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Sample records for adaptive intrusion data systems

  1. Adaptive intrusion data system

    International Nuclear Information System (INIS)

    Johnson, C.S.

    1976-01-01

    An 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 digital data compression, storage, and formatting system. It also incorporates capability for video selection and recording for assessment of the sensors monitored by the system. The system is software reprogrammable to numerous configurations that may be utilized for the collection of environmental, bi-level, analog and video data. The output of the system is digital tapes formatted for direct data reduction on a CDC 6400 computer, and video tapes containing timed tagged information that can be correlated with the digital data

  2. Adaptive Intrusion Data System (AIDS)

    International Nuclear Information System (INIS)

    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

  3. Adaptive intrusion data system (AIDS) software routines

    International Nuclear Information System (INIS)

    Corlis, N.E.

    1980-07-01

    An Adaptive Intrusion Data System (AIDS) was developed to collect information from intrusion alarm sensors as part of an evaluation system to improve sensor performance. AIDS is a unique digital data-compression, storage, and formatting system; it also incorporates a capability for video selection and recording for assessment of the sensors monitored by the system. The system is software reprogrammable to numerous configurations that may be used for the collection of environmental, bilevel, analog, and video data. This report describes the software routines that control the different AIDS data-collection modes, the diagnostic programs to test the operating hardware, and the data format. Sample data printouts are also included

  4. Environmental data processor of the adaptive intrusion data system

    International Nuclear Information System (INIS)

    Rogers, M.S.

    1977-06-01

    A data acquisition system oriented specifically toward collection and processing of various meteorological and environmental parameters has been designed around a National Semiconductor IMP-16 microprocessor, This system, called the Environmental Data Processor (EDP), was developed specifically for use with the Adaptive Intrusion Data System (AIDS) in a perimeter intrusion alarm evaluation, although its design is sufficiently general to permit use elsewhere. This report describes in general detail the design of the EDP and its interaction with other AIDS components

  5. Mass memory formatter subsystem of the adaptive intrusion data system

    International Nuclear Information System (INIS)

    Corlis, N.E.

    1980-09-01

    The Mass Memory Formatter was developed as part of the Adaptive Intrusion Data System (AIDS) to control a 2.4-megabit mass memory. The data from a Memory Controlled Processor is formatted before it is stored in the memory and reformatted during the readout mode. The data is then transmitted to a NOVA 2 minicomputer-controlled magnetic tape recorder for storage. Techniques and circuits are described

  6. Description, operation, and diagnostic routines for the adaptive intrusion data system

    International Nuclear Information System (INIS)

    Corlis, N.E.; Johnson, C.S.

    1978-03-01

    An 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 digital data compression, storage, and formatting system. It also incorporates a capability for video selection and recording for assessment of the sensors monitored by the system. The system is software reprogrammable to numerous configurations that may be utilized for the collection of environmental, bi-metal, analog, and video data. This manual covers the procedures for operating AIDS. Instructions are given to guide the operator in software programming and control option selections required to program AIDS for data collection. Software diagnostic programs are included in this manual as a method of isolating system problems

  7. An Adaptive Database Intrusion Detection System

    Science.gov (United States)

    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…

  8. An Immune-inspired Adaptive Automated Intrusion Response System Model

    Directory of Open Access Journals (Sweden)

    Ling-xi Peng

    2012-09-01

    Full Text Available An immune-inspired adaptive automated intrusion response system model, named as , is proposed. The descriptions of self, non-self, immunocyte, memory detector, mature detector and immature detector of the network transactions, and the realtime network danger evaluation equations are given. Then, the automated response polices are adaptively performed or adjusted according to the realtime network danger. Thus, not only accurately evaluates the network attacks, but also greatly reduces the response times and response costs.

  9. Autonomic intrusion detection: Adaptively detecting anomalies over unlabeled audit data streams in computer networks

    KAUST Repository

    Wang, Wei; Guyet, Thomas; Quiniou, René ; Cordier, Marie-Odile; Masseglia, Florent; Zhang, Xiangliang

    2014-01-01

    In this work, we propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection over unlabeled HTTP traffic streams in computer networks. The framework holds potential for self-managing: self-labeling, self-updating and self-adapting. Our framework employs the Affinity Propagation (AP) algorithm to learn a subject’s behaviors through dynamical clustering of the streaming data. It automatically labels the data and adapts to normal behavior changes while identifies anomalies. Two large real HTTP traffic streams collected in our institute as well as a set of benchmark KDD’99 data are used to validate the framework and the method. The test results show that the autonomic model achieves better results in terms of effectiveness and efficiency compared to adaptive Sequential Karhunen–Loeve method and static AP as well as three other static anomaly detection methods, namely, k-NN, PCA and SVM.

  10. Autonomic intrusion detection: Adaptively detecting anomalies over unlabeled audit data streams in computer networks

    KAUST Repository

    Wang, Wei

    2014-06-22

    In this work, we propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection over unlabeled HTTP traffic streams in computer networks. The framework holds potential for self-managing: self-labeling, self-updating and self-adapting. Our framework employs the Affinity Propagation (AP) algorithm to learn a subject’s behaviors through dynamical clustering of the streaming data. It automatically labels the data and adapts to normal behavior changes while identifies anomalies. Two large real HTTP traffic streams collected in our institute as well as a set of benchmark KDD’99 data are used to validate the framework and the method. The test results show that the autonomic model achieves better results in terms of effectiveness and efficiency compared to adaptive Sequential Karhunen–Loeve method and static AP as well as three other static anomaly detection methods, namely, k-NN, PCA and SVM.

  11. A Nuisance Alarm Data System for evaluation of intrusion detectors

    International Nuclear Information System (INIS)

    Ream, W.K.

    1990-01-01

    A Nuisance Alarm Data System (NADS) was developed to gather long-term background alarm data on exterior intrusion detectors as part of their evaluation. Since nuisance alarms play an important part in the selection of intrusion detectors for use at Department of Energy (DOE) facilities, an economical and reliable way to monitor and record these alarms was needed. NADS consists of an IBM personal computer and printer along with other commercial units to communicate with the detectors, to gather weather data, and to record video for assessment. Each alarm, its assessment, and the weather conditions occurring at alarm time are placed into a data base that is used in the evaluation of the detector. The operating software is written in Turbo Pascal for easy maintenance and modification. A portable system, based on the NADS design, has been built and shipped to other DOE locations to do on-site alarm monitoring. This has been valuable for the comparison of different detectors in the on-site environment and for testing new detectors when the appropriate conditions do not exist or cannot be simulated at the Exterior Intrusion Detection Testbed

  12. Effective approach toward Intrusion Detection System using data mining techniques

    Directory of Open Access Journals (Sweden)

    G.V. Nadiammai

    2014-03-01

    Full Text Available With the tremendous growth of the usage of computers over network and development in application running on various platform captures the attention toward network security. This paradigm exploits security vulnerabilities on all computer systems that are technically difficult and expensive to solve. Hence intrusion is used as a key to compromise the integrity, availability and confidentiality of a computer resource. The Intrusion Detection System (IDS plays a vital role in detecting anomalies and attacks in the network. In this work, data mining concept is integrated with an IDS to identify the relevant, hidden data of interest for the user effectively and with less execution time. Four issues such as Classification of Data, High Level of Human Interaction, Lack of Labeled Data, and Effectiveness of Distributed Denial of Service Attack are being solved using the proposed algorithms like EDADT algorithm, Hybrid IDS model, Semi-Supervised Approach and Varying HOPERAA Algorithm respectively. Our proposed algorithm has been tested using KDD Cup dataset. All the proposed algorithm shows better accuracy and reduced false alarm rate when compared with existing algorithms.

  13. Interior intrusion detection systems

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez, J.R.; Matter, J.C. (Sandia National Labs., Albuquerque, NM (United States)); Dry, B. (BE, Inc., Barnwell, SC (United States))

    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.

  14. Interior intrusion detection systems

    International Nuclear Information System (INIS)

    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

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

    International Nuclear Information System (INIS)

    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. Anomaly-Based Intrusion Detection Systems Utilizing System Call Data

    Science.gov (United States)

    2012-03-01

    52 Table 7. Place Reachability Statistics for Low Level CPN...54 Table 8. Place Reachability Statistics for High Level CPN................................................. 55 Table 9. Password Stealing...the efficiency of traditional anti-virus software tools that are dependent on gigantic , continuously updated databases. Fortunately, Intrusion

  17. Intrusion detection system elements

    International Nuclear Information System (INIS)

    Eaton, M.J.; Mangan, D.L.

    1980-09-01

    This report highlights elements required for an intrusion detection system and discusses problems which can be encountered in attempting to make the elements effective. Topics discussed include: sensors, both for exterior detection and interior detection; alarm assessment systems, with the discussion focused on video assessment; and alarm reporting systems, including alarm communication systems and dislay/console considerations. Guidance on careful planning and design of a new or to-be-improved system is presented

  18. Interior intrusion alarm systems

    International Nuclear Information System (INIS)

    Prell, J.A.

    1978-01-01

    In meeting the requirements for the safeguarding of special nuclear material and the physical protection of licensed facilities, the licensee is required to design a physical security system that will meet minimum performance requirements. An integral part of any physical security system is the interior intrusion alarm system. The purpose of this report is to provide the potential user of an interior intrusion alarm system with information on the various types, components, and performance capabilities available so that he can design and install the optimum alarm system for his particular environment. In addition, maintenance and testing procedures are discussed and recommended which, if followed, will help the user obtain the optimum results from his system

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  20. A Comparative Study of Data Mining Algorithms for High Detection Rate in Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Nabeela Ashraf

    2018-01-01

    Full Text Available Due to the fast growth and tradition of the internet over the last decades, the network security problems are increasing vigorously. Humans can not handle the speed of processes and the huge amount of data required to handle network anomalies. Therefore, it needs substantial automation in both speed and accuracy. Intrusion Detection System is one of the approaches to recognize illegal access and rare attacks to secure networks. In this proposed paper, Naive Bayes, J48 and Random Forest classifiers are compared to compute the detection rate and accuracy of IDS. For experiments, the KDD_NSL dataset is used.

  1. Intrusion Detection in NEAR System by Anti-denoising Traffic Data Series using Discrete Wavelet Transform

    Directory of Open Access Journals (Sweden)

    VANCEA, F.

    2014-11-01

    Full Text Available The paper presents two methods for detecting anomalies in data series derived from network traffic. Intrusion detection systems based on network traffic analysis are able to respond to incidents never seen before by detecting anomalies in data series extracted from the traffic. Some anomalies manifest themselves as pulses of various sizes and shapes, superimposed on series corresponding to normal traffic. In order to detect those impulses we propose two methods based on discrete wavelet transformation. Their effectiveness expressed in relative thresholds on pulse amplitude for no false negatives and no false positives is then evaluated against pulse duration and Hurst characteristic of original series. Different base functions are also evaluated for efficiency in the context of the proposed methods.

  2. Data Mining for Intrusion Detection

    Science.gov (United States)

    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.

  3. Intrusion Detection System Based on Decision Tree over Big Data in Fog Environment

    Directory of Open Access Journals (Sweden)

    Kai Peng

    2018-01-01

    Full Text Available Fog computing, as the supplement of cloud computing, can provide low-latency services between mobile users and the cloud. However, fog devices may encounter security challenges as a result of the fog nodes being close to the end users and having limited computing ability. Traditional network attacks may destroy the system of fog nodes. Intrusion detection system (IDS is a proactive security protection technology and can be used in the fog environment. Although IDS in tradition network has been well investigated, unfortunately directly using them in the fog environment may be inappropriate. Fog nodes produce massive amounts of data at all times, and, thus, enabling an IDS system over big data in the fog environment is of paramount importance. In this study, we propose an IDS system based on decision tree. Firstly, we propose a preprocessing algorithm to digitize the strings in the given dataset and then normalize the whole data, to ensure the quality of the input data so as to improve the efficiency of detection. Secondly, we use decision tree method for our IDS system, and then we compare this method with Naïve Bayesian method as well as KNN method. Both the 10% dataset and the full dataset are tested. Our proposed method not only completely detects four kinds of attacks but also enables the detection of twenty-two kinds of attacks. The experimental results show that our IDS system is effective and precise. Above all, our IDS system can be used in fog computing environment over big data.

  4. Rapid deployment intrusion detection system

    International Nuclear Information System (INIS)

    Graham, R.H.

    1997-01-01

    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

  5. Adaptable data management for systems biology investigations

    Directory of Open Access Journals (Sweden)

    Burdick David

    2009-03-01

    Full Text Available Abstract Background Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage. Results The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry. We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents. Conclusion Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community.

  6. A Real-Time Intrusion Detection System using Data Mining Technique

    Directory of Open Access Journals (Sweden)

    Fang-Yie Leu

    2008-04-01

    Full Text Available Presently, most computers authenticate user ID and password before users can login these systems. However, danger soon comes if the two items are known to hackers. In this paper, we propose a system, named Intrusion Detection and Identification System (IDIS, which builds a profile for each user in an intranet to keep track his/her usage habits as forensic features with which IDIS can identify who the underlying user in the intranet is. Our experimental results show that the recognition accuracy of students of computer science department is up to 98.99%.

  7. Network Intrusion Forensic Analysis Using Intrusion Detection System

    OpenAIRE

    Manish Kumar; Dr. M. Hanumanthappa; Dr. T.V. Suresh Kumar

    2011-01-01

    The need for computer intrusion forensics arises from the alarming increase in the number of computer crimes that are committed annually. After a computer system has been breached and an intrusion has been detected, there is a need for a computer forensics investigation to follow. Computer forensics is used to bring to justice, those responsible for conducting attacks on computer systems throughout the world. Because of this the law must be follow precisely when conducting a forensics investi...

  8. Network Intrusion Detection System using Apache Storm

    Directory of Open Access Journals (Sweden)

    Muhammad Asif Manzoor

    2017-06-01

    Full Text Available Network security implements various strategies for the identification and prevention of security breaches. Network intrusion detection is a critical component of network management for security, quality of service and other purposes. These systems allow early detection of network intrusion and malicious activities; so that the Network Security infrastructure can react to mitigate these threats. Various systems are proposed to enhance the network security. We are proposing to use anomaly based network intrusion detection system in this work. Anomaly based intrusion detection system can identify the new network threats. We also propose to use Real-time Big Data Stream Processing Framework, Apache Storm, for the implementation of network intrusion detection system. Apache Storm can help to manage the network traffic which is generated at enormous speed and size and the network traffic speed and size is constantly increasing. We have used Support Vector Machine in this work. We use Knowledge Discovery and Data Mining 1999 (KDD’99 dataset to test and evaluate our proposed solution.

  9. Seismic intrusion detector system

    Science.gov (United States)

    Hawk, Hervey L.; Hawley, James G.; Portlock, John M.; Scheibner, James E.

    1976-01-01

    A system for monitoring man-associated seismic movements within a control area including a geophone for generating an electrical signal in response to seismic movement, a bandpass amplifier and threshold detector for eliminating unwanted signals, pulse counting system for counting and storing the number of seismic movements within the area, and a monitoring system operable on command having a variable frequency oscillator generating an audio frequency signal proportional to the number of said seismic movements.

  10. Research on IPv6 intrusion detection system Snort-based

    Science.gov (United States)

    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.

  11. Coupling of hydrogeological models with hydrogeophysical data to characterize seawater intrusion and shallow geothermal systems

    Science.gov (United States)

    Beaujean, J.; Kemna, A.; Engesgaard, P. K.; Hermans, T.; Vandenbohede, A.; Nguyen, F.

    2013-12-01

    While coastal aquifers are being stressed due to climate changes and excessive groundwater withdrawals require characterizing efficiently seawater intrusion (SWI) dynamics, production of geothermal energy is increasingly being used to hinder global warming. To study these issues, we need both robust measuring technologies and reliable predictions based on numerical models. SWI models are currently calibrated using borehole observations. Similarly, geothermal models depend mainly on the temperature field at few locations. Electrical resistivity tomography (ERT) can be used to improve these models given its high sensitivity to TDS and temperature and its relatively high lateral resolution. Inherent geophysical limitations, such as the resolution loss, can affect the overall quality of the ERT images and also prevent the correct recovery of the desired hydrochemical property. We present an uncoupled and coupled hydrogeophysical inversion to calibrate SWI and thermohydrogeologic models using ERT. In the SWI models, we demonstrate with two synthetic benchmarks (homogeneous and heterogeneous coastal aquifers) the ability of cumulative sensitivity-filtered ERT images using surface-only data to recover the hydraulic conductivity. Filtering of ERT-derived data at depth, where resolution is poorer, and the model errors make the dispersivity more difficult to estimate. In the coupled approach, we showed that parameter estimation is significantly improved because regularization bias is replaced by forward modeling only. Our efforts are currently focusing on applying the uncoupled/coupled approaches on a real life case study using field data from the site of Almeria, SE Spain. In the thermohydrogeologic models, the most sensitive hydrologic parameters responsible for heat transport are estimated from surface ERT-derived temperatures and ERT resistance data. A real life geothermal experiment that took place on the Campus De Sterre of Ghent University, Belgium and a synthetic

  12. Smart sensor systems for outdoor intrusion detection

    International Nuclear Information System (INIS)

    Lynn, J.K.

    1988-01-01

    A major improvement in outdoor perimeter security system probability of detection (PD) and reduction in false alarm rate (FAR) and nuisance alarm rate (NAR) may be obtained by analyzing the indications immediately preceding an event which might be interpreted as an intrusion. Existing systems go into alarm after crossing a threshold. Very slow changes, which accumulate until the threshold is reached, may be assessed falsely as an intrusion. A hierarchial program has begun at Stellar to develop a modular, expandable Smart Sensor system which may be interfaced to most types of sensor and alarm reporting systems. A major upgrade to the SSI Test Site is in progress so that intrusions may be simulated in a controlled and repeatable manner. A test platform is being constructed which will operate in conduction with a mobile instrumentation center with CCTVB, lighting control, weather and data monitoring and remote control of the test platform and intrusion simulators. Additional testing was contracted with an independent test facility to assess the effects of severe winter weather conditions

  13. Improving Intrusion Detection System Based on Snort Rules for Network Probe Attacks Detection with Association Rules Technique of Data Mining

    Directory of Open Access Journals (Sweden)

    Nattawat Khamphakdee

    2015-07-01

    Full Text Available The intrusion detection system (IDS is an important network security tool for securing computer and network systems. It is able to detect and monitor network traffic data. Snort IDS is an open-source network security tool. It can search and match rules with network traffic data in order to detect attacks, and generate an alert. However, the Snort IDS  can detect only known attacks. Therefore, we have proposed a procedure for improving Snort IDS rules, based on the association rules data mining technique for detection of network probe attacks.  We employed the MIT-DARPA 1999 data set for the experimental evaluation. Since behavior pattern traffic data are both normal and abnormal, the abnormal behavior data is detected by way of the Snort IDS. The experimental results showed that the proposed Snort IDS rules, based on data mining detection of network probe attacks, proved more efficient than the original Snort IDS rules, as well as icmp.rules and icmp-info.rules of Snort IDS.  The suitable parameters for the proposed Snort IDS rules are defined as follows: Min_sup set to 10%, and Min_conf set to 100%, and through the application of eight variable attributes. As more suitable parameters are applied, higher accuracy is achieved.

  14. Abstracting audit data for lightweight intrusion detection

    KAUST Repository

    Wang, Wei

    2010-01-01

    High speed of processing massive audit data is crucial for an anomaly Intrusion Detection System (IDS) to achieve real-time performance during the detection. Abstracting audit data is a potential solution to improve the efficiency of data processing. In this work, we propose two strategies of data abstraction in order to build a lightweight detection model. The first strategy is exemplar extraction and the second is attribute abstraction. Two clustering algorithms, Affinity Propagation (AP) as well as traditional k-means, are employed to extract the exemplars, and Principal Component Analysis (PCA) is employed to abstract important attributes (a.k.a. features) from the audit data. Real HTTP traffic data collected in our institute as well as KDD 1999 data are used to validate the two strategies of data abstraction. The extensive test results show that the process of exemplar extraction significantly improves the detection efficiency and has a better detection performance than PCA in data abstraction. © 2010 Springer-Verlag.

  15. Apriori-based network intrusion detection system

    International Nuclear Information System (INIS)

    Wang Wenjin; Liu Junrong; Liu Baoxu

    2012-01-01

    With the development of network communication technology, more and more social activities run by Internet. In the meantime, the network information security is getting increasingly serious. Intrusion Detection System (IDS) has greatly improved the general security level of whole network. But there are still many problem exists in current IDS, e.g. high leak rate detection/false alarm rates and feature library need frequently upgrade. This paper presents an association-rule based IDS. This system can detect unknown attack by generate rules from training data. Experiment in last chapter proved the system has great accuracy on unknown attack detection. (authors)

  16. NIST Special Publication on Intrusion Detection Systems

    National Research Council Canada - National Science Library

    Bace, Rebecca Gurley

    2001-01-01

    Intrusion detection systems (IDSs) are software or hardware systems that automate the process of monitoring the events occurring in a computer system or network, analyzing them for signs of security problems...

  17. Data-Adaptable Modeling and Optimization for Runtime Adaptable Systems

    Science.gov (United States)

    2016-06-08

    and a circle denotes the application’s final output. The arrows represent the data consumed and produced by each task. This pedagogical application...application’s operational state is a complex task that requires a thorough understanding of the relationship between an application’s tunable

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

    Science.gov (United States)

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

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

  19. A Fusion of Multiagent Functionalities for Effective Intrusion Detection System

    OpenAIRE

    Dhanalakshmi Krishnan Sadhasivan; Kannapiran Balasubramanian

    2017-01-01

    Provision of high security is one of the active research areas in the network applications. The failure in the centralized system based on the attacks provides less protection. Besides, the lack of update of new attacks arrival leads to the minimum accuracy of detection. The major focus of this paper is to improve the detection performance through the adaptive update of attacking information to the database. We propose an Adaptive Rule-Based Multiagent Intrusion Detection System (ARMA-IDS) to...

  20. Security Enrichment in Intrusion Detection System Using Classifier Ensemble

    Directory of Open Access Journals (Sweden)

    Uma R. Salunkhe

    2017-01-01

    Full Text Available In the era of Internet and with increasing number of people as its end users, a large number of attack categories are introduced daily. Hence, effective detection of various attacks with the help of Intrusion Detection Systems is an emerging trend in research these days. Existing studies show effectiveness of machine learning approaches in handling Intrusion Detection Systems. In this work, we aim to enhance detection rate of Intrusion Detection System by using machine learning technique. We propose a novel classifier ensemble based IDS that is constructed using hybrid approach which combines data level and feature level approach. Classifier ensembles combine the opinions of different experts and improve the intrusion detection rate. Experimental results show the improved detection rates of our system compared to reference technique.

  1. Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

    Science.gov (United States)

    2016-04-05

    applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

  2. Intrusion Detection amp Prevention Systems - Sourcefire Snort

    Directory of Open Access Journals (Sweden)

    Rajesh Vuppala

    2015-08-01

    Full Text Available Information security is a challenging issue for all business organizations today amidst increasing cyber threats. While there are many alternative intrusion detection amp prevention systems available to choose from selecting the best solution to implement to detect amp prevent cyber-attacks is a difficult task. The best solution is of the one that gets the best reviews and suits the organizations needs amp budget. In this review paper we summarize various classes of intrusion detection and prevention systems compare features of alternative solutions and make recommendation for implementation of one as the best solution for business organization in Fiji.

  3. Data Fusion for Network Intrusion Detection: A Review

    Directory of Open Access Journals (Sweden)

    Guoquan Li

    2018-01-01

    Full Text Available Rapid progress of networking technologies leads to an exponential growth in the number of unauthorized or malicious network actions. As a component of defense-in-depth, Network Intrusion Detection System (NIDS has been expected to detect malicious behaviors. Currently, NIDSs are implemented by various classification techniques, but these techniques are not advanced enough to accurately detect complex or synthetic attacks, especially in the situation of facing massive high-dimensional data. Besides, the inherent defects of NIDSs, namely, high false alarm rate and low detection rate, have not been effectively solved. In order to solve these problems, data fusion (DF has been applied into network intrusion detection and has achieved good results. However, the literature still lacks thorough analysis and evaluation on data fusion techniques in the field of intrusion detection. Therefore, it is necessary to conduct a comprehensive review on them. In this article, we focus on DF techniques for network intrusion detection and propose a specific definition to describe it. We review the recent advances of DF techniques and propose a series of criteria to compare their performance. Finally, based on the results of the literature review, a number of open issues and future research directions are proposed at the end of this work.

  4. Uncertainty quantification for criticality problems using non-intrusive and adaptive Polynomial Chaos techniques

    International Nuclear Information System (INIS)

    Gilli, L.; Lathouwers, D.; Kloosterman, J.L.; Hagen, T.H.J.J. van der; Koning, A.J.; Rochman, D.

    2013-01-01

    Highlights: ► Non-intrusive spectral techniques are applied to perform UQ of criticality problems. ► A new adaptive algorithm based on the definition of sparse grid is derived. ► The method is applied to two reference criticality problems. - Abstract: In this paper we present the implementation and the application of non-intrusive spectral techniques for uncertainty analysis of criticality problems. Spectral techniques can be used to reconstruct stochastic quantities of interest by means of a Fourier-like expansion. Their application to uncertainty propagation problems can be performed in a non-intrusive fashion by evaluating a set of projection integrals that are used to reconstruct the spectral expansion. This can be done either by using standard Monte Carlo integration approaches or by adopting numerical quadrature rules. We present the derivation of a new adaptive quadrature algorithm, based on the definition of a sparse grid, which can be used to reduce the computational cost associated with non-intrusive spectral techniques. This new adaptive algorithm and the Monte Carlo integration alternative are then applied to two reference problems. First, a stochastic multigroup diffusion problem is introduced by considering the microscopic cross-sections of the system to be random quantities. Then a criticality benchmark is defined for which a set of resonance parameters in the resolved region are assumed to be stochastic

  5. Distributed fiber optic moisture intrusion sensing system

    Science.gov (United States)

    Weiss, Jonathan D.

    2003-06-24

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

  6. In-situ trainable intrusion detection system

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-11-15

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

  7. Perimeter intrusion detection and assessment system

    International Nuclear Information System (INIS)

    Eaton, M.J.; Jacobs, J.; McGovern, D.E.

    1977-11-01

    To obtain an effective perimeter intrusion detection system requires careful sensor selection, procurement, and installation. The selection process involves a thorough understanding of the unique site features and how these features affect the performance of each type of sensor. It is necessary to develop procurement specifications to establish acceptable sensor performance limits. Careful explanation and inspection of critical installation dimensions is required during on-site construction. The implementation of these activities at a particular site is discussed

  8. A Fusion of Multiagent Functionalities for Effective Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Dhanalakshmi Krishnan Sadhasivan

    2017-01-01

    Full Text Available Provision of high security is one of the active research areas in the network applications. The failure in the centralized system based on the attacks provides less protection. Besides, the lack of update of new attacks arrival leads to the minimum accuracy of detection. The major focus of this paper is to improve the detection performance through the adaptive update of attacking information to the database. We propose an Adaptive Rule-Based Multiagent Intrusion Detection System (ARMA-IDS to detect the anomalies in the real-time datasets such as KDD and SCADA. Besides, the feedback loop provides the necessary update of attacks in the database that leads to the improvement in the detection accuracy. The combination of the rules and responsibilities for multiagents effectively detects the anomaly behavior, misuse of response, or relay reports of gas/water pipeline data in KDD and SCADA, respectively. The comparative analysis of the proposed ARMA-IDS with the various existing path mining methods, namely, random forest, JRip, a combination of AdaBoost/JRip, and common path mining on the SCADA dataset conveys that the effectiveness of the proposed ARMA-IDS in the real-time fault monitoring. Moreover, the proposed ARMA-IDS offers the higher detection rate in the SCADA and KDD cup 1999 datasets.

  9. Neural Network Based Intrusion Detection System for Critical Infrastructures

    Energy Technology Data Exchange (ETDEWEB)

    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.

  10. Data mining approach to web application intrusions detection

    Science.gov (United States)

    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.

  11. Water System Adaptation To Hydrological Changes: Module 6, Synchronous Management of Storm Surge, Sea Level Rise, and Salt Water Intrusion: Case Study in Mattapoisett, Massachusetts, U.S.A.

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  12. Non-intrusive Quality Analysis of Monitoring Data

    CERN Document Server

    Brightwell, M; Suwalska, Anna

    2010-01-01

    Any large-scale operational system running over a variety of devices requires a monitoring mechanism to assess the health of the overall system. The Technical Infrastructure Monitoring System (TIM) at CERN is one such system, and monitors a wide variety of devices and their properties, such as electricity supplies, device temperatures, liquid flows etc. Without adequate quality assurance, the data collected from such devices leads to false-positives and false-negatives, reducing the effectiveness of the monitoring system. The quality must, however, be measured in a non-intrusive way, so that the critical path of the data flow is not affected by the quality computation. The quality computation should also scale to large volumes of incoming data. To address these challenges, we develop a new statistical module, which monitors the data collected by TIM and reports its quality to the operators. The statistical module uses Oracle RDBMS as the underlying store, and builds hierarchical summaries on the basic events ...

  13. A Targeted Attack For Enhancing Resiliency of Intelligent Intrusion Detection Modules in Energy Cyber Physical Systems

    Energy Technology Data Exchange (ETDEWEB)

    Youssef, Tarek [Florida Intl Univ., Miami, FL (United States); El Hariri, Mohammad [Florida Intl Univ., Miami, FL (United States); Habib, Hani [Florida Intl Univ., Miami, FL (United States); Mohammed, Osama [Florida Intl Univ., Miami, FL (United States); Harmon, E [Florida Intl Univ., Miami, FL (United States)

    2017-02-28

    Abstract— Secure high-speed communication is required to ensure proper operation of complex power grid systems and prevent malicious tampering activities. In this paper, artificial neural networks with temporal dependency are introduced for false data identification and mitigation for broadcasted IEC 61850 SMV messages. The fast responses of such intelligent modules in intrusion detection make them suitable for time- critical applications, such as protection. However, care must be taken in selecting the appropriate intelligence model and decision criteria. As such, this paper presents a customizable malware script to sniff and manipulate SMV messages and demonstrates the ability of the malware to trigger false positives in the neural network’s response. The malware developed is intended to be as a vaccine to harden the intrusion detection system against data manipulation attacks by enhancing the neural network’s ability to learn and adapt to these attacks.

  14. Windows Based Data Sets for Evaluation of Robustness of Host Based Intrusion Detection Systems (IDS to Zero-Day and Stealth Attacks

    Directory of Open Access Journals (Sweden)

    Waqas Haider

    2016-07-01

    Full Text Available The Windows Operating System (OS is the most popular desktop OS in the world, as it has the majority market share of both servers and personal computing necessities. However, as its default signature-based security measures are ineffectual for detecting zero-day and stealth attacks, it needs an intelligent Host-based Intrusion Detection System (HIDS. Unfortunately, a comprehensive data set that reflects the modern Windows OS’s normal and attack surfaces is not publicly available. To fill this gap, in this paper two open data sets generated by the cyber security department of the Australian Defence Force Academy (ADFA are introduced, namely: Australian Defence Force Academy Windows Data Set (ADFA-WD; and Australian Defence Force Academy Windows Data Set with a Stealth Attacks Addendum (ADFA-WD: SAA. Statistical analysis results based on these data sets show that, due to the low foot prints of modern attacks and high similarity of normal and attacked data, both these data sets are complex, and highly intelligent Host based Anomaly Detection Systems (HADS design will be required.

  15. Sensitive Data Protection Based on Intrusion Tolerance in Cloud Computing

    OpenAIRE

    Jingyu Wang; xuefeng Zheng; Dengliang Luo

    2011-01-01

    Service integration and supply on-demand coming from cloud computing can significantly improve the utilization of computing resources and reduce power consumption of per service, and effectively avoid the error of computing resources. However, cloud computing is still facing the problem of intrusion tolerance of the cloud computing platform and sensitive data of new enterprise data center. In order to address the problem of intrusion tolerance of cloud computing platform and sensitive data in...

  16. Semantic intrusion detection with multisensor data fusion using ...

    Indian Academy of Sciences (India)

    spatiotemporal relations to form complex events which model the intrusion patterns. ... Wireless sensor networks; complex event processing; event stream; ...... of the 2006 ACM SIGMOD International Conference on Management of Data, 407– ...

  17. Hybrid Intrusion Forecasting Framework for Early Warning System

    Science.gov (United States)

    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.

  18. The use of data-mining techniques for developing effective decisionsupport systems: A case study of simulating the effects ofclimate change on coastal salinity intrusion

    Science.gov (United States)

    Conrads, Paul; Edwin Roehl, Jr.

    2017-01-01

    Natural-resource managers and stakeholders face difficult challenges when managing interactions between natural and societal systems. Potential changes in climate could alter interactions between environmental and societal systems and adversely affect the availability of water resources in many coastal communities. The availability of freshwater in coastal streams can be threatened by saltwater intrusion. Even though the collective interests and computer skills of the community of managers, scientists and other stakeholders are quite varied, there is an overarching need for equal access by all to the scientific knowledge needed to make the best possible decisions. This paper describes a decision support system, PRISM-2, developed to evaluate salinity intrusion due to potential climate change along the South Carolina coast in southeastern USA. The decision support system is disseminated as a spreadsheet application and integrates the output of global circulation models, watershed models and salinity intrusion models with real-time databases for simulation, graphical user interfaces, and streaming displays of results. The results from PRISM-2 showed that a 31-cm and 62-cm increase in sea level reduced the daily availability of freshwater supply to a coastal municipal intake by 4% and 12% of the time, respectively. Future climate change projections by a global circulation model showed a seasonal change in salinity intrusion events from the summer to the fall for the majority of events.

  19. An intrusion detection system based on fiber hydrophone

    Science.gov (United States)

    Liu, Junrong; Qiu, Xiufen; Shen, Heping

    2017-10-01

    This paper provides a new intrusion detection system based on fiber hydrophone, focusing beam forming figure positioning according to the near field and high precision sound source location algorithm which can accurately position the intrusion; obtaining its behavior path , obtaining the intrusion events related information such as speed form tracking intrusion trace; And analyze identification the detected intrusion behavior. If the monitor area is larger, the algorithm will take too much time once, and influence the system response time, for reduce the calculating time. This paper provides way that coarse location first, and then scanned for accuracy, so as to realize the intrusion events (such as car, etc.) the remote monitoring of positioning. The system makes up the blank in process capture of the fiber optic intrusion detection technology, and improves the understanding of the invasion. Through the capture of the process of intrusion behavior, and the fusion detection of intrusion behavior itself, thus analysis, judgment, identification of the intrusion information can greatly reduce the rate of false positives, greatly improved the reliability and practicability of the perimeter security system.

  20. Anomaly-based intrusion detection for SCADA systems

    International Nuclear Information System (INIS)

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

    2006-01-01

    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)

  1. An ontology-based intrusion patterns classification system | Shonubi ...

    African Journals Online (AJOL)

    Studies have shown that computer intrusions have been on the increase in recent times. Many techniques and patterns are being used by intruders to gain access to data on host computer networks. In this work, intrusion patterns were identified and classified and inherent knowledge were represented using an ontology of ...

  2. Effects of igneous intrusions on the petroleum system: a review

    NARCIS (Netherlands)

    Senger, Kim; Millett, John; Planke, Sverre; Ogata, Kei; Eide, Christian Haug; Festøy, Marte; Galland, Olivier; Jerram, Dougal A.

    2017-01-01

    Igneous intrusions feature in many sedimentary basins where hydrocarbon exploration and production is continuing. Owing to distinct geophysical property contrasts with siliciclastic host rocks (e.g., higher Vp, density and resistivity than host rocks), intrusions can be easily delineated within data

  3. Abstracting audit data for lightweight intrusion detection

    KAUST Repository

    Wang, Wei; Zhang, Xiangliang; Pitsilis, Georgios

    2010-01-01

    are used to validate the two strategies of data abstraction. The extensive test results show that the process of exemplar extraction significantly improves the detection efficiency and has a better detection performance than PCA in data abstraction. © 2010

  4. A Labeled Data Set For Flow-based Intrusion Detection

    NARCIS (Netherlands)

    Sperotto, Anna; Sadre, R.; van Vliet, Frank; Pras, Aiko; Nunzi, Giorgio; Scoglio, Caterina; Li, Xing

    2009-01-01

    Flow-based intrusion detection has recently become a promising security mechanism in high speed networks (1-10 Gbps). Despite the richness in contributions in this field, benchmarking of flow-based IDS is still an open issue. In this paper, we propose the first publicly available, labeled data set

  5. Intrusion Detection System In IoT

    OpenAIRE

    Nygaard, Frederik

    2017-01-01

    Intrusion detection detects misbehaving nodes in a network. In Internet of Things(IoT), IPv6 Routing for Low-Power and Lossy Networks (RPL) is the standard routing protocol. In IoT, devices commonly have low energy, storage and memory, which is why the implemented intrusion algorithm in this thesis will try to minimize the usage of these resources. IDS for RPL-networks have been implemented before, but the use of resources or the number of packets sent was too high to be successful when findi...

  6. Resilient Control and Intrusion Detection for SCADA Systems

    Science.gov (United States)

    2014-05-01

    Lowe. The myths and facts behind cyber security risks for industrial control systems . VDE Congress, 2004. [45] I. S. C37.1-1994. Ieee standard...Resilient Control and Intrusion Detection for SCADA Systems Bonnie Xia Zhu Electrical Engineering and Computer Sciences University of California at...3. DATES COVERED 00-00-2014 to 00-00-2014 4. TITLE AND SUBTITLE Resilient Control and Intrusion Detection for SCADA Systems 5a. CONTRACT

  7. Intrusion Detection Systems with Live Knowledge System

    Science.gov (United States)

    2016-05-31

    people try to reveal sensitive information of Internet users, also called as phishing. Phishing detection has received great attention but there has...node. Figure 3 describes the result of modified nodes from the original RDR rule tree. Red- coloured ‘X’ sign represents the stopping rule, and the...green- coloured boxes describe the refined rule. However, when human knowledge is applied to those incorrectly classified data, not all of the

  8. Abstracting massive data for lightweight intrusion detection in computer networks

    KAUST Repository

    Wang, Wei

    2016-10-15

    Anomaly intrusion detection in big data environments calls for lightweight models that are able to achieve real-time performance during detection. Abstracting audit data provides a solution to improve the efficiency of data processing in intrusion detection. Data abstraction refers to abstract or extract the most relevant information from the massive dataset. In this work, we propose three strategies of data abstraction, namely, exemplar extraction, attribute selection and attribute abstraction. We first propose an effective method called exemplar extraction to extract representative subsets from the original massive data prior to building the detection models. Two clustering algorithms, Affinity Propagation (AP) and traditional . k-means, are employed to find the exemplars from the audit data. . k-Nearest Neighbor (k-NN), Principal Component Analysis (PCA) and one-class Support Vector Machine (SVM) are used for the detection. We then employ another two strategies, attribute selection and attribute extraction, to abstract audit data for anomaly intrusion detection. Two http streams collected from a real computing environment as well as the KDD\\'99 benchmark data set are used to validate these three strategies of data abstraction. The comprehensive experimental results show that while all the three strategies improve the detection efficiency, the AP-based exemplar extraction achieves the best performance of data abstraction.

  9. Ensemble of classifiers based network intrusion detection system performance bound

    CSIR Research Space (South Africa)

    Mkuzangwe, Nenekazi NP

    2017-11-01

    Full Text Available This paper provides a performance bound of a network intrusion detection system (NIDS) that uses an ensemble of classifiers. Currently researchers rely on implementing the ensemble of classifiers based NIDS before they can determine the performance...

  10. Implementing an Intrusion Detection System in the Mysea Architecture

    National Research Council Canada - National Science Library

    Tenhunen, Thomas

    2008-01-01

    .... The objective of this thesis is to design an intrusion detection system (IDS) architecture that permits administrators operating on MYSEA client machines to conveniently view and analyze IDS alerts from the single level networks...

  11. A Survey on Anomaly Based Host Intrusion Detection System

    Science.gov (United States)

    Jose, Shijoe; Malathi, D.; Reddy, Bharath; Jayaseeli, Dorathi

    2018-04-01

    An intrusion detection system (IDS) is hardware, software or a combination of two, for monitoring network or system activities to detect malicious signs. In computer security, designing a robust intrusion detection system is one of the most fundamental and important problems. The primary function of system is detecting intrusion and gives alerts when user tries to intrusion on timely manner. In these techniques when IDS find out intrusion it will send alert massage to the system administrator. Anomaly detection is an important problem that has been researched within diverse research areas and application domains. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. From the existing anomaly detection techniques, each technique has relative strengths and weaknesses. The current state of the experiment practice in the field of anomaly-based intrusion detection is reviewed and survey recent studies in this. This survey provides a study of existing anomaly detection techniques, and how the techniques used in one area can be applied in another application domain.

  12. The design about the intrusion defense system for IHEP

    International Nuclear Information System (INIS)

    Liu Baoxu; Xu Rongsheng; Yu Chuansong; Wu Chunzhen

    2003-01-01

    With the development of network technologies, limitations on traditional methods of network security protection are becoming more and more obvious. An individual network security product or the simple combination of several products can hardly complete the goal of keeping from hackers' intrusion. Therefore, on the basis of the analyses about the security problems of IHEPNET which is an open and scientific research network, the author designs an intrusion defense system especially for IHEPNET

  13. Adaptation of a Data Acquisition System for Monitoring Air Quality and Radioactivity

    International Nuclear Information System (INIS)

    Ramadan, A.B.; Hefnawi, M.; Hefnaw, M.

    2006-01-01

    the main aim from this work is adapting the data acquisition system for monitoring air quality and radioactivity to save cost, time and effort. the adaptation processes are not only based on rectifying drawbacks but also modifying new features for both systems.these drawbacks are hardware problems and software problems for both systems which cause more operation cost, more operation time and more human effort these new features are modified to achieve the grown user requirements, better performance, more flexibility for customization and better user acceptance the adaptation method is implemented by determining: how exactly two systems work, components for each system and relationships between them, which components need adaptation, and finally suitable adaptation procedure for each component with maintaining the relationships between them the proposed systems overcome the above-mentioned drawbacks associated with the old systems and have new facilities to verify their main goals

  14. Intrusive versus domiciliated triatomines and the challenge of adapting vector control practices against Chagas disease

    Directory of Open Access Journals (Sweden)

    Etienne Waleckx

    2015-05-01

    Full Text Available Chagas disease prevention remains mostly based on triatomine vector control to reduce or eliminate house infestation with these bugs. The level of adaptation of triatomines to human housing is a key part of vector competence and needs to be precisely evaluated to allow for the design of effective vector control strategies. In this review, we examine how the domiciliation/intrusion level of different triatomine species/populations has been defined and measured and discuss how these concepts may be improved for a better understanding of their ecology and evolution, as well as for the design of more effective control strategies against a large variety of triatomine species. We suggest that a major limitation of current criteria for classifying triatomines into sylvatic, intrusive, domiciliary and domestic species is that these are essentially qualitative and do not rely on quantitative variables measuring population sustainability and fitness in their different habitats. However, such assessments may be derived from further analysis and modelling of field data. Such approaches can shed new light on the domiciliation process of triatomines and may represent a key tool for decision-making and the design of vector control interventions.

  15. Hybrid feature selection for supporting lightweight intrusion detection systems

    Science.gov (United States)

    Song, Jianglong; Zhao, Wentao; Liu, Qiang; Wang, Xin

    2017-08-01

    Redundant and irrelevant features not only cause high resource consumption but also degrade the performance of Intrusion Detection Systems (IDS), especially when coping with big data. These features slow down the process of training and testing in network traffic classification. Therefore, a hybrid feature selection approach in combination with wrapper and filter selection is designed in this paper to build a lightweight intrusion detection system. Two main phases are involved in this method. The first phase conducts a preliminary search for an optimal subset of features, in which the chi-square feature selection is utilized. The selected set of features from the previous phase is further refined in the second phase in a wrapper manner, in which the Random Forest(RF) is used to guide the selection process and retain an optimized set of features. After that, we build an RF-based detection model and make a fair comparison with other approaches. The experimental results on NSL-KDD datasets show that our approach results are in higher detection accuracy as well as faster training and testing processes.

  16. Intrusion problematic during water supply systems' operation

    Energy Technology Data Exchange (ETDEWEB)

    Mora-Rodriguez, Jesus; Lopez-Jimenez, P. Amparo [Departamento de Ingenieria Hidraulica y Medio Ambiente, Universidad Politecnica de Valencia, Camino de Vera, s/n, 46022, Valencia (Spain); Ramos, Helena M. [Civil Engineering Department and CEHIDRO, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001, Lisbon (Portugal)

    2011-07-01

    Intrusion through leaks occurrence is a phenomenon when external fluid comes into water pipe systems. This phenomenon can cause contamination problems in drinking pipe systems. Hence, this paper focuses on the entry of external fluids across small leaks during normal operation conditions. This situation is especially important in elevated points of the pipe profile. Pressure variations can origin water volume losses and intrusion of contaminants into the drinking water pipes. This work focuses in obtaining up the physical representation on a specific case intrusion in a pipe water system. The combination of two factors is required to generate this kind of intrusion in a water supply system: on one hand the existence of at least a leak in the system; on the other hand, a pressure variation could occur during the operation of the system due to consumption variation, pump start-up or shutdown. The potential of intrusion during a dynamic or transient event is here analyzed. To obtain this objective an experimental case study of pressure transient scenario is analyzed with a small leak located nearby the transient source.

  17. Fair and adaptive data dissemination for traffic information systems

    NARCIS (Netherlands)

    de Souza Schwartz, Ramon; Ohazulike, Anthony; Sommer, Christoph; Scholten, Johan; Dressler, Falko; Havinga, Paul J.M.; IEEE,

    2012-01-01

    Vehicular Ad-hoc Networks (VANETs) are expected to serve as support to the development of not only safety applications but also information-rich applications that disseminate relevant data to vehicles. Due to the continuous collection, processing, and dissemination of data, one crucial requirement

  18. A subtractive approach to interior intrusion detection system design

    International Nuclear Information System (INIS)

    Sons, R.J.; Graham, R.H. Jr.

