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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. Intelligent agent-based intrusion detection system using enhanced multiclass SVM.

    PubMed

    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.

  3. 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.

  4. Bro Intrusion Detection System

    SciTech Connect

    Paxson, Vern; Campbell, Scott; leres, Craig; Lee, Jason

    2006-01-25

    Bro is a Unix-based Network Intrusion Detection System (IDS). Bro monitors network traffic and detects intrusion attempts based on the traffic characteristics and content. Bro detects intrusions by comparing network traffic against rules describing events that are deemed troublesome. These rules might describe activities (e.g., certain hosts connecting to certain services), what activities are worth alerting (e.g., attempts to a given number of different hosts constitutes a "scan"), or signatures describing known attacks or access to known vulnerabilities. If Bro detects something of interest, it can be instructed to either issue a log entry or initiate the execution of an operating system command. Bro targets high-speed (Gbps), high-volume intrusion detection. By judiciously leveraging packet filtering techniques, Bro is able to achieve the performance necessary to do so while running on commercially available PC hardware, and thus can serve as a cost effective means of monitoring a site’s Internet connection.

  5. Bro Intrusion Detection System

    2006-01-25

    Bro is a Unix-based Network Intrusion Detection System (IDS). Bro monitors network traffic and detects intrusion attempts based on the traffic characteristics and content. Bro detects intrusions by comparing network traffic against rules describing events that are deemed troublesome. These rules might describe activities (e.g., certain hosts connecting to certain services), what activities are worth alerting (e.g., attempts to a given number of different hosts constitutes a "scan"), or signatures describing known attacks or accessmore » to known vulnerabilities. If Bro detects something of interest, it can be instructed to either issue a log entry or initiate the execution of an operating system command. Bro targets high-speed (Gbps), high-volume intrusion detection. By judiciously leveraging packet filtering techniques, Bro is able to achieve the performance necessary to do so while running on commercially available PC hardware, and thus can serve as a cost effective means of monitoring a site’s Internet connection.« less

  6. Hybrid network intrusion detection

    NASA Astrophysics Data System (ADS)

    Tahmoush, David

    2014-05-01

    We report on a machine learning classifier that can be used to discover the patterns hidden within large networking data flows. It utilizes an existing intrusion detection system (IDS) as an oracle to learn a faster, less resource intensive normalcy classifier as a front-end to a hybrid network IDS. This system has the capability to recognize new attacks that are similar to known attack signatures. It is also more highly scalable and distributable than the signature-based IDS. The new hybrid design also allows distributed updates and retraining of the normalcy classifier to stay up-to-date with current threats.

  7. Rapid deployment intrusion detection system

    SciTech Connect

    Graham, R.H.

    1997-08-01

    A rapidly deployable security system is one that provides intrusion detection, assessment, communications, and annunciation capabilities; is easy to install and configure; can be rapidly deployed, and is reusable. A rapidly deployable intrusion detection system (RADIDS) has many potential applications within the DOE Complex: back-up protection for failed zones in a perimeter intrusion detection and assessment system, intrusion detection and assessment capabilities in temporary locations, protection of assets during Complex reconfiguration, and protection in hazardous locations, protection of assets during Complex reconfiguration, and protection in hazardous locations. Many DOE user-need documents have indicated an interest in a rapidly deployable intrusion detection system. The purpose of the RADIDS project is to design, develop, and implement such a system. 2 figs.

  8. Intrusion detection sensor testing tools

    SciTech Connect

    Hayward, D.R.

    1994-08-01

    Intrusion detection sensors must be frequently tested to verify that they are operational, and they must be periodically tested to verify that they are functioning at required performance levels. Concerns involving this testing can include: The significant amount of manpower required, inconsistent results due to variability in methods and personnel, exposure of personnel to hazardous environments, and difficulty in obtaining access to the areas containing some of the intrusion sensors. To address these concerns, the Department of Energy directed Sandia National Labs. to develop intrusion detection sensor testing tools. Over the past two years Sandia has developed several sensor testing tool prototypes. This paper describes the evolution of an exterior intrusion detection sensor tester and automatic data logger, and also describes various interior intrusion detection sensor test fixtures that can be remotely activated to simulate an intruder.

  9. 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.

  10. Data Mining for Intrusion Detection

    NASA Astrophysics Data System (ADS)

    Singhal, Anoop; Jajodia, Sushil

    Data Mining Techniques have been successfully applied in many different fields including marketing, manufacturing, fraud detection and network management. Over the past years there is a lot of interest in security technologies such as intrusion detection, cryptography, authentication and firewalls. This chapter discusses the application of Data Mining techniques to computer security. Conclusions are drawn and directions for future research are suggested.

  11. 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.

  12. 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.

  13. Association rule mining in intrusion detection systems

    NASA Astrophysics Data System (ADS)

    Zhao, Dong; Lu, Yan-sheng

    2004-04-01

    In a modern computer system, intrusion detection has become an essential and critical component. Data mining generally refers to the process of extracting models from large stores of data. The intrusion detection system first apply data mining programs to audit data to compute frequent patterns, extract features, and then use classification algorithms to compute detection models. The most important step of this process is to determine relations between fields in the database records to construct features. The standard association rules have not enough expressiveness. Intrusion detection system can extract the association rule with negations and with varying support thresholds to get better performance rather than extract the standard association rule.

  14. Advanced technologies for perimeter intrusion detection sensors

    SciTech Connect

    Williams, J.D.

    1995-03-01

    The development of integrated circuit fabrication techniques and the resulting devices have contributed more to the advancement of exterior intrusion detectors and alarm assessment devices than any other technology. The availability of this technology has led to the improvements in and further development of smaller more powerful computers, microprocessors, solid state memories, solid state cameras, thermal imagers, low-power lasers, and shorter pulse width and higher frequency electronic circuitry. This paper presents information on planning a perimeter intrusion detection system, identifies the site characteristics that affect its performance, and describes improvements to perimeter intrusion detection sensors and assessment devices that have been achieved by using integrated circuit technology.

  15. 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.

  16. 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.

  17. An Intrusion Detection Algorithm Based On NFPA

    NASA Astrophysics Data System (ADS)

    Anming, Zhong

    A process oriented intrusion detection algorithm based on Probabilistic Automaton with No Final probabilities (NFPA) is introduced, system call sequence of process is used as the source data. By using information in system call sequence of normal process and system call sequence of anomaly process, the anomaly detection and the misuse detection are efficiently combined. Experiments show better performance of our algorithm compared to the classical algorithm in this field.

  18. 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…

  19. NADIR (Network Anomaly Detection and Intrusion Reporter): A prototype network intrusion detection system

    SciTech Connect

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

    1990-01-01

    The Network Anomaly Detection and Intrusion Reporter (NADIR) is an expert system which is intended to provide real-time security auditing for intrusion and misuse detection at Los Alamos National Laboratory's Integrated Computing Network (ICN). It is based on three basic assumptions: that statistical analysis of computer system and user activities may be used to characterize normal system and user behavior, and that given the resulting statistical profiles, behavior which deviates beyond certain bounds can be detected, that expert system techniques can be applied to security auditing and intrusion detection, and that successful intrusion detection may take place while monitoring a limited set of network activities such as user authentication and access control, file movement and storage, and job scheduling. NADIR has been developed to employ these basic concepts while monitoring the audited activities of more than 8000 ICN users.

  20. 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.

  1. Research on IPv6 intrusion detection system Snort-based

    NASA Astrophysics Data System (ADS)

    Shen, Zihao; Wang, Hui

    2010-07-01

    This paper introduces the common intrusion detection technologies, discusses the work flow of Snort intrusion detection system, and analyzes IPv6 data packet encapsulation and protocol decoding technology. We propose the expanding Snort architecture to support IPv6 intrusion detection in accordance with CIDF standard combined with protocol analysis technology and pattern matching technology, and present its composition. The research indicates that the expanding Snort system can effectively detect various intrusion attacks; it is high in detection efficiency and detection accuracy and reduces false alarm and omission report, which effectively solves the problem of IPv6 intrusion detection.

  2. Intrusion-Aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

    PubMed Central

    Shaikh, Riaz Ahmed; Jameel, Hassan; d’Auriol, Brian J.; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

    2009-01-01

    Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm. PMID:22454568

  3. 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).

  4. Intrusion detection using pattern recognition methods

    NASA Astrophysics Data System (ADS)

    Jiang, Nan; Yu, Li

    2007-09-01

    Today, cyber attacks such as worms, scanning, active attackers are pervasive in Internet. A number of security approaches are proposed to address this problem, among which the intrusion detection system (IDS) appears to be one of the major and most effective solutions for defending against malicious users. Essentially, intrusion detection problem can be generalized as a classification problem, whose goal is to distinguish normal behaviors and anomalies. There are many well-known pattern recognition algorithms for classification purpose. In this paper we describe the details of applying pattern recognition methods to the intrusion detection research field. Experimenting on the KDDCUP 99 data set, we first use information gain metric to reduce the dimensionality of the original feature space. Two supervised methods, the support vector machine as well as the multi-layer neural network have been tested and the results display high detection rate and low false alarm rate, which is promising for real world applications. In addition, three unsupervised methods, Single-Linkage, K-Means, and CLIQUE, are also implemented and evaluated in the paper. The low computational complexity reveals their application in initial data reduction process.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. A novel interacting multiple model based network intrusion detection scheme

    NASA Astrophysics Data System (ADS)

    Xin, Ruichi; Venkatasubramanian, Vijay; Leung, Henry

    2006-04-01

    In today's information age, information and network security are of primary importance to any organization. Network intrusion is a serious threat to security of computers and data networks. In internet protocol (IP) based network, intrusions originate in different kinds of packets/messages contained in the open system interconnection (OSI) layer 3 or higher layers. Network intrusion detection and prevention systems observe the layer 3 packets (or layer 4 to 7 messages) to screen for intrusions and security threats. Signature based methods use a pre-existing database that document intrusion patterns as perceived in the layer 3 to 7 protocol traffics and match the incoming traffic for potential intrusion attacks. Alternately, network traffic data can be modeled and any huge anomaly from the established traffic pattern can be detected as network intrusion. The latter method, also known as anomaly based detection is gaining popularity for its versatility in learning new patterns and discovering new attacks. It is apparent that for a reliable performance, an accurate model of the network data needs to be established. In this paper, we illustrate using collected data that network traffic is seldom stationary. We propose the use of multiple models to accurately represent the traffic data. The improvement in reliability of the proposed model is verified by measuring the detection and false alarm rates on several datasets.

  13. 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.

  14. 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.

  15. A New Intrusion Detection Method Based on Antibody Concentration

    NASA Astrophysics Data System (ADS)

    Zeng, Jie; Li, Tao; Li, Guiyang; Li, Haibo

    Antibody is one kind of protein that fights against the harmful antigen in human immune system. In modern medical examination, the health status of a human body can be diagnosed by detecting the intrusion intensity of a specific antigen and the concentration indicator of corresponding antibody from human body’s serum. In this paper, inspired by the principle of antigen-antibody reactions, we present a New Intrusion Detection Method Based on Antibody Concentration (NIDMBAC) to reduce false alarm rate without affecting detection rate. In our proposed method, the basic definitions of self, nonself, antigen and detector in the intrusion detection domain are given. Then, according to the antigen intrusion intensity, the change of antibody number is recorded from the process of clone proliferation for detectors based on the antigen classified recognition. Finally, building upon the above works, a probabilistic calculation method for the intrusion alarm production, which is based on the correlation between the antigen intrusion intensity and the antibody concen-tration, is proposed. Our theoretical analysis and experimental results show that our proposed method has a better performance than traditional methods.

  16. Distributed intrusion detection system based on fuzzy rules

    NASA Astrophysics Data System (ADS)

    Qiao, Peili; Su, Jie; Liu, Yahui

    2006-04-01

    Computational Intelligence is the theory and method solving problems by simulating the intelligence of human using computer and it is the development of Artificial Intelligence. Fuzzy Technique is one of the most important theories of computational Intelligence. Genetic Fuzzy Technique and Neuro-Fuzzy Technique are the combination of Fuzzy Technique and novel techniques. This paper gives a distributed intrusion detection system based on fuzzy rules that has the characters of distributed parallel processing, self-organization, self-learning and self-adaptation by the using of Neuro-Fuzzy Technique and Genetic Fuzzy Technique. Specially, fuzzy decision technique can be used to reduce false detection. The results of the simulation experiment show that this intrusion detection system model has the characteristics of distributed, error tolerance, dynamic learning, and adaptation. It solves the problem of low identifying rate to new attacks and hidden attacks. The false detection rate is low. This approach is efficient to the distributed intrusion detection.

  17. Sandia Network Intrusion Detection Assessment Version 1.0

    SciTech Connect

    Bauer, Keith C.; Volkmer, Greg

    2002-09-20

    SNIDE Assess is a general-purpose software package for matching network event notifications from specialized sensors against on or more attack templattes. If a pattern of events matches an attack template, then SNIDE Assess can be configured to initate responses. SNIDE Assess provides a graphical user interface for configuring attack templates, and provides the required flexibility to define new event notification messages and responses. In general, SNIDE Assess is designed for event correlation for network intrusion detection systems. This version of SNIDE Assess is configured specifically for detection of control plane intrusions on Asynchronous Transfer Mode (ATM) networks. The SNIDE Assessment Engine is written in C. The SNIDE Assessment engine is a piece of the software that is responsible for receiving incoming messages from sensors, assimilating the information from the tripped sensors, and determining if the messages received constitute and intrusion, based on the rules specified by the system administrator. If it has been determined that a possible intrusion has occurred, the SNIDE Assessment engine will send a message to one or more response components to perform the action specified in the rule. The SNIDE Assessment engine is rule driven, that is, it's behavior is determined by specifying a set of text based rules. To provide flexibility, the definition of what constitutes an intrusion is left to the intrusion detection system administrator. a graphical rule editor is provided to allow the administrator to define what type of intrusions are to be monitored. The rules consist of combinations of sensors with boolean operators and filters. SNIDE Assessment rules can be made arbitrarily compled by using Operators and Filters. Operators allow for logic constructs to be created that combine incoming Sensor Notification events. When grouped together, they are referred to as solution sets. Each operator defnes on logic operation that is satisfied when a complete

  18. Power-Aware Intrusion Detection in Mobile Ad Hoc Networks

    NASA Astrophysics Data System (ADS)

    Şen, Sevil; Clark, John A.; Tapiador, Juan E.

    Mobile ad hoc networks (MANETs) are a highly promising new form of networking. However they are more vulnerable to attacks than wired networks. In addition, conventional intrusion detection systems (IDS) are ineffective and inefficient for highly dynamic and resource-constrained environments. Achieving an effective operational MANET requires tradeoffs to be made between functional and non-functional criteria. In this paper we show how Genetic Programming (GP) together with a Multi-Objective Evolutionary Algorithm (MOEA) can be used to synthesise intrusion detection programs that make optimal tradeoffs between security criteria and the power they consume.

  19. Alerts Visualization and Clustering in Network-based Intrusion Detection

    SciTech Connect

    Yang, Dr. Li; Gasior, Wade C; Dasireddy, Swetha

    2010-04-01

    Today's Intrusion detection systems when deployed on a busy network overload the network with huge number of alerts. This behavior of producing too much raw information makes it less effective. We propose a system which takes both raw data and Snort alerts to visualize and analyze possible intrusions in a network. Then we present with two models for the visualization of clustered alerts. Our first model gives the network administrator with the logical topology of the network and detailed information of each node that involves its associated alerts and connections. In the second model, flocking model, presents the network administrator with the visual representation of IDS data in which each alert is represented in different color and the alerts with maximum similarity move together. This gives network administrator with the idea of detecting various of intrusions through visualizing the alert patterns.

  20. 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

  1. 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

  2. Analytic sequential methods for detecting network intrusions

    NASA Astrophysics Data System (ADS)

    Chen, Xinjia; Walker, Ernest

    2014-05-01

    In this paper, we propose an analytic sequential methods for detecting port-scan attackers which routinely perform random "portscans" of IP addresses to find vulnerable servers to compromise. In addition to rigorously control the probability of falsely implicating benign remote hosts as malicious, our method performs significantly faster than other current solutions. We have developed explicit formulae for quick determination of the parameters of the new detection algorithm.

  3. 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)

  4. Adaptive sequential methods for detecting network intrusions

    NASA Astrophysics Data System (ADS)

    Chen, Xinjia; Walker, Ernest

    2013-06-01

    In this paper, we propose new sequential methods for detecting port-scan attackers which routinely perform random "portscans" of IP addresses to find vulnerable servers to compromise. In addition to rigorously control the probability of falsely implicating benign remote hosts as malicious, our method performs significantly faster than other current solutions. Moreover, our method guarantees that the maximum amount of observational time is bounded. In contrast to the previous most effective method, Threshold Random Walk Algorithm, which is explicit and analytical in nature, our proposed algorithm involve parameters to be determined by numerical methods. We have introduced computational techniques such as iterative minimax optimization for quick determination of the parameters of the new detection algorithm. A framework of multi-valued decision for detecting portscanners and DoS attacks is also proposed.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Misuse and intrusion detection at Los Alamos National Laboratory

    SciTech Connect

    Jackson, K.A.; Neuman, M.C.; Simmonds, D.D.; Stallings, C.A.; Thompson, J.L.; Christoph, G.G.

    1995-04-01

    An effective method for detecting computer misuse is the automatic auditing and analysis of on-line user activity. This activity is reflected in system audit records, in system vulnerability postures, and in other evidence found through active system testing. Since 1989 we have implemented a misuse and intrusion detection system at Los Alamos. This is the Network Anomaly Detection and Intrusion Reporter, or NADIR. NADIR currently audits a Kerberos distributed authentication system, file activity on a mass, storage system, and four Cray supercomputers that run the UNICOS operating system. NADIR summarizes user activity and system configuration in statistical profiles. It compares these profiles to expert rules that define security policy and improper or suspicious behavior. It reports suspicious behavior to security auditors and provides tools to aid in follow-up investigations, As NADIR is constantly evolving, this paper reports its development to date.

  10. The Mobile Intrusion Detection and Assessment System (MIDAS)

    SciTech Connect

    Arlowe, H.D.; Coleman, D.E.

    1990-01-01

    This paper describes MIDAS, the Mobile Intrusion Detection and Assessment System. MIDAS is a security system that can be quickly deployed to provide wide area coverage for a mobile asset. MIDAS uses two passive infrared imaging sensors, one for intruder detection and one for assessment. Detected targets are tracked while assessment cameras are directed to view the intruder location for operator observation and assessment. The dual sensor design allows simultaneous detection, assessment, and tracking. Control and status information is provided to an operator using a color graphics terminal, touch panel driven menus, and a joystick for control of the assessment sensor pan and tilt. 1 ref., 5 figs.

  11. 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. PMID:18348941

  12. Adaptive critic design for computer intrusion detection system

    NASA Astrophysics Data System (ADS)

    Novokhodko, Alexander; Wunsch, Donald C., II; Dagli, Cihan H.

    2001-03-01

    This paper summarizes ongoing research. A neural network is used to detect a computer system intrusion basing on data from the system audit trail generated by Solaris Basic Security Module. The data have been provided by Lincoln Labs, MIT. The system alerts the human operator, when it encounters suspicious activity logged in the audit trail. To reduce the false alarm rate and accommodate the temporal indefiniteness of moment of attack a reinforcement learning approach is chosen to train the network.

  13. Using Unix system auditing for detecting network intrusions

    SciTech Connect

    Christensen, M.J.

    1993-03-01

    Intrusion Detection Systems (IDSs) are designed to detect actions of individuals who use computer resources without authorization as well as legitimate users who exceed their privileges. This paper describes a novel approach to IDS research, namely a decision aiding approach to intrusion detection. The introduction of a decision tree represents the logical steps necessary to distinguish and identify different types of attacks. This tool, the Intrusion Decision Aiding Tool (IDAT), utilizes IDS-based attack models and standard Unix audit data. Since attacks have certain characteristics and are based on already developed signature attack models, experienced and knowledgeable Unix system administrators know what to look for in system audit logs to determine if a system has been attacked. Others, however, are usually less able to recognize common signatures of unauthorized access. Users can traverse the tree using available audit data displayed by IDAT and general knowledge they possess to reach a conclusion regarding suspicious activity. IDAT is an easy-to-use window based application that gathers, analyzes, and displays pertinent system data according to Unix attack characteristics. IDAT offers a more practical approach and allows the user to make an informed decision regarding suspicious activity.

  14. Sandia Network Intrusion Detection Assessment Version 1.0

    2002-09-20

    SNIDE Assess is a general-purpose software package for matching network event notifications from specialized sensors against on or more attack templattes. If a pattern of events matches an attack template, then SNIDE Assess can be configured to initate responses. SNIDE Assess provides a graphical user interface for configuring attack templates, and provides the required flexibility to define new event notification messages and responses. In general, SNIDE Assess is designed for event correlation for network intrusionmore » detection systems. This version of SNIDE Assess is configured specifically for detection of control plane intrusions on Asynchronous Transfer Mode (ATM) networks. The SNIDE Assessment Engine is written in C. The SNIDE Assessment engine is a piece of the software that is responsible for receiving incoming messages from sensors, assimilating the information from the tripped sensors, and determining if the messages received constitute and intrusion, based on the rules specified by the system administrator. If it has been determined that a possible intrusion has occurred, the SNIDE Assessment engine will send a message to one or more response components to perform the action specified in the rule. The SNIDE Assessment engine is rule driven, that is, it's behavior is determined by specifying a set of text based rules. To provide flexibility, the definition of what constitutes an intrusion is left to the intrusion detection system administrator. a graphical rule editor is provided to allow the administrator to define what type of intrusions are to be monitored. The rules consist of combinations of sensors with boolean operators and filters. SNIDE Assessment rules can be made arbitrarily compled by using Operators and Filters. Operators allow for logic constructs to be created that combine incoming Sensor Notification events. When grouped together, they are referred to as solution sets. Each operator defnes on logic operation that is satisfied when a

  15. Experiments on Adaptive Techniques for Host-Based Intrusion Detection

    SciTech Connect

    DRAELOS, TIMOTHY J.; COLLINS, MICHAEL J.; DUGGAN, DAVID P.; THOMAS, EDWARD V.; WUNSCH, DONALD

    2001-09-01

    This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerable preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.

  16. A model for anomaly classification in intrusion detection systems

    NASA Astrophysics Data System (ADS)

    Ferreira, V. O.; Galhardi, V. V.; Gonçalves, L. B. L.; Silva, R. C.; Cansian, A. M.

    2015-09-01

    Intrusion Detection Systems (IDS) are traditionally divided into two types according to the detection methods they employ, namely (i) misuse detection and (ii) anomaly detection. Anomaly detection has been widely used and its main advantage is the ability to detect new attacks. However, the analysis of anomalies generated can become expensive, since they often have no clear information about the malicious events they represent. In this context, this paper presents a model for automated classification of alerts generated by an anomaly based IDS. The main goal is either the classification of the detected anomalies in well-defined taxonomies of attacks or to identify whether it is a false positive misclassified by the IDS. Some common attacks to computer networks were considered and we achieved important results that can equip security analysts with best resources for their analyses.

  17. 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…

  18. MIDAS, the Mobile Intrusion Detection and Assessment System

    SciTech Connect

    Arlowe, H.D.; Coleman, D.E.; Williams, J.D.

    1990-01-01

    MIDAS is a semiautomated passive detection and assessment security system that can be quickly deployed to provide wide-area coverage for a mobile military asset. Designed to be mounted on top of an unguyed telescoping mast, its specially packaged set of 32 infrared sensors spin 360 degrees every two seconds. The unit produces a low resolution infrared image by sampling each sensor more than 16,000 times in a single 360-degree rotation. Drawing from image processing techniques, MIDAS detects vehicular and pedestrian intruders and produces an alarm when an intrusion is detected. Multiple intruders are tracked. MIDAS automatically directs either an assessment camera or a FLIR to one of the tracks. The alerted operator assesses the intruder and initiates a response. Once the operator assesses an intruder, the system continues to track it without generating new alarms. Because the system will track multiple targets and because the assessment system is a separate pan and tilt unit, the detection and tracking system cannot be blind-sided while the operator is assessing a diversionary intrusion. 4 figs.

  19. An integrated pattern recognition approach for intrusion detection.

    PubMed

    Pandit, Amod; Stanley, R Joe; McMillin, Bruce

    2002-01-01

    Intrusion detection systems (IDS) attempt to address the vulnerability of computer-based systems for abuse by insiders and to penetration by outsiders. An IDS is required to examine an enormous amount of data generated by computer networks to assist in the abuse detection process. Thus, there is a need to develop automated tools that address these requirements to assist system operators in the detection of violations of existing security policies. In this research, an automated IDS is proposed for insider threats in a distributed system. The proposed IDS functions as an anomaly detector for insider system operations based on the analysis of the system's log files. The approach integrates dynamic programming and adaptive resonance theory (ART1) clustering. The integrated approach aligns sequences of log events with prototypical sequences of events for performing tasks and classifies the aligned sequences for intrusion detection. The system examined for this research is a Boots System for controlling the movement of boots from one place to another under specific security restrictions related to the boot orders. We present the proposed model, the results achieved and the analysis of an implemented prototype.

  20. Operational tips for improving intrusion detection system performance

    SciTech Connect

    Adams, D.G.

