Search results for: network devices

Authors: Kamyar Fakhr, Roozbeh Salmani

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Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.

Keywords: biometric system, convolutional neural network, cyber-attack, secure

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Authors: Smithinun Thairoongrojana

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This research is a qualitative research with three main purposes: (1) to develop the local tax map software system to be linked to the main Local Tax Map System (LTAX3000) system; (2) to design and develop a program for tax data fieldwork on wireless devices and link it to LTAX3000 database of Surat Thani Municipality; (3) to develop the human resource responsible for the fieldwork to be able to use the program and maintain the system and also to be able to work with the dynamic of technologies. In-depth interviews with the two groups of samples, the board of Surat Thani Municipality and operation staff responsible for observing and taxing fieldworks were conducted. The result of this study demonstrates the new developed fieldworks system that can be used both stand-alone usage and networking usage. The fieldworks system to collect and store the variety of taxing information within Surat Thani Municipality will be explained. Then the fieldwork operation process development and the replacement of transferring and storing the information via the network communication.

Keywords: Local tax map, software system development, wireless devices, human resource

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Authors: S. S. Kenny Lee, C. C. Kong, S. K. Ting

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Teaching engineering lab provides opportunity for students to practice theories learned through physical experiment in the laboratory. However, building laboratories to accommodate increased number of students are expensive, making it impossible for an educational institution to afford the high expenses. In this paper, we develop a low cost and remote platform to aid teaching undergraduate students. The platform is constructed where the real experiment setting up in laboratory can be reconfigure and accessed remotely, the aim is to increase student’s desire to learn at which they can interact with the physical experiment using network enabled devices at anywhere in the campus. The platform is constructed with Raspberry Pi as a main control board that provides communication between computer interfaces to the actual experiment preset in the laboratory. The interface allows real-time remote viewing and triggering the physical experiment in the laboratory and also provides instructions and learning guide about the experimental.

Keywords: engineering lab, low cost, network, remote platform, reconfigure, real-time

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Authors: Yiannis Koumpouros, Effie Papageorgiou, Alexandra Karavasili, Foteini Koureta

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The objective of the present study was to develop a scale called PYTHEIA. The PYTHEIA is a self-reported measure for the assessment of rehabilitation and assistive robotics and other assistive technology devices. The development of PYTHEIA faced the absence of a valid instrument that can be used to evaluate the assistive robotic devices both as a whole, as well as any of their individual components or functionalities implemented. According to the results presented, PYTHEIA is a valid and reliable scale able to be applied to different target groups for the subjective evaluation of various assistive technology devices.

Keywords: rehabilitation, assistive technology, assistive robots, rehabilitation robots, scale, psychometric test, assessment, validation, user satisfaction

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Authors: Juha Kettunen

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The study analyzes the quality and the size of the strategic network of higher education institutions and the concept of fitness for purpose in quality assurance. It also analyses the transaction costs of networking that have consequences on the number of members in the network. Empirical evidence is presented from the Consortium on Applied Research and Professional Education, which is a European strategic network of six higher education institutions. The results of the study support the argument that the number of members in the strategic network should be relatively small to provide high-quality results. The practical importance is that networking has been able to promote international research and development projects. The results of this study are important for those who want to design and improve international networks in higher education.

Keywords: higher education, network, research and development, strategic management

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Authors: P. Kooche Baghy, S. Eskandari, E.javanmard

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Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

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Authors: Siti Navila

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Hedging as a kind of pragmatic competence is an essential part in achieving the goal in communication, especially in academic discourse where the process of sharing knowledge among academic community takes place. Academic discourse demands an appropriateness and modesty of an author or speaker in stating arguments, to name but few, by considering the politeness, being cautious and tentative, and differentiating personal opinions and facts in which these aspects can be achieved through hedging. This study was conducted to find the hedging devices used by students as well as to analyze how they use them in their oral presentation. Some oral presentations from English Department students of the State University of Jakarta on their Academic Presentation course final test were recorded and explored formally and functionally. It was found that the most frequent hedging devices used by students were shields from all hedging devices that students commonly used when they showed suggestion, stated claims, showed opinion to provide possible but still valid answer, and offered the appropriate solution. The researcher suggests that hedging can be familiarized in learning, since potential conflicts that is likely to occur while delivering ideas in academic contexts such as disagreement, criticism, and personal judgment can be reduced with the use of hedging. It will also benefit students in achieving the academic competence with an ability to demonstrate their ideas appropriately and more acceptable in academic discourse.