    1986-01-01

    This paper discusses the subtractive approach to interior intrusion detection system design which assumes that all sensors are viable candidates until they are subjected to the constraints imposed by a particular facility. The constraints are determined by a sequence of questions concerning parameters such as threat definition, facility description and operation, environment, assets to be protected, security system capabilities, and cost. As a result of the questioning, some sensors will be eliminated from the candidate list, and the ''best'' set of sensors for the facility will remain. This form of questioning could be incorporated into an expert system aiding future intrusion detection system designs

  19. Preventing Point-of-Sale System Intrusions

    Science.gov (United States)

    2014-06-01

    into point-of-sale systems of over 150 Subway sandwich franchises and fifty other retailers (U.S. v. Oprea et al.). The hacking group ultimately...automated “dumps site,” dumps.name. A “dumps site” is a Website devoted to the buying and selling of stolen card data (U.S. v. Horohorin). The United States...trafficking of numbers of credit and debit cards. Most of the buying and selling of bulk quantities of credit and debit card data is done through

  20. Cyclone, Salinity Intrusion and Adaptation and Coping Measures in Coastal Bangladesh

    Directory of Open Access Journals (Sweden)

    Sebak Kumar Saha

    2017-06-01

    Full Text Available Although households in the coastal areas of Bangladesh undertake various adaptation and coping measures to minimise their vulnerability to cyclone hazards and salinity intrusion, these autonomous measures have received little attention in the past. However, the Government of Bangladesh has recently emphasised the importance of understanding these measures so that necessary interventions to make households more resilient to natural hazards and the adverse impacts of climate change can be introduced. This paper, based on secondary sources, explores adaptation and coping measures that households in the coastal areas of Bangladesh undertake to minimise their vulnerability to cyclone hazards and salinity intrusion. This paper shows that many of the adaptation and coping measures contribute to making households less vulnerable and more resilient to cyclone hazards and salinity intrusion, although some coping measures do the opposite as they reduce households’ adaptive capacities instead of improving them. This paper argues that the adaptation and coping measures that contribute to reducing households’ vulnerability to natural hazards need to be supported and guided by the government and NGOs to make them more effective. Additionally, measures that make households more vulnerable also need to be addressed by the government and NGOs, as most of these measures are related to and constrained by both poverty, and because the households have little or no access to economic opportunities.

  1. Revisiting Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.

    2009-01-01

    Intrusion detection systems (IDSs) are well-known and widely-deployed security tools to detect cyber-attacks and malicious activities in computer systems and networks. A signature-based IDS works similar to anti-virus software. It employs a signature database of known attacks, and a successful match

  2. Protecting coastal abstraction boreholes from seawater intrusion using self-potential data

    Science.gov (United States)

    Graham, Malcolm; Butler, Adrian; MacAllister, Donald John; Vinogradov, Jan; Ijioma, Amadi; Jackson, Matthew

    2016-04-01

    We investigate whether the presence and transport of seawater can influence self-potentials (SPs) measured within coastal groundwater boreholes, with a view to using SP monitoring as part of an early warning system for saline intrusion. SP data were collected over a period of 18 months from a coastal groundwater borehole in the fractured Chalk of England. Spectral analysis of the results shows semi-diurnal fluctuations that are several orders of magnitude higher than those observed from monitoring of the Chalk more than 60 km inland, indicating a strong influence from oceanic tides. Hydrodynamic and geoelectric modelling of the coastal aquifer suggests that observed pressure changes (giving rise to the streaming potential) are not sufficient to explain the magnitude of the observed SP fluctuations. Simulation of the exclusion-diffusion potential, produced by changes in concentration across the saline front, is required to match the SP data from the borehole, despite the front being located some distance away. In late summer of 2013 and 2014, seawater intrusion occurred in the coastal monitoring borehole. When referenced to the shallowest borehole electrode, there was a characteristic increase in SP within the array, several days before any measurable increase in salinity. The size of this precursor increased steadily with depth, typically reaching values close to 0.3 mV in the deepest electrode. Numerical modelling suggests that the exclusion-diffusion potential can explain the magnitude of the precursor, but that the polarity of the change in SP cannot be replicated assuming a homogeneous aquifer. Small-scale models of idealised Chalk blocks were used to simulate the effects of discrete fractures on the distribution of SP. Initial results suggest that comparatively large reductions in voltage can develop in the matrix ahead of the front, in conjunction with a reduced or absent precursor in the vicinity of a fracture. Geophysical logging indicates the presence of a

  3. Approaches in anomaly-based network intrusion detection systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, S.; Di Pietro, R.; Mancini, L.V.

    2008-01-01

    Anomaly-based network intrusion detection systems (NIDSs) can take into consideration packet headers, the payload, or a combination of both. We argue that payload-based approaches are becoming the most effective methods to detect attacks. Nowadays, attacks aim mainly to exploit vulnerabilities at

  4. On Emulation-Based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Abbasi, Ali; Wetzel, Jos; Bokslag, Wouter; Zambon, Emmanuele; Etalle, Sandro

    2014-01-01

    Emulation-based network intrusion detection systems have been devised to detect the presence of shellcode in network traffic by trying to execute (portions of) the network packet payloads in an in- strumented environment and checking the execution traces for signs of shellcode activity.

  5. On emulation-based network intrusion detection systems

    NARCIS (Netherlands)

    Abbasi, A.; Wetzels, J.; Bokslag, W.; Zambon, E.; Etalle, S.; Stavrou, A.; Bos, H.; Portokalidis, G.

    2014-01-01

    Emulation-based network intrusion detection systems have been devised to detect the presence of shellcode in network traffic by trying to execute (portions of) the network packet payloads in an instrumented environment and checking the execution traces for signs of shellcode activity.

  6. Approaches in Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro

    Anomaly-based network intrusion detection systems (NIDSs) can take into consideration packet headers, the payload, or a combination of both. We argue that payload-based approaches are becoming the most effective methods to detect attacks. Nowadays, attacks aim mainly to exploit vulnerabilities at

  7. Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM) in advanced metering infrastructure of smart grid.

    Science.gov (United States)

    Li, Yuancheng; Qiu, Rixuan; Jing, Sitong

    2018-01-01

    Advanced Metering Infrastructure (AMI) realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM) is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

  8. AdiosStMan: Parallelizing Casacore Table Data System using Adaptive IO System

    Science.gov (United States)

    Wang, R.; Harris, C.; Wicenec, A.

    2016-07-01

    In this paper, we investigate the Casacore Table Data System (CTDS) used in the casacore and CASA libraries, and methods to parallelize it. CTDS provides a storage manager plugin mechanism for third-party developers to design and implement their own CTDS storage managers. Having this in mind, we looked into various storage backend techniques that can possibly enable parallel I/O for CTDS by implementing new storage managers. After carrying on benchmarks showing the excellent parallel I/O throughput of the Adaptive IO System (ADIOS), we implemented an ADIOS based parallel CTDS storage manager. We then applied the CASA MSTransform frequency split task to verify the ADIOS Storage Manager. We also ran a series of performance tests to examine the I/O throughput in a massively parallel scenario.

  9. Nuclear data needs for non-intrusive inspection

    International Nuclear Information System (INIS)

    Smith, D. L.; Michlich, B. J.

    2000-01-01

    Various nuclear-based techniques are being explored for use in non-intrusive inspection. Their development is motivated by the need to prevent the proliferation of nuclear weapons, to thwart trafficking in illicit narcotics, to stop the transport of explosives by terrorist organizations, to characterize nuclear waste, and to deal with various other societal concerns. Non-intrusive methods are sought in order to optimize inspection speed, to minimize damage to packages and containers, to satisfy environmental, health and safety requirements, to adhere to legal requirements, and to avoid inconveniencing the innocent. These inspection techniques can be grouped into two major categories: active and passive. They almost always require the use of highly penetrating radiation and therefore are generally limited to neutrons and gamma rays. Although x-rays are widely employed for these purposes, their use does not constitute nuclear technology and therefore is not discussed here. This paper examines briefly the basic concepts associated with nuclear inspection and investigates the related nuclear data needs. These needs are illustrated by considering four of the methods currently being developed and tested

  10. Nuclear data needs for non-intrusive inspection

    International Nuclear Information System (INIS)

    Smith, D.L.; Micklich, B.J.

    2001-01-01

    Various nuclear-based techniques are being explored for use in non-intrusive inspection. Their development is motivated by the need to prevent the proliferation of nuclear weapons, to thwart trafficking in illicit narcotics, to stop the transport of explosives by terrorist organizations, to characterize nuclear waste, and to deal with various other societal concerns. Non-intrusive methods are sought in order to optimize inspection speed, to minimize damage to packages and containers, to satisfy environmental, health and safety requirements, to adhere to legal requirements, and to avoid inconveniencing the innocent. These inspection techniques can be grouped into two major categories: active and passive. They almost always require the use of highly penetrating radiation and therefore are generally limited to neutrons and gamma rays. Although x-rays are widely employed for these purposes, their use does not constitute 'nuclear technology' and therefore is not discussed here. This paper examines briefly the basic concepts associated with nuclear inspection and investigates the related nuclear data needs. These needs are illustrated by considering four of the methods currently being developed and tested. (author)

  11. Anomaly-based online intrusion detection system as a sensor for cyber security situational awareness system

    OpenAIRE

    Kokkonen, Tero

    2016-01-01

    Almost all the organisations and even individuals rely on complex structures of data networks and networked computer systems. That complex data ensemble, the cyber domain, provides great opportunities, but at the same time it offers many possible attack vectors that can be abused for cyber vandalism, cyber crime, cyber espionage or cyber terrorism. Those threats produce requirements for cyber security situational awareness and intrusion detection capability. This dissertation conc...

  12. Feature Selection of Network Intrusion Data using Genetic Algorithm and Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Iwan Syarif

    2016-12-01

    Full Text Available This paper describes the advantages of using Evolutionary Algorithms (EA for feature selection on network intrusion dataset. Most current Network Intrusion Detection Systems (NIDS are unable to detect intrusions in real time because of high dimensional data produced during daily operation. Extracting knowledge from huge data such as intrusion data requires new approach. The more complex the datasets, the higher computation time and the harder they are to be interpreted and analyzed. This paper investigates the performance of feature selection algoritms in network intrusiona data. We used Genetic Algorithms (GA and Particle Swarm Optimizations (PSO as feature selection algorithms. When applied to network intrusion datasets, both GA and PSO have significantly reduces the number of features. Our experiments show that GA successfully reduces the number of attributes from 41 to 15 while PSO reduces the number of attributes from 41 to 9. Using k Nearest Neighbour (k-NN as a classifier,the GA-reduced dataset which consists of 37% of original attributes, has accuracy improvement from 99.28% to 99.70% and its execution time is also 4.8 faster than the execution time of original dataset. Using the same classifier, PSO-reduced dataset which consists of 22% of original attributes, has the fastest execution time (7.2 times faster than the execution time of original datasets. However, its accuracy is slightly reduced 0.02% from 99.28% to 99.26%. Overall, both GA and PSO are good solution as feature selection techniques because theyhave shown very good performance in reducing the number of features significantly while still maintaining and sometimes improving the classification accuracy as well as reducing the computation time.

  13. Securing Cloud Computing from Different Attacks Using Intrusion Detection Systems

    Directory of Open Access Journals (Sweden)

    Omar Achbarou

    2017-03-01

    Full Text Available Cloud computing is a new way of integrating a set of old technologies to implement a new paradigm that creates an avenue for users to have access to shared and configurable resources through internet on-demand. This system has many common characteristics with distributed systems, hence, the cloud computing also uses the features of networking. Thus the security is the biggest issue of this system, because the services of cloud computing is based on the sharing. Thus, a cloud computing environment requires some intrusion detection systems (IDSs for protecting each machine against attacks. The aim of this work is to present a classification of attacks threatening the availability, confidentiality and integrity of cloud resources and services. Furthermore, we provide literature review of attacks related to the identified categories. Additionally, this paper also introduces related intrusion detection models to identify and prevent these types of attacks.

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

    Directory of Open Access Journals (Sweden)

    Eung Jun Cho

    2013-11-01

    Full Text Available 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.

  15. An adaptive structure data acquisition system using a graphical-based programming language

    Science.gov (United States)

    Baroth, Edmund C.; Clark, Douglas J.; Losey, Robert W.

    1992-01-01

    An example of the implementation of data fusion using a PC and a graphical programming language is discussed. A schematic of the data acquisition system and user interface panel for an adaptive structure test are presented. The computer programs (a series of icons 'wired' together) are also discussed. The way in which using graphical-based programming software to control a data acquisition system can simplify analysis of data, promote multidisciplinary interaction, and provide users a more visual key to understanding their data are shown.

  16. System-level support for intrusion recovery

    NARCIS (Netherlands)

    Bacs, Andrei; Vermeulen, Remco; Slowinska, Asia; Bos, Herbert

    2013-01-01

    Recovering from attacks is hard and gets harder as the time between the initial infection and its detection increases. Which files did the attackers modify? Did any of user data depend on malicious inputs? Can I still trust my own documents or binaries? When malcode has been active for some time and

  17. Enhancing Trust Management for Wireless Intrusion Detection via Traffic Sampling in the Era of Big Data

    DEFF Research Database (Denmark)

    Meng, Weizhi; Li, Wenjuan; Su, Chunhua

    2017-01-01

    many kinds of information among sensors, whereas such network is vulnerable to a wide range of attacks, especially insider attacks, due to its natural environment and inherent unreliable transmission. To safeguard its security, intrusion detection systems (IDSs) are widely adopted in a WSN to defend...... against insider attacks through implementing proper trustbased mechanisms. However, in the era of big data, sensors may generate excessive information and data, which could degrade the effectiveness of trust computation. In this paper, we focus on this challenge and propose a way of combining Bayesian......-based trust management with traffic sampling for wireless intrusion detection under a hierarchical structure. In the evaluation, we investigate the performance of our approach in both a simulated and a real network environment. Experimental results demonstrate that packet-based trust management would become...

  18. Master data extraction and adaptation based on collected production data in manufacturing execution systems

    OpenAIRE

    Dimitrov, T.; Baumann, M.; Schenk, M.

    2010-01-01

    This paper presents an approach to extraction and correction of manufacturing master data, needed by Manufacturing Execution Systems (MES) to control and schedule the production. The implementation of the created schedule and the improvement of Key Performance Indicators depends strongly on the quality of the master data. The master data of most enterprises ages or the enterprises cannot fully provide it, because a highly manual expense for statistical analysis and administration is needed. T...

  19. Network Intrusion Detection through Stacking Dilated Convolutional Autoencoders

    Directory of Open Access Journals (Sweden)

    Yang Yu

    2017-01-01

    Full Text Available Network intrusion detection is one of the most important parts for cyber security to protect computer systems against malicious attacks. With the emergence of numerous sophisticated and new attacks, however, network intrusion detection techniques are facing several significant challenges. The overall objective of this study is to learn useful feature representations automatically and efficiently from large amounts of unlabeled raw network traffic data by using deep learning approaches. We propose a novel network intrusion model by stacking dilated convolutional autoencoders and evaluate our method on two new intrusion detection datasets. Several experiments were carried out to check the effectiveness of our approach. The comparative experimental results demonstrate that the proposed model can achieve considerably high performance which meets the demand of high accuracy and adaptability of network intrusion detection systems (NIDSs. It is quite potential and promising to apply our model in the large-scale and real-world network environments.

  20. Industrial Control System Process-Oriented Intrusion Detection (iPoid) Algorithm

    Science.gov (United States)

    2016-08-01

    SUBJECT TERMS supervisory control and data acquisition (SCADA), Modbus, industrial control system, intrusion detection system 16. SECURITY...List of Tables iv Acknowledgments v 1. Background 1 2. iPoid Modbus Packet-Inspection Capability 2 2.1 Software Requirements 2 2.2 Startup ...Mr Curtis Arnold’s support of Industrial Control Systems–Supervisory Control and Data Acquisition research at the US Army Research Laboratory

  1. A modeling study of saltwater intrusion in the Andarax delta area using multiple data sources

    DEFF Research Database (Denmark)

    Antonsson, Arni Valur; Engesgaard, Peter Knudegaard; Jorreto, Sara

    context. The validity of a conceptual model is determined by different factors, where both data quantity and quality is of crucial importance. Often, when dealing with saltwater intrusion, data is limited. Therefore, using different sources (and types) of data can be beneficial and increase......In groundwater model development, construction of the conceptual model is one of the (initial and) critical aspects that determines the model reliability and applicability in terms of e.g. system (hydrogeological) understanding, groundwater quality predictions, and general use in water resources...

  2. Attack Pattern Analysis Framework for a Multiagent Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Krzysztof Juszczyszyn

    2008-08-01

    Full Text Available The paper proposes the use of attack pattern ontology and formal framework for network traffic anomalies detection within a distributed multi-agent Intrusion Detection System architecture. Our framework assumes ontology-based attack definition and distributed processing scheme with exchange of communicates between agents. The role of traffic anomalies detection was presented then it has been discussed how some specific values characterizing network communication can be used to detect network anomalies caused by security incidents (worm attack, virus spreading. Finally, it has been defined how to use the proposed techniques in distributed IDS using attack pattern ontology.

  3. Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

    Science.gov (United States)

    Mitra, Sunanda; Pemmaraju, Surya

    1992-01-01

    Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

  4. Hybrid Intrusion Detection System for DDoS Attacks

    Directory of Open Access Journals (Sweden)

    Özge Cepheli

    2016-01-01

    Full Text Available Distributed denial-of-service (DDoS attacks are one of the major threats and possibly the hardest security problem for today’s Internet. In this paper we propose a hybrid detection system, referred to as hybrid intrusion detection system (H-IDS, for detection of DDoS attacks. Our proposed detection system makes use of both anomaly-based and signature-based detection methods separately but in an integrated fashion and combines the outcomes of both detectors to enhance the overall detection accuracy. We apply two distinct datasets to our proposed system in order to test the detection performance of H-IDS and conclude that the proposed hybrid system gives better results than the systems based on nonhybrid detection.

  5. Hydrodynamic modeling of the intrusion phenomenon in water distribution systems; Modelacion hidrodinamica del fenomeno de intrusion en tuberia de abastecimiento

    Energy Technology Data Exchange (ETDEWEB)

    Lopez-Jimenez, Petra Amparo; Mora-Rodriguez, Jose de Jesus; Perez-Garcia, Rafael; Martinez-Solano, F. Javier [Universidad Politecnica de Valencia (Spain)

    2008-10-15

    This paper describes a strategy for the hydrodynamic modeling of the pathogen intrusion phenomenon in water distribution systems by the combination of a breakage with a depression situation. This scenario will be modeled computationally and experimentally. The phenomenon to be represented by both simulations is the same: the entrance of an external volume into the circulation of a main volume, known as a pathogen intrusion, as long as the main volume is potable water. To this end, a prototype and a computational model based on Computational Fluid Dynamics (CFD) are used, which allow visualizing the fields of speeds and pressures in a simulated form. With the comparison of the results of both models, conclusions will be drawn on the detail of the studied pathogen intrusion phenomenon. [Spanish] En el presente documento se describe una estrategia de modelacion del fenomeno hidrodinamico de la intrusion patogena en redes de distribucion de agua por combinacion de una rotura con una situacion de depresion. Este escenario sera modelado computacional y experimentalmente. El fenomeno que se desea representar con ambas simulaciones es el mismo: la entrada de un caudal externo a una conduccion para la que circula un caudal principal, denominado intrusion patogena, siempre y cuando el caudal principal sea agua potable. Para ello se dispone de un prototipo y un modelo computacional basado en la Dinamica de Fluidos Computacional (DFC de aqui en adelante), que permite visualizar los campos de velocidades y presiones de forma simulada. Con la comparacion de los resultados de ambos modelos se extraeran conclusiones sobre el detalle del fenomeno de la intrusion patogena estudiado.

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

    International Nuclear Information System (INIS)

    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

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

    Science.gov (United States)

    Hortos, William S.

    2007-09-01

    and trust neighborhood, collecting parametric information and executing assigned decision tasks. The communications overhead due to security mechanisms and the latency in network response are thus minimized by reducing the need to move large amounts of audit data through resource-limited nodes and by locating detection/identification programs closer to audit data. If network partitioning occurs due to uncoordinated node exhaustion, data compromise or other effects of the attacks, the mobile agents can continue to operate, thereby increasing fault tolerance in the network response to intrusions. Since the mobile agents behave like an ant colony in securing the WSN, published ant colony optimization (ACO) routines and other evolutionary algorithms are adapted to protect network security, using data at and through nodes to create audit records to detect and respond to denial-of-service attacks. Performance evaluations of algorithms are performed by simulation of a few intrusion attacks, such as black hole, flooding, Sybil and others, to validate the ability of the cross-layer algorithms to enable WSNs to survive the attacks. Results are compared for the different algorithms.

  8. Evolution of optically nondestructive and data-non-intrusive credit card verifiers

    Science.gov (United States)

    Sumriddetchkajorn, Sarun; Intaravanne, Yuttana

    2010-04-01

    Since the deployment of the credit card, the number of credit card fraud cases has grown rapidly with a huge amount of loss in millions of US dollars. Instead of asking more information from the credit card's holder or taking risk through payment approval, a nondestructive and data-non-intrusive credit card verifier is highly desirable before transaction begins. In this paper, we review optical techniques that have been proposed and invented in order to make the genuine credit card more distinguishable than the counterfeit credit card. Several optical approaches for the implementation of credit card verifiers are also included. In particular, we highlight our invention on a hyperspectral-imaging based portable credit card verifier structure that offers a very low false error rate of 0.79%. Other key features include low cost, simplicity in design and implementation, no moving part, no need of an additional decoding key, and adaptive learning.

  9. Data mining methods application in reflexive adaptation realization in e-learning systems

    Directory of Open Access Journals (Sweden)

    A. S. Bozhday

    2017-01-01

    Full Text Available In recent years, e-learning technologies are rapidly gaining momentum in their evolution. In this regard, issues related to improving the quality of software for virtual educational systems are becoming topical: increasing the period of exploitation of programs, increasing their reliability and flexibility. The above characteristics directly depend on the ability of the software system to adapt to changes in the domain, environment and user characteristics. In some cases, this ability is reduced to the timely optimization of the program’s own interfaces and data structure. At present, several approaches to creating mechanisms for self-optimization of software systems are known, but all of them have an insufficient degree of formalization and, as a consequence, weak universality. The purpose of this work is to develop the basics of the technology of self-optimization of software systems in the structure of e-learning. The proposed technology is based on the formulated and formalized principle of reflexive adaptation of software, applicable to a wide class of software systems and based on the discovery of new knowledge in the behavioral products of the system.To solve this problem, methods of data mining were applied. Data mining allows finding regularities in the functioning of software systems, which may not be obvious at the stage of their development. Finding such regularities and their subsequent analysis will make it possible to reorganize the structure of the system in a more optimal way and without human intervention, which will prolong the life cycle of the software and reduce the costs of its maintenance. Achieving this effect is important for e-learning systems, since they are quite expensive.The main results of the work include: the proposed classification of software adaptation mechanisms, taking into account the latest trends in the IT field in general and in the field of e-learning in particular; Formulation and formalization of

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

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Yan [Northwesten University

    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.

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

    Directory of Open Access Journals (Sweden)

    Jayakumar Kaliappan

    2015-01-01

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

  12. CRITICAL INFORMATION INFRASTRUCTURE SECURITY - NETWORK INTRUSION DETECTION SYSTEMS

    Directory of Open Access Journals (Sweden)

    Cristea DUMITRU

    2011-12-01

    Full Text Available Critical Information Infrastructure security will always be difficult to ensure, just because of the features that make it irreplaceable tor other critical infrastructures normal operation. It is decentralized, interconnected interdependent, controlled by multiple actors (mainly private and incorporating diverse types of technologies. It is almost axiomatic that the disruption of the Critical Information Infrastructure affects systems located much farther away, and the cyber problems have direct consequences on the real world. Indeed the Internet can be used as a multiplier in order to amplify the effects of an attack on some critical infrastructures. Security challenges increase with the technological progress. One of the last lines of defense which comes to complete the overall security scheme of the Critical Information Infrastructure is represented by the Network Intrusion Detection Systems.

  13. Automatic Extraction and Coordination of Audit Data and Features for Intrusion and Damage Assessment

    National Research Council Canada - National Science Library

    Ye, Nong

    2006-01-01

    .... We create a new attack-norm separation approach to developing detection models for building cyber sensors monitoring and identifying intrusion data characteristics at various points along the path...

  14. System and method for the adaptive mapping of matrix data to sets of polygons

    Science.gov (United States)

    Burdon, David (Inventor)

    2003-01-01

    A system and method for converting bitmapped data, for example, weather data or thermal imaging data, to polygons is disclosed. The conversion of the data into polygons creates smaller data files. The invention is adaptive in that it allows for a variable degree of fidelity of the polygons. Matrix data is obtained. A color value is obtained. The color value is a variable used in the creation of the polygons. A list of cells to check is determined based on the color value. The list of cells to check is examined in order to determine a boundary list. The boundary list is then examined to determine vertices. The determination of the vertices is based on a prescribed maximum distance. When drawn, the ordered list of vertices create polygons which depict the cell data. The data files which include the vertices for the polygons are much smaller than the corresponding cell data files. The fidelity of the polygon representation can be adjusted by repeating the logic with varying fidelity values to achieve a given maximum file size or a maximum number of vertices per polygon.

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

    Science.gov (United States)

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

    2017-01-01

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

  16. INTRUSION DETECTION PREVENTION SYSTEM (IDPS PADA LOCAL AREA NETWORK (LAN

    Directory of Open Access Journals (Sweden)

    Didit Suhartono

    2015-02-01

    Full Text Available Penelitian ini berjudul “Intrusion Detection Prevention System Local Area Network (LAN” yang bertujuan untuk memproteksi jaringan dari usaha- usaha penyusupan yang dilakukan oleh seorang intruder. Metode yang digunakan pada penelitian ini adalah menggunakan metode kerangka pikir sebagai acuan dari tahap- tahap penelitian yang penulis lakukan. IDS difungsikan sebagai pendeteksi adanya serangan sesuai rule yang ada kemudian pesan peringatan disimpan dalam database dan dikirim via sms kepada seorang network administrator, sedangkan Firewall digunakan sebagai packet filtering dengan cara menentukan security policy yang dinilai penting. Hasilnya adalah ketika IDS memberikanpesan peringatan ketika ada serangan, seorang network administrator dapat memblok adanya serangan tersebut dengan cara manual dengan firewall, ataupun firewall akan memblok sendiri serangan tersebut sesuai dengan security policy yang diterapkan oleh network adminisrator sebelumnya

  17. Intrusion detection system using Online Sequence Extreme Learning Machine (OS-ELM in advanced metering infrastructure of smart grid.

    Directory of Open Access Journals (Sweden)

    Yuancheng Li

    Full Text Available Advanced Metering Infrastructure (AMI realizes a two-way communication of electricity data through by interconnecting with a computer network as the core component of the smart grid. Meanwhile, it brings many new security threats and the traditional intrusion detection method can't satisfy the security requirements of AMI. In this paper, an intrusion detection system based on Online Sequence Extreme Learning Machine (OS-ELM is established, which is used to detecting the attack in AMI and carrying out the comparative analysis with other algorithms. Simulation results show that, compared with other intrusion detection methods, intrusion detection method based on OS-ELM is more superior in detection speed and accuracy.

  18. A Neuro-genetic Based Short-term Forecasting Framework for Network Intrusion Prediction System

    Institute of Scientific and Technical Information of China (English)

    Siva S. Sivatha Sindhu; S. Geetha; M. Marikannan; A. Kannan

    2009-01-01

    Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attacks made in this way, usually done by "authorized" users of the system, cannot be immediately traced. Because the idea of filtering the traffic at the entrance door, by using firewalls and the like, is not completely successful, the use of intrusion detection systems should be considered to increase the defense capacity of an information system. An intrusion detection system (IDS) is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current IDS depends on the system operators in working out the tuning solution and in integrating it into the detection model. Furthermore, an extensive effort is required to tackle the newly evolving attacks and a deep study is necessary to categorize it into the respective classes. To reduce this dependence, an automatically evolving anomaly IDS using neuro-genetic algorithm is presented. The proposed system automatically tunes the detection model on the fly according to the feedback provided by the system operator when false predictions are encountered. The system has been evaluated using the Knowledge Discovery in Databases Conference (KDD 2009) intrusion detection dataset. Genetic paradigm is employed to choose the predominant features, which reveal the occurrence of intrusions. The neuro-genetic IDS (NGIDS) involves calculation of weightage value for each of the categorical attributes so that data of uniform representation can be processed by the neuro-genetic algorithm. In this system unauthorized invasion of a user are identified and newer types of attacks are sensed and classified respectively by the neuro-genetic algorithm. The experimental results obtained in this

  19. Thermal Error Modelling of the Spindle Using Data Transformation and Adaptive Neurofuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Yanlei Li

    2015-01-01

    Full Text Available This paper proposes a new method for predicting spindle deformation based on temperature data. The method introduces the adaptive neurofuzzy inference system (ANFIS, which is a neurofuzzy modeling approach that integrates the kernel and geometrical transformations. By utilizing data transformation, the number of ANFIS rules can be effectively reduced and the predictive model structure can be simplified. To build the predictive model, we first map the original temperature data to a feature space with Gaussian kernels. We then process the mapped data with the geometrical transformation and make the data gather in the square region. Finally, the transformed data are used as input to train the ANFIS. A verification experiment is conducted to evaluate the performance of the proposed method. Six Pt100 thermal resistances are used to monitor the spindle temperature, and a laser displacement sensor is used to detect the spindle deformation. Experimental results show that the proposed method can precisely predict the spindle deformation and greatly improve the thermal performance of the spindle. Compared with back propagation (BP networks, the proposed method is more suitable for complex working conditions in practical applications.

  20. The Use of Adaptive Traffic Signal Systems Based on Floating Car Data

    Directory of Open Access Journals (Sweden)

    Vittorio Astarita

    2017-01-01

    Full Text Available This paper presents a simple concept which has not been, up to now, thoroughly explored in scientific research: the use of information coming from the network of Internet connected mobile devices (on vehicles to regulate traffic light systems. Three large-scale changes are going to shape the future of transportation and could lead to the regulation of traffic signal system based on floating car data (FCD: (i the implementation of Internet connected cars with global navigation satellite (GNSS system receivers and the autonomous car revolution; (ii the spreading of mobile cooperative Web 2.0 and the extension to connected vehicles; (iii an increasing need for sustainability of transportation in terms of energy efficiency, traffic safety, and environmental issues. Up to now, the concept of floating car data (FCD has only been extensively used to obtain traffic information and estimate traffic parameters. Traffic lights regulation based on FCD technology has not been fully researched since the implementation requires new ideas and algorithms. This paper intends to provide a seminal insight into the important issue of adaptive traffic light based on FCD by presenting ideas that can be useful to researchers and engineers in the long-term task of developing new algorithms and systems that may revolutionize the way traffic lights are regulated.

  1. Personalized links recommendation based on data mining in adaptive educational hypermedia systems

    NARCIS (Netherlands)

    Romero, C.; Ventura, S.; Delgado, J.A.; De Bra, P.M.E.; Duval, E.; Klamma, R.; Wolpers, M.

    2007-01-01

    In this paper, we describe a personalized recommender system that uses web mining techniques for recommending a student which (next) links to visit within an adaptable educational hypermedia system. We present a specific mining tool and a recommender engine that we have integrated in the AHA! system

  2. A Frequency-Based Approach to Intrusion Detection

    Directory of Open Access Journals (Sweden)

    Mian Zhou

    2004-06-01

    Full Text Available Research on network security and intrusion detection strategies presents many challenging issues to both theoreticians and practitioners. Hackers apply an array of intrusion and exploit techniques to cause disruption of normal system operations, but on the defense, firewalls and intrusion detection systems (IDS are typically only effective in defending known intrusion types using their signatures, and are far less than mature when faced with novel attacks. In this paper, we adapt the frequency analysis techniques such as the Discrete Fourier Transform (DFT used in signal processing to the design of intrusion detection algorithms. We demonstrate the effectiveness of the frequency-based detection strategy by running synthetic network intrusion data in simulated networks using the OPNET software. The simulation results indicate that the proposed intrusion detection strategy is effective in detecting anomalous traffic data that exhibit patterns over time, which include several types of DOS and probe attacks. The significance of this new strategy is that it does not depend on the prior knowledge of attack signatures, thus it has the potential to be a useful supplement to existing signature-based IDS and firewalls.

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

    Science.gov (United States)

    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

  4. Data-driven adaptive fractional order PI control for PMSM servo system with measurement noise and data dropouts.

    Science.gov (United States)

    Xie, Yuanlong; Tang, Xiaoqi; Song, Bao; Zhou, Xiangdong; Guo, Yixuan

    2018-04-01

    In this paper, data-driven adaptive fractional order proportional integral (AFOPI) control is presented for permanent magnet synchronous motor (PMSM) servo system perturbed by measurement noise and data dropouts. The proposed method directly exploits the closed-loop process data for the AFOPI controller design under unknown noise distribution and data missing probability. Firstly, the proposed method constructs the AFOPI controller tuning problem as a parameter identification problem using the modified l p norm virtual reference feedback tuning (VRFT). Then, iteratively reweighted least squares is integrated into the l p norm VRFT to give a consistent compensation solution for the AFOPI controller. The measurement noise and data dropouts are estimated and eliminated by feedback compensation periodically, so that the AFOPI controller is updated online to accommodate the time-varying operating conditions. Moreover, the convergence and stability are guaranteed by mathematical analysis. Finally, the effectiveness of the proposed method is demonstrated both on simulations and experiments implemented on a practical PMSM servo system. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Nuisance alarm suppression techniques for fibre-optic intrusion detection systems

    Science.gov (United States)

    Mahmoud, Seedahmed S.; Visagathilagar, Yuvaraja; Katsifolis, Jim

    2012-02-01

    The suppression of nuisance alarms without degrading sensitivity in fibre-optic intrusion detection systems is important for maintaining acceptable performance. Signal processing algorithms that maintain the POD and minimize nuisance alarms are crucial for achieving this. A level crossings algorithm is presented for suppressing torrential rain-induced nuisance alarms in a fibre-optic fence-based perimeter intrusion detection system. Results show that rain-induced nuisance alarms can be suppressed for rainfall rates in excess of 100 mm/hr, and intrusion events can be detected simultaneously during rain periods. The use of a level crossing based detection and novel classification algorithm is also presented demonstrating the suppression of nuisance events and discrimination of nuisance and intrusion events in a buried pipeline fibre-optic intrusion detection system. The sensor employed for both types of systems is a distributed bidirectional fibre-optic Mach Zehnder interferometer.

  6. Diagnostic Indicators for Shipboard Mechanical Systems Using Non-Intrusive Load Monitoring

    National Research Council Canada - National Science Library

    McKay, Thomas D

    2006-01-01

    This thesis examines the use of Non-intrusive Load Monitoring (NILM) in auxiliary shipboard systems, such as a low pressure air system, to determine the state of equipment in larger connected systems, such as the main propulsion engines...

  7. The 2001 Mt. Etna eruption: new constraints on the intrusive mechanism from ground deformation data

    Science.gov (United States)

    Palano, Mimmo; González, Pablo J.

    2013-04-01

    The occurrence of seismic swarms beneath the SW flank of Mt. Etna, often observed just a few months before an eruption, has been considered as the fragile response to a magma intrusion (Bonanno et al., 2011 and reference therein). These intrusions and/or pressurization of deep magmatic bodies, have been able to significantly affect the seismic pattern within the volcano edifice, leading to a changes in the local stress field. For example, during the months preceding the 1991-1993 Mt. Etna eruption, shallow intense seismic swarms (4-6 km deep) occurring in the SW flank (e.g. Cocina et al., 1998), related to the magma intrusion before the eruption onset, were observed contemporaneously with a rotation of stress field of about 90°. A similar scenario was observed during January 1998, when a magma recharging phases induced a local rotation of stress tensor, forcing a buried fault zone located beneath the SW flank of Mt. Etna to slip as a right-lateral strike-slip fault (Bonanno et al., 2011). This fault system was forced to slip again, during late April 2001 (more than 200 events in less than 5 days; maximum Magnitude = 3.6) by the pressurization of the magmatic bodies feeding the July-August 2001 Mt. Etna eruption. Here we analyzed in detail the July-August 2001 Mt. Etna eruption as well as the dynamics preceding this event, by using a large dataset of geodetic data (GPS and synthetic aperture radar interferometry) collected between July 2000 and August 2001. References Cocina, O., Neri, G., Privitera, E. and Spampinato S., 1998. Seismogenic stress field beneath Mt. Etna South Italy and possible relationships with volcano-tectonic features. J. Volcanol. Geotherm. Res., 83, 335-348. Bonanno A., Palano M., Privitera E., Gresta S., Puglisi G., 2011. Magma intrusion mechanisms and redistribution of seismogenic stress at Mt. Etna volcano (1997-1998). Terra Nova, 23, 339-348, doi: 10.1111/j.1365-3121.2011.01019.x, 2011.

  8. Duo: Software Defined Intrusion Tolerant System Using Dual Cluster

    Directory of Open Access Journals (Sweden)

    Yongjae Lee

    2018-01-01

    Full Text Available An intrusion tolerant system (ITS is a network security system that is composed of redundant virtual servers that are online only in a short time window, called exposure time. The servers are periodically recovered to their clean state, and any infected servers are refreshed again, so attackers have insufficient time to succeed in breaking into the servers. However, there is a conflicting interest in determining exposure time, short for security and long for performance. In other words, the short exposure time can increase security but requires more servers to run in order to process requests in a timely manner. In this paper, we propose Duo, an ITS incorporated in SDN, which can reduce exposure time without consuming computing resources. In Duo, there are two types of servers: some servers with long exposure time (White server and others with short exposure time (Gray server. Then, Duo classifies traffic into benign and suspicious with the help of SDN/NFV technology that also allows dynamically forwarding the classified traffic to White and Gray servers, respectively, based on the classification result. By reducing exposure time of a set of servers, Duo can decrease exposure time on average. We have implemented the prototype of Duo and evaluated its performance in a realistic environment.

  9. Optic Nerve Stimulation System with Adaptive Wireless Powering and Data Telemetry

    Directory of Open Access Journals (Sweden)

    Xing Li

    2017-12-01

    Full Text Available To treat retinal degenerative diseases, a transcorneal electrical stimulation-based system is proposed, which consists of an eye implant and an external component. The eye implant is wirelessly powered and controlled by the external component to generate the required bi-polar current pattern for transcorneal stimulation with an amplitude range of 5 μA to 320 μA, a frequency range of 10 Hz to 160 Hz and a duty ratio range of 2.5% to 20%. Power delivery control includes power boosting in preparation for stimulation, and normal power regulation that adapts to both coupling and load variations. Only one pair of coils is used for both the power link and the bi-directional data link. Except for the secondary coil, the eye implant is fully integrated on chip and is fabricated using UMC (United Microelectronics Corporation, Hsinchu, Taiwan 0.13 μm complementary metal-oxide-semiconductor (CMOS process with a size of 1.5 mm × 1.5 mm. The secondary coil is fabricated on a printed circuit board (PCB with a diameter of only 4.4 mm. After coating with biocompatible silicone, the whole implant has dimensions of 6 mm in diameter with a thickness of less than 1 mm. The whole device can be put onto the sclera and beneath the eye’s conjunctiva. System functionality and electrical performance are demonstrated with measurement results.

  10. A New Intrusion Detection System Based on KNN Classification Algorithm in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Wenchao Li

    2014-01-01

    abnormal nodes from normal nodes by observing their abnormal behaviors, and we analyse parameter selection and error rate of the intrusion detection system. The paper elaborates on the design and implementation of the detection system. This system has achieved efficient, rapid intrusion detection by improving the wireless ad hoc on-demand distance vector routing protocol (Ad hoc On-Demand Distance the Vector Routing, AODV. Finally, the test results show that: the system has high detection accuracy and speed, in accordance with the requirement of wireless sensor network intrusion detection.

  11. Experimental Study of Nuclear Security System Components for Achieving the Intrusion Process via Sensor's Network System

    International Nuclear Information System (INIS)

    EL-Kafas, A.A.

    2011-01-01

    Cluster sensors are one of nuclear security system components which are used to detect any intrusion process of the nuclear sites. In this work, an experimental measuring test for sensor performance and procedures are presented. Sensor performance testing performed to determine whether a particular sensor will be acceptable in a proposed design. We have access to a sensors test field in which the sensor of interest is already properly installed and the parameters have been set to optimal levels by preliminary testing. The glass-breakage (G.B) and open door (O.D) sensors construction, operation and design for the investigated nuclear site are explained. Intrusion tests were carried out inside the field areas of the sensors to evaluate the sensor performance during the intrusion process. Experimental trials were performed for achieving the intrusion process via sensor network system. The performance and intrusion senses of cluster sensors inside the internal zones was recorded and evaluated. The obtained results explained that the tested and experimented G.B sensors have a probability of detection P (D) value 65% founded, and 80% P (D) of Open-door sensor

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

    Science.gov (United States)

    Shyu, Mei-Ling; Sainani, Varsha

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

  13. Optimizing the data acquisition rate for a remotely controllable structural monitoring system with parallel operation and self-adaptive sampling

    International Nuclear Information System (INIS)

    Sheng, Wenjuan; Guo, Aihuang; Liu, Yang; Azmi, Asrul Izam; Peng, Gang-Ding

    2011-01-01

    We present a novel technique that optimizes the real-time remote monitoring and control of dispersed civil infrastructures. The monitoring system is based on fiber Bragg gating (FBG) sensors, and transfers data via Ethernet. This technique combines parallel operation and self-adaptive sampling to increase the data acquisition rate in remote controllable structural monitoring systems. The compact parallel operation mode is highly efficient at achieving the highest possible data acquisition rate for the FBG sensor based local data acquisition system. Self-adaptive sampling is introduced to continuously coordinate local acquisition and remote control for data acquisition rate optimization. Key issues which impact the operation of the whole system, such as the real-time data acquisition rate, data processing capability, and buffer usage, are investigated. The results show that, by introducing parallel operation and self-adaptive sampling, the data acquisition rate can be increased by several times without affecting the system operating performance on both local data acquisition and remote process control

  14. Boosting Web Intrusion Detection Systems by Inferring Positive Signatures

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro

    2008-01-01

    We present a new approach to anomaly-based network intrusion detection for web applications. This approach is based on dividing the input parameters of the monitored web application in two groups: the "regular" and the "irregular" ones, and applying a new method for anomaly detection on the

  15. A Metrics-Based Approach to Intrusion Detection System Evaluation for Distributed Real-Time Systems

    Science.gov (United States)

    2002-04-01

    Based Approach to Intrusion Detection System Evaluation for Distributed Real - Time Systems Authors: G. A. Fink, B. L. Chappell, T. G. Turner, and...Distributed, Security. 1 Introduction Processing and cost requirements are driving future naval combat platforms to use distributed, real - time systems of...distributed, real - time systems . As these systems grow more complex, the timing requirements do not diminish; indeed, they may become more constrained

  16. System using data compression and hashing adapted for use for multimedia encryption

    Science.gov (United States)

    Coffland, Douglas R [Livermore, CA

    2011-07-12

    A system and method is disclosed for multimedia encryption. Within the system of the present invention, a data compression module receives and compresses a media signal into a compressed data stream. A data acquisition module receives and selects a set of data from the compressed data stream. And, a hashing module receives and hashes the set of data into a keyword. The method of the present invention includes the steps of compressing a media signal into a compressed data stream; selecting a set of data from the compressed data stream; and hashing the set of data into a keyword.

  17. Novel Non-Intrusive Vibration Monitoring System for Turbopumps, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — ASRI proposes to develop an advanced and commercially viable Non-Intrusive Vibration Monitoring System (NI-VMS) which can provide effective on-line/off-line engine...

  18. Novel Non-Intrusive Vibration Monitoring System for Turbopumps, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — AI Signal Research, Inc. proposes to develop a Non-Intrusive Vibration Measurement System (NI-VMS) for turbopumps which will provide effective on-board/off-board...

  19. Multi-Use Non-Intrusive Flow Characterization System (FCS), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The innovation is a Multi-Use Non-Intrusive Flow Characterization System (FCS) for densified, normal boiling point, and two-phase cryogenic flows, capable of...

  20. Computational neural network regression model for Host based Intrusion Detection System

    Directory of Open Access Journals (Sweden)

    Sunil Kumar Gautam

    2016-09-01

    Full Text Available The current scenario of information gathering and storing in secure system is a challenging task due to increasing cyber-attacks. There exists computational neural network techniques designed for intrusion detection system, which provide security to single machine and entire network's machine. In this paper, we have used two types of computational neural network models, namely, Generalized Regression Neural Network (GRNN model and Multilayer Perceptron Neural Network (MPNN model for Host based Intrusion Detection System using log files that are generated by a single personal computer. The simulation results show correctly classified percentage of normal and abnormal (intrusion class using confusion matrix. On the basis of results and discussion, we found that the Host based Intrusion Systems Model (HISM significantly improved the detection accuracy while retaining minimum false alarm rate.

  1. Large scale applicability of a Fully Adaptive Non-Intrusive Spectral Projection technique: Sensitivity and uncertainty analysis of a transient

    International Nuclear Information System (INIS)

    Perkó, Zoltán; Lathouwers, Danny; Kloosterman, Jan Leen; Hagen, Tim van der

    2014-01-01

    Highlights: • Grid and basis adaptive Polynomial Chaos techniques are presented for S and U analysis. • Dimensionality reduction and incremental polynomial order reduce computational costs. • An unprotected loss of flow transient is investigated in a Gas Cooled Fast Reactor. • S and U analysis is performed with MC and adaptive PC methods, for 42 input parameters. • PC accurately estimates means, variances, PDFs, sensitivities and uncertainties. - Abstract: Since the early years of reactor physics the most prominent sensitivity and uncertainty (S and U) analysis methods in the nuclear community have been adjoint based techniques. While these are very effective for pure neutronics problems due to the linearity of the transport equation, they become complicated when coupled non-linear systems are involved. With the continuous increase in computational power such complicated multi-physics problems are becoming progressively tractable, hence affordable and easily applicable S and U analysis tools also have to be developed in parallel. For reactor physics problems for which adjoint methods are prohibitive Polynomial Chaos (PC) techniques offer an attractive alternative to traditional random sampling based approaches. At TU Delft such PC methods have been studied for a number of years and this paper presents a large scale application of our Fully Adaptive Non-Intrusive Spectral Projection (FANISP) algorithm for performing the sensitivity and uncertainty analysis of a Gas Cooled Fast Reactor (GFR) Unprotected Loss Of Flow (ULOF) transient. The transient was simulated using the Cathare 2 code system and a fully detailed model of the GFR2400 reactor design that was investigated in the European FP7 GoFastR project. Several sources of uncertainty were taken into account amounting to an unusually high number of stochastic input parameters (42) and numerous output quantities were investigated. The results show consistently good performance of the applied adaptive PC

  2. Abstracting massive data for lightweight intrusion detection in computer networks

    KAUST Repository

    Wang, Wei; Liu, Jiqiang; Pitsilis, Georgios; Zhang, Xiangliang

    2016-01-01

    detection. Data abstraction refers to abstract or extract the most relevant information from the massive dataset. In this work, we propose three strategies of data abstraction, namely, exemplar extraction, attribute selection and attribute abstraction. We

  3. Scalable High-Performance Parallel Design for Network Intrusion Detection Systems on Many-Core Processors

    OpenAIRE

    Jiang, Hayang; Xie, Gaogang; Salamatian, Kavé; Mathy, Laurent

    2013-01-01

    Network Intrusion Detection Systems (NIDSes) face significant challenges coming from the relentless network link speed growth and increasing complexity of threats. Both hardware accelerated and parallel software-based NIDS solutions, based on commodity multi-core and GPU processors, have been proposed to overcome these challenges. Network Intrusion Detection Systems (NIDSes) face significant challenges coming from the relentless network link speed growth and increasing complexity of threats. ...