    1996-09-01

    The installation of a new intrusion detection system (IDS) is, of course, expected to improve site security. However, depending upon the way the system is used, it can, over time, actually degrade security. Proper use, control, and maintenance of the IDS is critical if site security is to be maintained. This paper discusses several operational issues that should be addressed in order to use an IDS effectively. Several anecdotes from the author`s experience are given to illustrate proper and improper use of an IDS. Improper operational use of an IDS can render it ineffective. Applying these tips can help keep the IDS operating at peak performance.

  1. Operational tips for improving intrusion detection system performance

    SciTech Connect

    Adams, D.G.

    1996-12-31

    The installation of a new intrusion detection system (IDS) is, of course, expected to improve site security. However, depending upon the way the system is used, it can, over time, actually degrade security. Proper use, control, and maintenance of the IDS is critical if site security is to be maintained. This paper discusses several operational issues that should be addressed in order to use an IDS effectively. Several anecdotes from the author`s experience are given to illustrate proper and improper use of an IDS. Improper operational use of an IDS can render it ineffective. Applying these tips can help keep the IDS operating at peak performance.

  2. Performance of Neural Networks Methods In Intrusion Detection

    SciTech Connect

    Dao, V N; Vemuri, R

    2001-07-09

    By accurately profiling the users via their unique attributes, it is possible to view the intrusion detection problem as a classification of authorized users and intruders. This paper demonstrates that artificial neural network (ANN) techniques can be used to solve this classification problem. Furthermore, the paper compares the performance of three neural networks methods in classifying authorized users and intruders using synthetically generated data. The three methods are the gradient descent back propagation (BP) with momentum, the conjugate gradient BP, and the quasi-Newton BP.

  3. 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.

  4. SiC: An Agent Based Architecture for Preventing and Detecting Attacks to Ubiquitous Databases

    NASA Astrophysics Data System (ADS)

    Pinzón, Cristian; de Paz, Yanira; Bajo, Javier; Abraham, Ajith; Corchado, Juan M.

    One of the main attacks to ubiquitous databases is the structure query language (SQL) injection attack, which causes severe damages both in the commercial aspect and in the user’s confidence. This chapter proposes the SiC architecture as a solution to the SQL injection attack problem. This is a hierarchical distributed multiagent architecture, which involves an entirely new approach with respect to existing architectures for the prevention and detection of SQL injections. SiC incorporates a kind of intelligent agent, which integrates a case-based reasoning system. This agent, which is the core of the architecture, allows the application of detection techniques based on anomalies as well as those based on patterns, providing a great degree of autonomy, flexibility, robustness and dynamic scalability. The characteristics of the multiagent system allow an architecture to detect attacks from different types of devices, regardless of the physical location. The architecture has been tested on a medical database, guaranteeing safe access from various devices such as PDAs and notebook computers.

  5. 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

  6. A survey of artificial immune system based intrusion detection.

    PubMed

    Yang, Hua; 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

  7. A study on intrusion detection model based on hybrid classifier

    NASA Astrophysics Data System (ADS)

    Liu, Kewen; Yang, Qingbo

    2013-03-01

    In order to improve the accuracy of classification problem in intrusion detection, a hybrid classifier which was composed by KPCA, BPNN and QGA, has been proposed in this paper. In the hybrid classifier, KPCA was used to reduce dimensions, and then QGA was used to search the best parameters for BPNN. BPNN which has been got the best weights matrix and thresholds by QGA, was used to train classification model. The main core factors of original dataset can be preserved by KPCA, and greatly reduced the computations. The weakness of BPNN, which was usually easy to get stuck in local minimum, can be solved by QGA. Finally, the effectiveness of hybrid classifier was proved by experiments. Compared with traditional methods, the hybrid classifier has better performance in reducing the classify errors.

  8. Online Adaboost-Based Parameterized Methods for Dynamic Distributed Network Intrusion Detection.

    PubMed

    Hu, Weiming; Gao, Jun; Wang, Yanguo; Wu, Ou; Maybank, Stephen

    2014-01-01

    Current network intrusion detection systems lack adaptability to the frequently changing network environments. Furthermore, intrusion detection in the new distributed architectures is now a major requirement. In this paper, we propose two online Adaboost-based intrusion detection algorithms. In the first algorithm, a traditional online Adaboost process is used where decision stumps are used as weak classifiers. In the second algorithm, an improved online Adaboost process is proposed, and online Gaussian mixture models (GMMs) are used as weak classifiers. We further propose a distributed intrusion detection framework, in which a local parameterized detection model is constructed in each node using the online Adaboost algorithm. A global detection model is constructed in each node by combining the local parametric models using a small number of samples in the node. This combination is achieved using an algorithm based on particle swarm optimization (PSO) and support vector machines. The global model in each node is used to detect intrusions. Experimental results show that the improved online Adaboost process with GMMs obtains a higher detection rate and a lower false alarm rate than the traditional online Adaboost process that uses decision stumps. Both the algorithms outperform existing intrusion detection algorithms. It is also shown that our PSO, and SVM-based algorithm effectively combines the local detection models into the global model in each node; the global model in a node can handle the intrusion types that are found in other nodes, without sharing the samples of these intrusion types. PMID:23757534

  9. 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.

  10. 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

  11. 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

  12. Mobile agent and multilayer integrated distributed intrusion detection model for clustering ad hoc networks

    NASA Astrophysics Data System (ADS)

    Feng, Jianxin; Wang, Guangxing

    2004-04-01

    Ad hoc networks do not depend on any predefined infrastructure or centralized administration to operate. Their security characters require more complex security preventions. As the second line of defense, Intrusion detection is the necessary means of getting the high survivability. In this paper the security characters of ad hoc networks and the related contents of intrusion detection are discussed. Mobile Agent and Multi-layer Integrated Distributed Intrusion Detection Model (MAMIDIDM) and a heuristic global detection algorithm are proposed tentatively by combining the mobile agent technology with the multi-layer conception. This heuristic global detection algorithm combines the mobile agent detection engine with the multi-layer detection engines and analyzes the results obtained by the corresponding detection engines. MAMIDIDM has the better flexibility and extensibility, can execute the intrusion detection in clustering ad hoc networks effectively.

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

    PubMed

    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

  14. 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

  15. 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.

  16. 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)

  17. Detection of stratospheric ozone intrusions by windprofiler radars.

    PubMed

    Hocking, W K; Carey-Smith, T; Tarasick, D W; Argall, P S; Strong, K; Rochon, Y; Zawadzki, I; Taylor, P A

    2007-11-01

    Stratospheric ozone attenuates harmful ultraviolet radiation and protects the Earth's biosphere. Ozone is also of fundamental importance for the chemistry of the lowermost part of the atmosphere, the troposphere. At ground level, ozone is an important by-product of anthropogenic pollution, damaging forests and crops, and negatively affecting human health. Ozone is critical to the chemical and thermal balance of the troposphere because, via the formation of hydroxyl radicals, it controls the capacity of tropospheric air to oxidize and remove other pollutants. Moreover, ozone is an important greenhouse gas, particularly in the upper troposphere. Although photochemistry in the lower troposphere is the major source of tropospheric ozone, the stratosphere-troposphere transport of ozone is important to the overall climatology, budget and long-term trends of tropospheric ozone. Stratospheric intrusion events, however, are still poorly understood. Here we introduce the use of modern windprofiler radars to assist in such transport investigations. By hourly monitoring the radar-derived tropopause height in combination with a series of frequent ozonesonde balloon launches, we find numerous intrusions of ozone from the stratosphere into the troposphere in southeastern Canada. On some occasions, ozone is dispersed at altitudes of two to four kilometres, but on other occasions it reaches the ground, where it can dominate the ozone density variability. We observe rapid changes in radar tropopause height immediately preceding these intrusion events. Such changes therefore serve as a valuable diagnostic for the occurrence of ozone intrusion events. Our studies emphasize the impact that stratospheric ozone can have on tropospheric ozone, and show that windprofiler data can be used to infer the possibility of ozone intrusions, as well as better represent tropopause motions in association with stratosphere-troposphere transport.

  18. 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

  19. 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.

  20. RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

    PubMed

    Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

    2009-01-01

    The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components.

  1. RIDES: Robust Intrusion Detection System for IP-Based Ubiquitous Sensor Networks.

    PubMed

    Amin, Syed Obaid; Siddiqui, Muhammad Shoaib; Hong, Choong Seon; Lee, Sungwon

    2009-01-01

    The IP-based Ubiquitous Sensor Network (IP-USN) is an effort to build the "Internet of things". By utilizing IP for low power networks, we can benefit from existing well established tools and technologies of IP networks. Along with many other unresolved issues, securing IP-USN is of great concern for researchers so that future market satisfaction and demands can be met. Without proper security measures, both reactive and proactive, it is hard to envisage an IP-USN realm. In this paper we present a design of an IDS (Intrusion Detection System) called RIDES (Robust Intrusion DEtection System) for IP-USN. RIDES is a hybrid intrusion detection system, which incorporates both Signature and Anomaly based intrusion detection components. For signature based intrusion detection this paper only discusses the implementation of distributed pattern matching algorithm with the help of signature-code, a dynamically created attack-signature identifier. Other aspects, such as creation of rules are not discussed. On the other hand, for anomaly based detection we propose a scoring classifier based on the SPC (Statistical Process Control) technique called CUSUM charts. We also investigate the settings and their effects on the performance of related parameters for both of the components. PMID:22412321

  2. Implementing and testing a fiber-optic polarization-based intrusion detection system

    NASA Astrophysics Data System (ADS)

    Hajj, Rasha El; MacDonald, Gregory; Verma, Pramode; Huck, Robert

    2015-09-01

    We describe a layer-1-based intrusion detection system for fiber-optic-based networks. Layer-1-based intrusion detection represents a significant elevation in security as it prohibits an adversary from obtaining information in the first place (no cryptanalysis is possible). We describe the experimental setup of the intrusion detection system, which is based on monitoring the behavior of certain attributes of light both in unperturbed and perturbed optical fiber links. The system was tested with optical fiber links of various lengths and types, under different environmental conditions, and under changes in fiber geometry similar to what is experienced during tapping activity. Comparison of the results for perturbed and unperturbed links has shown that the state of polarization is more sensitive to intrusion activity than the degree of polarization or power of the received light. The testing was conducted in a simulated telecommunication network environment that included both underground and aerial links. The links were monitored for intrusion activity. Attempts to tap the link were easily detected with no apparent degradation in the visual quality of the real-time surveillance video.

  3. 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.

  4. 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.

  5. Creating a two-layered augmented artificial immune system for application to computer network intrusion detection

    NASA Astrophysics Data System (ADS)

    Judge, Matthew G.; Lamont, Gary B.

    2009-05-01

    Computer network security has become a very serious concern of commercial, industrial, and military organizations due to the increasing number of network threats such as outsider intrusions and insider covert activities. An important security element of course is network intrusion detection which is a difficult real world problem that has been addressed through many different solution attempts. Using an artificial immune system has been shown to be one of the most promising results. By enhancing jREMISA, a multi-objective evolutionary algorithm inspired artificial immune system, with a secondary defense layer; we produce improved accuracy of intrusion classification and a flexibility in responsiveness. This responsiveness can be leveraged to provide a much more powerful and accurate system, through the use of increased processing time and dedicated hardware which has the flexibility of being located out of band.

  6. 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

  7. 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.

  8. 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.

  9. Application of covert illumination to intrusion surveillance, assessment, and detection

    NASA Astrophysics Data System (ADS)

    Maki, Melvin C.; Scherbarth, Stefan

    1995-05-01

    Covert illumination is an important element in providing surveillance, detection, and assessment for security applications. IR illumination is increasingly providing this function; however, conventional filament-based illuminators have limited performance and life. A new variety of light emitting diode (LED) illuminators is described that provides long life at low power. A further advance is to use a planar array of LED's with lenses to optimize the uniformity of scene illumination and maximize the illumination range. Modern CCD cameras have an inherently high IR sensitivity so are well matched to work with this illumination. Further enhancements are to integrate the combination of low-light camera and LED illuminator in a discrete column type package to make the overall illumination and assessment system unobtrusive. Finally, these components can be further combined with automated assessment aids to turn the surveillance device into a true detection sensor that can operate stand-alone without active personnel monitoring. A review of the major IR design considerations is included, along with several examples of systems to illustrate potential applications.

  10. 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.

  11. 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.

  12. 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. PMID:26540724

  13. 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.

  14. State-Based Network Intrusion Detection Systems for SCADA Protocols: A Proof of Concept

    NASA Astrophysics Data System (ADS)

    Carcano, Andrea; Fovino, Igor Nai; Masera, Marcelo; Trombetta, Alberto

    We present a novel Intrusion Detection System able to detect complex attacks to SCADA systems. By complex attack, we mean a set of commands (carried in Modbus packets) that, while licit when considered in isolation on a single-packet basis, interfere with the correct behavior of the system. The proposed IDS detects such attacks thanks to an internal representation of the controlled SCADA system and a corresponding rule language, powerful enough to express the system's critical states. Furthermore, we detail the implementation and provide experimental comparative results.

  15. Comparative study of adaptive-noise-cancellation algorithms for intrusion detection systems

    SciTech Connect

    Claassen, J.P.; Patterson, M.M.

    1981-01-01

    Some intrusion detection systems are susceptible to nonstationary noise resulting in frequent nuisance alarms and poor detection when the noise is present. Adaptive inverse filtering for single channel systems and adaptive noise cancellation for two channel systems have both demonstrated good potential in removing correlated noise components prior detection. For such noise susceptible systems the suitability of a noise reduction algorithm must be established in a trade-off study weighing algorithm complexity against performance. The performance characteristics of several distinct classes of algorithms are established through comparative computer studies using real signals. The relative merits of the different algorithms are discussed in the light of the nature of intruder and noise signals.

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

    PubMed

    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

  17. 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

  18. Investigation of novel spectral and wavelet statistics for UGS-based intrusion detection

    NASA Astrophysics Data System (ADS)

    Narayanaswami, Ranga; Gandhe, Avinash; Tyurina, Anastasia; McComas, Michael; Mehra, Raman K.

    2012-06-01

    Seismic Unattended Ground Sensors (UGS) are low cost and covert, making them a suitable candidate for border patrol. Current seismic UGS systems use cadence-based intrusion detection algorithms and are easily confused between humans and animals. The poor discrimination ability between humans and animals results in missed detections as well as higher false (nuisance) alarm rates. In order for seismic UGS systems to be deployed successfully, new signal processing algorithms with better discrimination ability between humans and animals are needed. We have characterized the seismic signals using frequency domain and time-frequency domain statistics, which improve the discrimination between humans, animals and vehicles.

  19. Unsupervised algorithms for intrusion detection and identification in wireless ad hoc sensor networks

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    2009-05-01

    In previous work by the author, parameters across network protocol layers were selected as features in supervised algorithms that detect and identify certain intrusion attacks on wireless ad hoc sensor networks (WSNs) carrying multisensor data. The algorithms improved the residual performance of the intrusion prevention measures provided by any dynamic key-management schemes and trust models implemented among network nodes. The approach of this paper does not train algorithms on the signature of known attack traffic, but, instead, the approach is based on unsupervised anomaly detection techniques that learn the signature of normal network traffic. Unsupervised learning does not require the data to be labeled or to be purely of one type, i.e., normal or attack traffic. The approach can be augmented to add any security attributes and quantified trust levels, established during data exchanges among nodes, to the set of cross-layer features from the WSN protocols. A two-stage framework is introduced for the security algorithms to overcome the problems of input size and resource constraints. The first stage is an unsupervised clustering algorithm which reduces the payload of network data packets to a tractable size. The second stage is a traditional anomaly detection algorithm based on a variation of support vector machines (SVMs), whose efficiency is improved by the availability of data in the packet payload. In the first stage, selected algorithms are adapted to WSN platforms to meet system requirements for simple parallel distributed computation, distributed storage and data robustness. A set of mobile software agents, acting like an ant colony in securing the WSN, are distributed at the nodes to implement the algorithms. The agents move among the layers involved in the network response to the intrusions at each active node and trustworthy neighborhood, collecting parametric values and executing assigned decision tasks. This minimizes the need to move large amounts

  20. Integrated Scalable Parallel Firewall and Intrusion Detection System for High-Speed Networks

    SciTech Connect

    Fulp, Errin W; Anderson, Robert E; Ahn, David K

    2009-08-31

    This project developed a new scalable network firewall and Intrusion Protection System (IPS) that can manage increasing traffic loads, higher network speeds, and strict Quality of Service (QoS) requirements. This new approach provides a strong foundation for next-generation network security technologies and products that address growing and unmet needs in the government and corporate sectors by delivering Optimal Network Security. Controlling access is an essential task for securing networks that are vital to private industry, government agencies, and the military. This access can be granted or denied based on the packet header or payload contents. For example, a simple network firewall enforces a security policy by inspecting and filtering the packet headers. As a complement to the firewall, an Intrusion Detection System (IDS) inspects the packet payload for known threat signatures; for example, virus or worm. Similar to a firewall policy, IDS policies consist of multiple rules that specify an action for matching packets. Each rule can specify different items, such as the signature contents and the signature location within the payload. When the firewall and IDS are merged into one device, the resulting system is referred to as an Intrusion Protection System (IPS), which provides both packet header and payload inspections. Having both types of inspections is very desirable and more manageable in a single device.

  1. A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments

    PubMed Central

    Avalappampatty Sivasamy, Aneetha; Sundan, Bose

    2015-01-01

    The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T2 method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T2 statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better. PMID:26357668

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Cross-layer design for intrusion detection and data security in wireless ad hoc sensor networks

    NASA Astrophysics Data System (ADS)

    Hortos, William S.

    2007-09-01

    A wireless ad hoc sensor network is a configuration for area surveillance that affords rapid, flexible deployment in arbitrary threat environments. There is no infrastructure support and sensor nodes communicate with each other only when they are in transmission range. The nodes are severely resource-constrained, with limited processing, memory and power capacities and must operate cooperatively to fulfill a common mission in typically unattended modes. In a wireless sensor network (WSN), each sensor at a node can observe locally some underlying physical phenomenon and sends a quantized version of the observation to sink (destination) nodes via wireless links. Since the wireless medium can be easily eavesdropped, links can be compromised by intrusion attacks from nodes that may mount denial-of-service attacks or insert spurious information into routing packets, leading to routing loops, long timeouts, impersonation, and node exhaustion. A cross-layer design based on protocol-layer interactions is proposed for detection and identification of various intrusion attacks on WSN operation. A feature set is formed from selected cross-layer parameters of the WSN protocol to detect and identify security threats due to intrusion attacks. A separate protocol is not constructed from the cross-layer design; instead, security attributes and quantified trust levels at and among nodes established during data exchanges complement customary WSN metrics of energy usage, reliability, route availability, and end-to-end quality-of-service (QoS) provisioning. Statistical pattern recognition algorithms are applied that use observed feature-set patterns observed during network operations, viewed as security audit logs. These algorithms provide the "best" network global performance in the presence of various intrusion attacks. A set of mobile (software) agents distributed at the nodes implement the algorithms, by moving among the layers involved in the network response at each active node

  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. PMID:27271802

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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.

  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. Laser spectroscopy for totally non-intrusive detection of oxygen in modified atmosphere food packages

    NASA Astrophysics Data System (ADS)

    Cocola, L.; Fedel, M.; Poletto, L.; Tondello, G.

    2015-04-01

    A device for measuring the oxygen concentration inside packages in modified atmosphere working in a completely non-intrusive way has been developed and tested. The device uses tunable diode laser spectroscopy in a geometry similar to a short distance LIDAR: A laser beam is sent through the top film of a food package, and the absorption is measured by detecting the light scattered by the bottom of the container or by a portion of the food herein contained. The device can operate completely in a contactless way from the package, and the distances of absorption both outside and inside the package are measured with a triangulation system. The performances of the device have been tested for various types of containers, and absolute values for the oxygen concentration have been compared with standard albeit destructive measurements.

  19. Using the sequential regression (SER) algorithm for long-term signal processing. [Intrusion detection

    SciTech Connect

    Soldan, D. L.; Ahmed, N.; Stearns, S. D.

    1980-01-01

    The use of the sequential regression (SER) algorithm (Electron. Lett., 14, 118(1978); 13, 446(1977)) for long-term processing applications is limited by two problems that can occur when an SER predictor has more weights than required to predict the input signal. First, computational difficulties related to updating the autocorrelation matrix inverse could arise, since no unique least-squares solution exists. Second, the predictor strives to remove very low-level components in the input, and hence could implement a gain function that is essentially zero over the entire passband. The predictor would then tend to become a no-pass filter which is undesirable in certain applications, e.g., intrusion detection (SAND--78-1032). Modifications to the SER algorithm that overcome the above problems are presented, which enable its use for long-term signal processing applications. 3 figures.

  20. 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. PMID:16902133

  1. Verifying the secure setup of Unix client/servers and detection of network intrusion

    SciTech Connect

    Feingold, R.; Bruestle, H.R.; Bartoletti, T.; Saroyan, A.; Fisher, J.

    1995-07-01

    This paper describes our technical approach to developing and delivering Unix host- and network-based security products to meet the increasing challenges in information security. Today`s global ``Infosphere`` presents us with a networked environment that knows no geographical, national, or temporal boundaries, and no ownership, laws, or identity cards. This seamless aggregation of computers, networks, databases, applications, and the like store, transmit, and process information. This information is now recognized as an asset to governments, corporations, and individuals alike. This information must be protected from misuse. The Security Profile Inspector (SPI) performs static analyses of Unix-based clients and servers to check on their security configuration. SPI`s broad range of security tests and flexible usage options support the needs of novice and expert system administrators alike. SPI`s use within the Department of Energy and Department of Defense has resulted in more secure systems, less vulnerable to hostile intentions. Host-based information protection techniques and tools must also be supported by network-based capabilities. Our experience shows that a weak link in a network of clients and servers presents itself sooner or later, and can be more readily identified by dynamic intrusion detection techniques and tools. The Network Intrusion Detector (NID) is one such tool. NID is designed to monitor and analyze activity on an Ethernet broadcast Local Area Network segment and produce transcripts of suspicious user connections. NID`s retrospective and real-time modes have proven invaluable to security officers faced with ongoing attacks to their systems and networks.

  2. 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.

  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. PMID:27285146

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

    PubMed Central

    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. PMID:27285146

  5. 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.

  6. 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.

  7. Agent-Based Literacy Theory

    ERIC Educational Resources Information Center

    McEneaney, John E.

    2006-01-01

    The purpose of this theoretical essay is to explore the limits of traditional conceptualizations of reader and text and to propose a more general theory based on the concept of a literacy agent. The proposed theoretical perspective subsumes concepts from traditional theory and aims to account for literacy online. The agent-based literacy theory…

  8. 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

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

    PubMed

    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

  10. Non-intrusive rattle noise detection in non-stationary conditions by an angle/time cyclostationary approach

    NASA Astrophysics Data System (ADS)

    Baudin, Sophie; Rémond, Didier; Antoni, Jérôme; Sauvage, Olivier

    2016-03-01

    This work proposes an original non-intrusive approach to detect and quantify rattle noise in automotive gearboxes operating under non-stationary conditions by means of vibration or instantaneous angular speed measurements. Rattle noise is produced by vibro impacts between teeth of unloaded gears excited by the engine acyclism. It appears during acceleration or deceleration phases and its detection requires the analysis of non-stationary signals. In order to take advantage of the repetitive nature of the impacts, an angle/time cyclostationary approach is introduced. Rattle noise is thus characterized through the angle/time duality: the cyclic frequency expressed in events per revolution is directly linked to the periodicity of the impacts while their frequency content is expressed in Hertz. The proposed detection method uses an order/frequency spectral coherence and may be applied either on vibration signals or instantaneous angular speed signals. For validation purposes, a specific instrumentation of a gearbox is set up. The relative speed of the unloaded meshing gears is observed by means of optical encoders to directly detect the instants of impact which then serve as a basis for validation of the non-intrusive detection method proposed in this paper.

  11. 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

  12. 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

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

    PubMed

    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. 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

  15. A Choline Oxidase Amperometric Bioassay for the Detection of Mustard Agents Based on Screen-Printed Electrodes Modified with Prussian Blue Nanoparticles

    PubMed Central

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

    2015-01-01

    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. PMID:25688587

  16. 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

  17. A Non-Intrusive Pressure Sensor by Detecting Multiple Longitudinal Waves

    PubMed Central

    Zhou, Hongliang; Lin, Weibin; Ge, Xiaocheng; Zhou, Jian

    2016-01-01

    Pressure vessels are widely used in industrial fields, and some of them are safety-critical components in the system—for example, those which contain flammable or explosive material. Therefore, the pressure of these vessels becomes one of the critical measurements for operational management. In the paper, we introduce a new approach to the design of non-intrusive pressure sensors, based on ultrasonic waves. The model of this sensor is built based upon the travel-time change of the critically refracted longitudinal wave (LCR wave) and the reflected longitudinal waves with the pressure. To evaluate the model, experiments are carried out to compare the proposed model with other existing models. The results show that the proposed model can improve the accuracy compared to models based on a single wave. PMID:27527183

  18. A Non-Intrusive Pressure Sensor by Detecting Multiple Longitudinal Waves.

    PubMed

    Zhou, Hongliang; Lin, Weibin; Ge, Xiaocheng; Zhou, Jian

    2016-01-01

    Pressure vessels are widely used in industrial fields, and some of them are safety-critical components in the system-for example, those which contain flammable or explosive material. Therefore, the pressure of these vessels becomes one of the critical measurements for operational management. In the paper, we introduce a new approach to the design of non-intrusive pressure sensors, based on ultrasonic waves. The model of this sensor is built based upon the travel-time change of the critically refracted longitudinal wave (LCR wave) and the reflected longitudinal waves with the pressure. To evaluate the model, experiments are carried out to compare the proposed model with other existing models. The results show that the proposed model can improve the accuracy compared to models based on a single wave. PMID:27527183

  19. A Non-Intrusive Pressure Sensor by Detecting Multiple Longitudinal Waves.

    PubMed

    Zhou, Hongliang; Lin, Weibin; Ge, Xiaocheng; Zhou, Jian

    2016-08-05

    Pressure vessels are widely used in industrial fields, and some of them are safety-critical components in the system-for example, those which contain flammable or explosive material. Therefore, the pressure of these vessels becomes one of the critical measurements for operational management. In the paper, we introduce a new approach to the design of non-intrusive pressure sensors, based on ultrasonic waves. The model of this sensor is built based upon the travel-time change of the critically refracted longitudinal wave (LCR wave) and the reflected longitudinal waves with the pressure. To evaluate the model, experiments are carried out to compare the proposed model with other existing models. The results show that the proposed model can improve the accuracy compared to models based on a single wave.

