Search results for: Network and Information Security

Authors: Supachai Supmak, Yachai Limpiyakorn

Abstract:

Mutation testing can be applied for the quality assessment of test cases. Prioritization of mutation test generation has been a critical element of the industry practice that would contribute to the evaluation of test cases. The industry generally delivers the product under the condition of time to the market and thus, inevitably sacrifices software testing tasks, even though many test cases are required for software verification. This paper presents an approach of applying a social network centrality measure, PageRank, to prioritize mutation test generation. The source code with the highest values of PageRank, will be focused first when developing their test cases as these modules are vulnerable for defects or anomalies which may cause the consequent defects in many other associated modules. Moreover, the approach would help identify the reducible test cases in the test suite, still maintaining the same criteria as the original number of test cases.

Keywords: Software testing, mutation test, network centrality measure, test case prioritization.

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Authors: B. Leela Devi, A. Sankar

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The web’s increased popularity has included a huge amount of information, due to which automated web page classification systems are essential to improve search engines’ performance. Web pages have many features like HTML or XML tags, hyperlinks, URLs and text contents which can be considered during an automated classification process. It is known that Webpage classification is enhanced by hyperlinks as it reflects Web page linkages. The aim of this study is to reduce the number of features to be used to improve the accuracy of the classification of web pages. In this paper, a novel feature selection method using an improved Particle Swarm Optimization (PSO) using principle of evolution is proposed. The extracted features were tested on the WebKB dataset using a parallel Neural Network to reduce the computational cost.

Keywords: Web page classification, WebKB Dataset, Term Frequency-Inverse Document Frequency (TF-IDF), Particle Swarm Optimization (PSO).

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Authors: Srinivasan Chandrasekaran, Thailammai Chithambaram, Shihas A. Khader

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The early-stage damage detection in offshore structures requires continuous structural health monitoring and for the large area the position of sensors will also plays an important role in the efficient damage detection. Determining the dynamic behavior of offshore structures requires dense deployment of sensors. The wired Structural Health Monitoring (SHM) systems are highly expensive and always needs larger installation space to deploy. Wireless sensor networks can enhance the SHM system by deployment of scalable sensor network, which consumes lesser space. This paper presents the results of wireless sensor network based Structural Health Monitoring method applied to a scaled experimental model of offshore structure that underwent wave loading. This method determines the serviceability of the offshore structure which is subjected to various environment loads. Wired and wireless sensors were installed in the model and the response of the scaled BLSRP model under wave loading was recorded. The wireless system discussed in this study is the Raspberry pi board with Arm V6 processor which is programmed to transmit the data acquired by the sensor to the server using Wi-Fi adapter, the data is then hosted in the webpage. The data acquired from the wireless and wired SHM systems were compared and the design of the wireless system is verified.

Keywords: Condition assessment, damage detection, structural health monitoring, structural response, wireless sensor network.

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Authors: Wen-Chieh, Hsieh

Abstract:

The purpose of this study is to analyze the islands tourist travel information sources, as well as for the satisfaction of the tourist destination services. This study used questionnaires to the island of Taiwan to the Penghu Islands to engage in tourism activities tourist adopt the designated convenience sampling method, a total of 889 valid questionnaires were collected. After statistical analysis, this study found that: 1. tourists to the Penghu Islands travel information source for “friends and family came to Penghu". 2. Tourists feel the service of the outlying islands of Penghu, the highest feelings of “friendly local residents". 3. There are different demographic variables affect the tourist travel information source and service satisfaction. Based on the findings of this study not only for Penghu's tourism industry with the unit in charge of the proposed operating and suggestions for future research to other researchers.

Keywords: Island tourism, destination, travel information, service satisfaction.

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Authors: Marina Diković

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By giving personal opinions, suggestions and criticism through e-democracy, young people can reinforce the adoption of decisions which they have an impact on. The purpose of this research was to examine the opinion of university students about the possibility of their decision-making by using information and communication technology (ICT). The questionnaire examined young people's values and behaviour associated with e-democracy and the related decision-making. Students are most active online when it comes to finding information connected with their academic responsibilities, but less frequently take part in democratic processes in society, both at the national and local level. E-democracy as a tool can be learned in programmes of Human Rights Education and Citizenship Education. 