  4. Volcano monitoring using GPS: Developing data analysis strategies based on the June 2007 Kīlauea Volcano intrusion and eruption

    Science.gov (United States)

    Larson, Kristine M.; Poland, Michael; Miklius, Asta

    2010-01-01

    The global positioning system (GPS) is one of the most common techniques, and the current state of the art, used to monitor volcano deformation. In addition to slow (several centimeters per year) displacement rates, GPS can be used to study eruptions and intrusions that result in much larger (tens of centimeters over hours-days) displacements. It is challenging to resolve precise positions using GPS at subdaily time intervals because of error sources such as multipath and atmospheric refraction. In this paper, the impact of errors due to multipath and atmospheric refraction at subdaily periods is examined using data from the GPS network on Kīlauea Volcano, Hawai'i. Methods for filtering position estimates to enhance precision are both simulated and tested on data collected during the June 2007 intrusion and eruption. Comparisons with tiltmeter records show that GPS instruments can precisely recover the timing of the activity.

  5. Adaptation in Living Systems

    Science.gov (United States)

    Tu, Yuhai; Rappel, Wouter-Jan

    2018-03-01

    Adaptation refers to the biological phenomenon where living systems change their internal states in response to changes in their environments in order to maintain certain key functions critical for their survival and fitness. Adaptation is one of the most ubiquitous and arguably one of the most fundamental properties of living systems. It occurs throughout all biological scales, from adaptation of populations of species over evolutionary time to adaptation of a single cell to different environmental stresses during its life span. In this article, we review some of the recent progress made in understanding molecular mechanisms of cellular-level adaptation. We take the minimalist (or the physicist) approach and study the simplest systems that exhibit generic adaptive behaviors, namely chemotaxis in bacterium cells (Escherichia coli) and eukaryotic cells (Dictyostelium). We focus on understanding the basic biochemical interaction networks that are responsible for adaptation dynamics. By combining theoretical modeling with quantitative experimentation, we demonstrate universal features in adaptation as well as important differences in different cellular systems. Future work in extending the modeling framework to study adaptation in more complex systems such as sensory neurons is also discussed.

  6. Bald Mountain gold mining district, Nevada: A Jurassic reduced intrusion-related gold system

    Science.gov (United States)

    Nutt, C.J.; Hofstra, A.H.

    2007-01-01

    The Bald Mountain mining district has produced about 2 million ounces (Moz) of An. Geologic mapping, field relationships, geochemical data, petrographic observations, fluid inclusion characteristics, and Pb, S, O, and H isotope data indicate that An mineralization was associated with a reduced Jurassic intrusion. Gold deposits are localized within and surrounding a Jurassic (159 Ma) quartz monzonite porphyry pluton and dike complex that intrudes Cambrian to Mississippian carbonate and clastic rocks. The pluton, associated dikes, and An mineralization were controlled by a crustal-scale northwest-trending structure named the Bida trend. Gold deposits are localized by fracture networks in the pluton and the contact metamorphic aureole, dike margins, high-angle faults, and certain strata or shale-limestone contacts in sedimentary rocks. Gold mineralization was accompanied by silicification and phyllic alteration, ??argillic alteration at shallow levels. Although An is typically present throughout, the system exhibits a classic concentric geochemical zonation pattern with Mo, W, Bi, and Cu near the center, Ag, Pb, and Zn at intermediate distances, and As and Sb peripheral to the intrusion. Near the center of the system, micron-sized native An occurs with base metal sulfides and sulfosalts. In peripheral deposits and in later stages of mineralization, Au is typically submicron in size and resides in pyrite or arsenopyrite. Electron microprobe and laser ablation ICP-MS analyses show that arsenopyrite, pyrite, and Bi sulfide minerals contain 10s to 1,000s of ppm Au. Ore-forming fluids were aqueous and carbonic at deep levels and episodically hypersaline at shallow levels due to boiling. The isotopic compositions of H and O in quartz and sericite and S and Pb in sulfides are indicative of magmatic ore fluids with sedimentary sulfur. Together, the evidence suggests that Au was introduced by reduced S-bearing magmatic fluids derived from a reduced intrusion. The reduced

  7. A data-driven adaptive controller for a class of unknown nonlinear discrete-time systems with estimated PPD

    Directory of Open Access Journals (Sweden)

    Chidentree Treesatayapun

    2015-06-01

    Full Text Available An adaptive control scheme based on data-driven controller (DDC is proposed in this article. Unlike several DDC techniques, the proposed controller is constructed by an adaptive fuzzy rule emulated network (FREN which is able to include human knowledge based on controlled plant's input–output signals within the format of IF-THEN rules. Regarding to this advantage, an on-line estimation of pseudo partial derivative (PPD and resetting algorithms, which are commonly used by DDC, can be omitted here. Furthermore, a novel adaptive algorithm is introduced to minimize for both tracking error and control effort with stability analysis for the closed-loop system. The experimental system with brushed DC-motor current control is constructed to validate the performance of the proposed control scheme. Comparative results with conventional DDC and radial basis function (RBF controllers demonstrate that the proposed controller can provide the less tracking error and minimize the control effort.

  8. Fast and Adaptive Lossless On-Board Hyperspectral Data Compression System for Space Applications

    Science.gov (United States)

    Aranki, Nazeeh; Bakhshi, Alireza; Keymeulen, Didier; Klimesh, Matthew

    2009-01-01

    Efficient on-board lossless hyperspectral data compression reduces the data volume necessary to meet NASA and DoD limited downlink capabilities. The techniques also improves signature extraction, object recognition and feature classification capabilities by providing exact reconstructed data on constrained downlink resources. At JPL a novel, adaptive and predictive technique for lossless compression of hyperspectral data was recently developed. This technique uses an adaptive filtering method and achieves a combination of low complexity and compression effectiveness that far exceeds state-of-the-art techniques currently in use. The JPL-developed 'Fast Lossless' algorithm requires no training data or other specific information about the nature of the spectral bands for a fixed instrument dynamic range. It is of low computational complexity and thus well-suited for implementation in hardware, which makes it practical for flight implementations of pushbroom instruments. A prototype of the compressor (and decompressor) of the algorithm is available in software, but this implementation may not meet speed and real-time requirements of some space applications. Hardware acceleration provides performance improvements of 10x-100x vs. the software implementation (about 1M samples/sec on a Pentium IV machine). This paper describes a hardware implementation of the JPL-developed 'Fast Lossless' compression algorithm on a Field Programmable Gate Array (FPGA). The FPGA implementation targets the current state of the art FPGAs (Xilinx Virtex IV and V families) and compresses one sample every clock cycle to provide a fast and practical real-time solution for Space applications.

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

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Dr. Li [University of Tennessee

    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.

  10. Turbine system and adapter

    Science.gov (United States)

    Hogberg, Nicholas Alvin; Garcia-Crespo, Andres Jose

    2017-05-30

    A turbine system and adapter are disclosed. The adapter includes a turbine attachment portion having a first geometry arranged to receive a corresponding geometry of a wheelpost of a turbine rotor, and a bucket attachment portion having a second geometry arranged to receive a corresponding geometry of a root portion of a non-metallic turbine bucket. Another adapter includes a turbine attachment portion arranged to receive a plurality of wheelposts of a turbine rotor, and a bucket attachment portion arranged to receive a plurality of non-metallic turbine buckets having single dovetail configuration root portions. The turbine system includes a turbine rotor wheel configured to receive metal buckets, at least one adapter secured to at least one wheelpost on the turbine rotor wheel, and at least one non-metallic bucket secured to the at least one adapter.

  11. Calibrating a Salt Water Intrusion Model with Time-Domain Electromagnetic Data

    DEFF Research Database (Denmark)

    Herckenrath, Daan; Odlum, Nick; Nenna, Vanessa

    2013-01-01

    Salt water intrusion models are commonly used to support groundwater resource management in coastal aquifers. Concentration data used for model calibration are often sparse and limited in spatial extent. With airborne and ground-based electromagnetic surveys, electrical resistivity models can......, we perform a coupled hydrogeophysical inversion (CHI) in which we use a salt water intrusion model to interpret the geophysical data and guide the geophysical inversion. We refer to this methodology as a Coupled Hydrogeophysical Inversion-State (CHI-S), in which simulated salt concentrations...... are transformed to an electrical resistivity model, after which a geophysical forward response is calculated and compared with the measured geophysical data. This approach was applied for a field site in Santa Cruz County, California, where a time-domain electromagnetic (TDEM) dataset was collected...

  12. When Intrusion Detection Meets Blockchain Technology: A Review

    DEFF Research Database (Denmark)

    Meng, Weizhi; Tischhauser, Elmar Wolfgang; Wang, Qingju

    2018-01-01

    developed, which allow IDS nodes to exchange data with each other. However, data and trust management still remain two challenges for current detection architectures, which may degrade the effectiveness of such detection systems. In recent years, blockchain technology has shown its adaptability in many...... fields such as supply chain management, international payment, interbanking and so on. As blockchain can protect the integrity of data storage and ensure process transparency, it has a potential to be applied to intrusion detection domain. Motivated by this, this work provides a review regarding...... the intersection of IDSs and blockchains. In particular, we introduce the background of intrusion detection and blockchain, discuss the applicability of blockchain to intrusion detection, and identify open challenges in this direction....

  13. From intrusive to oscillating thoughts.

    Science.gov (United States)

    Peirce, Anne Griswold

    2007-10-01

    This paper focused on the possibility that intrusive thoughts (ITs) are a form of an evolutionary, adaptive, and complex strategy to prepare for and resolve stressful life events through schema formation. Intrusive thoughts have been studied in relation to individual conditions, such as traumatic stress disorder and obsessive-compulsive disorder. They have also been documented in the average person experiencing everyday stress. In many descriptions of thought intrusion, it is accompanied by thought suppression. Several theories have been put forth to describe ITs, although none provides a satisfactory explanation as to whether ITs are a normal process, a normal process gone astray, or a sign of pathology. There is also no consistent view of the role that thought suppression plays in the process. I propose that thought intrusion and thought suppression may be better understood by examining them together as a complex and adaptive mechanism capable of escalating in times of need. The ability of a biological mechanism to scale up in times of need is one hallmark of a complex and adaptive system. Other hallmarks of complexity, including self-similarity across scales, sensitivity to initial conditions, presence of feedback loops, and system oscillation, are also discussed in this article. Finally, I propose that thought intrusion and thought suppression are better described together as an oscillatory cycle.

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

    Science.gov (United States)

    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

  15. Combining Host-based and network-based intrusion detection system

    African Journals Online (AJOL)

    These attacks were simulated using hping. The proposed system is implemented in Java. The results show that the proposed system is able to detect attacks both from within (host-based) and outside sources (network-based). Key Words: Intrusion Detection System (IDS), Host-based, Network-based, Signature, Security log.

  16. Radioactive elements behaviour in multiphase intrusive series and petrological significance of radiogeochemical data

    International Nuclear Information System (INIS)

    Ponomareva, A.P.; Zlobin, V.A.

    1982-01-01

    The behaviour of radioactive elements (RE) during formation of multiphase intrusive series of various ages, types and alkalinity nature, placed in different structural formation zones of West Uzbekistan is discussed (on the basis of 230 quantitative determinations). It is established that maximum RE concentrations in the intrusive series considered are U=3-5, Th=11-17 g/t and correspond to granodiorites, adamellites, granites and granosienites. The typical behaviour for U and Th is the growth of their concentrations in the direction from gabbro- to granodiorites (granosienites) and granites, and then decrease to leucocrat granites (alkaline, biotite or bimica ones). The evolution of magmatic systems occurred not along the line of differentiation of melts, but along the line of their ''washing'' with fluid mainly at the level of magma generation and on their way to upper horizons of Earth crust. High concentrations (several times more than a clark) must occur in cases of additional RE introduction

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Sungwon Lee

    2009-05-01

    Full Text Available TheIP-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.

  19. PERFORMANCE COMPARISON FOR INTRUSION DETECTION SYSTEM USING NEURAL NETWORK WITH KDD DATASET

    Directory of Open Access Journals (Sweden)

    S. Devaraju

    2014-04-01

    Full Text Available Intrusion Detection Systems are challenging task for finding the user as normal user or attack user in any organizational information systems or IT Industry. The Intrusion Detection System is an effective method to deal with the kinds of problem in networks. Different classifiers are used to detect the different kinds of attacks in networks. In this paper, the performance of intrusion detection is compared with various neural network classifiers. In the proposed research the four types of classifiers used are Feed Forward Neural Network (FFNN, Generalized Regression Neural Network (GRNN, Probabilistic Neural Network (PNN and Radial Basis Neural Network (RBNN. The performance of the full featured KDD Cup 1999 dataset is compared with that of the reduced featured KDD Cup 1999 dataset. The MATLAB software is used to train and test the dataset and the efficiency and False Alarm Rate is measured. It is proved that the reduced dataset is performing better than the full featured dataset.

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

    Science.gov (United States)

    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.

  1. Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure.

    Science.gov (United States)

    Luo, Biao; Liu, Derong; Wu, Huai-Ning

    2018-06-01

    Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.

  2. Technologies, Methodologies and Challenges in Network Intrusion Detection and Prevention Systems

    Directory of Open Access Journals (Sweden)

    Nicoleta STANCIU

    2013-01-01

    Full Text Available This paper presents an overview of the technologies and the methodologies used in Network Intrusion Detection and Prevention Systems (NIDPS. Intrusion Detection and Prevention System (IDPS technologies are differentiated by types of events that IDPSs can recognize, by types of devices that IDPSs monitor and by activity. NIDPSs monitor and analyze the streams of network packets in order to detect security incidents. The main methodology used by NIDPSs is protocol analysis. Protocol analysis requires good knowledge of the theory of the main protocols, their definition, how each protocol works.

  3. Identifying seawater intrusion in coastal areas by means of 1D and quasi-2D joint inversion of TDEM and VES data

    Science.gov (United States)

    Martínez-Moreno, F. J.; Monteiro-Santos, F. A.; Bernardo, I.; Farzamian, M.; Nascimento, C.; Fernandes, J.; Casal, B.; Ribeiro, J. A.

    2017-09-01

    Seawater intrusion is an increasingly widespread problem in coastal aquifers caused by climate changes -sea-level rise, extreme phenomena like flooding and droughts- and groundwater depletion near to the coastline. To evaluate and mitigate the environmental risks of this phenomenon it is necessary to characterize the coastal aquifer and the salt intrusion. Geophysical methods are the most appropriate tool to address these researches. Among all geophysical techniques, electrical methods are able to detect seawater intrusions due to the high resistivity contrast between saltwater, freshwater and geological layers. The combination of two or more geophysical methods is recommended and they are more efficient when both data are inverted jointly because the final model encompasses the physical properties measured for each methods. In this investigation, joint inversion of vertical electric and time domain soundings has been performed to examine seawater intrusion in an area within the Ferragudo-Albufeira aquifer system (Algarve, South of Portugal). For this purpose two profiles combining electrical resistivity tomography (ERT) and time domain electromagnetic (TDEM) methods were measured and the results were compared with the information obtained from exploration drilling. Three different inversions have been carried out: single inversion of the ERT and TDEM data, 1D joint inversion and quasi-2D joint inversion. Single inversion results identify seawater intrusion, although the sedimentary layers detected in exploration drilling were not well differentiated. The models obtained with 1D joint inversion improve the previous inversion due to better detection of sedimentary layer and the seawater intrusion appear to be better defined. Finally, the quasi-2D joint inversion reveals a more realistic shape of the seawater intrusion and it is able to distinguish more sedimentary layers recognised in the exploration drilling. This study demonstrates that the quasi-2D joint

  4. Adaptive security systems -- Combining expert systems with adaptive technologies

    International Nuclear Information System (INIS)

    Argo, P.; Loveland, R.; Anderson, K.

    1997-01-01

    The Adaptive Multisensor Integrated Security System (AMISS) uses a variety of computational intelligence techniques to reason from raw sensor data through an array of processing layers to arrive at an assessment for alarm/alert conditions based on human behavior within a secure facility. In this paper, the authors give an overview of the system and briefly describe some of the major components of the system. This system is currently under development and testing in a realistic facility setting

  5. ATLANTIDES: An Architecture for Alert Verification in Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Crispo, Bruno; Etalle, Sandro

    2007-01-01

    We present an architecture designed for alert verification (i.e., to reduce false positives) in network intrusion-detection systems. Our technique is based on a systematic (and automatic) anomaly-based analysis of the system output, which provides useful context information regarding the network

  6. Predicting Seawater Intrusion in Coastal Groundwater Boreholes Using Self-Potential Data

    Science.gov (United States)

    Graham, M.; MacAllister, D. J.; Jackson, M.; Vinogradov, J.; Butler, A. P.

    2017-12-01

    Many coastal groundwater abstraction wells are under threat from seawater intrusion: this is exacerbated in summer by low water tables and increased abstraction. Existing hydrochemistry or geophysical techniques often fail to predict the timing of intrusion events. We investigate whether the presence and transport of seawater can influence self-potentials (SPs) measured within groundwater boreholes, with the aim of using SP monitoring to provide early warning of saline intrusion. SP data collection: SP data were collected from a coastal groundwater borehole and an inland borehole (> 60 km from the coast) in the Seaford Chalk of southern England. The SP gradient in the inland borehole was approximately 0.05 mV/m, while that in the coastal borehole varied from 0.16-0.26 mV/m throughout the monitoring period. Spectral analysis showed that semi-diurnal fluctuations in the SP gradient were several orders of magnitude higher at the coast than inland, indicating a strong influence from oceanic tides. A characteristic decrease in the gradient, or precursor, was observed in the coastal borehole several days prior to seawater intrusion. Modelling results: Hydrodynamic transport and geoelectric modelling suggest that observed pressure changes (associated with the streaming potential) are insufficient to explain either the magnitude of the coastal SP gradient or the semi-diurnal SP fluctuations. By contrast, a model of the exclusion-diffusion potential closely matches these observations and produces a precursor similar to that observed in the field. Sensitivity analysis suggests that both a sharp saline front and spatial variations in the exclusion efficiency arising from aquifer heterogeneities are necessary to explain the SP gradient observed in the coastal borehole. The presence of the precursor in the model depends also on the presence and depth of fractures near the base of the borehole. Conclusions: Our results indicate that SP monitoring, combined with hydrodynamic

  7. An Embedded, Eight Channel, Noise Canceling, Wireless, Wearable sEMG Data Acquisition System With Adaptive Muscle Contraction Detection.

    Science.gov (United States)

    Ergeneci, Mert; Gokcesu, Kaan; Ertan, Erhan; Kosmas, Panagiotis

    2018-02-01

    Wearable technology has gained increasing popularity in the applications of healthcare, sports science, and biomedical engineering in recent years. Because of its convenient nature, the wearable technology is particularly useful in the acquisition of the physiological signals. Specifically, the (surface electromyography) sEMG systems, which measure the muscle activation potentials, greatly benefit from this technology in both clinical and industrial applications. However, the current wearable sEMG systems have several drawbacks including inefficient noise cancellation, insufficient measurement quality, and difficult integration to customized applications. Additionally, none of these sEMG data acquisition systems can detect sEMG signals (i.e., contractions), which provides a valuable environment for further studies such as human machine interaction, gesture recognition, and fatigue tracking. To this end, we introduce an embedded, eight channel, noise canceling, wireless, wearable sEMG data acquisition system with adaptive muscle contraction detection. Our design consists of two stages, which are the sEMG sensors and the multichannel data acquisition unit. For the first stage, we propose a low cost, dry, and active sEMG sensor that captures the muscle activation potentials, a data acquisition unit that evaluates these captured multichannel sEMG signals and transmits them to a user interface. In the data acquisition unit, the sEMG signals are processed through embedded, adaptive methods in order to reject the power line noise and detect the muscle contractions. Through extensive experiments, we demonstrate that our sEMG sensor outperforms a widely used commercially available product and our data acquisition system achieves 4.583 dB SNR gain with accuracy in the detection of the contractions.

  8. Ensemble Kalman Filter Assimilation of ERT Data for Numerical Modeling of Seawater Intrusion in a Laboratory Experiment

    Directory of Open Access Journals (Sweden)

    Véronique Bouzaglou

    2018-03-01

    Full Text Available Seawater intrusion in coastal aquifers is a worldwide problem exacerbated by aquifer overexploitation and climate changes. To limit the deterioration of water quality caused by saline intrusion, research studies are needed to identify and assess the performance of possible countermeasures, e.g., underground barriers. Within this context, numerical models are fundamental to fully understand the process and for evaluating the effectiveness of the proposed solutions to contain the saltwater wedge; on the other hand, they are typically affected by uncertainty on hydrogeological parameters, as well as initial and boundary conditions. Data assimilation methods such as the ensemble Kalman filter (EnKF represent promising tools that can reduce such uncertainties. Here, we present an application of the EnKF to the numerical modeling of a laboratory experiment where seawater intrusion was reproduced in a specifically designed sandbox and continuously monitored with electrical resistivity tomography (ERT. Combining EnKF and the SUTRA model for the simulation of density-dependent flow and transport in porous media, we assimilated the collected ERT data by means of joint and sequential assimilation approaches. In the joint approach, raw ERT data (electrical resistances are assimilated to update both salt concentration and soil parameters, without the need for an electrical inversion. In the sequential approach, we assimilated electrical conductivities computed from a previously performed electrical inversion. Within both approaches, we suggest dual-step update strategies to minimize the effects of spurious correlations in parameter estimation. The results show that, in both cases, ERT data assimilation can reduce the uncertainty not only on the system state in terms of salt concentration, but also on the most relevant soil parameters, i.e., saturated hydraulic conductivity and longitudinal dispersivity. However, the sequential approach is more prone to

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

    Science.gov (United States)

    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.

  10. Adapting the SpaceCube v2.0 Data Processing System for Mission-Unique Application Requirements

    Science.gov (United States)

    Petrick, David; Gill, Nat; Hasouneh, Munther; Stone, Robert; Winternitz, Luke; Thomas, Luke; Davis, Milton; Sparacino, Pietro; Flatley, Thomas

    2015-01-01

    The SpaceCube (sup TM) v2.0 system is a superior high performance, reconfigurable, hybrid data processing system that can be used in a multitude of applications including those that require a radiation hardened and reliable solution. This paper provides an overview of the design architecture, flexibility, and the advantages of the modular SpaceCube v2.0 high performance data processing system for space applications. The current state of the proven SpaceCube technology is based on nine years of engineering and operations. Five systems have been successfully operated in space starting in 2008 with four more to be delivered for launch vehicle integration in 2015. The SpaceCube v2.0 system is also baselined as the avionics solution for five additional flight projects and is always a top consideration as the core avionics for new instruments or spacecraft control. This paper will highlight how this multipurpose system is currently being used to solve design challenges of three independent applications. The SpaceCube hardware adapts to new system requirements by allowing for application-unique interface cards that are utilized by reconfiguring the underlying programmable elements on the core processor card. We will show how this system is being used to improve on a heritage NASA GPS technology, enable a cutting-edge LiDAR instrument, and serve as a typical command and data handling (C&DH) computer for a space robotics technology demonstration.

  11. Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

    International Nuclear Information System (INIS)

    Gonzalez, J.; Ruiz, M.; Barrera, E.; Lopez, J.M.; Arcas, G. de; Vega, J.

    2010-01-01

    The data acquisition systems used in long-pulse fusion experiments need to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations, it is essential to employ software tools that allow for hot swap capabilities throughout the temporal evolution of the experiments. This is very important because processing needs are not equal during different phases of the experiment. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of a technology for implementing scalable data acquisition and processing systems based on PXI and CompactPCI hardware. In the ITMS platform, a set of software tools allows the user to define the processing algorithms associated with the different experimental phases using state machines driven by software events. These state machines are specified using the State Chart XML (SCXML) language. The software tools are developed using JAVA, JINI, an SCXML engine and several LabVIEW applications. Within this schema, it is possible to execute data acquisition and processing applications in an adaptive way. The power of SCXML semantics and the ability to work with XML user-defined data types allow for very easy programming of the ITMS platform. With this approach, the ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems based on a service-oriented model with the ability to easily implement remote participation applications.

  12. Services oriented architecture for adaptive and intelligent data acquisition and processing systems in long pulse fusion experiments

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez, J.; Ruiz, M.; Barrera, E.; Lopez, J.M.; De Arcas, G. [Universidad Politecnica de Madrid (Spain); Vega, J. [Association EuratomCIEMAT para Fusion, Madrid (Spain)

    2009-07-01

    Data acquisition systems used in long pulse fusion experiments require to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations is essential to dispose software tools that allow hot swap capabilities throughout the temporal evolution of the experiments. This is very important because the processing needs are not equal in the different experiment's phases. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of technology for implementing scalable data acquisition and processing systems based in PXI and compact PCI hardware. In the ITMS platform a set of software tools allows the user to define the processing associated with the different experiment's phases using state machines driven by software events. These state machines are specified using State Chart XML (SCXML) language. The software tools are developed using: JAVA, JINI, a SCXML engine and several LabVIEW applications. With this schema it is possible to execute data acquisition and processing applications in an adaptive way. The powerful of SCXML semantics and the possibility of to work with XML user defined data types allow a very easy programming of ITMS platform. With this approach ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems, based in a services oriented model, with ease possibility for implement remote participation applications. (authors)

  13. Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez, J. [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Ruiz, M., E-mail: mariano.ruiz@upm.e [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Barrera, E.; Lopez, J.M.; Arcas, G. de [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain)

    2010-07-15

    The data acquisition systems used in long-pulse fusion experiments need to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations, it is essential to employ software tools that allow for hot swap capabilities throughout the temporal evolution of the experiments. This is very important because processing needs are not equal during different phases of the experiment. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of a technology for implementing scalable data acquisition and processing systems based on PXI and CompactPCI hardware. In the ITMS platform, a set of software tools allows the user to define the processing algorithms associated with the different experimental phases using state machines driven by software events. These state machines are specified using the State Chart XML (SCXML) language. The software tools are developed using JAVA, JINI, an SCXML engine and several LabVIEW applications. Within this schema, it is possible to execute data acquisition and processing applications in an adaptive way. The power of SCXML semantics and the ability to work with XML user-defined data types allow for very easy programming of the ITMS platform. With this approach, the ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems based on a service-oriented model with the ability to easily implement remote participation applications.

  14. Panacea: Automating Attack Classification for Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro; Hartel, Pieter H.; Kirda, E.; Jha, S.; Balzarotti, D.

    Anomaly-based intrusion detection systems are usually criticized because they lack a classication of attack, thus security teams have to manually inspect any raised alert to classify it. We present a new approach, Panacea, to automatically and systematically classify attacks detected by an

  15. Reading between the fields: practical, effective intrusion detection for industrial control systems

    NARCIS (Netherlands)

    Yüksel, Ömer; den Hartog, Jeremy; Etalle, Sandro

    2016-01-01

    Detection of previously unknown attacks and malicious messages is a challenging problem faced by modern network intrusion detection systems. Anomaly-based solutions, despite being able to detect unknown attacks, have not been used often in practice due to their high false positive rate, and because

  16. Panacea : Automating attack classification for anomaly-based network intrusion detection systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, S.; Hartel, P.H.; Kirda, E.; Jha, S.; Balzarotti, D.

    2009-01-01

    Anomaly-based intrusion detection systems are usually criticized because they lack a classification of attacks, thus security teams have to manually inspect any raised alert to classify it. We present a new approach, Panacea, to automatically and systematically classify attacks detected by an

  17. Panacea : Automating attack classification for anomaly-based network intrusion detection systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, S.; Hartel, P.H.

    2009-01-01

    Anomaly-based intrusion detection systems are usually criticized because they lack a classification of attack, thus security teams have to manually inspect any raised alert to classify it. We present a new approach, Panacea, to automatically and systematically classify attacks detected by an

  18. Panacea: Automating Attack Classification for Anomaly-based Network Intrusion Detection Systems

    NARCIS (Netherlands)

    Bolzoni, D.; Etalle, Sandro; Hartel, Pieter H.

    2009-01-01

    Anomaly-based intrusion detection systems are usually criticized because they lack a classication of attack, thus security teams have to manually inspect any raised alert to classify it. We present a new approach, Panacea, to automatically and systematically classify attacks detected by an

  19. The potential for health risks from intrusion of contaminants into the distribution system from pressure transients.

    Science.gov (United States)

    LeChevallier, Mark W; Gullick, Richard W; Karim, Mohammad R; Friedman, Melinda; Funk, James E

    2003-03-01

    The potential for public health risks associated with intrusion of contaminants into water supply distribution systems resulting from transient low or negative pressures is assessed. It is shown that transient pressure events occur in distribution systems; that during these negative pressure events pipeline leaks provide a potential portal for entry of groundwater into treated drinking water; and that faecal indicators and culturable human viruses are present in the soil and water exterior to the distribution system. To date, all observed negative pressure events have been related to power outages or other pump shutdowns. Although there are insufficient data to indicate whether pressure transients are a substantial source of risk to water quality in the distribution system, mitigation techniques can be implemented, principally the maintenance of an effective disinfectant residual throughout the distribution system, leak control, redesign of air relief venting, and more rigorous application of existing engineering standards. Use of high-speed pressure data loggers and surge modelling may have some merit, but more research is needed.

  20. Conjunctive Management of Multi-Aquifer System for Saltwater Intrusion Mitigation

    Science.gov (United States)

    Tsai, F. T. C.; Pham, H. V.

    2015-12-01

    Due to excessive groundwater withdrawals, many water wells in Baton Rouge, Louisiana experience undesirable chloride concentration because of saltwater intrusion. The study goal is to develop a conjunctive management framework that takes advantage of the Baton Rouge multi-aquifer system to mitigate saltwater intrusion. The conjunctive management framework utilizes several hydraulic control techniques to mitigate saltwater encroachment. These hydraulic control approaches include pumping well relocation, freshwater injection, saltwater scavenging, and their combinations. Specific objectives of the study are: (1) constructing scientific geologic architectures of the "800-foot" sand, the "1,000-foot" sand, the "1,200-foot" sand, the "1,500-foot" sand, the "1,700-foot" sand, and the "2,000-foot" sand, (2) developing scientific saltwater intrusion models for these sands. (3) using connector wells to draw native groundwater from one sand and inject to another sand to create hydraulic barriers to halt saltwater intrusion, (4) using scavenger wells or well couples to impede saltwater intrusion progress and reduce chloride concentration in pumping wells, and (5) reducing cones of depression by relocating and dispersing pumping wells to different sands. The study utilizes optimization techniques and newest LSU high performance computing (HPC) facilities to derive solutions. The conjunctive management framework serves as a scientific tool to assist policy makers to solve the urgent saltwater encroachment issue in the Baton Rouge area. The research results will help water companies as well as industries in East Baton Rouge Parish and neighboring parishes by reducing their saltwater intrusion threats, which in turn would sustain Capital Area economic development.

  1. Link Adaptation for Framed Multimedia Data Transmission over a DS-CDMA Communication System

    Directory of Open Access Journals (Sweden)

    David Declercq

    2005-02-01

    Full Text Available In the context of frame-based multimedia wireless transmission, a link adaptation strategy is proposed, assuming that the source decoder may accept some remaining errors at the output of the channel decoder. Based on a target mean bit error rate for erroneous frames, a minimum bit-energy-to-equivalent-noise ratio is chosen. Under this constraint, a new link adaptation criterion is proposed: the maximization of the minimum user's information rate through dynamic spreading gain and power control, allowing to guarantee a transmission for each and every user. An analytical solution to this constrained optimization problem is proposed and its performance is studied in a Rayleigh-fading environment.

  2. Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data.

    Science.gov (United States)

    Dexter, Franklin; Wachtel, Ruth E; Epstein, Richard H

    2011-01-07

    No systematic process has previously been described for a needs assessment that identifies the operating room (OR) management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach. A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e.g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1). Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS) data for most scenarios (43 of 45). Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered. Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of individualized assessments. Our technical advance is the

  3. Event-based knowledge elicitation of operating room management decision-making using scenarios adapted from information systems data

    Directory of Open Access Journals (Sweden)

    Epstein Richard H

    2011-01-01

    Full Text Available Abstract Background No systematic process has previously been described for a needs assessment that identifies the operating room (OR management decisions made by the anesthesiologists and nurse managers at a facility that do not maximize the efficiency of use of OR time. We evaluated whether event-based knowledge elicitation can be used practically for rapid assessment of OR management decision-making at facilities, whether scenarios can be adapted automatically from information systems data, and the usefulness of the approach. Methods A process of event-based knowledge elicitation was developed to assess OR management decision-making that may reduce the efficiency of use of OR time. Hypothetical scenarios addressing every OR management decision influencing OR efficiency were created from published examples. Scenarios are adapted, so that cues about conditions are accurate and appropriate for each facility (e.g., if OR 1 is used as an example in a scenario, the listed procedure is a type of procedure performed at the facility in OR 1. Adaptation is performed automatically using the facility's OR information system or anesthesia information management system (AIMS data for most scenarios (43 of 45. Performing the needs assessment takes approximately 1 hour of local managers' time while they decide if their decisions are consistent with the described scenarios. A table of contents of the indexed scenarios is created automatically, providing a simple version of problem solving using case-based reasoning. For example, a new OR manager wanting to know the best way to decide whether to move a case can look in the chapter on "Moving Cases on the Day of Surgery" to find a scenario that describes the situation being encountered. Results Scenarios have been adapted and used at 22 hospitals. Few changes in decisions were needed to increase the efficiency of use of OR time. The few changes were heterogeneous among hospitals, showing the usefulness of

  4. On Cyber Attacks and Signature Based Intrusion Detection for MODBUS Based Industrial Control Systems

    Directory of Open Access Journals (Sweden)

    Wei Gao

    2014-03-01

    Full Text Available Industrial control system communication networks are vulnerable to reconnaissance, response injection, command injection, and denial of service attacks.  Such attacks can lead to an inability to monitor and control industrial control systems and can ultimately lead to system failure. This can result in financial loss for control system operators and economic and safety issues for the citizens who use these services.  This paper describes a set of 28 cyber attacks against industrial control systems which use the MODBUS application layer network protocol. The paper also describes a set of standalone and state based intrusion detection system rules which can be used to detect cyber attacks and to store evidence of attacks for post incident analysis. All attacks described in this paper were validated in a laboratory environment. The detection rate of the intrusion detection system rules presented by attack class is also presented.

  5. Proposed Network Intrusion Detection System ‎Based on Fuzzy c Mean Algorithm in Cloud ‎Computing Environment

    Directory of Open Access Journals (Sweden)

    Shawq Malik Mehibs

    2017-12-01

    Full Text Available Nowadays cloud computing had become is an integral part of IT industry, cloud computing provides Working environment allow a user of environmental to share data and resources over the internet. Where cloud computing its virtual grouping of resources offered over the internet, this lead to different matters related to the security and privacy in cloud computing. And therefore, create intrusion detection very important to detect outsider and insider intruders of cloud computing with high detection rate and low false positive alarm in the cloud environment. This work proposed network intrusion detection module using fuzzy c mean algorithm. The kdd99 dataset used for experiments .the proposed system characterized by a high detection rate with low false positive alarm

  6. Sequence-aware intrusion detection in industrial control systems

    NARCIS (Netherlands)

    Caselli, M.; Zambon, Emmanuele; Kargl, Frank; Zhou, Jianying; Jones, D.

    Nowadays, several threats endanger cyber-physical systems. Among these systems, industrial control systems (ICS) operating on critical infrastructures have been proven to be an attractive target for attackers. The case of Stuxnet has not only showed that ICSs are vulnerable to cyber-attacks, but

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

    International Nuclear Information System (INIS)

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

    2014-01-01

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

  8. Design and Implementation of a Smart LED Lighting System Using a Self Adaptive Weighted Data Fusion Algorithm

    Science.gov (United States)

    Sung, Wen-Tsai; Lin, Jia-Syun

    2013-01-01

    This work aims to develop a smart LED lighting system, which is remotely controlled by Android apps via handheld devices, e.g., smartphones, tablets, and so forth. The status of energy use is reflected by readings displayed on a handheld device, and it is treated as a criterion in the lighting mode design of a system. A multimeter, a wireless light dimmer, an IR learning remote module, etc. are connected to a server by means of RS 232/485 and a human computer interface on a touch screen. The wireless data communication is designed to operate in compliance with the ZigBee standard, and signal processing on sensed data is made through a self adaptive weighted data fusion algorithm. A low variation in data fusion together with a high stability is experimentally demonstrated in this work. The wireless light dimmer as well as the IR learning remote module can be instructed directly by command given on the human computer interface, and the reading on a multimeter can be displayed thereon via the server. This proposed smart LED lighting system can be remotely controlled and self learning mode can be enabled by a single handheld device via WiFi transmission. Hence, this proposal is validated as an approach to power monitoring for home appliances, and is demonstrated as a digital home network in consideration of energy efficiency.

  9. Design and Implementation of a Smart LED Lighting System Using a Self Adaptive Weighted Data Fusion Algorithm

    Directory of Open Access Journals (Sweden)

    Wen-Tsai Sung

    2013-12-01

    Full Text Available This work aims to develop a smart LED lighting system, which is remotely controlled by Android apps via handheld devices, e.g., smartphones, tablets, and so forth. The status of energy use is reflected by readings displayed on a handheld device, and it is treated as a criterion in the lighting mode design of a system. A multimeter, a wireless light dimmer, an IR learning remote module, etc. are connected to a server by means of RS 232/485 and a human computer interface on a touch screen. The wireless data communication is designed to operate in compliance with the ZigBee standard, and signal processing on sensed data is made through a self adaptive weighted data fusion algorithm. A low variation in data fusion together with a high stability is experimentally demonstrated in this work. The wireless light dimmer as well as the IR learning remote module can be instructed directly by command given on the human computer interface, and the reading on a multimeter can be displayed thereon via the server. This proposed smart LED lighting system can be remotely controlled and self learning mode can be enabled by a single handheld device via WiFi transmission. Hence, this proposal is validated as an approach to power monitoring for home appliances, and is demonstrated as a digital home network in consideration of energy efficiency.

  10. Rb-Sr ages and palaeomagnetic data for some Angolan alkaline intrusives

    International Nuclear Information System (INIS)

    Allsopp, H.L.; Hargraves, R.B.

    1985-01-01

    New Rb-Sr age measurements are reported for a number of intrusives from Angola. Data for the Njoio and Tchivira nepheline syenite bodies yield mineral isochrons indicating ages of 104,3+-0,8 Ma and 130,8+-1,4 Ma respectively. Palaeomagnetic studies on the same occurrences gave marginal and scattered results respectively. Micas from the Camafuca crater-facies kimberlite yielded and apparent age of 1 822+-151 Ma, a result that is far in excess of the Tertiary (or younger) age inferred for this pipe. Similarly conflicting data were obtained for the Nova Lisboa kimberlite. It is likely that older crustal micas incorporated in the kimberlite breccias are responsible for the anomalous ages reported on the kimberlites. Satisfactory palaeomagnetic data are reported for the Zenza and Bailundu occurrences, not dated by the Rb-Sr method. A convenient K-Ar age of 80+-0,8 Ma was obtainable for Zenza

  11. On the applicability of fair and adaptive data dissemination in traffic information systems

    NARCIS (Netherlands)

    de Souza Schwartz, Ramon; Ohazulike, Anthony; Sommer, Christoph; Scholten, Johan; Dressler, Falko; Havinga, Paul J.M.

    Vehicular Ad hoc Networks (VANETs) are expected to serve as support to the development of not only safety applications but also information-rich applications that disseminate relevant data to vehicles. Due to the continuous collection, processing, and dissemination of data, one crucial requirement

  12. Provide a model to improve the performance of intrusion detection systems in the cloud

    OpenAIRE

    Foroogh Sedighi

    2016-01-01

    High availability of tools and service providers in cloud computing and the fact that cloud computing services are provided by internet and deal with public, have caused important challenges for new computing model. Cloud computing faces problems and challenges such as user privacy, data security, data ownership, availability of services, and recovery after breaking down, performance, scalability, programmability. So far, many different methods are presented for detection of intrusion in clou...

  13. PERFORMANCE COMPARISON OF INTRUSION DETECTION SYSTEM USING VARIOUS TECHNIQUES – A REVIEW

    Directory of Open Access Journals (Sweden)

    S. Devaraju

    2013-09-01

    Full Text Available Nowadays, the security has become a critical part of any organization or industry information systems. The Intrusion Detection System is an effective method to deal with the new kind of threats such as DoS, Porbe, R2L and U2R. In this paper, we analyze the various approaches such as Hidden Semi Markov Model, Conditional Random Fields and Layered Approach, Bayesian classification, Data Mining techniques, Clustering Algorithms such as K-Means and Fuzzy c-Means, Back Propagation Neural Network, SOM Neural Network, Rough Set Neural Network Algorithm, Genetic Algorithm, Pattern Matching, Principle Component Analysis, Linear Discriminant Analysis, Independent Component Analysis, Multivariate Statistical Analysis, SOM/PSO algorithm etc. The performance is measured for two different datasets using various approaches. The datasets are trained and tested for identifying the new attacks that will affect the hosts or networks. The well known KDD Cup 1999 or DARPA 1999 dataset has been used to improve the accuracy and performance. The four groups of attacks are identified as Probe, DoS, U2R and R2L. The dataset used for training set is 494,021 and testing set is 311,028. The aim is to improve the detection rate and performance of the proposed system.

  14. PENERAPAN NAIVE BAYES PADA INTRUSION DETECTION SYSTEM DENGAN DISKRITISASI VARIABEL

    Directory of Open Access Journals (Sweden)

    I Nyoman Trisna Wirawan

    2015-07-01

    Pada penelitian ini akan dibahas mengenai penerapan naive bayes classifier dengan menggunakan pemilihan atribut berdasarkan pada korelasi serta preprocessing data dengan diskritisasi dengan menggunakan metode mean/standar deviasi untuk atribut kontinu dengan menggunakan 3-interval dan 5-interval. Hasil percobaan menunjukan bahwa penerapan naive bayes pada klasifikasi data yang telah melewati proses diskritisasi mampu memberikan akurasi hingga 89% dengan running time rata-rata adalah 31 detik.

  15. New device to measure dynamic intrusion/extrusion cycles of lyophobic heterogeneous systems.

    Science.gov (United States)

    Guillemot, Ludivine; Galarneau, Anne; Vigier, Gérard; Abensur, Thierry; Charlaix, Élisabeth

    2012-10-01

    Lyophobic heterogeneous systems (LHS) are made of mesoporous materials immersed in a non-wetting liquid. One application of LHS is the nonlinear damping of high frequency vibrations. The behaviour of LHS is characterized by P - ΔV cycles, where P is the pressure applied to the system, and ΔV its volume change due to the intrusion of the liquid into the pores of the material, or its extrusion out of the pores. Very few dynamic studies of LHS have been performed until now. We describe here a new apparatus that allows us to carry out dynamic intrusion/extrusion cycles with various liquid/porous material systems, controlling the temperature from ambient to 120 °C and the frequency from 0.01 to 20 Hz. We show that for two LHS: water/MTS and Galinstan/CPG, the energy dissipated during one cycle depends very weakly on the cycle frequency, in strong contrast to conventional dampers.

  16. An intrusion prevention system as a proactive security mechanism in network infrastructure

    Directory of Open Access Journals (Sweden)

    Dulanović Nenad

    2008-01-01

    Full Text Available A properly configured firewall is a good starting point in securing a computer network. However, complex network environments that involve higher number of participants and endpoints require better security infrastructure. Intrusion Detection Systems (IDS, proposed as a solution to perimeter defense, have many open problems and it is clear that better solutions must be found. Due to many unsolved problems associated with IDS, Intrusion Prevention Systems (IPS are introduced. The main idea in IPS is to be proactive. This paper gives an insight of Cobrador Bouncer IPS implementation. System architecture is given and three different Bouncer IPS deployment modes are presented. The Bouncer IPS as a proactive honeypot is also discussed.

  17. An adapter-aware, non-intrusive dependency injection framework for Java

    NARCIS (Netherlands)

    Roemers, Arnout; Hatun, Kardelen; Bockisch, Christoph

    In strongly typed Object-Oriented Programming languages, it is common to encounter type incompatibilities between separately developed software components one desires to compose. Using the Adapter pattern to overcome these type incompatibilities is only an option if changing the source code of the

  18. Complex adaptive systems ecology

    DEFF Research Database (Denmark)

    Sommerlund, Julie

    2003-01-01

    In the following, I will analyze two articles called Complex Adaptive Systems EcologyI & II (Molin & Molin, 1997 & 2000). The CASE-articles are some of the more quirkyarticles that have come out of the Molecular Microbial Ecology Group - a groupwhere I am currently making observational studies....... They are the result of acooperation between Søren Molin, professor in the group, and his brother, JanMolin, professor at Department of Organization and Industrial Sociology atCopenhagen Business School. The cooperation arises from the recognition that bothmicrobial ecology and sociology/organization theory works...

  19. Model-Data Fusion and Adaptive Sensing for Large Scale Systems: Applications to Atmospheric Release Incidents

    Science.gov (United States)

    Madankan, Reza

    All across the world, toxic material clouds are emitted from sources, such as industrial plants, vehicular traffic, and volcanic eruptions can contain chemical, biological or radiological material. With the growing fear of natural, accidental or deliberate release of toxic agents, there is tremendous interest in precise source characterization and generating accurate hazard maps of toxic material dispersion for appropriate disaster management. In this dissertation, an end-to-end framework has been developed for probabilistic source characterization and forecasting of atmospheric release incidents. The proposed methodology consists of three major components which are combined together to perform the task of source characterization and forecasting. These components include Uncertainty Quantification, Optimal Information Collection, and Data Assimilation. Precise approximation of prior statistics is crucial to ensure performance of the source characterization process. In this work, an efficient quadrature based method has been utilized for quantification of uncertainty in plume dispersion models that are subject to uncertain source parameters. In addition, a fast and accurate approach is utilized for the approximation of probabilistic hazard maps, based on combination of polynomial chaos theory and the method of quadrature points. Besides precise quantification of uncertainty, having useful measurement data is also highly important to warranty accurate source parameter estimation. The performance of source characterization is highly affected by applied sensor orientation for data observation. Hence, a general framework has been developed for the optimal allocation of data observation sensors, to improve performance of the source characterization process. The key goal of this framework is to optimally locate a set of mobile sensors such that measurement of textit{better} data is guaranteed. This is achieved by maximizing the mutual information between model predictions

  20. An Analysis of Security System for Intrusion in Smartphone Environment

    Directory of Open Access Journals (Sweden)

    Maya Louk

    2014-01-01

    Full Text Available There are many malware applications in Smartphone. Smartphone’s users may become unaware if their data has been recorded and stolen by intruders via malware. Smartphone—whether for business or personal use—may not be protected from malwares. Thus, monitoring, detecting, tracking, and notification (MDTN have become the main purpose of the writing of this paper. MDTN is meant to enable Smartphone to prevent and reduce the number of cybercrimes. The methods are shown to be effective in protecting Smartphone and isolating malware and sending warning in the form of notification to the user about the danger in progress. In particular, (a MDTN process is possible and will be enabled for Smartphone environment. (b The methods are shown to be an advanced security for private sensitive data of the Smartphone user.