Keywords: academic discourse, hedging, hedging devices, lexical hedges, Meyer classification

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Authors: Dorota Galeza

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This paper argues that networks, such as the ECN and the American network, are affected by certain small events which are inherent to path dependence and preclude the full evolution towards efficiency. It is advocated that the American network is superior to the ECN in many respects due to its greater flexibility and longer history. This stems in particular from the creation of the American network, which was based on a small number of cases. Such a structure encourages further changes and modifications which are not necessarily radical. The ECN, by contrast, was established by legislative action, which explains its rigid structure and resistance to change. This paper is an attempt to transpose the superiority of the American network on to the ECN. It looks at concepts such as judicial cooperation, harmonisation of procedure, peer review and regulatory impact assessments (RIAs), and dispute resolution procedures.

Keywords: antitrust, competition, networks, path dependence

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Authors: Foteini Zagklavara, Peter Jimack, Nikil Kapur, Ozz Querin, Harvey Thompson

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The invention and development of the Polymerase Chain Reaction (PCR) technology have revolutionised molecular biology and molecular diagnostics. There is an urgent need to optimise their performance of those devices while reducing the total construction and operation costs. The present study proposes a CFD-enabled optimisation methodology for continuous flow (CF) PCR devices with serpentine-channel structure, which enables the trade-offs between competing objectives of DNA amplification efficiency and pressure drop to be explored. This is achieved by using a surrogate-enabled optimisation approach accounting for the geometrical features of a CF μPCR device by performing a series of simulations at a relatively small number of Design of Experiments (DoE) points, with the use of COMSOL Multiphysics 5.4. The values of the objectives are extracted from the CFD solutions, and response surfaces created using the polyharmonic splines and neural networks. After creating the respective response surfaces, genetic algorithm, and a multi-level coordinate search optimisation function are used to locate the optimum design parameters. Both optimisation methods produced similar results for both the neural network and the polyharmonic spline response surfaces. The results indicate that there is the possibility of improving the DNA efficiency by ∼2% in one PCR cycle when doubling the width of the microchannel to 400 μm while maintaining the height at the value of the original design (50μm). Moreover, the increase in the width of the serpentine microchannel is combined with a decrease in its total length in order to obtain the same residence times in all the simulations, resulting in a smaller total substrate volume (32.94% decrease). A multi-objective optimisation is also performed with the use of a Pareto Front plot. Such knowledge will enable designers to maximise the amount of DNA amplified or to minimise the time taken throughout thermal cycling in such devices.

Keywords: PCR, optimisation, microfluidics, COMSOL

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Authors: G. R. Kavitha, T. S. Indumathi

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With the constantly rising demands of the multimedia services, the requirements of long haul transport network are constantly changing in the area of optical network. Maximum data transmission using optimization of the communication channel poses the biggest challenge. Although there has been a constant focus on this area from the past decade, there was no evidence of a significant result that has been accomplished. Hence, after reviewing some potential design of optical network from literatures, it was understood that optical signal to noise ratio was one of the elementary attributes that can define the performance of the optical network. In this paper, we propose a framework termed as ECON (Enhanced Constraint-based Optical Network) that primarily optimize the optical signal to noise ratio using ROADM. The simulation is performed in Matlab and optical signal to noise ratio is extracted considering the system matrix. The outcome of the proposed study shows that optimized OSNR as compared to the existing studies.

Keywords: component, optical network, reconfigurable optical add-drop multiplexer, optical signal-to-noise ratio

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Authors: Saurabh Chaudhury, Sanjeet Kumar Sinha

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The MOSFET has been the main building block in high performance and low power VLSI chips for the last several decades. Device scaling is fundamental to technological advancements, which allows more devices to be integrated on a single die providing greater functionality per chip. Ultimately, the goal of scaling is to build an individual transistor that is smaller, faster, cheaper, and consumes less power. Scaling continued following Moore's law initially and now we see an exponential growth in today's nano scaled chip. However, device scaling to deep nano meter regime leads to exponential increase in leakage currents and excessive heat generation. Moreover, fabrication process variability causing a limitation to further scaling. Researchers believe that with a mix of chemistry, physics, and engineering, nano electronics may provide a solution to increasing fabrication costs and may allow integrated circuits to be scaled beyond the limits of the modern transistor. Carbon nano tube (CNT) and nano wires (NW) based FETs have been analyzed and characterized in laboratory and also been demonstrated as prototypes. This work presents an extensive simulation based study and analysis of CNTFET and NW-FET devices and comparison of the results with conventional MOSFET. From this study, we can conclude that these devices have got some excellent properties and favorable characteristics which will definitely lead the future semiconductor devices in post silicon era.

