Search results for: air data system

Authors: Joon-young Jung, Dong-oh Kang, Chang-seok Bae

Abstract:

Power consumption is rapidly increased in data centers because the number of data center is increased and more the scale of data center become larger. Therefore, it is one of key research items to reduce power consumption in data center. The peak power of a typical server is around 250 watts. When a server is idle, it continues to use around 60% of the power consumed when in use, though vendors are putting effort into reducing this “idle" power load. Servers tend to work at only around a 5% to 20% utilization rate, partly because of response time concerns. An average of 10% of servers in their data centers was unused. In those reason, we propose dynamic power management system to reduce power consumption in green data center. Experiment result shows that about 55% power consumption is reduced at idle time.

Keywords: Data Center, Green IT, Management Server, Power Saving.

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Authors: Rosziati Ibrahim, Tiu Kian Yong

Abstract:

Reverse Engineering is a very important process in Software Engineering. It can be performed backwards from system development life cycle (SDLC) in order to get back the source data or representations of a system through analysis of its structure, function and operation. We use reverse engineering to introduce an automatic tool to generate system requirements from its program source codes. The tool is able to accept the Cµ programming source codes, scan the source codes line by line and parse the codes to parser. Then, the engine of the tool will be able to generate system requirements for that specific program to facilitate reuse and enhancement of the program. The purpose of producing the tool is to help recovering the system requirements of any system when the system requirements document (SRD) does not exist due to undocumented support of the system.

Keywords: System Requirements, Reverse Engineering, SourceCodes.

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Authors: Sujala.D.Shetty, S.Vadivel, Sakshi Vaghella

Abstract:

Data mining is the process of sifting through large volumes of data, analyzing data from different perspectives and summarizing it into useful information. One of the widely used desktop applications for data mining is the Weka tool which is nothing but a collection of machine learning algorithms implemented in Java and open sourced under the General Public License (GPL). A web service is a software system designed to support interoperable machine to machine interaction over a network using SOAP messages. Unlike a desktop application, a web service is easy to upgrade, deliver and access and does not occupy any memory on the system. Keeping in mind the advantages of a web service over a desktop application, in this paper we are demonstrating how this Java based desktop data mining application can be implemented as a web service to support data mining across the internet.

Keywords: desktop application, Weka mining, web service

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Authors: Charles D. Otine, Samuel B. Kucel, Lena Trojer

Abstract:

Selecting the data modeling technique for an information system is determined by the objective of the resultant data model. Dimensional modeling is the preferred modeling technique for data destined for data warehouses and data mining, presenting data models that ease analysis and queries which are in contrast with entity relationship modeling. The establishment of data warehouses as components of information system landscapes in many organizations has subsequently led to the development of dimensional modeling. This has been significantly more developed and reported for the commercial database management systems as compared to the open sources thereby making it less affordable for those in resource constrained settings. This paper presents dimensional modeling of HIV patient information using open source modeling tools. It aims to take advantage of the fact that the most affected regions by the HIV virus are also heavily resource constrained (sub-Saharan Africa) whereas having large quantities of HIV data. Two HIV data source systems were studied to identify appropriate dimensions and facts these were then modeled using two open source dimensional modeling tools. Use of open source would reduce the software costs for dimensional modeling and in turn make data warehousing and data mining more feasible even for those in resource constrained settings but with data available.

Keywords: About Database, Data Mining, Data warehouse, Dimensional Modeling, Open Source.

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Authors: Alpesh Adeshara, Rajendrasinh Jadeja, Praghnesh Bhatt

Abstract:

Implementation of advanced technologies requires sophisticated instruments that deal with the operation, control, restoration and protection of rapidly growing power system network under normal and abnormal conditions. Presently, the applications of Phasor Measurement Unit (PMU) are widely found in real time operation, monitoring, controlling and analysis of power system network as it eliminates the various limitations of supervisory control and data acquisition system (SCADA) conventionally used in power system. The use of PMU data is very rapidly increasing its importance for online and offline analysis. Wide area measurement system (WAMS) is developed as new technology by use of multiple PMUs in power system. The present paper proposes a model of Matlab based PMU using Discrete Fourier Transform (DFT) algorithm and evaluation of its operation under different contingencies. In this paper, PMU based two bus system having WAMS network is presented as a case study.