  1. An analysis of security system for intrusion in Smartphone environment.

    Science.gov (United States)

    Louk, Maya; Lim, Hyotaek; Lee, HoonJae

    2014-01-01

    There are many malware applications in Smartphone. Smartphone's users may become unaware if their data has been recorded and stolen by intruders via malware. Smartphone--whether for business or personal use--may not be protected from malwares. Thus, monitoring, detecting, tracking, and notification (MDTN) have become the main purpose of the writing of this paper. MDTN is meant to enable Smartphone to prevent and reduce the number of cybercrimes. The methods are shown to be effective in protecting Smartphone and isolating malware and sending warning in the form of notification to the user about the danger in progress. In particular, (a) MDTN process is possible and will be enabled for Smartphone environment. (b) The methods are shown to be an advanced security for private sensitive data of the Smartphone user.

  2. An Analysis of Security System for Intrusion in Smartphone Environment

    OpenAIRE

    Louk, Maya; Lim, Hyotaek; Lee, HoonJae

    2014-01-01

    There are many malware applications in Smartphone. Smartphone's users may become unaware if their data has been recorded and stolen by intruders via malware. Smartphone—whether for business or personal use—may not be protected from malwares. Thus, monitoring, detecting, tracking, and notification (MDTN) have become the main purpose of the writing of this paper. MDTN is meant to enable Smartphone to prevent and reduce the number of cybercrimes. The methods are shown to be effective in protecti...

  3. Cloud Detours: A Non-intrusive Approach for Automatic Software Adaptation to the Cloud

    OpenAIRE

    Maia , Paulo; Vasconcelos , Michel; Mendonça , Nabor ,

    2015-01-01

    Part 1: Research Track; International audience; A major challenge facing cloud migration is the need to change a legacy (on-premise) application’s source code so that it can better benefit from the inherit cloud computing characteristics, such as resource elasticity and high scalability. When performed manually, those changes are error-prone and may require a great effort from application developers. This paper presents a novel approach to support organizations in automatically adapting their...

  4. A methodical and adaptive framework for Data Warehouse of Salary Management System

    OpenAIRE

    Manzoor Ahmad

    2015-01-01

    Years of experience as an employee of University of Kashmir has always desired us to have a typical solution where most of the activities related to salary are fully automated without checking across the files whenever there is a need e.g. individual month‟s salary report , web based information submission, filing of returns , increment information etc. After thorough analysis , taking employee satisfaction , sensitivity and security of data , a long term solution was to develop a centralized...

  5. Adaptive Data Processing Technique for Lidar-Assisted Control to Bridge the Gap between Lidar Systems and Wind Turbines: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Schlipf, David; Raach, Steffen; Haizmann, Florian; Cheng, Po Wen; Fleming, Paul; Scholbrock, Andrew, Krishnamurthy, Raghu; Boquet, Mathieu

    2015-12-14

    This paper presents first steps toward an adaptive lidar data processing technique crucial for lidar-assisted control in wind turbines. The prediction time and the quality of the wind preview from lidar measurements depend on several factors and are not constant. If the data processing is not continually adjusted, the benefit of lidar-assisted control cannot be fully exploited, or can even result in harmful control action. An online analysis of the lidar and turbine data are necessary to continually reassess the prediction time and lidar data quality. In this work, a structured process to develop an analysis tool for the prediction time and a new hardware setup for lidar-assisted control are presented. The tool consists of an online estimation of the rotor effective wind speed from lidar and turbine data and the implementation of an online cross correlation to determine the time shift between both signals. Further, initial results from an ongoing campaign in which this system was employed for providing lidar preview for feed-forward pitch control are presented.

  6. Dynamic Modeling of a Reformed Methanol Fuel Cell System using Empirical Data and Adaptive Neuro-Fuzzy Inference System Models

    DEFF Research Database (Denmark)

    Justesen, Kristian Kjær; Andreasen, Søren Juhl; Shaker, Hamid Reza

    2013-01-01

    In this work, a dynamic MATLAB Simulink model of a H3-350 Reformed Methanol Fuel Cell (RMFC) stand-alone battery charger produced by Serenergy is developed on the basis of theoretical and empirical methods. The advantage of RMFC systems is that they use liquid methanol as a fuel instead of gaseous...... of the reforming process are implemented. Models of the cooling flow of the blowers for the fuel cell and the burner which supplies process heat for the reformer are made. The two blowers have a common exhaust, which means that the two blowers influence each other’s output. The models take this into account using...... an empirical approach. Fin efficiency models for the cooling effect of the air are also developed using empirical methods. A fuel cell model is also implemented based on a standard model which is adapted to fit the measured performance of the H3-350 module. All the individual parts of the model are verified...

  7. Dynamic Modeling of a Reformed Methanol Fuel Cell System using Empirical Data and Adaptive Neuro-Fuzzy Inference System Models

    DEFF Research Database (Denmark)

    Justesen, Kristian Kjær; Andreasen, Søren Juhl; Shaker, Hamid Reza

    2014-01-01

    In this work, a dynamic MATLAB Simulink model of a H3-350 Reformed Methanol Fuel Cell (RMFC) stand-alone battery charger produced by Serenergy is developed on the basis of theoretical and empirical methods. The advantage of RMFC systems is that they use liquid methanol as a fuel instead of gaseous...... of the reforming process are implemented. Models of the cooling flow of the blowers for the fuel cell and the burner which supplies process heat for the reformer are made. The two blowers have a common exhaust, which means that the two blowers influence each other’s output. The models take this into account using...... an empirical approach. Fin efficiency models for the cooling effect of the air are also developed using empirical methods. A fuel cell model is also implemented based on a standard model which is adapted to fit the measured performance of the H3-350 module. All the individual parts of the model are verified...

  8. Cybersecurity managing systems, conducting testing, and investigating intrusions

    CERN Document Server

    Mowbray, Thomas J

    2013-01-01

    A must-have, hands-on guide for working in the cybersecurity profession Cybersecurity involves preventative methods to protect information from attacks. It requires a thorough understanding of potential threats, such as viruses and other malicious code, as well as system vulnerability and security architecture. This essential book addresses cybersecurity strategies that include identity management, risk management, and incident management, and also serves as a detailed guide for anyone looking to enter the security profession. Doubling as the text for a cybersecurity course, it is also a usef

  9. Instant OSSEC host-based intrusion detection system

    CERN Document Server

    Lhotsky, Brad

    2013-01-01

    Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. A fast-paced, practical guide to OSSEC-HIDS that will help you solve host-based security problems.This book is great for anyone concerned about the security of their servers-whether you are a system administrator, programmer, or security analyst, this book will provide you with tips to better utilize OSSEC-HIDS. Whether you're new to OSSEC-HIDS or a seasoned veteran, you'll find something in this book you can apply today!This book assumes some knowledge of basic security concepts an

  10. An adaptive map-matching algorithm based on hierarchical fuzzy system from vehicular GPS data.

    Directory of Open Access Journals (Sweden)

    Jinjun Tang

    Full Text Available An improved hierarchical fuzzy inference method based on C-measure map-matching algorithm is proposed in this paper, in which the C-measure represents the certainty or probability of the vehicle traveling on the actual road. A strategy is firstly introduced to use historical positioning information to employ curve-curve matching between vehicle trajectories and shapes of candidate roads. It improves matching performance by overcoming the disadvantage of traditional map-matching algorithm only considering current information. An average historical distance is used to measure similarity between vehicle trajectories and road shape. The input of system includes three variables: distance between position point and candidate roads, angle between driving heading and road direction, and average distance. As the number of fuzzy rules will increase exponentially when adding average distance as a variable, a hierarchical fuzzy inference system is then applied to reduce fuzzy rules and improve the calculation efficiency. Additionally, a learning process is updated to support the algorithm. Finally, a case study contains four different routes in Beijing city is used to validate the effectiveness and superiority of the proposed method.

  11. Non-intrusive uncertainty quantification in structural-acoustic systems using polynomial chaos expansion method

    Directory of Open Access Journals (Sweden)

    Wang Mingjie

    2017-01-01

    Full Text Available A framework of non-intrusive polynomial chaos expansion method (PC was proposed to investigate the statistic characteristics of the response of structural-acoustic system containing random uncertainty. The PC method does not need to reformulate model equations, and the statistics of the response can be evaluated directly. The results show that compared to the direct Monte Carlo method (MCM based on the original numerical model, the PC method is effective and more efficient.

  12. A Database of Computer Attacks for the Evaluation of Intrusion Detection Systems

    Science.gov (United States)

    1999-06-01

    administrator whenever a system binary file (such as the ps, login , or ls program) is modified. Normal users have no legitimate reason to alter these files...development of EMERALD [46], which combines statistical anomaly detection from NIDES with signature verification. Specification-based intrusion detection...the creation of a single host that can act as many hosts. Daemons that provide network services—including telnetd, ftpd, and login — display banners

  13. A framework for implementing a Distributed Intrusion Detection System (DIDS) with interoperabilty and information analysis

    OpenAIRE

    Davicino, Pablo; Echaiz, Javier; Ardenghi, Jorge Raúl

    2011-01-01

    Computer Intrusion Detection Systems (IDS) are primarily designed to protect availability, condentiality and integrity of critical information infrastructures. A Distributed IDS (DIDS) consists of several IDS over a large network(s), all of which communicate with each other, with a central server or with a cluster of servers that facilitates advanced network monitoring. In a distributed environment, DIDS are implemented using cooperative intelligent sensors distributed across the network(s). ...

  14. Rate Adaptive OFDMA Communication Systems

    International Nuclear Information System (INIS)

    Abdelhakim, M.M.M.

    2009-01-01

    Due to the varying nature of the wireless channels, adapting the transmission parameters, such as code rate, modulation order and power, in response to the channel variations provides a significant improvement in the system performance. In the OFDM systems, Per-Frame adaptation (PFA) can be employed where the transmission variables are fixed over a given frame and may change from one frame to the other. Subband (tile) loading offers more degrees of adaptation such that each group of carriers (subband) uses the same transmission parameters and different subbands may use different parameters. Changing the code rate for each tile in the same frame, results in transmitting multiple codewords (MCWs) for a single frame. In this thesis a scheme is proposed for adaptively changing the code rate of coded OFDMA systems via changing the puncturing rate within a single codeword (SCW). In the proposed structure, the data is encoded with the lowest available code rate then it is divided among the different tiles where it is punctured adaptively based on some measure of the channel quality for each tile. The proposed scheme is compared against using multiple codewords (MCWs) where the different code rates for the tiles are obtained using separate encoding processes. For bit interleaved coded modulation architecture two novel interleaving methods are proposed, namely the puncturing dependant interleaver (PDI) and interleaved puncturing (IntP), which provide larger interleaving depth. In the PDI method the coded bits with the same rate over different tiles are grouped for interleaving. In IntP structure the interleaving is performed prior to puncturing. The performance of the adaptive puncturing technique is investigated under constant bit rate constraint and variable bit rate. Two different adaptive modulation and coding (AMC) selection methods are examined for variable bit rate adaptive system. The first is a recursive scheme that operates directly on the SNR whereas the second

  15. Adaptable Web Modules to Stimulate Active Learning in Engineering Hydrology using Data and Model Simulations of Three Regional Hydrologic Systems

    Science.gov (United States)

    Habib, E. H.; Tarboton, D. G.; Lall, U.; Bodin, M.; Rahill-Marier, B.; Chimmula, S.; Meselhe, E. A.; Ali, A.; Williams, D.; Ma, Y.

    2013-12-01

    server-based system. Open source web technologies and community-based tools are used to facilitate wide dissemination and adaptation by diverse, independent institutions. The new hydrologic learning modules are based on recent developments in hydrologic modeling, data, and resources. The modules are embedded in three regional-scale ecosystems, Coastal Louisiana, Florida Everglades, and Utah Great Salt Lake Basin. These sites provide a wealth of hydrologic concepts and scenarios that can be used in most water resource and hydrology curricula. The study develops several learning modules based on the three hydro-systems covering subjects such as: water-budget analysis, effects of human and natural changes, climate-hydrology teleconnections, and water-resource management scenarios. The new developments include an instructional interface to give critical guidance and support to the learner and an instructor's guide containing adaptation and implementation procedures to assist instructors in adopting and integrating the material into courses and provide a consistent experience. The design of the new hydrologic education developments will be transferable to independent institutions and adaptable both instructionally and technically through a server system capable of supporting additional developments by the educational community.

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

    Science.gov (United States)

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

    2005-11-01

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

  17. 3D modeling of a dolerite intrusion from the photogrammetric and geophysical data integration.

    Science.gov (United States)

    Duarte, João; Machadinho, Ana; Figueiredo, Fernando; Mira, Maria

    2015-04-01

    The aims of this study is create a methodology based on the integration of data obtained from various available technologies, which allow a credible and complete evaluation of rock masses. In this particular case of a dolerite intrusion, which deployed an exploration of aggregates and belongs to the Jobasaltos - Extracção e Britagem. S.A.. Dolerite intrusion is situated in the volcanic complex of Serra de Todo-o-Mundo, Casais Gaiola, intruded in Jurassic sandstones. The integration of the surface and subsurface mapping, obtained by technology UAVs (Drone) and geophysical surveys (Electromagnetic Method - TEM 48 FAST), allows the construction of 2D and 3D models of the study local. The combination of the 3D point clouds produced from two distinct processes, modeling of photogrammetric and geophysical data, will be the basis for the construction of a single model of set. The rock masses in an integral perspective being visible their development above the surface and subsurface. The presentation of 2D and 3D models will give a perspective of structures, fracturation, lithology and their spatial correlations contributing to a better local knowledge, as well as its potential for the intended purpose. From these local models it will be possible to characterize and quantify the geological structures. These models will have its importance as a tool to assist in the analysis and drafting of regional models. The qualitative improvement in geological/structural modeling, seeks to reduce the value of characterization/cost ratio, in phase of prospecting, improving the investment/benefit ratio. This methodology helps to assess more accurately the economic viability of the projects.

  18. Improved wavelet packet classification algorithm for vibrational intrusions in distributed fiber-optic monitoring systems

    Science.gov (United States)

    Wang, Bingjie; Pi, Shaohua; Sun, Qi; Jia, Bo

    2015-05-01

    An improved classification algorithm that considers multiscale wavelet packet Shannon entropy is proposed. Decomposition coefficients at all levels are obtained to build the initial Shannon entropy feature vector. After subtracting the Shannon entropy map of the background signal, components of the strongest discriminating power in the initial feature vector are picked out to rebuild the Shannon entropy feature vector, which is transferred to radial basis function (RBF) neural network for classification. Four types of man-made vibrational intrusion signals are recorded based on a modified Sagnac interferometer. The performance of the improved classification algorithm has been evaluated by the classification experiments via RBF neural network under different diffusion coefficients. An 85% classification accuracy rate is achieved, which is higher than the other common algorithms. The classification results show that this improved classification algorithm can be used to classify vibrational intrusion signals in an automatic real-time monitoring system.

  19. Intrusion detection sensors

    International Nuclear Information System (INIS)

    Williams, J.D.

    1978-07-01

    Intrusion detection sensors are an integral part of most physical security systems. Under the sponsorship of the U.S. Department of Energy, Office of Safeguards and Security, Sandia Laboratories has conducted a survey of available intrusion detection sensors and has tested a number of different sensors. An overview of these sensors is provided. This overview includes (1) the operating principles of each type of sensor, (2) unique sensor characteristics, (3) desired sensor improvements which must be considered in planning an intrusion detection system, and (4) the site characteristics which affect the performance of both exterior and interior sensors. Techniques which have been developed to evaluate various intrusion detection sensors are also discussed

  20. Optimal Placement and Sizing of PV-STATCOM in Power Systems Using Empirical Data and Adaptive Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    Reza Sirjani

    2018-03-01

    Full Text Available Solar energy is a source of free, clean energy which avoids the destructive effects on the environment that have long been caused by power generation. Solar energy technology rivals fossil fuels, and its development has increased recently. Photovoltaic (PV solar farms can only produce active power during the day, while at night, they are completely idle. At the same time, though, active power should be supported by reactive power. Reactive power compensation in power systems improves power quality and stability. The use during the night of a PV solar farm inverter as a static synchronous compensator (or PV-STATCOM device has recently been proposed which can improve system performance and increase the utility of a PV solar farm. In this paper, a method for optimal PV-STATCOM placement and sizing is proposed using empirical data. Considering the objectives of power loss and cost minimization as well as voltage improvement, two sub-problems of placement and sizing, respectively, are solved by a power loss index and adaptive particle swarm optimization (APSO. Test results show that APSO not only performs better in finding optimal solutions but also converges faster compared with bee colony optimization (BCO and lightening search algorithm (LSA. Installation of a PV solar farm, STATCOM, and PV-STATCOM in a system are each evaluated in terms of efficiency and cost.

  1. On-line detection of Escherichia coli intrusion in a pilot-scale drinking water distribution system.

    Science.gov (United States)

    Ikonen, Jenni; Pitkänen, Tarja; Kosse, Pascal; Ciszek, Robert; Kolehmainen, Mikko; Miettinen, Ilkka T

    2017-08-01

    Improvements in microbial drinking water quality monitoring are needed for the better control of drinking water distribution systems and for public health protection. Conventional water quality monitoring programmes are not always able to detect a microbial contamination of drinking water. In the drinking water production chain, in addition to the vulnerability of source waters, the distribution networks are prone to contamination. In this study, a pilot-scale drinking-water distribution network with an on-line monitoring system was utilized for detecting bacterial intrusion. During the experimental Escherichia coli intrusions, the contaminant was measured by applying a set of on-line sensors for electric conductivity (EC), pH, temperature (T), turbidity, UV-absorbance at 254 nm (UVAS SC) and with a device for particle counting. Monitored parameters were compared with the measured E. coli counts using the integral calculations of the detected peaks. EC measurement gave the strongest signal compared with the measured baseline during the E. coli intrusion. Integral calculations showed that the peaks in the EC, pH, T, turbidity and UVAS SC data were detected corresponding to the time predicted. However, the pH and temperature peaks detected were barely above the measured baseline and could easily be mixed with the background noise. The results indicate that on-line monitoring can be utilized for the rapid detection of microbial contaminants in the drinking water distribution system although the peak interpretation has to be performed carefully to avoid being mixed up with normal variations in the measurement data. Copyright © 2017 Elsevier Ltd. All rights reserved.

  2. Linking precious metal enrichment and halogen cycling in mafic magmatic systems: insights from the Rum layered intrusion, NW Scotland

    Science.gov (United States)

    Kelly, A. P.; O'Driscoll, B.; Clay, P. L.; Burgess, R.

    2017-12-01

    Layered intrusions host the world's largest known concentrations of the platinum-group elements (PGE). Emphasis has been attached to the role of halogen-bearing fluids in concentrating the precious metals, but whether this occurs at the magmatic stage, or via subsequent metasomatism, is actively debated. One obstacle to progress has been the analytical difficulty of measuring low abundances of the halogens in the cumulate products of layered intrusions. To elucidate the importance of the halogens in facilitating PGE-mineralisation, as well as fingerprint halogen provenance and assess the importance of halogen cycling in mafic magma systems more generally, a suite of samples encompassing different stages of activity of the Palaeogene Rum layered intrusion was investigated. Halogen abundances were measured by neutron irradiation noble gas mass spectrometric analysis, permitting the detection of relatively low (ppm-ppb) abundances of Cl, Br and I in mg-sized samples. The samples include PGE-enriched chromite seams, various cumulates (e.g., peridotites), picrites (approximating the Rum parental magma), and pegmatites representing volatile-rich melts that circulated the intrusion at a late-stage in its solidification history. The new data reveal that PGE-bearing chromite seams contain relatively low Cl concentrations (2-3 ppm), with high molar ratios of Br/Cl and I/Cl (0.005 and 0.009, respectively). The picrites and cumulates have Br/Cl and I/Cl ratios close to sub-continental lithospheric mantle values of approximately 0.0013 and 0.00002, respectively, and thus likely reflect the Rum magma source region. A positive correlation between Cl and Br signifies comparable partitioning behaviour in all samples. However, I is more variable, displaying a positive correlation with Cl for more primitive samples (e.g. picrite and peridotite), and seemingly decoupling from Br and Cl in chromite seams and pegmatites. The relative enrichment of I over Cl in the chromite seams points

  3. Adaptivity in Professional Printing Systems

    NARCIS (Netherlands)

    Verriet, J.H.; Basten, T; Hamberg, R.; Reckers, F.J.; Somers, L.

    2013-01-01

    There is a constant pressure on developers of embedded systems to simultaneously increase system functionality and to decrease development costs. Aviable way to obtain a better system performance with the same physical hardware is adaptivity: a system should be able to adapt itself to dynamically

  4. Human intrusion

    International Nuclear Information System (INIS)

    Hora, S.; Neill, R.; Williams, R.; Bauser, M.; Channell, J.

    1993-01-01

    This paper focused on the possible approaches to evaluating the impacts of human intrusion on nuclear waste disposal. Several major issues were reviewed. First, it was noted that human intrusion could be addressed either quantitatively through performance assessments or qualitatively through design requirements. Second, it was decided that it was impossible to construct a complete set of possible future human intrusion scenarios. Third, the question of when the effect of possible human intrusion should be considered, before or after site selection was reviewed. Finally, the time frame over which human intrusion should be considered was discussed

  5. H2-optimal control of an adaptive optics system : Part I, data-driven modeling of the wavefront disturbance

    NARCIS (Netherlands)

    Hinnen, K.; Verhaegen, M.; Doelman, N.

    2005-01-01

    Even though the wavefront distortion introduced by atmospheric turbulence is a dynamic process, its temporal evolution is usually neglected in the adaptive optics (AO) control design. Most AO control systems consider only the spatial correlation in a separate wavefront reconstruction step. By

  6. An Adaptable Seismic Data Format

    Science.gov (United States)

    Krischer, Lion; Smith, James; Lei, Wenjie; Lefebvre, Matthieu; Ruan, Youyi; de Andrade, Elliott Sales; Podhorszki, Norbert; Bozdağ, Ebru; Tromp, Jeroen

    2016-11-01

    We present ASDF, the Adaptable Seismic Data Format, a modern and practical data format for all branches of seismology and beyond. The growing volume of freely available data coupled with ever expanding computational power opens avenues to tackle larger and more complex problems. Current bottlenecks include inefficient resource usage and insufficient data organization. Properly scaling a problem requires the resolution of both these challenges, and existing data formats are no longer up to the task. ASDF stores any number of synthetic, processed or unaltered waveforms in a single file. A key improvement compared to existing formats is the inclusion of comprehensive meta information, such as event or station information, in the same file. Additionally, it is also usable for any non-waveform data, for example, cross-correlations, adjoint sources or receiver functions. Last but not least, full provenance information can be stored alongside each item of data, thereby enhancing reproducibility and accountability. Any data set in our proposed format is self-describing and can be readily exchanged with others, facilitating collaboration. The utilization of the HDF5 container format grants efficient and parallel I/O operations, integrated compression algorithms and check sums to guard against data corruption. To not reinvent the wheel and to build upon past developments, we use existing standards like QuakeML, StationXML, W3C PROV and HDF5 wherever feasible. Usability and tool support are crucial for any new format to gain acceptance. We developed mature C/Fortran and Python based APIs coupling ASDF to the widely used SPECFEM3D_GLOBE and ObsPy toolkits.

  7. Systematic adaptation of data delivery

    Science.gov (United States)

    Bakken, David Edward

    2016-02-02

    This disclosure describes, in part, a system management component for use in a power grid data network to systematically adjust the quality of service of data published by publishers and subscribed to by subscribers within the network. In one implementation, subscribers may identify a desired data rate, a minimum acceptable data rate, desired latency, minimum acceptable latency and a priority for each subscription and the system management component may adjust the data rates in real-time to ensure that the power grid data network does not become overloaded and/or fail. In one example, subscriptions with lower priorities may have their quality of service adjusted before subscriptions with higher priorities. In each instance, the quality of service may be maintained, even if reduced, to meet or exceed the minimum acceptable quality of service for the subscription.

  8. Farming System Evolution and Adaptive Capacity: Insights for Adaptation Support

    Directory of Open Access Journals (Sweden)

    Jami L. Dixon

    2014-02-01

    Full Text Available Studies of climate impacts on agriculture and adaptation often provide current or future assessments, ignoring the historical contexts farming systems are situated within. We investigate how historical trends have influenced farming system adaptive capacity in Uganda using data from household surveys, semi-structured interviews, focus-group discussions and observations. By comparing two farming systems, we note three major findings: (1 similar trends in farming system evolution have had differential impacts on the diversity of farming systems; (2 trends have contributed to the erosion of informal social and cultural institutions and an increasing dependence on formal institutions; and (3 trade-offs between components of adaptive capacity are made at the farm-scale, thus influencing farming system adaptive capacity. To identify the actual impacts of future climate change and variability, it is important to recognize the dynamic nature of adaptation. In practice, areas identified for further adaptation support include: shift away from one-size-fits-all approach the identification and integration of appropriate modern farming method; a greater focus on building inclusive formal and informal institutions; and a more nuanced understanding regarding the roles and decision-making processes of influential, but external, actors. More research is needed to understand farm-scale trade-offs and the resulting impacts across spatial and temporal scales.

  9. Torque Control During Intrusion on Upper Central Incisor in Labial and Lingual bracket System - A 3D Finite Element Study.

    Science.gov (United States)

    Pol, Tejas R; Vandekar, Meghna; Patil, Anuradha; Desai, Sanjana; Shetty, Vikram; Hazarika, Saptarshi

    2018-01-01

    The aim of present study was to investigate the difference of torque control during intrusive force on upper central incisors with normal, under and high torque in lingual and labial orthodontic systems through 3D finite element analysis. Six 3D models of an upper right central incisor with different torque were designed in Solid Works 2006. Software ANSYS Version 16.0 was used to evaluate intrusive force on upper central incisor model . An intrusive force of 0.15 N was applied to the bracket slot in different torque models and the displacements along a path of nodes in the upper central incisor was assessed. On application of Intrusive force on under torqued upper central incisor in Labial system produce labial crown movement but in Lingual system caused lingual movement in the apical and incisal parts. The same intrusive force in normal-torqued central incisor led to a palatal movement in apical and labial displacement of incisal edge in Lingual system and a palatal displacement in apical area and a labial movement in the incisal edge in Labial systemin. In overtorqued upper central incisor, the labial crown displacement in Labial system is more than Lingual system. In labial and lingual system on application of the same forces in upper central incisor with different inclinations showed different responses. The magnitudes of torque Loss during intrusive loads in incisors with normal, under and over-torque were higher in Labial system than Lingual orthodontic appliances. Key words: FEM, lingual orthodontics, intrusion, torque control, labial bracket systems.

  10. Space-time adaptive decision feedback neural receivers with data selection for high-data-rate users in DS-CDMA systems.

    Science.gov (United States)

    de Lamare, Rodrigo C; Sampaio-Neto, Raimundo

    2008-11-01

    A space-time adaptive decision feedback (DF) receiver using recurrent neural networks (RNNs) is proposed for joint equalization and interference suppression in direct-sequence code-division multiple-access (DS-CDMA) systems equipped with antenna arrays. The proposed receiver structure employs dynamically driven RNNs in the feedforward section for equalization and multiaccess interference (MAI) suppression and a finite impulse response (FIR) linear filter in the feedback section for performing interference cancellation. A data selective gradient algorithm, based upon the set-membership (SM) design framework, is proposed for the estimation of the coefficients of RNN structures and is applied to the estimation of the parameters of the proposed neural receiver structure. Simulation results show that the proposed techniques achieve significant performance gains over existing schemes.

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

    Directory of Open Access Journals (Sweden)

    Angelo Catalano

    2014-09-01

    Full Text Available 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.

  12. Oxygen isotope mapping and evaluation of paleo-hydrothermal systems associated with synvolcanic intrusion and VMS deposits

    International Nuclear Information System (INIS)

    Taylor, B.E

    2001-01-01

    Whole-rock oxygen isotope mapping provides a useful method for the delineation and quantitative evaluation of paleo-hydrothermal systems associated with syn-volcanic intrusions and volcanic-associated massive sulfide (VMS) deposits. During the course of a four-year study of regional alteration systems associated with VMS Deposits, four syn-volcanic intrusive complexes in Canada were mapped using stable isotope techniques. The complexes included Noranda, Quebec; Clifford-Ben Nevis, Ontario; Snow Lake, Manitoba, and Sturgeon Lake, Ontario. This study was regional in extent, involving large areas and large numbers of whole-rock samples: Noranda (625 km 2 ;≥600 samples, plus others (total = 1198); Sturgeon Lake (525 km 2 ; 452 samples); Clifford-Ben Nevis (160 km 2 ; 251 samples); and Snow Lake (84 km 2 ; 575 samples). Isotopic data on whole-rock carbonates and hydrous minerals were also collected. The regional isotopic studies were carried out in concert with other studies on mineral assemblages and mineral composition, and on associated intrusive and extrusive rocks. The Clifford-Ben Nevis area was selected as a control area, in as much as it contains no known VMS deposits; all other areas are well-known, productive VMS districts. Oxygen isotope maps are, in a sense, thermal maps, illustrating the paleo-distribution of heat and fluids, and offering a potential aid to exploration. The isotopic data may be contoured to reveal zones of 18 O depletion and enrichment, relative to unaltered rocks. Zones of δ 18 O≤60% comprise rocks that have reacted with seawater at high (e.g., 300+ o C) temperatures. The volume of foot-wall rocks isotopically-depleted by water/rock interaction during the life of one or more episodes of submarine hydrothermal activity is proportional to the amount of heat available from the syn-volcanic intrusive center. These altered rocks comprise the reaction zone often inferred to have supplied metals and other constituents for the VMS deposits

  13. Prospective relations between intrusive parenting and child behavior problems: Differential moderation by parasympathetic nervous system regulation and child sex.

    Science.gov (United States)

    Rudd, Kristen L; Alkon, Abbey; Yates, Tuppett M

    2017-10-15

    This study examined children's parasympathetic nervous system (PNS) regulation, which was indexed by respiratory sinus arrhythmia (RSA) during rest, reactivity, and recovery episodes, and sex as moderators of predicted relations between observed intrusive parenting and later observer-rated child behavior problems. Child-caregiver dyads (N=250; 50% girls; 46% Latino/a) completed a series of laboratory assessments yielding independent measures of intrusive parenting at age 4, PNS regulation at age 6, and child behavior problems at age 8. Results indicated that intrusive parenting was related to more internalizing problems among boys who showed low RSA reactivity (i.e., PNS withdrawal from pre-startle to startle challenge), but RSA reactivity did not moderate this relation among girls. Interestingly, RSA recovery (i.e., PNS activation from startle challenge to post-startle) moderated these relations differently for boys and girls. For girls with relatively low RSA post-startle (i.e., less recovery), intrusive parenting was positively related to both internalizing and externalizing problems. However, the reverse was true for boys, such that there was a significant positive relation between intrusive parenting and later externalizing problems among boys who evidenced relatively high RSA post-startle (i.e., more recovery). Findings provide evidence for the moderation of intrusive caregiving effects by children's PNS regulation while highlighting the differential patterning of these relations across distinct phases of the regulatory response and as a function of child sex. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Non-intrusive appliance load monitoring system based on a modern kWh-meter

    Energy Technology Data Exchange (ETDEWEB)

    Pihala, H. [VTT Energy, Espoo (Finland). Energy Systems

    1998-12-01

    Non-intrusive appliance load monitoring (NIALM) is a fairly new method to estimate load profiles of individual electric appliances in a small building, like a household, by monitoring the whole load at a single point with one recording device without sub-meters. Appliances have special electrical characteristics, the positive and negative active and reactive power changes during the time they are switched on or off. These changes are called events and are detected with a monitoring device called an event recorder. Different NIALM-concepts developed in Europe and in the United States are generally discussed. The NIALM-concept developed in this study is based on a 3-phase, power quality monitoring kWh-meter and unique load identification algorithms. This modern kWh-meter with a serial data bus to a laptop personal computer is used as die event recorder. The NIALM-concept of this presentation shows for the first time how a kWh-meter can be used at the same time for billing, power quality and appliance end-use monitoring. An essential part of the developed NIALM-system prototype is the software of load identification algorithms which runs in an off-line personal computer. These algorithms are able to identify, with a certain accuracy, both two-state and multi-state appliances. This prototype requires manual-setup in which the naming of appliances is performed. The results of the prototype NIALMS were verified in a large, single family detached house and they were compared to the results of other prototypes in France and the United States, although this comparison is difficult because of different supply systems, appliance stock and number of tested sites. Different applications of NIALM are discussed. Gathering of load research data, verification of DSM-programs, home automation, failure analysis of appliances and security surveillance of buildings are interesting areas of NIALM. Both utilities and customers can benefit from these applications. It is possible to

  15. Network Intrusion Detection System (NIDS in Cloud Environment based on Hidden Naïve Bayes Multiclass Classifier

    Directory of Open Access Journals (Sweden)

    Hafza A. Mahmood

    2018-04-01

    Full Text Available Cloud Environment is next generation internet based computing system that supplies customiza-ble services to the end user to work or access to the various cloud applications. In order to provide security and decrease the damage of information system, network and computer system it is im-portant to provide intrusion detection system (IDS. Now Cloud environment are under threads from network intrusions, as one of most prevalent and offensive means Denial of Service (DoS attacks that cause dangerous impact on cloud computing systems. This paper propose Hidden naïve Bayes (HNB Classifier to handle DoS attacks which is a data mining (DM model used to relaxes the conditional independence assumption of Naïve Bayes classifier (NB, proposed sys-tem used HNB Classifier supported with discretization and feature selection where select the best feature enhance the performance of the system and reduce consuming time. To evaluate the per-formance of proposal system, KDD 99 CUP and NSL KDD Datasets has been used. The experi-mental results show that the HNB classifier improves the performance of NIDS in terms of accu-racy and detecting DoS attacks, where the accuracy of detect DoS is 100% in three test KDD cup 99 dataset by used only 12 feature that selected by use gain ratio while in NSL KDD Dataset the accuracy of detect DoS attack is 90 % in three Experimental NSL KDD dataset by select 10 fea-ture only.

  16. Cyber-intrusion Auto-response and Policy Management System (CAPMS)

    Energy Technology Data Exchange (ETDEWEB)

    Lusk, Steve [ViaSat Inc., Boston, MA (United States); Lawrence, David [Duke Energy, Charlotte, NC (United States); Suvana, Prakash [Southern California Edison, Rosemead, CA (United States)

    2015-11-11

    The Cyber-intrusion Auto-response and Policy Management System (CAPMS) project was funded by a grant from the US Department of Energy (DOE) Cybersecurity for Energy Delivery Systems (CEDS) program with contributions from two partner electric utilities: Southern California Edison (SCE) and Duke Energy. The goal of the project was to demonstrate protecting smart grid assets from a cyber attack in a way that “does not impede critical energy delivery functions.” This report summarizes project goals and activities for the CAPMS project and explores what did and did not work as expected. It concludes with an assessment of possible benefits and value of the system for the future.

  17. An Ontology for Identifying Cyber Intrusion Induced Faults in Process Control Systems

    Science.gov (United States)

    Hieb, Jeffrey; Graham, James; Guan, Jian

    This paper presents an ontological framework that permits formal representations of process control systems, including elements of the process being controlled and the control system itself. A fault diagnosis algorithm based on the ontological model is also presented. The algorithm can identify traditional process elements as well as control system elements (e.g., IP network and SCADA protocol) as fault sources. When these elements are identified as a likely fault source, the possibility exists that the process fault is induced by a cyber intrusion. A laboratory-scale distillation column is used to illustrate the model and the algorithm. Coupled with a well-defined statistical process model, this fault diagnosis approach provides cyber security enhanced fault diagnosis information to plant operators and can help identify that a cyber attack is underway before a major process failure is experienced.

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

    Science.gov (United States)

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

    2017-08-01

    Over the past few decades, the design of an intelligent Intrusion Detection System (IDS) remains an open challenge to the research community. Continuous efforts by the researchers have resulted in the development of several learning models based on Artificial Neural Network (ANN) to improve the performance of the IDSs. However, there exists a tradeoff with respect to the stability of ANN architecture and the detection rate for less frequent attacks. This paper presents a novel approach based on Helly property of Hypergraph and Arithmetic Residue-based Probabilistic Neural Network (HG AR-PNN) to address the classification problem in IDS. The Helly property of Hypergraph was exploited for the identification of the optimal feature subset and the arithmetic residue of the optimal feature subset was used to train the PNN. The performance of HG AR-PNN was evaluated using KDD CUP 1999 intrusion dataset. Experimental results prove the dominance of HG AR-PNN classifier over the existing classifiers with respect to the stability and improved detection rate for less frequent attacks. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Monitoring and Assessment of Saltwater Intrusion using Geographic Information Systems (GIS), Remote Sensing and Geophysical measurements of Guimaras Island, Philippines

    Science.gov (United States)

    Hernandez, B. C. B.

    2015-12-01

    Degrading groundwater quality due to saltwater intrusion is one of the key challenges affecting many island aquifers. These islands hold limited capacity for groundwater storage and highly dependent on recharge due to precipitation. But its ease of use, natural storage and accessibility make it more vulnerable to exploitation and more susceptible to encroachment from its surrounding oceanic waters. Estimating the extent of saltwater intrusion and the state of groundwater resources are important in predicting and managing water supply options for the community. In Guimaras island, central Philippines, increasing settlements, agriculture and tourism are causing stresses on its groundwater resource. Indications of saltwater intrusion have already been found at various coastal areas in the island. A Geographic Information Systems (GIS)-based approach using the GALDIT index was carried out. This includes six parameters assessing the seawater intrusion vulnerability of each hydrogeologic setting: Groundwater occurrence, Aquifer hydraulic conductivity, Groundwater Level above sea, Distance to shore, Impact of existing intrusion and Thickness of Aquifer. To further determine the extent of intrusion, Landsat images of various thematic layers were stacked and processed for unsupervised classification and electrical resistivity tomography using a 28-electrode system with array lengths of 150 and 300 meters was conducted. The GIS index showed where the vulnerable areas are located, while the geophysical measurements and images revealed extent of seawater encroachment along the monitoring wells. These results are further confirmed by the measurements collected from the monitoring wells. This study presents baseline information on the state of groundwater resources and increase understanding of saltwater intrusion dynamics in island ecosystems by providing a guideline for better water resource management in the Philippines.

  20. Morphologic and hemodynamic analysis of dental pulp in dogs after molar intrusion with the skeletal anchorage system.

    Science.gov (United States)

    Konno, Yuichi; Daimaruya, Takayoshi; Iikubo, Masahiro; Kanzaki, Reiko; Takahashi, Ichiro; Sugawara, Junji; Sasano, Takashi

    2007-08-01

    We have successfully treated skeletal open bite by intruding posterior teeth with the skeletal anchorage system. Our aim in this study was to morphologically and hemodynamically evaluate the changes in pulp tissues when molars are radically intruded. The mandibular fourth premolars of 9 adult beagle dogs were divided into 3 groups: a sham operated group (n = 6, 3 dogs), 4-month intrusion group (n = 6, 3 dogs), and a further 4-month retention group (n = 6, 3 dogs). We evaluated the morphological changes of the pulp and dentin-the amount of vacuolar degeneration in the odontoblast layer, the predentin width and nervous continuity in the pulp tissue, and the pulpal blood-flow response evoked by electrical stimulation in the dental pulp. Extreme molar intrusion with the skeletal anchorage system caused slight degenerative changes in the pulp tissue, followed by recovery after the orthodontic force was released. Circulatory system and nervous functions were basically maintained during the intrusion, although a certain level of downregulation was observed. These morphologic and functional regressive changes in the pulp tissue after molar intrusion improved during the retention period. Histologic changes and changes in pulpal blood flow and function are reversible, even during radical intrusion of molars.

  1. Adaptive protection algorithm and system

    Science.gov (United States)

    Hedrick, Paul [Pittsburgh, PA; Toms, Helen L [Irwin, PA; Miller, Roger M [Mars, PA

    2009-04-28

    An adaptive protection algorithm and system for protecting electrical distribution systems traces the flow of power through a distribution system, assigns a value (or rank) to each circuit breaker in the system and then determines the appropriate trip set points based on the assigned rank.

  2. Adaptive web data extraction policies

    Directory of Open Access Journals (Sweden)

    Provetti, Alessandro

    2008-12-01

    Full Text Available Web data extraction is concerned, among other things, with routine data accessing and downloading from continuously-updated dynamic Web pages. There is a relevant trade-off between the rate at which the external Web sites are accessed and the computational burden on the accessing client. We address the problem by proposing a predictive model, typical of the Operating Systems literature, of the rate-of-update of each Web source. The presented model has been implemented into a new version of the Dynamo project: a middleware that assists in generating informative RSS feeds out of traditional HTML Web sites. To be effective, i.e., make RSS feeds be timely and informative and to be scalable, Dynamo needs a careful tuning and customization of its polling policies, which are described in detail.

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

    Science.gov (United States)

    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

  4. Confidentiality Protection of User Data and Adaptive Resource Allocation for Managing Multiple Workflow Performance in Service-Based Systems

    Science.gov (United States)

    An, Ho

    2012-01-01

    In this dissertation, two interrelated problems of service-based systems (SBS) are addressed: protecting users' data confidentiality from service providers, and managing performance of multiple workflows in SBS. Current SBSs pose serious limitations to protecting users' data confidentiality. Since users' sensitive data is sent in…

  5. Fractal analysis of SEM images and mercury intrusion porosimetry data for the microstructural characterization of microcrystalline cellulose-based pellets

    International Nuclear Information System (INIS)

    Gomez-Carracedo, A.; Alvarez-Lorenzo, C.; Coca, R.; Martinez-Pacheco, R.; Concheiro, A.; Gomez-Amoza, J.L.

    2009-01-01

    The microstructure of theophylline pellets prepared from microcrystalline cellulose, carbopol and dicalcium phosphate dihydrate, according to a mixture design, was characterized using textural analysis of gray-level scanning electron microscopy (SEM) images and thermodynamic analysis of the cumulative pore volume distribution obtained by mercury intrusion porosimetry. Surface roughness evaluated in terms of gray-level non-uniformity and fractal dimension of pellet surface depended on agglomeration phenomena during extrusion/spheronization. Pores at the surface, mainly 1-15 μm in diameter, determined both the mechanism and the rate of theophylline release, and a strong negative correlation between the fractal geometry and the b parameter of the Weibull function was found for pellets containing >60% carbopol. Theophylline mean dissolution time from these pellets was about two to four times greater. Textural analysis of SEM micrographs and fractal analysis of mercury intrusion data are complementary techniques that enable complete characterization of multiparticulate drug dosage forms

  6. Application of the Concept of Intrusion Tolerant System for Evaluating Cyber Security Enhancements

    International Nuclear Information System (INIS)

    Lee, Chanyoung; Seong, Poong Hyun

    2016-01-01

    One of the major problems is that nuclear industry is in very early stage in dealing with cyber security issues. It is because that cyber security has received less attention compared to other safety problems. In addition, late adoption of digital I and C systems has resulted in lower level of cyber security advancements in nuclear industry than ones in other industries. For the cyber security of NPP I and C systems, many regulatory documents, guides and standards were already published. These documents include cyber security plans, methods for cyber security assessments and comprehensive set of security controls. However, methods which can help assess how much security is improved if a specific security control is applied are not included in these documents. Hence, NPP I and C system designers may encounter difficulties when trying to apply security controls with limited structure and cost. In order to provide useful information about cyber security issues including cyber security enhancements, this paper suggests a framework to evaluate how much cyber security is improved when a specific cyber security enhancement is applied in NPPs. In order to provide useful information about cyber security issues including cyber security enhancements, this paper suggests a framework to evaluate how much cyber security is improved when a specific cyber security enhancement is applied in NPPs. The extent of cyber security improvement caused by security enhancement was defined as reduction ratio of the failure probability to secure the system from cyber-attack as Eq.1. The concept of 'intrusion tolerant system' was applied to not only prevent cyber-attacks but also limit the extent of damage in this study. For applying the concept of intrusion tolerant system to NPP, the event tree was constructed with some assumptions. Cyber security improvement caused by cyber security enhancement can be estimated as Eq.3. By comparing current system to the enhanced system, it is possible to

  7. Application of the Concept of Intrusion Tolerant System for Evaluating Cyber Security Enhancements

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Chanyoung; Seong, Poong Hyun [KAIST, Daejeon (Korea, Republic of)

    2016-10-15

    One of the major problems is that nuclear industry is in very early stage in dealing with cyber security issues. It is because that cyber security has received less attention compared to other safety problems. In addition, late adoption of digital I and C systems has resulted in lower level of cyber security advancements in nuclear industry than ones in other industries. For the cyber security of NPP I and C systems, many regulatory documents, guides and standards were already published. These documents include cyber security plans, methods for cyber security assessments and comprehensive set of security controls. However, methods which can help assess how much security is improved if a specific security control is applied are not included in these documents. Hence, NPP I and C system designers may encounter difficulties when trying to apply security controls with limited structure and cost. In order to provide useful information about cyber security issues including cyber security enhancements, this paper suggests a framework to evaluate how much cyber security is improved when a specific cyber security enhancement is applied in NPPs. In order to provide useful information about cyber security issues including cyber security enhancements, this paper suggests a framework to evaluate how much cyber security is improved when a specific cyber security enhancement is applied in NPPs. The extent of cyber security improvement caused by security enhancement was defined as reduction ratio of the failure probability to secure the system from cyber-attack as Eq.1. The concept of 'intrusion tolerant system' was applied to not only prevent cyber-attacks but also limit the extent of damage in this study. For applying the concept of intrusion tolerant system to NPP, the event tree was constructed with some assumptions. Cyber security improvement caused by cyber security enhancement can be estimated as Eq.3. By comparing current system to the enhanced system, it is

  8. Diabetes Intrusiveness and Wellness among Elders: A Test of the Illness Intrusiveness Model

    Science.gov (United States)

    DeCoster, Vaughn A.; Killian, Tim; Roessler, Richard T.

    2013-01-01

    Using data collected from 147 predominately African American senior citizens in Arkansas, this research examined the Illness Intrusiveness Model (Devins, 1991; Devins & Seland, 1987; Devins & Shnek, 2000) to explain variations in wellness specifically related to participants' adaptation to diabetes. The theoretical model hypothesized that…

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

    Directory of Open Access Journals (Sweden)

    Min-Joo Kang

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

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

    Science.gov (United States)

    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 Non-Intrusive GMA Welding Process Quality Monitoring System Using Acoustic Sensing.

    Science.gov (United States)

    Cayo, Eber Huanca; Alfaro, Sadek Crisostomo Absi

    2009-01-01

    Most of the inspection methods used for detection and localization of welding disturbances are based on the evaluation of some direct measurements of welding parameters. This direct measurement requires an insertion of sensors during the welding process which could somehow alter the behavior of the metallic transference. An inspection method that evaluates the GMA welding process evolution using a non-intrusive process sensing would allow not only the identification of disturbances during welding runs and thus reduce inspection time, but would also reduce the interference on the process caused by the direct sensing. In this paper a nonintrusive method for weld disturbance detection and localization for weld quality evaluation is demonstrated. The system is based on the acoustic sensing of the welding electrical arc. During repetitive tests in welds without disturbances, the stability acoustic parameters were calculated and used as comparison references for the detection and location of disturbances during the weld runs.