Keywords: carbon nanotube, nanowire FET, low power, nanoscaled devices, VLSI

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Authors: C. Temaneh-Nyah, F. A. Phiri, D. Karegeya

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This paper presents an algorithm for obtaining the map of subscriber’s density distribution for a mobile wireless communication network based on the actual subscriber's traffic data obtained from the base station. This is useful in statistical characterization of the mobile wireless network.

Keywords: electromagnetic compatibility, statistical analysis, simulation of communication network, subscriber density

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Authors: Zhao Yu, Zhi-Nan Zhang

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More and more interactive devices are used in the transportation service system. Our mobile phones, on-board computers, and Head-Up Displays (HUDs) can all be used as the tools of the in-car service system. People can access smart systems with different terminals such as mobile phones, computers, pads and even their cars and watches. Different forms of terminals bring the different quality of interaction by the various human-computer Interaction modes. The new interactive devices require good ergonomics design at each stage of the whole design process. According to the theory of human factors and ergonomics, this paper compared three types of interactive devices by four driving tasks. Forty-eight drivers were chosen to experience these three interactive devices (mobile phones, on-board computers, and HUDs) by a simulate driving process. The subjects evaluated ergonomics performance and subjective workload after the process. And subjects were encouraged to support suggestions for improving the interactive device. The result shows that different interactive devices have different advantages in driving tasks, especially in non-driving tasks such as information and entertainment fields. Compared with mobile phones and onboard groups, the HUD groups had shorter response times in most tasks. The tasks of slow-up and the emergency braking are less accurate than the performance of a control group, which may because the haptic feedback of these two tasks is harder to distinguish than the visual information. Simulated driving is also helpful in improving the design of in-vehicle interactive devices. The paper summarizes the ergonomics characteristics of three in-vehicle interactive devices. And the research provides a reference for the future design of in-vehicle interactive devices through an ergonomic approach to ensure a good interaction relationship between the driver and the in-vehicle service system.

Keywords: human factors, industrial ergonomics, transportation system, usability, vehicle user interface

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Authors: Gregory D. Saxton

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Networks are everywhere: lunch ties among co-workers, golfing partnerships among employees, interlocking board-of-director connections, Facebook friendship ties, etc. Each network varies in terms of its structure -its size, how inter-connected network members are, and the prevalence of sub-groups and cliques. At the same time, within any given network, some network members will have a more important, more central position on account of their greater number of connections or their capacity as “bridges” connecting members of different network cliques. The logic of network structure and position is at the heart of what is known as social network analysis, and this paper applies this logic to the study of the stock market. Using an array of data analytics and machine learning tools, this study will examine 17 million Twitter messages discussing the stocks of the firms in the S&P 1,500 index in 2018. Each of these 1,500 stocks has a distinct Twitter discussion network that varies in terms of core network characteristics such as size, density, influence, norms and values, level of activity, and embedded resources. The study’s core proposition is that the ultimate effect of any market-relevant information is contingent on the characteristics of the network through which it flows. To test this proposition, this study operationalizes each of the core network characteristics and examines their influence on market reactions to 2018 quarterly earnings announcement events.

Keywords: data analytics, investor-to-investor communication, social network analysis, Twitter

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Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

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Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

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Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

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Authors: Anuradha Banerjee

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A mobile ad hoc network is an infrastructure less network, where nodes are free to move independently in any direction. The nodes have limited battery power; hence, we require energy efficient route discovery technique to enhance their lifetime and network performance. In this paper, we propose an energy-efficient route discovery technique CERD that greatly reduces the number of route requests flooded into the network and also gives priority to the route request packets sent from the routers that has communicated with the destination very recently, in single or multi-hop paths. This does not only enhance the lifetime of nodes but also decreases the delay in tracking the destination.