  20. 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.

  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. 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

  3. Detection of ethene and other hydrocarbons in gas turbine engine exhaust using non-intrusive FTIR spectroscopy

    NASA Astrophysics Data System (ADS)

    Arrigone, Giovanni M.; Welch, Michael A.; Hilton, Moira; Miller, Michael N.; Wilson, Christopher W.

    2003-04-01

    As part of the EU funded project AEROJET2, a number of gas turbine engine tests were performed in different facilities around Europe. At Farnborough, UK a Spey engine was used to test a suite of prototype optically based instrumentation designed to measure exhaust gas emissions without using extractive probe systems. In addition to the AEROJET 2 prototype instrumentation, a Bruker Equinox 55 Fourier transform infrared (FTIR) spectrometer was used to obtain infrared spectra of the exhaust plume both in emission and absorption mode. The Bruker FTIR spectrometer was fitted with a periscope system so that different lines of sight could be monitored in the plume in a vertical plane 25 cm downstream from the nozzle exit and 20 cm upstream of the center line of sight of the AEROJET 2 prototype instrumentation. DERA (now QinetiQ) provided exhaust gas analysis data for different engine running conditions using samples extracted from the plume with an intrusive probe. The probe sampled along a horizontal plane across the centerline of the engine 45 cm downstream of the nozzle exit. The Bruker spectrometer used both InSb (indium antimonide) and MCT (mercury-cadmium-telluride) detectors to maximize the sensitivity across the IR range 600-4000 cm-1. Typically, CO2 and H2O IR signatures dominate the observed spectra of the plume. However, the engine tests showed that at low power engine conditions spectral features associated with CO around 2147 cm-1 and with hydrocarbons could be observed at around 3000 cm-1. In particular the presence of ethene (C2H2) was detected from observation of its characteristic in and out of plane vibration mode at 949 cm-1. At high engine powers the presence of NO was detected at 1900.3 cm-1. Species concentrations were calculated using a slab model for each line of sight compared against reference spectra. The engine plume was assumed to be symmetric about the centerline. On this basis, data from the extractive sampling gas analysis that had been

  4. 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

  5. An improved real time image detection system for elephant intrusion along the forest border areas.

    PubMed

    Sugumar, S J; Jayaparvathy, R

    2014-01-01

    Human-elephant conflict is a major problem leading to crop damage, human death and injuries caused by elephants, and elephants being killed by humans. In this paper, we propose an automated unsupervised elephant image detection system (EIDS) as a solution to human-elephant conflict in the context of elephant conservation. The elephant's image is captured in the forest border areas and is sent to a base station via an RF network. The received image is decomposed using Haar wavelet to obtain multilevel wavelet coefficients, with which we perform image feature extraction and similarity match between the elephant query image and the database image using image vision algorithms. A GSM message is sent to the forest officials indicating that an elephant has been detected in the forest border and is approaching human habitat. We propose an optimized distance metric to improve the image retrieval time from the database. We compare the optimized distance metric with the popular Euclidean and Manhattan distance methods. The proposed optimized distance metric retrieves more images with lesser retrieval time than the other distance metrics which makes the optimized distance method more efficient and reliable.

  6. An Improved Real Time Image Detection System for Elephant Intrusion along the Forest Border Areas

    PubMed Central

    Sugumar, S. J.; Jayaparvathy, R.

    2014-01-01

    Human-elephant conflict is a major problem leading to crop damage, human death and injuries caused by elephants, and elephants being killed by humans. In this paper, we propose an automated unsupervised elephant image detection system (EIDS) as a solution to human-elephant conflict in the context of elephant conservation. The elephant's image is captured in the forest border areas and is sent to a base station via an RF network. The received image is decomposed using Haar wavelet to obtain multilevel wavelet coefficients, with which we perform image feature extraction and similarity match between the elephant query image and the database image using image vision algorithms. A GSM message is sent to the forest officials indicating that an elephant has been detected in the forest border and is approaching human habitat. We propose an optimized distance metric to improve the image retrieval time from the database. We compare the optimized distance metric with the popular Euclidean and Manhattan distance methods. The proposed optimized distance metric retrieves more images with lesser retrieval time than the other distance metrics which makes the optimized distance method more efficient and reliable. PMID:24574886

  7. 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.

  8. 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.

  9. 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.

  10. Rapid dike intrusion into Sakurajima volcano on August 15, 2015, as detected by multi-parameter ground deformation observations

    NASA Astrophysics Data System (ADS)

    Hotta, Kohei; Iguchi, Masato; Tameguri, Takeshi

    2016-04-01

    We present observations of ground deformation at Sakurajima in August 2015 and model the deformation using a combination of GNSS, tilt and strain data in order to interpret a rapid deformation event on August 15, 2015. The pattern of horizontal displacement during the period from August 14 to 16, 2015, shows a WNW-ESE extension, which suggests the opening of a dike. Using a genetic algorithm, we obtained the position, dip, strike length, width and opening of a dislocation source based on the combined data. A nearly vertical dike with a NNE-SSW strike was found at a depth of 1.0 km below sea level beneath the Showa crater. The length and width are 2.3 and 0.6 km, respectively, and a dike opening of 1.97 m yields a volume increase of 2.7 × 106 m3. 887 volcano-tectonic (VT) earthquakes beside the dike suggest that the rapid opening of the dike caused an accumulation of strain in the surrounding rocks, and the VT earthquakes were generated to release this strain. Half of the total amount of deformation was concentrated between 10:27 and 11:54 on August 15. It is estimated that the magma intrusion rate was 1 × 106 m3/h during this period. This is 200 times larger than the magma intrusion rate prior to one of the biggest eruptions at the summit crater of Minami-dake on July 24, 2012, and 2200 times larger than the average magma intrusion rate during the period from October 2011 to March 2012. The previous Mogi-type ground deformation is considered to be a process of magma accumulation in preexisting spherical reservoirs. Conversely, the August 2015 event was a dike intrusion and occurred in a different location to the preexisting reservoirs. The direction of the opening of the dike coincides with the T-axes and direction of faults creating a graben structure.

  11. 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.

  12. 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

  13. Agent Based Modeling as an Educational Tool

    NASA Astrophysics Data System (ADS)

    Fuller, J. H.; Johnson, R.; Castillo, V.

    2012-12-01

    Motivation is a key element in high school education. One way to improve motivation and provide content, while helping address critical thinking and problem solving skills, is to have students build and study agent based models in the classroom. This activity visually connects concepts with their applied mathematical representation. "Engaging students in constructing models may provide a bridge between frequently disconnected conceptual and mathematical forms of knowledge." (Levy and Wilensky, 2011) We wanted to discover the feasibility of implementing a model based curriculum in the classroom given current and anticipated core and content standards.; Simulation using California GIS data ; Simulation of high school student lunch popularity using aerial photograph on top of terrain value map.

  14. 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.

  15. 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

  16. 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.

  17. 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...

  18. 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 ...

  19. 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

  20. 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.

  1. 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…

  2. Exploring cooperation and competition using agent-based modeling

    PubMed Central

    Elliott, Euel; Kiel, L. Douglas

    2002-01-01

    Agent-based modeling enhances our capacity to model competitive and cooperative behaviors at both the individual and group levels of analysis. Models presented in these proceedings produce consistent results regarding the relative fragility of cooperative regimes among agents operating under diverse rules. These studies also show how competition and cooperation may generate change at both the group and societal level. Agent-based simulation of competitive and cooperative behaviors may reveal the greatest payoff to social science research of all agent-based modeling efforts because of the need to better understand the dynamics of these behaviors in an increasingly interconnected world. PMID:12011396

  3. 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

  4. 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.

  5. 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.

  6. 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)

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Simulating Cancer Growth with Multiscale Agent-Based Modeling

    PubMed Central

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

    2014-01-01

    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. PMID:24793698

  12. Scanning Seismic Intrusion Detector

    NASA Technical Reports Server (NTRS)

    Lee, R. D.

    1982-01-01

    Scanning seismic intrusion detector employs array of automatically or manually scanned sensors to determine approximate location of intruder. Automatic-scanning feature enables one operator to tend system of many sensors. Typical sensors used with new system are moving-coil seismic pickups. Detector finds uses in industrial security systems.

  13. Intrusive STM imaging

    NASA Astrophysics Data System (ADS)

    Boulanger-Lewandowski, Nicolas; Rochefort, Alain

    2011-03-01

    An interactive scanning tunneling microscopy (STM) simulator has been designed to efficiently compute the effects of chemical and structural modifications of adsorbed species on resulting STM images. Our general approach is based on first-order perturbation theory that takes into account different tip geometries. In our intrusive STM imaging strategy, we consider small variations such as substitutions, vacancies, functionalizations, and molecular reorganizations from a reference system. First, we show that our perturbation theory approach can provide STM images that are qualitatively similar to those of a more rigorous electron scattering technique based on the Landauer-Büttiker formalism for the case of adsorbed tetracyanoethylene on a Cu(100) single crystal. Second, we demonstrate that the efficiency of Bardeen and Tersoff-Hamann approaches to generate STM images can be substantially improved by exploiting different algorithms to evaluate the tunnel current and to deal with large-scale eigenvalue problems. Following our general intrusive strategy, we have reduced the computing time to generate an STM image of a modified system by about an order of magnitude with respect to the reference image. The shape and position of the contrasts of the STM image evaluated in the context of intrusion are virtually identical to an image computed without intrusive features but within a considerably smaller computing time.

  14. Intrusion tolerant model for spatial information networks based on defense-in-depth

    NASA Astrophysics Data System (ADS)

    Zhang, Juan; Qin, Zhihong; Wang, Junfeng

    2009-12-01

    The spatial information networks (SIN) plays a more and more important role in current communication networks, while its security problem is rigorous. To enhance the information survivability, based on the concept of defense-in-depth, this paper proposes an intrusion tolerant (IT) model which can be applied in SIN, analyzes it in detail on three-tier of intrusion defense, intrusion detection and intrusion tolerant. And some suggestions are made for each tier.

  15. 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

  16. 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

  17. Investigating biocomplexity through the agent-based paradigm.

    PubMed

    Kaul, Himanshu; Ventikos, Yiannis

    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.

  18. 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.

  19. 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.

  20. 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

  1. Agent-based models in robotized manufacturing cells designing

    NASA Astrophysics Data System (ADS)

    Sekala, A.; Gwiazda, A.; Foit, K.; Banas, W.; Hryniewicz, P.; Kost, G.

    2015-11-01

    The complexity of the components, presented in robotized manufacturing workcells, causes that already at the design phase is necessary to develop models presenting various aspects of their structure and functioning. These models are simplified representation of real systems and allow to, among others, systematize knowledge about the designed manufacturing workcell. They also facilitate defining and analyzing the interrelationships between its particular components. This paper proposes the agent-based approach applied for designing robotized manufacturing cells.

  2. 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.

  3. Agent-based modeling and simulation Part 3 : desktop ABMS.

    SciTech Connect

    Macal, C. M.; North, M. J.; Decision and Information Sciences

    2007-01-01

    Agent-based modeling and simulation (ABMS) is a new approach to modeling systems comprised of autonomous, interacting agents. ABMS promises to have far-reaching effects on the way that businesses use computers to support decision-making and researchers use electronic laboratories to support their research. Some have gone so far as to contend that ABMS 'is a third way of doing science,' in addition to traditional deductive and inductive reasoning (Axelrod 1997b). Computational advances have made possible a growing number of agent-based models across a variety of application domains. Applications range from modeling agent behavior in the stock market, supply chains, and consumer markets, to predicting the spread of epidemics, the threat of bio-warfare, and the factors responsible for the fall of ancient civilizations. This tutorial describes the theoretical and practical foundations of ABMS, identifies toolkits and methods for developing agent models, and illustrates the development of a simple agent-based model of shopper behavior using spreadsheets.

  4. Interactive agent based modeling of public health decision-making.

    PubMed

    Parks, Amanda L; Walker, Brett; Pettey, Warren; Benuzillo, Jose; Gesteland, Per; Grant, Juliana; Koopman, James; Drews, Frank; Samore, Matthew

    2009-01-01

    Agent-based models have yielded important insights regarding the transmission dynamics of communicable diseases. To better understand how these models can be used to study decision making of public health officials, we developed a computer program that linked an agent-based model of pertussis with an agent-based model of public health management. The program, which we call the Public Health Interactive Model & simulation (PHIMs) encompassed the reporting of cases to public health, case investigation, and public health response. The user directly interacted with the model in the role of the public health decision-maker. In this paper we describe the design of our model, and present the results of a pilot study to assess its usability and potential for future development. Affinity for specific tools was demonstrated. Participants ranked the program high in usability and considered it useful for training. Our ultimate goal is to achieve better public health decisions and outcomes through use of public health decision support tools. PMID:20351907

  5. 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

  6. 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.

  7. Agent-based model of macrophage action on endocrine pancreas.

    PubMed

    Martínez, Ignacio V; Gómez, Enrique J; Hernando, M Elena; Villares, Ricardo; Mellado, Mario

    2012-01-01

    This paper proposes an agent-based model of the action of macrophages on the beta cells of the endocrine pancreas. The aim of this model is to simulate the processes of beta cell proliferation and apoptosis and also the process of phagocytosis of cell debris by macrophages, all of which are related to the onset of the autoimmune response in type 1 diabetes. We have used data from the scientific literature to design the model. The results show that the model obtains good approximations to real processes and could be used to shed light on some open questions concerning such processes.

  8. 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.

  9. 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.

  10. 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.

  11. 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. PMID:27340402

  12. 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.

  13. Strengthening Theoretical Testing in Criminology Using Agent-based Modeling

    PubMed Central

    Groff, Elizabeth R.

    2014-01-01

    Objectives: The Journal of Research in Crime and Delinquency (JRCD) has published important contributions to both criminological theory and associated empirical tests. In this article, we consider some of the challenges associated with traditional approaches to social science research, and discuss a complementary approach that is gaining popularity—agent-based computational modeling—that may offer new opportunities to strengthen theories of crime and develop insights into phenomena of interest. Method: Two literature reviews are completed. The aim of the first is to identify those articles published in JRCD that have been the most influential and to classify the theoretical perspectives taken. The second is intended to identify those studies that have used an agent-based model (ABM) to examine criminological theories and to identify which theories have been explored. Results: Ecological theories of crime pattern formation have received the most attention from researchers using ABMs, but many other criminological theories are amenable to testing using such methods. Conclusion: Traditional methods of theory development and testing suffer from a number of potential issues that a more systematic use of ABMs—not without its own issues—may help to overcome. ABMs should become another method in the criminologists toolbox to aid theory testing and falsification. PMID:25419001

  14. 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.

  15. An agent-based multilayer architecture for bioinformatics grids.

    PubMed

    Bartocci, Ezio; Cacciagrano, Diletta; Cannata, Nicola; Corradini, Flavio; Merelli, Emanuela; Milanesi, Luciano; Romano, Paolo

    2007-06-01

    Due to the huge volume and complexity of biological data available today, a fundamental component of biomedical research is now in silico analysis. This includes modelling and simulation of biological systems and processes, as well as automated bioinformatics analysis of high-throughput data. The quest for bioinformatics resources (including databases, tools, and knowledge) becomes therefore of extreme importance. Bioinformatics itself is in rapid evolution and dedicated Grid cyberinfrastructures already offer easier access and sharing of resources. Furthermore, the concept of the Grid is progressively interleaving with those of Web Services, semantics, and software agents. Agent-based systems can play a key role in learning, planning, interaction, and coordination. Agents constitute also a natural paradigm to engineer simulations of complex systems like the molecular ones. We present here an agent-based, multilayer architecture for bioinformatics Grids. It is intended to support both the execution of complex in silico experiments and the simulation of biological systems. In the architecture a pivotal role is assigned to an "alive" semantic index of resources, which is also expected to facilitate users' awareness of the bioinformatics domain.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. Agent-based Bayesian approach to monitoring the progress of invasive species eradication programs

    PubMed Central

    Keith, Jonathan M.; Spring, Daniel

    2013-01-01

    Eradication of an invasive species can provide significant environmental, economic, and social benefits, but eradication programs often fail. Constant and careful monitoring improves the chance of success, but an invasion may seem to be in decline even when it is expanding in abundance or spatial extent. Determining whether an invasion is in decline is a challenging inference problem for two reasons. First, it is typically infeasible to regularly survey the entire infested region owing to high cost. Second, surveillance methods are imperfect and fail to detect some individuals. These two factors also make it difficult to determine why an eradication program is failing. Agent-based methods enable inferences to be made about the locations of undiscovered individuals over time to identify trends in invader abundance and spatial extent. We develop an agent-based Bayesian method and apply it to Australia’s largest eradication program: the campaign to eradicate the red imported fire ant (Solenopsis invicta) from Brisbane. The invasion was deemed to be almost eradicated in 2004 but our analyses indicate that its geographic range continued to expand despite a sharp decline in number of nests. We also show that eradication would probably have been achieved with a relatively small increase in the area searched and treated. Our results demonstrate the importance of inferring temporal and spatial trends in ongoing invasions. The method can handle incomplete observations and takes into account the effects of human intervention. It has the potential to transform eradication practices. PMID:23878210

  6. 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.

  7. 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.

  8. Human intrusion in geologic disposal

    SciTech Connect

    Not Available

    1993-12-31

    This report discusses the possibility of human intrusion into the WIPP facility, an undergound disposal facility for alpha-bearing wastes. The probability of exploratory drilling occurring at the site is described.

  9. 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

  10. 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

  11. 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.

  12. Patient-centered appointment scheduling using agent-based simulation.

    PubMed

    Turkcan, Ayten; Toscos, Tammy; Doebbeling, Brad N

    2014-01-01

    Enhanced access and continuity are key components of patient-centered care. Existing studies show that several interventions such as providing same day appointments, walk-in services, after-hours care, and group appointments, have been used to redesign the healthcare systems for improved access to primary care. However, an intervention focusing on a single component of care delivery (i.e. improving access to acute care) might have a negative impact other components of the system (i.e. reduced continuity of care for chronic patients). Therefore, primary care clinics should consider implementing multiple interventions tailored for their patient population needs. We collected rapid ethnography and observations to better understand clinic workflow and key constraints. We then developed an agent-based simulation model that includes all access modalities (appointments, walk-ins, and after-hours access), incorporate resources and key constraints and determine the best appointment scheduling method that improves access and continuity of care. This paper demonstrates the value of simulation models to test a variety of alternative strategies to improve access to care through scheduling. PMID:25954423

  13. 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

  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. 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.

  17. Endogenizing geopolitical boundaries with agent-based modeling

    PubMed Central

    Cederman, Lars-Erik

    2002-01-01

    Agent-based modeling promises to overcome the reification of actors. Whereas this common, but limiting, assumption makes a lot of sense during periods characterized by stable actor boundaries, other historical junctures, such as the end of the Cold War, exhibit far-reaching and swift transformations of actors' spatial and organizational existence. Moreover, because actors cannot be assumed to remain constant in the long run, analysis of macrohistorical processes virtually always requires “sociational” endogenization. This paper presents a series of computational models, implemented with the software package REPAST, which trace complex macrohistorical transformations of actors be they hierarchically organized as relational networks or as collections of symbolic categories. With respect to the former, dynamic networks featuring emergent compound actors with agent compartments represented in a spatial grid capture organizational domination of the territorial state. In addition, models of “tagged” social processes allows the analyst to show how democratic states predicate their behavior on categorical traits. Finally, categorical schemata that select out politically relevant cultural traits in ethnic landscapes formalize a constructivist notion of national identity in conformance with the qualitative literature on nationalism. This “finite-agent method”, representing both states and nations as higher-level structures superimposed on a lower-level grid of primitive agents or cultural traits, avoids reification of agency. Furthermore, it opens the door to explicit analysis of entity processes, such as the integration and disintegration of actors as well as boundary transformations. PMID:12011409

  18. Agent-Based Modeling and Simulation on Emergency Evacuation

    NASA Astrophysics Data System (ADS)

    Ren, Chuanjun; Yang, Chenghui; Jin, Shiyao

    Crowd stampedes and evacuation induced by panic caused by emergences often lead to fatalities as people are crushed, injured, trampled or even dead. Such phenomena may be triggered in life-threatening situations such as fires, explosions in crowded buildings. Emergency evacuation simulation has recently attracted the interest of a rapidly increasing number of scientists. This paper presents an Agent-Based Modeling and Simulation using Repast software to construct crowd evacuations for emergency response from an area under a fire. Various types of agents and different attributes of agents are designed in contrast to traditional modeling. The attributes that govern the characteristics of the people are studied and tested by iterative simulations. Simulations are also conducted to demonstrate the effect of various parameters of agents. Some interesting results were observed such as "faster is slower" and the ignorance of available exits. At last, simulation results suggest practical ways of minimizing the harmful consequences of such events and the existence of an optimal escape strategy.

  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. 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. PMID:27152214

  1. 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. PMID:25945790

  2. 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.

  3. An agent-based mathematical model about carp aggregation

    NASA Astrophysics Data System (ADS)

    Liang, Yu; Wu, Chao

    2005-05-01

    This work presents an agent-based mathematical model to simulate the aggregation of carp, a harmful fish in North America. The referred mathematical model is derived from the following assumptions: (1) instead of the consensus among every carps involved in the aggregation, the aggregation of carp is completely a random and spontaneous physical behavior of numerous of independent carp; (2) carp aggregation is a collective effect of inter-carp and carp-environment interaction; (3) the inter-carp interaction can be derived from the statistical analytics about large-scale observed data. The proposed mathematical model is mainly based on empirical inter-carp force field, whose effect is featured with repulsion, parallel orientation, attraction, out-of-perception zone, and blind. Based on above mathematical model, the aggregation behavior of carp is formulated and preliminary simulation results about the aggregation of small number of carps within simple environment are provided. Further experiment-based validation about the mathematical model will be made in our future work.

  4. 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

  5. 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.

  6. 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…

  7. 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…

  8. 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).…

  9. 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…

  10. 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

    2016-01-01

    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

  11. 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

  12. 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.

  13. 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.

  14. The agent-based spatial information semantic grid

    NASA Astrophysics Data System (ADS)

    Cui, Wei; Zhu, YaQiong; Zhou, Yong; Li, Deren

    2006-10-01

    Analyzing the characteristic of multi-Agent and geographic Ontology, The concept of the Agent-based Spatial Information Semantic Grid (ASISG) is defined and the architecture of the ASISG is advanced. ASISG is composed with Multi-Agents and geographic Ontology. The Multi-Agent Systems are composed with User Agents, General Ontology Agent, Geo-Agents, Broker Agents, Resource Agents, Spatial Data Analysis Agents, Spatial Data Access Agents, Task Execution Agent and Monitor Agent. The architecture of ASISG have three layers, they are the fabric layer, the grid management layer and the application layer. The fabric layer what is composed with Data Access Agent, Resource Agent and Geo-Agent encapsulates the data of spatial information system so that exhibits a conceptual interface for the Grid management layer. The Grid management layer, which is composed with General Ontology Agent, Task Execution Agent and Monitor Agent and Data Analysis Agent, used a hybrid method to manage all resources that were registered in a General Ontology Agent that is described by a General Ontology System. The hybrid method is assembled by resource dissemination and resource discovery. The resource dissemination push resource from Local Ontology Agent to General Ontology Agent and the resource discovery pull resource from the General Ontology Agent to Local Ontology Agents. The Local Ontology Agent is derived from special domain and describes the semantic information of local GIS. The nature of the Local Ontology Agents can be filtrated to construct a virtual organization what could provides a global scheme. The virtual organization lightens the burdens of guests because they need not search information site by site manually. The application layer what is composed with User Agent, Geo-Agent and Task Execution Agent can apply a corresponding interface to a domain user. The functions that ASISG should provide are: 1) It integrates different spatial information systems on the semantic The Grid

  15. Adaptive Intrusion Data System (AIDS)

    SciTech Connect

    Corlis, N. E.

