    PubMed Central

    Sakamoto, Takuto

    2016-01-01

    Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level. PMID:26963526

  2. Linking MODFLOW with an agent-based land-use model to support decision making

    USGS Publications Warehouse

    Reeves, H.W.; Zellner, M.L.

    2010-01-01

    The U.S. Geological Survey numerical groundwater flow model, MODFLOW, was integrated with an agent-based land-use model to yield a simulator for environmental planning studies. Ultimately, this integrated simulator will be used as a means to organize information, illustrate potential system responses, and facilitate communication within a participatory modeling framework. Initial results show the potential system response to different zoning policy scenarios in terms of the spatial patterns of development, which is referred to as urban form, and consequent impacts on groundwater levels. These results illustrate how the integrated simulator is capable of representing the complexity of the system. From a groundwater modeling perspective, the most important aspect of the integration is that the simulator generates stresses on the groundwater system within the simulation in contrast to the traditional approach that requires the user to specify the stresses through time. Copyright ?? 2010 The Author(s). Journal compilation ?? 2010 National Ground Water Association.

  3. Re-Examining of Moffitt's Theory of Delinquency through Agent Based Modeling.

    PubMed

    Leaw, Jia Ning; Ang, Rebecca P; Huan, Vivien S; Chan, Wei Teng; Cheong, Siew Ann

    2015-01-01

    Moffitt's theory of delinquency suggests that at-risk youths can be divided into two groups, the adolescence- limited group and the life-course-persistent group, predetermined at a young age, and social interactions between these two groups become important during the adolescent years. We built an agent-based model based on the microscopic interactions Moffitt described: (i) a maturity gap that dictates (ii) the cost and reward of antisocial behavior, and (iii) agents imitating the antisocial behaviors of others more successful than themselves, to find indeed the two groups emerging in our simulations. Moreover, through an intervention simulation where we moved selected agents from one social network to another, we also found that the social network plays an important role in shaping the life course outcome.

  4. GridLAB-D: An Agent-Based Simulation Framework for Smart Grids

    SciTech Connect

    Chassin, David P.; Fuller, Jason C.; Djilali, Ned

    2014-06-23

    Simulation of smart grid technologies requires a fundamentally new approach to integrated modeling of power systems, energy markets, building technologies, and the plethora of other resources and assets that are becoming part of modern electricity production, delivery, and consumption systems. As a result, the US Department of Energy’s Office of Electricity commissioned the development of a new type of power system simulation tool called GridLAB-D that uses an agent-based approach to simulating smart grids. This paper presents the numerical methods and approach to time-series simulation used by GridLAB-D and reviews applications in power system studies, market design, building control system design, and integration of wind power in a smart grid.

  5. Computational Research on Mobile Pastoralism Using Agent-Based Modeling and Satellite Imagery.

    PubMed

    Sakamoto, Takuto

    2016-01-01

    Dryland pastoralism has long attracted considerable attention from researchers in diverse fields. However, rigorous formal study is made difficult by the high level of mobility of pastoralists as well as by the sizable spatio-temporal variability of their environment. This article presents a new computational approach for studying mobile pastoralism that overcomes these issues. Combining multi-temporal satellite images and agent-based modeling allows a comprehensive examination of pastoral resource access over a realistic dryland landscape with unpredictable ecological dynamics. The article demonstrates the analytical potential of this approach through its application to mobile pastoralism in northeast Nigeria. Employing more than 100 satellite images of the area, extensive simulations are conducted under a wide array of circumstances, including different land-use constraints. The simulation results reveal complex dependencies of pastoral resource access on these circumstances along with persistent patterns of seasonal land use observed at the macro level.

  6. AN AGENT-BASED SIMULATION STUDY OF A COMPLEX ADAPTIVE COLLABORATION NETWORK

    SciTech Connect

    Ozmen, Ozgur; Smith, Jeffrey; Yilmaz, Levent

    2013-01-01

    One of the most significant problems in organizational scholarship is to discern how social collectives govern, organize, and coordinate the actions of individuals to achieve collective outcomes. The collectives are usually interpreted as complex adaptive systems (CAS). The understanding of CAS is more likely to arise with the help of computer-based simulations. In this tutorial, using agent-based modeling approach, a complex adaptive social communication network model is introduced. The objective is to present the underlying dynamics of the system in a form of computer simulation that enables analyzing the impacts of various mechanisms on network topologies and emergent behaviors. The ultimate goal is to further our understanding of the dynamics in the system and facilitate developing informed policies for decision-makers.

  7. Integrated PK-PD and agent-based modeling in oncology.

    PubMed

    Wang, Zhihui; Butner, Joseph D; Cristini, Vittorio; Deisboeck, Thomas S

    2015-04-01

    Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.