Keywords: ad hoc network, energy efficiency, flooding, node lifetime, route discovery

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Authors: Zakarya Kourdi, Mohammed Khaouani, Benyounes Bouazza, Ahlam Guen-Bouazza, Amine Boursali

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In this paper, we have evaluated the thermal effect for high electron mobility transistors (HEMTs) heterostructure InAlN/GaN with a gate length 30nm high-performance. It also shows the analysis and simulated these devices, and how can be used in different application. The simulator Tcad-Silvaco software has used for predictive results good for the DC, AC and RF characteristic, Devices offered max drain current 0.67A; transconductance is 720 mS/mm the unilateral power gain of 180 dB. A cutoff frequency of 385 GHz, and max frequency 810 GHz These results confirm the feasibility of using HEMTs with InAlN/GaN in high power amplifiers, as well as thermal places.

Keywords: HEMT, Thermal Effect, Silvaco, InAlN/GaN

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Authors: E. Baltas, E. Feloni, G. Bariamis

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The operation of a network of hydrometeorological-hydrometric stations is basic infrastructure for the management of water resources, as well as, for flood protection. The assessment of water resources potential led to the necessity of adoption management practices including a multi-criteria analysis for the optimum design of the region’s station network. This research work aims at the optimisation of a new/existing network, using GIS methods. The planning of optimum network stations is based on the guidelines of international organizations such as World Meteorological Organization (WMO). The uniform spatial distribution of the stations, the drainage basin for the hydrometric stations and criteria concerning the low terrain slope, the accessibility to the stations and proximity to hydrological interest sites, were taken into consideration for its development. The abovementioned methodology has been implemented for two different areas the Florina municipality and the Argolis area in Greece, and comparison of the results has been conducted.

Keywords: GIS, hydrometeorological, hydrometric, network, optimisation

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Authors: Vishwesh Kulkarni, Nikhil Bellarykar

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Cellular complexity stems from the interactions among thousands of different molecular species. Thanks to the emerging fields of systems and synthetic biology, scientists are beginning to unravel these regulatory, signaling, and metabolic interactions and to understand their coordinated action. Reverse engineering of biological networks has has several benefits but a poor quality of data combined with the difficulty in reproducing it limits the applicability of these methods. A few years back, many of the commonly used predictive algorithms were tested on a network constructed in the yeast Saccharomyces cerevisiae (S. cerevisiae) to resolve this issue. The network was a synthetic network of five genes regulating each other for the so-called in vivo reverse-engineering and modeling assessment (IRMA). The network was constructed in S. cereviase since it is a simple and well characterized organism. The synthetic network included a variety of regulatory interactions, thus capturing the behaviour of larger eukaryotic gene networks on a smaller scale. We derive a new set of algorithms by solving a nonlinear optimization problem and show how these algorithms outperform other algorithms on these datasets.

Keywords: synthetic gene network, network identification, optimization, nonlinear modeling

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Authors: Nareshkumar Harale, B. B. Meshram

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The continued exponential growth of successful cyber intrusions against today’s businesses has made it abundantly clear that traditional perimeter security measures are no longer adequate and effective. We evolved the network trust architecture from trust-untrust to Zero-Trust, With Zero Trust, essential security capabilities are deployed in a way that provides policy enforcement and protection for all users, devices, applications, data resources, and the communications traffic between them, regardless of their location. Information exchange over the Internet, in spite of inclusion of advanced security controls, is always under innovative, inventive and prone to cyberattacks. TCP/IP protocol stack, the adapted standard for communication over network, suffers from inherent design vulnerabilities such as communication and session management protocols, routing protocols and security protocols are the major cause of major attacks. With the explosion of cyber security threats, such as viruses, worms, rootkits, malwares, Denial of Service attacks, accomplishing efficient and effective intrusion detection and prevention is become crucial and challenging too. In this paper, we propose a design and analysis model for next generation network intrusion detection and protection system as part of layered security strategy. The proposed system design provides intrusion detection for wide range of attacks with layered architecture and framework. The proposed network intrusion classification framework deals with cyberattacks on standard TCP/IP protocol, routing protocols and security protocols. It thereby forms the basis for detection of attack classes and applies signature based matching for known cyberattacks and data mining based machine learning approaches for unknown cyberattacks. Our proposed implemented software can effectively detect attacks even when malicious connections are hidden within normal events. The unsupervised learning algorithm applied to network audit data trails results in unknown intrusion detection. Association rule mining algorithms generate new rules from collected audit trail data resulting in increased intrusion prevention though integrated firewall systems. Intrusion response mechanisms can be initiated in real-time thereby minimizing the impact of network intrusions. Finally, we have shown that our approach can be validated and how the analysis results can be used for detecting and protection from the new network anomalies.