    1980-05-01

    The adaptive intrusion data system (AIDS) was developed to collect data from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique data system which uses computer controlled data systems, video cameras and recorders, analog-to-digital conversion, environmental sensors, and digital recorders to collect sensor data. The data can be viewed either manually or with a special computerized data-reduction system which adds new data to a data base stored on a magnetic disc recorder. This report provides a synoptic account of the AIDS as it presently exists. Modifications to the purchased subsystems are described, and references are made to publications which describe the Sandia-designed subsystems.

  16. 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.

  17. De Novo Designed Imaging Agents Based on Lanthanide Peptides Complexes.

    PubMed

    Peacock, A F A

    2016-01-01

    Herein are discussed a selection of lanthanide peptide/protein complexes in view of their potential applications as imaging agents, both in terms of luminescence detection and magnetic resonance imaging. Though this chapter covers a range of different peptides and protein, if focuses specifically on the opportunities afforded by the de novo design of coiled coils, miniature protein scaffolds, and the development on lanthanide-binding sites into these architectures. The requirements for lanthanide coordination and the challenges that need to be addressed when preparing lanthanide peptides with a view to their potential adoption as clinical imaging applications, will be highlighted. PMID:27586349

  18. An Agent-Based Approach to Care in Independent Living

    NASA Astrophysics Data System (ADS)

    Kaluža, Boštjan; Mirchevska, Violeta; Dovgan, Erik; Luštrek, Mitja; Gams, Matjaž

    This paper presents a multi-agent system for the care of elderly people living at home on their own, with the aim to prolong their independence. The system is composed of seven groups of agents providing a reliable, robust and flexible monitoring by sensing the user in the environment, reconstructing the position and posture to create the physical awareness of the user in the environment, reacting to critical situations, calling for help in the case of an emergency, and issuing warnings if unusual behavior is detected. The system has been tested during several on-line demonstrations.

  19. 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.

  20. Dynamics of bloggers’ communities: Bipartite networks from empirical data and agent-based modeling

    NASA Astrophysics Data System (ADS)

    Mitrović, Marija; Tadić, Bosiljka

    2012-11-01

    We present an analysis of the empirical data and the agent-based modeling of the emotional behavior of users on the Web portals where the user interaction is mediated by posted comments, like Blogs and Diggs. We consider the dataset of discussion-driven popular Diggs, in which all comments are screened by machine-learning emotion detection in the text, to determine positive and negative valence (attractiveness and aversiveness) of each comment. By mapping the data onto a suitable bipartite network, we perform an analysis of the network topology and the related time-series of the emotional comments. The agent-based model is then introduced to simulate the dynamics and to capture the emergence of the emotional behaviors and communities. The agents are linked to posts on a bipartite network, whose structure evolves through their actions on the posts. The emotional states (arousal and valence) of each agent fluctuate in time, subject to the current contents of the posts to which the agent is exposed. By an agent’s action on a post its current emotions are transferred to the post. The model rules and the key parameters are inferred from the considered empirical data to ensure their realistic values and mutual consistency. The model assumes that the emotional arousal over posts drives the agent’s action. The simulations are preformed for the case of constant flux of agents and the results are analyzed in full analogy with the empirical data. The main conclusions are that the emotion-driven dynamics leads to long-range temporal correlations and emergent networks with community structure, that are comparable with the ones in the empirical system of popular posts. In view of pure emotion-driven agents actions, this type of comparisons provide a quantitative measure for the role of emotions in the dynamics on real blogs. Furthermore, the model reveals the underlying mechanisms which relate the post popularity with the emotion dynamics and the prevalence of negative

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. Intrusion signature creation via clustering anomalies

    NASA Astrophysics Data System (ADS)

    Hendry, Gilbert R.; Yang, Shanchieh J.

    2008-03-01

    Current practices for combating cyber attacks typically use Intrusion Detection Systems (IDSs) to detect and block multistage attacks. Because of the speed and impacts of new types of cyber attacks, current IDSs are limited in providing accurate detection while reliably adapting to new attacks. In signature-based IDS systems, this limitation is made apparent by the latency from day zero of an attack to the creation of an appropriate signature. This work hypothesizes that this latency can be shortened by creating signatures via anomaly-based algorithms. A hybrid supervised and unsupervised clustering algorithm is proposed for new signature creation. These new signatures created in real-time would take effect immediately, ideally detecting new attacks. This work first investigates a modified density-based clustering algorithm as an IDS, with its strengths and weaknesses identified. A signature creation algorithm leveraging the summarizing abilities of clustering is investigated. Lessons learned from the supervised signature creation are then leveraged for the development of unsupervised real-time signature classification. Automating signature creation and classification via clustering is demonstrated as satisfactory but with limitations.

  6. Saline and particle-driven interfacial intrusions

    NASA Astrophysics Data System (ADS)

    de Rooij, Frans; Linden, P. F.; Dalziel, Stuart B.

    1999-06-01

    This paper presents a theoretical and experimental investigation into saline and particle-driven intrusions along the interface between two layers of different densities. The conditions at the nose of an intrusion are described in an analysis similar to that applied by Benjamin (1968) to boundary gravity currents. Equations for propagation velocity and front position as functions of relative density are derived. These are used in an integral model for intrusions, which also includes the effects of sedimentation of particles and detrainment of interstitial fluid. The model describes the time-evolution of the length of the intrusion and the sediment distribution it produces. Laboratory experiments were carried out with lock-releases of a fixed volume of saline or particle-laden fluid into a two-layer stratification. Measurements were taken of the intrusion propagation, intrusion position and sediment distribution, and are found to be in good agreement with the solutions of the integral model.

  7. 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. PMID:27347649

  8. 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.

  9. 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.

  10. 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

  11. Intrusive images and intrusive thoughts as different phenomena: two experimental studies.

    PubMed

    Hagenaars, Muriel A; Brewin, Chris R; van Minnen, Agnes; Holmes, Emily A; Hoogduin, Kees A L

    2010-01-01

    According to the dual representation theory of PTSD, intrusive trauma images and intrusive verbal thoughts are produced by separate memory systems. In a previous article it was shown that after watching an aversive film, participants in non-movement conditions reported more intrusive images than participants in a free-to-move control condition (Hagenaars, Van Minnen, Holmes, Brewin, & Hoogduin, 2008). The present study investigates whether the experimental conditions of the Hagenaars et al. study had a different effect on intrusive thoughts than on intrusive images. Experiment 2 further investigated the image-thoughts distinction by manipulating stimulus valence (trauma film versus neutral film) and assessing the subsequent development of intrusive images and thoughts. In addition, both experiments studied the impact of peri-traumatic emotions on subsequent intrusive images and thoughts frequency across conditions. Results showed that experimental manipulations (non-movement and trauma film) caused higher levels of intrusive images relative to control conditions (free movement and neutral film) but they did not affect intrusive thoughts. Peri-traumatic anxiety and horror were associated with subsequent higher levels of intrusive images, but not intrusive thoughts. Correlations were inconclusive for anger and sadness. The results suggest intrusive images and thoughts can be manipulated independently and as such can be considered different phenomena. PMID:20391178

  12. 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.

  13. 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.

  14. 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. PMID:25683347

  15. 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

  16. 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

  17. 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.

  18. 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.

  19. Magmatic intrusions and hydrothermal systems

    NASA Astrophysics Data System (ADS)

    Gulick, Virginia Claire

    1993-01-01

    This dissertation investigates the possible role of hydrothermally driven ground-water outflow in the formation of fluvial valleys on Mars. Although these landforms have often been cited as evidence for a past warmer climate and denser atmosphere, recent theoretical modeling precludes such climatic conditions on early Mars when most fluvial valleys formed. Because fluvial valleys continued to form throughout Mars' geological history and the most Earth-like stream valleys on Mars formed well after the decline of the early putative Earth-like climate, it may be unnecessary to invoke drastically different climatic conditions for the formation of the earliest stream valleys. The morphology of most Martian fluvial valleys indicates formation by ground-water sapping which is consistent with a subsurface origin. Additionally, many Martian fluvial valleys formed on volcanoes, impact craters, near fractures, or adjacent to terrains interpreted as igneous intrusions; all are possible locales of vigorous, geologically long-lived hydrothermal circulation. Comparison of Martian valley morphology to similar features on Earth constrains valley genesis scenarios. Volumes of measured Martian fluvial valleys range from 1010 to 1013 m3. Based on terrestrial analogs, total water volumes required to erode these valleys range from approximately 1010 to 1015 m3. The clustered distribution of Martian valleys within a given terrain type, the sapping dominated morphology, and the general lack of associated runoff valleys all indicate the importance of localized ground-water outflow in the formation of these fluvial systems. An analytic model of a conductively cooling cylindrical intrusion is coupled with the U.S. Geological Survey's numerical ground-water computer code SUTRA to evaluate the magnitude of ground-water outflow expected from magmatically-driven hydrothermal systems on Mars. Results indicate that magmatic intrusions of several 102 km3 or larger can provide sufficient ground

  20. 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.

  1. 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

  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 mental…

  3. Reduction of Attrition Through Intrusive Advising.

    ERIC Educational Resources Information Center

    Glennen, Robert E.; Baxley, Dan M.

    1985-01-01

    Examines the effects of an intrusive advising program on the attrition rate of college freshmen and sophomores. Identifies reasons students drop out and outlines an advising program used at Western New Mexico University. Results showed the intrusive advising program to be effective in reducing attrition rates. (BH)

  4. Emotional and Behavioral Reaction to Intrusive Thoughts

    ERIC Educational Resources Information Center

    Berry, Lisa-Marie; May, Jon; Andrade, Jackie; Kavanagh, David

    2010-01-01

    A self-report measure of the emotional and behavioral reactions to intrusive thoughts was developed. The article presents data that confirm the stability, reliability, and validity of the new seven-item measure. Emotional and behavioral reactions to intrusions emerged as separate factors on the Emotional and Behavioral Reactions to Intrusions…

  5. 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...

  6. 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.

  7. 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.

  8. 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.

  9. 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. PMID:27044046

  10. 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

  11. 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.

  12. Hybrid Intrusion Forecasting Framework for Early Warning System

    NASA Astrophysics Data System (ADS)

    Kim, Sehun; Shin, Seong-Jun; Kim, Hyunwoo; Kwon, Ki Hoon; Han, Younggoo

    Recently, cyber attacks have become a serious hindrance to the stability of Internet. These attacks exploit interconnectivity of networks, propagate in an instant, and have become more sophisticated and evolutionary. Traditional Internet security systems such as firewalls, IDS and IPS are limited in terms of detecting recent cyber attacks in advance as these systems respond to Internet attacks only after the attacks inflict serious damage. In this paper, we propose a hybrid intrusion forecasting system framework for an early warning system. The proposed system utilizes three types of forecasting methods: time-series analysis, probabilistic modeling, and data mining method. By combining these methods, it is possible to take advantage of the forecasting technique of each while overcoming their drawbacks. Experimental results show that the hybrid intrusion forecasting method outperforms each of three forecasting methods.

  13. Intrusion-Tolerant Location Information Services in Intelligent Vehicular Networks

    NASA Astrophysics Data System (ADS)

    Yan, Gongjun; Yang, Weiming; Shaner, Earl F.; Rawat, Danda B.

    Intelligent Vehicular Networks, known as Vehicle-to-Vehicle and Vehicle-to-Roadside wireless communications (also called Vehicular Ad hoc Networks), are revolutionizing our daily driving with better safety and more infortainment. Most, if not all, applications will depend on accurate location information. Thus, it is of importance to provide intrusion-tolerant location information services. In this paper, we describe an adaptive algorithm that detects and filters the false location information injected by intruders. Given a noisy environment of mobile vehicles, the algorithm estimates the high resolution location of a vehicle by refining low resolution location input. We also investigate results of simulations and evaluate the quality of the intrusion-tolerant location service.

  14. 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…

  15. 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. PMID:27372059

  16. 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.

  17. 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…

  18. 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.

  19. 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…

  20. 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…

  1. 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…

  2. Formalizing the Role of Agent-Based Modeling in Causal Inference and Epidemiology

    PubMed Central

    Marshall, Brandon D. L.; Galea, Sandro

    2015-01-01

    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. PMID:25480821

  3. 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…

  4. 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…

  5. 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…

  6. Self-report may underestimate trauma intrusions.

    PubMed

    Takarangi, Melanie K T; Strange, Deryn; Lindsay, D Stephen

    2014-07-01

    Research examining maladaptive responses to trauma routinely relies on spontaneous self-report to index intrusive thoughts, which assumes people accurately recognize and report their intrusive thoughts. However, "mind-wandering" research reveals people are not always meta-aware of their thought content: they often fail to notice shifts in their attention. In two experiments, we exposed subjects to trauma films, then instructed them to report intrusive thoughts during an unrelated reading task. Intermittently, we asked whether they were thinking about the trauma. As expected, subjects often spontaneously reported intrusive thoughts. However, they were also "caught" engaging in unreported trauma-oriented thoughts. The presence and frequency of intermittent probes did not influence self-caught intrusions. Both self-caught and probe-caught intrusions were related to an existing tendency toward intrusive cognition, film-related distress, and thought suppression attempts. Our data suggest people may lack meta-awareness of trauma-related thoughts, which has implications for theory, research and treatment relating to trauma-related psychopathology. PMID:24993526

  7. 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

  8. 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.

  9. [Intrusive care and the nursing approach].

    PubMed

    Bécu, Anays Vaplet; Viltart, Valérie

    2015-04-01

    All caregivers who listen to patients will hear them tell their experience of the intrusive nature of care, whether it be basic, technical, educational or relational. The relational approach implemented by nurses enables them to identify organisational and behavioural methods which favour the establishment of a climate of trust. It helps them appropriate this interdisciplinary approach to caregiving, limiting as much as possible the intrusion felt by the patient during their hospital stay. PMID:26043629

  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, 2013 CFR

    2013-01-01

    ... 10 Energy 2 2013-01-01 2013-01-01 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. 10 CFR 63.322 - Human intrusion scenario.

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 10 Energy 2 2014-01-01 2014-01-01 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...

  13. 10 CFR 63.322 - Human intrusion scenario.

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 10 Energy 2 2012-01-01 2012-01-01 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...

  14. The neural representation of intrusive thoughts

    PubMed Central

    Schmiedek, Florian; Brose, Annette; Schott, Björn H.; Lindenberger, Ulman; Lövden, Martin

    2013-01-01

    Based on the philosophical notion that language embodies thought we investigated whether a habitual tendency for intrusive thought that younger and older participants report over a period of 100 sessions, spread out over about 6 months, is associated with brain regions related to language production. In favour of this hypothesis, we found that individual differences in habitual intrusive thoughts are correlated with activity in the left inferior frontal gyrus (IFG, Broca’s area) as well as the cingulate cortex (CC) during a two-choice reaction-time task in fMRI. Participants who habitually tended to experience intrusive thoughts showed greater activity during task-free (baseline) compared to task periods in brain regions involved in language production. Task performance was unrelated to individual differences in intrusive thoughts. We conclude that intrusive thoughts may be represented in a language-like format and that individuals reporting a habitually higher tendency for intrusive thoughts may have stronger and more habitual inner speech processes. PMID:22563007

  15. Quantitative agent based model of user behavior in an Internet discussion forum.

    PubMed

    Sobkowicz, Pawel

    2013-01-01

    The paper presents an agent based simulation of opinion evolution, based on a nonlinear emotion/information/opinion (E/I/O) individual dynamics, to an actual Internet discussion forum. The goal is to reproduce the results of two-year long observations and analyses of the user communication behavior and of the expressed opinions and emotions, via simulations using an agent based model. The model allowed to derive various characteristics of the forum, including the distribution of user activity and popularity (outdegree and indegree), the distribution of length of dialogs between the participants, their political sympathies and the emotional content and purpose of the comments. The parameters used in the model have intuitive meanings, and can be translated into psychological observables.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. Comparing large-scale computational approaches to epidemic modeling: agent based versus structured metapopulation models

    NASA Astrophysics Data System (ADS)

    Gonçalves, Bruno; Ajelli, Marco; Balcan, Duygu; Colizza, Vittoria; Hu, Hao; Ramasco, José; Merler, Stefano; Vespignani, Alessandro

    2010-03-01

    We provide for the first time a side by side comparison of the results obtained with a stochastic agent based model and a structured metapopulation stochastic model for the evolution of a baseline pandemic event in Italy. The Agent Based model is based on the explicit representation of the Italian population through highly detailed data on the socio-demographic structure. The metapopulation simulations use the GLobal Epidemic and Mobility (GLEaM) model, based on high resolution census data worldwide, and integrating airline travel flow data with short range human mobility patterns at the global scale. Both models provide epidemic patterns that are in very good agreement at the granularity levels accessible by both approaches, with differences in peak timing of the order of few days. The age breakdown analysis shows that similar attack rates are obtained for the younger age classes.

  4. 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.

  5. ACACIA: an agent-based program for simulating behavior to reach long-term goals.

    PubMed

    Beltran, Francesc S; Quera, Vicenç; Zibetti, Elisabetta; Tijus, Charles; Miñano, Meritxell

    2009-05-01

    We present ACACIA, an agent-based program implemented in Java StarLogo 2.0 that simulates a two-dimensional microworld populated by agents, obstacles and goals. Our program simulates how agents can reach long-term goals by following sensorial-motor couplings (SMCs) that control how the agents interact with their environment and other agents through a process of local categorization. Thus, while acting in accordance with this set of SMCs, the agents reach their goals through the emergence of global behaviors. This agent-based simulation program would allow us to understand some psychological processes such as planning behavior from the point of view that the complexity of these processes is the result of agent-environment interaction.

  6. 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.

  7. Analyzing the Validity of Relationship Banking through Agent-based Modeling

    NASA Astrophysics Data System (ADS)

    Nishikido, Yukihito; Takahashi, Hiroshi

    This article analyzes the validity of relationship banking through agent-based modeling. In the analysis, we especially focus on the relationship between economic conditions and both lenders' and borrowers' behaviors. As a result of intensive experiments, we made the following interesting findings: (1) Relationship banking contributes to reducing bad loan; (2) relationship banking is more effective in enhancing the market growth compared to transaction banking, when borrowers' sales scale is large; (3) keener competition among lenders may bring inefficiency to the market.

  8. 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. PMID:26655734

  9. 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.

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

    PubMed Central

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

    2015-01-01

    Abstract 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. PMID:26655734

  11. 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.

  12. 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.

  13. 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).

  14. 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.

  15. Use of agent-based simulations to design and interpret HIV clinical trials.

    PubMed

    Cuadros, Diego F; Abu-Raddad, Laith J; Awad, Susanne F; García-Ramos, Gisela

    2014-07-01

    In this study, we illustrate the utility of an agent-based simulation to inform a trial design and how this supports outcome interpretation of randomized controlled trials (RCTs). We developed agent-based Monte Carlo models to simulate existing landmark HIV RCTs, such as the Partners in Prevention HSV/HIV Transmission Study. We simulated a variation of this study using valacyclovir therapy as the intervention, and we used a male circumcision RCT based on the Rakai Male Circumcision Trial. Our results indicate that a small fraction (20%) of the simulated Partners in Prevention HSV/HIV Transmission Study realizations rejected the null hypothesis, which was no effect from the intervention. Our results also suggest that an RCT designed to evaluate the effectiveness of a more potent drug regimen for HSV-2 suppression (valacyclovir therapy) is more likely to identify the efficacy of the intervention. For the male circumcision RCT simulation, the greater biological effect of the male circumcision yielded a major fraction (81%) of RCT realizations' that rejects the null hypothesis, which was no effect from the intervention. Our study highlights how agent-based simulations synthesize individual variation in the epidemiological context of the RCT. This methodology will be particularly useful for designing RCTs aimed at evaluating combination prevention interventions in community-based RCTs, wherein an intervention׳s effectiveness is challenging to predict. PMID:24792492

  16. Agent-based simulation of building evacuation using a grid graph-based model

    NASA Astrophysics Data System (ADS)

    Tan, L.; Lin, H.; Hu, M.; Che, W.

    2014-02-01

    Shifting from macroscope models to microscope models, the agent-based approach has been widely used to model crowd evacuation as more attentions are paid on individualized behaviour. Since indoor evacuation behaviour is closely related to spatial features of the building, effective representation of indoor space is essential for the simulation of building evacuation. The traditional cell-based representation has limitations in reflecting spatial structure and is not suitable for topology analysis. Aiming at incorporating powerful topology analysis functions of GIS to facilitate agent-based simulation of building evacuation, we used a grid graph-based model in this study to represent the indoor space. Such model allows us to establish an evacuation network at a micro level. Potential escape routes from each node thus could be analysed through GIS functions of network analysis considering both the spatial structure and route capacity. This would better support agent-based modelling of evacuees' behaviour including route choice and local movements. As a case study, we conducted a simulation of emergency evacuation from the second floor of an official building using Agent Analyst as the simulation platform. The results demonstrate the feasibility of the proposed method, as well as the potential of GIS in visualizing and analysing simulation results.

  17. 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.

  18. An Agent-Based Model of Signal Transduction in Bacterial Chemotaxis

    PubMed Central

    Miller, Jameson; Parker, Miles; Bourret, Robert B.; Giddings, Morgan C.

    2010-01-01

    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. PMID:20485527

  19. 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

  20. Recent Advances in Agent-Based Tsunami Evacuation Simulations: Case Studies in Indonesia, Thailand, Japan and Peru

    NASA Astrophysics Data System (ADS)

    Mas, Erick; Koshimura, Shunichi; Imamura, Fumihiko; Suppasri, Anawat; Muhari, Abdul; Adriano, Bruno

    2015-12-01

    As confirmed by the extreme tsunami events over the last decade (the 2004 Indian Ocean, 2010 Chile and 2011 Japan tsunami events), mitigation measures and effective evacuation planning are needed to reduce disaster risks. Modeling tsunami evacuations is an alternative means to analyze evacuation plans and possible scenarios of evacuees' behaviors. In this paper, practical applications of an agent-based tsunami evacuation model are presented to demonstrate the contributions that agent-based modeling has added to tsunami evacuation simulations and tsunami mitigation efforts. A brief review of previous agent-based evacuation models in the literature is given to highlight recent progress in agent-based methods. Finally, challenges are noted for bridging gaps between geoscience and social science within the agent-based approach for modeling tsunami evacuations.

  1. 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.

  2. 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

  3. 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.

  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

    2016-01-01

    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

  5. 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.

  6. Dyke intrusion dynamics during the ongoing rifting episode in Afar

    NASA Astrophysics Data System (ADS)

    Jacques, E.; Grandin, R.; Nercessian, A.; Ayele, A.; Keir, D.; Doubre, C.; Socquet, A.; Lemarchand, A.

    2010-12-01

    Dyke intrusion is one of the main processes of crustal accretion occurring along magma-assisted divergent plate boundaries, in particular along Mid-Ocean Ridges. Seismology, through the analysis of earthquake migration coeval to dyke intrusion, is one of the few tools, with geodesy, which allows studying the dynamics of this fundamental process. In Afar (Ethiopia), the major Dabbahu-Manda Hararo rifting episode started in September 2005 with the intrusion a 60 km-long, 5 m-wide mega-dyke. Between June 2006 and May 2010, 13 smaller dykes (~10 km long) were emplaced, giving an outstanding opportunity to perform such studies. A few weeks after the rifting episode commenced, a regional seismological network of broadband stations was installed in Afar (part of a multinational project including UK, US and Ethiopia). In November 2007, in collaboration with the Geophysical Observatory of Addis Ababa University, IPGP (Institut de Physique du Globe de Paris) installed a local telemetered seismological network including 5 short-period stations around the southern half of the Dabbahu-Manda Hararo rift. We focus here on the microseismicity related to five dyke intrusions, which occurred between June 2006 and February 2009. The dykes propagated away from the Walis magma reservoir (WMR, 12.3°N, 40.6°E) at velocities ranging from 0.5km/h to 2km/h. Earthquake migrations during dyke intrusions involved a narrow (less than 5 km wide), seismically-active strip around the dykes, and seem to show the following pattern: first, near the tip of the propagating dyke, probably in the damage zone, small to moderate earthquakes are detected. Subsequent, more energetic earthquakes may have been triggered only after sufficient dyke inflation had occurred. Earthquake sequences, which occurred north of WMR, migrated faster (~2km/h) than those that took place south of WMR (0.5-1km/h), and liberated a greater amount of seismic energy. This is in keeping with results of normal stress modeling

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. 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.

  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. PMID:26259926

  13. 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.