  8. Linking MODFLOW with an agent-based land-use model to support decision making.

    PubMed

    Reeves, Howard W; Zellner, Moira L

    2010-01-01

    The U.S. Geological Survey numerical groundwater flow model, MODFLOW, was integrated with an agent-based land-use model to yield a simulator for environmental planning studies. Ultimately, this integrated simulator will be used as a means to organize information, illustrate potential system responses, and facilitate communication within a participatory modeling framework. Initial results show the potential system response to different zoning policy scenarios in terms of the spatial patterns of development, which is referred to as urban form, and consequent impacts on groundwater levels. These results illustrate how the integrated simulator is capable of representing the complexity of the system. From a groundwater modeling perspective, the most important aspect of the integration is that the simulator generates stresses on the groundwater system within the simulation in contrast to the traditional approach that requires the user to specify the stresses through time.

  9. Agent based model of effects of task allocation strategies in flat organizations

    NASA Astrophysics Data System (ADS)

    Sobkowicz, Pawel

    2016-09-01

    A common practice in many organizations is to pile the work on the best performers. It is easy to implement by the management and, despite the apparent injustice, appears to be working in many situations. In our work we present a simple agent based model, constructed to simulate this practice and to analyze conditions under which the overall efficiency of the organization (for example measured by the backlog of unresolved issues) breaks down, due to the cumulative effect of the individual overloads. The model confirms that the strategy mentioned above is, indeed, rational: it leads to better global results than an alternative one, using equal workload distribution among all workers. The presented analyses focus on the behavior of the organizations close to the limit of the maximum total throughput and provide results for the growth of the unprocessed backlog in several situations, as well as suggestions related to avoiding such buildup.

  10. Projecting Sexual and Injecting HIV Risks into Future Outcomes with Agent-Based Modeling

    NASA Astrophysics Data System (ADS)

    Bobashev, Georgiy V.; Morris, Robert J.; Zule, William A.

    Longitudinal studies of health outcomes for HIV could be very costly cumbersome and not representative of the risk population. Conversely, cross-sectional approaches could be representative but rely on the retrospective information to estimate prevalence and incidence. We present an Agent-based Modeling (ABM) approach where we use behavioral data from a cross-sectional representative study and project the behavior into the future so that the risks of acquiring HIV could be studied in a dynamical/temporal sense. We show how the blend of behavior and contact network factors (sexual, injecting) play the role in the risk of future HIV acquisition and time till obtaining HIV. We show which subjects are the most likely persons to get HIV in the next year, and whom they are likely to infect. We examine how different behaviors are related to the increase or decrease of HIV risks and how to estimate the quantifiable risk measures such as survival HIV free.

  11. Understanding the Dynamics of Violent Political Revolutions in an Agent-Based Framework

    PubMed Central

    Moro, Alessandro

    2016-01-01

    This paper develops an agent-based computational model of violent political revolutions in which a subjugated population of citizens and an armed revolutionary organisation attempt to overthrow a central authority and its loyal forces. The model replicates several patterns of rebellion consistent with major historical revolutions, and provides an explanation for the multiplicity of outcomes that can arise from an uprising. The relevance of the heterogeneity of scenarios predicted by the model can be understood by considering the recent experience of the Arab Spring involving several rebellions that arose in an apparently similar way, but resulted in completely different political outcomes: the successful revolution in Tunisia, the failed protests in Saudi Arabia and Bahrain, and civil war in Syria and Libya. PMID:27104855

  12. 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.

  13. Bankruptcy Problem Approach to Load-Shedding in Agent-Based Microgrid Operation

    NASA Astrophysics Data System (ADS)

    Kim, Hak-Man; Kinoshita, Tetsuo; Lim, Yujin; Kim, Tai-Hoon

    Research, development, and demonstration projects on microgrids have been progressed in many countries. Furthermore, microgrids are expected to introduce into power grids as eco-friendly small-scale power grids in the near future. Load-shedding is a problem not avoided to meet power balance between power supply and power demand to maintain specific frequency such as 50 Hz or 60 Hz. Load-shedding causes consumers inconvenience and therefore should be performed minimally. Recently, agent-based microgrid operation has been studied and new algorithms for their autonomous operation including load-shedding has been required. The bankruptcy problem deals with distribution insufficient sources to claimants. In this paper, we approach the load-shedding problem as a bankruptcy problem and adopt the Talmud rule as an algorithm. Load-shedding using the Talmud rule is tested in islanded microgrid operation based on a multiagent system.

  14. Method for distributed agent-based non-expert simulation of manufacturing process behavior

    DOEpatents

    Ivezic, Nenad; Potok, Thomas E.

    2004-11-30

    A method for distributed agent based non-expert simulation of manufacturing process behavior on a single-processor computer comprises the steps of: object modeling a manufacturing technique having a plurality of processes; associating a distributed agent with each the process; and, programming each the agent to respond to discrete events corresponding to the manufacturing technique, wherein each discrete event triggers a programmed response. The method can further comprise the step of transmitting the discrete events to each agent in a message loop. In addition, the programming step comprises the step of conditioning each agent to respond to a discrete event selected from the group consisting of a clock tick message, a resources received message, and a request for output production message.