Keywords: network intrusion detection, network intrusion prevention, association rule mining, system analysis and design

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Authors: M. Khouil, N. Saber, M. Mestari

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In this paper, a different architecture of a collision detection neural network (DCNN) is developed. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons, linear and threshold logic, which simplified the actual implementation of all the networks proposed. The study of the collision detection is divided into two sections, the collision between a point and a polyhedron and then the collision between two convex polyhedra. The aim of this research is to determine through the AMAXNET network a mini maximum point in a fixed time, which allows us to detect the presence of a potential collision.

Keywords: collision identification, fixed time, convex polyhedra, neural network, AMAXNET

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Authors: Clara Oliver, Oibar Martinez

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This paper is intended to reveal the severity of electrostatic discharge (ESD) effects in electronic and optoelectronic devices by performing sensitivity tests based on Human Body Model (HBM) standard. We explain here the HBM standard in detail together with the typical failure modes associated with electrostatic discharges. In addition, a prototype of electrostatic charge generator has been designed, fabricated, and verified to stress electronic devices, which features a compact high voltage source. This prototype is inexpensive and enables one to do a battery of pre-compliance tests aimed at detecting unexpected weaknesses to static discharges at the component level. Some tests with different devices were performed to illustrate the behavior of the proposed generator. A set of discharges was applied according to the HBM standard to commercially available bipolar transistors, complementary metal-oxide-semiconductor transistors and light emitting diodes. It is observed that high current and voltage ratings in electronic devices not necessarily provide a guarantee that the device will withstand high levels of electrostatic discharges. We have also compared the result obtained by performing the sensitivity tests based on HBM with a real discharge generated by a human. For this purpose, the charge accumulated in the person is monitored, and a direct discharge against the devices is generated by touching them. Every test has been performed under controlled relative humidity conditions. It is believed that this paper can be of interest for research teams involved in the development of electronic and optoelectronic devices which need to verify the reliability of their devices in terms of robustness to electrostatic discharges.

Keywords: human body model, electrostatic discharge, sensitivity tests, static charge monitoring

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Authors: S. Dhib, S. A. Addouche, T. Loukil, A. Elmhamedi

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In this paper, a reverse supply chain network is investigated for a decision making. This decision is surrounded by complex flows of returned products, due to the increasing quantity, the type of returned products and the variety of recovery option products (reuse, recycling, and refurbishment). The most important problem in the reverse logistic network (RLN) is to orient returned products to the suitable type of recovery option. However, returned products orientations from collect sources to the recovery disposition have not well considered in performance model. In this study, we propose a performance model for designing a network configuration on reverse logistics. Conceptual and analytical models are developed with taking into account operational, economic and environmental factors on designing network.

Keywords: reverse logistics, network design, performance model, open loop configuration

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Authors: Ahmad M. Awwad, Jehad Al-Sadi

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The star network is one of the promising interconnection networks for future high speed parallel computers, it is expected to be one of the future-generation networks. The star network is both edge and vertex symmetry, it was shown to have many gorgeous topological proprieties also it is owns hierarchical structure framework. Although much of the research work has been done on this promising network in literature, it still suffers from having enough algorithms for load balancing problem. In this paper we try to work on this issue by investigating and proposing an efficient algorithm for load balancing problem for the star network. The proposed algorithm is called Star Clustered Dimension Exchange Method SCDEM to be implemented on the star network. The proposed algorithm is based on the Clustered Dimension Exchange Method (CDEM). The SCDEM algorithm is shown to be efficient in redistributing the load balancing as evenly as possible among all nodes of different factor networks.