Keywords: Active citizens, e-democracy, information and communication technology, university students.

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Authors: Samson Abayomi Olasoju, Olufemi Adekunle, Titilope Edun, Johnson Owoseni

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Science offers opportunities for revolutionizing human activities, enriched by input from scientific research and technology. Biotechnology is a major force for development in developing countries such as Nigeria. It is found to contribute to solving human problems like water and food insecurity that impede national development and threaten peace wherever it is applied. This review identified the problems of agricultural biotechnology in Nigeria. On the part of rural farmers, there is a lack of adequate knowledge or awareness of biotechnology despite the fact that they constitute the bulk of Nigerian farmers. On part of the government, the problems include: lack of adequate implementation of government policy on bio-safety and genetically modified products, inadequate funding of education as well as research and development of products related to biotechnology. Other problems include: inadequate infrastructures (including laboratory), poor funding and lack of national strategies needed for development and running of agricultural biotechnology. In spite of all the challenges associated with agricultural biotechnology, its prospects still remain great if Nigeria is to meet with the food needs of the country’s ever increasing population. The introduction of genetically engineered products will lead to the high productivity needed for commercialization and food security. Insect, virus and other related diseases resistant crops and livestock are another viable area of contribution of biotechnology to agricultural production. In conclusion, agricultural biotechnology will not only ensure food security, but, in addition, will ensure that the local farmers utilize appropriate technology needed for large production, leading to the prosperity of the farmers and national economic growth, provided government plays its role of adequate funding and good policy implementation.

Keywords: Biosafety, biotechnology, food security, genetic engineering, genetic modification.

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Authors: Tatiana A. Dolenko, Sergey A. Burikov, Alexander O. Efitorov, Sergey A. Dolenko

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In this study, a comparative analysis of the approaches associated with the use of neural network algorithms for effective solution of a complex inverse problem – the problem of identifying and determining the individual concentrations of inorganic salts in multicomponent aqueous solutions by the spectra of Raman scattering of light – is performed. It is shown that application of artificial neural networks provides the average accuracy of determination of concentration of each salt no worse than 0.025 M. The results of comparative analysis of input data compression methods are presented. It is demonstrated that use of uniform aggregation of input features allows decreasing the error of determination of individual concentrations of components by 16-18% on the average.

Keywords: Inverse problems, multi-component solutions, neural networks, Raman spectroscopy.

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Currently the most prevalent deep learning methods require a large amount of data for training, whereas few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: Few-shot learning, triplet network, adaptive margin, deep learning.

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Authors: M. Bouguerra, H. Meglouli, I. Habi

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The great majority of the electric installations belong to the first and second category. In order to ensure a high level of reliability of their electric system feeder, two power supply sources are envisaged, one principal, the other of reserve, generally a cold reserve (electric diesel group). The principal source being under operation, its control can be ideal and sure, however for the reserve source being in stop, a preventive maintenance-s which proceeds on time intervals (periodicity) and for well defined lengths of time are envisaged, so that this source will always available in case of the principal source failure. The choice of the periodicity of preventive maintenance of the source of reserve influences directly the reliability of the electric feeder system. On the basis of the semi-markovians processes, the influence of the periodicity of the preventive maintenance of the source of reserve is studied and is given the optimal periodicity.

Keywords: Semi Markovians processes, reliability, optimization, electric network.

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Authors: M. Nageswara Rao

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In this paper, a topology for high voltage gain half-bridge z-source inverter with low voltage stress on capacitors is proposed. The proposed inverter has only one impedance network. It can generate symmetric and asymmetric voltages with different magnitudes during both half-cycles. By selecting the duty cycle it can also produce conventional half-bridge inverter characteristics. It is used in special applications like, electrochemical and electro plating applications. Calculations of voltage ripple of capacitors, capacitors voltage stress inductors current ripple are presented. The proposed topology is simulated using PSCAD software and the simulated values are compared with the theoretical values.

Keywords: Half-bridge inverter, impedance network-source inverter, high voltage gain inverter, power system computer aided design.