Keywords: DFT-Discrete Fourier Transform, GPS-Global Positioning System, PMU-Phasor Measurement System, WAMS-Wide Area Monitoring System.

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

Abstract:

In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: Time series, fluctuation in statistical characteristics, optimal learning.

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Authors: Aidil Azwin Zainul Abidin, Farrukh Hafiz Nagi, Agileswari K. Ramasamy, Izham Zainal Abidin

Abstract:

In power system protection, the need to know the load current together with the fault level detected by a relay is important. This is due to the fact that the relay is required to isolate the equipment being protected if a fault is present and keep the breaker associated with it closed if the current level is lower than the maximum load level. This is not an issue for a radial system. This is not the same however in a looped power system. In a looped power system, the isolation of an equipment system will contribute to a topology change. The change in the power system topology will then influence or change the maximum load current and the fault level detected by each relay. In this paper, a method of data collection for changing topology using matlab and sim-power will be presented. The method will take into consideration the change in topology and collect data for each possible topology.

Keywords: Topology Change, Power System Protection, Power System simulation, Matlab, Sim-power.

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Authors: Mountassar Maamoun, Abdelhamid Meraghni, Abdelhalim Benbelkacem, Daoud Berkani

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This paper describes an efficient hardware implementation of a new technique for interfacing the data exchange between the microprocessor-based systems and the external devices. This technique, based on the use of software/hardware system and a reduced physical address, enlarges the interfacing capacity of the microprocessor-based systems, uses the Direct Memory Access (DMA) to increases the frequency of the new bus, and improves the speed of data exchange. While using this architecture in microprocessor-based system or in computer, the input of the hardware part of our system will be connected to the bus system, and the output, which is a new bus, will be connected to an external device. The new bus is composed of a data bus, a control bus and an address bus. A Xilinx Integrated Software Environment (ISE) 7.1i has been used for the programmable logic implementation.

Keywords: Interfacing, Software/hardware System, CPLD, programmable logic, DMA.

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Authors: Chris Ewe, Naoum Jamous, Holger Schrödl

Abstract:

Like most entrepreneurs, data center operators pursue goals such as profit-maximization, improvement of the company’s reputation or basically to exist on the market. Part of those aims is to guarantee a given quality of service. Quality characteristics are specified in a contract called the service level agreement. Central part of this agreement is non-functional properties of an IT service. The system availability is one of the most important properties as it will be shown in this paper. To comply with availability requirements, data center operators can use virtualization technologies. A clear model to assess the effect of virtualization functions on the parts of a data center in relation to the system availability is still missing. This paper aims to introduce a basic model that shows these connections, and consider if the identified effects are positive or negative. Thus, this work also points out possible disadvantages of the technology. In consequence, the paper shows opportunities as well as risks of data center virtualization in relation to system availability.

Keywords: Availability, cloud computing IT service, quality of service, service level agreement, virtualization.

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Authors: Rosziati Ibrahim, Siow Yen Yen

Abstract:

System development life cycle (SDLC) is a process uses during the development of any system. SDLC consists of four main phases: analysis, design, implement and testing. During analysis phase, context diagram and data flow diagrams are used to produce the process model of a system. A consistency of the context diagram to lower-level data flow diagrams is very important in smoothing up developing process of a system. However, manual consistency check from context diagram to lower-level data flow diagrams by using a checklist is time-consuming process. At the same time, the limitation of human ability to validate the errors is one of the factors that influence the correctness and balancing of the diagrams. This paper presents a tool that automates the consistency check between Data Flow Diagrams (DFDs) based on the rules of DFDs. The tool serves two purposes: as an editor to draw the diagrams and as a checker to check the correctness of the diagrams drawn. The consistency check from context diagram to lower-level data flow diagrams is embedded inside the tool to overcome the manual checking problem.