  12. Geophysical detection of marine intrusions in Black Sea coastal areas (Romania) using VES and ERT data

    OpenAIRE

    CHITEA, Florina; GEORGESCU, Paul; IOANE, Dumitru

    2011-01-01

    Abstract. Communities living in coastal areas depend in a great extent on the fresh water resources exploited from aquifers which are usually in a natural hydrodynamic equilibrium with the sea water. The contamination of fresh water with marine saltwater determines a significant increase in the aquifers electric conductivity, allowing an efficient application of resistivity methods in detecting and monitoring the marine intrusions. We present case studies from Romania (Costinesti and Vama Vec...

  13. Context-aware local Intrusion Detection in SCADA systems : a testbed and two showcases

    NARCIS (Netherlands)

    Chromik, Justyna Joanna; Haverkort, Boudewijn R.H.M.; Remke, Anne Katharina Ingrid; Pilch, Carina; Brackmann, Pascal; Duhme, Christof; Everinghoff, Franziska; Giberlein, Artur; Teodorowicz, Thomas; Wieland, Julian

    2017-01-01

    This paper illustrates the use of a testbed that we have developed for context-aware local intrusion detection. This testbed is based on the co-simulation framework Mosaik and allows for the validation of local intrusion detection mechanisms at field stations in power distribution networks. For two

  14. Petrogenesis of postcollisional magmatism at Scheelite Dome, Yukon, Canada: Evidence for a lithospheric mantle source for magmas associated with intrusion-related gold systems

    Science.gov (United States)

    Mair, John L.; Farmer, G. Lang; Groves, David I.; Hart, Craig J.R.; Goldfarb, Richard J.

    2011-01-01

    The type examples for the class of deposits termed intrusion-related gold systems occur in the Tombstone-Tungsten belt of Alaska and Yukon, on the eastern side of the Tintina gold province. In this part of the northern Cordillera, extensive mid-Cretaceous postcollisional plutonism took place following the accretion of exotic terranes to the continental margin. The most cratonward of the resulting plutonic belts comprises small isolated intrusive centers, with compositionally diverse, dominantly potassic rocks, as exemplified at Scheelite Dome, located in central Yukon. Similar to other spatially and temporally related intrusive centers, the Scheelite Dome intrusions are genetically associated with intrusion-related gold deposits. Intrusions have exceptional variability, ranging from volumetrically dominant clinopyroxene-bearing monzogranites, to calc-alkaline minettes and spessartites, with an intervening range of intermediate to felsic stocks and dikes, including leucominettes, quartz monzonites, quartz monzodiorites, and granodiorites. All rock types are potassic, are strongly enriched in LILEs and LREEs, and feature high LILE/HFSE ratios. Clinopyroxene is common to all rock types and ranges from salite in felsic rocks to high Mg augite and Cr-rich diopside in lamprophyres. Less common, calcic amphibole ranges from actinolitic hornblende to pargasite. The rocks have strongly radiogenic Sr (initial 87Sr/86Sr from 0.711-0.714) and Pb isotope ratios (206Pb/204Pb from 19.2-19.7), and negative initial εNd values (-8.06 to -11.26). Whole-rock major and trace element, radiogenic isotope, and mineralogical data suggest that the felsic to intermediate rocks were derived from mafic potassic magmas sourced from the lithospheric mantle via fractional crystallization and minor assimilation of metasedimentary crust. Mainly unmodified minettes and spessartites represent the most primitive and final phases emplaced. Metasomatic enrichments in the underlying lithospheric mantle

  15. Recommendation System for Adaptive Learning.

    Science.gov (United States)

    Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

    2018-01-01

    An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.

  16. BLACK HOLE ATTACK IN AODV & FRIEND FEATURES UNIQUE EXTRACTION TO DESIGN DETECTION ENGINE FOR INTRUSION DETECTION SYSTEM IN MOBILE ADHOC NETWORK

    Directory of Open Access Journals (Sweden)

    HUSAIN SHAHNAWAZ

    2012-10-01

    Full Text Available Ad-hoc network is a collection of nodes that are capable to form dynamically a temporary network without the support of any centralized fixed infrastructure. Since there is no central controller to determine the reliable & secure communication paths in Mobile Adhoc Network, each node in the ad hoc network has to rely on each other in order to forward packets, thus highly cooperative nodes are required to ensure that the initiated data transmission process does not fail. In a mobile ad hoc network (MANET where security is a crucial issue and they are forced to rely on the neighbor node, trust plays an important role that could improve the number of successful data transmission. Larger the number of trusted nodes, higher successful data communication process rates could be expected. In this paper, Black Hole attack is applied in the network, statistics are collected to design intrusion detection engine for MANET Intrusion Detection System (IDS. Feature extraction and rule inductions are applied to find out the accuracy of detection engine by using support vector machine. In this paper True Positive generated by the detection engine is very high and this is a novel approach in the area of Mobile Adhoc Intrusion detection system.

  17. Improved Information Retrieval Performance on SQL Database Using Data Adapter

    Science.gov (United States)

    Husni, M.; Djanali, S.; Ciptaningtyas, H. T.; Wicaksana, I. G. N. A.

    2018-02-01

    The NoSQL databases, short for Not Only SQL, are increasingly being used as the number of big data applications increases. Most systems still use relational databases (RDBs), but as the number of data increases each year, the system handles big data with NoSQL databases to analyze and access data more quickly. NoSQL emerged as a result of the exponential growth of the internet and the development of web applications. The query syntax in the NoSQL database differs from the SQL database, therefore requiring code changes in the application. Data adapter allow applications to not change their SQL query syntax. Data adapters provide methods that can synchronize SQL databases with NotSQL databases. In addition, the data adapter provides an interface which is application can access to run SQL queries. Hence, this research applied data adapter system to synchronize data between MySQL database and Apache HBase using direct access query approach, where system allows application to accept query while synchronization process in progress. From the test performed using data adapter, the results obtained that the data adapter can synchronize between SQL databases, MySQL, and NoSQL database, Apache HBase. This system spends the percentage of memory resources in the range of 40% to 60%, and the percentage of processor moving from 10% to 90%. In addition, from this system also obtained the performance of database NoSQL better than SQL database.

  18. Water System Adaptation To Hydrological Changes: Module 7, Adaptation Principles and Considerations

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  19. Ant colony induced decision trees for intrusion detection

    CSIR Research Space (South Africa)

    Botes, FH

    2017-06-01

    Full Text Available platform. Intrusion Detection Systems (IDS) analyse network traffic to identify suspicious patterns with the intention to compromise the system. Practitioners train classifiers to classify the data within different categories e.g. malicious or normal...

  20. A web-based non-intrusive ambient system to measure and classify activities of daily living.

    Science.gov (United States)

    Stucki, Reto A; Urwyler, Prabitha; Rampa, Luca; Müri, René; Mosimann, Urs P; Nef, Tobias

    2014-07-21

    The number of older adults in the global population is increasing. This demographic shift leads to an increasing prevalence of age-associated disorders, such as Alzheimer's disease and other types of dementia. With the progression of the disease, the risk for institutional care increases, which contrasts with the desire of most patients to stay in their home environment. Despite doctors' and caregivers' awareness of the patient's cognitive status, they are often uncertain about its consequences on activities of daily living (ADL). To provide effective care, they need to know how patients cope with ADL, in particular, the estimation of risks associated with the cognitive decline. The occurrence, performance, and duration of different ADL are important indicators of functional ability. The patient's ability to cope with these activities is traditionally assessed with questionnaires, which has disadvantages (eg, lack of reliability and sensitivity). Several groups have proposed sensor-based systems to recognize and quantify these activities in the patient's home. Combined with Web technology, these systems can inform caregivers about their patients in real-time (e.g., via smartphone). We hypothesize that a non-intrusive system, which does not use body-mounted sensors, video-based imaging, and microphone recordings would be better suited for use in dementia patients. Since it does not require patient's attention and compliance, such a system might be well accepted by patients. We present a passive, Web-based, non-intrusive, assistive technology system that recognizes and classifies ADL. The components of this novel assistive technology system were wireless sensors distributed in every room of the participant's home and a central computer unit (CCU). The environmental data were acquired for 20 days (per participant) and then stored and processed on the CCU. In consultation with medical experts, eight ADL were classified. In this study, 10 healthy participants (6 women

  1. Adapting bioinformatics curricula for big data.

    Science.gov (United States)

    Greene, Anna C; Giffin, Kristine A; Greene, Casey S; Moore, Jason H

    2016-01-01

    Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. © The Author 2015. Published by Oxford University Press.

  2. Adapting bioinformatics curricula for big data

    Science.gov (United States)

    Greene, Anna C.; Giffin, Kristine A.; Greene, Casey S.

    2016-01-01

    Modern technologies are capable of generating enormous amounts of data that measure complex biological systems. Computational biologists and bioinformatics scientists are increasingly being asked to use these data to reveal key systems-level properties. We review the extent to which curricula are changing in the era of big data. We identify key competencies that scientists dealing with big data are expected to possess across fields, and we use this information to propose courses to meet these growing needs. While bioinformatics programs have traditionally trained students in data-intensive science, we identify areas of particular biological, computational and statistical emphasis important for this era that can be incorporated into existing curricula. For each area, we propose a course structured around these topics, which can be adapted in whole or in parts into existing curricula. In summary, specific challenges associated with big data provide an important opportunity to update existing curricula, but we do not foresee a wholesale redesign of bioinformatics training programs. PMID:25829469

  3. Basic Study on Data-Centric design information integration system framework development for adapting Nuclear Power Plant construction in Korea

    Energy Technology Data Exchange (ETDEWEB)

    Lim, Byung Ki [KHNP, Gyeongju (Korea, Republic of)

    2016-05-15

    This study established the concept of data-centric design, which is the latest design technique, by analyzing the existing literature so that the data-centric design would be applied to the nuclear power plant projects in Korea and analyzed the status of data-centric design application by the advanced companies and the domestic design companies participating in the nuclear power plant projects. By analyzing the function of the 3D CAD commercial system and all design drawings used in the nuclear power plant projects in Korea, a data-centric design integrated system model has been developed. This study established the concept of data-centric design technology, analyzed the functions of the plant architect engineering (A/E) software being globally used in the plant field and the design process status of nuclear power plant projects in Korea. A design information integration system building model, which is capable of data-centric design, in the place of the existing document-centric system design such as P and ID and SLD, has been suggested through the investigation on the data-centric design cases of the advanced companies. The major functions of the suggested model required for the application to the domestic industry were drawn. The suggested framework builds the field design, which was performed in the 3D system of the constructor, as an owner's field design system, which can manage all design drawings generated from the field design and the related information in integrated way. An as-built full model integrated of plant architect engineering, supplier design and field design is built. It is handed over to the operation team at the O and M stage and utilized in the maintenance and repair. As a power plant full model of future construction project has been enabled, an improved design process has been suggested, in which only the design change information during the plant architect engineering (A/E) and the design change information during the field design

  4. A Survey on Cross-Layer Intrusion Detection System for Wireless ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... excessive packet collision, artificially increases contention, decrease signal .... Intelligent security architecture was conducted by [36], as an intrusion ... the main disadvantages of this scheme is: The IDS node is static (runs ...

  5. Electrical Resistivity Imaging of Seawater Intrusion into the Monterey Bay Aquifer System.

    Science.gov (United States)

    Pidlisecky, A; Moran, T; Hansen, B; Knight, R

    2016-03-01

    We use electrical resistivity tomography to obtain a 6.8-km electrical resistivity image to a depth of approximately 150 m.b.s.l. along the coast of Monterey Bay. The resulting image is used to determine the subsurface distribution of saltwater- and freshwater-saturated sediments and the geologic controls on fluid distributions in the region. Data acquisition took place over two field seasons in 2011 and 2012. To maximize our ability to image both vertical and horizontal variations in the subsurface, a combination of dipole-dipole, Wenner, Wenner-gamma, and gradient measurements were made, resulting in a large final dataset of approximately 139,000 data points. The resulting resistivity section extends to a depth of 150 m.b.s.l., and is used, in conjunction with the gamma logs from four coastal monitoring wells to identify four dominant lithologic units. From these data, we are able to infer the existence of a contiguous clay layer in the southern portion of our transect, which prevents downward migration of the saltwater observed in the upper 25 m of the subsurface to the underlying freshwater aquifer. The saltwater and brackish water in the northern portion of the transect introduce the potential for seawater intrusion into the hydraulically connected freshwater aquifer to the south, not just from the ocean, but also laterally from north to south. © 2015, National Ground Water Association.

  6. Generic adaptation framework for unifying adaptive web-based systems

    NARCIS (Netherlands)

    Knutov, E.

    2012-01-01

    The Generic Adaptation Framework (GAF) research project first and foremost creates a common formal framework for describing current and future adaptive hypermedia (AHS) and adaptive webbased systems in general. It provides a commonly agreed upon taxonomy and a reference model that encompasses the

  7. Uniqueness for cross-diffusion systems issuing from seawater intrusion problems

    Directory of Open Access Journals (Sweden)

    Catherine Choquet

    2017-10-01

    Full Text Available We consider a model mixing sharp and diffuse interface approaches for seawater intrusion phenomenons in confined and unconfined aquifers. More precisely, a phase field model is introduced in the boundary conditions on the virtual sharp interfaces. We thus include in the model the existence of diffuse transition zones but we preserve the simplified structure allowing front tracking. The three-dimensional problem then reduces to a two-dimensional model involving a strongly coupled system of partial differential equations of parabolic and elliptic type describing the evolution of the depth of the interface between salt- and freshwater and the evolution of the freshwater hydraulic head. Assuming a low hydraulic conductivity inside the aquifer, we prove the uniqueness of a weak solution for the model completed with initial and boundary conditions. Thanks to a generalization of a Meyer's regularity result, we establish that the gradient of the solution belongs to the space $L^r$, r>2. This additional regularity combined with the Gagliardo-Nirenberg inequality for r=4 allows to handle the nonlinearity of the system in the proof of uniqueness.

  8. Adaptive, dynamic, and resilient systems

    CERN Document Server

    Suri, Niranjan

    2015-01-01

    As the complexity of today's networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas.The book presents the insights of a different group of international experts in each chapter. Reporting on r

  9. Seawater intrusion mapping using electrical resistivity tomography and hydrochemical data. An application in the coastal area of eastern Thermaikos Gulf, Greece

    International Nuclear Information System (INIS)

    Kazakis, N.; Pavlou, A.; Vargemezis, G.; Voudouris, K.S.; Soulios, G.; Pliakas, F.; Tsokas, G.

    2016-01-01

    The aim of this study was to determine the extent and geometrical characteristics of seawater intrusion in the coastal aquifer of the eastern Thermaikos Gulf, Greece. Hydrochemical data and geoelectrical measurements were combined and supplemented to determine the hydrochemical regime of the study site in regard to seawater phenomena. Chemical analysis of groundwater was performed in 126 boreholes and fifteen electrical resistivity tomographies (ERT) were measured, whereas in two sites the ERT measurements were repeated following the wet season. The Cl"− concentrations recorded reached 2240 mg/L indicating seawater intrusion which was also verified by ionic ratios. The ionic ratios were overlapped and a seawater intrusion map (SWIM) was produced. A significant part of the coastal aquifer (up to 150 km"2) is influenced by seawater intrusion. The areas with the most intensive salinization are located between Nea Kallikratia–Epanomi and Aggelochori–Peraia. According to the ERTs, in the influenced areas the salinization of the aquifer exceeds 1 km toward the mainland and its depth reaches 200 m. In the area surrounding Thessaloniki airport, the ERTs revealed salinization of the upper aquifer to depths of up to 40 m, whereas the lower aquifer is uninfluenced. This abnormal distribution of seawater intrusion demonstrates the value of geoelectrical methods in the study of seawater intrusion especially in areas with limited available hydrochemical data. - Highlights: • ERTs determined the geometrical characteristics of the saline aquifer. • An abnormal distribution of seawater intrusion was recorded. • Four ionic ratios overlapped and a seawater intrusion map was produced. • Cl"− concentrations increased significantly from 2005 to 2010 by up to 1800 mg/L.

  10. Seawater intrusion mapping using electrical resistivity tomography and hydrochemical data. An application in the coastal area of eastern Thermaikos Gulf, Greece

    Energy Technology Data Exchange (ETDEWEB)

    Kazakis, N., E-mail: kazanera@yahoo.com [Aristotle University of Thessaloniki, Department of Geology, Lab. of Engineering Geology & Hydrogeology, 54124 Thessaloniki (Greece); Pavlou, A. [Aristotle University of Thessaloniki, Department of Geology, Lab. of Engineering Geology & Hydrogeology, 54124 Thessaloniki (Greece); Vargemezis, G. [Aristotle University of Thessaloniki, Department of Geology, Lab. of Applied Geophysics, 54124 Thessaloniki (Greece); Voudouris, K.S.; Soulios, G. [Aristotle University of Thessaloniki, Department of Geology, Lab. of Engineering Geology & Hydrogeology, 54124 Thessaloniki (Greece); Pliakas, F. [Democritus University of Thrace, Department of Civil Engineering, Xanthi 67100 (Greece); Tsokas, G. [Aristotle University of Thessaloniki, Department of Geology, Lab. of Applied Geophysics, 54124 Thessaloniki (Greece)

    2016-02-01

    The aim of this study was to determine the extent and geometrical characteristics of seawater intrusion in the coastal aquifer of the eastern Thermaikos Gulf, Greece. Hydrochemical data and geoelectrical measurements were combined and supplemented to determine the hydrochemical regime of the study site in regard to seawater phenomena. Chemical analysis of groundwater was performed in 126 boreholes and fifteen electrical resistivity tomographies (ERT) were measured, whereas in two sites the ERT measurements were repeated following the wet season. The Cl{sup −} concentrations recorded reached 2240 mg/L indicating seawater intrusion which was also verified by ionic ratios. The ionic ratios were overlapped and a seawater intrusion map (SWIM) was produced. A significant part of the coastal aquifer (up to 150 km{sup 2}) is influenced by seawater intrusion. The areas with the most intensive salinization are located between Nea Kallikratia–Epanomi and Aggelochori–Peraia. According to the ERTs, in the influenced areas the salinization of the aquifer exceeds 1 km toward the mainland and its depth reaches 200 m. In the area surrounding Thessaloniki airport, the ERTs revealed salinization of the upper aquifer to depths of up to 40 m, whereas the lower aquifer is uninfluenced. This abnormal distribution of seawater intrusion demonstrates the value of geoelectrical methods in the study of seawater intrusion especially in areas with limited available hydrochemical data. - Highlights: • ERTs determined the geometrical characteristics of the saline aquifer. • An abnormal distribution of seawater intrusion was recorded. • Four ionic ratios overlapped and a seawater intrusion map was produced. • Cl{sup −} concentrations increased significantly from 2005 to 2010 by up to 1800 mg/L.

  11. Seawater intrusion mapping using electrical resistivity tomography and hydrochemical data. An application in the coastal area of eastern Thermaikos Gulf, Greece.

    Science.gov (United States)

    Kazakis, N; Pavlou, A; Vargemezis, G; Voudouris, K S; Soulios, G; Pliakas, F; Tsokas, G

    2016-02-01

    The aim of this study was to determine the extent and geometrical characteristics of seawater intrusion in the coastal aquifer of the eastern Thermaikos Gulf, Greece. Hydrochemical data and geoelectrical measurements were combined and supplemented to determine the hydrochemical regime of the study site in regard to seawater phenomena. Chemical analysis of groundwater was performed in 126 boreholes and fifteen electrical resistivity tomographies (ERT) were measured, whereas in two sites the ERT measurements were repeated following the wet season. The Cl(-) concentrations recorded reached 2240 mg/L indicating seawater intrusion which was also verified by ionic ratios. The ionic ratios were overlapped and a seawater intrusion map (SWIM) was produced. A significant part of the coastal aquifer (up to 150 km(2)) is influenced by seawater intrusion. The areas with the most intensive salinization are located between Nea Kallikratia-Epanomi and Aggelochori-Peraia. According to the ERTs, in the influenced areas the salinization of the aquifer exceeds 1 km toward the mainland and its depth reaches 200 m. In the area surrounding Thessaloniki airport, the ERTs revealed salinization of the upper aquifer to depths of up to 40 m, whereas the lower aquifer is uninfluenced. This abnormal distribution of seawater intrusion demonstrates the value of geoelectrical methods in the study of seawater intrusion especially in areas with limited available hydrochemical data. Copyright © 2015 Elsevier B.V. All rights reserved.

  12. Fuzzy Based Advanced Hybrid Intrusion Detection System to Detect Malicious Nodes in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Rupinder Singh

    2017-01-01

    Full Text Available In this paper, an Advanced Hybrid Intrusion Detection System (AHIDS that automatically detects the WSNs attacks is proposed. AHIDS makes use of cluster-based architecture with enhanced LEACH protocol that intends to reduce the level of energy consumption by the sensor nodes. AHIDS uses anomaly detection and misuse detection based on fuzzy rule sets along with the Multilayer Perceptron Neural Network. The Feed Forward Neural Network along with the Backpropagation Neural Network are utilized to integrate the detection results and indicate the different types of attackers (i.e., Sybil attack, wormhole attack, and hello flood attack. For detection of Sybil attack, Advanced Sybil Attack Detection Algorithm is developed while the detection of wormhole attack is done by Wormhole Resistant Hybrid Technique. The detection of hello flood attack is done by using signal strength and distance. An experimental analysis is carried out in a set of nodes; 13.33% of the nodes are determined as misbehaving nodes, which classified attackers along with a detection rate of the true positive rate and false positive rate. Sybil attack is detected at a rate of 99,40%; hello flood attack has a detection rate of 98, 20%; and wormhole attack has a detection rate of 99, 20%.

  13. AdaBoost-based algorithm for network intrusion detection.

    Science.gov (United States)

    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.

  14. ImmuneDB: a system for the analysis and exploration of high-throughput adaptive immune receptor sequencing data.

    Science.gov (United States)

    Rosenfeld, Aaron M; Meng, Wenzhao; Luning Prak, Eline T; Hershberg, Uri

    2017-01-15

    As high-throughput sequencing of B cells becomes more common, the need for tools to analyze the large quantity of data also increases. This article introduces ImmuneDB, a system for analyzing vast amounts of heavy chain variable region sequences and exploring the resulting data. It can take as input raw FASTA/FASTQ data, identify genes, determine clones, construct lineages, as well as provide information such as selection pressure and mutation analysis. It uses an industry leading database, MySQL, to provide fast analysis and avoid the complexities of using error prone flat-files. ImmuneDB is freely available at http://immunedb.comA demo of the ImmuneDB web interface is available at: http://immunedb.com/demo CONTACT: Uh25@drexel.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  15. Water System Adaptation To Hydrological Changes: Module 12, Models and Tools for Stormwater and Wastewater System Adaptation

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  16. Water System Adaptation To Hydrological Changes: Module 14, Life Cycle Analysis (LCA) and Prioritization Tools in Water System Adaptation

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  17. Cross-bandwidth adaptation for ASR systems

    CSIR Research Space (South Africa)

    Kleynhans, N

    2013-12-01

    Full Text Available not be feasible for resource-scarce environments. Utilising limited amounts of in-domain data and a combination of feature normalisation and acoustic model adaptation techniques has therefore found wide use in ASR systems. Various approaches have been proposed...

  18. Zero Trust Intrusion Containment for Telemedicine

    National Research Council Canada - National Science Library

    Sood, Arun

    2002-01-01

    .... Our objective is the design and analysis of 'zero-trust' Intrusion Tolerant Systems. These are systems built under the extreme assumption that all intrusion detection techniques will eventually fail...

  19. Financial markets as adaptive systems

    Science.gov (United States)

    Potters, M.; Cont, R.; Bouchaud, J.-P.

    1998-02-01

    We show, by studying in detail the market prices of options on liquid markets, that the market has empirically corrected the simple, but inadequate Black-Scholes formula to account for two important statistical features of asset fluctuations: "fat tails" and correlations in the scale of fluctuations. These aspects, although not included in the pricing models, are very precisely reflected in the price fixed by the market as a whole. Financial markets thus behave as rather efficient adaptive systems.

  20. Computerized adaptive testing item selection in computerized adaptive learning systems

    NARCIS (Netherlands)

    Eggen, Theodorus Johannes Hendrikus Maria; Eggen, T.J.H.M.; Veldkamp, B.P.

    2012-01-01

    Item selection methods traditionally developed for computerized adaptive testing (CAT) are explored for their usefulness in item-based computerized adaptive learning (CAL) systems. While in CAT Fisher information-based selection is optimal, for recovering learning populations in CAL systems item

  1. Certification Considerations for Adaptive Systems

    Science.gov (United States)

    Bhattacharyya, Siddhartha; Cofer, Darren; Musliner, David J.; Mueller, Joseph; Engstrom, Eric

    2015-01-01

    Advanced capabilities planned for the next generation of aircraft, including those that will operate within the Next Generation Air Transportation System (NextGen), will necessarily include complex new algorithms and non-traditional software elements. These aircraft will likely incorporate adaptive control algorithms that will provide enhanced safety, autonomy, and robustness during adverse conditions. Unmanned aircraft will operate alongside manned aircraft in the National Airspace (NAS), with intelligent software performing the high-level decision-making functions normally performed by human pilots. Even human-piloted aircraft will necessarily include more autonomy. However, there are serious barriers to the deployment of new capabilities, especially for those based upon software including adaptive control (AC) and artificial intelligence (AI) algorithms. Current civil aviation certification processes are based on the idea that the correct behavior of a system must be completely specified and verified prior to operation. This report by Rockwell Collins and SIFT documents our comprehensive study of the state of the art in intelligent and adaptive algorithms for the civil aviation domain, categorizing the approaches used and identifying gaps and challenges associated with certification of each approach.

  2. A synthetic study on constaining a 2D density-dependent saltwater intrusion model using electrical imaging data

    DEFF Research Database (Denmark)

    Antonsson, Arni Valur; Nguyen, Frederic; Engesgaard, Peter Knudegaard

    of the synthetic model, basically a salinity distribution in the coastal aquifer, was converted to resistivity distribution by assuming a certain petrophysical relation between water salinity and electrical conductivity. The obtained resistivity distribution was then used when electrical data acquisition...... was simulated. By applying an advanced inversion approach, electrical images of resistivity were obtained and based on the assumed petrophysical model the salinity distribution was derived. A number of different intrusion simulations were conducted with the aim of assessing the applicability of the method under....... Compared to conventional methods, which only give (few) point information, electrical images can give data over large spatial distances but that can be of great value for groundwater modeling purposes. The aim of this study is to investigate in a synthetic way, the applicability of using electrical images...

  3. Resident Load Influence Analysis Method for Price Based on Non-intrusive Load Monitoring and Decomposition Data

    Science.gov (United States)

    Jiang, Wenqian; Zeng, Bo; Yang, Zhou; Li, Gang

    2018-01-01

    In the non-invasive load monitoring mode, the load decomposition can reflect the running state of each load, which will help the user reduce unnecessary energy costs. With the demand side management measures of time of using price, a resident load influence analysis method for time of using price (TOU) based on non-intrusive load monitoring data are proposed in the paper. Relying on the current signal of the resident load classification, the user equipment type, and different time series of self-elasticity and cross-elasticity of the situation could be obtained. Through the actual household load data test with the impact of TOU, part of the equipment will be transferred to the working hours, and users in the peak price of electricity has been reduced, and in the electricity at the time of the increase Electrical equipment, with a certain regularity.

  4. Unique Challenges in WiFi Intrusion Detection

    OpenAIRE

    Milliken, Jonny

    2014-01-01

    The Intrusion Detection System (IDS) is a common means of protecting networked systems from attack or malicious misuse. The deployment of an IDS can take many different forms dependent on protocols, usage and cost. This is particularly true of Wireless Intrusion Detection Systems (WIDS) which have many detection challenges associated with data transmission through an open, shared medium, facilitated by fundamental changes at the Physical and MAC layers. WIDS need to be considered in more deta...

  5. Statistical Inference for Data Adaptive Target Parameters.

    Science.gov (United States)

    Hubbard, Alan E; Kherad-Pajouh, Sara; van der Laan, Mark J

    2016-05-01

    Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples, and use this partitioning to define V splits in an estimation sample (one of the V subsamples) and corresponding complementary parameter-generating sample. For each of the V parameter-generating samples, we apply an algorithm that maps the sample to a statistical target parameter. We define our sample-split data adaptive statistical target parameter as the average of these V-sample specific target parameters. We present an estimator (and corresponding central limit theorem) of this type of data adaptive target parameter. This general methodology for generating data adaptive target parameters is demonstrated with a number of practical examples that highlight new opportunities for statistical learning from data. This new framework provides a rigorous statistical methodology for both exploratory and confirmatory analysis within the same data. Given that more research is becoming "data-driven", the theory developed within this paper provides a new impetus for a greater involvement of statistical inference into problems that are being increasingly addressed by clever, yet ad hoc pattern finding methods. To suggest such potential, and to verify the predictions of the theory, extensive simulation studies, along with a data analysis based on adaptively determined intervention rules are shown and give insight into how to structure such an approach. The results show that the data adaptive target parameter approach provides a general framework and resulting methodology for data-driven science.

  6. A Survey on Cross-Layer Intrusion Detection System for Wireless ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... forwarding, and open wireless medium are the factors that make ... Wireless Sensor Network (WSN) is a kind of network that ... These tiny sensors are mainly small sized and have low ..... they were integrated to WSN for intrusion detection in ..... Anomaly Detection Techniques for Smart City Wireless Sensor.

  7. 76 FR 5370 - Potential Addition of Vapor Intrusion Component to the Hazard Ranking System

    Science.gov (United States)

    2011-01-31

    ... Estimated Costs to Remediate Existing Sites Exceed Current Funding Levels, and More Sites are Expected to Be.... Methods for incorporating vapor intrusion into the HRS while, to the extent possible, maintaining the... will also be able to sign up for a mailing list that will be used to distribute logistical information...

  8. Anomaly based intrusion detection for a biometric identification system using neural networks

    CSIR Research Space (South Africa)

    Mgabile, T

    2012-10-01

    Full Text Available detection technique that analyses the fingerprint biometric network traffic for evidence of intrusion. The neural network algorithm that imitates the way a human brain works is used in this study to classify normal traffic and learn the correct traffic...

  9. Proposed Network Intrusion Detection System ‎In Cloud Environment Based on Back ‎Propagation Neural Network

    Directory of Open Access Journals (Sweden)

    Shawq Malik Mehibs

    2017-12-01

    Full Text Available Cloud computing is distributed architecture, providing computing facilities and storage resource as a service over the internet. This low-cost service fulfills the basic requirements of users. Because of the open nature and services introduced by cloud computing intruders impersonate legitimate users and misuse cloud resource and services. To detect intruders and suspicious activities in and around the cloud computing environment, intrusion detection system used to discover the illegitimate users and suspicious action by monitors different user activities on the network .this work proposed based back propagation artificial neural network to construct t network intrusion detection in the cloud environment. The proposed module evaluated with kdd99 dataset the experimental results shows promising approach to detect attack with high detection rate and low false alarm rate

  10. Self-adaptive change detection in streaming data with non-stationary distribution

    KAUST Repository

    Zhang, Xiangliang

    2010-01-01

    Non-stationary distribution, in which the data distribution evolves over time, is a common issue in many application fields, e.g., intrusion detection and grid computing. Detecting the changes in massive streaming data with a non-stationary distribution helps to alarm the anomalies, to clean the noises, and to report the new patterns. In this paper, we employ a novel approach for detecting changes in streaming data with the purpose of improving the quality of modeling the data streams. Through observing the outliers, this approach of change detection uses a weighted standard deviation to monitor the evolution of the distribution of data streams. A cumulative statistical test, Page-Hinkley, is employed to collect the evidence of changes in distribution. The parameter used for reporting the changes is self-adaptively adjusted according to the distribution of data streams, rather than set by a fixed empirical value. The self-adaptability of the novel approach enhances the effectiveness of modeling data streams by timely catching the changes of distributions. We validated the approach on an online clustering framework with a benchmark KDDcup 1999 intrusion detection data set as well as with a real-world grid data set. The validation results demonstrate its better performance on achieving higher accuracy and lower percentage of outliers comparing to the other change detection approaches. © 2010 Springer-Verlag.

  11. Processing and Linguistics Properties of Adaptable Systems

    Directory of Open Access Journals (Sweden)

    Dumitru TODOROI

    2006-01-01

    Full Text Available Continuation and development of the research in Adaptable Programming Initialization [Tod-05.1,2,3] is presented. As continuation of [Tod-05.2,3] in this paper metalinguistic tools used in the process of introduction of new constructions (data, operations, instructions and controls are developed. The generalization schemes of evaluation of adaptable languages and systems are discussed. These results analogically with [Tod-05.2,3] are obtained by the team, composed from the researchers D. Todoroi [Tod-05.4], Z. Todoroi [ZTod-05], and D. Micusa [Mic-03]. Presented results will be included in the book [Tod-06].

  12. Towards Adaptive Spoken Dialog Systems

    CERN Document Server

    Schmitt, Alexander

    2013-01-01

    In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Spoken Dialog Systems (SDS). The presented stochastic methods allow a flexible, portable and  accurate use.  Beginning with the foundations of machine learning and pattern recognition, this monograph examines how frequently users show negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions. The authors make use of statistical methods based on acoustic, linguistic and contextual features to examine the relationship between the interaction flow and the occurrence of emotions using non-acted  recordings several thousand real users from commercial and non-commercial SDS. Additionally, the authors present novel statistical methods that spot problems within a dialog based on interaction patterns. The approaches enable future SDS to offer m...

  13. From Automatic to Adaptive Data Acquisition

    DEFF Research Database (Denmark)

    Chang, Marcus

    2009-01-01

    the exibility of sensornets and reduce the complexity for the domain scientist, we developed an AI-based controller to act as a proxy between the scientist and sensornet. This controller is driven by the scientist's requirements to the collected data, and uses adaptive sampling in order to reach these goals....

  14. Adaptive Behaviour Assessment System: Indigenous Australian Adaptation Model (ABAS: IAAM)

    Science.gov (United States)

    du Plessis, Santie

    2015-01-01

    The study objectives were to develop, trial and evaluate a cross-cultural adaptation of the Adaptive Behavior Assessment System-Second Edition Teacher Form (ABAS-II TF) ages 5-21 for use with Indigenous Australian students ages 5-14. This study introduced a multiphase mixed-method design with semi-structured and informal interviews, school…

  15. Stress reaction process-based hierarchical recognition algorithm for continuous intrusion events in optical fiber prewarning system

    Science.gov (United States)

    Qu, Hongquan; Yuan, Shijiao; Wang, Yanping; Yang, Dan

    2018-04-01

    To improve the recognition performance of optical fiber prewarning system (OFPS), this study proposed a hierarchical recognition algorithm (HRA). Compared with traditional methods, which employ only a complex algorithm that includes multiple extracted features and complex classifiers to increase the recognition rate with a considerable decrease in recognition speed, HRA takes advantage of the continuity of intrusion events, thereby creating a staged recognition flow inspired by stress reaction. HRA is expected to achieve high-level recognition accuracy with less time consumption. First, this work analyzed the continuity of intrusion events and then presented the algorithm based on the mechanism of stress reaction. Finally, it verified the time consumption through theoretical analysis and experiments, and the recognition accuracy was obtained through experiments. Experiment results show that the processing speed of HRA is 3.3 times faster than that of a traditional complicated algorithm and has a similar recognition rate of 98%. The study is of great significance to fast intrusion event recognition in OFPS.

  16. When Intrusion Detection Meets Blockchain Technology: A Review

    OpenAIRE

    Meng, Weizhi; Tischhauser, Elmar Wolfgang; Wang, Qingju; Wang, Yu; Han, Jinguang

    2018-01-01

    With the purpose of identifying cyber threats and possible incidents, intrusion detection systems (IDSs) are widely deployed in various computer networks. In order to enhance the detection capability of a single IDS, collaborative intrusion detection networks (or collaborative IDSs) have been developed, which allow IDS nodes to exchange data with each other. However, data and trust management still remain two challenges for current detection architectures, which may degrade the effectiveness ...

  17. Adaptive control of port-Hamiltonian systems

    NARCIS (Netherlands)

    Dirksz, D.A.; Scherpen, J.M.A.; Edelmayer, András

    2010-01-01

    In this paper an adaptive control scheme is presented for general port-Hamiltonian systems. Adaptive control is used to compensate for control errors that are caused by unknown or uncertain parameter values of a system. The adaptive control is also combined with canonical transformation theory for

  18. Data Requirements for Developing Adaptations to Climate Variability and Change

    International Nuclear Information System (INIS)

    Basher, Reid E.

    1999-01-01

    An extensive foundation of high quality data and information on the climate and on the biological, environmental and social systems affected by climate is required in order to understand the climate impact processes involved, to develop new adaptation practices, and to subsequently implement these practices. Experience of the impacts of current and past variability of climate and sea level is a prime source of information. Many practices are in use to reduce climate impacts, for example in engineering design, agricultural risk management and climate prediction services, though their roles as adaptations to climate change are not widely appreciated. While there are good data sets on some factors and in some regions, in many cases the databases are inadequate and there are few data sets on adaptation-specific quantities such as vulnerability, resilience and adaptation effectiveness. Current international action under the United Nations Framework Convention on Climate Change (UNFCCC) pays little attention to adaptation and its information requirements. Furthermore there are trends toward reduced data gathering and to restrictions on access to data sets, especially arising from cost and commercialisation pressures. To effectively respond to the changes in climate that are now inevitable, governments will need to more clearly identify adaptation as a central feature of climate change policy and make a renewed shared commitment to collecting and freely exchanging the necessary data. 12 refs

  19. Multi-rate cubature Kalman filter based data fusion method with residual compensation to adapt to sampling rate discrepancy in attitude measurement system.

    Science.gov (United States)

    Guo, Xiaoting; Sun, Changku; Wang, Peng

    2017-08-01

    This paper investigates the multi-rate inertial and vision data fusion problem in nonlinear attitude measurement systems, where the sampling rate of the inertial sensor is much faster than that of the vision sensor. To fully exploit the high frequency inertial data and obtain favorable fusion results, a multi-rate CKF (Cubature Kalman Filter) algorithm with estimated residual compensation is proposed in order to adapt to the problem of sampling rate discrepancy. During inter-sampling of slow observation data, observation noise can be regarded as infinite. The Kalman gain is unknown and approaches zero. The residual is also unknown. Therefore, the filter estimated state cannot be compensated. To obtain compensation at these moments, state error and residual formulas are modified when compared with the observation data available moments. Self-propagation equation of the state error is established to propagate the quantity from the moments with observation to the moments without observation. Besides, a multiplicative adjustment factor is introduced as Kalman gain, which acts on the residual. Then the filter estimated state can be compensated even when there are no visual observation data. The proposed method is tested and verified in a practical setup. Compared with multi-rate CKF without residual compensation and single-rate CKF, a significant improvement is obtained on attitude measurement by using the proposed multi-rate CKF with inter-sampling residual compensation. The experiment results with superior precision and reliability show the effectiveness of the proposed method.

  20. Semantic models for adaptive interactive systems

    CERN Document Server

    Hussein, Tim; Lukosch, Stephan; Ziegler, Jürgen; Calvary, Gaëlle

    2013-01-01

    Providing insights into methodologies for designing adaptive systems based on semantic data, and introducing semantic models that can be used for building interactive systems, this book showcases many of the applications made possible by the use of semantic models.Ontologies may enhance the functional coverage of an interactive system as well as its visualization and interaction capabilities in various ways. Semantic models can also contribute to bridging gaps; for example, between user models, context-aware interfaces, and model-driven UI generation. There is considerable potential for using

  1. Adaptive SVM for Data Stream Classification

    Directory of Open Access Journals (Sweden)

    Isah A. Lawal

    2017-07-01

    Full Text Available In this paper, we address the problem of learning an adaptive classifier for the classification of continuous streams of data. We present a solution based on incremental extensions of the Support Vector Machine (SVM learning paradigm that updates an existing SVM whenever new training data are acquired. To ensure that the SVM effectiveness is guaranteed while exploiting the newly gathered data, we introduce an on-line model selection approach in the incremental learning process. We evaluated the proposed method on real world applications including on-line spam email filtering and human action classification from videos. Experimental results show the effectiveness and the potential of the proposed approach.

  2. The implementation of two stages clustering (k-means clustering and adaptive neuro fuzzy inference system) for prediction of medicine need based on medical data

    Science.gov (United States)

    Husein, A. M.; Harahap, M.; Aisyah, S.; Purba, W.; Muhazir, A.

    2018-03-01

    Medication planning aim to get types, amount of medicine according to needs, and avoid the emptiness medicine based on patterns of disease. In making the medicine planning is still rely on ability and leadership experience, this is due to take a long time, skill, difficult to obtain a definite disease data, need a good record keeping and reporting, and the dependence of the budget resulted in planning is not going well, and lead to frequent lack and excess of medicines. In this research, we propose Adaptive Neuro Fuzzy Inference System (ANFIS) method to predict medication needs in 2016 and 2017 based on medical data in 2015 and 2016 from two source of hospital. The framework of analysis using two approaches. The first phase is implementing ANFIS to a data source, while the second approach we keep using ANFIS, but after the process of clustering from K-Means algorithm, both approaches are calculated values of Root Mean Square Error (RMSE) for training and testing. From the testing result, the proposed method with better prediction rates based on the evaluation analysis of quantitative and qualitative compared with existing systems, however the implementation of K-Means Algorithm against ANFIS have an effect on the timing of the training process and provide a classification accuracy significantly better without clustering.

  3. Adjoint-state inversion of electric resistivity tomography data of seawater intrusion at the Argentona coastal aquifer (Spain)

    Science.gov (United States)

    Fernández-López, Sheila; Carrera, Jesús; Ledo, Juanjo; Queralt, Pilar; Luquot, Linda; Martínez, Laura; Bellmunt, Fabián

    2016-04-01

    Seawater intrusion in aquifers is a complex phenomenon that can be characterized with the help of electric resistivity tomography (ERT) because of the low resistivity of seawater, which underlies the freshwater floating on top. The problem is complex because of the need for joint inversion of electrical and hydraulic (density dependent flow) data. Here we present an adjoint-state algorithm to treat electrical data. This method is a common technique to obtain derivatives of an objective function, depending on potentials with respect to model parameters. The main advantages of it are its simplicity in stationary problems and the reduction of computational cost respect others methodologies. The relationship between the concentration of chlorides and the resistivity values of the field is well known. Also, these resistivities are related to the values of potentials measured using ERT. Taking this into account, it will be possible to define the different resistivities zones from the field data of potential distribution using the basis of inverse problem. In this case, the studied zone is situated in Argentona (Baix Maresme, Catalonia), where the values of chlorides obtained in some wells of the zone are too high. The adjoint-state method will be used to invert the measured data using a new finite element code in C ++ language developed in an open-source framework called Kratos. Finally, the information obtained numerically with our code will be checked with the information obtained with other codes.

  4. Intrusion Detection in Networked Control Systems: From System Knowledge to Network Security

    NARCIS (Netherlands)

    Caselli, M.

    2016-01-01

    “Networked control system‿ (NCS) is an umbrella term encompassing a broad variety of infrastructures such as industrial control systems (ICSs) and building automation systems (BASs). Nowadays, all these infrastructures play an important role in several aspects of our daily life, from managing

  5. Research on the technology of detecting the SQL injection attack and non-intrusive prevention in WEB system

    Science.gov (United States)

    Hu, Haibin

    2017-05-01

    Among numerous WEB security issues, SQL injection is the most notable and dangerous. In this study, characteristics and procedures of SQL injection are analyzed, and the method for detecting the SQL injection attack is illustrated. The defense resistance and remedy model of SQL injection attack is established from the perspective of non-intrusive SQL injection attack and defense. Moreover, the ability of resisting the SQL injection attack of the server has been comprehensively improved through the security strategies on operation system, IIS and database, etc.. Corresponding codes are realized. The method is well applied in the actual projects.

  6. Environment Adaptive Lighting Systems for Smart Homes

    Directory of Open Access Journals (Sweden)

    Cem Mehmet Catalbas

    2017-09-01

    Full Text Available In this work, an application of adaptive lighting system is proposed for smart homes. In this paper, it is suggested that, an intelligent lighting system with outdoor adaptation can be realized via a real fisheye image. During the implementation of the proposed method, the fuzzy c-means method, which is a commonly used data clustering method, has been used. The input image is divided into three different regions according to its brightness levels. Then, the RGB image is converted to CIE 1931 XYZ color space; and the obtained XYZ values are converted to x and y values. The parameters of x and y values are shown in CIE Chromaticity Diagram for different regions in the sky. Thereafter, the coordinate values are converted to Correlated Color Temperature by using two different formulas. Additionally, the conversion results are examined with respect to actual and estimated CCT values.

  7. Intrusion Detection in Networked Control Systems: From System Knowledge to Network Security

    OpenAIRE

    Caselli, M.

    2016-01-01

    “Networked control system‿ (NCS) is an umbrella term encompassing a broad variety of infrastructures such as industrial control systems (ICSs) and building automation systems (BASs). Nowadays, all these infrastructures play an important role in several aspects of our daily life, from managing essential services such as en- ergy and water (e.g., critical infrastructures) to monitoring the increasingly smart environments that surround us (e.g., the Internet of Things). Over the years, NCS techn...

  8. Non-intrusive accurate and traceable flow measurements in nuclear power plant systems

    Energy Technology Data Exchange (ETDEWEB)

    Gurevich, A.; Kanda, V.; Sharp, B.; Lopez, A. [Advanced Measurement and Analysis Group Inc., ON (Canada); Gurevich, Y. [Daystar Technologies Inc., ON (Canada)

    2014-07-01

    Ultrasonic cross correlation flow meters, are a non-intrusive flow measurement technology based on measurement of the transport velocity of turbulent structures, and have many advantages over other ultrasonic flow measurement methods. The cross correlation flow meter CROSSFLOW, produced and operated by the Canadian company Advanced Measurement and Analysis Group Inc., is used in nuclear power plants around the world, for various application. This paper describes the operating principals of the ultrasonic cross correlation flow meter, its advantages over other ultrasonic flow measurement methods, its application around the world. (author)

  9. Saltwater intrusion in the surficial aquifer system of the Big Cypress Basin, southwest Florida, and a proposed plan for improved salinity monitoring

    Science.gov (United States)

    Prinos, Scott T.