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Authors: Shivakumar Krishnamurti, Ruchi Agarwal

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The study examines the influence of marital status on consumers of products and services using blogs as a source of information. A pre-designed questionnaire was used to collect the primary data from the respondents (experiences). Data were collected from one hundred and eighty seven respondents residing in and around the Emirates of Sharjah and Dubai of the United Arab Emirates. The collected data was analyzed with the help of statistical tools such as averages, percentages, factor analysis, Student’s t-test and Structural Equation Modelling Technique. Objectives of the study are to know the reasons how married and unmarried or single consumers of products and services are motivated to use blogs as a source of information, to know whether the consumers of products and services irrespective of their marital status share their views and experiences with other bloggers and to know the respondents’ future intentions towards blogging. The study revealed the following: Majority of the respondents have the motivation to blog because they are willing to receive comments on what they post about services, convenience of blogs to search for information about services and products, by blogging respondents share information on the symptoms of a disease/ disorder that may be experienced by someone, helps to share information about ready to cook mix products and are keen to spend more time blogging in the future.

Keywords: Blog, consumer, information, marital status.

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Authors: Semih Demir, Anil Celebi

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Circuit switched networks widely used until the end of the 20^th century have been transformed into packages switched networks. Time Division Multiplexing over Internet Protocol (TDMoIP) is a system that enables Time Division Multiplexing (TDM) traffic to be carried over packet switched networks (PSN). In TDMoIP systems, devices that send TDM data to the PSN and receive it from the network must operate with the same clock frequency. In this study, it was aimed to implement clock synchronization process in Field Programmable Gate Array (FPGA) chips using time information attached to the packages received from PSN. The designed hardware is verified using the datasets obtained for the different carrier types and comparing the results with the software model. Field tests are also performed by using the real time TDMoIP system.

Keywords: Clock recovery on TDMoIP, FPGA, MATLAB reference model, clock synchronization.

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Authors: Rajoo Pandey

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Most of the commonly used blind equalization algorithms are based on the minimization of a nonconvex and nonlinear cost function and a neural network gives smaller residual error as compared to a linear structure. The efficacy of complex valued feedforward neural networks for blind equalization of linear and nonlinear communication channels has been confirmed by many studies. In this paper we present two neural network models for blind equalization of time-varying channels, for M-ary QAM and PSK signals. The complex valued activation functions, suitable for these signal constellations in time-varying environment, are introduced and the learning algorithms based on the CMA cost function are derived. The improved performance of the proposed models is confirmed through computer simulations.

Keywords: Blind Equalization, Neural Networks, Constant Modulus Algorithm, Time-varying channels.

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Authors: Tirtha S. Das, Ayan K. Sau, Subir K. Sarkar

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Digital watermarking is a way to provide the facility of secure multimedia data communication besides its copyright protection approach. The Spread Spectrum modulation principle is widely used in digital watermarking to satisfy the robustness of multimedia signals against various signal-processing operations. Several SS watermarking algorithms have been proposed for multimedia signals but very few works have discussed on the issues responsible for secure data communication and its robustness improvement. The current paper has critically analyzed few such factors namely properties of spreading codes, proper signal decomposition suitable for data embedding, security provided by the key, successive bit cancellation method applied at decoder which have greater impact on the detection reliability, secure communication of significant signal under camouflage of insignificant signals etc. Based on the analysis, robust SS watermarking scheme for secure data communication is proposed in wavelet domain and improvement in secure communication and robustness performance is reported through experimental results. The reported result also shows improvement in visual and statistical invisibility of the hidden data.

Keywords: Spread spectrum modulation, spreading code, signaldecomposition, security, successive bit cancellation

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Authors: Santosh Kumar Singh, Krishna Chandra Roy, Vibhakar Pathak

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Spectrum is a scarce commodity, and considering the spectrum scarcity faced by the wireless-based service providers led to high congestion levels. Technical inefficiencies from pooled, since all networks share a common pool of channels, exhausting the available channels will force networks to block the services. Researchers found that cognitive radio (CR) technology may resolve the spectrum scarcity. A CR is a self-configuring entity in a wireless networking that senses its environment, tracks changes, and frequently exchanges information with their networks. However, CRN facing challenges and condition become worst while tracks changes i.e. reallocation of another under-utilized channels while primary network user arrives. In this paper, channels or resource reallocation technique based on DNA-inspired computing algorithm for CRN has been proposed.