  15. Improving an Agent-Based Model by Using Interdisciplinary Approaches for Analyzing Structural Change in Agriculture

    NASA Astrophysics Data System (ADS)

    Appel, Franziska; Ostermeyer, Arlette; Balmann, Alfons; Larsen, Karin

    Structural change in the German dairy sector seems to be lagged behind. Heterogeneous farm structures, a low efficiency and profitability are persistent although farms operate under similar market and policy conditions. This raises the questions whether these structures are path dependent and how they can eventually be overcome. To answer these questions we use the agent-based model AgriPoliS. The aim of our project is to improve assumptions in AgriPoliS by using it as an experimental laboratory. In a second part AgriPoliS will be used in stakeholder workshops to define scenarios for the dairy sector and communicate and discuss results to practitioners and decision makers.

  16. Reducing the complexity of an agent-based local heroin market model.

    PubMed

    Heard, Daniel; Bobashev, Georgiy V; Morris, Robert J

    2014-01-01

    This project explores techniques for reducing the complexity of an agent-based model (ABM). The analysis involved a model developed from the ethnographic research of Dr. Lee Hoffer in the Larimer area heroin market, which involved drug users, drug sellers, homeless individuals and police. The authors used statistical techniques to create a reduced version of the original model which maintained simulation fidelity while reducing computational complexity. This involved identifying key summary quantities of individual customer behavior as well as overall market activity and replacing some agents with probability distributions and regressions. The model was then extended to allow external market interventions in the form of police busts. Extensions of this research perspective, as well as its strengths and limitations, are discussed.

  17. Promoting Conceptual Change for Complex Systems Understanding: Outcomes of an Agent-Based Participatory Simulation

    NASA Astrophysics Data System (ADS)

    Rates, Christopher A.; Mulvey, Bridget K.; Feldon, David F.

    2016-08-01

    Components of complex systems apply across multiple subject areas, and teaching these components may help students build unifying conceptual links. Students, however, often have difficulty learning these components, and limited research exists to understand what types of interventions may best help improve understanding. We investigated 32 high school students' understandings of complex systems components and whether an agent-based simulation could improve their understandings. Pretest and posttest essays were coded for changes in six components to determine whether students showed more expert thinking about the complex system of the Chesapeake Bay watershed. Results showed significant improvement for the components Emergence ( r = .26, p = .03), Order ( r = .37, p = .002), and Tradeoffs ( r = .44, p = .001). Implications include that the experiential nature of the simulation has the potential to support conceptual change for some complex systems components, presenting a promising option for complex systems instruction.

  18. Microscopic understanding of heavy-tailed return distributions in an agent-based model

    NASA Astrophysics Data System (ADS)

    Schmitt, Thilo A.; Schäfer, Rudi; Münnix, Michael C.; Guhr, Thomas

    2012-11-01

    The distribution of returns in financial time series exhibits heavy tails. It has been found that gaps between the orders in the order book lead to large price shifts and thereby to these heavy tails. We set up an agent-based model to study this issue and, in particular, how the gaps in the order book emerge. The trading mechanism in our model is based on a double-auction order book. In situations where the order book is densely occupied with limit orders we do not observe fat-tailed distributions. As soon as less liquidity is available, a gap structure forms which leads to return distributions with heavy tails. We show that return distributions with heavy tails are an order-book effect if the available liquidity is constrained. This is largely independent of specific trading strategies.

  19. Multi-Agent-Based Simulation of a Complex Ecosystem of Mental Health Care.

    PubMed

    Kalton, Alan; Falconer, Erin; Docherty, John; Alevras, Dimitris; Brann, David; Johnson, Kyle

    2016-02-01

    This paper discusses the creation of an Agent-Based Simulation that modeled the introduction of care coordination capabilities into a complex system of care for patients with Serious and Persistent Mental Illness. The model describes the engagement between patients and the medical, social and criminal justice services they interact with in a complex ecosystem of care. We outline the challenges involved in developing the model, including process mapping and the collection and synthesis of data to support parametric estimates, and describe the controls built into the model to support analysis of potential changes to the system. We also describe the approach taken to calibrate the model to an observable level of system performance. Preliminary results from application of the simulation are provided to demonstrate how it can provide insights into potential improvements deriving from introduction of care coordination technology.

  20. Security Analysis of Selected AMI Failure Scenarios Using Agent Based Game Theoretic Simulation

    SciTech Connect

    Abercrombie, Robert K; Schlicher, Bob G; Sheldon, Frederick T

    2014-01-01

    Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. We concentrated our analysis on the Advanced Metering Infrastructure (AMI) functional domain which the National Electric Sector Cyber security Organization Resource (NESCOR) working group has currently documented 29 failure scenarios. The strategy for the game was developed by analyzing five electric sector representative failure scenarios contained in the AMI functional domain. From these five selected scenarios, we characterize them into three specific threat categories affecting confidentiality, integrity and availability (CIA). The analysis using our ABGT simulation demonstrates how to model the AMI functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the AMI network with respect to CIA.