    2013-01-01

    The installation of drainage canals, poorly cased wells, and water-supply withdrawals have led to saltwater intrusion in the primary water-use aquifers in southwest Florida. Increasing population and water use have exacerbated this problem. Installation of water-control structures, well-plugging projects, and regulation of water use have slowed saltwater intrusion, but the chloride concentration of samples from some of the monitoring wells in this area indicates that saltwater intrusion continues to occur. In addition, rising sea level could increase the rate and extent of saltwater intrusion. The existing saltwater intrusion monitoring network was examined and found to lack the necessary organization, spatial distribution, and design to properly evaluate saltwater intrusion. The most recent hydrogeologic framework of southwest Florida indicates that some wells may be open to multiple aquifers or have an incorrect aquifer designation. Some of the sampling methods being used could result in poor-quality data. Some older wells are badly corroded, obstructed, or damaged and may not yield useable samples. Saltwater in some of the canals is in close proximity to coastal well fields. In some instances, saltwater occasionally occurs upstream from coastal salinity control structures. These factors lead to an incomplete understanding of the extent and threat of saltwater intrusion in southwest Florida. A proposed plan to improve the saltwater intrusion monitoring network in the South Florida Water Management District’s Big Cypress Basin describes improvements in (1) network management, (2) quality assurance, (3) documentation, (4) training, and (5) data accessibility. The plan describes improvements to hydrostratigraphic and geospatial network coverage that can be accomplished using additional monitoring, surface geophysical surveys, and borehole geophysical logging. Sampling methods and improvements to monitoring well design are described in detail. Geochemical analyses

  10. Adapt

    Science.gov (United States)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  11. Complex Environmental Data Modelling Using Adaptive General Regression Neural Networks

    Science.gov (United States)

    Kanevski, Mikhail

    2015-04-01

    The research deals with an adaptation and application of Adaptive General Regression Neural Networks (GRNN) to high dimensional environmental data. GRNN [1,2,3] are efficient modelling tools both for spatial and temporal data and are based on nonparametric kernel methods closely related to classical Nadaraya-Watson estimator. Adaptive GRNN, using anisotropic kernels, can be also applied for features selection tasks when working with high dimensional data [1,3]. In the present research Adaptive GRNN are used to study geospatial data predictability and relevant feature selection using both simulated and real data case studies. The original raw data were either three dimensional monthly precipitation data or monthly wind speeds embedded into 13 dimensional space constructed by geographical coordinates and geo-features calculated from digital elevation model. GRNN were applied in two different ways: 1) adaptive GRNN with the resulting list of features ordered according to their relevancy; and 2) adaptive GRNN applied to evaluate all possible models N [in case of wind fields N=(2^13 -1)=8191] and rank them according to the cross-validation error. In both cases training were carried out applying leave-one-out procedure. An important result of the study is that the set of the most relevant features depends on the month (strong seasonal effect) and year. The predictabilities of precipitation and wind field patterns, estimated using the cross-validation and testing errors of raw and shuffled data, were studied in detail. The results of both approaches were qualitatively and quantitatively compared. In conclusion, Adaptive GRNN with their ability to select features and efficient modelling of complex high dimensional data can be widely used in automatic/on-line mapping and as an integrated part of environmental decision support systems. 1. Kanevski M., Pozdnoukhov A., Timonin V. Machine Learning for Spatial Environmental Data. Theory, applications and software. EPFL Press

  12. FEATURES OF LOGISTIC SYSTEM ADAPTIVE MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Natalya VOZNENKO

    2015-08-01

    Full Text Available The study presents literature survey on enterprise logistic system adaptive management place and structure in the general enterprise management system. The theoretical basics of logistic system functioning, levels of its management and its effectiveness had been investigated. The role of adaptive management and its types had been scrutinized. The necessity of creating company’s adaptive regulator such as its economic mechanism had been proved.

  13. Enhancing Trust Management for Wireless Intrusion Detection via Traffic Sampling in the Era of Big Data

    DEFF Research Database (Denmark)

    Meng, Weizhi; Li, Wenjuan; Su, Chunhua

    2017-01-01

    Internet of Things (IoT) has been widely used in our daily life, which enables various objects to be interconnected for data exchange, including physical devices, vehicles, and other items embedded with network connectivity. Wireless sensor network (WSN) is a vital application of IoT, providing...

  14. Adaptive Analysis of Functional MRI Data

    International Nuclear Information System (INIS)

    Friman, Ola

    2003-01-01

    Functional Magnetic Resonance Imaging (fMRI) is a recently developed neuro-imaging technique with capacity to map neural activity with high spatial precision. To locate active brain areas, the method utilizes local blood oxygenation changes which are reflected as small intensity changes in a special type of MR images. The ability to non-invasively map brain functions provides new opportunities to unravel the mysteries and advance the understanding of the human brain, as well as to perform pre-surgical examinations in order to optimize surgical interventions. This dissertation introduces new approaches for the analysis of fMRI data. The detection of active brain areas is a challenging problem due to high noise levels and artifacts present in the data. A fundamental tool in the developed methods is Canonical Correlation Analysis (CCA). CCA is used in two novel ways. First as a method with the ability to fully exploit the spatio-temporal nature of fMRI data for detecting active brain areas. Established analysis approaches mainly focus on the temporal dimension of the data and they are for this reason commonly referred to as being mass-univariate. The new CCA detection method encompasses and generalizes the traditional mass-univariate methods and can in this terminology be viewed as a mass-multivariate approach. The concept of spatial basis functions is introduced as a spatial counterpart of the temporal basis functions already in use in fMRI analysis. The spatial basis functions implicitly perform an adaptive spatial filtering of the fMRI images, which significantly improves detection performance. It is also shown how prior information can be incorporated into the analysis by imposing constraints on the temporal and spatial models and a constrained version of CCA is devised to this end. A general Principal Component Analysis technique for generating and constraining temporal and spatial subspace models is proposed to be used in combination with the constrained CCA

  15. Modeling Power Systems as Complex Adaptive Systems

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

    2004-12-30

    Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

  16. Perimeter intrusion sensors

    International Nuclear Information System (INIS)

    Eaton, M.J.

    1977-01-01

    To obtain an effective perimeter intrusion detection system requires careful sensor selection, procurement, and installation. The selection process involves a thorough understanding of the unique site features and how these features affect the performance of each type of sensor. It is necessary to develop procurement specifications to establish acceptable sensor performance limits. Careful explanation and inspection of critical installation dimensions is required during on-site construction. The implementation of these activities at a particular site is discussed

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

    Science.gov (United States)

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

    2017-01-01

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

  18. Model-Free Adaptive Control Algorithm with Data Dropout Compensation

    Directory of Open Access Journals (Sweden)

    Xuhui Bu

    2012-01-01

    Full Text Available The convergence of model-free adaptive control (MFAC algorithm can be guaranteed when the system is subject to measurement data dropout. The system output convergent speed gets slower as dropout rate increases. This paper proposes a MFAC algorithm with data compensation. The missing data is first estimated using the dynamical linearization method, and then the estimated value is introduced to update control input. The convergence analysis of the proposed MFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that the proposed algorithm can compensate the effect of the data dropout, and the better output performance can be obtained.

  19. Water System Adaptation to Hydrological Changes: Module 10, Basic Principles of Incorporating Adaptation Science into Hydrologic Planning and Design

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  20. Visual Cues for an Adaptive Expert System.

    Science.gov (United States)

    Miller, Helen B.

    NCR (National Cash Register) Corporation is pursuing opportunities to make their point of sale (POS) terminals easy to use and easy to learn. To approach the goal of making the technology invisible to the user, NCR has developed an adaptive expert prototype system for a department store POS operation. The structure for the adaptive system, the…

  1. A fuzzy logic based network intrusion detection system for predicting the TCP SYN flooding attack

    CSIR Research Space (South Africa)

    Mkuzangwe, Nenekazi NP

    2017-04-01

    Full Text Available decision tree which is one of the well-known machine learning techniques. The results indicate that the performance difference, in terms of predicting the proportion of attacks in the data, of the proposed system with respect to the decision tree...

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

    Science.gov (United States)

    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.

  3. Intrusive trauma memory: A review and functional analysis

    NARCIS (Netherlands)

    Krans, J.; Näring, G.W.B.; Becker, E.S.; Holmes, E.A.

    2009-01-01

    Our contribution to this special issue focuses on the phenomenon of intrusive trauma memory. While intrusive trauma memories can undoubtedly cause impairment, we argue that they may exist for a potentially adaptive reason. Theory and experimental research on intrusion development are reviewed and

  4. Operator adaptation to changes in system reliability under adaptable automation.

    Science.gov (United States)

    Chavaillaz, Alain; Sauer, Juergen

    2017-09-01

    This experiment examined how operators coped with a change in system reliability between training and testing. Forty participants were trained for 3 h on a complex process control simulation modelling six levels of automation (LOA). In training, participants either experienced a high- (100%) or low-reliability system (50%). The impact of training experience on operator behaviour was examined during a 2.5 h testing session, in which participants either experienced a high- (100%) or low-reliability system (60%). The results showed that most operators did not often switch between LOA. Most chose an LOA that relieved them of most tasks but maintained their decision authority. Training experience did not have a strong impact on the outcome measures (e.g. performance, complacency). Low system reliability led to decreased performance and self-confidence. Furthermore, complacency was observed under high system reliability. Overall, the findings suggest benefits of adaptable automation because it accommodates different operator preferences for LOA. Practitioner Summary: The present research shows that operators can adapt to changes in system reliability between training and testing sessions. Furthermore, it provides evidence that each operator has his/her preferred automation level. Since this preference varies strongly between operators, adaptable automation seems to be suitable to accommodate these large differences.

  5. Dynamic and adaptive data-management in ATLAS

    CERN Document Server

    Lassnig, M; Branco, M; Molfetas, A

    2010-01-01

    Distributed data-management on the grid is subject to huge uncertainties yet static policies govern its usage. Due to the unpredictability of user behaviour, the high-latency and the heterogeneous nature of the environment, distributed data-management on the grid is challenging. In this paper we present the first steps towards a future dynamic data-management system that adapts to the changing conditions and environment. Such a system would eliminate the number of manual interventions and remove unnecessary software layers, thereby providing a higher quality of service to the collaboration.

  6. Adaptive partial volume classification of MRI data

    International Nuclear Information System (INIS)

    Chiverton, John P; Wells, Kevin

    2008-01-01

    Tomographic biomedical images are commonly affected by an imaging artefact known as the partial volume (PV) effect. The PV effect produces voxels composed of a mixture of tissues in anatomical magnetic resonance imaging (MRI) data resulting in a continuity of these tissue classes. Anatomical MRI data typically consist of a number of contiguous regions of tissues or even contiguous regions of PV voxels. Furthermore discontinuities exist between the boundaries of these contiguous image regions. The work presented here probabilistically models the PV effect using spatial regularization in the form of continuous Markov random fields (MRFs) to classify anatomical MRI brain data, simulated and real. A unique approach is used to adaptively control the amount of spatial regularization imposed by the MRF. Spatially derived image gradient magnitude is used to identify the discontinuities between image regions of contiguous tissue voxels and PV voxels, imposing variable amounts of regularization determined by simulation. Markov chain Monte Carlo (MCMC) is used to simulate the posterior distribution of the probabilistic image model. Promising quantitative results are presented for PV classification of simulated and real MRI data of the human brain.

  7. Self-Adaptive Systems for Machine Intelligence

    CERN Document Server

    He, Haibo

    2011-01-01

    This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide application

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

    Science.gov (United States)

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

    2016-10-13

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

  9. Adaptive Hypermedia Systems for E-Learning

    Directory of Open Access Journals (Sweden)

    Aammou Souhaib

    2010-11-01

    Full Text Available The domain of traditional hypermedia is revolutionized by the arrival of the concept of adaptation. Currently the domain of Adaptive Hypermedia Systems (AHS is constantly growing. A major goal of current research is to provide a personalized educational experience that meets the needs specific to each learner (knowledge level, goals, motivation etc.... In this article we have studied the possibility of implementing traditional features of adaptive hypermedia in an open environment, and discussed the standards for describing learning objects and architectural models based on the use of ontologies as a prerequisite for such an adaptation.

  10. Geochemical and isotopic data for restricting seawater intrusion and groundwater circulation in a series of typical volcanic islands in the South China Sea.

    Science.gov (United States)

    Zhang, Wenjie; Chen, Xi; Tan, Hongbing; Zhang, Yanfei; Cao, Jifu

    2015-04-15

    The decline of groundwater table and deterioration of water quality related to seawater have long been regarded as a crucial problem in coastal regions. In this work, a hydrogeologic investigation using combined hydrochemical and isotopic approaches was conducted in the coastal region of the South China Sea near the Leizhou peninsular to provide primary insight into seawater intrusion and groundwater circulation. Hydrochemical and isotopic data show that local groundwater is subjected to anthropogenic activities and geochemical processes, such as evaporation, water-rock interaction, and ion exchange. However, seawater intrusion driven by the over-exploitation of groundwater and insufficient recharge is the predominant factor controlling groundwater salinization. Systematic and homologic isotopic characteristics of most samples suggest that groundwater in volcanic area is locally recharged and likely caused by modern precipitation. However, very depleted stable isotopes and extremely low tritium of groundwater in some isolated aquifers imply a dominant role of palaeowater. Copyright © 2015 Elsevier Ltd. All rights reserved.

  11. Ground Motion Prediction Model Using Adaptive Neuro-Fuzzy Inference Systems: An Example Based on the NGA-West 2 Data

    Science.gov (United States)

    Ameur, Mourad; Derras, Boumédiène; Zendagui, Djawed

    2018-03-01

    Adaptive neuro-fuzzy inference systems (ANFIS) are used here to obtain the robust ground motion prediction model (GMPM). Avoiding a priori functional form, ANFIS provides fully data-driven predictive models. A large subset of the NGA-West2 database is used, including 2335 records from 580 sites and 137 earthquakes. Only shallow earthquakes and recordings corresponding to stations with measured V s30 properties are selected. Three basics input parameters are chosen: the moment magnitude ( Mw), the Joyner-Boore distance ( R JB) and V s30. ANFIS model output is the peak ground acceleration (PGA), peak ground velocity (PGV) and 5% damped pseudo-spectral acceleration (PSA) at periods from 0.01 to 4 s. A procedure similar to the random-effects approach is developed to provide between- and within-event standard deviations. The total standard deviation (SD) varies between [0.303 and 0.360] (log10 units) depending on the period. The ground motion predictions resulting from such simple three explanatory variables ANFIS models are shown to be comparable to the most recent NGA results (e.g., Boore et al., in Earthquake Spectra 30:1057-1085, 2014; Derras et al., in Earthquake Spectra 32:2027-2056, 2016). The main advantage of ANFIS compared to artificial neuronal network (ANN) is its simple and one-off topology: five layers. Our results exhibit a number of physically sound features: magnitude scaling of the distance dependency, near-fault saturation distance increasing with magnitude and amplification on soft soils. The ability to implement ANFIS model using an analytic equation and Excel is demonstrated.

  12. Adaptation in CRISPR-Cas Systems.

    Science.gov (United States)

    Sternberg, Samuel H; Richter, Hagen; Charpentier, Emmanuelle; Qimron, Udi

    2016-03-17

    Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) proteins constitute an adaptive immune system in prokaryotes. The system preserves memories of prior infections by integrating short segments of foreign DNA, termed spacers, into the CRISPR array in a process termed adaptation. During the past 3 years, significant progress has been made on the genetic requirements and molecular mechanisms of adaptation. Here we review these recent advances, with a focus on the experimental approaches that have been developed, the insights they generated, and a proposed mechanism for self- versus non-self-discrimination during the process of spacer selection. We further describe the regulation of adaptation and the protein players involved in this fascinating process that allows bacteria and archaea to harbor adaptive immunity. Copyright © 2016 Elsevier Inc. All rights reserved.

  13. Development and evaluation of a decision-supporting model for identifying the source location of microbial intrusions in real gravity sewer systems.

    Science.gov (United States)

    Kim, Minyoung; Choi, Christopher Y; Gerba, Charles P

    2013-09-01

    Assuming a scenario of a hypothetical pathogenic outbreak, we aimed this study at developing a decision-support model for identifying the location of the pathogenic intrusion as a means of facilitating rapid detection and efficient containment. The developed model was applied to a real sewer system (the Campbell wash basin in Tucson, AZ) in order to validate its feasibility. The basin under investigation was divided into 14 sub-basins. The geometric information associated with the sewer network was digitized using GIS (Geological Information System) and imported into an urban sewer network simulation model to generate microbial breakthrough curves at the outlet. A pre-defined amount of Escherichia coli (E. coli), which is an indicator of fecal coliform bacteria, was hypothetically introduced into 56 manholes (four in each sub-basin, chosen at random), and a total of 56 breakthrough curves of E. coli were generated using the simulation model at the outlet. Transport patterns were classified depending upon the location of the injection site (manhole), various known characteristics (peak concentration and time, pipe length, travel time, etc.) extracted from each E. coli breakthrough curve and the layout of sewer network. Using this information, we back-predicted the injection location once an E. coli intrusion was detected at a monitoring site using Artificial Neural Networks (ANNs). The results showed that ANNs identified the location of the injection sites with 57% accuracy; ANNs correctly recognized eight out of fourteen expressions with relying on data from a single detection sensor. Increasing the available sensors within the basin significantly improved the accuracy of the simulation results (from 57% to 100%). Copyright © 2013 Elsevier Ltd. All rights reserved.

  14. Adaptive feedback synchronization of Lue system

    International Nuclear Information System (INIS)

    Han, X.; Lu, J.-A.; Wu, X.

    2004-01-01

    This letter further improves and extends the works of Chen and Lue [Chaos, Solitons and Fractals 14 (2002) 643] and Wang et al. [Phys. Lett. A 312 (2003) 34]. In detail, the linear feedback synchronization and adaptive feedback synchronization for Lue system are discussed. And the lower bound of the feedback gain in linear feedback synchronization is presented. The adaptive feedback synchronization with only one controller is designed, which improves the proof in the work by Wang et al. The adaptive synchronization with two controllers for completely uncertain Lue system is also discussed, which extends the work of Chen and Lue. Also, numerical simulations show the effectiveness of these methods

  15. Orthodontic intrusion : Conventional and mini-implant assisted intrusion mechanics

    Directory of Open Access Journals (Sweden)

    Anup Belludi

    2012-01-01

    intrusion has revolutionized orthodontic anchorage and biomechanics by making anchorage perfectly stable. This article addresses various conventional clinical intrusion mechanics and especially intrusion using mini-implants that have proven effective over the years for intrusion of maxillary anteriors.

  16. Wireless Sensor Network Based Smart Grid Communications: Cyber Attacks, Intrusion Detection System and Topology Control

    Directory of Open Access Journals (Sweden)

    Lipi Chhaya

    2017-01-01

    Full Text Available The existing power grid is going through a massive transformation. Smart grid technology is a radical approach for improvisation in prevailing power grid. Integration of electrical and communication infrastructure is inevitable for the deployment of Smart grid network. Smart grid technology is characterized by full duplex communication, automatic metering infrastructure, renewable energy integration, distribution automation and complete monitoring and control of entire power grid. Wireless sensor networks (WSNs are small micro electrical mechanical systems that are deployed to collect and communicate the data from surroundings. WSNs can be used for monitoring and control of smart grid assets. Security of wireless sensor based communication network is a major concern for researchers and developers. The limited processing capabilities of wireless sensor networks make them more vulnerable to cyber-attacks. The countermeasures against cyber-attacks must be less complex with an ability to offer confidentiality, data readiness and integrity. The address oriented design and development approach for usual communication network requires a paradigm shift to design data oriented WSN architecture. WSN security is an inevitable part of smart grid cyber security. This paper is expected to serve as a comprehensive assessment and analysis of communication standards, cyber security issues and solutions for WSN based smart grid infrastructure.

  17. Data Systems vs. Information Systems

    OpenAIRE

    Amatayakul, Margret K.

    1982-01-01

    This paper examines the current status of “hospital information systems” with respect to the distinction between data systems and information systems. It is proposed that the systems currently existing are incomplete data dystems resulting in ineffective information systems.

  18. Petroleum Vapor Intrusion

    Science.gov (United States)

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

  19. Human intrusion: New ideas?

    International Nuclear Information System (INIS)

    Cooper, J.R.

    2002-01-01

    Inadvertent human intrusion has been an issue for the disposal of solid radioactive waste for many years. This paper discusses proposals for an approach for evaluating the radiological significance of human intrusion as put forward by ICRP with contribution from work at IAEA. The approach focuses on the consequences of the intrusion. Protective actions could, however, include steps to reduce the probability of human intrusion as well as the consequences. (author)

  20. Self-adaptive change detection in streaming data with non-stationary distribution

    KAUST Repository

    Zhang, Xiangliang; Wang, Wei

    2010-01-01

    Non-stationary distribution, in which the data distribution evolves over time, is a common issue in many application fields, e.g., intrusion detection and grid computing. Detecting the changes in massive streaming data with a non

  1. Adaptive, full-spectrum solar energy system

    Science.gov (United States)

    Muhs, Jeffrey D.; Earl, Dennis D.

    2003-08-05

    An adaptive full spectrum solar energy system having at least one hybrid solar concentrator, at least one hybrid luminaire, at least one hybrid photobioreactor, and a light distribution system operably connected to each hybrid solar concentrator, each hybrid luminaire, and each hybrid photobioreactor. A lighting control system operates each component.

  2. Adaptive Dialogue Systems for Assistive Living Environments

    Science.gov (United States)

    Papangelis, Alexandros

    2013-01-01

    Adaptive Dialogue Systems (ADS) are intelligent systems, able to interact with users via multiple modalities, such as speech, gestures, facial expressions and others. Such systems are able to make conversation with their users, usually on a specific, narrow topic. Assistive Living Environments are environments where the users are by definition not…

  3. DataFed: A Federated Data System for Visualization and Analysis of Spatio-Temporal Air Quality Data

    Science.gov (United States)

    Husar, R. B.; Hoijarvi, K.

    2017-12-01

    DataFed is a distributed web-services-based computing environment for accessing, processing, and visualizing atmospheric data in support of air quality science and management. The flexible, adaptive environment facilitates the access and flow of atmospheric data from provider to users by enabling the creation of user-driven data processing/visualization applications. DataFed `wrapper' components, non-intrusively wrap heterogeneous, distributed datasets for access by standards-based GIS web services. The mediator components (also web services) map the heterogeneous data into a spatio-temporal data model. Chained web services provide homogeneous data views (e.g., geospatial, time views) using a global multi-dimensional data model. In addition to data access and rendering, the data processing component services can be programmed for filtering, aggregation, and fusion of multidimensional data. A complete application software is written in a custom made data flow language. Currently, the federated data pool consists of over 50 datasets originating from globally distributed data providers delivering surface-based air quality measurements, satellite observations, emissions data as well as regional and global-scale air quality models. The web browser-based user interface allows point and click navigation and browsing the XYZT multi-dimensional data space. The key applications of DataFed are for exploring spatial pattern of pollutants, seasonal, weekly, diurnal cycles and frequency distributions for exploratory air quality research. Since 2008, DataFed has been used to support EPA in the implementation of the Exceptional Event Rule. The data system is also used at universities in the US, Europe and Asia.

  4. Intrusion scenarios in fusion waste disposal sites

    International Nuclear Information System (INIS)

    Zucchetti, M.; Zucchetti, M.; Rocco, P.

    1998-01-01

    Results of analyses on human intrusions into repositories of fusion radioactive waste are presented. The main topics are: duration of the institutional control, occurrence of intrusion, intrusion scenarios, acceptable risk limits and probabilistic data. Application to fusion waste repositories is implemented with a computational model: wells drilling is considered as the possible scenario. Doses and risks to intruder for different SEAFP-2 cases turn out to be very small. No intervention to reduce the hazard is necessary. (authors)

  5. Intrusion scenarios in fusion waste disposal sites

    Energy Technology Data Exchange (ETDEWEB)

    Zucchetti, M. [European Commission, JRC, Institute for Advanced Material, Ispra, Vatican City State, Holy See (Italy); Zucchetti, M.; Rocco, P. [Energetics Dept., Polytechnic of Turin (Italy)

    1998-07-01

    Results of analyses on human intrusions into repositories of fusion radioactive waste are presented. The main topics are: duration of the institutional control, occurrence of intrusion, intrusion scenarios, acceptable risk limits and probabilistic data. Application to fusion waste repositories is implemented with a computational model: wells drilling is considered as the possible scenario. Doses and risks to intruder for different SEAFP-2 cases turn out to be very small. No intervention to reduce the hazard is necessary. (authors)

  6. AANtID: an alternative approach to network intrusion detection ...

    African Journals Online (AJOL)

    Journal of Computer Science and Its Application ... Security has become not just a feature of an information system, but the core and a necessity especially the systems that communicate and transmit data over the Internet for they are more ... Keywords: Intrusion, Genetic Algorithm, detection, Security, DARPA dataset ...

  7. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2007-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  8. Complex and Adaptive Dynamical Systems A Primer

    CERN Document Server

    Gros, Claudius

    2011-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  9. Foundations for Survivable System Development: Service Traces, Intrusion Traces, and Evaluation Models

    National Research Council Canada - National Science Library

    Linger, Richard

    2001-01-01

    .... On the system side, survivability specifications can be defined by essential-service traces that map essential-service workflows, derived from user requirements, into system component dependencies...

  10. CONSTRUCTIVE MODEL OF ADAPTATION OF DATA STRUCTURES IN RAM. PART II. CONSTRUCTORS OF SCENARIOS AND ADAPTATION PROCESSES

    Directory of Open Access Journals (Sweden)

    V. I. Shynkarenko

    2016-04-01

    Full Text Available Purpose.The second part of the paper completes presentation of constructive and the productive structures (CPS, modeling adaptation of data structures in memory (RAM. The purpose of the second part in the research is to develop a model of process of adaptation data in a RAM functioning in different hardware and software environments and scenarios of data processing. Methodology. The methodology of mathematical and algorithmic constructionism was applied. In this part of the paper, changes were developed the constructors of scenarios and adaptation processes based on a generalized CPS through its transformational conversions. Constructors are interpreted, specialized CPS. Were highlighted the terminal alphabets of the constructor scenarios in the form of data processing algorithms and the constructor of adaptation – in the form of algorithmic components of the adaptation process. The methodology involves the development of substitution rules that determine the output process of the relevant structures. Findings. In the second part of the paper, system is represented by CPS modeling adaptation data placement in the RAM, namely, constructors of scenarios and of adaptation processes. The result of the implementation of constructor of scenarios is a set of data processing operations in the form of text in the language of programming C#, constructor of the adaptation processes – a process of adaptation, and the result the process of adaptation – the adapted binary code of processing data structures. Originality. For the first time proposed the constructive model of data processing – the scenario that takes into account the order and number of calls to the various elements of data structures and adaptation of data structures to the different hardware and software environments. At the same the placement of data in RAM and processing algorithms are adapted. Constructionism application in modeling allows to link data models and algorithms for

  11. Adaptive processes in economic systems

    CERN Document Server

    Murphy, Roy E

    1965-01-01

    In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;. methods for low-rank m

  12. Carbon dynamics in a Late Quaternary-age coastal limestone aquifer system undergoing saltwater intrusion.

    Science.gov (United States)

    Bryan, Eliza; Meredith, Karina T; Baker, Andy; Andersen, Martin S; Post, Vincent E A

    2017-12-31

    This study investigates the inorganic and organic aspects of the carbon cycle in groundwaters throughout the freshwater lens and transition zone of a carbonate island aquifer and identifies the transformation of carbon throughout the system. We determined 14 C and 13 C carbon isotope values for both DIC and DOC in groundwaters, and investigated the composition of DOC throughout the aquifer. In combination with hydrochemical and 3 H measurements, the chemical evolution of groundwaters was then traced from the unsaturated zone to the deeper saline zone. The data revealed three distinct water types: Fresh (F), Transition zone 1 (T1) and Transition zone 2 (T2) groundwaters. The 3 H values in F and T1 samples indicate that these groundwaters are mostly modern. 14 C DOC values are higher than 14 C DIC values and are well correlated with 3 H values. F and T1 groundwater geochemistry is dominated by carbonate mineral recrystallisation reactions that add dead carbon to the groundwater. T2 groundwaters are deeper, saline and characterised by an absence of 3 H, lower 14 C DOC values and a different DOC composition, namely a higher proportion of Humic Substances relative to total DOC. The T2 groundwaters are suggested to result from either the slow circulation of water within the seawater wedge, or from old remnant seawater caused by past sea level highstands. While further investigations are required to identify the origin of the T2 groundwaters, this study has identified their occurrence and shown that they did not evolve along the same pathway as fresh groundwaters. This study has also shown that a combined approach using 14 C and 13 C carbon isotope values for both DIC and DOC and the composition of DOC, as well as hydrochemical and 3 H measurements, can provide invaluable information regarding the transformation of carbon in a groundwater system and the evolution of fresh groundwater recharge. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Adaptive data management in the ARC Grid middleware

    International Nuclear Information System (INIS)

    Cameron, D; Karpenko, D; Konstantinov, A; Gholami, A

    2011-01-01

    The Advanced Resource Connector (ARC) Grid middleware was designed almost 10 years ago, and has proven to be an attractive distributed computing solution and successful in adapting to new data management and storage technologies. However, with an ever-increasing user base and scale of resources to manage, along with the introduction of more advanced data transfer protocols, some limitations in the current architecture have become apparent. The simple first-in first-out approach to data transfer leads to bottlenecks in the system, as does the built-in assumption that all data is immediately available from remote data storage. We present an entirely new data management architecture for ARC which aims to alleviate these problems, by introducing a three-layer structure. The top layer accepts incoming requests for data transfer and directs them to the middle layer, which schedules individual transfers and negotiates with various intermediate catalog and storage systems until the physical file is ready to be transferred. The lower layer performs all operations which use large amounts of bandwidth, i.e. the physical data transfer. Using such a layered structure allows more efficient use of the available bandwidth as well as enabling late-binding of jobs to data transfer slots based on a priority system. Here we describe in full detail the design and implementation of the new system.

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

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Dr. Li [University of Tennessee; Gasior, Wade C [ORNL; Dasireddy, Swetha [University of Tennessee

    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.

  15. Method and apparatus for distributed intrusion protection system for ultra high bandwidth networks

    Science.gov (United States)

    Goranson, Craig A.; Burnette, John R.; Greitzer, Frank L.; McMillan, Bryan H.

    2013-10-15

    A method for providing security to a network having a data stream with a plurality of portions of data, each having differing levels of sensitivity. The data stream is interrogated to determine the presence of predetermined characteristics associated with at least one of the portions of data within the data stream. At least one of the portions of data is then characterized, based upon the portion of data exhibiting a predetermined combination of characteristics, wherein the predetermined combination of characteristics is related to the sensitivity of the portion of data. The portions of the data stream are then distributed into a plurality of different channels, each of the channels associated with different level of sensitivity.

  16. The impact of river water intrusion on trace metal cycling in karst aquifers: an example from the Floridan aquifer system at Madison Blue Spring, Florida

    Science.gov (United States)

    Brown, A. L.; Martin, J. B.; Screaton, E.; Spellman, P.; Gulley, J.

    2011-12-01

    Springs located adjacent to rivers can serve as recharge points for aquifers when allogenic runoff increases river stage above the hydraulic head of the spring, forcing river water into the spring vent. Depending on relative compositions of the recharged water and groundwater, the recharged river water could be a source of dissolved trace metals to the aquifer, could mobilize solid phases such as metal oxide coatings, or both. Whether metals are mobilized or precipitated should depend on changes in redox and pH conditions as dissolved oxygen and organic carbon react following intrusion of the river water. To assess how river intrusion events affect metal cycling in springs, we monitored a small recharge event in April 2011 into Madison Blue Spring, which discharges to the Withlacoochee River in north-central Florida. Madison Blue Spring is the entrance to a phreatic cave system that includes over 7.8 km of surveyed conduits. During the event, river stage increased over base flow conditions for approximately 25 days by a maximum of 8%. Intrusion of the river water was monitored with conductivity, temperature and depth sensors that were installed within the cave system and adjacent wells. Decreased specific conductivity within the cave system occurred for approximately 20 days, reflecting the length of time that river water was present in the cave system. During this time, grab samples were collected seven times over a period of 34 days for measurements of major ion and trace metal concentrations at the spring vent and at Martz sink, a karst window connected to the conduit system approximately 150 meters from the spring vent. Relative fractions of surface water and groundwater were estimated based on Cl concentrations of the samples, assuming conservative two end-member mixing during the event. This mixing model indicates that maximum river water contribution to the groundwater system was approximately 20%. River water had concentrations of iron, manganese, and other

  17. Non-intrusive Methods for Mode Estimation in Power Systems using Synchrophasors

    NARCIS (Netherlands)

    Peri?, V.

    2016-01-01

    The power system industry has been going through dynamic infrastructural and operational changes in recent years that have caused more prominent lightly damped electromechanical oscillations. Real-time monitoring of electromechanical oscillations is of great significance for power system operators;

  18. Analytical scaling relations to evaluate leakage and intrusion in intermittent water supply systems

    Science.gov (United States)

    Slocum, Alexander H.; Whittle, Andrew J.

    2018-01-01

    Intermittent water supplies (IWS) deliver piped water to one billion people; this water is often microbially contaminated. Contaminants that accumulate while IWS are depressurized are flushed into customers’ homes when these systems become pressurized. In addition, during the steady-state phase of IWS, contaminants from higher-pressure sources (e.g., sewers) may continue to intrude where pipe pressure is low. To guide the operation and improvement of IWS, this paper proposes an analytic model relating supply pressure, supply duration, leakage, and the volume of intruded, potentially-contaminated, fluids present during flushing and steady-state. The proposed model suggests that increasing the supply duration may improve water quality during the flushing phase, but decrease the subsequent steady-state water quality. As such, regulators and academics should take more care in reporting if water quality samples are taken during flushing or steady-state operational conditions. Pipe leakage increases with increased supply pressure and/or duration. We propose using an equivalent orifice area (EOA) to quantify pipe quality. This provides a more stable metric for regulators and utilities tracking pipe repairs. Finally, we show that the volume of intruded fluid decreases in proportion to reductions in EOA. The proposed relationships are applied to self-reported performance indicators for IWS serving 108 million people described in the IBNET database and in the Benchmarking and Data Book of Water Utilities in India. This application shows that current high-pressure, continuous water supply targets will require extensive EOA reductions. For example, in order to achieve national targets, utilities in India will need to reduce their EOA by a median of at least 90%. PMID:29775462

  19. Analytical scaling relations to evaluate leakage and intrusion in intermittent water supply systems.

    Science.gov (United States)

    Taylor, David D J; Slocum, Alexander H; Whittle, Andrew J

    2018-01-01

    Intermittent water supplies (IWS) deliver piped water to one billion people; this water is often microbially contaminated. Contaminants that accumulate while IWS are depressurized are flushed into customers' homes when these systems become pressurized. In addition, during the steady-state phase of IWS, contaminants from higher-pressure sources (e.g., sewers) may continue to intrude where pipe pressure is low. To guide the operation and improvement of IWS, this paper proposes an analytic model relating supply pressure, supply duration, leakage, and the volume of intruded, potentially-contaminated, fluids present during flushing and steady-state. The proposed model suggests that increasing the supply duration may improve water quality during the flushing phase, but decrease the subsequent steady-state water quality. As such, regulators and academics should take more care in reporting if water quality samples are taken during flushing or steady-state operational conditions. Pipe leakage increases with increased supply pressure and/or duration. We propose using an equivalent orifice area (EOA) to quantify pipe quality. This provides a more stable metric for regulators and utilities tracking pipe repairs. Finally, we show that the volume of intruded fluid decreases in proportion to reductions in EOA. The proposed relationships are applied to self-reported performance indicators for IWS serving 108 million people described in the IBNET database and in the Benchmarking and Data Book of Water Utilities in India. This application shows that current high-pressure, continuous water supply targets will require extensive EOA reductions. For example, in order to achieve national targets, utilities in India will need to reduce their EOA by a median of at least 90%.

  20. Adaptive networks as second order governance systems

    NARCIS (Netherlands)

    S.G. Nooteboom (Sibout); P.K. Marks (Peter)

    2010-01-01

    textabstractWe connect the idea of 'levers for change' with 'governance capacity' and propose 'adaptive networks' as an ideal type embedded in, and leveraging change in, governance systems. Discourses connect practices of citizens and companies with that governance system. Aware of

  1. Using Data to Understand How to Better Design Adaptive Learning

    Science.gov (United States)

    Liu, Min; Kang, Jina; Zou, Wenting; Lee, Hyeyeon; Pan, Zilong; Corliss, Stephanie

    2017-01-01

    There is much enthusiasm in higher education about the benefits of adaptive learning and using big data to investigate learning processes to make data-informed educational decisions. The benefits of adaptive learning to achieve personalized learning are obvious. Yet, there lacks evidence-based research to understand how data such as user behavior…

  2. Adaptation of a software development methodology to the implementation of a large-scale data acquisition and control system. [for Deep Space Network

    Science.gov (United States)

    Madrid, G. A.; Westmoreland, P. T.

    1983-01-01

    A progress report is presented on a program to upgrade the existing NASA Deep Space Network in terms of a redesigned computer-controlled data acquisition system for channelling tracking, telemetry, and command data between a California-based control center and three signal processing centers in Australia, California, and Spain. The methodology for the improvements is oriented towards single subsystem development with consideration for a multi-system and multi-subsystem network of operational software. Details of the existing hardware configurations and data transmission links are provided. The program methodology includes data flow design, interface design and coordination, incremental capability availability, increased inter-subsystem developmental synthesis and testing, system and network level synthesis and testing, and system verification and validation. The software has been implemented thus far to a 65 percent completion level, and the methodology being used to effect the changes, which will permit enhanced tracking and communication with spacecraft, has been concluded to feature effective techniques.

  3. Potential effects of deepening the St. Johns River navigation channel on saltwater intrusion in the surficial aquifer system, Jacksonville, Florida

    Science.gov (United States)

    Bellino, Jason C.; Spechler, Rick M.

    2013-01-01

    The U.S. Army Corps of Engineers (USACE) has proposed dredging a 13-mile reach of the St. Johns River navigation channel in Jacksonville, Florida, deepening it to depths between 50 and 54 feet below North American Vertical Datum of 1988. The dredging operation will remove about 10 feet of sediments from the surficial aquifer system, including limestone in some locations. The limestone unit, which is in the lowermost part of the surficial aquifer system, supplies water to domestic wells in the Jacksonville area. Because of density-driven hydrodynamics of the St. Johns River, saline water from the Atlantic Ocean travels upstream as a saltwater “wedge” along the bottom of the channel, where the limestone is most likely to be exposed by the proposed dredging. A study was conducted to determine the potential effects of navigation channel deepening in the St. Johns River on salinity in the adjacent surficial aquifer system. Simulations were performed with each of four cross-sectional, variable-density groundwater-flow models, developed using SEAWAT, to simulate hypothetical changes in salinity in the surficial aquifer system as a result of dredging. The cross-sectional models were designed to incorporate a range of hydrogeologic conceptualizations to estimate the effect of uncertainty in hydrogeologic properties. The cross-sectional models developed in this study do not necessarily simulate actual projected conditions; instead, the models were used to examine the potential effects of deepening the navigation channel on saltwater intrusion in the surficial aquifer system under a range of plausible hypothetical conditions. Simulated results for modeled conditions indicate that dredging will have little to no effect on salinity variations in areas upstream of currently proposed dredging activities. Results also indicate little to no effect in any part of the surficial aquifer system along the cross section near River Mile 11 or in the water-table unit along the cross

  4. Adaptation in the auditory system: an overview

    Directory of Open Access Journals (Sweden)

    David ePérez-González

    2014-02-01

    Full Text Available The early stages of the auditory system need to preserve the timing information of sounds in order to extract the basic features of acoustic stimuli. At the same time, different processes of neuronal adaptation occur at several levels to further process the auditory information. For instance, auditory nerve fiber responses already experience adaptation of their firing rates, a type of response that can be found in many other auditory nuclei and may be useful for emphasizing the onset of the stimuli. However, it is at higher levels in the auditory hierarchy where more sophisticated types of neuronal processing take place. For example, stimulus-specific adaptation, where neurons show adaptation to frequent, repetitive stimuli, but maintain their responsiveness to stimuli with different physical characteristics, thus representing a distinct kind of processing that may play a role in change and deviance detection. In the auditory cortex, adaptation takes more elaborate forms, and contributes to the processing of complex sequences, auditory scene analysis and attention. Here we review the multiple types of adaptation that occur in the auditory system, which are part of the pool of resources that the neurons employ to process the auditory scene, and are critical to a proper understanding of the neuronal mechanisms that govern auditory perception.

  5. Managing adaptively for multifunctionality in agricultural systems

    Science.gov (United States)

    Hodbod, Jennifer; Barreteau, Olivier; Allen, Craig R.; Magda, Danièle

    2016-01-01

    The critical importance of agricultural systems for food security and as a dominant global landcover requires management that considers the full dimensions of system functions at appropriate scales, i.e. multifunctionality. We propose that adaptive management is the most suitable management approach for such goals, given its ability to reduce uncertainty over time and support multiple objectives within a system, for multiple actors. As such, adaptive management may be the most appropriate method for sustainably intensifying production whilst increasing the quantity and quality of ecosystem services. However, the current assessment of performance of agricultural systems doesn’t reward ecosystem service provision. Therefore, we present an overview of the ecosystem functions agricultural systems should and could provide, coupled with a revised definition for assessing the performance of agricultural systems from a multifunctional perspective that, when all satisfied, would create adaptive agricultural systems that can increase production whilst ensuring food security and the quantity and quality of ecosystem services. The outcome of this high level of performance is the capacity to respond to multiple shocks without collapse, equity and triple bottom line sustainability. Through the assessment of case studies, we find that alternatives to industrialized agricultural systems incorporate more functional goals, but that there are mixed findings as to whether these goals translate into positive measurable outcomes. We suggest that an adaptive management perspective would support the implementation of a systematic analysis of the social, ecological and economic trade-offs occurring within such systems, particularly between ecosystem services and functions, in order to provide suitable and comparable assessments. We also identify indicators to monitor performance at multiple scales in agricultural systems which can be used within an adaptive management framework to

  6. Managing adaptively for multifunctionality in agricultural systems.

    Science.gov (United States)

    Hodbod, Jennifer; Barreteau, Olivier; Allen, Craig; Magda, Danièle

    2016-12-01

    The critical importance of agricultural systems for food security and as a dominant global landcover requires management that considers the full dimensions of system functions at appropriate scales, i.e. multifunctionality. We propose that adaptive management is the most suitable management approach for such goals, given its ability to reduce uncertainty over time and support multiple objectives within a system, for multiple actors. As such, adaptive management may be the most appropriate method for sustainably intensifying production whilst increasing the quantity and quality of ecosystem services. However, the current assessment of performance of agricultural systems doesn't reward ecosystem service provision. Therefore, we present an overview of the ecosystem functions agricultural systems should and could provide, coupled with a revised definition for assessing the performance of agricultural systems from a multifunctional perspective that, when all satisfied, would create adaptive agricultural systems that can increase production whilst ensuring food security and the quantity and quality of ecosystem services. The outcome of this high level of performance is the capacity to respond to multiple shocks without collapse, equity and triple bottom line sustainability. Through the assessment of case studies, we find that alternatives to industrialized agricultural systems incorporate more functional goals, but that there are mixed findings as to whether these goals translate into positive measurable outcomes. We suggest that an adaptive management perspective would support the implementation of a systematic analysis of the social, ecological and economic trade-offs occurring within such systems, particularly between ecosystem services and functions, in order to provide suitable and comparable assessments. We also identify indicators to monitor performance at multiple scales in agricultural systems which can be used within an adaptive management framework to increase

  7. Computational identification of adaptive mutants using the VERT system

    Directory of Open Access Journals (Sweden)

    Winkler James

    2012-04-01

    Full Text Available Background Evolutionary dynamics of microbial organisms can now be visualized using the Visualizing Evolution in Real Time (VERT system, in which several isogenic strains expressing different fluorescent proteins compete during adaptive evolution and are tracked using fluorescent cell sorting to construct a population history over time. Mutations conferring enhanced growth rates can be detected by observing changes in the fluorescent population proportions. Results Using data obtained from several VERT experiments, we construct a hidden Markov-derived model to detect these adaptive events in VERT experiments without external intervention beyond initial training. Analysis of annotated data revealed that the model achieves consensus with human annotation for 85-93% of the data points when detecting adaptive events. A method to determine the optimal time point to isolate adaptive mutants is also introduced. Conclusions The developed model offers a new way to monitor adaptive evolution experiments without the need for external intervention, thereby simplifying adaptive evolution efforts relying on population tracking. Future efforts to construct a fully automated system to isolate adaptive mutants may find the algorithm a useful tool.

  8. Adaptive PI Controller for a Nonlinear System

    Directory of Open Access Journals (Sweden)

    D. Rathikarani

    2009-10-01

    Full Text Available Most of the industrial processes are inherently nonlinear in their behaviour. Designs of controllers for these nonlinear processes are difficult, as they do not follow superposition theorem. Adaptive controller can change its behaviour in response to changes in the dynamics of the process and disturbances. Hence adaptive controller can be used to control nonlinear processes. Direct Model Reference Adaptive Control is a technique, in which a reference model involving the desired performances is specified. In the present work, a DMRAC is designed and implemented to achieve satisfactory control of a nonlinear system in all its local linear operating regions. The closed loop system is made BIBO stable by proper control techniques. The controller is designed through simulation in Matlab platform and is validated in real time by conducting experiments on the laboratory Air Flow Control System using the dSPACE interface.

  9. Intrusion Prevention System Based on the Aççess Control Mechanism in the Operating System Miçrosoft Windows

    Directory of Open Access Journals (Sweden)

    V. S. Matveeva

    2012-03-01

    Full Text Available It is suggested to implement an intrusion prevention system based on the access control mechanism of Microsoft Windows operating system to restrict the execution of malicious code. Most of the existing computer security facilities use behavioral and heuristic analyses based on an undocumented method of system calls interception that is not an uniform approach in designing of proactive security mechanism. The IPS is portable among different versions of the OS because it is implemented with documented functions only, it does not need to be updated and uses less system resources in comparison with another protection systems. The system protects from zero-day malware and therefore prevents companies from online-banking fraud that is a very actual problem of information security nowadays.

  10. Real Time Adaptive Stream-oriented Geo-data Filtering

    Directory of Open Access Journals (Sweden)

    A. A. Golovkov

    2016-01-01

    Full Text Available The cutting-edge engineering maintenance software systems of various objects are aimed at processing of geo-location data coming from the employees’ mobile devices in real time. To reduce the amount of transmitted data such systems, usually, use various filtration methods of geo-coordinates recorded directly on mobile devices.The paper identifies the reasons for errors of geo-data coming from different sources, and proposes an adaptive dynamic method to filter geo-location data. Compared with the static method previously described in the literature [1] the approach offers to align adaptively the filtering threshold with changing characteristics of coordinates from many sources of geo-location data.To evaluate the efficiency of the developed filter method have been involved about 400 thousand points, representing motion paths of different type (on foot, by car and high-speed train and parking (indoors, outdoors, near high-rise buildings to take data from different mobile devices. Analysis of results has shown that the benefits of the proposed method are the more precise location of long parking (up to 6 hours and coordinates when user is in motion, the capability to provide steam-oriented filtering of data from different sources that allows to use the approach in geo-information systems, providing continuous monitoring of the location in streamoriented data processing in real time. The disadvantage is a little bit more computational complexity and increasing amount of points of the final track as compared to other filtration techniques.In general, the developed approach enables a significant quality improvement of displayed paths of moving mobile objects.