  14. Agent-based modeling of malaria vectors: the importance of spatial simulation

    PubMed Central

    2014-01-01

    Background The modeling of malaria vector mosquito populations yields great insight into drivers of malaria transmission at the village scale. Simulation of individual mosquitoes as “agents” in a distributed, dynamic model domain may be greatly beneficial for simulation of spatial relationships of vectors and hosts. Methods In this study, an agent-based model is used to simulate the life cycle and movement of individual malaria vector mosquitoes in a Niger Sahel village, with individual simulated mosquitoes interacting with their physical environment as well as humans. Various processes that are known to be epidemiologically important, such as the dependence of parity on flight distance between developmental habitat and blood meal hosts and therefore spatial relationships of pools and houses, are readily simulated using this modeling paradigm. Impacts of perturbations can be evaluated on the basis of vectorial capacity, because the interactions between individuals that make up the population- scale metric vectorial capacity can be easily tracked for simulated mosquitoes and human blood meal hosts, without the need to estimate vectorial capacity parameters. Results As expected, model results show pronounced impacts of pool source reduction from larvicide application and draining, but with varying degrees of impact depending on the spatial relationship between pools and human habitation. Results highlight the importance of spatially-explicit simulation that can model individuals such as in an agent-based model. Conclusions The impacts of perturbations on village scale malaria transmission depend on spatial locations of individual mosquitoes, as well as the tracking of relevant life cycle events and characteristics of individual mosquitoes. This study demonstrates advantages of using an agent-based approach for village-scale mosquito simulation to address questions in which spatial relationships are known to be important. PMID:24992942

  15. 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

  16. Is the Person-Situation Debate Important for Agent-Based Modeling and Vice-Versa?

    PubMed Central

    Sznajd-Weron, Katarzyna; Szwabiński, Janusz; Weron, Rafał

    2014-01-01

    Background Agent-based models (ABM) are believed to be a very powerful tool in the social sciences, sometimes even treated as a substitute for social experiments. When building an ABM we have to define the agents and the rules governing the artificial society. Given the complexity and our limited understanding of the human nature, we face the problem of assuming that either personal traits, the situation or both have impact on the social behavior of agents. However, as the long-standing person-situation debate in psychology shows, there is no consensus as to the underlying psychological mechanism and the important question that arises is whether the modeling assumptions we make will have a substantial influence on the simulated behavior of the system as a whole or not. Methodology/Principal Findings Studying two variants of the same agent-based model of opinion formation, we show that the decision to choose either personal traits or the situation as the primary factor driving social interactions is of critical importance. Using Monte Carlo simulations (for Barabasi-Albert networks) and analytic calculations (for a complete graph) we provide evidence that assuming a person-specific response to social influence at the microscopic level generally leads to a completely different and less realistic aggregate or macroscopic behavior than an assumption of a situation-specific response; a result that has been reported by social psychologists for a range of experimental setups, but has been downplayed or ignored in the opinion dynamics literature. Significance This sensitivity to modeling assumptions has far reaching consequences also beyond opinion dynamics, since agent-based models are becoming a popular tool among economists and policy makers and are often used as substitutes of real social experiments. PMID:25369531

  17. Magmatic intrusions in the lunar crust

    NASA Astrophysics Data System (ADS)

    Michaut, C.; Thorey, C.

    2015-10-01

    The lunar highlands are very old, with ages covering a timespan between 4.5 to 4.2 Gyr, and probably formed by flotation of light plagioclase minerals on top of the lunar magma ocean. The lunar crust provides thus an invaluable evidence of the geological and magmatic processes occurring in the first times of the terrestrial planets history. According to the last estimates from the GRAIL mission, the lunar primary crust is particularly light and relatively thick [1] This low-density crust acted as a barrier for the dense primary mantle melts. This is particularly evident in the fact that subsequent mare basalts erupted primarily within large impact basin: at least part of the crust must have been removed for the magma to reach the surface. However, the trajectory of the magma from the mantle to the surface is unknown. Using a model of magma emplacement below an elastic overlying layer with a flexural wavelength Λ, we characterize the surface deformations induced by the presence of shallow magmatic intrusions. We demonstrate that, depending on its size, the intrusion can show two different shapes: a bell shape when its radius is smaller than 4 times Λ or a flat top with small bended edges if its radius is larger than 4 times Λ[2]. These characteristic shapes for the intrusion result in characteristic deformations at the surface that also depend on the topography of the layer overlying the intrusion [3].Using this model we provide evidence of the presence of intrusions within the crust of the Moon as surface deformations in the form of low-slope lunar domes and floor-fractured craters. All these geological features have morphologies consistent with models of magma spreading at depth and deforming an overlying elastic layer. Further more,at floor-fractured craters, the deformation is contained within the crater interior, suggesting that the overpressure at the origin of magma ascent and intrusion was less than the pressure due to the weight of the crust removed by

  18. 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.

  19. 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.

  20. An agent-based model of centralized institutions, social network technology, and revolution.

    PubMed

    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.

  1. A Participatory Agent-Based Simulation for Indoor Evacuation Supported by Google Glass.

    PubMed

    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

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. An agent-based computational model of the spread of tuberculosis

    NASA Astrophysics Data System (ADS)

    de Espíndola, Aquino L.; Bauch, Chris T.; Troca Cabella, Brenno C.; Souto Martinez, Alexandre

    2011-05-01

    In this work we propose an alternative model of the spread of tuberculosis (TB) and the emergence of drug resistance due to the treatment with antibiotics. We implement the simulations by an agent-based model computational approach where the spatial structure is taken into account. The spread of tuberculosis occurs according to probabilities defined by the interactions among individuals. The model was validated by reproducing results already known from the literature in which different treatment regimes yield the emergence of drug resistance. The different patterns of TB spread can be visualized at any time of the system evolution. The implementation details as well as some results of this alternative approach are discussed.

  7. 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.

  8. 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.

  9. 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.

  10. An agent-based epidemic simulation of social behaviors affecting HIV transmission among Taiwanese homosexuals.

    PubMed

    Huang, Chung-Yuan

    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.

  11. 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.

  12. 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.

  13. 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. PMID:24864263

  14. 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

  15. Attribute Assignment to a Synthetic Population in Support of Agent-Based Disease Modeling

    PubMed Central

    Cajka, James C.; Cooley, Philip C.; Wheaton, William D.

    2010-01-01

    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. PMID:22577617

  16. Combining agent-based modeling and life cycle assessment for the evaluation of mobility policies.

    PubMed

    Florent, Querini; Enrico, Benetto

    2015-02-01

    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.

  17. An Agent-Based Dynamic Model for Analysis of Distributed Space Exploration Architectures

    NASA Astrophysics Data System (ADS)

    Sindiy, Oleg V.; DeLaurentis, Daniel A.; Stein, William B.

    2009-07-01

    A range of complex challenges, but also potentially unique rewards, underlie the development of exploration architectures that use a distributed, dynamic network of resources across the solar system. From a methodological perspective, the prime challenge is to systematically model the evolution (and quantify comparative performance) of such architectures, under uncertainty, to effectively direct further study of specialized trajectories, spacecraft technologies, concept of operations, and resource allocation. A process model for System-of-Systems Engineering is used to define time-varying performance measures for comparative architecture analysis and identification of distinguishing patterns among interoperating systems. Agent-based modeling serves as the means to create a discrete-time simulation that generates dynamics for the study of architecture evolution. A Solar System Mobility Network proof-of-concept problem is introduced representing a set of longer-term, distributed exploration architectures. Options within this set revolve around deployment of human and robotic exploration and infrastructure assets, their organization, interoperability, and evolution, i.e., a system-of-systems. Agent-based simulations quantify relative payoffs for a fully distributed architecture (which can be significant over the long term), the latency period before they are manifest, and the up-front investment (which can be substantial compared to alternatives). Verification and sensitivity results provide further insight on development paths and indicate that the framework and simulation modeling approach may be useful in architectural design of other space exploration mass, energy, and information exchange settings.

  18. 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

  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. 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.

  1. 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.

  2. 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.

  3. 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. PMID:24714635

  4. An Agent-Based Modeling Framework and Application for the Generic Nuclear Fuel Cycle

    NASA Astrophysics Data System (ADS)

    Gidden, Matthew J.

    Key components of a novel methodology and implementation of an agent-based, dynamic nuclear fuel cycle simulator, Cyclus , are presented. The nuclear fuel cycle is a complex, physics-dependent supply chain. To date, existing dynamic simulators have not treated constrained fuel supply, time-dependent, isotopic-quality based demand, or fuel fungibility particularly well. Utilizing an agent-based methodology that incorporates sophisticated graph theory and operations research techniques can overcome these deficiencies. This work describes a simulation kernel and agents that interact with it, highlighting the Dynamic Resource Exchange (DRE), the supply-demand framework at the heart of the kernel. The key agent-DRE interaction mechanisms are described, which enable complex entity interaction through the use of physics and socio-economic models. The translation of an exchange instance to a variant of the Multicommodity Transportation Problem, which can be solved feasibly or optimally, follows. An extensive investigation of solution performance and fidelity is then presented. Finally, recommendations for future users of Cyclus and the DRE are provided.

  5. 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.

  6. 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.

  7. 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

  8. Combining agent-based modeling and life cycle assessment for the evaluation of mobility policies.

    PubMed

    Florent, Querini; Enrico, Benetto

    2015-02-01

    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. PMID:25587896

  9. 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

  10. 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

  11. 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...

  12. 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

  13. Intrusive [r] and Optimal Epenthetic Consonants

    ERIC Educational Resources Information Center

    Uffmann, Christian

    2007-01-01

    This paper argues against the view of intrusive [r] as a synchronically arbitrary insertion process. Instead, it is seen as a phonologically natural process, which can be modelled within the framework of Optimality Theory (OT). Insertion of [r] in phonologically restricted environments is a consequence of a more general theory of consonant…

  14. 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...

  15. 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...

  16. 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.

  17. 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…

  18. 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.

  19. Agent-based modeling of a multi-room multi-floor building emergency evacuation

    NASA Astrophysics Data System (ADS)

    Ha, Vi; Lykotrafitis, George

    2012-04-01

    Panic during emergency building evacuation can cause crowd stampede, resulting in serious injuries and casualties. Agent-based methods have been successfully employed to investigate the collective human behavior during emergency evacuation in cases where the configurational space is extremely simple-usually one rectangular room-but not in evacuations of multi-room or multi-floor buildings. This implies that the effect of the complexity of building architecture on the collective behavior of the agents during evacuation has not been fully investigated. Here, we employ a system of self-moving particles whose motion is governed by the social-force model to investigate the effect of complex building architecture on the uncoordinated crowd motion during urgent evacuation. In particular, we study how the room door size, the size of the main exit, the desired speed and the friction coefficient affect the evacuation time and under what circumstances the evacuation efficiency improves.

  20. Modeling Interdependencies between power and economic sectors using the N-ABLE agent-based model.

    SciTech Connect

    Ehlen, Mark Andrew; Scholand, Andrew Joseph

    2005-01-01

    The nation's electric power sector is highly interdependent with the economic sectors it serves; electric power needs are driven by economic activity while the economy itself depends on reliable and sustainable electric power. To advance higher level understandings of the vulnerabilities that result from these interdependencies and to identify the loss prevention and loss mitigation policies that best serve the nation, the National Infrastructure Simulation and Analysis Center is developing and using N-ABLE{trademark}, an agent-based microeconomic framework and simulation tool that models these interdependencies at the level of collections of individual economic firms. Current projects that capture components of these electric power and economic sector interdependencies illustrate some of the public policy issues that should be addressed for combined power sector reliability and national economic security.

  1. Agent-based modeling: a new approach for theory building in social psychology.

    PubMed

    Smith, Eliot R; Conrey, Frederica R

    2007-02-01

    Most social and psychological phenomena occur not as the result of isolated decisions by individuals but rather as the result of repeated interactions between multiple individuals over time. Yet the theory-building and modeling techniques most commonly used in social psychology are less than ideal for understanding such dynamic and interactive processes. This article describes an alternative approach to theory building, agent-based modeling (ABM), which involves simulation of large numbers of autonomous agents that interact with each other and with a simulated environment and the observation of emergent patterns from their interactions. The authors believe that the ABM approach is better able than prevailing approaches in the field, variable-based modeling (VBM) techniques such as causal modeling, to capture types of complex, dynamic, interactive processes so important in the social world. The article elaborates several important contrasts between ABM and VBM and offers specific recommendations for learning more and applying the ABM approach. PMID:18453457

  2. Brazilian Proposal for Agent-Based Learning Objects Metadata Standard - OBAA

    NASA Astrophysics Data System (ADS)

    Vicari, Rosa Maria; Ribeiro, Alexandre; da Silva, Júlia Marques Carvalho; Santos, Elder Rizzon; Primo, Tiago; Bez, Marta

    This paper presents the Agent Based Learning Objects - OBAA standard proposal. The main goal of the research was to establish a standardized specification of the technical and functional requirements of interoperable learning objects. In our context, interoperability regards the operation of the content inside Web, Digital TV and mobile environments, supporting accessibility and pedagogical issues. In this proposal it has been explored the convergence among the multi-agent systems, learning object and ubiquitous computing technologies, allowing the authoring, storage and recovery of learning object in varied contexts and through different digital platforms. The result of this research was the definition of the OBAA proposal containing the requirements, specifications and architectures that will compose the Brazilian standard for the management, transmission, storage, search, editing and use of interoperable learning object.

  3. 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.

  4. 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.

  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. 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.

  7. Health care supply networks in tightly and loosely coupled structures: exploration using agent-based modelling

    NASA Astrophysics Data System (ADS)

    Kanagarajah, A.; Parker, D.; Xu, H.

    2010-03-01

    Health care supply networks are multi-faceted complex structures. This article discusses architecture of complex systems and an agent-based modelling framework to study health care supply networks and their impact on patient safety, economics, and workloads. Here we demonstrate the application of a safety dynamics model proposed by Cook and Rasmussen (2005, '"Going Solid": A Model of System Dynamics and Consequences for Patient Safety', Quality & Safety in Health Care, 14, 67-84.) to study a health care system, using a hypothetical simulation of an emergency department as a representative unit and its dynamic behaviour. By means of simulation, this article demonstrates the non-linear behaviours of a health service unit and its complexities; and how the safety dynamic model may be used to evaluate the various policy and design aspects of health care supply networks.

  8. 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. PMID:26062022

  9. 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. PMID:26590977

  10. 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.

  11. 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.

  12. 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.

  13. 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'. PMID:27431525

  14. 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'.

  15. An agent based multi-optional model for the diffusion of innovations

    NASA Astrophysics Data System (ADS)

    Laciana, Carlos E.; Oteiza-Aguirre, Nicolás

    2014-01-01

    We propose a model for the diffusion of several products competing in a common market based on the generalization of the Ising model of statistical mechanics (Potts model). Using an agent based implementation we analyze two problems: (i) a three options case, i.e. to adopt a product A, a product B, or non-adoption and (ii) a four option case, i.e. the adoption of product A, product B, both, or none. In the first case we analyze a launching strategy for one of the two products, which delays its launching with the objective of competing with improvements. Market shares reached by each product are then estimated at market saturation. Finally, simulations are carried out with varying degrees of social network topology, uncertainty, and population homogeneity.

  16. 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.

  17. Quantitative agent-based firm dynamics simulation with parameters estimated by financial and transaction data analysis

    NASA Astrophysics Data System (ADS)

    Ikeda, Yuichi; Souma, Wataru; Aoyama, Hideaki; Iyetomi, Hiroshi; Fujiwara, Yoshi; Kaizoji, Taisei

    2007-03-01

    Firm dynamics on a transaction network is considered from the standpoint of econophysics, agent-based simulations, and game theory. In this model, interacting firms rationally invest in a production facility to maximize net present value. We estimate parameters used in the model through empirical analysis of financial and transaction data. We propose two different methods ( analytical method and regression method) to obtain an interaction matrix of firms. On a subset of a real transaction network, we simulate firm's revenue, cost, and fixed asset, which is the accumulated investment for the production facility. The simulation reproduces the quantitative behavior of past revenues and costs within a standard error when we use the interaction matrix estimated by the regression method, in which only transaction pairs are taken into account. Furthermore, the simulation qualitatively reproduces past data of fixed assets.

  18. Skin Stem Cell Hypotheses and Long Term Clone Survival – Explored Using Agent-based Modelling

    PubMed Central

    Li, X.; Upadhyay, A. K.; Bullock, A. J.; Dicolandrea, T.; Xu, J.; Binder, R. L.; Robinson, M. K.; Finlay, D. R.; Mills, K. J.; Bascom, C. C.; Kelling, C. K.; Isfort, R. J.; Haycock, J. W.; MacNeil, S.; Smallwood, R. H.

    2013-01-01

    Epithelial renewal in skin is achieved by the constant turnover and differentiation of keratinocytes. Three popular hypotheses have been proposed to explain basal keratinocyte regeneration and epidermal homeostasis: 1) asymmetric division (stem-transit amplifying cell); 2) populational asymmetry (progenitor cell with stochastic fate); and 3) populational asymmetry with stem cells. In this study, we investigated lineage dynamics using these hypotheses with a 3D agent-based model of the epidermis. The model simulated the growth and maintenance of the epidermis over three years. The offspring of each proliferative cell was traced. While all lineages were preserved in asymmetric division, the vast majority were lost when assuming populational asymmetry. The third hypothesis provided the most reliable mechanism for self-renewal by preserving genetic heterogeneity in quiescent stem cells, and also inherent mechanisms for skin ageing and the accumulation of genetic mutation. PMID:23712735

  19. 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

  20. Agent based spin model for financial markets on regular lattices and complex networks

    NASA Astrophysics Data System (ADS)

    Kim, Hong-Joo; Yook, Soon-Hyung; Kim, Yup

    2008-03-01

    We study an agent based microscopic model for price formation in financial markets on various topologies motivated by the dynamics of agents. The model consists of interacting agents (spins) with localand global couplings. The local interaction denotes the tendency of agents to make the same decision with their interacting partners. On the other hand, the global coupling to the self-generating field represents the process which maximizes the profit of each agent. In order to incorporate more realistic situations, we also introduce an external field which changes in time. This time-varying external field represents any internal or external interference in the dynamics of the market. For the proper choice of model parameters, the competition between the interactions causes an intermittency dynamics and we find that the distribution of logarithmic return of price follows a power-law.

  1. 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.

  2. 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

  3. 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.

  4. 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

  5. Understanding the Dynamics of Violent Political Revolutions in an Agent-Based Framework.

    PubMed

    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

  6. 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

  7. 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.

  8. An agent-based interaction model for Chinese personal income distribution

    NASA Astrophysics Data System (ADS)

    Zou, Yijiang; Deng, Weibing; Li, Wei; Cai, Xu

    2015-10-01

    The personal income distribution in China was studied by employing the data from China Household Income Projects (CHIP) between 1990 and 2002. It was observed that the low and middle income regions could be described by the log-normal law, while the large income region could be well fitted by the power law. To characterize these empirical findings, a stochastic interactive model with mean-field approach was discussed, and the analytic result shows that the wealth distribution is of the Pareto type. Then we explored the agent-based model on networks, in which the exchange of wealth among agents depends on their connectivity. Numerical results suggest that the wealth of agents would largely rely on their connectivity, and the Pareto index of the simulated wealth distributions is comparable to those of the empirical data. The Pareto behavior of the tails of the empirical wealth distributions is consistent with that of the 'mean-field' model, as well as numerical simulations.

  9. 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.

  10. 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. PMID:26963526

  11. Introducing AN Agent-Based Object Recognition Operator for Proximity Analysis

    NASA Astrophysics Data System (ADS)

    Behzadi, S.; Ali. Alesheikh, A.

    2013-09-01

    Object selection is a basic procedure in a Geographic Information System (GIS). Most current methods for doing so, select objects in two phases: create a simple distance-bounded geometric buffer; and intersect it with available features. This paper introduces a novel and intelligent selection operator based on the autonomy of the agent-based approach. The proposed operator recognizes objects around one object only in one step. In the proposed approach, each point object acts as an agent-automata object. It then senses its vicinity and identifies the surrounding objects. To assess the proposed model, the operator is designed, implemented, and evaluated in a case study. Finally, the results are evaluated and presented in details in the paper.

  12. 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.

  13. 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

  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. 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.

  16. Agent-Based Model with Asymmetric Trading and Herding for Complex Financial Systems

    PubMed Central

    Chen, Jun-Jie; Zheng, Bo; Tan, Lei

    2013-01-01

    Background For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. Methods To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors’ asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. Results With the model parameters determined for six representative stock-market indices in the world, respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. Conclusions We reveal that for the leverage and anti-leverage effects, both the investors’ asymmetric trading and herding are essential generation mechanisms. Among the six markets, however, the investors’ trading is approximately symmetric for the five markets which exhibit the leverage effect, thus contributing very little. These two microscopic mechanisms and the methods for the determination of the key

  17. 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.

  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. Evolving nutritional strategies in the presence of competition: a geometric agent-based model.

    PubMed

    Senior, Alistair M; Charleston, Michael A; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J

    2015-03-01

    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.

  20. 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.

  1. Combination HIV Prevention among MSM in South Africa: Results from Agent-based Modeling

    PubMed Central

    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

  2. Estimating Impacts of Climate Change Policy on Land Use: An Agent-Based Modelling Approach

    PubMed Central

    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. PMID:25996591

  3. The Evolution of Cooperation in Managed Groundwater Systems: An Agent-Based Modelling Approach

    NASA Astrophysics Data System (ADS)

    Castilla Rho, J. C.; Mariethoz, G.; Rojas, R. F.; Andersen, M. S.; Kelly, B. F.; Holley, C.

    2014-12-01

    Human interactions with groundwater systems often exhibit complex features that hinder the sustainable management of the resource. This leads to costly and persistent conflicts over groundwater at the catchment scale. One possible way to address these conflicts is by gaining a better understanding of how social and groundwater dynamics coevolve using agent-based models (ABM). Such models allow exploring 'bottom-up' solutions (i.e., self-organised governance systems), where the behaviour of individual agents (e.g., farmers) results in the emergence of mutual cooperation among groundwater users. There is significant empirical evidence indicating that this kind of 'bottom-up' approach may lead to more enduring and sustainable outcomes, compared to conventional 'top-down' strategies such as centralized control and water right schemes (Ostrom 1990). New modelling tools are needed to study these concepts systematically and efficiently. Our model uses a conceptual framework to study cooperation and the emergence of social norms as initially proposed by Axelrod (1986), which we adapted to groundwater management. We developed an ABM that integrates social mechanisms and the physics of subsurface flow. The model explicitly represents feedback between groundwater conditions and social dynamics, capturing the spatial structure of these interactions and the potential effects on cooperation levels in an agricultural setting. Using this model, we investigate a series of mechanisms that may trigger norms supporting cooperative strategies, which can be sustained and become stable over time. For example, farmers in a self-monitoring community can be more efficient at achieving the objective of sustainable groundwater use than government-imposed regulation. Our coupled model thus offers a platform for testing new schemes promoting cooperation and improved resource use, which can be used as a basis for policy design. Importantly, we hope to raise awareness of agent-based modelling as

  4. 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

  5. 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

  6. 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

  7. 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.

  8. A task-oriented modular and agent-based collaborative design mechanism for distributed product development

    NASA Astrophysics Data System (ADS)

    Liu, Jinfei; Chen, Ming; Wang, Lei; Wu, Qidi

    2014-05-01

    The rapid expansion of enterprises makes product collaborative design (PCD) a critical issue under the distributed heterogeneous environment, but as the collaborative task of large-scale network becomes more complicated, neither unified task decomposition and allocation methodology nor Agent-based network management platform can satisfy the increasing demands. In this paper, to meet requirements of PCD for distributed product development, a collaborative design mechanism based on the thought of modularity and the Agent technology is presented. First, the top-down 4-tier process model based on task-oriented modular and Agent is constructed for PCD after analyzing the mapping relationships between requirements and functions in the collaborative design. Second, on basis of sub-task decomposition for PCD based on a mixed method, the mathematic model of task-oriented modular based on multi-objective optimization is established to maximize the module cohesion degree and minimize the module coupling degree, while considering the module executable degree as a restriction. The mathematic model is optimized and simulated by the modified PSO, and the decomposed modules are obtained. Finally, the Agent structure model for collaborative design is put forward, and the optimism matching Agents are selected by using similarity algorithm to implement different task-modules by the integrated reasoning and decision-making mechanism with the behavioral model of collaborative design Agents. With the results of experimental studies for automobile collaborative design, the feasibility and efficiency of this methodology of task-oriented modular and Agent-based collaborative design in the distributed heterogeneous environment are verified. On this basis, an integrative automobile collaborative R&D platform is developed. This research provides an effective platform for automobile manufacturing enterprises to achieve PCD, and helps to promote product numeralization collaborative R&D and

  9. 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.

  10. 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.

  11. A simplified approach to true molar intrusion

    PubMed Central

    2012-01-01

    Background Orthodontic management of anterior open bites is a demanding task for orthodontists. Molar intrusion as a primary means of open bite correction entails the need for appropriate anchorage. Orthodontic mini implants can provide the required mechanical support. The suggested procedure aims to reduce the risk of complications such as root damage or soft tissue irritations while minimizing overall complexity. Methods Three female patients aged 14, 18 and 19 years who decided against a surgical correction were treated with a device consisting of mini implants in the palatal slope, a palatal bar and intrusion cantilevers. Results In all three patients, an open bite reduction of more than a millimeter occurred within four months. An anterior overbite of 2 mm or more could be established within 6 to 9 months. Conclusions The method presented in this article enables the practitioner to use mini implants in an easily accessible insertion site. A lab-side procedure is optional but not required. PMID:23134693

  12. [Approaching intrusive care in nursing education].

    PubMed

    Flament, Nathalie; Godon, Guillaume; Henon, Nathalie; Witzak, Elisabeth; Grousset, Sylvie

    2015-04-01

    The initial representations of the profession and of proper care of student nurses beginning their training, will, throughout their course, come up against the reality of nursing practice. At the heart of the complexity of potentially intrusive care procedures and the relational approach in which they are players or witnesses, their practical work experience becomes a modelling tool for their career. This is facilitated when the teaching team structures the reflexive analysis through pedagogical approaches favouring expression and objectivity between peers.