Keywords: Ad hoc networks, channels reallocation, cognitive radio, DNA local sequence alignment.

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Authors: Yasar Guneri Sahin, Mehmet Cudi Okur

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In this presentation, we discuss the use of information technologies in the area of special education for teaching individuals with learning disabilities. Application software which was developed for this purpose is used to demonstrate the applicability of a database integrated information processing system to alleviate the burden of educators. The software allows the preparation of individualized education programs based on the predefined objectives, goals and behaviors.

Keywords: Special education, disabled individual, informationtechnology, individual education programs.

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Authors: Yung-Chuan Lee, Shahram Rahimi, Bidyut Gupta

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In this paper, we introduce an mobile agent framework with proactive load balancing for ambient intelligence (AmI) environments. One of the main obstacles of AmI is the scalability in which the openness of AmI environment introduces dynamic resource requirements on agencies. To mediate this scalability problem, our framework proposes a load balancing module to proactively analyze the resource consumption of network bandwidth and preferred agencies to suggest the optimal communication method to its user. The framework generally formulates an AmI environment that consists of three main components: (1) mobile devices, (2) hosts or agencies, and (3) directory service center (DSC). A preliminary implementation was conducted with NetLogo and the experimental results show that the proposed approach provides enhanced system performance by minimizing the network utilization to provide users with responsive services.

Keywords: Ambient intelligence, load balancing, multiagent systems, ubiquitous computing.

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Authors: Ana Cázares

Abstract:

Aims for this study: first, to compare the expertise level in data analysis, communication and information technologies in undergraduate psychology students. Second, to verify the factor structure of E-ETICA (Escala de Experticia en Tecnologias de la Informacion, la Comunicacion y el Análisis or Data Analysis, Communication and Information'Expertise Scale) which had shown an excellent internal consistency (α= 0.92) as well as a simple factor structure. Three factors, Complex, Basic Information and Communications Technologies and E-Searching and Download Abilities, explains 63% of variance. In the present study, 260 students (119 juniors and 141 seniors) were asked to respond to ETICA (16 items Likert scale of five points 1: null domain to 5: total domain). The results show that both junior and senior students report having very similar expertise level; however, E-ETICA presents a different factor structure for juniors and four factors explained also 63% of variance: Information E-Searching, Download and Process; Data analysis; Organization; and Communication technologies.

Keywords: Data analysis, Information, Communications Technologies, Expertise'Levels.

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Authors: Geoff D. Skinner

Abstract:

Australia, while being a large and eager consumer of innovative and cutting edge Information and Communication Technologies (ICT), continues to struggle to remain a leader in Technological Innovation. This paper has two main contributions to address certain aspects of this complex issue. The first being the current findings of an ongoing research project on Information and Innovation Management in the Australian Information and Communication Technologies (ICT) sector. The major issues being considered by the project include: investigation of the possible inherent entrepreneurial nature of ICT; how to foster ICT innovation; and examination of the inherent difficulties currently found within the ICT industry of Australia in regards to supporting the development of innovative and creative ideas. The second major contribution is details of the I.-C.A.N. (Innovation by Collaborative Anonymous Networking) software application information management tool created and evolving in our research group. I-CAN, besides having a positive reinforcement acronym, is aimed at facilitating productive collaborative innovation in an Australian workplace. Such a work environment is frequently subjected to cultural influences such as the 'tall poppy syndrome' and 'negative' or 'unconstructive' peer-pressure. There influences are frequently seen as inhibitors to employee participation, entrepreneurship and innovation.

Keywords: Innovation Management, Knowledge Management, Technology Incubation.

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Authors: Joachim Kimmerle, Johannes Moskaliuk, Ulrike Cress

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The development of Internet technology in recent years has led to a more active role of users in creating Web content. This has significant effects both on individual learning and collaborative knowledge building. This paper will present an integrative framework model to describe and explain learning and knowledge building with shared digital artifacts on the basis of Luhmann-s systems theory and Piaget-s model of equilibration. In this model, knowledge progress is based on cognitive conflicts resulting from incongruities between an individual-s prior knowledge and the information which is contained in a digital artifact. Empirical support for the model will be provided by 1) applying it descriptively to texts from Wikipedia, 2) examining knowledge-building processes using a social network analysis, and 3) presenting a survey of a series of experimental laboratory studies.