  1. Minority persistence in agent based model using information and emotional arousal as control variables

    NASA Astrophysics Data System (ADS)

    Sobkowicz, Pawel

    2013-07-01

    We present detailed analysis of the behavior of an agent based model of opinion formation, using a discrete variant of cusp catastrophe behavior of single agents. The agent opinion about a particular issue is determined by its information about the issue and its emotional arousal. It is possible that for agitated agents the same information would lead to different opinions. This results in a nontrivial individual opinion dynamics. The agents communicate via messages, which allows direct application of the model to ICT based communities. We study the dependence of the composition of an agent society on the range of interactions and the rate of emotional arousal. Despite the minimal number of adjustable parameters, the model reproduces several phenomena observed in real societies, for example nearly perfectly balanced results of some highly contested elections or the fact that minorities seldom perceive themselves to be a minority.

  2. Agent-based models for the emergence and evolution of grammar.

    PubMed

    Steels, Luc

    2016-08-19

    Human languages are extraordinarily complex adaptive systems. They feature intricate hierarchical sound structures, are able to express elaborate meanings and use sophisticated syntactic and semantic structures to relate sound to meaning. What are the cognitive mechanisms that speakers and listeners need to create and sustain such a remarkable system? What is the collective evolutionary dynamics that allows a language to self-organize, become more complex and adapt to changing challenges in expressive power? This paper focuses on grammar. It presents a basic cycle observed in the historical language record, whereby meanings move from lexical to syntactic and then to a morphological mode of expression before returning to a lexical mode, and discusses how we can discover and validate mechanisms that can cause these shifts using agent-based models.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

  3. Preliminary analysis of an agent-based model for a tick-borne disease.

    PubMed

    Gaff, Holly

    2011-04-01

    Ticks have a unique life history including a distinct set of life stages and a single blood meal per life stage. This makes tick-host interactions more complex from a mathematical perspective. In addition, any model of these interactions must involve a significant degree of stochasticity on the individual tick level. In an attempt to quantify these relationships, I have developed an individual-based model of the interactions between ticks and their hosts as well as the transmission of tick-borne disease between the two populations. The results from this model are compared with those from previously published differential equation based population models. The findings show that the agent-based model produces significantly lower prevalence of disease in both the ticks and their hosts than what is predicted by a similar differential equation model.

  4. Price Response Can Make the Grid Robust: An Agent-based Discussion

    SciTech Connect

    Roop, Joseph M.; Fathelrahman, Eihab M.; Widergren, Steven E.

    2005-11-07

    There is considerable agreement that a more price responsive system would make for a more robust grid. This raises the issue of how the end-user can be induced to accept a system that relies more heavily on price signals than the current system. From a modeling perspective, how should the software ‘agent’ representing the consumer of electricity be modeled so that this agent exhibits some price responsiveness in a realistic manner? To address these issues, we construct an agent-based approach that is realistic in the sense that it can transition from the current system behavior to one that is more price responsive. Evidence from programs around the country suggests that there are ways to implement such a program that could add robustness to the grid.

  5. The Evolution of ICT Markets: An Agent-Based Model on Complex Networks

    NASA Astrophysics Data System (ADS)

    Zhao, Liangjie; Wu, Bangtao; Chen, Zhong; Li, Li

    Information and communication technology (ICT) products exhibit positive network effects.The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others’ purchasing decision; (2) customers are intelligent agents with bounded rationality.Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network.We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market.We also find that the intensity of customers’ communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.

  6. Re-Examining of Moffitt’s Theory of Delinquency through Agent Based Modeling

    PubMed Central

    Leaw, Jia Ning; Ang, Rebecca P.; Huan, Vivien S.; Chan, Wei Teng; Cheong, Siew Ann

    2015-01-01

    Moffitt’s theory of delinquency suggests that at-risk youths can be divided into two groups, the adolescence- limited group and the life-course-persistent group, predetermined at a young age, and social interactions between these two groups become important during the adolescent years. We built an agent-based model based on the microscopic interactions Moffitt described: (i) a maturity gap that dictates (ii) the cost and reward of antisocial behavior, and (iii) agents imitating the antisocial behaviors of others more successful than themselves, to find indeed the two groups emerging in our simulations. Moreover, through an intervention simulation where we moved selected agents from one social network to another, we also found that the social network plays an important role in shaping the life course outcome. PMID:26062022

  7. Estimating impacts of climate change policy on land use: an agent-based modelling approach.

    PubMed

    Morgan, Fraser J; Daigneault, Adam J

    2015-01-01

    Agriculture is important to New Zealand's economy. Like other primary producers, New Zealand strives to increase agricultural output while maintaining environmental integrity. Utilising modelling to explore the economic, environmental and land use impacts of policy is critical to understand the likely effects on the sector. Key deficiencies within existing land use and land cover change models are the lack of heterogeneity in farmers and their behaviour, the role that social networks play in information transfer, and the abstraction of the global and regional economic aspects within local-scale approaches. To resolve these issues we developed the Agent-based Rural Land Use New Zealand model. The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer's decisions affect farm conversion and the resulting land use at a catchment scale. The model is intended to assist in the development of policy to shape agricultural land use intensification in New Zealand. We illustrate the model, by modelling the impact of a greenhouse gas price on farm-level land use, net revenue, and environmental indicators such as nutrient losses and soil erosion for key enterprises in the Hurunui and Waiau catchments of North Canterbury in New Zealand. Key results from the model show that farm net revenue is estimated to increase over time regardless of the greenhouse gas price. Net greenhouse gas emissions are estimated to decline over time, even under a no GHG price baseline, due to an expansion of forestry on low productivity land. Higher GHG prices provide a greater net reduction of emissions. While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises.