Keywords: Data Flow Diagram, Context Diagram, ConsistencyCheck, Syntax and Semantic Rules

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Authors: Martin Juhas, Bohuslava Juhasova, Igor Halenar, Andrej Elias

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This article deals with the possibility of increasing efficiency, reliability and safety of the system for teledosimetric data collection management and their evaluation as a part of complex study for activity “Research of data collection, their measurement and evaluation with mobile and autonomous units” within project “Research of monitoring and evaluation of non-standard conditions in the area of nuclear power plants”. Possible weaknesses in existing system are identified. A study of available cluster solutions with possibility of their deploying to analysed system is presented

Keywords: Teledosimetric data, efficiency, reliability, safety, cluster solution.

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Authors: Gyoutae Park, Woosuk Kim, Sangguk Ahn, Seungmo Kim, Minjun Kim, Jinhan Lee, Youngdo Jo, Jongsam Moon, Hiesik Kim

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In this research, we designed a remote system to test parameters of gas detectors such as gas concentration and initial response time. This testing system is available to measure two gas instruments simultaneously. First of all, we assembled an experimental jig with a square structure. Those parts are included with a glass flask, two high-quality cameras, and two Ethernet modems for transmitting data. This remote gas detector testing system extracts numerals from videos with continually various gas concentrations while LCDs show photographs from cameras. Extracted numeral data are received to a laptop computer through Ethernet modem. And then, the numerical data with gas concentrations and the measured initial response speeds are recorded and graphed. Our remote testing system will be diversely applied on gas detector’s test and will be certificated in domestic and international countries.

Keywords: Gas leakage detector, inspection instrument, extracting numerals, concentration.

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Authors: Magdalena Pejas

Abstract:

This article concerns the presentation of an integrated method for detection of steganographic content embedded by new unknown programs. The method is based on data mining and aggregated hypothesis testing. The article contains the theoretical basics used to deploy the proposed detection system and the description of improvement proposed for the basic system idea. Further main results of experiments and implementation details are collected and described. Finally example results of the tests are presented.

Keywords: Steganography, steganalysis, data embedding, data mining, feature extraction, knowledge base, system learning, hypothesis testing, error estimation, black box program, file structure.

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Authors: S. Balaji, M. Rajaram

Abstract:

The method of introducing the proxy interpretation for sending and receiving requests increase the capability of the server and our approach UDIV (User-Data Identity Security) to solve the data and user authentication without extending size of the data makes better than hybrid IDS (Intrusion Detection System). And at the same time all the security stages we have framed have to pass through less through that minimize the response time of the request. Even though an anomaly detected, before rejecting it the proxy extracts its identity to prevent it to enter into system. In case of false anomalies, the request will be reshaped and transformed into legitimate request for further response. Finally we are holding the normal and abnormal requests in two different queues with own priorities.

Keywords: IDS, Data & User authentication, UDIS.

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Authors: Chakkrit Snae, Michael Brueckner

Abstract:

In this paper the authors present the framework of a system for assisting users through counseling on personal health, the Personal Health Assistance Service Expert System (PHASES). Personal health assistance systems need Personal Health Records (PHR), which support wellness activities, improve the understanding of personal health issues, enable access to data from providers of health services, strengthen health promotion, and in the end improve the health of the population. This is especially important in societies where the health costs increase at a higher rate than the overall economy. The most important elements of a healthy lifestyle are related to food (such as balanced nutrition and diets), activities for body fitness (such as walking, sports, fitness programs), and other medical treatments (such as massage, prescriptions of drugs). The PHASES framework uses an ontology of food, which includes nutritional facts, an expert system keeping track of personal health data that are matched with medical treatments, and a comprehensive data transfer between patients and the system.