Keywords: Individual learning, collaborative knowledge building, systems theory, equilibration.

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: Autonomous surveillance, Bayesian reasoning, decision-support, interventions, patterns-of-life, predictive analytics, predictive insights.

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Authors: Daniel F. Garcia, Diego Gonzalez

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This paper shows a simple and effective approach to the design and implementation of Industrial Information Systems (IIS) oriented to control the characteristics of each individual product manufactured in a production line and also their manufacturing conditions. The particular products considered in this work are large steel strips that are coiled just after their manufacturing. However, the approach is directly applicable to coiled strips in other industries, like paper, textile, aluminum, etc. These IIS provide very detailed information of each manufactured product, which complement the general information managed by the ERP system of the production line. In spite of the high importance of this type of IIS to guarantee and improve the quality of the products manufactured in many industries, there are very few works about them in the technical literature. For this reason, this paper represents an important contribution to the development of this type of IIS, providing guidelines for their design, implementation and exploitation.

Keywords: Data storage, industrial information systems, measurement systems integration, signal acquisition.

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Authors: Guenther Schuh, Sebastian Woelk

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Companies face increasing challenges in research due to higher costs and risks. The intensifying technology complexity and interdisciplinarity require unique know-how. Therefore, companies need to decide whether research shall be conducted internally or externally with partners. On the other hand, research institutes meet increasing efforts to achieve good financing and to maintain high research reputation. Therefore, relevant research topics need to be identified and specialization of competency is necessary. However, additional competences for solving interdisciplinary research projects are also often required. Secured financing can be achieved by bonding industry partners as well as public fundings. The realization of faster and better research drives companies and research institutes to cooperate in organized research networks, which are managed by an administrative organization. For an effective and efficient cooperation, necessary processes, roles, tools and a set of rules need to be determined. Goal of this paper is to show the state-of-art research and to propose a governance framework for organized research networks.

Keywords: Interorganizational cooperation, design of network governance, research network.

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Authors: C. Nallusamy, A. Sabari, K. Suganya

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Geographical routing protocol requires node physical location information to make forwarding decision. Geographical routing uses location service or position service to obtain the position of a node. The geographical information is a geographic coordinates or can be obtained through reference points on some fixed coordinate system. Link can be formed between two nodes. Link lifetime plays a crucial role in MANET. Link lifetime represent how long the link is stable without any failure between the nodes. Link failure may occur due to mobility and because of link failure energy of nodes can be drained. Thus this paper proposes survey about link lifetime prediction using geographical information.

Keywords: MANET, Geographical routing, Link lifetime, Link stability.

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Authors: Laveen Sundararaj, Palanisamy Vellaiyan

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Delay and Disruption Tolerant Networking is part of the Inter Planetary Internet with primary application being Deep Space Networks. Its Terrestrial form has interesting research applications such as Alagappa University Delay Tolerant Water Monitoring Network which doubles as test beds for improvising its routing scheme. DTNs depend on node mobility to deliver packets using a store-carry-and forward paradigm. Throwboxes are small and inexpensive stationary devices equipped with wireless interfaces and storage. We propose the use of Throwboxes to enhance the contact opportunities of the nodes and hence improve the Throughput. The enhancement is evaluated using Alunivdtnsim, a desktop simulator in C language and the results are graphically presented.

Keywords: Alunivdtnsim – Alagappa University Delay TolerantNetwork Simulator, AUDTWMN- Alagappa University DelayTolerant Water Monitoring Network, DTN - Delay and DisruptionTolerant Networking, LTP – Lick Lider Transmission Protocol.