  11. Tree root intrusion in sewer systems: A review of extent and costs

    Science.gov (United States)

    T.B. Randrup; E.G. McPherson; L.R. Costello

    2001-01-01

    Interference between trees and sewer systems is likely to occur in old systems and in cracked pipes. Factors that contribute to damage include old pipes with joints, shallow pipes, small-dimension pipes, and fast-growing tree species. Because roots are reported to cause >50% of all sewer blockages, costs associated with root removal from sewers is substantial. In...

  12. Building an intrusion detection system using a filter-based feature selection algorithm

    NARCIS (Netherlands)

    Ambusaidi, Mohammed A.; He, Xiangjian; Nanda, Priyadarsi; Tan, Zhiyuan

    2016-01-01

    Redundant and irrelevant features in data have caused a long-term problem in network traffic classification. These features not only slow down the process of classification but also prevent a classifier from making accurate decisions, especially when coping with big data. In this paper, we propose a

  13. Adaptive control of solar energy collector systems

    CERN Document Server

    Lemos, João M; Igreja, José M

    2014-01-01

    This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants:they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time;their dynamics is nonlinear, with a bilinear structure;there is a significant level of uncertainty in plant knowledge.Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts

  14. Environmentally-adapted local energy systems

    Energy Technology Data Exchange (ETDEWEB)

    Moe, N; Oefverholm, E [NUTEK, Stockholm (Sweden); Andersson, Owe [EKAN Gruppen (Sweden); Froste, H [Swedish Environmental Protection Agency, Stockholm (Sweden)

    1997-10-01

    Energy companies, municipalities, property companies, firms of consultants, environmental groups and individuals are examples of players working locally to shape environmentally adapted energy systems. These players have needed information making them better able to make decisions on cost-efficient, environmentally-adapted energy systems. This book answers many of the questions they have put. The volume is mainly based on Swedish handbooks produced by the Swedish National Board for Industrial and Technical Development, NUTEK, together with the Swedish Environmental Protection Agency. These handbooks have been used in conjunction with municipal energy planning, local Agenda 21 work, to provide a basis for deciding on concrete local energy systems. The contents in brief: -The book throws new light on the concept of energy efficiency; -A section on the environment compares how air-polluting emissions vary with different methods of energy production; -A section contains more than 40 ideas for measures which can be profitable, reduce energy consumption and the impact on the environment all at the same time; -The book gives concrete examples of new, alternative and environmentally-adapted local energy systems. More efficient use of energy is included as a possible change of energy system; -The greatest emphasis is laid upon alternative energy systems for heating. It may be heating in a house, block of flats, office building or school; -Finally, there are examples of environmentally-adapted local energy planning.

  15. Geophysical characterization from Itu intrusive suite

    International Nuclear Information System (INIS)

    Pascholati, M.E.

    1989-01-01

    The integrated use of geophysical, geological, geochemical, petrographical and remote sensing data resulted in a substantial increase in the knowledge of the Itu Intrusive Suite. The main geophysical method was gamma-ray spectrometry together with fluorimetry and autoradiography. Three methods were used for calculation of laboratory gamma-ray spectrometry data. For U, the regression method was the best one. For K and Th, equations system and absolute calibration presented the best results. Surface gamma-ray spectrometry allowed comparison with laboratory data and permitted important contribution to the study of environmental radiation. (author)

  16. Secure Border Gateway Protocol and the External Routing Intrusion Detection System

    National Research Council Canada - National Science Library

    Kent, Stephen

    2000-01-01

    .... The Secure BGP projects designed a secure, scalable, deployable architecture (S-BGP) for an authorization and authentication system that addresses most of the security problems associated with BGP...

  17. Improving Air Force Active Network Defense Systems through an Analysis of Intrusion Detection Techniques

    National Research Council Canada - National Science Library

    Dunklee, David R

    2007-01-01

    .... The research then presents four recommendations to improve DCC operations. These include: Transition or improve the current signature-based IDS systems to include the capability to query and visualize network flows to detect malicious traffic...

  18. An innovative non-intrusive driver assistance system for vital signal monitoring.

    NARCIS (Netherlands)

    Sun, Y. & Yu, X.

    2016-01-01

    This paper describes an in-vehicle nonintrusive biopotential measurement system for driver health monitoring and fatigue detection. Previous research has found that the physiological signals including eye features, electrocardiography (ECG), electroencephalography (EEG) and their secondary

  19. Adaptive polymeric system for Hebbian type learning

    OpenAIRE

    2011-01-01

    Abstract We present the experimental realization of an adaptive polymeric system displaying a ?learning behaviour?. The system consists on a statistically organized networks of memristive elements (memory-resitors) based on polyaniline. In a such network the path followed by the current increments its conductivity, a property which makes the system able to mimic Hebbian type learning and have application in hardware neural networks. After discussing the working principle of ...

  20. Security engineering: systems engineering of security through the adaptation and application of risk management

    Science.gov (United States)

    Gilliam, David P.; Feather, Martin S.

    2004-01-01

    Information Technology (IT) Security Risk Management is a critical task in the organization, which must protect its resources and data against the loss of confidentiality, integrity, and availability. As systems become more complex and diverse, and more vulnerabilities are discovered while attacks from intrusions and malicious content increase, it is becoming increasingly difficult to manage IT security. This paper describes an approach to address IT security risk through risk management and mitigation in both the institution and in the project life cycle.

  1. Pukala intrusion, its age and connection to hydrothermal alteration in Orivesi, southwestern Finland

    Directory of Open Access Journals (Sweden)

    Matti Talikka

    2005-01-01

    Full Text Available The Pukala intrusion is situated in the Paleoproterozoic Svecofennian domain of the Fennoscandian Shield in the contact region between the Central Finland Granitoid Complex and the Tampere Belt. The acid subvolcanic intrusion, which is in contact or close to severalaltered domains, mainly consists of porphyritic granodiorite and trondhjemite. The Pukala intrusion was emplaced into volcanic sequence in an island-arc or fore-arc setting before or during the early stages of the main regional deformation phase of the Svecofennian orogeny. On the basis of the geochemical data, the Pukala intrusion is a peraluminous volcanic-arc granitoid. After crystallisation at 1896±3 Ma, multiphase deformation and metamorphismcaused alteration, recrystallisation, and orientation of the minerals, and tilted the intrusion steeply towards south. The 1851±5 Ma U-Pb age for titanite is connected to the late stages of the Svecofennian tectonometamorphic evolution of the region. Several hydrothermally altered domains are located in the felsic and intermediate metavolcanic rocks of the Tampere Belt within less than one kilometre south of the Pukala intrusion. Alteration is divided into three basic types: partial silica alteration, chlorite-sericite±silica alteration, and sericite alteration in shear zones. The first two types probably formed during the emplacement and crystallisation of the Pukala intrusion, and the third is linked to late shearing. Intense sericitisation and comb quartz bands in the contact of theintrusion and the altered domain at Kutemajärvi suggest that the hydrothermal system was driven by the Pukala intrusion.

  2. Dynamically adaptive data-driven simulation of extreme hydrological flows

    Science.gov (United States)

    Kumar Jain, Pushkar; Mandli, Kyle; Hoteit, Ibrahim; Knio, Omar; Dawson, Clint

    2018-02-01

    Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

  3. Dynamically adaptive data-driven simulation of extreme hydrological flows

    KAUST Repository

    Kumar Jain, Pushkar

    2017-12-27

    Hydrological hazards such as storm surges, tsunamis, and rainfall-induced flooding are physically complex events that are costly in loss of human life and economic productivity. Many such disasters could be mitigated through improved emergency evacuation in real-time and through the development of resilient infrastructure based on knowledge of how systems respond to extreme events. Data-driven computational modeling is a critical technology underpinning these efforts. This investigation focuses on the novel combination of methodologies in forward simulation and data assimilation. The forward geophysical model utilizes adaptive mesh refinement (AMR), a process by which a computational mesh can adapt in time and space based on the current state of a simulation. The forward solution is combined with ensemble based data assimilation methods, whereby observations from an event are assimilated into the forward simulation to improve the veracity of the solution, or used to invert for uncertain physical parameters. The novelty in our approach is the tight two-way coupling of AMR and ensemble filtering techniques. The technology is tested using actual data from the Chile tsunami event of February 27, 2010. These advances offer the promise of significantly transforming data-driven, real-time modeling of hydrological hazards, with potentially broader applications in other science domains.

  4. Computer Adaptive Testing, Big Data and Algorithmic Approaches to Education

    Science.gov (United States)

    Thompson, Greg

    2017-01-01

    This article critically considers the promise of computer adaptive testing (CAT) and digital data to provide better and quicker data that will improve the quality, efficiency and effectiveness of schooling. In particular, it uses the case of the Australian NAPLAN test that will become an online, adaptive test from 2016. The article argues that…

  5. SWIBANGLA: Managing salt water intrusion impacts in coastal groundwater systems of Bangladesh

    NARCIS (Netherlands)

    Faneca Sànchez, Marta; Bashar, Khairul; Janssen, Gijs; Vogels, Marjolein; Snel, Jan; Zhou, Yangxiao; Stuurman, Roelof J.; Oude Essink, Gualbert

    Bangladesh is densely populated and it is expected that the population increases significantly in the coming decade, up to 60% more by 2050 according to IIASA (2013). Demand for drinking water will increase accordingly. These developments may cause significant changes in the hydrological system,

  6. Options for human intrusion

    International Nuclear Information System (INIS)

    Bauser, M.; Williams, R.

    1993-01-01

    This paper addresses options for dealing with human intrusion in terms of performance requirements and repository siting and design requirements. Options are presented, along with the advantages and disadvantages of certain approaches. At the conclusion, a conceptual approach is offered emphasizing both the minimization of subjective judgements concerning future human activity, and specification of repository requirements to minimize the likelihood of human intrusion and any resulting, harmful effects should intrusion occur

  7. On complex adaptive systems and terrorism

    International Nuclear Information System (INIS)

    Ahmed, E.; Elgazzar, A.S.; Hegazi, A.S.

    2005-01-01

    Complex adaptive systems (CAS) are ubiquitous in nature. They are basic in social sciences. An overview of CAS is given with emphasize on the occurrence of bad side effects to seemingly 'wise' decisions. Hence application to terrorism is given. Some conclusions on how to deal with this phenomena are proposed

  8. Adaptive radiotherapy using helical tomotherapy system

    International Nuclear Information System (INIS)

    Jeswani, Sam; Ruchala, Kenneth; Olivera, Gustavo; Mackie, T.R.

    2008-01-01

    As commonly known in the field, adaptive radiation therapy (ART) is the use of feedback to modify a radiotherapy treatment. There are numerous ways in which this feedback can be received and used, and this presentation will discuss some of the implementations of ART being investigated with a helical TomoTherapy system

  9. Two Perspectives on Information System Adaptation

    DEFF Research Database (Denmark)

    Jensen, Tina Blegind; Kjærgaard, Annemette; Svejvig, Per

    Institutional theory has proven to be a central analytical perspective for investigating the role of larger social and historical structures of Information System (IS) adaptation. However, it does not explicitly account for how organizational actors make sense of and enact IS in their local context...

  10. A minimally intrusive monitoring system that utilizes electricity consumption as a proxy for wellbeing

    Directory of Open Access Journals (Sweden)

    Tim D. Hunt

    Full Text Available The purpose of this work was to test the hypothesis: \\'Off-the-shelf domestic electricity meters can be utilised to assist in monitoring the wellbeing of elderly people\\'. Many studies have shown that it is, in theory, possible to use domestic electricity consumption to determine \\'activities of daily living\\' but the availability of systems for actual use is very limited. This work followed the Design Science Research Methodology to create a Java application running on the Google App Engine cloud service that interfaced with both electricity meters and voice and text services. The system was implemented and tested over a three month period with one older person and their carer. Results demonstrated that the technology readily succeeds in meeting the study\\'s initial objectives. The need for more sophisticated decision logic was apparent and a method to determine whether a home is currently occupied is likely to improve the ability to create more timely alerts.

  11. Data acquisition and test system software

    International Nuclear Information System (INIS)

    Bourgeois, N.A. Jr.

    1979-03-01

    Sandia Laboratories has been assigned the task by the Base and Installation Security Systems (BISS) Program Office to develop various aspects of perimeter security systems. One part of this effort involves the development of advanced signal processing techniques to reduce the false and nuisance alarms from sensor systems while improving the probability of intrusion detection. The need existed for both data acquisition hardware and software. Also, the hardware is used to implement and test the signal processing algorithms in real time. The hardware developed for this signal processing task is the Data Acquisition and Test System (DATS). The programs developed for use on DATS are described. The descriptions are taken directly from the documentation included within the source programs themselves

  12. Surface Operations Data Analysis and Adaptation Tool, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — This effort undertook the creation of a Surface Operations Data Analysis and Adaptation (SODAA) tool to store data relevant to airport surface research and...

  13. Workload modelling for data-intensive systems

    CERN Document Server

    Lassnig, Mario

    This thesis presents a comprehensive study built upon the requirements of a global data-intensive system, built for the ATLAS Experiment at CERN's Large Hadron Collider. First, a scalable method is described to capture distributed data management operations in a non-intrusive way. These operations are collected into a globally synchronised sequence of events, the workload. A comparative analysis of this new data-intensive workload against existing computational workloads is conducted, leading to the discovery of the importance of descriptive attributes in the operations. Existing computational workload models only consider the arrival rates of operations, however, in data-intensive systems the correlations between attributes play a central role. Furthermore, the detrimental effect of rapid correlated arrivals, so called bursts, is assessed. A model is proposed that can learn burst behaviour from captured workload, and in turn forecast potential future bursts. To help with the creation of a full representative...

  14. Adaptive Integration of Nonsmooth Dynamical Systems

    Science.gov (United States)

    2017-10-11

    2017 W911NF-12-R-0012-03: Adaptive Integration of Nonsmooth Dynamical Systems The views, opinions and/or findings contained in this report are those of...Integration of Nonsmooth Dynamical Systems Report Term: 0-Other Email: drum@gwu.edu Distribution Statement: 1-Approved for public release; distribution is...classdrake_1_1systems_1_1_integrator_base.html ; 3) a solver for dynamical systems with arbitrary unilateral and bilateral constraints (the key component of the time stepping systems )- see

  15. Changing Paradigms: From Schooling to Schools as Adaptive Recommendation Systems

    DEFF Research Database (Denmark)

    Christiansen, René Boyer; Gynther, Karsten; Petersen, Anne Kristine

    2017-01-01

    The paper explores a shift in education from educational systems requiring student adaptation to educational recommendation systems adapting to students’ individual needs. The paper discusses the concept of adaptation as addressed in educational research and draws on the system theory of Heinz von...... Foerster to shed light on how the educational system has used and understood adaptation. In this context, we point out two different approaches to educational adaptation: 1) students adapting to the educational system and 2) the attempt of the educational system to adapt to students through automatized...... system adaptation and recommendation systems. These different understandings constitute a design framework that is used to analyze two current trends: Adaptive learning systems and learning analytics. Finally, the paper discusses the potential of looking at adaptation as recommendation systems...

  16. Changing Paradigms: From Schooling to Schools as Adaptive Recommendation Systems

    DEFF Research Database (Denmark)

    Christiansen, René Boyer; Gynther, Karsten; Petersen, Anne Kristine

    2017-01-01

    The paper explores a shift in education from educational systems requiring student adaptation to educational recommendation systems adapting to students’ individual needs. The paper discusses the concept of adaptation as addressed in educational research and draws on the system theory of Heinz von...... system adaptation and recommendation systems. These different understandings constitute a design framework that is used to analyze two current trends: Adaptive learning systems and learning analytics. Finally, the paper discusses the potential of looking at adaptation as recommendation systems...... Foerster to shed light on how the educational system has used and understood adaptation. In this context, we point out two different approaches to educational adaptation: 1) students adapting to the educational system and 2) the attempt of the educational system to adapt to students through automatized...

  17. MFIRE-2: A Multi Agent System for Flow-Based Intrusion Detection Using Stochastic Search

    Science.gov (United States)

    2012-03-01

    Algorithms to pattern recognition comes from Radtke et al. [72]. The authors apply Multi- Objective Genetic Algorithms (MOGAs) to two parts of a handwritten...Postel, J.B. “User Datagram Protocol. RFC 768”, 1980. [72] Radtke , Paulo V. W., Robert Sabourin, and Tony Wong. “Classification system optimization...Rennes 1, Suvisoft, La Baule (France), 10 2006. URL http://hal.inria.fr/inria-00104200/en/. [73] Radtke , P.V.W., T. Wong, and R. Sabourin. “A multi

  18. Building a highly available and intrusion tolerant Database Security and Protection System (DSPS).

    Science.gov (United States)

    Cai, Liang; Yang, Xiao-Hu; Dong, Jin-Xiang

    2003-01-01

    Database Security and Protection System (DSPS) is a security platform for fighting malicious DBMS. The security and performance are critical to DSPS. The authors suggested a key management scheme by combining the server group structure to improve availability and the key distribution structure needed by proactive security. This paper detailed the implementation of proactive security in DSPS. After thorough performance analysis, the authors concluded that the performance difference between the replicated mechanism and proactive mechanism becomes smaller and smaller with increasing number of concurrent connections; and that proactive security is very useful and practical for large, critical applications.

  19. Indirect adaptive control of discrete chaotic systems

    International Nuclear Information System (INIS)

    Salarieh, Hassan; Shahrokhi, Mohammad

    2007-01-01

    In this paper an indirect adaptive control algorithm is proposed to stabilize the fixed points of discrete chaotic systems. It is assumed that the functionality of the chaotic dynamics is known but the system parameters are unknown. This assumption is usually applicable to many chaotic systems, such as the Henon map, logistic and many other nonlinear maps. Using the recursive-least squares technique, the system parameters are identified and based on the feedback linearization method an adaptive controller is designed for stabilizing the fixed points, or unstable periodic orbits of the chaotic maps. The stability of the proposed scheme has been shown and the effectiveness of the control algorithm has been demonstrated through computer simulations

  20. Check valve slam caused by air intrusion in emergency cooling water system

    International Nuclear Information System (INIS)

    Martin, C.S.

    2011-01-01

    Waterhammer pressures were experienced during periodic starting of Residual Heat Removal (RHR) pumps at a nuclear plant. Prior to an analytical investigation careful analysis performed by plant engineers indicated that the spring effect of entrapped air in a heat exchanger resulted in water hammer due to check valve slam following flow reversal. In order to determine in more detail the values of pertinent parameters controlling this water hammer a hydraulic transient analysis was performed of the RHR piping system, including essential elements such as the pump, check valve, and heat exchanger. Using characteristic torque and pressure loss curves the motion of the check valve was determined. By comparing output of the water hammer analysis with site recordings of pump discharge pressure the computer model was calibrated, allowing for a realistic estimate of the quantity of entrapped air in the heat exchanger. (author)

  1. Electric vehicle data acquisition system

    DEFF Research Database (Denmark)

    Svendsen, Mathias; Winther-Jensen, Mads; Pedersen, Anders Bro

    2014-01-01

    and industrial applications, e.g. research in electric vehicle driving patterns, vehicle substitutability analysis and fleet management. The platform is based on a embedded computer running Linux, and features a high level of modularity and flexibility. The system operates independently of the make of the car......, by using the On-board Diagnostic port to identify car model and adapt its software accordingly. By utilizing on-board Global Navigation Satellite System, General Packet Radio Service, accelerometer, gyroscope and magnetometer, the system not only provides valuable data for research in the field of electric......A data acquisition system for electric vehicles is presented. The system connects to the On-board Diagnostic port of newer vehicles, and utilizes the in-vehicle sensor network, as well as auxiliary sensors, to gather data. Data is transmitted continuously to a central database for academic...

  2. Water System Adaptation To Hydrological Changes: Module 8, Regulatory Framework Intersections: Past, Present, and Future

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  3. Water System Adaptation To Hydrological Changes: Module 11, Methods and Tools: Computational Models

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  4. Numerical Continuation Methods for Intrusive Uncertainty Quantification Studies

    Energy Technology Data Exchange (ETDEWEB)

    Safta, Cosmin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Najm, Habib N. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Phipps, Eric Todd [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2014-09-01

    Rigorous modeling of engineering systems relies on efficient propagation of uncertainty from input parameters to model outputs. In recent years, there has been substantial development of probabilistic polynomial chaos (PC) Uncertainty Quantification (UQ) methods, enabling studies in expensive computational models. One approach, termed ”intrusive”, involving reformulation of the governing equations, has been found to have superior computational performance compared to non-intrusive sampling-based methods in relevant large-scale problems, particularly in the context of emerging architectures. However, the utility of intrusive methods has been severely limited due to detrimental numerical instabilities associated with strong nonlinear physics. Previous methods for stabilizing these constructions tend to add unacceptably high computational costs, particularly in problems with many uncertain parameters. In order to address these challenges, we propose to adapt and improve numerical continuation methods for the robust time integration of intrusive PC system dynamics. We propose adaptive methods, starting with a small uncertainty for which the model has stable behavior and gradually moving to larger uncertainty where the instabilities are rampant, in a manner that provides a suitable solution.

  5. Adaptive vibration isolation system for diesel engine

    Institute of Scientific and Technical Information of China (English)

    YANG Tie-jun; ZHANG Xin-yu; XIAO You-hong; HUANG Jin-e; LIU Zhi-gang

    2004-01-01

    An active two-stage isolation mounting, on which servo-hydraulic system is used as the actuator (secondary vibration source) and a diesel engine is used as primary vibration source, has been built. The upper mass of the mounting is composed of a 495diesel and an electrical eddy current dynamometer. The lower mass is divided into four small masses to which servo-hydraulic actuator and rubber isolators are attached. According to the periodical characteristics of diesel vibration signals, a multi-point adaptive strategy based on adaptive comb filtered algorithm is applied to active multi-direction coupled vibrations control for the engine. The experimental results demonstrate that a good suppression in the effective range of phase compensation in secondary path (within 100Hz) at different operation conditions is achieved, and verify that this strategy is effective. The features of the active system, the development activities carried out on the system and experimental results are discussed in the paper.

  6. Adaptive traffic control systems for urban networks

    Directory of Open Access Journals (Sweden)

    Radivojević Danilo

    2017-01-01

    Full Text Available Adaptive traffic control systems represent complex, but powerful tool for improvement of traffic flow conditions in locations or zones where applied. Many traffic agencies, especially those that have a large number of signalized intersections with high variability of the traffic demand, choose to apply some of the adaptive traffic control systems. However, those systems are manufactured and offered by multiple vendors (companies that are competing for the market share. Due to that fact, besides the information available from the vendors themselves, or the information from different studies conducted on different continents, very limited amount of information is available about the details how those systems are operating. The reason for that is the protecting of the intellectual property from plagiarism. The primary goal of this paper is to make a brief analysis of the functionalities, characteristics, abilities and results of the most recognized, but also less known adaptive traffic control systems to the professional public and other persons with interest in this subject.

  7. Distributed adaptive diagnosis of sensor faults using structural response data

    Science.gov (United States)

    Dragos, Kosmas; Smarsly, Kay

    2016-10-01

    The reliability and consistency of wireless structural health monitoring (SHM) systems can be compromised by sensor faults, leading to miscalibrations, corrupted data, or even data loss. Several research approaches towards fault diagnosis, referred to as ‘analytical redundancy’, have been proposed that analyze the correlations between different sensor outputs. In wireless SHM, most analytical redundancy approaches require centralized data storage on a server for data analysis, while other approaches exploit the on-board computing capabilities of wireless sensor nodes, analyzing the raw sensor data directly on board. However, using raw sensor data poses an operational constraint due to the limited power resources of wireless sensor nodes. In this paper, a new distributed autonomous approach towards sensor fault diagnosis based on processed structural response data is presented. The inherent correlations among Fourier amplitudes of acceleration response data, at peaks corresponding to the eigenfrequencies of the structure, are used for diagnosis of abnormal sensor outputs at a given structural condition. Representing an entirely data-driven analytical redundancy approach that does not require any a priori knowledge of the monitored structure or of the SHM system, artificial neural networks (ANN) are embedded into the sensor nodes enabling cooperative fault diagnosis in a fully decentralized manner. The distributed analytical redundancy approach is implemented into a wireless SHM system and validated in laboratory experiments, demonstrating the ability of wireless sensor nodes to self-diagnose sensor faults accurately and efficiently with minimal data traffic. Besides enabling distributed autonomous fault diagnosis, the embedded ANNs are able to adapt to the actual condition of the structure, thus ensuring accurate and efficient fault diagnosis even in case of structural changes.

  8. Adaptive Distributed Data Structure Management for Parallel CFD Applications

    KAUST Repository

    Frisch, Jerome

    2013-09-01

    Computational fluid dynamics (CFD) simulations require a lot of computing resources in terms of CPU time and memory in order to compute with a reasonable physical accuracy. If only uniformly refined domains are applied, the amount of computing cells is growing rather fast if a certain small resolution is physically required. This can be remedied by applying adaptively refined grids. Unfortunately, due to the adaptive refinement procedures, errors are introduced which have to be taken into account. This paper is focussing on implementation details of the applied adaptive data structure management and a qualitative analysis of the introduced errors by analysing a Poisson problem on the given data structure, which has to be solved in every time step of a CFD analysis. Furthermore an adaptive CFD benchmark example is computed, showing the benefits of an adaptive refinement as well as measurements of parallel data distribution and performance. © 2013 IEEE.

  9. Quality data systems

    International Nuclear Information System (INIS)

    Bergman, J.E.; Patterson, R.G.

    1976-01-01

    General Electric's Nuclear Fuel Department data system strategy of multifunctional system integration and specific applications of data systems for the Quality Assurance Programme is detailed. Descriptions of two manufacturing control systems and their function in satisfying quality data requirements are included. The timesharing quality data system developed for processing laboratory, traceability and material release data in the Fuel Manufacturing Operation is described. In addition, specific references are made to those areas where significant time reductions have been realized through the utilization of mechanized data-handling systems. (author)

  10. Intelligent Adaptation Process for Case Based Systems

    International Nuclear Information System (INIS)

    Nassar, A.M.; Mohamed, A.H.; Mohamed, A.H.

    2014-01-01

    Case Based Reasoning (CBR) Systems is one of the important decision making systems applied in many fields all over the world. The effectiveness of any CBR system based on the quality of the storage cases in the case library. Similar cases can be retrieved and adapted to produce the solution for the new problem. One of the main issues faced the CBR systems is the difficulties of achieving the useful cases. The proposed system introduces a new approach that uses the genetic algorithm (GA) technique to automate constructing the cases into the case library. Also, it can optimize the best one to be stored in the library for the future uses. However, the proposed system can avoid the problems of the uncertain and noisy cases. Besides, it can simply the retrieving and adaptation processes. So, it can improve the performance of the CBR system. The suggested system can be applied for many real-time problems. It has been applied for diagnosis the faults of the wireless network, diagnosis of the cancer diseases, diagnosis of the debugging of a software as cases of study. The proposed system has proved its performance in this field

  11. Adaptive and non-adaptive data hiding methods for grayscale images based on modulus function

    Directory of Open Access Journals (Sweden)

    Najme Maleki

    2014-07-01

    Full Text Available This paper presents two adaptive and non-adaptive data hiding methods for grayscale images based on modulus function. Our adaptive scheme is based on the concept of human vision sensitivity, so the pixels in edge areas than to smooth areas can tolerate much more changes without making visible distortion for human eyes. In our adaptive scheme, the average differencing value of four neighborhood pixels into a block via a threshold secret key determines whether current block is located in edge or smooth area. Pixels in the edge areas are embedded by Q-bit of secret data with a larger value of Q than that of pixels placed in smooth areas. Also in this scholar, we represent one non-adaptive data hiding algorithm. Our non-adaptive scheme, via an error reduction procedure, produces a high visual quality for stego-image. The proposed schemes present several advantages. 1-of aspects the embedding capacity and visual quality of stego-image are scalable. In other words, the embedding rate as well as the image quality can be scaled for practical applications 2-the high embedding capacity with minimal visual distortion can be achieved, 3-our methods require little memory space for secret data embedding and extracting phases, 4-secret keys have used to protect of the embedded secret data. Thus, level of security is high, 5-the problem of overflow or underflow does not occur. Experimental results indicated that the proposed adaptive scheme significantly is superior to the currently existing scheme, in terms of stego-image visual quality, embedding capacity and level of security and also our non-adaptive method is better than other non-adaptive methods, in view of stego-image quality. Results show which our adaptive algorithm can resist against the RS steganalysis attack.

  12. Water System Adaptation To Hydrological Changes: Module 9, Water System Resilience and Security under Hydrologic Variability and Uncertainty

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  13. Modeling Adaptive Behavior for Systems Design

    DEFF Research Database (Denmark)

    Rasmussen, Jens

    1994-01-01

    Field studies in modern work systems and analysis of recent major accidents have pointed to a need for better models of the adaptive behavior of individuals and organizations operating in a dynamic and highly competitive environment. The paper presents a discussion of some key characteristics.......) The basic difference between the models of system functions used in engineering and design and those evolving from basic research within the various academic disciplines and finally 3.) The models and methods required for closed-loop, feedback system design....

  14. Intrusion detection techniques for plant-wide network in a nuclear power plant

    International Nuclear Information System (INIS)

    Rajasekhar, P.; Shrikhande, S.V.; Biswas, B.B.; Patil, R.K.

    2012-01-01

    Nuclear power plants have a lot of critical data to be sent to the operator workstations. A plant wide integrated communication network, with high throughput, determinism and redundancy, is required between the workstations and the field. Switched Ethernet network is a promising prospect for such an integrated communication network. But for such an integrated system, intrusion is a major issue. Hence the network should have an intrusion detection system to make the network data secure and enhance the network availability. Intrusion detection is the process of monitoring the events occurring in a network and analyzing them for signs of possible incidents, which are violations or imminent threats of violation of network security policies, acceptable user policies, or standard security practices. This paper states the various intrusion detection techniques and approaches which are applicable for analysis of a plant wide network. (author)

  15. Organization of an optimal adaptive immune system

    Science.gov (United States)

    Walczak, Aleksandra; Mayer, Andreas; Balasubramanian, Vijay; Mora, Thierry

    The repertoire of lymphocyte receptors in the adaptive immune system protects organisms from a diverse set of pathogens. A well-adapted repertoire should be tuned to the pathogenic environment to reduce the cost of infections. I will discuss a general framework for predicting the optimal repertoire that minimizes the cost of infections contracted from a given distribution of pathogens. The theory predicts that the immune system will have more receptors for rare antigens than expected from the frequency of encounters and individuals exposed to the same infections will have sparse repertoires that are largely different, but nevertheless exploit cross-reactivity to provide the same coverage of antigens. I will show that the optimal repertoires can be reached by dynamics that describes the competitive binding of antigens by receptors, and selective amplification of stimulated receptors.

  16. Adaptive optics system application for solar telescope

    Science.gov (United States)

    Lukin, V. P.; Grigor'ev, V. M.; Antoshkin, L. V.; Botugina, N. N.; Emaleev, O. N.; Konyaev, P. A.; Kovadlo, P. G.; Krivolutskiy, N. P.; Lavrionova, L. N.; Skomorovski, V. I.

    2008-07-01

    The possibility of applying adaptive correction to ground-based solar astronomy is considered. Several experimental systems for image stabilization are described along with the results of their tests. Using our work along several years and world experience in solar adaptive optics (AO) we are assuming to obtain first light to the end of 2008 for the first Russian low order ANGARA solar AO system on the Big Solar Vacuum Telescope (BSVT) with 37 subapertures Shack-Hartmann wavefront sensor based of our modified correlation tracker algorithm, DALSTAR video camera, 37 elements deformable bimorph mirror, home made fast tip-tip mirror with separate correlation tracker. Too strong daytime turbulence is on the BSVT site and we are planning to obtain a partial correction for part of Sun surface image.

  17. Next generation intelligent environments ambient adaptive systems

    CERN Document Server

    Nothdurft, Florian; Heinroth, Tobias; Minker, Wolfgang

    2016-01-01

    This book covers key topics in the field of intelligent ambient adaptive systems. It focuses on the results worked out within the framework of the ATRACO (Adaptive and TRusted Ambient eCOlogies) project. The theoretical background, the developed prototypes, and the evaluated results form a fertile ground useful for the broad intelligent environments scientific community as well as for industrial interest groups. The new edition provides: Chapter authors comment on their work on ATRACO with final remarks as viewed in retrospective Each chapter has been updated with follow-up work emerging from ATRACO An extensive introduction to state-of-the-art statistical dialog management for intelligent environments Approaches are introduced on how Trust is reflected during the dialog with the system.

  18. Front-end data processing the SLD data acquisition system

    International Nuclear Information System (INIS)

    Nielsen, B.S.

    1986-07-01

    The data acquisition system for the SLD detector will make extensive use of parallel at the front-end level. Fastbus acquisition modules are being built with powerful processing capabilities for calibration, data reduction and further pre-processing of the large amount of analog data handled by each module. This paper describes the read-out electronics chain and data pre-processing system adapted for most of the detector channels, exemplified by the central drift chamber waveform digitization and processing system

  19. Extensible Adaptive System for STEM Learning

    Science.gov (United States)

    2013-07-16

    Copyright 2013 Raytheon BBN Technologies Corp. All Rights Reserved ONR STEM Grand Challenge Extensible Adaptive System for STEM Learning ...Contract # N00014-12-C-0535 Raytheon BBN Technologies Corp. (BBN) Reference # 14217 In partial fulfillment of contract deliverable item # A001...Quarterly Progress Report #2 April 7, 2013 –July 6, 2013 Submitted July 16, 2013 BBN Technical POC: John Makhoul Raytheon BBN Technologies

  20. Adaptive stimulus optimization for sensory systems neuroscience

    OpenAIRE

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system...

  1. STATISTICS. The reusable holdout: Preserving validity in adaptive data analysis.

    Science.gov (United States)

    Dwork, Cynthia; Feldman, Vitaly; Hardt, Moritz; Pitassi, Toniann; Reingold, Omer; Roth, Aaron

    2015-08-07

    Misapplication of statistical data analysis is a common cause of spurious discoveries in scientific research. Existing approaches to ensuring the validity of inferences drawn from data assume a fixed procedure to be performed, selected before the data are examined. In common practice, however, data analysis is an intrinsically adaptive process, with new analyses generated on the basis of data exploration, as well as the results of previous analyses on the same data. We demonstrate a new approach for addressing the challenges of adaptivity based on insights from privacy-preserving data analysis. As an application, we show how to safely reuse a holdout data set many times to validate the results of adaptively chosen analyses. Copyright © 2015, American Association for the Advancement of Science.

  2. Telemetry System Data Latency

    Science.gov (United States)

    2017-07-13

    latencies will be measured. DATS Network TM Antenna TM ReceiverMCS System IOPlex IOPlexIADS CDS IADS Client TM Transmitter Sensors Signal Conditioning...TIME Figure 1-2 Mission Control System (MCS) / Interactive Analysis and Display System (IADS) Overview IADS CDSIADS Client TELEMETRY SYSTEM DATA...Sim GPS Signal Combiner MCS system Oscilloscope IADS Client IADS CDS Figure 13-1 IADS Data Flow 13.2. Test Results The results of the data test at

  3. Adaptive Modeling of the International Space Station Electrical Power System

    Science.gov (United States)

    Thomas, Justin Ray

    2007-01-01

    Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

  4. Simulated climate adaptation in storm-water systems: Evaluating the efficiency of within-system flexibility

    Directory of Open Access Journals (Sweden)

    Adam D. McCurdy

    Full Text Available Changes in regional temperature and precipitation patterns resulting from global climate change may adversely affect the performance of long-lived infrastructure. Adaptation may be necessary to ensure that infrastructure offers consistent service and remains cost effective. But long service times and deep uncertainty associated with future climate projections make adaptation decisions especially challenging for managers. Incorporating flexibility into systems can increase their effectiveness across different climate futures but can also add significant costs. In this paper we review existing work on flexibility in climate change adaptation of infrastructure, such as robust decision-making and dynamic adaptive pathways, apply a basic typology of flexibility, and test alternative strategies for flexibility in distributed infrastructure systems comprised of multiple emplacements of a common, long-lived element: roadway culverts. Rather than treating a system of dispersed infrastructure elements as monolithic, we simulate “options flexibility” in which inherent differences in individual elements is incorporated into adaptation decisions. We use a virtual testbed of highway drainage crossing structures to examine the performance under different climate scenarios of policies that allow for multiple adaptation strategies with varying timing based on individual emplacement characteristics. Results indicate that a strategy with options flexibility informed by crossing characteristics offers a more efficient method of adaptation than do monolithic policies. In some cases this results in more cost-effective adaptation for agencies building long-lived, climate-sensitive infrastructure, even where detailed system data and analytical capacity is limited. Keywords: Climate adaptation, Stormwater management, Adaptation pathways

  5. Development and validation of a nuclear data and calculation system for Superphenix with steel reflectors; Developpement et qualification d`un formulaire adapte a superphenix avec reflecteurs

    Energy Technology Data Exchange (ETDEWEB)

    Bosq, J Ch

    1998-11-09

    This thesis concerns the definition and the validation of the ERANOS neutronic calculation system for steel reflected fast reactors. The calculation system uses JEF2.2 evaluated nuclear data, the ECCO cell code and the BISTRO and VARIANT transport codes. After a description of the physical phenomena induced by the existence of the these sub-critical media, an inventory of the past studies related to steel reflectors is reported. A calculational scheme taking into account the important physical phenomena (strong neutronic slowing-down, presence of broad resonances of the structural materials and spatial variation of the spectrum in the reflector) is defined. This method is validated with the TRIPOLI4 reference Monte-Carlo code. The use of this upgraded calculation method for the analysis of the part of the CIRANO experimental program devoted to the study of steel reflected configurations leads to discrepancies between the calculated and measured values. These remaining discrepancies obtained for the reactivity and the fission rate traverses are due to inaccurate nuclear data for the structural materials. The adjustment of these nuclear data in order to reduce these discrepancies id demonstrated. The additional uncertainty associated to the integral parameters of interest for a nuclear reactor (reactivity and power distribution) induced by the replacement of a fertile blanket by a steel reflector is determined for the Superphenix reactor and is proved to be small. (author) 86 refs.

  6. Scoping calculation of nuclides migration in engineering barrier system for effect of volume expansion due to overpack corrosion and intrusion of the buffer material

    International Nuclear Information System (INIS)

    Yoshita, Takashi; Ishihara, Yoshinao; Ishiguro, Katsuhiko; Ohi, Takao; Nakajima, Kunihiko

    1999-11-01

    Corrosion of the carbon steel overpack leads to a volume expansion since the specific gravity of corrosion products is smaller than carbon steel. The buffer material is compressed due to the corrosive swelling, reducing its thickness and porosity. On the other hand, buffer material may be extruded into fractures of the surrounding rock and this may lead to a deterioration of the planned functions of the buffer, including retardation of nuclides migration and colloid filtration. In this study, the sensitivity analyses for the effect of volume expansion and intrusion of the buffer material on nuclide migration in the engineering barrier system are carried out. The sensitivity analyses were performed on the decrease in the thickness of the buffer material in the radial direction caused by the corrosive swelling, and the change in the porosity and dry density of the buffer caused by both compacting due to corrosive swelling and intrusion of buffer material. As results, it was found the maximum release rates of relatively shorter half-life nuclides from the outside of the buffer material decreased for taking into account of a volume expansion due to overpack corrosion. On the other hand, the maximum release rates increased when the intrusion of buffer material was also taking into account. It was, however, the maximum release rates of longer half-life nuclides, such as Cs-137 and Np-237, were insensitive to the change of buffer material thickness, and porosity and dry density of buffer. (author)

  7. An Adaptable Seismic Data Format for Modern Scientific Workflows

    Science.gov (United States)

    Smith, J. A.; Bozdag, E.; Krischer, L.; Lefebvre, M.; Lei, W.; Podhorszki, N.; Tromp, J.

    2013-12-01

    Data storage, exchange, and access play a critical role in modern seismology. Current seismic data formats, such as SEED, SAC, and SEG-Y, were designed with specific applications in mind and are frequently a major bottleneck in implementing efficient workflows. We propose a new modern parallel format that can be adapted for a variety of seismic workflows. The Adaptable Seismic Data Format (ASDF) features high-performance parallel read and write support and the ability to store an arbitrary number of traces of varying sizes. Provenance information is stored inside the file so that users know the origin of the data as well as the precise operations that have been applied to the waveforms. The design of the new format is based on several real-world use cases, including earthquake seismology and seismic interferometry. The metadata is based on the proven XML schemas StationXML and QuakeML. Existing time-series analysis tool-kits are easily interfaced with this new format so that seismologists can use robust, previously developed software packages, such as ObsPy and the SAC library. ADIOS, netCDF4, and HDF5 can be used as the underlying container format. At Princeton University, we have chosen to use ADIOS as the container format because it has shown superior scalability for certain applications, such as dealing with big data on HPC systems. In the context of high-performance computing, we have implemented ASDF into the global adjoint tomography workflow on Oak Ridge National Laboratory's supercomputer Titan.

  8. Complex Adaptive Systems of Systems (CASOS) engineering environment.

    Energy Technology Data Exchange (ETDEWEB)

    Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy

    2012-02-01

    Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

  9. Towards an Empathizing and Adaptive Storyteller System

    DEFF Research Database (Denmark)

    Bae, Byung Chull; Brunete, Alberto; Malik, Usman

    2012-01-01

    to deliver a story in an effective manner. We conducted a pilot study and the results were analyzed in two ways: first, through a survey questionnaire analysis based on the participant’s subjective ratings; second, through automated video analysis based on the participant’s emotional facial expression......This paper describes our ongoing effort to build an empathizing and adaptive storyteller system. The system under development aims to utilize emotional expressions generated from an avatar or a humanoid robot in addition to the listener’s responses which are monitored in real time, in order...

  10. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2013-01-01

    Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase...

  11. Medication Adherence using Non-intrusive Wearable Sensors

    Directory of Open Access Journals (Sweden)

    T. H. Lim

    2017-12-01

    Full Text Available Activity recognition approaches have been applied in home ambient systems to monitor the status and well- being of occupant especially for home care systems. With the advancement of embedded wireless sensing devices, various applications have been proposed to monitor user´s activities and maintain a healthy lifestyle. In this paper, we propose and evaluate a Smart Medication Alert and Treatment Electronic Systems (SmartMATES using a non-intrusive wearable activity recognition sensing system to monitor and alert an user for missing medication prescription. Two sensors are used to collect data from the accelerometer and radio transceiver. Based on the data collected, SmartMATES processes the data and generate a model for the various actions including taking medication. We have evaluated the SmartMATES on 9 participants. The results show that the SmartMATES can identify and prevent missing dosage in a less intrusive way than existing mobile application and traditional approaches.

  12. US ecology data system

    International Nuclear Information System (INIS)

    Crase, A.

    1987-01-01

    The US Ecology computer data system was instituted March 1, 1982. This system was designed to manage the increasing flow of paperwork and data associated with the receipt and disposal of low-level radioactive waste at Richland, Washington and Beatty, Nevada. The system was modified and upgraded in 1984 to accommodate a revised shipping manifest pursuant to the requirements of 10 CFR 20.311. The data system is used to generate various reports for both internal and external distribution. The computer system is located at US Ecology's corporate headquarters in Louisville, Kentucky. Remote access terminals are located at the disposal sites. The system is supported by a Wang VS-100 processor. In addition to supporting the radwaste data system, the system supports a chemical waste data base, word processing, and electronic mail. The management and operation of this data base are described. 19 figures

  13. Hybrid cognitive engine for radio systems adaptation

    KAUST Repository

    Alqerm, Ismail

    2017-07-20

    Network efficiency and proper utilization of its resources are essential requirements to operate wireless networks in an optimal fashion. Cognitive radio aims to fulfill these requirements by exploiting artificial intelligence techniques to create an entity called cognitive engine. Cognitive engine exploits awareness about the surrounding radio environment to optimize the use of radio resources and adapt relevant transmission parameters. In this paper, we propose a hybrid cognitive engine that employs Case Based Reasoning (CBR) and Decision Trees (DTs) to perform radio adaptation in multi-carriers wireless networks. The engine complexity is reduced by employing DTs to improve the indexing methodology used in CBR cases retrieval. The performance of our hybrid engine is validated using software defined radios implementation and simulation in multi-carrier environment. The system throughput, signal to noise and interference ratio, and packet error rate are obtained and compared with other schemes in different scenarios.

  14. Adaptive self-correcting control system

    International Nuclear Information System (INIS)

    Ellis, S.H.

    1984-01-01

    A control system for regulating a controlled device or process, such as a turbofan engine, produces independent multiple estimates of one or more controlled variables of the device or process by combining the signals from a plurality of feedback sensors, which provide information related to the controlled variables, in weighted nonordered pairs. The independent multiple estimates of each controlled variable are combined into a weighted average, and individual estimates which differ by more than a specified amount from the weighted average are edited and temporarily removed from consideration. A revised weighted average value of each controlled variable is then produced, and this value is used to limit or control operation of the device or process. Adaptive trim is provided to compensate for changes in the device or process being controlled, such as engine deterioration, by slowly trimming each individual estimate toward the mean, and includes error compensation which constrains the weighted sum of the adaptive trims to equal zero, thereby preventing the adaptive trim from changing the operating level of the device or process. A secondary editing circuit based on a majority rule principle identifies a failed feedback sensor and permanently excludes all individual estimates of the controlled variable based on the failed sensor. Editing boundaries are increased and adaptive trim rate is varied when a transient occurs in the operation of the device or process. Further transient compensation may be required for a system with more severe transient requirements, and this invention includes compensation to selected feedback parameters such as turbine temperature to account for differences between steady state and transient values

  15. Water System Adaptation To Hydrological Changes: Module 5, Water Quality and Infrastructure Response to Rapid Urbanization: Adaptation Case Study in China

    Science.gov (United States)

    This course will introduce students to the fundamental principles of water system adaptation to hydrological changes, with emphasis on data analysis and interpretation, technical planning, and computational modeling. Starting with real-world scenarios and adaptation needs, the co...

  16. Multiprocessor data acquisition system

    International Nuclear Information System (INIS)

    Haumann, J.R.; Crawford, R.K.

    1987-01-01

    A multiprocessor data acquisition system has been built to replace the single processor systems at the Intense Pulsed Neutron Source (IPNS) at Argonne National Laboratory. The multiprocessor system was needed to accommodate the higher data rates at IPNS brought about by improvements in the source and changes in instrument configurations. This paper describes the hardware configuration of the system and the method of task sharing and compares results to the single processor system

  17. Data adaptive estimation of transversal blood flow velocities

    DEFF Research Database (Denmark)

    Pirnia, E.; Jakobsson, A.; Gudmundson, E.