Keywords: Personal health assistance service, expert system, ontologies, knowledge management, information technology.

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Authors: Ichihan Tai, Bill Olson, Paul Blessner

Abstract:

Traditional early warning systems that alarm against crisis are generally based on structured or numerical data; therefore, a system that can make predictions based on unstructured textual data, an uncorrelated data source, is a great complement to the traditional early warning systems. The Chicago Board Options Exchange (CBOE) Volatility Index (VIX), commonly referred to as the fear index, measures the cost of insurance against market crash, and spikes in the event of crisis. In this study, news data is consumed for prediction of whether there will be a market-wide crisis by predicting the movement of the fear index, and the historical references to similar events are presented in an unsupervised manner. Topic modeling-based prediction and representation are made based on daily news data between 1990 and 2015 from The Wall Street Journal against VIX index data from CBOE.

Keywords: Early Warning System, Knowledge Management, Topic Modeling, Market Prediction.

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Authors: W. Jaipahkdee, C. Srinilta

Abstract:

The overall service performance of I/O intensive system depends mainly on workload on its storage system. In heterogeneous storage environment where storage elements from different vendors with different capacity and performance are put together, workload should be distributed according to storage capability. This paper addresses data placement issue in short video sharing website. Workload contributed by a video is estimated by the number of views and life time span of existing videos in same category. Experiment was conducted on 42,000 video titles in six weeks. Result showed that the proposed algorithm distributed workload and maintained balance better than round robin and random algorithms.

Keywords: data placement, heterogeneous storage system, YouTube, short videos

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Authors: Dilek Özdemir, Gül Tekin Temur

Abstract:

In Supply Chain Management (SCM), strengthening partnerships with suppliers is a significant factor for enhancing competitiveness. Hence, firms increasingly emphasize supplier evaluation processes. Supplier evaluation systems are basically developed in terms of criteria such as quality, cost, delivery, and flexibility. Because there are many variables to be analyzed, this process becomes hard to execute and needs expertise. On this account, this study aims to develop an expert system on supplier evaluation process by designing Artificial Neural Network (ANN) that is supported with Data Envelopment Analysis (DEA). The methods are applied on the data of 24 suppliers, which have longterm relationships with a medium sized company from German Iron and Steel Industry. The data of suppliers consists of variables such as material quality (MQ), discount of amount (DOA), discount of cash (DOC), payment term (PT), delivery time (DT) and annual revenue (AR). Meanwhile, the efficiency that is generated by using DEA is added to the supplier evaluation system in order to use them as system outputs.

Keywords: Artificial Neural Network (ANN), DataEnvelopment Analysis (DEA), Supplier Evaluation System.

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Authors: T. S. Myers, J. Trevathan

Abstract:

Improvements in the data fusion and data analysis phase of research are imperative due to the exponential growth of sensed data. Currently, there are developments in the Semantic Sensor Web community to explore efficient methods for reuse, correlation and integration of web-based data sets and live data streams. This paper describes the integration of remotely sensed data with web-available static data for use in observational hypothesis testing and the analysis phase of research. The Semantic Reef system combines semantic technologies (e.g., well-defined ontologies and logic systems) with scientific workflows to enable hypothesis-based research. A framework is presented for how the data fusion concepts from the Semantic Reef architecture map to the Smart Environment Monitoring and Analysis Technologies (SEMAT) intelligent sensor network initiative. The data collected via SEMAT and the inferred knowledge from the Semantic Reef system are ingested to the Tropical Data Hub for data discovery, reuse, curation and publication.

Keywords: Information architecture, Semantic technologies Sensor networks, Ontologies.

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Authors: Hyeyoung Cho, Sungho Kim, Sik Lee

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I/O workload is a critical and important factor to analyze I/O pattern and to maximize file system performance. However to measure I/O workload on running distributed parallel file system is non-trivial due to collection overhead and large volume of data. In this paper, we measured and analyzed file system activities on two large-scale cluster systems which had TFlops level high performance computation resources. By comparing file system activities of 2009 with those of 2006, we analyzed the change of I/O workloads by the development of system performance and high-speed network technology.