  8. Evolving Nutritional Strategies in the Presence of Competition: A Geometric Agent-Based Model

    PubMed Central

    Senior, Alistair M.; Charleston, Michael A.; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J.

    2015-01-01

    Access to nutrients is a key factor governing development, reproduction and ultimately fitness. Within social groups, contest-competition can fundamentally affect nutrient access, potentially leading to reproductive asymmetry among individuals. Previously, agent-based models have been combined with the Geometric Framework of nutrition to provide insight into how nutrition and social interactions affect one another. Here, we expand this modelling approach by incorporating evolutionary algorithms to explore how contest-competition over nutrient acquisition might affect the evolution of animal nutritional strategies. Specifically, we model tolerance of nutrient excesses and deficits when ingesting nutritionally imbalanced foods, which we term ‘nutritional latitude’; a higher degree of nutritional latitude constitutes a higher tolerance of nutritional excess and deficit. Our results indicate that a transition between two alternative strategies occurs at moderate to high levels of competition. When competition is low, individuals display a low level of nutritional latitude and regularly switch foods in search of an optimum. When food is scarce and contest-competition is intense, high nutritional latitude appears optimal, and individuals continue to consume an imbalanced food for longer periods before attempting to switch to an alternative. However, the relative balance of nutrients within available foods also strongly influences at what levels of competition, if any, transitions between these two strategies occur. Our models imply that competition combined with reproductive skew in social groups can play a role in the evolution of diet breadth. We discuss how the integration of agent-based, nutritional and evolutionary modelling may be applied in future studies to further understand the evolution of nutritional strategies across social and ecological contexts. PMID:25815976

  9. Investigating the role of water in the Diffusion of Cholera using Agent-Based simulation

    NASA Astrophysics Data System (ADS)

    Augustijn, Ellen-Wien; Doldersum, Tom; Augustijn, Denie

    2014-05-01

    Traditionally, cholera was considered to be a waterborne disease. Currently we know that many other factors can contribute to the spread of this disease including human mobility and human behavior. However, the hydrological component in cholera diffusion is significant. The interplay between cholera and water includes bacteria (V. cholera) that survive in the aquatic environment, the possibility that run-off water from dumpsites carries the bacteria to surface water (rivers and lakes), and when the bacteria reach streams they can be carried downstream to infect new locations. Modelling is a very important tool to build theory on the interplay between different types of transmission mechanisms that together are responsible for the spread of Cholera. Agent-based simulation models are very suitable to incorporate behavior at individual level and to reproduce emergence. However, it is more difficult to incorporate the hydrological components in this type of model. In this research we present the hydrological component of an Agent-Based Cholera model developed to study a Cholera epidemic in Kumasi (Ghana) in 2005. The model was calibrated on the relative contribution of each community to the distributed pattern of cholera rather than the absolute number of incidences. Analysis of the results shows that water plays an important role in the diffusion of cholera: 75% of the cholera cases were infected via river water that was contaminated by runoff from the dumpsites. To initiate infections upstream, the probability of environment-to-human transmission seemed to be overestimated compared to what may be expected from literature. Scenario analyses show that there is a strong relation between the epidemic curve and the rainfall. Removing dumpsites that are situated close to the river resulted in a strong decrease in the number of cholera cases. Results are sensitive to the scheduling of the daily activities and the survival time of the cholera bacteria.

  10. Impact of urban planning on household's residential decisions: An agent-based simulation model for Vienna☆

    PubMed Central

    Gaube, Veronika; Remesch, Alexander

    2013-01-01

    Interest in assessing the sustainability of socio-ecological systems of urban areas has increased notably, with additional attention generated due to the fact that half the world's population now lives in cities. Urban areas face both a changing urban population size and increasing sustainability issues in terms of providing good socioeconomic and environmental living conditions. Urban planning has to deal with both challenges. Households play a major role by being affected by urban planning decisions on the one hand and by being responsible – among many other factors – for the environmental performance of a city (e.g. energy use). We here present an agent-based decision model referring to the city of Vienna, the capital of Austria, with a population of about 1.7 million (2.3 million within the metropolitan area, the latter being more than 25% of Austria's total population). Since the early 1990s, after decades of negative population growth, Vienna has been experiencing a steady increase in population, mainly driven by immigration. The aim of the agent-based decision model is to simulate new residential patterns of different household types based on demographic development and migration scenarios. Model results were used to assess spatial patterns of energy use caused by different household types in the four scenarios (1) conventional urban planning, (2) sustainable urban planning, (3) expensive centre and (4) no green area preference. Outcomes show that changes in preferences of households relating to the presence of nearby green areas have the most important impact on the distribution of households across the small-scaled city area. Additionally, the results demonstrate the importance of the distribution of different household types regarding spatial patterns of energy use. PMID:27667962