  13. Count out your intrusions: effects of verbal encoding on intrusive memories.

    PubMed

    Krans, Julie; Naring, Gerard; Becker, Eni S

    2009-11-01

    Peri-traumatic information processing is thought to affect the development of intrusive trauma memories. This study aimed to replicate and improve the study by Holmes, Brewin, and Hennessy (2004, Exp. 3) on the role of peri-traumatic verbal processing in analogue traumatic intrusion development. Participants viewed an aversive film under one of three conditions: counting backwards in 3s ("verbal interference"), verbalising emotions and thoughts ("verbal enhancement"), or without an extra task. A dual-process account of PTSD would predict that verbal interference would increase intrusion frequency compared to no task, whereas verbal enhancement would lead to a decrease. In contrast, mainstream memory theory predicts a decrease in intrusion frequency from any concurrent task that diverts attention away from the trauma film. The main finding was that the verbal interference task led to a decrease in intrusive memories of the film compared to the other two conditions. This finding does not support a dual-process account of PTSD, but is in line with general theories of memory and attention.

  14. Saline intrusion in partially mixed estuaries

    NASA Astrophysics Data System (ADS)

    Prandle, D.

    2004-03-01

    Restricting interest to partially mixed estuaries, earlier studies of tidally averaged linearised theories relating to the vertical structure of salinity and velocities (accompanying saline intrusion) are extended to take account of tidal straining and associated convective overturning. The applicability of these theories is evaluated by reference to a 'single-point' numerical model in which the time-varying cycle of depth-averaged tidal current amplitude, Û, and a (temporally and vertically) constant saline gradient, S x, are specified. This model highlights the importance of convective overturning in counteracting unstable density structures introduced by tidal straining. By omitting overturning in the model, results agree closely with linearised theoretical derivations. However, incorporating overturning substantially increases tidally averaged surface-to-bed differences for both residual currents, δ u, and salinity, δ s. The vertical structure of tidal currents is a maximum, and hence the effect of tidal straining, in shallow macro-tidal estuaries. The propagation of tidal elevations and currents remains insensitive to saline intrusion in partially mixed estuaries. The applicability of the model was evaluated by simulation of recent measurements by Rippeth et al. (J. Phys. Oceanogr. 31 (2001) 2458). To explore the generality of estuarine responses, the model was run for a wide range of values of saline intrusion lengths, L, and water depths, D. Additional sensitivity analyses were made for changes in Û and bed stress coefficient, k. Response frameworks are shown for: δ u, δ s, potential energy anomaly φ, work done by bed friction and internal shear, rates and efficiency of saline mixing and ratios of relative mixing by diffusion to overturning. By equating the rate of mixing associated with vertical diffusion with river flow, Q, an expression for saline intrusion length L∝D 2/k ÛU o ( Uo river flow velocity) was derived. This formulation agrees with

  15. Irrigated Agriculture in Morocco: An Agent-Based Model of Adaptation and Decision Making Amid Increasingly Frequent Drought Events

    NASA Astrophysics Data System (ADS)

    Norton, M.

    2015-12-01

    In the past 100 years, Morocco has undertaken a heavy investment in developing water infrastructure that has led to a dramatic expansion of irrigated agriculture. Irrigated agriculture is the primary user of water in many arid countries, often accounting for 80-90% of total water usage. Irrigation is adopted by farmers not only because it leads to increased production, but also because it improves resilience to an uncertain climate. However, the Mediterranean region as a whole has also seen an increase in the frequency and severity of drought events. These droughts have had a dramatic impact on farmer livelihoods and have led to a number of coping strategies, including the adoption or disadoption of irrigation. In this study, we use a record of the annual extent of irrigated agriculture in Morocco to model the effect of drought on the extent of irrigated agriculture. Using an agent-based socioeconomic model, we seek to answer the following questions: 1) Do farmers expand irrigated agriculture in response to droughts? 2) Do drought events entail the removal of perennial crops like orchards? 3) Can we detect the retreat of irrigated agriculture in the more fragile watersheds of Morocco? Understanding the determinants of irrigated crop expansion and contractions will help us understand how agro-ecological systems transition from 20th century paradigms of expansion of water supply to a 21st century paradigm of water use efficiency. The answers will become important as countries learn how to manage water in new climate regimes characterized by less reliable and available precipitation.

  16. An artificial intelligence approach for modeling molecular self-assembly: agent-based simulations of rigid molecules.

    PubMed

    Fortuna, Sara; Troisi, Alessandro

    2009-07-23

    Agent-based simulations are rule-based models traditionally used for the simulations of complex systems. In this paper, an algorithm based on the concept of agent-based simulations is developed to predict the lowest energy packing of a set of identical rigid molecules. The agents are identified with rigid portions of the system under investigation, and they evolve following a set of rules designed to drive the system toward the lowest energy minimum. The algorithm is compared with a conventional Metropolis Monte Carlo algorithm, and it is applied on a large set of representative models of molecules. For all the systems studied, the agent-based method consistently finds a significantly lower energy minima than the Monte Carlo algorithm because the system evolution includes elements of adaptation (new configurations induce new types of moves) and learning (past successful choices are repeated).

  17. Nuclear resonance fluorescence imaging in non-intrusive cargo inspection

    NASA Astrophysics Data System (ADS)

    Bertozzi, William; Ledoux, Robert J.

    2005-12-01

    Nuclear resonance fluorescence is able to non-intrusively interrogate a region space and measure the isotopic content of the material in that space for any element with atomic number greater than that of helium. The technique involves exposing material to a continuous energy distribution of photons and detecting the scattered photons that have a discrete energy distribution unique to an isotope. The interrogating photons, which range from 2 to 8 MeV, are the most penetrating probes and can "see" through many inches of steel. Determination of the chemical components of the material occupying a region of space greatly enhances the identification of threats such as explosives, fissile materials, toxic materials and weapons of mass destruction. Systems can be designed to involve minimal operator intervention, to minimize dose to the sample, and to provide high throughput at commercial seaports, airports and other entry points.

  18. Evaluation of wholesale electric power market rules and financial risk management by agent-based simulations

    NASA Astrophysics Data System (ADS)

    Yu, Nanpeng

    As U.S. regional electricity markets continue to refine their market structures, designs and rules of operation in various ways, two critical issues are emerging. First, although much experience has been gained and costly and valuable lessons have been learned, there is still a lack of a systematic platform for evaluation of the impact of a new market design from both engineering and economic points of view. Second, the transition from a monopoly paradigm characterized by a guaranteed rate of return to a competitive market created various unfamiliar financial risks for various market participants, especially for the Investor Owned Utilities (IOUs) and Independent Power Producers (IPPs). This dissertation uses agent-based simulation methods to tackle the market rules evaluation and financial risk management problems. The California energy crisis in 2000-01 showed what could happen to an electricity market if it did not go through a comprehensive and rigorous testing before its implementation. Due to the complexity of the market structure, strategic interaction between the participants, and the underlying physics, it is difficult to fully evaluate the implications of potential changes to market rules. This dissertation presents a flexible and integrative method to assess market designs through agent-based simulations. Realistic simulation scenarios on a 225-bus system are constructed for evaluation of the proposed PJM-like market power mitigation rules of the California electricity market. Simulation results show that in the absence of market power mitigation, generation company (GenCo) agents facilitated by Q-learning are able to exploit the market flaws and make significantly higher profits relative to the competitive benchmark. The incorporation of PJM-like local market power mitigation rules is shown to be effective in suppressing the exercise of market power. The importance of financial risk management is exemplified by the recent financial crisis. In this

  19. Frequency of intrusive luxation in deciduous teeth and its effects.

    PubMed

    Carvalho, Vivian; Jacomo, Diana Ribeiro; Campos, Vera

    2010-08-01

    The aims of this study were three-fold: First, to determine the prevalence of partial and total intrusion of the primary anterior teeth. Second, to investigate the sequelae of total and partial intrusive luxation in the primary anterior teeth and in their successors and finally, to establish whether the sequelae on both deciduous and permanent teeth were related to the child's age at the time of the intrusion. Data collected from records of 169 boys and 138 girls, all between the ages of zero and 10 years, who were undergoing treatment during the period of March 1996 to December 2004. The sample was composed of 753 traumatized deciduous teeth, of which 221 presented intrusive luxation injury. Children with ages ranging from one to 4 years were the most affected with falls being the main cause of intrusion. Of all intruded teeth 128 (57.9%) were totally intruded and 93 (42.1%) partially. Pulp necrosis/premature loss and color change were the most frequent sequelae in both total and partial intrusions. Concerning permanent dentition, the most common disturbances were color change and/or enamel hypoplasia. Both types of intrusion caused eruption disturbance. Total intrusion was the most frequent type of intrusive luxation. There was no significant correlation between the child's age at the time of intrusion and the frequency of subsequent sequela on primary injured teeth (P = 0.035), between the age at the time of injury and the developmental disturbances on permanent teeth (P = 0.140).

  20. Comparing administered and market-based water allocation systems using an agent-based modeling approach

    NASA Astrophysics Data System (ADS)

    Zhao, J.; Cai, X.; Wang, Z.

    2009-12-01

    It also has been well recognized that market-based systems can have significant advantages over administered systems for water allocation. However there are not many successful water markets around the world yet and administered systems exist commonly in water allocation management practice. This paradox has been under discussion for decades and still calls for attention for both research and practice. This paper explores some insights for the paradox and tries to address why market systems have not been widely implemented for water allocation. Adopting the theory of agent-based system we develop a consistent analytical model to interpret both systems. First we derive some theorems based on the analytical model, with respect to the necessary conditions for economic efficiency of water allocation. Following that the agent-based model is used to illustrate the coherence and difference between administered and market-based systems. The two systems are compared from three aspects: 1) the driving forces acting on the system state, 2) system efficiency, and 3) equity. Regarding economic efficiency, penalty on the violation of water use permits (or rights) under an administered system can lead to system-wide economic efficiency, as well as being acceptable by some agents, which follows the theory of the so-call rational violation. Ideal equity will be realized if penalty equals incentive with an administered system and if transaction costs are zero with a market system. The performances of both agents and the over system are explained with an administered system and market system, respectively. The performances of agents are subject to different mechanisms of interactions between agents under the two systems. The system emergency (i.e., system benefit, equilibrium market price, etc), resulting from the performance at the agent level, reflects the different mechanism of the two systems, the “invisible hand” with the market system and administrative measures (penalty

  1. Evolutionary Agent-based Models to design distributed water management strategies

    NASA Astrophysics Data System (ADS)

    Giuliani, M.; Castelletti, A.; Reed, P. M.

    2012-12-01

    There is growing awareness in the scientific community that the traditional centralized approach to water resources management, as described in much of the water resources literature, provides an ideal optimal solution, which is certainly useful to quantify the best physically achievable performance, but is generally inapplicable. Most real world water resources management problems are indeed characterized by the presence of multiple, distributed and institutionally-independent decision-makers. Multi-Agent Systems provide a potentially more realistic alternative framework to model multiple and self-interested decision-makers in a credible context. Each decision-maker can be represented by an agent who, being self-interested, acts according to local objective functions and produces negative externalities on system level objectives. Different levels of coordination can potentially be included in the framework by designing coordination mechanisms to drive the current decision-making structure toward the global system efficiency. Yet, the identification of effective coordination strategies can be particularly complex in modern institutional contexts and current practice is dependent on largely ad-hoc coordination strategies. In this work we propose a novel Evolutionary Agent-based Modeling (EAM) framework that enables a mapping of fully uncoordinated and centrally coordinated solutions into their relative "many-objective" tradeoffs using multiobjective evolutionary algorithms. Then, by analysing the conflicts between local individual agent and global system level objectives it is possible to more fully understand the causes, consequences, and potential solution strategies for coordination failures. Game-theoretic criteria have value for identifying the most interesting alternatives from a policy making point of view as well as the coordination mechanisms that can be applied to obtain these interesting solutions. The proposed approach is numerically tested on a

  2. Using simple agent-based modeling to inform and enhance neighborhood walkability

    PubMed Central

    2013-01-01

    Background Pedestrian-friendly neighborhoods with proximal destinations and services encourage walking and decrease car dependence, thereby contributing to more active and healthier communities. Proximity to key destinations and services is an important aspect of the urban design decision making process, particularly in areas adopting a transit-oriented development (TOD) approach to urban planning, whereby densification occurs within walking distance of transit nodes. Modeling destination access within neighborhoods has been limited to circular catchment buffers or more sophisticated network-buffers generated using geoprocessing routines within geographical information systems (GIS). Both circular and network-buffer catchment methods are problematic. Circular catchment models do not account for street networks, thus do not allow exploratory ‘what-if’ scenario modeling; and network-buffering functionality typically exists within proprietary GIS software, which can be costly and requires a high level of expertise to operate. Methods This study sought to overcome these limitations by developing an open-source simple agent-based walkable catchment tool that can be used by researchers, urban designers, planners, and policy makers to test scenarios for improving neighborhood walkable catchments. A simplified version of an agent-based model was ported to a vector-based open source GIS web tool using data derived from the Australian Urban Research Infrastructure Network (AURIN). The tool was developed and tested with end-user stakeholder working group input. Results The resulting model has proven to be effective and flexible, allowing stakeholders to assess and optimize the walkability of neighborhood catchments around actual or potential nodes of interest (e.g., schools, public transport stops). Users can derive a range of metrics to compare different scenarios modeled. These include: catchment area versus circular buffer ratios; mean number of streets crossed; and

  3. Multi-scale analysis of a household level agent-based model of landcover change.

    PubMed

    Evans, Tom P; Kelley, Hugh

    2004-08-01

    Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition

  4. An Agent-Based Modeling Approach for Determining Corn Stover Removal Rate and Transboundary Effects

    NASA Astrophysics Data System (ADS)

    Gan, Jianbang; Langeveld, J. W. A.; Smith, C. T.

    2014-02-01

    Bioenergy production involves different agents with potentially different objectives, and an agent's decision often has transboundary impacts on other agents along the bioenergy value chain. Understanding and estimating the transboundary impacts is essential to portraying the interactions among the different agents and in the search for the optimal configuration of the bioenergy value chain. We develop an agent-based model to mimic the decision making by feedstock producers and feedstock-to-biofuel conversion plant operators and propose multipliers (i.e., ratios of economic values accruing to different segments and associated agents in the value chain) for assessing the transboundary impacts. Our approach is generic and thus applicable to a variety of bioenergy production systems at different sites and geographic scales. We apply it to the case of producing ethanol using corn stover in Iowa, USA. The results from the case study indicate that stover removal rate is site specific and varies considerably with soil type, as well as other factors, such as stover price and harvesting cost. In addition, ethanol production using corn stover in the study region would have strong positive ripple effects, with the values of multipliers varying with greenhouse gas price and national energy security premium. The relatively high multiplier values suggest that a large portion of the value associated with corn stover ethanol production would accrue to the downstream end of the value chain instead of stover producers.

  5. Policy design and performance of emissions trading markets: an adaptive agent-based analysis.

    PubMed

    Bing, Zhang; Qinqin, Yu; Jun, Bi

    2010-08-01

    Emissions trading is considered to be a cost-effective environmental economic instrument for pollution control. However, the pilot emissions trading programs in China have failed to bring remarkable success in the campaign for pollution control. The policy design of an emissions trading program is found to have a decisive impact on its performance. In this study, an artificial market for sulfur dioxide (SO2) emissions trading applying the agent-based model was constructed. The performance of the Jiangsu SO2 emissions trading market under different policy design scenario was also examined. Results show that the market efficiency of emissions trading is significantly affected by policy design and existing policies. China's coal-electricity price system is the principal factor influencing the performance of the SO2 emissions trading market. Transaction costs would also reduce market efficiency. In addition, current-level emissions discharge fee/tax and banking mechanisms do not distinctly affect policy performance. Thus, applying emissions trading in emission control in China should consider policy design and interaction with other existing policies.

  6. An agent-based hydroeconomic model to evaluate water policies in Jordan

    NASA Astrophysics Data System (ADS)

    Yoon, J.; Gorelick, S.

    2014-12-01

    Modern water systems can be characterized by a complex network of institutional and private actors that represent competing sectors and interests. Identifying solutions to enhance water security in such systems calls for analysis that can adequately account for this level of complexity and interaction. Our work focuses on the development of a hierarchical, multi-agent, hydroeconomic model that attempts to realistically represent complex interactions between hydrologic and multi-faceted human systems. The model is applied to Jordan, one of the most water-poor countries in the world. In recent years, the water crisis in Jordan has escalated due to an ongoing drought and influx of refugees from regional conflicts. We adopt a modular approach in which biophysical modules simulate natural and engineering phenomena, and human modules represent behavior at multiple scales of decision making. The human modules employ agent-based modeling, in which agents act as autonomous decision makers at the transboundary, state, organizational, and user levels. A systematic nomenclature and conceptual framework is used to characterize model agents and modules. Concepts from the Unified Modeling Language (UML) are adopted to promote clear conceptualization of model classes and process sequencing, establishing a foundation for full deployment of the integrated model in a scalable object-oriented programming environment. Although the framework is applied to the Jordanian water context, it is generalizable to other regional human-natural freshwater supply systems.

  7. Development and evaluation of liquid embolic agents based on liquid crystalline material of glyceryl monooleate.

    PubMed

    Du, Ling-Ran; Lu, Xiao-Jing; Guan, Hai-Tao; Yang, Yong-Jie; Gu, Meng-Jie; Zheng, Zhuo-Zhao; Lv, Tian-Shi; Yan, Zi-Guang; Song, Li; Zou, Ying-Hua; Fu, Nai-Qi; Qi, Xian-Rong; Fan, Tian-Yuan

    2014-08-25

    New type of liquid embolic agents based on a liquid crystalline material of glyceryl monooleate (GMO) was developed and evaluated in this study. Ternary phase diagram of GMO, water and ethanol was constructed and three isotropic liquids (ILs, GMO:ethanol:water=49:21:30, 60:20:20 and 72:18:10 (w/w/w)) were selected as potential liquid embolic agents, which could spontaneously form viscous gel cast when contacting with water or physiological fluid. The ILs exhibited excellent microcatheter deliverability due to low viscosity, and were proved to successfully block the saline flow when performed in a device to simulate embolization in vitro. The ILs also showed good cytocompatibility on L929 mouse fibroblast cell line. The embolization of ILs to rabbit kidneys was performed successfully under monitoring of digital subtraction angiography (DSA), and embolic degree was affected by the initial formulation composition and used volume. At 5th week after embolization, DSA and computed tomography (CT) confirmed the renal arteries embolized with IL did not recanalize in follow-up period, and an obvious atrophy of the embolized kidney was observed. Therefore, the GMO-based liquid embolic agents showed feasible and effective to embolize, and potential use in clinical interventional embolization therapy.

  8. Designing novel cellulase systems through agent-based modeling and global sensitivity analysis.

    PubMed

    Apte, Advait A; Senger, Ryan S; Fong, Stephen S

    2014-01-01

    Experimental techniques allow engineering of biological systems to modify functionality; however, there still remains a need to develop tools to prioritize targets for modification. In this study, agent-based modeling (ABM) was used to build stochastic models of complexed and non-complexed cellulose hydrolysis, including enzymatic mechanisms for endoglucanase, exoglucanase, and β-glucosidase activity. Modeling results were consistent with experimental observations of higher efficiency in complexed systems than non-complexed systems and established relationships between specific cellulolytic mechanisms and overall efficiency. Global sensitivity analysis (GSA) of model results identified key parameters for improving overall cellulose hydrolysis efficiency including: (1) the cellulase half-life, (2) the exoglucanase activity, and (3) the cellulase composition. Overall, the following parameters were found to significantly influence cellulose consumption in a consolidated bioprocess (CBP): (1) the glucose uptake rate of the culture, (2) the bacterial cell concentration, and (3) the nature of the cellulase enzyme system (complexed or non-complexed). Broadly, these results demonstrate the utility of combining modeling and sensitivity analysis to identify key parameters and/or targets for experimental improvement.

  9. An agent-based approach to modelling the effects of extreme events on global food prices

    NASA Astrophysics Data System (ADS)

    Schewe, Jacob; Otto, Christian; Frieler, Katja

    2015-04-01

    Extreme climate events such as droughts or heat waves affect agricultural production in major food producing regions and therefore can influence the price of staple foods on the world market. There is evidence that recent dramatic spikes in grain prices were at least partly triggered by actual and/or expected supply shortages. The reaction of the market to supply changes is however highly nonlinear and depends on complex and interlinked processes such as warehousing, speculation, and export restrictions. Here we present for the first time an agent-based modelling framework that accounts, in simplified terms, for these processes and allows to estimate the reaction of world food prices to supply shocks on a short (monthly) timescale. We test the basic model using observed historical supply, demand, and price data of wheat as a major food grain. Further, we illustrate how the model can be used in conjunction with biophysical crop models to assess the effect of future changes in extreme event regimes on the volatility of food prices. In particular, the explicit representation of storage dynamics makes it possible to investigate the potentially nonlinear interaction between simultaneous extreme events in different food producing regions, or between several consecutive events in the same region, which may both occur more frequently under future global warming.

  10. New Transfection Agents Based on Liposomes Containing Biosurfactant MEL-A

    PubMed Central

    Nakanishi, Mamoru; Inoh, Yoshikazu; Furuno, Tadahide

    2013-01-01

    Nano vectors are useful tools to deliver foreign DNAs, oligonucleotides, and small interfering double-stranded RNAs (siRNAs) into mammalian cells with gene transfection and gene regulation. In such experiments we have found the liposomes with a biosurfacant mannosylerythriol lipid (MEL-A) are useful because of their high transfer efficiency, and their unique mechanism to transfer genes to target cells with the lowest toxicity. In the present review we will describe our current work, which may contribute to the great advance of gene transfer to target cells and gene regulations. For more than two decades, the liposome technologies have changed dramatically and various methods have been proposed in the fields of biochemistry, cell biology, biotechnology, and so on. In addition, they were towards to pharmaceutics and clinical applications. The liposome technologies were expected to use gene therapy, however, they have not reached a requested goal as of yet. In the present paper we would like to present an approach using a biosurfactant, MEL-A, which is a surface-active compound produced by microorganisms growing on water-insoluble substrates and increases efficiency in gene transfection. The present work shows new transfection agents based on liposomes containing biosurfactant MEL-A. PMID:24300514

  11. Policy design and performance of emissions trading markets: an adaptive agent-based analysis.

    PubMed

    Bing, Zhang; Qinqin, Yu; Jun, Bi

    2010-08-01

    Emissions trading is considered to be a cost-effective environmental economic instrument for pollution control. However, the pilot emissions trading programs in China have failed to bring remarkable success in the campaign for pollution control. The policy design of an emissions trading program is found to have a decisive impact on its performance. In this study, an artificial market for sulfur dioxide (SO2) emissions trading applying the agent-based model was constructed. The performance of the Jiangsu SO2 emissions trading market under different policy design scenario was also examined. Results show that the market efficiency of emissions trading is significantly affected by policy design and existing policies. China's coal-electricity price system is the principal factor influencing the performance of the SO2 emissions trading market. Transaction costs would also reduce market efficiency. In addition, current-level emissions discharge fee/tax and banking mechanisms do not distinctly affect policy performance. Thus, applying emissions trading in emission control in China should consider policy design and interaction with other existing policies. PMID:20590153

  12. Buying on margin, selling short in an agent-based market model

    NASA Astrophysics Data System (ADS)

    Zhang, Ting; Li, Honggang

    2013-09-01

    Credit trading, or leverage trading, which includes buying on margin and selling short, plays an important role in financial markets, where agents tend to increase their leverages for increased profits. This paper presents an agent-based asset market model to study the effect of the permissive leverage level on traders’ wealth and overall market indicators. In this model, heterogeneous agents can assume fundamental value-converging expectations or trend-persistence expectations, and their effective demands of assets depend both on demand willingness and wealth constraints, where leverage can relieve the wealth constraints to some extent. The asset market price is determined by a market maker, who watches the market excess demand, and is influenced by noise factors. By simulations, we examine market results for different leverage ratios. At the individual level, we focus on how the leverage ratio influences agents’ wealth accumulation. At the market level, we focus on how the leverage ratio influences changes in the asset price, volatility, and trading volume. Qualitatively, our model provides some meaningful results supported by empirical facts. More importantly, we find a continuous phase transition as we increase the leverage threshold, which may provide a further prospective of credit trading.

  13. Modelling the Transport of Nanoparticles under Blood Flow using an Agent-based Approach

    PubMed Central

    Fullstone, Gavin; Wood, Jonathan; Holcombe, Mike; Battaglia, Giuseppe

    2015-01-01

    Blood-mediated nanoparticle delivery is a new and growing field in the development of therapeutics and diagnostics. Nanoparticle properties such as size, shape and surface chemistry can be controlled to improve their performance in biological systems. This enables modulation of immune system interactions, blood clearance profile and interaction with target cells, thereby aiding effective delivery of cargo within cells or tissues. Their ability to target and enter tissues from the blood is highly dependent on their behaviour under blood flow. Here we have produced an agent-based model of nanoparticle behaviour under blood flow in capillaries. We demonstrate that red blood cells are highly important for effective nanoparticle distribution within capillaries. Furthermore, we use this model to demonstrate how nanoparticle size can selectively target tumour tissue over normal tissue. We demonstrate that the polydispersity of nanoparticle populations is an important consideration in achieving optimal specificity and to avoid off-target effects. In future this model could be used for informing new nanoparticle design and to predict general and specific uptake properties under blood flow. PMID:26058969

  14. A Model of Rapid Radicalization Behavior Using Agent-Based Modeling and Quorum Sensing

    NASA Technical Reports Server (NTRS)

    Schwartz, Noah; Drucker, Nick; Campbell, Kenyth

    2012-01-01

    Understanding the dynamics of radicalization, especially rapid radicalization, has become increasingly important to US policy in the past several years. Traditionally, radicalization is considered a slow process, but recent social and political events demonstrate that the process can occur quickly. Examining this rapid process, in real time, is impossible. However, recreating an event using modeling and simulation (M&S) allows researchers to study some of the complex dynamics associated with rapid radicalization. We propose to adapt the biological mechanism of quorum sensing as a tool to explore, or possibly explain, rapid radicalization. Due to the complex nature of quorum sensing, M&S allows us to examine events that we could not otherwise examine in real time. For this study, we employ Agent Based Modeling (ABM), an M&S paradigm suited to modeling group behavior. The result of this study was the successful creation of rapid radicalization using quorum sensing. The Battle of Mogadishu was the inspiration for this model and provided the testing conditions used to explore quorum sensing and the ideas behind rapid radicalization. The final product has wider applicability however, using quorum sensing as a possible tool for examining other catalytic rapid radicalization events.