Keywords: I/O workload, Lustre, GPFS, Cluster File System

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Authors: P. Jomsri

Abstract:

Currently, web usage make a huge data from a lot of user attention. In general, proxy server is a system to support web usage from user and can manage system by using hit rates. This research tries to improve hit rates in proxy system by applying data mining technique. The data set are collected from proxy servers in the university and are investigated relationship based on several features. The model is used to predict the future access websites. Association rule technique is applied to get the relation among Date, Time, Main Group web, Sub Group web, and Domain name for created model. The results showed that this technique can predict web content for the next day, moreover the future accesses of websites increased from 38.15% to 85.57 %. This model can predict web page access which tends to increase the efficient of proxy servers as a result. In additional, the performance of internet access will be improved and help to reduce traffic in networks.

Keywords: Association rule, proxy server, data mining.

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: Data mining, hybrid storage system, recurrent neural network, support vector machine.

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Authors: J. R. Wang, Y. Chiang, W. Y. Li, H. T. Lin, H. C. Chen, C. Shih, S. W. Chen

Abstract:

The dry-storage systems of nuclear power plants (NPPs) in Taiwan have become one of the major safety concerns. There are two steps considered in this study. The first step is the verification of the TRACE by using VSC-17 experimental data. The results of TRACE were similar to the VSC-17 data. It indicates that TRACE has the respectable accuracy in the simulation and analysis of the dry-storage systems. The next step is the application of TRACE in the dry-storage system of Kuosheng NPP (BWR/6). Kuosheng NPP is the second BWR NPP of Taiwan Power Company. In order to solve the storage of the spent fuels, Taiwan Power Company developed the new dry-storage system for Kuosheng NPP. In this step, the dry-storage system model of Kuosheng NPP was established by TRACE. Then, the steady state simulation of this model was performed and the results of TRACE were compared with the Kuosheng NPP data. Finally, this model was used to perform the safety analysis of Kuosheng NPP dry-storage system. Besides, FRAPTRAN was used tocalculate the transient performance of fuel rods.

Keywords: BWR, TRACE, FRAPTRAN, Dry-Storage.

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Authors: Brett E. Shelton, Joel Duffin, Yuxuan Wang, Justin Ball

Abstract:

With a growing number of digital libraries and other open education repositories being made available throughout the world, effective search and retrieval tools are necessary to access the desired materials that surpass the effectiveness of traditional, allinclusive search engines. This paper discusses the design and use of Folksemantic, a platform that integrates OpenCourseWare search, Open Educational Resource recommendations, and social network functionality into a single open source project. The paper describes how the system was originally envisioned, its goals for users, and data that provides insight into how it is actually being used. Data sources include website click-through data, query logs, web server log files and user account data. Based on a descriptive analysis of its current use, modifications to the platform's design are recommended to better address goals of the system, along with recommendations for additional phases of research.

Keywords: Digital libraries, open education, recommendation system, social networks

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Authors: Julia Moehrmann, Gunter Heidemann, Oliver Siemoneit, Christoph Hubig, Uwe-Philipp Kaeppeler, Paul Levi

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Image data holds a large amount of different context information. However, as of today, these resources remain largely untouched. It is thus the aim of this paper to present a basic technical framework which allows for a quick and easy exploitation of context information from image data especially by non-expert users. Furthermore, the proposed framework is discussed in detail concerning important social and ethical issues which demand special requirements in system design. Finally, a first sensor prototype is presented which meets the identified requirements. Additionally, necessary implications for the software and hardware design of the system are discussed, rendering a sensor system which could be regarded as a good, acceptable and justifiable technical and thereby enabling the extraction of context information from image data.

Keywords: Context-aware computing, ethical and social issues, image recognition, requirements in system design.