  11. An agent-based simulation model to study accountable care organizations.

    PubMed

    Liu, Pai; Wu, Shinyi

    2016-03-01

    Creating accountable care organizations (ACOs) has been widely discussed as a strategy to control rapidly rising healthcare costs and improve quality of care; however, building an effective ACO is a complex process involving multiple stakeholders (payers, providers, patients) with their own interests. Also, implementation of an ACO is costly in terms of time and money. Immature design could cause safety hazards. Therefore, there is a need for analytical model-based decision-support tools that can predict the outcomes of different strategies to facilitate ACO design and implementation. In this study, an agent-based simulation model was developed to study ACOs that considers payers, healthcare providers, and patients as agents under the shared saving payment model of care for congestive heart failure (CHF), one of the most expensive causes of sometimes preventable hospitalizations. The agent-based simulation model has identified the critical determinants for the payment model design that can motivate provider behavior changes to achieve maximum financial and quality outcomes of an ACO. The results show nonlinear provider behavior change patterns corresponding to changes in payment model designs. The outcomes vary by providers with different quality or financial priorities, and are most sensitive to the cost-effectiveness of CHF interventions that an ACO implements. This study demonstrates an increasingly important method to construct a healthcare system analytics model that can help inform health policy and healthcare management decisions. The study also points out that the likely success of an ACO is interdependent with payment model design, provider characteristics, and cost and effectiveness of healthcare interventions.

  12. Combination HIV prevention among MSM in South Africa: results from agent-based modeling.

    PubMed

    Brookmeyer, Ron; Boren, David; Baral, Stefan D; Bekker, Linda-Gail; Phaswana-Mafuya, Nancy; Beyrer, Chris; Sullivan, Patrick S

    2014-01-01

    HIV prevention trials have demonstrated the effectiveness of a number of behavioral and biomedical interventions. HIV prevention packages are combinations of interventions and offer potential to significantly increase the effectiveness of any single intervention. Estimates of the effectiveness of prevention packages are important for guiding the development of prevention strategies and for characterizing effect sizes before embarking on large scale trials. Unfortunately, most research to date has focused on testing single interventions rather than HIV prevention packages. Here we report the results from agent-based modeling of the effectiveness of HIV prevention packages for men who have sex with men (MSM) in South Africa. We consider packages consisting of four components: antiretroviral therapy for HIV infected persons with CD4 count <350; PrEP for high risk uninfected persons; behavioral interventions to reduce rates of unprotected anal intercourse (UAI); and campaigns to increase HIV testing. We considered 163 HIV prevention packages corresponding to different intensity levels of the four components. We performed 2252 simulation runs of our agent-based model to evaluate those packages. We found that a four component package consisting of a 15% reduction in the rate of UAI, 50% PrEP coverage of high risk uninfected persons, 50% reduction in persons who never test for HIV, and 50% ART coverage over and above persons already receiving ART at baseline, could prevent 33.9% of infections over 5 years (95% confidence interval, 31.5, 36.3). The package components with the largest incremental prevention effects were UAI reduction and PrEP coverage. The impact of increased HIV testing was magnified in the presence of PrEP. We find that HIV prevention packages that include both behavioral and biomedical components can in combination prevent significant numbers of infections with levels of coverage, acceptance and adherence that are potentially achievable among MSM in

  13. Agent-based computational model investigates muscle-specific responses to disuse-induced atrophy

    PubMed Central

    Martin, Kyle S.; Peirce, Shayn M.

    2015-01-01

    Skeletal muscle is highly responsive to use. In particular, muscle atrophy attributable to decreased activity is a common problem among the elderly and injured/immobile. However, each muscle does not respond the same way. We developed an agent-based model that generates a tissue-level skeletal muscle response to disuse/immobilization. The model incorporates tissue-specific muscle fiber architecture parameters and simulates changes in muscle fiber size as a result of disuse-induced atrophy that are consistent with published experiments. We created simulations of 49 forelimb and hindlimb muscles of the rat by incorporating eight fiber-type and size parameters to explore how these parameters, which vary widely across muscles, influence sensitivity to disuse-induced atrophy. Of the 49 muscles modeled, the soleus exhibited the greatest atrophy after 14 days of simulated immobilization (51% decrease in fiber size), whereas the extensor digitorum communis atrophied the least (32%). Analysis of these simulations revealed that both fiber-type distribution and fiber-size distribution influence the sensitivity to disuse atrophy even though no single tissue architecture parameter correlated with atrophy rate. Additionally, software agents representing fibroblasts were incorporated into the model to investigate cellular interactions during atrophy. Sensitivity analyses revealed that fibroblast agents have the potential to affect disuse-induced atrophy, albeit with a lesser effect than fiber type and size. In particular, muscle atrophy elevated slightly with increased initial fibroblast population and increased production of TNF-α. Overall, the agent-based model provides a novel framework for investigating both tissue adaptations and cellular interactions in skeletal muscle during atrophy. PMID:25722379