  15. Partner choice promotes cooperation: the two faces of testing with agent-based models.

    PubMed

    Campennì, Marco; Schino, Gabriele

    2014-03-01

    Reciprocity is one of the most debated among the mechanisms that have been proposed to explain the evolution of cooperation. While a distinction can be made between two general processes that can underlie reciprocation (within-pair temporal relations between cooperative events, and partner choice based on benefits received), theoretical modelling has concentrated on the former, while the latter has been often neglected. We developed a set of agent-based models in which agents adopted a strategy of obligate cooperation and partner choice based on benefits received. Our models tested the ability of partner choice both to reproduce significant emergent features of cooperation in group living animals and to promote the evolution of cooperation. Populations formed by agents adopting a strategy of obligate cooperation and partner choice based on benefits received showed differentiated "social relationships" and a positive correlation between cooperation given and received, two common phenomena in animal cooperation. When selection across multiple generations was added to the model, agents adopting a strategy of partner choice based on benefits received outperformed selfish agents that did not cooperate. Our results suggest partner choice is a significant aspect of cooperation and provides a possible mechanism for its evolution.

  16. Agent-based modeling of hyporheic dissolved organic carbon transport and transformation

    NASA Astrophysics Data System (ADS)

    Gabrielsen, P. J.; Wilson, J. L.; Pullin, M.

    2011-12-01

    Dissolved organic carbon (DOC) is a complex suite of organic compounds present in natural ecosystems, and is particularly studied in river and stream systems. The hyporheic zone (HZ), a region of surface water-shallow groundwater exchange, has been identified as a hotspot of DOC processing and is generally regarded as a net sink of organic matter. More recent studies into stream DOC have shifted to examining DOC quality rather than bulk quantity. DOC quality variability has been linked to hydrologic and climatic variability, both focuses of current climate change research. A new agent-based model in the NetLogo modeling environment couples hydrologic transport with chemical and biological transformation of DOC to simulate changing DOC quality in hyporheic flow. A pore-scale model implements a Lattice Boltzmann fluid dynamic model and surficial interactions to simulate sorption and microbial uptake. Upscaled to a stream meander scale, this model displays spatial variation and evolution of DOC quality. Model output metrics are correlated to field sample analytical results from a hyporheic meander of the East Fork Jemez River, Sandoval Co., NM.

  17. Agent Based Modeling of Atherosclerosis: A Concrete Help in Personalized Treatments

    NASA Astrophysics Data System (ADS)

    Pappalardo, Francesco; Cincotti, Alessandro; Motta, Alfredo; Pennisi, Marzio

    Atherosclerosis, a pathology affecting arterial blood vessels, is one of most common diseases of the developed countries. We present studies on the increased atherosclerosis risk using an agent based model of atherogenesis that has been previously validated using clinical data. It is well known that the major risk in atherosclerosis is the persistent high level of low density lipoprotein (LDL) concentration. However, it is not known if short period of high LDL concentration can cause irreversible damage and if reduction of the LDL concentration (either by life style or drug) can drastically or partially reduce the already acquired risk. We simulated four different clinical situations in a large set of virtual patients (200 per clinical scenario). In the first one the patients lifestyle maintains the concentration of LDL in a no risk range. This is the control case simulation. The second case is represented by patients having high level of LDL with a delay to apply appropriate treatments; The third scenario is characterized by patients with high LDL levels treated with specific drugs like statins. Finally we simulated patients that are characterized by several oxidative events (smoke, sedentary life style, assumption of alcoholic drinks and so on so forth) that effective increase the risk of LDL oxidation. Those preliminary results obviously need to be clinically investigated. It is clear, however, that SimAthero has the power to concretely help medical doctors and clinicians in choosing personalized treatments for the prevention of the atherosclerosis damages.

  18. BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology

    PubMed Central

    Gorochowski, Thomas E.; Matyjaszkiewicz, Antoni; Todd, Thomas; Oak, Neeraj; Kowalska, Kira; Reid, Stephen; Tsaneva-Atanasova, Krasimira T.

    2012-01-01

    Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI) recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher. PMID:22936991

  19. Provider dismissal policies and clustering of vaccine-hesitant families: an agent-based modeling approach.

    PubMed

    Buttenheim, Alison M; Cherng, Sarah T; Asch, David A

    2013-08-01

    Many pediatric practices have adopted vaccine policies that require parents who refuse to vaccinate according to the ACIP schedule to find another health care provider. Such policies may inadvertently cluster unvaccinated patients into practices that tolerate non vaccination or alternative schedules, turning them into risky pockets of low herd immunity. The objective of this study was to assess the effect of provider zero-tolerance vaccination policies on the clustering of intentionally unvaccinated children. We developed an agent-based model of parental vaccine hesitancy, provider non-vaccination tolerance, and selection of patients into pediatric practices. We ran 84 experiments across a range of parental hesitancy and provider tolerance scenarios. When the model is initialized, all providers accommodate refusals and intentionally unvaccinated children are evenly distributed across providers. As provider tolerance decreases, hesitant children become more clustered in a smaller number of practices and eventually are not able to find a practice that will accept them. Each of these effects becomes more pronounced as the level of hesitancy in the population rises. Heterogeneity in practice tolerance to vaccine-hesitant parents has the unintended result of concentrating susceptible individuals within a small number of tolerant practices, while providing little if any compensatory protection to adherent individuals. These externalities suggest an agenda for stricter policy regulation of individual practice decisions.

  20. Evaluating Infection Prevention Strategies in Out-Patient Dialysis Units Using Agent-Based Modeling.

    PubMed

    Wares, Joanna R; Lawson, Barry; Shemin, Douglas; D'Agata, Erika M C

    2016-01-01

    Patients receiving chronic hemodialysis (CHD) are among the most vulnerable to infections caused by multidrug-resistant organisms (MDRO), which are associated with high rates of morbidity and mortality. Current guidelines to reduce transmission of MDRO in the out-patient dialysis unit are targeted at patients considered to be high-risk for transmitting these organisms: those with infected skin wounds not contained by a dressing, or those with fecal incontinence or uncontrolled diarrhea. Here, we hypothesize that targeting patients receiving antimicrobial treatment would more effectively reduce transmission and acquisition of MDRO. We also hypothesize that environmental contamination plays a role in the dissemination of MDRO in the dialysis unit. To address our hypotheses, we built an agent-based model to simulate different treatment strategies in a dialysis unit. Our results suggest that reducing antimicrobial treatment, either by reducing the number of patients receiving treatment or by reducing the duration of the treatment, markedly reduces overall colonization rates and also the levels of environmental contamination in the dialysis unit. Our results also suggest that improving the environmental decontamination efficacy between patient dialysis treatments is an effective method for reducing colonization and contamination rates. These findings have important implications for the development and implementation of future infection prevention strategies. PMID:27195984

  1. A Framework for Model-Based Inquiry Through Agent-Based Programming

    NASA Astrophysics Data System (ADS)

    Xiang, Lin; Passmore, Cynthia

    2015-04-01

    There has been increased recognition in the past decades that model-based inquiry (MBI) is a promising approach for cultivating deep understandings by helping students unite phenomena and underlying mechanisms. Although multiple technology tools have been used to improve the effectiveness of MBI, there are not enough detailed examinations of how agent-based programmable modeling (ABPM) tools influence students' MBI learning. The present collective case study sought to contribute by closely investigating ABPM-supported MBI processes for 8th grade students learning about natural selection and adaptation. Eight 8th grade students in groups of 2-3 spent 15 h during a span of 4 weeks collaboratively programming simulations of adaptation based on the natural selection model, using an ABPM tool named NetLogo. The entire programming processes of these learning groups, up to 50 h, were videotaped and then analyzed using mixed methods. Our analysis revealed that the programming task created a context that calls for nine types of MBI actions. These MBI actions were related to both phenomena and the underlying model. Results also showed that students' programming processes took place in consecutive programming cycles and aligned with iterative MBI cycles. A framework for ABPM-supported MBI learning is proposed based upon the findings. Implications in developing MBI instruction involving ABPM tools are discussed.

  2. Fortune favours the bold: an agent-based model reveals adaptive advantages of overconfidence in war.

    PubMed

    Johnson, Dominic D P; Weidmann, Nils B; Cederman, Lars-Erik

    2011-01-01

    Overconfidence has long been considered a cause of war. Like other decision-making biases, overconfidence seems detrimental because it increases the frequency and costs of fighting. However, evolutionary biologists have proposed that overconfidence may also confer adaptive advantages: increasing ambition, resolve, persistence, bluffing opponents, and winning net payoffs from risky opportunities despite occasional failures. We report the results of an agent-based model of inter-state conflict, which allows us to evaluate the performance of different strategies in competition with each other. Counter-intuitively, we find that overconfident states predominate in the population at the expense of unbiased or underconfident states. Overconfident states win because: (1) they are more likely to accumulate resources from frequent attempts at conquest; (2) they are more likely to gang up on weak states, forcing victims to split their defences; and (3) when the decision threshold for attacking requires an overwhelming asymmetry of power, unbiased and underconfident states shirk many conflicts they are actually likely to win. These "adaptive advantages" of overconfidence may, via selection effects, learning, or evolved psychology, have spread and become entrenched among modern states, organizations and decision-makers. This would help to explain the frequent association of overconfidence and war, even if it no longer brings benefits today.

  3. Agent-based model with multi-level herding for complex financial systems

    NASA Astrophysics Data System (ADS)

    Chen, Jun-Jie; Tan, Lei; Zheng, Bo

    2015-02-01

    In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

  4. Agent-based model with multi-level herding for complex financial systems.

    PubMed

    Chen, Jun-Jie; Tan, Lei; Zheng, Bo

    2015-02-11

    In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

  5. Agent-based model with multi-level herding for complex financial systems

    PubMed Central

    Chen, Jun-Jie; Tan, Lei; Zheng, Bo

    2015-01-01

    In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

  6. A standard protocol for describing individual-based and agent-based models

    USGS Publications Warehouse

    Grimm, Volker; Berger, Uta; Bastiansen, Finn; Eliassen, Sigrunn; Ginot, Vincent; Giske, Jarl; Goss-Custard, John; Grand, Tamara; Heinz, Simone K.; Huse, Geir; Huth, Andreas; Jepsen, Jane U.; Jorgensen, Christian; Mooij, Wolf M.; Muller, Birgit; Pe'er, Guy; Piou, Cyril; Railsback, Steven F.; Robbins, Andrew M.; Robbins, Martha M.; Rossmanith, Eva; Ruger, Nadja; Strand, Espen; Souissi, Sami; Stillman, Richard A.; Vabo, Rune; Visser, Ute; DeAngelis, Donald L.

    2006-01-01

    Simulation models that describe autonomous individual organisms (individual based models, IBM) or agents (agent-based models, ABM) have become a widely used tool, not only in ecology, but also in many other disciplines dealing with complex systems made up of autonomous entities. However, there is no standard protocol for describing such simulation models, which can make them difficult to understand and to duplicate. This paper presents a proposed standard protocol, ODD, for describing IBMs and ABMs, developed and tested by 28 modellers who cover a wide range of fields within ecology. This protocol consists of three blocks (Overview, Design concepts, and Details), which are subdivided into seven elements: Purpose, State variables and scales, Process overview and scheduling, Design concepts, Initialization, Input, and Submodels. We explain which aspects of a model should be described in each element, and we present an example to illustrate the protocol in use. In addition, 19 examples are available in an Online Appendix. We consider ODD as a first step for establishing a more detailed common format of the description of IBMs and ABMs. Once initiated, the protocol will hopefully evolve as it becomes used by a sufficiently large proportion of modellers.

  7. Impact of road environment on drivers' behaviors in dilemma zone: Application of agent-based simulation.

    PubMed

    Kim, Sojung; Son, Young-Jun; Chiu, Yi-Chang; Jeffers, Mary Anne B; Yang, C Y David

    2016-11-01

    At a signalized intersection, there exists an area where drivers become indecisive as to either stop their car or proceed through when the traffic signal turns yellow. This point, called a dilemma zone, has remained a safety concern for drivers due to the great possibility of a rear-end or right-angle crash occurring. In order to reduce the risk of car crashes at the dilemma zone, Institute of Transportation Engineers (ITE) recommended a dilemma zone model. The model, however, fails to provide precise calculations on the decision of drivers because it disregards the supplemental roadway information, such as whether a red light camera is present. Hence, the goal of this study was to incorporate such roadway environmental factors into a more realistic driver decision-making model for the dilemma zone. A driving simulator was used to determine the influence of roadway conditions on decision-making of real drivers. Following data collection, each driver's decision outcomes were implemented in an Agent-Based Simulation (ABS) so as to analyze behaviors under realistic road environments. The experimental results revealed that the proposed dilemma zone model was able to accurately predict the decisions of drivers. Specifically, the model confirmed the findings from the driving simulator study that the changes in the roadway environment reduced the number of red light violations at an intersection.

  8. Physics and financial economics (1776-2014): puzzles, Ising and agent-based models.

    PubMed

    Sornette, Didier

    2014-06-01

    This short review presents a selected history of the mutual fertilization between physics and economics--from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistical physics. Recent extensions in terms of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it did not cover the dynamical field of agent-based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the 'Emerging Intelligence Market Hypothesis' to reconcile the pervasive presence of 'noise traders' with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets. PMID:24875470

  9. Retail Location Choice with Complementary Goods: An Agent-Based Model

    NASA Astrophysics Data System (ADS)

    Huang, Arthur; Levinson, David

    This paper models the emergence of retail clusters on a supply chain network comprised of suppliers, retailers, and consumers. Firstly, an agent-based model is proposed to investigate retail location distribution in a market of two complementary goods. The methodology controls for supplier locales and unit sales prices of retailers and suppliers, and a consumer’s willingness to patronize a retailer depends on the total travel distance of buying both goods. On a circle comprised of discrete locations, retailers play a non-cooperative game of location choice to maximize individual profits. Our findings suggest that the probability distribution of the number of clusters in equilibrium follows power law and that hierarchical distribution patterns are much more likely to occur than the spread-out ones. In addition, retailers of complementary goods tend to co-locate at supplier locales. Sensitivity tests on the number of retailers are also performed. Secondly, based on the County Business Patterns (CBP) data of Minneapolis-St. Paul from US Census 2000 database, we find that the number of clothing stores and the distribution of food stores at the zip code level follows power-law distribution.

  10. Combining Bayesian Networks and Agent Based Modeling to develop a decision-support model in Vietnam

    NASA Astrophysics Data System (ADS)

    Nong, Bao Anh; Ertsen, Maurits; Schoups, Gerrit

    2016-04-01

    Complexity and uncertainty in natural resources management have been focus themes in recent years. Within these debates, with the aim to define an approach feasible for water management practice, we are developing an integrated conceptual modeling framework for simulating decision-making processes of citizens, in our case in the Day river area, Vietnam. The model combines Bayesian Networks (BNs) and Agent-Based Modeling (ABM). BNs are able to combine both qualitative data from consultants / experts / stakeholders, and quantitative data from observations on different phenomena or outcomes from other models. Further strengths of BNs are that the relationship between variables in the system is presented in a graphical interface, and that components of uncertainty are explicitly related to their probabilistic dependencies. A disadvantage is that BNs cannot easily identify the feedback of agents in the system once changes appear. Hence, ABM was adopted to represent the reaction among stakeholders under changes. The modeling framework is developed as an attempt to gain better understanding about citizen's behavior and factors influencing their decisions in order to reduce uncertainty in the implementation of water management policy.

  11. Quantitative Agent Based Model of Opinion Dynamics: Polish Elections of 2015.

    PubMed

    Sobkowicz, Pawel

    2016-01-01

    We present results of an abstract, agent based model of opinion dynamics simulations based on the emotion/information/opinion (E/I/O) approach, applied to a strongly polarized society, corresponding to the Polish political scene between 2005 and 2015. Under certain conditions the model leads to metastable coexistence of two subcommunities of comparable size (supporting the corresponding opinions)-which corresponds to the bipartisan split found in Poland. Spurred by the recent breakdown of this political duopoly, which occurred in 2015, we present a model extension that describes both the long term coexistence of the two opposing opinions and a rapid, transitory change due to the appearance of a third party alternative. We provide quantitative comparison of the model with the results of polls and elections in Poland, testing the assumptions related to the modeled processes and the parameters used in the simulations. It is shown, that when the propaganda messages of the two incumbent parties differ in emotional tone, the political status quo may be unstable. The asymmetry of the emotions within the support bases of the two parties allows one of them to be 'invaded' by a newcomer third party very quickly, while the second remains immune to such invasion.

  12. Agent-Based Spatiotemporal Simulation of Biomolecular Systems within the Open Source MASON Framework

    PubMed Central

    Pérez-Rodríguez, Gael; Pérez-Pérez, Martín; Glez-Peña, Daniel; Azevedo, Nuno F.; Lourenço, Anália

    2015-01-01

    Agent-based modelling is being used to represent biological systems with increasing frequency and success. This paper presents the implementation of a new tool for biomolecular reaction modelling in the open source Multiagent Simulator of Neighborhoods framework. The rationale behind this new tool is the necessity to describe interactions at the molecular level to be able to grasp emergent and meaningful biological behaviour. We are particularly interested in characterising and quantifying the various effects that facilitate biocatalysis. Enzymes may display high specificity for their substrates and this information is crucial to the engineering and optimisation of bioprocesses. Simulation results demonstrate that molecule distributions, reaction rate parameters, and structural parameters can be adjusted separately in the simulation allowing a comprehensive study of individual effects in the context of realistic cell environments. While higher percentage of collisions with occurrence of reaction increases the affinity of the enzyme to the substrate, a faster reaction (i.e., turnover number) leads to a smaller number of time steps. Slower diffusion rates and molecular crowding (physical hurdles) decrease the collision rate of reactants, hence reducing the reaction rate, as expected. Also, the random distribution of molecules affects the results significantly. PMID:25874228

  13. BSim: an agent-based tool for modeling bacterial populations in systems and synthetic biology.

    PubMed

    Gorochowski, Thomas E; Matyjaszkiewicz, Antoni; Todd, Thomas; Oak, Neeraj; Kowalska, Kira; Reid, Stephen; Tsaneva-Atanasova, Krasimira T; Savery, Nigel J; Grierson, Claire S; di Bernardo, Mario

    2012-01-01

    Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI) recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher. PMID:22936991

  14. A dynamic agent-based analysis for the environmental impacts of conventional and novel book retailing.

    PubMed

    Xu, Ming; Allenby, Braden; Kim, Junbeum; Kahhat, Ramzy

    2009-04-15

    The dynamics of an e-commerce market and the associated environmental impacts from a bottom-up perspective using an agent-based model is explored. A conceptual meta-theory from psychology is adopted to form the behavioral rules of artificial consumers choosing different methods of buying a book, including conventional bookstores, e-commerce, and a proposed self-pick-up option. Given the energy and emissions savings that result from a shift to e-commerce from bookstore purchase, it appears that reductions in environmental impacts are relatively probable. Additionally, our results suggest that the shift to e-commerce is mainly due to the growth of Internet users, which ties energy and emissions savings to Internet penetration. Moreover, under any scenario, the energy and emissions savings will be provided by the introduction of the proposed self-pick-up option. Our model thus provides insights into market behaviors and related environmental impacts of the growing use of e-commerce systems at the retail level, and provides a basis for the development and implementation of more sustainable policies and practices.

  15. A CSP-Based Agent Modeling Framework for the Cougaar Agent-Based Architecture

    NASA Technical Reports Server (NTRS)

    Gracanin, Denis; Singh, H. Lally; Eltoweissy, Mohamed; Hinchey, Michael G.; Bohner, Shawn A.

    2005-01-01

    Cognitive Agent Architecture (Cougaar) is a Java-based architecture for large-scale distributed agent-based applications. A Cougaar agent is an autonomous software entity with behaviors that represent a real-world entity (e.g., a business process). A Cougaar-based Model Driven Architecture approach, currently under development, uses a description of system's functionality (requirements) to automatically implement the system in Cougaar. The Communicating Sequential Processes (CSP) formalism is used for the formal validation of the generated system. Two main agent components, a blackboard and a plugin, are modeled as CSP processes. A set of channels represents communications between the blackboard and individual plugins. The blackboard is represented as a CSP process that communicates with every agent in the collection. The developed CSP-based Cougaar modeling framework provides a starting point for a more complete formal verification of the automatically generated Cougaar code. Currently it is used to verify the behavior of an individual agent in terms of CSP properties and to analyze the corresponding Cougaar society.

  16. Physics and financial economics (1776-2014): puzzles, Ising and agent-based models

    NASA Astrophysics Data System (ADS)

    Sornette, Didier

    2014-06-01

    This short review presents a selected history of the mutual fertilization between physics and economics—from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistical physics. Recent extensions in terms of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it did not cover the dynamical field of agent-based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the ‘Emerging Intelligence Market Hypothesis’ to reconcile the pervasive presence of ‘noise traders’ with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets.

  17. iMuseumA: an agent-based context-aware intelligent museum system.

    PubMed

    Ayala, Inmaculada; Amor, Mercedes; Pinto, Mónica; Fuentes, Lidia; Gámez, Nadia

    2014-11-10

    Currently, museums provide their visitors with interactive tour guide applications that can be installed in mobile devices and provide timely tailor-made multimedia information about exhibits on display. In this paper, we argue that mobile devices not only could provide help to visitors, but also to museum staff. Our goal is to integrate, within the same system, multimedia tour guides with the management facilities required by museums. In this paper, we present iMuseumA (intelligent museum with agents), a mobile-based solution to customize visits and perform context-aware management tasks. iMuseumA follows an agent-based approach, which makes it possible to interact easily with the museum environment and make decisions based on its current status. This system is currently deployed in the Museum of Informatics at the Informatics School of the University of Málaga, and its main contributions are: (i) a mobile application that provides management facilities to museum staff by means of sensing and processing environmental data; (ii) providing an integrated solution for visitors, tour guides and museum staff that allows coordination and communication enrichment among different groups of users; (iii) using and benefiting from group communication for heterogeneous groups of users that can be created on demand.

  18. Development and evaluation of liquid embolic agents based on liquid crystalline material of glyceryl monooleate.

    PubMed

    Du, Ling-Ran; Lu, Xiao-Jing; Guan, Hai-Tao; Yang, Yong-Jie; Gu, Meng-Jie; Zheng, Zhuo-Zhao; Lv, Tian-Shi; Yan, Zi-Guang; Song, Li; Zou, Ying-Hua; Fu, Nai-Qi; Qi, Xian-Rong; Fan, Tian-Yuan

    2014-08-25

    New type of liquid embolic agents based on a liquid crystalline material of glyceryl monooleate (GMO) was developed and evaluated in this study. Ternary phase diagram of GMO, water and ethanol was constructed and three isotropic liquids (ILs, GMO:ethanol:water=49:21:30, 60:20:20 and 72:18:10 (w/w/w)) were selected as potential liquid embolic agents, which could spontaneously form viscous gel cast when contacting with water or physiological fluid. The ILs exhibited excellent microcatheter deliverability due to low viscosity, and were proved to successfully block the saline flow when performed in a device to simulate embolization in vitro. The ILs also showed good cytocompatibility on L929 mouse fibroblast cell line. The embolization of ILs to rabbit kidneys was performed successfully under monitoring of digital subtraction angiography (DSA), and embolic degree was affected by the initial formulation composition and used volume. At 5th week after embolization, DSA and computed tomography (CT) confirmed the renal arteries embolized with IL did not recanalize in follow-up period, and an obvious atrophy of the embolized kidney was observed. Therefore, the GMO-based liquid embolic agents showed feasible and effective to embolize, and potential use in clinical interventional embolization therapy. PMID:24858389

  19. Can human-like Bots control collective mood: agent-based simulations of online chats

    NASA Astrophysics Data System (ADS)

    Tadić, Bosiljka; Šuvakov, Milovan

    2013-10-01

    Using an agent-based modeling approach, in this paper, we study self-organized dynamics of interacting agents in the presence of chat Bots. Different Bots with tunable ‘human-like’ attributes, which exchange emotional messages with agents, are considered, and the collective emotional behavior of agents is quantitatively analyzed. In particular, using detrended fractal analysis we determine persistent fluctuations and temporal correlations in time series of agent activity and statistics of avalanches carrying emotional messages of agents when Bots favoring positive/negative affects are active. We determine the impact of Bots and identify parameters that can modulate that impact. Our analysis suggests that, by these measures, the emotional Bots induce collective emotion among interacting agents by suitably altering the fractal characteristics of the underlying stochastic process. Positive emotion Bots are slightly more effective than negative emotion Bots. Moreover, Bots which periodically alternate between positive and negative emotion can enhance fluctuations in the system, leading to avalanches of agent messages that are reminiscent of self-organized critical states.