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Authors: Peng Li, Jun Zhou, Xin Liu, Chee Keong Ho, Xiaodan Zou, Minkyu Je

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A digital system is proposed for low power 100- channel neural recording system in this paper, which consists of 100 amplifiers, 100 analog-to-digital converters (ADC), digital controller and baseband, transceiver for data link and RF command link. The proposed system is designed in a 0.18 μm CMOS process and 65 nm CMOS process.

Keywords: multiplex, neural recording, synchronization, transceiver

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Authors: Kuo-Yang Cheng, Yi-Lun Pan, Chang-Hsing Wu, His-En Yu, Hui-Shan Chen, Weicheng Huang

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The main mission of Ezilla is to provide a friendly interface to access the virtual machine and quickly deploy the high performance computing environment. Ezilla has been developed by Pervasive Computing Team at National Center for High-performance Computing (NCHC). Ezilla integrates the Cloud middleware, virtualization technology, and Web-based Operating System (WebOS) to form a virtual computer in distributed computing environment. In order to upgrade the dataset and speedup, we proposed the sensor observation system to deal with a huge amount of data in the Cassandra database. The sensor observation system is based on the Ezilla to store sensor raw data into distributed database. We adopt the Ezilla Cloud service to create virtual machines and login into virtual machine to deploy the sensor observation system. Integrating the sensor observation system with Ezilla is to quickly deploy experiment environment and access a huge amount of data with distributed database that support the replication mechanism to protect the data security.

Keywords: Cloud, Virtualization, Cassandra, WebOS

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Authors: Qingrong Liu, Tetsuo Hayashi, Yuji Ryu

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In this paper, in order to investigate the effects of photovoltaic system introduction to detached houses in Japan, two kinds of works were done. Firstly, the hourly generation amount of a 4.2kW photovoltaic system were simulated in 46 cities to investigate the potential of the system in different regions in Japan using a simulation model of photovoltaic system. Secondly, based on the simulated electricity generation amount, the energy saving, the environmental and the economic effect of the photovoltaic system were examined from hourly to annual timescales, based upon calculations of typical electricity, heating, cooling and hot water supply load profiles for Japanese dwellings. The above analysis was carried out using a standard year-s hourly weather data for the different city provided by the Expanded AMeDAS Weather Data issued by AIJ (Architectural Institute of Japan).

Keywords: Photovoltaic system, Energy saving, Environmental effect, Japanese dwelling, Detached house.

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Authors: Iliana Marinova, Valentin Mateev

Abstract:

In this paper a computer system for electromagnetic properties measurements is designed. The system employs Agilent 4294A precision impedance analyzer to measure the amplitude and the phase of a signal applied over a tested biological tissue sample. Measured by the developed computer system data could be used for tissue characterization in wide frequency range from 40Hz to 110MHz. The computer system can interface with output devices acquiring flexible testing process.

Keywords: Electromagnetic properties, human tissue, bioimpedance, measurement system.

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Authors: Norbik Bashah, Idris Bharanidharan Shanmugam, Abdul Manan Ahmed

Abstract:

Intrusion Detection Systems are increasingly a key part of systems defense. Various approaches to Intrusion Detection are currently being used, but they are relatively ineffective. Artificial Intelligence plays a driving role in security services. This paper proposes a dynamic model Intelligent Intrusion Detection System, based on specific AI approach for intrusion detection. The techniques that are being investigated includes neural networks and fuzzy logic with network profiling, that uses simple data mining techniques to process the network data. The proposed system is a hybrid system that combines anomaly, misuse and host based detection. Simple Fuzzy rules allow us to construct if-then rules that reflect common ways of describing security attacks. For host based intrusion detection we use neural-networks along with self organizing maps. Suspicious intrusions can be traced back to its original source path and any traffic from that particular source will be redirected back to them in future. Both network traffic and system audit data are used as inputs for both.

Keywords: Intrusion Detection, Network Security, Data mining, Fuzzy Logic.

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