  14. Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

    NASA Astrophysics Data System (ADS)

    Dickes, Amanda Catherine; Sengupta, Pratim

    2013-06-01

    In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these agents obey simple rules assigned or manipulated by the user (e.g., speeding up, slowing down, etc.). It is the interactions between these agents, based on the rules assigned by the user, that give rise to emergent, aggregate-level behavior (e.g., formation and movement of the traffic jam). Natural selection is such an emergent phenomenon, which has been shown to be challenging for novices (K16 students) to understand. Whereas prior research on learning evolutionary phenomena with MABMs has typically focused on high school students and beyond, we investigate how elementary students (4th graders) develop multi-level explanations of some introductory aspects of natural selection—species differentiation and population change—through scaffolded interactions with an MABM that simulates predator-prey dynamics in a simple birds-butterflies ecosystem. We conducted a semi-clinical interview based study with ten participants, in which we focused on the following: a) identifying the nature of learners' initial interpretations of salient events or elements of the represented phenomena, b) identifying the roles these interpretations play in the development of their multi-level explanations, and c) how attending to different levels of the relevant phenomena can make explicit different mechanisms to the learners. In addition, our analysis also shows that although there were differences between high- and low-performing students (in terms of being able to explain population-level behaviors) in the pre-test, these differences disappeared in the post-test.

  15. Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

    NASA Astrophysics Data System (ADS)

    Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

    2014-09-01

    Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

  16. Holistic flood risk assessment using agent-based modelling: the case of Sint Maarten Island

    NASA Astrophysics Data System (ADS)

    Abayneh Abebe, Yared; Vojinovic, Zoran; Nikolic, Igor; Hammond, Michael; Sanchez, Arlex; Pelling, Mark

    2015-04-01

    Floods in coastal regions are regarded as one of the most dangerous and harmful disasters. Though commonly referred to as natural disasters, coastal floods are also attributable to various social, economic, historical and political issues. Rapid urbanisation in coastal areas combined with climate change and poor governance can lead to a significant increase in the risk of pluvial flooding coinciding with fluvial and coastal flooding posing a greater risk of devastation in coastal communities. Disasters that can be triggered by hydro-meteorological events are interconnected and interrelated with both human activities and natural processes. They, therefore, require holistic approaches to help understand their complexity in order to design and develop adaptive risk management approaches that minimise social and economic losses and environmental impacts, and increase resilience to such events. Being located in the North Atlantic Ocean, Sint Maarten is frequently subjected to hurricanes. In addition, the stormwater catchments and streams on Sint Maarten have several unique characteristics that contribute to the severity of flood-related impacts. Urban environments are usually situated in low-lying areas, with little consideration for stormwater drainage, and as such are subject to flash flooding. Hence, Sint Maarten authorities drafted policies to minimise the risk of flood-related disasters on the island. In this study, an agent-based model is designed and applied to understand the implications of introduced policies and regulations, and to understand how different actors' behaviours influence the formation, propagation and accumulation of flood risk. The agent-based model built for this study is based on the MAIA meta-model, which helps to decompose, structure and conceptualize socio-technical systems with an agent-oriented perspective, and is developed using the NetLogo simulation environment. The agents described in this model are households and businesses, and

  17. CystiSim - An Agent-Based Model for Taenia solium Transmission and Control.

    PubMed

    Braae, Uffe Christian; Devleesschauwer, Brecht; Gabriël, Sarah; Dorny, Pierre; Speybroeck, Niko; Magnussen, Pascal; Torgerson, Paul; Johansen, Maria Vang

    2016-12-01

    Taenia solium taeniosis/cysticercosis was declared eradicable by the International Task Force for Disease Eradication in 1993, but remains a neglected zoonosis. To assist in the attempt to regionally eliminate this parasite, we developed cystiSim, an agent-based model for T. solium transmission and control. The model was developed in R and available as an R package (http://cran.r-project.org/package=cystiSim). cystiSim was adapted to an observed setting using field data from Tanzania, but adaptable to other settings if necessary. The model description adheres to the Overview, Design concepts, and Details (ODD) protocol and consists of two entities-pigs and humans. Pigs acquire cysticercosis through the environment or by direct contact with a tapeworm carrier's faeces. Humans acquire taeniosis from slaughtered pigs proportional to their infection intensity. The model allows for evaluation of three interventions measures or combinations hereof: treatment of humans, treatment of pigs, and pig vaccination, and allows for customary coverage and efficacy settings. cystiSim is the first agent-based transmission model for T. solium and suggests that control using a strategy consisting of an intervention only targeting the porcine host is possible, but that coverage and efficacy must be high if elimination is the ultimate goal. Good coverage of the intervention is important, but can be compensated for by including an additional intervention targeting the human host. cystiSim shows that the scenarios combining interventions in both hosts, mass drug administration to humans, and vaccination and treatment of pigs, have a high probability of success if coverage of 75% can be maintained over at least a four year period. In comparison with an existing mathematical model for T. solium transmission, cystiSim also includes parasite maturation, host immunity, and environmental contamination. Adding these biological parameters to the model resulted in new insights in the potential

  18. Prediction Markets and Beliefs about Climate: Results from Agent-Based Simulations

    NASA Astrophysics Data System (ADS)

    Gilligan, J. M.; John, N. J.; van der Linden, M.