  20. The Influence of Seasonal Forecast Accuracy on Farmer Behavior: An Agent-Based Modeling Approach

    NASA Astrophysics Data System (ADS)

    Jacobi, J. H.; Nay, J.; Gilligan, J. M.

    2013-12-01

    Seasonal climates dictate the livelihoods of farmers in developing countries. While farmers in developed countries often have seasonal forecasts on which to base their cropping decisions, developing world farmers usually make plans for the season without such information. Climate change increases the seasonal uncertainty, making things more difficult for farmers. Providing seasonal forecasts to these farmers is seen as a way to help buffer these typically marginal groups from the effects of climate change, though how to do so and the efficacy of such an effort is still uncertain. In Sri Lanka, an effort is underway to provide such forecasts to farmers. The accuracy of these forecasts is likely to have large impacts on how farmers accept and respond to the information they receive. We present an agent-based model to explore how the accuracy of seasonal rainfall forecasts affects the growing decisions and behavior of farmers in Sri Lanka. Using a decision function based on prospect theory, this model simulates farmers' behavior in the face of a wet, dry, or normal forecast. Farmers can either choose to grow paddy rice or plant a cash crop. Prospect theory is used to evaluate outcomes of the growing season; the farmer's memory of the level of success under a certain set of conditions affects next season's decision. Results from this study have implications for policy makers and seasonal forecasters.

  1. An Exploratory Study of the Butterfly Effect Using Agent-Based Modeling

    NASA Technical Reports Server (NTRS)

    Khasawneh, Mahmoud T.; Zhang, Jun; Shearer, Nevan E. N.; Rodriquez-Velasquez, Elkin; Bowling, Shannon R.

    2010-01-01

    This paper provides insights about the behavior of chaotic complex systems, and the sensitive dependence of the system on the initial starting conditions. How much does a small change in the initial conditions of a complex system affect it in the long term? Do complex systems exhibit what is called the "Butterfly Effect"? This paper uses an agent-based modeling approach to address these questions. An existing model from NetLogo library was extended in order to compare chaotic complex systems with near-identical initial conditions. Results show that small changes in initial starting conditions can have a huge impact on the behavior of chaotic complex systems. The term the "butterfly effect" is attributed to the work of Edward Lorenz [1]. It is used to describe the sensitive dependence of the behavior of chaotic complex systems on the initial conditions of these systems. The metaphor refers to the notion that a butterfly flapping its wings somewhere may cause extreme changes in the ecological system's behavior in the future, such as a hurricane.

  2. iMuseumA: An Agent-Based Context-Aware Intelligent Museum System

    PubMed Central

    Ayala, Inmaculada; Amor, Mercedes; Pinto, Mónica; Fuentes, Lidia; Gámez, Nadia

    2014-01-01

    Currently, museums provide their visitors with interactive tour guide applications that can be installed in mobile devices and provide timely tailor-made multimedia information about exhibits on display. In this paper, we argue that mobile devices not only could provide help to visitors, but also to museum staff. Our goal is to integrate, within the same system, multimedia tour guides with the management facilities required by museums. In this paper, we present iMuseumA (intelligent museum with agents), a mobile-based solution to customize visits and perform context-aware management tasks. iMuseumA follows an agent-based approach, which makes it possible to interact easily with the museum environment and make decisions based on its current status. This system is currently deployed in the Museum of Informatics at the Informatics School of the University of Málaga, and its main contributions are: (i) a mobile application that provides management facilities to museum staff by means of sensing and processing environmental data; (ii) providing an integrated solution for visitors, tour guides and museum staff that allows coordination and communication enrichment among different groups of users; (iii) using and benefiting from group communication for heterogeneous groups of users that can be created on demand. PMID:25390409

  3. Study of the attractor structure of an agent-based sociological model

    NASA Astrophysics Data System (ADS)

    Timpanaro, André M.; Prado, Carmen P. C.

    2011-03-01

    The Sznajd model is a sociophysics model that is based in the Potts model, and used for describing opinion propagation in a society. It employs an agent-based approach and interaction rules favouring pairs of agreeing agents. It has been successfully employed in modeling some properties and scale features of both proportional and majority elections (see for instance the works of A. T. Bernardes and R. N. Costa Filho), but its stationary states are always consensus states. In order to explain more complicated behaviours, we have modified the bounded confidence idea (introduced before in other opinion models, like the Deffuant model), with the introduction of prejudices and biases (we called this modification confidence rules), and have adapted it to the discrete Sznajd model. This generalized Sznajd model is able to reproduce almost all of the previous versions of the Sznajd model, by using appropriate choices of parameters. We solved the attractor structure of the resulting model in a mean-field approach and made Monte Carlo simulations in a Barabási-Albert network. These simulations show great similarities with the mean-field, for the tested cases of 3 and 4 opinions. The dynamical systems approach that we devised allows for a deeper understanding of the potential of the Sznajd model as an opinion propagation model and can be easily extended to other models, like the voter model. Our modification of the bounded confidence rule can also be readily applied to other opinion propagation models.

  4. Agent-Based Crowd Simulation Considering Emotion Contagion for Emergency Evacuation Problem

    NASA Astrophysics Data System (ADS)

    Faroqi, H.; Mesgari, M.-S.

    2015-12-01

    During emergencies, emotions greatly affect human behaviour. For more realistic multi-agent systems in simulations of emergency evacuations, it is important to incorporate emotions and their effects on the agents. In few words, emotional contagion is a process in which a person or group influences the emotions or behavior of another person or group through the conscious or unconscious induction of emotion states and behavioral attitudes. In this study, we simulate an emergency situation in an open square area with three exits considering Adults and Children agents with different behavior. Also, Security agents are considered in order to guide Adults and Children for finding the exits and be calm. Six levels of emotion levels are considered for each agent in different scenarios and situations. The agent-based simulated model initialize with the random scattering of agent populations and then when an alarm occurs, each agent react to the situation based on its and neighbors current circumstances. The main goal of each agent is firstly to find the exit, and then help other agents to find their ways. Numbers of exited agents along with their emotion levels and damaged agents are compared in different scenarios with different initialization in order to evaluate the achieved results of the simulated model. NetLogo 5.2 is used as the multi-agent simulation framework with R language as the developing language.

  5. Coevolution of risk perception, sexual behaviour, and HIV transmission in an agent-based model.

    PubMed

    Tully, Stephen; Cojocaru, Monica; Bauch, Chris T

    2013-11-21

    Risk perception shapes individual behaviour, and is in turn shaped by the consequences of that behaviour. Here we explore this dynamics in the context of human immunodeficiency virus (HIV) spread. We construct a simplified agent-based model based on a partner selection game, where individuals are paired with others in the population, and through a decision tree, agree on unprotected sex, protected sex, or no sex. An individual's choice is conditioned on their HIV status, their perceived population-level HIV prevalence, and the preferences expressed by the individual with whom they are paired. HIV is transmitted during unprotected sex with a certain probability. As expected, in model simulations, the perceived population-level HIV prevalence climbs along with actual HIV prevalence. During this time, HIV- individuals increasingly switch from unprotected sex to protected sex, HIV+ individuals continue practicing unprotected sex whenever possible, and unprotected sex between HIV+ and HIV- individuals eventually becomes rare. We also find that the perceived population-level HIV prevalence diverges according to HIV status: HIV- individuals develop a higher perceived HIV prevalence than HIV+ individuals, although this result is sensitive to how much information is derived from global versus local sources. This research illustrates a potential mechanism by which distinct groups, as defined by their sexual behaviour, HIV status, and risk perceptions, can emerge through coevolution of HIV transmission and risk perception dynamics. PMID:23988796

  6. Mesoscopic Effects in an Agent-Based Bargaining Model in Regular Lattices

    PubMed Central

    Poza, David J.; Santos, José I.; Galán, José M.; López-Paredes, Adolfo

    2011-01-01

    The effect of spatial structure has been proved very relevant in repeated games. In this work we propose an agent based model where a fixed finite population of tagged agents play iteratively the Nash demand game in a regular lattice. The model extends the multiagent bargaining model by Axtell, Epstein and Young [1] modifying the assumption of global interaction. Each agent is endowed with a memory and plays the best reply against the opponent's most frequent demand. We focus our analysis on the transient dynamics of the system, studying by computer simulation the set of states in which the system spends a considerable fraction of the time. The results show that all the possible persistent regimes in the global interaction model can also be observed in this spatial version. We also find that the mesoscopic properties of the interaction networks that the spatial distribution induces in the model have a significant impact on the diffusion of strategies, and can lead to new persistent regimes different from those found in previous research. In particular, community structure in the intratype interaction networks may cause that communities reach different persistent regimes as a consequence of the hindering diffusion effect of fluctuating agents at their borders. PMID:21408019

  7. Agent-based modeling approach of immune defense against spores of opportunistic human pathogenic fungi.

    PubMed

    Tokarski, Christian; Hummert, Sabine; Mech, Franziska; Figge, Marc Thilo; Germerodt, Sebastian; Schroeter, Anja; Schuster, Stefan

    2012-01-01

    Opportunistic human pathogenic fungi like the ubiquitous fungus Aspergillus fumigatus are a major threat to immunocompromised patients. An impaired immune system renders the body vulnerable to invasive mycoses that often lead to the death of the patient. While the number of immunocompromised patients is rising with medical progress, the process, and dynamics of defense against invaded and ready to germinate fungal conidia are still insufficiently understood. Besides macrophages, neutrophil granulocytes form an important line of defense in that they clear conidia. Live imaging shows the interaction of those phagocytes and conidia as a dynamic process of touching, dragging, and phagocytosis. To unravel strategies of phagocytes on the hunt for conidia an agent-based modeling approach is used, implemented in NetLogo. Different modes of movement of phagocytes are tested regarding their clearing efficiency: random walk, short-term persistence in their recent direction, chemotaxis of chemokines excreted by conidia, and communication between phagocytes. While the short-term persistence hunting strategy turned out to be superior to the simple random walk, following a gradient of chemokines released by conidial agents is even better. The advantage of communication between neutrophilic agents showed a strong dependency on the spatial scale of the focused area and the distribution of the pathogens.

  8. An agent-based model of stock markets incorporating momentum investors

    NASA Astrophysics Data System (ADS)

    Wei, J. R.; Huang, J. P.; Hui, P. M.

    2013-06-01

    It has been widely accepted that there exist investors who adopt momentum strategies in real stock markets. Understanding the momentum behavior is of both academic and practical importance. For this purpose, we propose and study a simple agent-based model of trading incorporating momentum investors and random investors. The random investors trade randomly all the time. The momentum investors could be idle, buying or selling, and they decide on their action by implementing an action threshold that assesses the most recent price movement. The model is able to reproduce some of the stylized facts observed in real markets, including the fat-tails in returns, weak long-term correlation and scaling behavior in the kurtosis of returns. An analytic treatment of the model relates the model parameters to several quantities that can be extracted from real data sets. To illustrate how the model can be applied, we show that real market data can be used to constrain the model parameters, which in turn provide information on the behavior of momentum investors in different markets.

  9. Mechanisms of self-organization and finite size effects in a minimal agent based model

    NASA Astrophysics Data System (ADS)

    Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

    2009-03-01

    We present a detailed analysis of the self-organization phenomenon in which the stylized facts originate from finite size effects with respect to the number of agents considered and disappear in the limit of an infinite population. By introducing the possibility that agents can enter or leave the market depending on the behavior of the price, it is possible to show that the system self-organizes in a regime with a finite number of agents which corresponds to the stylized facts. The mechanism for entering or leaving the market is based on the idea that a too stable market is unappealing for traders, while the presence of price movements attracts agents to enter and speculate on the market. We show that this mechanism is also compatible with the idea that agents are scared by a noisy and risky market at shorter timescales. We also show that the mechanism for self-organization is robust with respect to variations of the exit/entry rules and that the attempt to trigger the system to self-organize in a region without stylized facts leads to an unrealistic dynamics. We study the self-organization in a specific agent based model but we believe that the basic ideas should be of general validity.

  10. Physics and financial economics (1776-2014): puzzles, Ising and agent-based models.

    PubMed

    Sornette, Didier

    2014-06-01

    This short review presents a selected history of the mutual fertilization between physics and economics--from Isaac Newton and Adam Smith to the present. The fundamentally different perspectives embraced in theories developed in financial economics compared with physics are dissected with the examples of the volatility smile and of the excess volatility puzzle. The role of the Ising model of phase transitions to model social and financial systems is reviewed, with the concepts of random utilities and the logit model as the analog of the Boltzmann factor in statistical physics. Recent extensions in terms of quantum decision theory are also covered. A wealth of models are discussed briefly that build on the Ising model and generalize it to account for the many stylized facts of financial markets. A summary of the relevance of the Ising model and its extensions is provided to account for financial bubbles and crashes. The review would be incomplete if it did not cover the dynamical field of agent-based models (ABMs), also known as computational economic models, of which the Ising-type models are just special ABM implementations. We formulate the 'Emerging Intelligence Market Hypothesis' to reconcile the pervasive presence of 'noise traders' with the near efficiency of financial markets. Finally, we note that evolutionary biology, more than physics, is now playing a growing role to inspire models of financial markets.

  11. Price dynamics and market power in an agent-based power exchange

    NASA Astrophysics Data System (ADS)

    Cincotti, Silvano; Guerci, Eric; Raberto, Marco

    2005-05-01

    This paper presents an agent-based model of a power exchange. Supply of electric power is provided by competing generating companies, whereas demand is assumed to be inelastic with respect to price and is constant over time. The transmission network topology is assumed to be a fully connected graph and no transmission constraints are taken into account. The price formation process follows a common scheme for real power exchanges: a clearing house mechanism with uniform price, i.e., with price set equal across all matched buyer-seller pairs. A single class of generating companies is considered, characterized by linear cost function for each technology. Generating companies compete for the sale of electricity through repeated rounds of the uniform auction and determine their supply functions according to production costs. However, an individual reinforcement learning algorithm characterizes generating companies behaviors in order to attain the expected maximum possible profit in each auction round. The paper investigates how the market competitive equilibrium is affected by market microstructure and production costs.

  12. Parallel Agent-Based Simulations on Clusters of GPUs and Multi-Core Processors

    SciTech Connect

    Aaby, Brandon G; Perumalla, Kalyan S; Seal, Sudip K

    2010-01-01

    An effective latency-hiding mechanism is presented in the parallelization of agent-based model simulations (ABMS) with millions of agents. The mechanism is designed to accommodate the hierarchical organization as well as heterogeneity of current state-of-the-art parallel computing platforms. We use it to explore the computation vs. communication trade-off continuum available with the deep computational and memory hierarchies of extant platforms and present a novel analytical model of the tradeoff. We describe our implementation and report preliminary performance results on two distinct parallel platforms suitable for ABMS: CUDA threads on multiple, networked graphical processing units (GPUs), and pthreads on multi-core processors. Message Passing Interface (MPI) is used for inter-GPU as well as inter-socket communication on a cluster of multiple GPUs and multi-core processors. Results indicate the benefits of our latency-hiding scheme, delivering as much as over 100-fold improvement in runtime for certain benchmark ABMS application scenarios with several million agents. This speed improvement is obtained on our system that is already two to three orders of magnitude faster on one GPU than an equivalent CPU-based execution in a popular simulator in Java. Thus, the overall execution of our current work is over four orders of magnitude faster when executed on multiple GPUs.

  13. Distributed Multi-Agent-Based Protection Scheme for Transient Stability Enhancement in Power Systems

    NASA Astrophysics Data System (ADS)

    Rahman, M. S.; Mahmud, M. A.; Pota, H. R.; Hossain, M. J.; Orchi, T. F.

    2015-04-01

    This paper presents a new distributed agent-based scheme to enhance the transient stability of power systems by maintaining phase angle cohesiveness of interconnected generators through proper relay coordination with critical clearing time (CCT) information. In this distributed multi-agent infrastructure, intelligent agents represent various physical device models to provide dynamic information and energy flow among different physical processes of power systems. The agents can communicate with each other in a distributed manner with a final aim to control circuit breakers (CBs) with CCT information as this is the key issue for maintaining and enhancing the transient stability of power systems. The performance of the proposed scheme is evaluated on a standard IEEE 39-bus New England benchmark system under different large disturbances such as three-phase short-circuit faults and changes in loads within the systems. From the simulation results, it is found that the proposed scheme significantly enhances the transient stability of power systems as compared to a conventional scheme of static CB operation.

  14. A Scaffolding Framework to Support Learning of Emergent Phenomena Using Multi-Agent-Based Simulation Environments

    NASA Astrophysics Data System (ADS)

    Basu, Satabdi; Sengupta, Pratim; Biswas, Gautam

    2015-04-01

    Students from middle school to college have difficulties in interpreting and understanding complex systems such as ecological phenomena. Researchers have suggested that students experience difficulties in reconciling the relationships between individuals, populations, and species, as well as the interactions between organisms and their environment in the ecosystem. Multi-agent-based computational models (MABMs) can explicitly capture agents and their interactions by representing individual actors as computational objects with assigned rules. As a result, the collective aggregate-level behavior of the population dynamically emerges from simulations that generate the aggregation of these interactions. Past studies have used a variety of scaffolds to help students learn ecological phenomena. Yet, there is no theoretical framework that supports the systematic design of scaffolds to aid students' learning in MABMs. Our paper addresses this issue by proposing a comprehensive framework for the design, analysis, and evaluation of scaffolding to support students' learning of ecology in a MABM. We present a study in which middle school students used a MABM to investigate and learn about a desert ecosystem. We identify the different types of scaffolds needed to support inquiry learning activities in this simulation environment and use our theoretical framework to demonstrate the effectiveness of our scaffolds in helping students develop a deep understanding of the complex ecological behaviors represented in the simulation..

  15. An agent-based model of dialect evolution in killer whales.

    PubMed

    Filatova, Olga A; Miller, Patrick J O

    2015-05-21

    The killer whale is one of the few animal species with vocal dialects that arise from socially learned group-specific call repertoires. We describe a new agent-based model of killer whale populations and test a set of vocal-learning rules to assess which mechanisms may lead to the formation of dialect groupings observed in the wild. We tested a null model with genetic transmission and no learning, and ten models with learning rules that differ by template source (mother or matriline), variation type (random errors or innovations) and type of call change (no divergence from kin vs. divergence from kin). The null model without vocal learning did not produce the pattern of group-specific call repertoires we observe in nature. Learning from either mother alone or the entire matriline with calls changing by random errors produced a graded distribution of the call phenotype, without the discrete call types observed in nature. Introducing occasional innovation or random error proportional to matriline variance yielded more or less discrete and stable call types. A tendency to diverge from the calls of related matrilines provided fast divergence of loose call clusters. A pattern resembling the dialect diversity observed in the wild arose only when rules were applied in combinations and similar outputs could arise from different learning rules and their combinations. Our results emphasize the lack of information on quantitative features of wild killer whale dialects and reveal a set of testable questions that can draw insights into the cultural evolution of killer whale dialects.

  16. Fortune Favours the Bold: An Agent-Based Model Reveals Adaptive Advantages of Overconfidence in War

    PubMed Central

    Johnson, Dominic D. P.; Weidmann, Nils B.; Cederman, Lars-Erik

    2011-01-01

    Overconfidence has long been considered a cause of war. Like other decision-making biases, overconfidence seems detrimental because it increases the frequency and costs of fighting. However, evolutionary biologists have proposed that overconfidence may also confer adaptive advantages: increasing ambition, resolve, persistence, bluffing opponents, and winning net payoffs from risky opportunities despite occasional failures. We report the results of an agent-based model of inter-state conflict, which allows us to evaluate the performance of different strategies in competition with each other. Counter-intuitively, we find that overconfident states predominate in the population at the expense of unbiased or underconfident states. Overconfident states win because: (1) they are more likely to accumulate resources from frequent attempts at conquest; (2) they are more likely to gang up on weak states, forcing victims to split their defences; and (3) when the decision threshold for attacking requires an overwhelming asymmetry of power, unbiased and underconfident states shirk many conflicts they are actually likely to win. These “adaptive advantages” of overconfidence may, via selection effects, learning, or evolved psychology, have spread and become entrenched among modern states, organizations and decision-makers. This would help to explain the frequent association of overconfidence and war, even if it no longer brings benefits today. PMID:21731627

  17. Quantitative Agent Based Model of Opinion Dynamics: Polish Elections of 2015

    PubMed Central

    Sobkowicz, Pawel

    2016-01-01

    We present results of an abstract, agent based model of opinion dynamics simulations based on the emotion/information/opinion (E/I/O) approach, applied to a strongly polarized society, corresponding to the Polish political scene between 2005 and 2015. Under certain conditions the model leads to metastable coexistence of two subcommunities of comparable size (supporting the corresponding opinions)—which corresponds to the bipartisan split found in Poland. Spurred by the recent breakdown of this political duopoly, which occurred in 2015, we present a model extension that describes both the long term coexistence of the two opposing opinions and a rapid, transitory change due to the appearance of a third party alternative. We provide quantitative comparison of the model with the results of polls and elections in Poland, testing the assumptions related to the modeled processes and the parameters used in the simulations. It is shown, that when the propaganda messages of the two incumbent parties differ in emotional tone, the political status quo may be unstable. The asymmetry of the emotions within the support bases of the two parties allows one of them to be ‘invaded’ by a newcomer third party very quickly, while the second remains immune to such invasion. PMID:27171226

  18. Minimal agent based model for financial markets II. Statistical properties of the linear and multiplicative dynamics

    NASA Astrophysics Data System (ADS)

    Alfi, V.; Cristelli, M.; Pietronero, L.; Zaccaria, A.

    2009-02-01

    We present a detailed study of the statistical properties of the Agent Based Model introduced in paper I [Eur. Phys. J. B, DOI: 10.1140/epjb/e2009-00028-4] and of its generalization to the multiplicative dynamics. The aim of the model is to consider the minimal elements for the understanding of the origin of the stylized facts and their self-organization. The key elements are fundamentalist agents, chartist agents, herding dynamics and price behavior. The first two elements correspond to the competition between stability and instability tendencies in the market. The herding behavior governs the possibility of the agents to change strategy and it is a crucial element of this class of models. We consider a linear approximation for the price dynamics which permits a simple interpretation of the model dynamics and, for many properties, it is possible to derive analytical results. The generalized non linear dynamics results to be extremely more sensible to the parameter space and much more difficult to analyze and control. The main results for the nature and self-organization of the stylized facts are, however, very similar in the two cases. The main peculiarity of the non linear dynamics is an enhancement of the fluctuations and a more marked evidence of the stylized facts. We will also discuss some modifications of the model to introduce more realistic elements with respect to the real markets.

  19. Agent-Based Modleing of Power Plants Placement to Evaluate the Clean Energy Standard Goal

    SciTech Connect

    Omitaomu, Olufemi A

    2014-01-01

    There is a political push for utilities to supply a specified share of their electricity sales from clean energy resources under the clean energy standard (CES). The goal is to achieve 80% clean energy by 2035. However, there are uncertainties about the ability of the utility industry to ramp up quickly even with the incentives that will be provided. Water availability from the streams is one of the major factors. The contiguous United States is divided into eighteen water regions, and multiple states share water from a single water region. Consequently, water usage decisions made in one state (located upstream of a water region that crosses multiple states) will greatly impact what is available downstream in another state. In this paper, an agent-based modeling approach is proposed to evaluate the clean energy standard goal for water-dependent energy resources. Specifically, using a water region rather than a state boundary as a bounding envelope for the modeling and starting at the headwaters, virtual power plants are placed based on the conditions that there is: (i) suitable land to site a particular power plant, (ii) enough water that meet regulatory guidelines within 20 miles of the suitable land, and (iii) a 20-mile buffer zone from an existing or a virtual power plant. The results obtained are discussed in the context of the proposed clean energy standard goal for states that overlap with one water region.

  20. Agent based modeling of blood coagulation system: implementation using a GPU based high speed framework.

    PubMed

    Chen, Wenan; Ward, Kevin; Li, Qi; Kecman, Vojislav; Najarian, Kayvan; Menke, Nathan

    2011-01-01

    The coagulation and fibrinolytic systems are complex, inter-connected biological systems with major physiological roles. The complex, nonlinear multi-point relationships between the molecular and cellular constituents of two systems render a comprehensive and simultaneous study of the system at the microscopic and macroscopic level a significant challenge. We have created an Agent Based Modeling and Simulation (ABMS) approach for simulating these complex interactions. As the scale of agents increase, the time complexity and cost of the resulting simulations presents a significant challenge. As such, in this paper, we also present a high-speed framework for the coagulation simulation utilizing the computing power of graphics processing units (GPU). For comparison, we also implemented the simulations in NetLogo, Repast, and a direct C version. As our experiments demonstrate, the computational speed of the GPU implementation of the million-level scale of agents is over 10 times faster versus the C version, over 100 times faster versus the Repast version and over 300 times faster versus the NetLogo simulation. PMID:22254271