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Authors: N. Moghadam, H. Sadeghi

Abstract:

In this paper a novel scheme for watermarking digital audio during its compression to MPEG-1 Layer III format is proposed. For this purpose we slightly modify some of the selected MDCT coefficients, which are used during MPEG audio compression procedure. Due to the possibility of modifying different MDCT coefficients, there will be different choices for embedding the watermark into audio data, considering robustness and transparency factors. Our proposed method uses a genetic algorithm to select the best coefficients to embed the watermark. This genetic selection is done according to the parameters that are extracted from the perceptual content of the audio to optimize the robustness and transparency of the watermark. On the other hand the watermark security is increased due to the random nature of the genetic selection. The information of the selected MDCT coefficients that carry the watermark bits, are saves in a database for future extraction of the watermark. The proposed method is suitable for online MP3 stores to pursue illegal copies of musical artworks. Experimental results show that the detection ratio of the watermarks at the bitrate of 128kbps remains above 90% while the inaudibility of the watermark is preserved.

Keywords: Content-Based Audio Watermarking, Genetic AudioWatermarking.

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Authors: Candido Alcaide, Manuel Dıaz, Luis Llopis, Antonio Marquez, Bartolome Rubio, Enrique Soler

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The increasing complexity of software development based on peer to peer networks makes necessary the creation of new frameworks in order to simplify the developer-s task. Additionally, some applications, e.g. fire detection or security alarms may require real-time constraints and the high level definition of these features eases the application development. In this paper, a service model based on a component model with real-time features is proposed. The high-level model will abstract developers from implementation tasks, such as discovery, communication, security or real-time requirements. The model is oriented to deploy services on small mobile devices, such as sensors, mobile phones and PDAs, where the computation is light-weight. Services can be composed among them by means of the port concept to form complex ad-hoc systems and their implementation is carried out using a component language called UM-RTCOM. In order to apply our proposals a fire detection application is described.

Keywords: Peer-to-peer, mobile systems, real-time, service-oriented architecture.

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Authors: Wenqing Fan, Yixuan Cheng, Wei Huang

Abstract:

The diversity and complexity of modern IT systems make it almost impossible for internal teams to find vulnerabilities in all software before the software is officially released. The emergence of threat intelligence and vulnerability reporting policy has greatly reduced the burden on software vendors and organizations to find vulnerabilities. However, to prove the existence of the reported vulnerability, it is necessary but difficult for security incident response team to build a deliberated vulnerable environment from the vulnerability report with limited and incomplete information. This paper presents a structured, standardized, machine-oriented vulnerability intelligence format, that can be used to automate the orchestration of Deliberated Vulnerable Environment (DVE). This paper highlights the important role of software configuration and proof of vulnerable specifications in vulnerability intelligence, and proposes a triad model, which is called DIR (Dependency Configuration, Installation Configuration, Runtime Configuration), to define software configuration. Finally, this paper has also implemented a prototype system to demonstrate that the orchestration of DVE can be automated with the intelligence.

Keywords: DIR Triad Model, DVE, vulnerability intelligence, vulnerability recurrence.

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Authors: Hemashree Bordoloi, Kandarpa Kumar Sarma

Abstract:

Rotation or tilt present in an image capture by digital means can be detected and corrected using Artificial Neural Network (ANN) for application with a Face Recognition System (FRS). Principal Component Analysis (PCA) features of faces at different angles are used to train an ANN which detects the rotation for an input image and corrected using a set of operations implemented using another system based on ANN. The work also deals with the recognition of human faces with features from the foreheads, eyes, nose and mouths as decision support entities of the system configured using a Generalized Feed Forward Artificial Neural Network (GFFANN). These features are combined to provide a reinforced decision for verification of a person-s identity despite illumination variations. The complete system performing facial image rotation detection, correction and recognition using re-enforced decision support provides a success rate in the higher 90s.

Keywords: Rotation, Face, Recognition, ANN.

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Authors: Jindong Gu, Matthias Schubert, Volker Tresp

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In many outlier detection tasks, only training data belonging to one class, i.e., the positive class, is available. The task is then to predict a new data point as belonging either to the positive class or to the negative class, in which case the data point is considered an outlier. For this task, we propose a novel corrupted Generative Adversarial Network (CorGAN). In the adversarial process of training CorGAN, the Generator generates outlier samples for the negative class, and the Discriminator is trained to distinguish the positive training data from the generated negative data. The proposed framework is evaluated using an image dataset and a real-world network intrusion dataset. Our outlier-detection method achieves state-of-the-art performance on both tasks.

Keywords: Outlier detection, generative adversary networks, semi-supervised learning.

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