    2015-12-01

    Climate scientists have long been frustrated by persistent doubts a large portion of the public expresses toward the scientific consensus about anthropogenic global warming. The political and ideological polarization of this doubt led Vandenbergh, Raimi, and Gilligan [1] to propose that prediction markets for climate change might influence the opinions of those who mistrust the scientific community but do trust the power of markets.We have developed an agent-based simulation of a climate prediction market in which traders buy and sell future contracts that will pay off at some future year with a value that depends on the global average temperature at that time. The traders form a heterogeneous population with different ideological positions, different beliefs about anthropogenic global warming, and different degrees of risk aversion. We also vary characteristics of the market, including the topology of social networks among the traders, the number of traders, and the completeness of the market. Traders adjust their beliefs about climate according to the gains and losses they and other traders in their social network experience. This model predicts that if global temperature is predominantly driven by greenhouse gas concentrations, prediction markets will cause traders' beliefs to converge toward correctly accepting anthropogenic warming as real. This convergence is largely independent of the structure of the market and the characteristics of the population of traders. However, it may take considerable time for beliefs to converge. Conversely, if temperature does not depend on greenhouse gases, the model predicts that traders' beliefs will not converge. We will discuss the policy-relevance of these results and more generally, the use of agent-based market simulations for policy analysis regarding climate change, seasonal agricultural weather forecasts, and other applications.[1] MP Vandenbergh, KT Raimi, & JM Gilligan. UCLA Law Rev. 61, 1962 (2014).

  19. Impact of urban planning on household's residential decisions: An agent-based simulation model for Vienna.

    PubMed

    Gaube, Veronika; Remesch, Alexander

    2013-07-01

    Interest in assessing the sustainability of socio-ecological systems of urban areas has increased notably, with additional attention generated due to the fact that half the world's population now lives in cities. Urban areas face both a changing urban population size and increasing sustainability issues in terms of providing good socioeconomic and environmental living conditions. Urban planning has to deal with both challenges. Households play a major role by being affected by urban planning decisions on the one hand and by being responsible - among many other factors - for the environmental performance of a city (e.g. energy use). We here present an agent-based decision model referring to the city of Vienna, the capital of Austria, with a population of about 1.7 million (2.3 million within the metropolitan area, the latter being more than 25% of Austria's total population). Since the early 1990s, after decades of negative population growth, Vienna has been experiencing a steady increase in population, mainly driven by immigration. The aim of the agent-based decision model is to simulate new residential patterns of different household types based on demographic development and migration scenarios. Model results were used to assess spatial patterns of energy use caused by different household types in the four scenarios (1) conventional urban planning, (2) sustainable urban planning, (3) expensive centre and (4) no green area preference. Outcomes show that changes in preferences of households relating to the presence of nearby green areas have the most important impact on the distribution of households across the small-scaled city area. Additionally, the results demonstrate the importance of the distribution of different household types regarding spatial patterns of energy use.

  20. CystiSim – An Agent-Based Model for Taenia solium Transmission and Control

    PubMed Central

    Gabriël, Sarah; Dorny, Pierre; Speybroeck, Niko; Magnussen, Pascal; Torgerson, Paul; Johansen, Maria Vang

    2016-01-01

    Taenia solium taeniosis/cysticercosis was declared eradicable by the International Task Force for Disease Eradication in 1993, but remains a neglected zoonosis. To assist in the attempt to regionally eliminate this parasite, we developed cystiSim, an agent-based model for T. solium transmission and control. The model was developed in R and available as an R package (http://cran.r-project.org/package=cystiSim). cystiSim was adapted to an observed setting using field data from Tanzania, but adaptable to other settings if necessary. The model description adheres to the Overview, Design concepts, and Details (ODD) protocol and consists of two entities—pigs and humans. Pigs acquire cysticercosis through the environment or by direct contact with a tapeworm carrier's faeces. Humans acquire taeniosis from slaughtered pigs proportional to their infection intensity. The model allows for evaluation of three interventions measures or combinations hereof: treatment of humans, treatment of pigs, and pig vaccination, and allows for customary coverage and efficacy settings. cystiSim is the first agent-based transmission model for T. solium and suggests that control using a strategy consisting of an intervention only targeting the porcine host is possible, but that coverage and efficacy must be high if elimination is the ultimate goal. Good coverage of the intervention is important, but can be compensated for by including an additional intervention targeting the human host. cystiSim shows that the scenarios combining interventions in both hosts, mass drug administration to humans, and vaccination and treatment of pigs, have a high probability of success if coverage of 75% can be maintained over at least a four year period. In comparison with an existing mathematical model for T. solium transmission, cystiSim also includes parasite maturation, host immunity, and environmental contamination. Adding these biological parameters to the model resulted in new insights in the potential