    2014-01-01

    the transversal blood flow. In this paper, we propose a novel data-adaptive blood flow estimator exploiting this modulation scheme. Using realistic Field II simulations, the proposed estimator is shown to achieve a notable performance improvement as compared to current state-of-the-art techniques.......The examination of blood flow inside the body may yield important information about vascular anomalies, such as possible indications of, for example, stenosis. Current Medical ultrasound systems suffer from only allowing for measuring the blood flow velocity along the direction of irradiation......, posing natural difficulties due to the complex behaviour of blood flow, and due to the natural orientation of most blood vessels. Recently, a transversal modulation scheme was introduced to induce also an oscillation along the transversal direction, thereby allowing for the measurement of also...

  18. Multiresolution Analysis Adapted to Irregularly Spaced Data

    Directory of Open Access Journals (Sweden)

    Anissa Mokraoui

    2009-01-01

    Full Text Available This paper investigates the mathematical background of multiresolution analysis in the specific context where the signal is represented by irregularly sampled data at known locations. The study is related to the construction of nested piecewise polynomial multiresolution spaces represented by their corresponding orthonormal bases. Using simple spline basis orthonormalization procedures involves the construction of a large family of orthonormal spline scaling bases defined on consecutive bounded intervals. However, if no more additional conditions than those coming from multiresolution are imposed on each bounded interval, the orthonormal basis is represented by a set of discontinuous scaling functions. The spline wavelet basis also has the same problem. Moreover, the dimension of the corresponding wavelet basis increases with the spline degree. An appropriate orthonormalization procedure of the basic spline space basis, whatever the degree of the spline, allows us to (i provide continuous scaling and wavelet functions, (ii reduce the number of wavelets to only one, and (iii reduce the complexity of the filter bank. Examples of the multiresolution implementations illustrate that the main important features of the traditional multiresolution are also satisfied.

  19. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2015-01-01

    This primer offers readers an introduction to the central concepts that form our modern understanding of complex and emergent behavior, together with detailed coverage of accompanying mathematical methods. All calculations are presented step by step and are easy to follow. This new fourth edition has been fully reorganized and includes new chapters, figures and exercises. The core aspects of modern complex system sciences are presented in the first chapters, covering network theory, dynamical systems, bifurcation and catastrophe theory, chaos and adaptive processes, together with the principle of self-organization in reaction-diffusion systems and social animals. Modern information theoretical principles are treated in further chapters, together with the concept of self-organized criticality, gene regulation networks, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard ...

  20. The adaptive safety analysis and monitoring system

    Science.gov (United States)

    Tu, Haiying; Allanach, Jeffrey; Singh, Satnam; Pattipati, Krishna R.; Willett, Peter

    2004-09-01

    The Adaptive Safety Analysis and Monitoring (ASAM) system is a hybrid model-based software tool for assisting intelligence analysts to identify terrorist threats, to predict possible evolution of the terrorist activities, and to suggest strategies for countering terrorism. The ASAM system provides a distributed processing structure for gathering, sharing, understanding, and using information to assess and predict terrorist network states. In combination with counter-terrorist network models, it can also suggest feasible actions to inhibit potential terrorist threats. In this paper, we will introduce the architecture of the ASAM system, and discuss the hybrid modeling approach embedded in it, viz., Hidden Markov Models (HMMs) to detect and provide soft evidence on the states of terrorist network nodes based on partial and imperfect observations, and Bayesian networks (BNs) to integrate soft evidence from multiple HMMs. The functionality of the ASAM system is illustrated by way of application to the Indian Airlines Hijacking, as modeled from open sources.

  1. Managing Temperature Effects in Nanoscale Adaptive Systems

    CERN Document Server

    Wolpert, David

    2012-01-01

    This book discusses new techniques for detecting, controlling, and exploiting the impacts of temperature variations on nanoscale circuits and systems.  It provides a holistic discussion of temperature management, including physical phenomena (reversal of the MOSFET temperature dependence) that have recently become problematic, along with circuit techniques for detecting, controlling, and adapting to these phenomena. A detailed discussion is also included of the general aspects of thermal-aware system design and management of temperature-induced faults. A new sensor system is described that can determine the temperature dependence as well as the operating temperature to improve system reliability.  A new method is presented to control a circuit’s temperature dependence by individually tuning pull-up and pull-down networks to their temperature-insensitive operating points. This method extends the range of supply voltages that can be made temperature-insensitive, achieving insensitivity at nominal voltage fo...

  2. Intrusion problematic during water supply systems’ operation

    OpenAIRE

    Jesus Mora-Rodriguez, P. Amparo López-Jimenez, Helena M. Ramos

    2011-01-01

    Intrusion through leaks occurrence is a phenomenon when external fluid comes into water pipe systems. This phenomenon can cause contamination problems in drinking pipe systems. Hence, this paper focuses on the entry of external fluids across small leaks during normal operation conditions. This situation is especially important in elevated points of the pipe profile. Pressure variations can origin water volume losses and intrusion of contaminants into the drinking water pipes. This work focuse...

  3. Adaptive Sensing Based on Profiles for Sensor Systems

    Directory of Open Access Journals (Sweden)

    Yoshiteru Ishida

    2009-10-01

    Full Text Available This paper proposes a profile-based sensing framework for adaptive sensor systems based on models that relate possibly heterogeneous sensor data and profiles generated by the models to detect events. With these concepts, three phases for building the sensor systems are extracted from two examples: a combustion control sensor system for an automobile engine, and a sensor system for home security. The three phases are: modeling, profiling, and managing trade-offs. Designing and building a sensor system involves mapping the signals to a model to achieve a given mission.

  4. ADAPTATION TO POVERTY IN LONG-RUN PANEL DATA.

    Science.gov (United States)

    Clark, Andrew E; D'Ambrosio, Conchita; Ghislandi, Simone

    2016-07-01

    We consider the link between poverty and subjective well-being and focus in particular on potential adaptation to poverty. We use panel data on almost 54,000 individuals living in Germany from 1985 to 2012 to show, first, that life satisfaction falls with both the incidence and intensity of contemporaneous poverty. We then reveal that there is little evidence of adaptation within a poverty spell: poverty starts bad and stays bad in terms of subjective well-being. We cannot identify any cause of poverty entry that explains the overall lack of poverty adaptation.

  5. PyParse: a semiautomated system for scoring spoken recall data.

    Science.gov (United States)

    Solway, Alec; Geller, Aaron S; Sederberg, Per B; Kahana, Michael J

    2010-02-01

    Studies of human memory often generate data on the sequence and timing of recalled items, but scoring such data using conventional methods is difficult or impossible. We describe a Python-based semiautomated system that greatly simplifies this task. This software, called PyParse, can easily be used in conjunction with many common experiment authoring systems. Scored data is output in a simple ASCII format and can be accessed with the programming language of choice, allowing for the identification of features such as correct responses, prior-list intrusions, extra-list intrusions, and repetitions.

  6. Adaptive Sliding Mode Observer for a Class of Systems

    OpenAIRE

    D.Elleuch; T.Damak

    2010-01-01

    In this paper, the performance of two adaptive observers applied to interconnected systems is studied. The nonlinearity of systems can be written in a fractional form. The first adaptive observer is an adaptive sliding mode observer for a Lipchitz nonlinear system and the second one is an adaptive sliding mode observer having a filtered error as a sliding surface. After comparing their performances throughout the inverted pendulum mounted on a car system, it was shown tha...

  7. Adaptive stimulus optimization for sensory systems neuroscience.

    Science.gov (United States)

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.

  8. Small Aircraft Data Distribution System

    Science.gov (United States)

    Chazanoff, Seth L.; Dinardo, Steven J.

    2012-01-01

    The CARVE Small Aircraft Data Distribution System acquires the aircraft location and attitude data that is required by the various programs running on a distributed network. This system distributes the data it acquires to the data acquisition programs for inclusion in their data files. It uses UDP (User Datagram Protocol) to broadcast data over a LAN (Local Area Network) to any programs that might have a use for the data. The program is easily adaptable to acquire additional data and log that data to disk. The current version also drives displays using precision pitch and roll information to aid the pilot in maintaining a level-level attitude for radar/radiometer mapping beyond the degree available by flying visually or using a standard gyro-driven attitude indicator. The software is designed to acquire an array of data to help the mission manager make real-time decisions as to the effectiveness of the flight. This data is displayed for the mission manager and broadcast to the other experiments on the aircraft for inclusion in their data files. The program also drives real-time precision pitch and roll displays for the pilot and copilot to aid them in maintaining the desired attitude, when required, during data acquisition on mapping lines.

  9. Hydrometeorological Automated Data System

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Office of Hydrologic Development of the National Weather Service operates HADS, the Hydrometeorological Automated Data System. This data set contains the last 48...

  10. Planetary Data System (PDS)

    Data.gov (United States)

    National Aeronautics and Space Administration — The Planetary Data System (PDS) is an archive of data products from NASA planetary missions, which is sponsored by NASA's Science Mission Directorate. We actively...

  11. Longline Observer Data System

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LODS, the Hawaii Longline Observer Data System, is a complete suite of tools designed to collect, process, and manage quality fisheries data and information. Guided...

  12. Signal system data mining

    Science.gov (United States)

    2000-09-01

    Intelligent transportation systems (ITS) include large numbers of traffic sensors that collect enormous quantities of data. The data provided by ITS is necessary for advanced forms of control, however basic forms of control, primarily time-of-day (TO...

  13. The state of the art in intrusion prevention and detection

    CERN Document Server

    Pathan, Al-Sakib Khan

    2013-01-01

    The State of the Art in Intrusion Prevention and Detection analyzes the latest trends and issues surrounding intrusion detection systems in computer networks, especially in communications networks. Its broad scope of coverage includes wired, wireless, and mobile networks; next-generation converged networks; and intrusion in social networks.Presenting cutting-edge research, the book presents novel schemes for intrusion detection and prevention. It discusses tracing back mobile attackers, secure routing with intrusion prevention, anomaly detection, and AI-based techniques. It also includes infor

  14. MAST data acquisition system

    International Nuclear Information System (INIS)

    Shibaev, S.; Counsell, G.; Cunningham, G.; Manhood, S.J.; Thomas-Davies, N.; Waterhouse, J.

    2006-01-01

    The data acquisition system of the Mega-Amp Spherical Tokamak (MAST) presently collects up to 400 MB of data in about 3000 data items per shot, and subsequent fast growth is expected. Since the start of MAST operations (in 1999) the system has changed dramatically. Though we continue to use legacy CAMAC hardware, newer VME, PCI, and PXI based sub-systems collect most of the data now. All legacy software has been redesigned and new software has been developed. Last year a major system improvement was made-replacement of the message distribution system. The new message system provides easy connection of any sub-system independently of its platform and serves as a framework for many new applications. A new data acquisition controller provides full control of common sub-systems, central error logging, and data acquisition alarms for the MAST plant. A number of new sub-systems using Linux and Windows OSs on VME, PCI, and PXI platforms have been developed. A new PXI unit has been designed as a base sub-system accommodating any type of data acquisition and control devices. Several web applications for the real-time MAST monitoring and data presentation have been developed

  15. Managing Schools as Complex Adaptive Systems: A Strategic Perspective

    Science.gov (United States)

    Fidan, Tuncer; Balci, Ali

    2017-01-01

    This conceptual study examines the analogies between schools and complex adaptive systems and identifies strategies used to manage schools as complex adaptive systems. Complex adaptive systems approach, introduced by the complexity theory, requires school administrators to develop new skills and strategies to realize their agendas in an…

  16. Changing Paradigms: From Schooling to Schools as Adaptive Recommendation Systems

    Science.gov (United States)

    Petersen, Anne Kristine; Christiansen, Rene B.; Gynther, Karsten

    2017-01-01

    The paper explores a shift in education from educational systems requiring student adaptation to educational recommendation systems adapting to students' individual needs. The paper discusses the concept of adaptation as addressed in educational research and draws on the system theory of Heinz von Foerster to shed light on how the educational…

  17. Adaptive pseudolinear compensators of dynamic characteristics of automatic control systems

    Science.gov (United States)

    Skorospeshkin, M. V.; Sukhodoev, M. S.; Timoshenko, E. A.; Lenskiy, F. V.

    2016-04-01

    Adaptive pseudolinear gain and phase compensators of dynamic characteristics of automatic control systems are suggested. The automatic control system performance with adaptive compensators has been explored. The efficiency of pseudolinear adaptive compensators in the automatic control systems with time-varying parameters has been demonstrated.

  18. Intrusion Detection Algorithm for Mitigating Sinkhole Attack on LEACH Protocol in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ranjeeth Kumar Sundararajan

    2015-01-01

    Full Text Available In wireless sensor network (WSN, the sensors are deployed and placed uniformly to transmit the sensed data to a centralized station periodically. So, the major threat of the WSN network layer is sinkhole attack and it is still being a challenging issue on the sensor networks, where the malicious node attracts the packets from the other normal sensor nodes and drops the packets. Thus, this paper proposes an Intrusion Detection System (IDS mechanism to detect the intruder in the network which uses Low Energy Adaptive Clustering Hierarchy (LEACH protocol for its routing operation. In the proposed algorithm, the detection metrics, such as number of packets transmitted and received, are used to compute the intrusion ratio (IR by the IDS agent. The computed numeric or nonnumeric value represents the normal or malicious activity. As and when the sinkhole attack is captured, the IDS agent alerts the network to stop the data transmission. Thus, it can be a resilient to the vulnerable attack of sinkhole. Above all, the simulation result is shown for the proposed algorithm which is proven to be efficient compared with the existing work, namely, MS-LEACH, in terms of minimum computational complexity and low energy consumption. Moreover, the algorithm was numerically analyzed using TETCOS NETSIM.

  19. Four-dimensional cone beam CT with adaptive gantry rotation and adaptive data sampling

    International Nuclear Information System (INIS)

    Lu Jun; Guerrero, Thomas M.; Munro, Peter; Jeung, Andrew; Chi, P.-C. M.; Balter, Peter; Zhu, X. Ronald; Mohan, Radhe; Pan Tinsu

    2007-01-01

    We have developed a new four-dimensional cone beam CT (4D-CBCT) on a Varian image-guided radiation therapy system, which has radiation therapy treatment and cone beam CT imaging capabilities. We adapted the speed of gantry rotation time of the CBCT to the average breath cycle of the patient to maintain the same level of image quality and adjusted the data sampling frequency to keep a similar level of radiation exposure to the patient. Our design utilized the real-time positioning and monitoring system to record the respiratory signal of the patient during the acquisition of the CBCT data. We used the full-fan bowtie filter during data acquisition, acquired the projection data over 200 deg of gantry rotation, and reconstructed the images with a half-scan cone beam reconstruction. The scan time for a 200-deg gantry rotation per patient ranged from 3.3 to 6.6 min for the average breath cycle of 3-6 s. The radiation dose of the 4D-CBCT was about 1-2 times the radiation dose of the 4D-CT on a multislice CT scanner. We evaluated the 4D-CBCT in scanning, data processing and image quality with phantom studies. We demonstrated the clinical applicability of the 4D-CBCT and compared the 4D-CBCT and the 4D-CT scans in four patient studies. The contrast-to-noise ratio of the 4D-CT was 2.8-3.5 times of the contrast-to-noise ratio of the 4D-CBCT in the four patient studies

  20. Environmental data qualification system

    International Nuclear Information System (INIS)

    Hester, O.V.; Groh, M.R.

    1989-01-01

    The Integrated Environmental Data Management System (IEDMS) is a PC-based system that can support environmental investigations from their design stage and throughout the duration of the study. The system integrates data originating from the Sampling and Analysis Plan, field data and analytical findings. The IEDMS automated features include sampling guidance forms, barcoded sample labels and tags, field and analytical forms reproduction, sample tracking, analytical data qualification, completeness reports, and results and QC data reporting. The IEDMS has extensive automated capabilities that support a systematic and comprehensive process for performing quality assessment of EPA-CLP chemical analyses data. One product of this process is a unique and extremely useful tabular presentation of the data. One table contains the complete set of results and QC data included on the CLP data forms while presenting the information consistent with the chronology in which the analysis was performed. 3 refs., 1 fig

  1. DIRAC Data Management System

    CERN Document Server

    Smith, A C

    2007-01-01

    The LHCb experiment being built to utilize CERN’s flagship Large Hadron Collider will generate data to be analysed by a community of over 600 physicists worldwide. DIRAC, LHCb’s Workload and Data Management System, facilitates the use of underlying EGEE Grid resources to generate, process and analyse this data in the distributed environment. The Data Management System, presented here, provides real-time, data-driven distribution in accordance with LHCb’s Computing Model. The data volumes produced by the LHC experiments are unprecedented, rendering individual institutes and even countries, unable to provide the computing and storage resources required to make full use of the produced data. EGEE Grid resources allow the processing of LHCb data possible in a distributed fashion and LHCb’s Computing Model is based on this approach. Data Management in this environment requires reliable and high-throughput transfer of data, homogeneous access to storage resources and the cataloguing of data replicas, all of...

  2. USING THE ADAPTED DLP SYSTEM FOR BLOCKING INFORMATION LEAKS

    Directory of Open Access Journals (Sweden)

    T. A. Andryianava

    2017-01-01

    Full Text Available The importance of using the adapted DLP-system in the «Blocking» mode of leaking confidential information of the company is investigated. The scheme of interception of information security events in the «Copy» mode is given, the analysis of which reflects the main drawback of using this mode – the DLP-system works only with copies of confidential documents, while the originals were delivered to the recipient. Such cases inflict enormous damage on companies, so the transfer of critical information beyond the corporate network is unacceptable.A solution is proposed for transferring the operation of the DLP-system from the «Copy» mode to the «Blocking» mode. It is important that the operation of the DLP-system does not hinder the staff members from performing regular operations and does not hinder business processes. Therefore, it is mandatory to adapt the standard DLP-system to the specifics of the company’s activities. After that the transition of the adapted DLP-system to the «Blocking» mode is carried out.Developed: the transition procedure of the adapted DLP-system from the «Copy» mode to the «Blocking» mode, the scheme of the event capture by the DLP-system for the two modes. The main channels of data leaks were investigated, the main leaks were identified by the data type and by the transmission channel. The analysis of the DLP-system operation in the «Blocking» mode is performed.

  3. Adaptive Restoration of Airborne Daedalus AADS1268 ATM Thermal Data

    International Nuclear Information System (INIS)

    D. Yuan; E. Doak; P. Guss; A. Will

    2002-01-01

    To incorporate the georegistration and restoration processes into airborne data processing in support of U.S. Department of Energy's nuclear emergency response task, we developed an adaptive restoration filter for airborne Daedalus AADS1268 ATM thermal data based on the Wiener filtering theory. Preliminary assessment shows that this filter enhances the detectability of small weak thermal anomalies in AADS1268 thermal images

  4. TOPEX ground data system

    Science.gov (United States)

    Rosell, S. N.; Yamarone, C. A., Jr.

    The TOPEX Project is a proposed oceanographic mission to measure the topography of the sea surface for a period of three years. This mission is sponsored by the National Aeronautics and Space Administration and managed by the Jet Propulsion Laboratory. Measurements of topography are used to study ocean currents, tides, bathymetry and the oceanic geoid. Several of the primary goals of this mission are to process and verify the altimetric data, and distribute them within days to the science investigators. This paper describes the TOPEX end-to-end ground data system. In addition to controlling the TOPEX satellite, the ground data system has been designed to minimize the time from data acquisition to science processing and data distribution. A centralized design supports the favorable response time of the system and also allows for operational efficiencies. Networking of real time and non-real time elements of the data system provides for more effective data processing.

  5. Smarter Earth Science Data System

    Science.gov (United States)

    Huang, Thomas

    2013-01-01

    The explosive growth in Earth observational data in the recent decade demands a better method of interoperability across heterogeneous systems. The Earth science data system community has mastered the art in storing large volume of observational data, but it is still unclear how this traditional method scale over time as we are entering the age of Big Data. Indexed search solutions such as Apache Solr (Smiley and Pugh, 2011) provides fast, scalable search via keyword or phases without any reasoning or inference. The modern search solutions such as Googles Knowledge Graph (Singhal, 2012) and Microsoft Bing, all utilize semantic reasoning to improve its accuracy in searches. The Earth science user community is demanding for an intelligent solution to help them finding the right data for their researches. The Ontological System for Context Artifacts and Resources (OSCAR) (Huang et al., 2012), was created in response to the DARPA Adaptive Vehicle Make (AVM) programs need for an intelligent context models management system to empower its terrain simulation subsystem. The core component of OSCAR is the Environmental Context Ontology (ECO) is built using the Semantic Web for Earth and Environmental Terminology (SWEET) (Raskin and Pan, 2005). This paper presents the current data archival methodology within a NASA Earth science data centers and discuss using semantic web to improve the way we capture and serve data to our users.

  6. Assessment of permeation quality of concrete through mercury intrusion porosimetry

    International Nuclear Information System (INIS)

    Kumar, Rakesh; Bhattacharjee, B.

    2004-01-01

    Permeation quality of laboratory cast concrete beams was determined through initial surface absorption test (ISAT). The pore system characteristics of the same concrete beam specimens were determined through mercury intrusion porosimetry (MIP). Data so obtained on the measured initial surface absorption rate of water by concrete and characteristics of pore system of concrete estimated from porosimetry results were used to develop correlations between them. Through these correlations, potential of MIP in assessing the durability quality of concrete in actual structure is demonstrated

  7. The Adaptive Immune System of Haloferax volcanii

    Directory of Open Access Journals (Sweden)

    Lisa-Katharina Maier

    2015-02-01

    Full Text Available To fight off invading genetic elements, prokaryotes have developed an elaborate defence system that is both adaptable and heritable—the CRISPR-Cas system (CRISPR is short for: clustered regularly interspaced short palindromic repeats and Cas: CRISPR associated. Comprised of proteins and multiple small RNAs, this prokaryotic defence system is present in 90% of archaeal and 40% of bacterial species, and enables foreign intruders to be eliminated in a sequence-specific manner. There are three major types (I–III and at least 14 subtypes of this system, with only some of the subtypes having been analysed in detail, and many aspects of the defence reaction remaining to be elucidated. Few archaeal examples have so far been analysed. Here we summarize the characteristics of the CRISPR-Cas system of Haloferax volcanii, an extremely halophilic archaeon originally isolated from the Dead Sea. It carries a single CRISPR-Cas system of type I-B, with a Cascade like complex composed of Cas proteins Cas5, Cas6b and Cas7. Cas6b is essential for CRISPR RNA (crRNA maturation but is otherwise not required for the defence reaction. A systematic search revealed that six protospacer adjacent motif (PAM sequences are recognised by the Haloferax defence system. For successful invader recognition, a non-contiguous seed sequence of 10 base-pairs between the crRNA and the invader is required.

  8. Online data processing system

    International Nuclear Information System (INIS)

    Nakahara, Yoshinori; Yagi, Hideyuki; Yamada, Takayuki

    1979-02-01

    A pulse height analyzer terminal system PHATS has been developed for online data processing via JAERI-TOKAI computer network. The system is controled by using a micro-computer MICRO-8 which was developed for the JAERI-TOKAI network. The system program consists of two subprograms, online control system ONLCS and pulse height analyzer control system PHACS. ONLCS links the terminal with the conversational programming system of FACOM 230/75 through the JAERI-TOKAI network and controls data processing in TSS and remote batch modes. PHACS is used to control INPUT/OUTPUT of data between pulse height analyzer and cassette-MT or typewriter. This report describes the hardware configuration and the system program in detail. In the appendix, explained are real time monitor, type of message, PEX to PEX protocol and Host to Host protocol, required for the system programming. (author)

  9. Adaptive cyber-attack modeling system

    Science.gov (United States)

    Gonsalves, Paul G.; Dougherty, Edward T.

    2006-05-01

    The pervasiveness of software and networked information systems is evident across a broad spectrum of business and government sectors. Such reliance provides an ample opportunity not only for the nefarious exploits of lone wolf computer hackers, but for more systematic software attacks from organized entities. Much effort and focus has been placed on preventing and ameliorating network and OS attacks, a concomitant emphasis is required to address protection of mission critical software. Typical software protection technique and methodology evaluation and verification and validation (V&V) involves the use of a team of subject matter experts (SMEs) to mimic potential attackers or hackers. This manpower intensive, time-consuming, and potentially cost-prohibitive approach is not amenable to performing the necessary multiple non-subjective analyses required to support quantifying software protection levels. To facilitate the evaluation and V&V of software protection solutions, we have designed and developed a prototype adaptive cyber attack modeling system. Our approach integrates an off-line mechanism for rapid construction of Bayesian belief network (BN) attack models with an on-line model instantiation, adaptation and knowledge acquisition scheme. Off-line model construction is supported via a knowledge elicitation approach for identifying key domain requirements and a process for translating these requirements into a library of BN-based cyber-attack models. On-line attack modeling and knowledge acquisition is supported via BN evidence propagation and model parameter learning.

  10. MPS Data Acquisition System

    International Nuclear Information System (INIS)

    Eiseman, S.E.; Miller, W.J.

    1975-01-01

    A description is given of the data acquisition system used with the multiparticle spectrometer facility at Brookhaven. Detailed information is provided on that part of the system which connects the detectors to the data handler; namely, the detector electronics, device controller, and device port optical isolator

  11. Atomic switch networks as complex adaptive systems

    Science.gov (United States)

    Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

    2018-03-01

    Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

  12. Adaptive Control of the Chaotic System via Singular System Approach

    Directory of Open Access Journals (Sweden)

    Yudong Li

    2014-01-01

    Full Text Available This paper deals with the control problem of the chaotic system subject to disturbance. The sliding mode surface is designed by singular system approach, and sufficient condition for convergence is given. Then, the adaptive sliding mode controller is designed to make the state arrive at the sliding mode surface in finite time. Finally, Lorenz system is considered as an example to show the effectiveness of the proposed method.

  13. Adaptive lag synchronization and parameters adaptive lag identification of chaotic systems

    Energy Technology Data Exchange (ETDEWEB)

    Xu Yuhua, E-mail: yuhuaxu2004@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Department of Mathematics, Yunyang Teachers' College, Hubei, Shiyan 442000 (China); Zhou Wuneng, E-mail: wnzhou@163.co [College of Information Science and Technology, Donghua University, Shanghai 201620 (China) and Key Laboratory of Wireless Sensor Network and Communication, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050 (China); Fang Jian' an, E-mail: jafang@dhu.edu.c [College of Information Science and Technology, Donghua University, Shanghai 201620 (China); Sun Wen, E-mail: sunwen_2201@163.co [School of Mathematics and Information, Yangtze University, Hubei, Jingzhou 434023 (China)

    2010-07-26

    This Letter investigates the problem of adaptive lag synchronization and parameters adaptive lag identification of chaotic systems. In comparison with those of existing parameters identification schemes, the unknown parameters are identified by adaptive lag laws, and the delay time is also identified in this Letter. Numerical simulations are also given to show the effectiveness of the proposed method.

  14. CMAC-based adaptive backstepping synchronization of uncertain chaotic systems

    International Nuclear Information System (INIS)

    Lin, C.-M.; Peng, Y.-F.; Lin, M.-H.

    2009-01-01

    This study proposes an adaptive backstepping control system for synchronizing uncertain chaotic system by using cerebellar model articulation controller (CMAC). CMAC is a nonlinear network with simple computation, good generalization capability and fast learning property. The proposed CMAC-based adaptive backstepping control (CABC) system uses backstepping method and adaptive cerebellar model articulation controller (ACMAC) for synchronizing uncertain chaotic system. Finally, simulation results for the Genesio system are presented to illustrate the effectiveness of the proposed control system.

  15. Robust adaptive optics systems for vision science

    Science.gov (United States)

    Burns, S. A.; de Castro, A.; Sawides, L.; Luo, T.; Sapoznik, K.

    2018-02-01

    Adaptive Optics (AO) is of growing importance for understanding the impact of retinal and systemic diseases on the retina. While AO retinal imaging in healthy eyes is now routine, AO imaging in older eyes and eyes with optical changes to the anterior eye can be difficult and requires a control and an imaging system that is resilient when there is scattering and occlusion from the cornea and lens, as well as in the presence of irregular and small pupils. Our AO retinal imaging system combines evaluation of local image quality of the pupil, with spatially programmable detection. The wavefront control system uses a woofer tweeter approach, combining an electromagnetic mirror and a MEMS mirror and a single Shack Hartmann sensor. The SH sensor samples an 8 mm exit pupil and the subject is aligned to a region within this larger system pupil using a chin and forehead rest. A spot quality metric is calculated in real time for each lenslet. Individual lenslets that do not meet the quality metric are eliminated from the processing. Mirror shapes are smoothed outside the region of wavefront control when pupils are small. The system allows imaging even with smaller irregular pupils, however because the depth of field increases under these conditions, sectioning performance decreases. A retinal conjugate micromirror array selectively directs mid-range scatter to additional detectors. This improves detection of retinal capillaries even when the confocal image has poorer image quality that includes both photoreceptors and blood vessels.

  16. Development of an Assessment Procedure for Seawater Intrusion Mitigation

    Science.gov (United States)

    Hsi Ting, F.; Yih Chi, T.

    2017-12-01

    The Pingtung Plain is one of the areas with extremely plentiful groundwater resources in Taiwan. Due to that the application of the water resource is restricted by significant variation of precipitation between wet and dry seasons, groundwater must be used as a recharge source to implement the insufficient surface water resource during dry seasons. In recent years, the coastal aquaculture rises, and the over withdrawn of groundwater by private well results in fast drop of groundwater level. Then it causes imbalance of groundwater supply and leads to serious seawater intrusion in the coastal areas. The purpose of this study is to develop an integrated numerical model of groundwater resources and seawater intrusion. Soil and Water Assessment Tool (SWAT), MODFLOW and MT3D models were applied to analyze the variation of the groundwater levels and salinity concentration to investigate the correlation of parameters, which are used to the model applications in order to disposal saltwater intrusion. The data of groundwater levels, pumping capacity and hydrogeological data to were collected to build an integrated numerical model. Firstly, we will collect the information of layered aquifer and the data of hydrological parameters to build the groundwater numerical model at Pingtung Plain, and identify the amount of the groundwater which flow into the sea. In order to deal with the future climate change conditions or extreme weather conditions, we will consider the recharge with groundwater model to improve the seawater intrusion problem. The integrated numerical model which describes that seawater intrusion to deep confined aquifers and shallow unsaturated aquifers. Secondly, we will use the above model to investigate the weights influenced by different factors to the amount area of seawater intrusion, and predict the salinity concentration distribution of evaluation at coastal area of Pingtung Plain. Finally, we will simulate groundwater recharge/ injection at the coastal

  17. TFTR data management system

    International Nuclear Information System (INIS)

    Randerson, L.; Chu, J.; Ludescher, C.; Malsbury, J.; Stark, W.

    1986-01-01

    Developments in the tokamak fusion test reactor (TFTR) data management system supporting data management system supporting data acquisition and off-line physics data reduction are described. Data from monitor points, timing channels, and transient recorder channels and other devices are acquired and stored for use by on-line tasks. Files are transferred off-line automatically. A configuration utility determines data acquired and files transferred. An event system driven by file arrival activates off-line reduction processes. A post-run process transfers files not shipped during runs. Files are archived to tape and are retrievable by digraph and shot number. Automatic skimming based on most recent access, file type, shot numbers, and user-set protection maintains the files required for post-run data reduction

  18. Data management in the mission data system

    Science.gov (United States)

    Wagner, David A.

    2005-01-01

    As spacecraft evolve from simple embedded devices to become more sophisticated computing platforms with complex behaviors it is increasingly necessary to model and manage the flow of data, and to provide uniform models for managing data that promote adaptability, yet pay heed to the physical limitations of the embedded and space environments.

  19. Autonomous Rule Creation for Intrusion Detection

    Energy Technology Data Exchange (ETDEWEB)

    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.

  20. Engineering the presentation layer of adaptable web information systems

    NARCIS (Netherlands)

    Fiala, Z.; Frasincar, F.; Hinz, M.; Houben, G.J.P.M.; Barna, P.; Meissner, K.; Koch, N.; Fraternali, P.; Wirsing, M.

    2004-01-01

    Engineering adaptable Web Information Systems (WIS) requires systematic design models and specification frameworks. A complete model-driven methodology like Hera distinguishes between the conceptual, navigational, and presentational aspects of WIS design and identifies different adaptation hot-spots

  1. Specification and Generation of Adapters for System Integration

    NARCIS (Netherlands)

    Mooij, A.J.; Voorhoeve, M.

    2013-01-01

    Large systems-of-systems are developed by integrating several smaller systems that have been developed independently. System integration often requires adaptation mechanisms for bridging any technical incompatibilities between the systems. In order to develop adapters in a faster way, we study ways

  2. Flexible data acquisition system

    Energy Technology Data Exchange (ETDEWEB)

    Clout, P N; Ridley, P A [Science Research Council, Daresbury (UK). Daresbury Lab.

    1978-06-01

    A data acquisition system has been developed which enables several independent experiments to be controlled by a 24 K word PDP-11 computer. Significant features of the system are the use of CAMAC, a high level language (RTL/2) and a general-purpose operating system executive which assist the rapid implementation of new experiments. This system has been used successfully for EXAFS and photo-electron spectroscopy experiments. It is intended to provide powerful concurrent data analysis and feedback facilities to the experimenter by on-line connection to the central IBM 370/165 computer.

  3. Intelligent Optical Systems Using Adaptive Optics

    Science.gov (United States)

    Clark, Natalie

    2012-01-01

    Until recently, the phrase adaptive optics generally conjured images of large deformable mirrors being integrated into telescopes to compensate for atmospheric turbulence. However, the development of smaller, cheaper devices has sparked interest for other aerospace and commercial applications. Variable focal length lenses, liquid crystal spatial light modulators, tunable filters, phase compensators, polarization compensation, and deformable mirrors are becoming increasingly useful for other imaging applications including guidance navigation and control (GNC), coronagraphs, foveated imaging, situational awareness, autonomous rendezvous and docking, non-mechanical zoom, phase diversity, and enhanced multi-spectral imaging. The active components presented here allow flexibility in the optical design, increasing performance. In addition, the intelligent optical systems presented offer advantages in size and weight and radiation tolerance.

  4. Seismic data acquisition systems

    International Nuclear Information System (INIS)

    Kolvankar, V.G.; Nadre, V.N.; Rao, D.S.

    1989-01-01

    Details of seismic data acquisition systems developed at the Bhabha Atomic Research Centre, Bombay are reported. The seismic signals acquired belong to different signal bandwidths in the band from 0.02 Hz to 250 Hz. All these acquisition systems are built around a unique technique of recording multichannel data on to a single track of an audio tape and in digital form. Techniques of how these signals in different bands of frequencies were acquired and recorded are described. Method of detecting seismic signals and its performance is also discussed. Seismic signals acquired in different set-ups are illustrated. Time indexing systems for different set-ups and multichannel waveform display systems which form essential part of the data acquisition systems are also discussed. (author). 13 refs., 6 figs., 1 tab

  5. Network Intrusion Dataset Assessment

    Science.gov (United States)

    2013-03-01

    International Conference on Computational Intelligence and Natural Computing, volume 2, pages 413–416, June 2009. • Rung Ching Chen, Kai -Fan Cheng, and...Chia-Fen Hsieh . “Using rough set and support vector machine for network intrusion detection.” International Journal of Network Security & Its...intrusion detection using FP tree rules.” Journal Of Advanced Networking and Applications, 1(1):30–39, 2009. • Ming-Yang Su, Gwo-Jong Yu , and Chun-Yuen

  6. Adaptation to Poverty in Long-Run Panel Data

    OpenAIRE

    Clark , Andrew E.; D'Ambrosio , Conchita; Ghislandi , Simone

    2014-01-01

    I31, D60; We consider the link between poverty and subjective well-being, and focus in particular on potential adaptation to poverty. We use panel data on almost 45,800 individuals living in Germany from 1992 to 2011 to show first that life satisfaction falls with both the incidence and intensity of contemporaneous poverty. We then reveal that there is little evidence of adaptation within a poverty spell: poverty starts bad and stays bad in terms of subjective well-being. We cannot identify a...

  7. TFTR data management system

    International Nuclear Information System (INIS)

    Randerson, L.; Chu, J.; Ludescher, C.; Malsbury, J.; Stark, W.

    1986-01-01

    Developments in the tokamak fusion test reactor (TFTR) data-management system supporting data acquisition and off-line physics data reduction are described. Data from monitor points, timing channels, transient recorder channels, and other devices are acquired and stored for use by on-line tasks. Files are transferred off line automatically. A configuration utility determines data acquired and files transferred. An event system driven by file arrival activates off-line reduction processes. A post-run process transfers files not shipped during runs. Files are archived to tape and are retrievable by digraph and shot number. Automatic skimming based on most recent access, file type, shot numbers, and user-set protections maintains the files required for post-run data reduction

  8. Information Quality Aware Data Collection for Adaptive Monitoring of Distribution Grids

    DEFF Research Database (Denmark)

    Kemal, Mohammed Seifu; Olsen, Rasmus Løvenstein; Schwefel, Hans-Peter

    2017-01-01

    frequency during run time. The data collection system should adapt to changing dynamics of the communication network and electrical grid. This paper first introduces adaptation functionalities for the data collection mechanism. To study and analyse the influence of configuration parameters that can......Abstract. Information from existing smart metering infrastructure, mainly used for billing purposes can also be utilised to monitor and control state of the grid. To add functionalities such as fault detection and real-time state estimation, data from smart meters should be accessed with increased...... be utilised for adaptation, a two-layer smart meter data access infrastructure is presented. An information quality metric, Mismatch Probability (mmPr) is introduced for the quantitative analysis of the two-layer data access system implemented in MATLAB based discrete event simulation study....

  9. Data-acquisition systems

    International Nuclear Information System (INIS)

    Cyborski, D.R.; Teh, K.M.

    1995-01-01

    Up to now, DAPHNE, the data-acquisition system developed for ATLAS, was used routinely for experiments at ATLAS and the Dynamitron. More recently, the Division implemented 2 MSU/DAPHNE systems. The MSU/DAPHNE system is a hybrid data-acquisition system which combines the front-end of the Michigan State University (MSU) DA system with the traditional DAPHNE back-end. The MSU front-end is based on commercially available modules. This alleviates the problems encountered with the DAPHNE front-end which is based on custom designed electronics. The first MSU system was obtained for the APEX experiment and was used there successfully. A second MSU front-end, purchased as a backup for the APEX experiment, was installed as a fully-independent second MSU/DAPHNE system with the procurement of a DEC 3000 Alpha host computer, and was used successfully for data-taking in an experiment at ATLAS. Additional hardware for a third system was bought and will be installed. With the availability of 2 MSU/DAPHNE systems in addition to the existing APEX setup, it is planned that the existing DAPHNE front-end will be decommissioned

  10. On the Performance of Adaptive Data Rate over Deep Space Ka-Bank Link: Case Study Using Kepler Data

    Science.gov (United States)

    Gao, Jay L.

    2016-01-01

    Future missions envisioned for both human and robotic exploration demand increasing communication capacity through the use of Ka-band communications. The Ka-band channel, being more sensitive to weather impairments, presents a unique trade-offs between data storage, latency, data volume and reliability. While there are many possible techniques for optimizing Ka-band operations such as adaptive modulation and coding and site-diversity, this study focus exclusively on the use of adaptive data rate (ADR) to achieve significant improvement in the data volume-availability tradeoff over a wide range of link distances for near Earth and Mars exploration. Four years of Kepler Ka-band downlink symbol signal-to-noise (SNR) data reported by the Deep Space Network were utilized to characterize the Ka-band channel statistics at each site and conduct various what-if performance analysis for different link distances. We model a notional closed-loop adaptive data rate system in which an algorithm predicts the channel condition two-way light time (TWLT) into the future using symbol SNR reported in near-real time by the ground receiver and determines the best data rate to use. Fixed and adaptive margins were used to mitigate errors in channel prediction. The performance of this closed-loop adaptive data rate approach is quantified in terms of data volume and availability and compared to the actual mission configuration and a hypothetical, optimized single rate configuration assuming full a priori channel knowledge.

  11. Beyond Low Rank: A Data-Adaptive Tensor Completion Method

    OpenAIRE

    Zhang, Lei; Wei, Wei; Shi, Qinfeng; Shen, Chunhua; Hengel, Anton van den; Zhang, Yanning

    2017-01-01

    Low rank tensor representation underpins much of recent progress in tensor completion. In real applications, however, this approach is confronted with two challenging problems, namely (1) tensor rank determination; (2) handling real tensor data which only approximately fulfils the low-rank requirement. To address these two issues, we develop a data-adaptive tensor completion model which explicitly represents both the low-rank and non-low-rank structures in a latent tensor. Representing the no...

  12. Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

    Science.gov (United States)

    Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

    2017-10-01

    The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

  13. Adaptive Systems in Education: A Review and Conceptual Unification

    Science.gov (United States)

    Wilson, Chunyu; Scott, Bernard

    2017-01-01

    Purpose: The purpose of this paper is to review the use of adaptive systems in education. It is intended to be a useful introduction for the non-specialist reader. Design/methodology/approach: A distinction is made between intelligent tutoring systems (ITSs) and adaptive hypermedia systems (AHSs). The two kinds of system are defined, compared and…

  14. Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

    KAUST Repository

    Rakia, Tamer; Yang, Hong-Chuan; Gebali, Fayez; Alouini, Mohamed-Slim

    2016-01-01

    Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non

  15. Quantifying adaptive evolution in the Drosophila immune system.

    Directory of Open Access Journals (Sweden)

    Darren J Obbard

    2009-10-01

    Full Text Available It is estimated that a large proportion of amino acid substitutions in Drosophila have been fixed by natural selection, and as organisms are faced with an ever-changing array of pathogens and parasites to which they must adapt, we have investigated the role of parasite-mediated selection as a likely cause. To quantify the effect, and to identify which genes and pathways are most likely to be involved in the host-parasite arms race, we have re-sequenced population samples of 136 immunity and 287 position-matched non-immunity genes in two species of Drosophila. Using these data, and a new extension of the McDonald-Kreitman approach, we estimate that natural selection fixes advantageous amino acid changes in immunity genes at nearly double the rate of other genes. We find the rate of adaptive evolution in immunity genes is also more variable than other genes, with a small subset of immune genes evolving under intense selection. These genes, which are likely to represent hotspots of host-parasite coevolution, tend to share similar functions or belong to the same pathways, such as the antiviral RNAi pathway and the IMD signalling pathway. These patterns appear to be general features of immune system evolution in both species, as rates of adaptive evolution are correlated between the D. melanogaster and D. simulans lineages. In summary, our data provide quantitative estimates of the elevated rate of adaptive evolution in immune system genes relative to the rest of the genome, and they suggest that adaptation to parasites is an important force driving molecular evolution.

  16. An adaptive interface (KNOWBOT) for nuclear power industry data bases

    International Nuclear Information System (INIS)

    Heger, A.S.

    1989-01-01

    An adaptive interface, KNOWBOT, has been designed to solve some of the problems that face the users of large centralized databases. The interface applies the neural network approach to information retrieval from a database. The database is a subset of the Nuclear Plant Reliability Data System (NPRDS). KNOWBOT preempts an existing database interface and works in conjunction with it. By design, KNOWBOT starts as a tabula rasa but acquires knowledge through its interactions with the user and the database. The interface uses its gained knowledge to personalize the database retrieval process and to induce new queries. In addition, the interface forgets the information that is no longer needed by the user. These self-organizing features of the interface reduce the scope of the database to the subsets that are highly relevant to the user needs. A proof-of-principle version of this interface has been implemented in Common LISP on a Texas Instruments Explorer I workstation. Experiments with KNOWBOT have successfully demonstrated the robustness of the model especially with induction and self-organization

  17. IPNS data acquisition system

    International Nuclear Information System (INIS)

    Worlton, T.G.; Crawford, R.K.; Haumann, J.R.; Daly, R.

    1983-01-01

    The IPNS Data Acquisition System (DAS) was designed to be reliable, flexible, and easy to use. It provides unique methods of acquiring Time-of-Flight neutron scattering data and allows collection, storage, display, and analysis of very large data arrays with a minimum of user input. Data can be collected from normal detectors, linear position-sensitive detectors, and/or area detectors. The data can be corrected for time-delays and can be time-focussed before being binned. Corrections to be made to the data and selection of inputs to be summed are entirely software controlled, as are the time ranges and resolutions for each detector element. Each system can be configured to collect data into millions of channels. Maximum continuous data rates are greater than 2000 counts/sec with full corrections, or 16,000 counts/sec for the simpler binning scheme used with area detectors. Live displays of the data may be made as a function of time, wavevector, wavelength, lattice spacing, or energy. In most cases the complete data analysis can be done on the DAS host computer. The IPNS DAS became operational for four neutron scattering instruments in 1981 and has since been expanded to seven instruments

  18. Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

    KAUST Repository

    Rakia, Tamer

    2016-02-26

    Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non- coherent hybrid FSO/RF systems, employing an adaptive combining scheme. Specifically, we activate the RF link along with the FSO link when FSO link quality is unacceptable, and adaptively set RF transmission power to ensure constant combined signal-to-noise ratio at receiver terminal. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are derived. Numerical examples show that, the hybrid FSO/RF systems with power adaptation achieve considerable outage performance improvement over conventional hybrid FSO/RF systems without power adaptation. © 2015 IEEE.

  19. The adaptive synchronization of fractional-order Liu chaotic system ...

    Indian Academy of Sciences (India)

    In this paper, the chaos control and the synchronization of two fractional-order Liu chaotic systems with unknown parameters are studied. According to the Lyapunov stabilization theory and the adaptive control theorem, the adaptive control rule is obtained for the described error dynamic stabilization. Using the adaptive rule ...

  20. Biofeedback systems and adaptive control hemodialysis treatment

    Directory of Open Access Journals (Sweden)

    Azar Ahmad

    2008-01-01

    Full Text Available On-line monitoring devices to control functions such as volume, body temperature, and ultrafiltration, were considered more toys than real tools for routine clinical application. However, bio-feedback blood volume controlled hemodialysis (HD is now possible in routine dialysis, allowing the delivery of a more physiologically acceptable treatment. This system has proved to reduce the incidence of intra-HD hypotension episodes significantly. Ionic dialysance and the patient′s plasma conductivity can be calculated easily from on-line measurements at two different steps of dialysate conductivity. A bio-feedback system has been devised to calculate the patient′s plasma conductivity and modulate the conductivity of the dialysate continuously in order to achieve a desired end-dialysis patient plasma conductivity corresponding to a desired end-dialysis plasma sodium concentration. Another bio-feedback system can control the body tempe-rature by measuring it at the arterial and venous lines of the extra-corporeal circuit, and then modulating the dialysate temperature in order to stabilize the patients′ temperature at constant values that result in improved intra-HD cardiovascular stability. The module can also be used to quantify vascular access recirculation. Finally, the simultaneous computer control of ultrafiltration has proven the most effective means for automatic blood pressure stabilization during hemo-dialysis treatment. The application of fuzzy logic in the blood-pressure-guided biofeedback con-trol of ultrafiltration during hemodialysis is able to minimize HD-induced hypotension. In con-clusion, online monitoring and adaptive control of the patient during the dialysis session using the bio-feedback systems is expected to render the process of renal replacement therapy more physiological and less eventful.