Keywords: load balancing, star network, interconnection networks, algorithm

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Authors: Radhamanohar Aepuru, R. V. Mangalaraja

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Flexible electronic devices have drawn potential interest and provide significant new insights to develop energy conversion and storage devices such as photodetectors and nanogenerators. Recently, self-powered electronic systems have captivated huge attention for next generation MEMS/NEMS devices that can operate independently by generating built-in field without any need of external bias voltage and have wide variety of applications in telecommunication, imaging, environmental and defence sectors. The basic physical process involved in these devices are charge generation, separation, and charge flow across the electrodes. Many inorganic nanostructures have been exploring to fabricate various optoelectronic and electromechanical devices. However, the interaction of nanostructures and their excited charge carrier dynamics, photoinduced charge separation, and fast carrier mobility are yet to be studied. The proposed research is to address one such area and to realize the self-powered electronic devices. In the present work, nanocomposites of inorganic nanostructures based on ZnO, metal halide perovskites; and polyvinylidene fluoride (PVDF) based nanocomposites are realized for photodetectors and nanogenerators. The characterization of the inorganic nanostructures is carried out through steady state optical absorption and luminescence spectroscopies as well as X-ray diffraction and high-resolution transmission electron microscopy (TEM) studies. The detailed carrier dynamics is investigated using various spectroscopic techniques. The developed composite nanostructures exhibit significant optical and electrical properties, which have wide potential applications in various MEMS/NEMS devices such as photodetectors and nanogenerators.

Keywords: dielectrics, nanocomposites, nanogenerators, photodetectors

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Authors: Abdelfetah Laouzai, Rachid Ouafi

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In a traffic network, users usually choose their way so that it reduces their travel time between pairs origin-destination. This behavior might seem selfish as it produces congestions in different parts of the network. The traffic assignment problem (TAP) models the interactions between congestion and user travel decisions to obtain vehicles flows over each axis of the traffic network. The resolution methods of TAP serve as a tool allows predicting users’ distribution, identifying congesting points and affecting the travelers’ behavior in the choice of their route in the network following dynamic data. In this article, we will present a review about specific resolution approach of TAP. A comparative analysis is carried out on those approaches so that it highlights the characteristics, advantages and disadvantages of each.

Keywords: network traffic, travel decisions, approaches, traffic assignment, flows

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Authors: A. A. Behroozpoor, M. M. Mazarei

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In this paper, a fuzzy recurrent neural network is proposed for solving the classical quadratic control problem subject to linear equality and bound constraints. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed.

Keywords: REFERENCES [1] Xia, Y, A new neural network for solving linear and quadratic programming problems. IEEE Transactions on Neural Networks, 7(6), 1996, pp.1544–1548. [2] Xia, Y., & Wang, J, A recurrent neural network for solving nonlinear convex programs subject to linear constraints. IEEE Transactions on Neural Networks, 16(2), 2005, pp. 379–386. [3] Xia, Y., H, Leung, & J, Wang, A projection neural network and its application to constrained optimization problems. IEEE Transactions Circuits and Systems-I, 49(4), 2002, pp.447–458.B. [4] Q. Liu, Z. Guo, J. Wang, A one-layer recurrent neural network for constrained seudoconvex optimization and its application for dynamic portfolio optimization. Neural Networks, 26, 2012, pp. 99-109.

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Authors: Nir Nissim, Erez Shalom, Tomer Lancewiki, Yuval Elovici, Yuval Shahar

Abstract:

Background: A Medical Device (MD) is an instrument, machine, implant, or similar device that includes a component intended for the purpose of the diagnosis, cure, treatment, or prevention of disease in humans or animals. Medical devices play increasingly important roles in health services eco-systems, including: (1) Patient Diagnostics and Monitoring; Medical Treatment and Surgery; and Patient Life Support Devices and Stabilizers. MDs are part of the medical device eco-system and are connected to the network, sending vital information to the internal medical information systems of medical centers that manage this data. Wireless components (e.g. Wi-Fi) are often embedded within medical devices, enabling doctors and technicians to control and configure them remotely. All these functionalities, roles, and uses of MDs make them attractive targets of cyber-attacks launched for many malicious goals; this trend is likely to significantly increase over the next several years, with increased awareness regarding MD vulnerabilities, the enhancement of potential attackers’ skills, and expanded use of medical devices. Significance: We propose to develop and implement Cyber-Med, a unique collaborative project of Ben-Gurion University of the Negev and the Clalit Health Services Health Maintenance Organization. Cyber-Med focuses on the development of a comprehensive detection framework that relies on a critical attack repository that we aim to create. Cyber-Med will allow researchers and companies to better understand the vulnerabilities and attacks associated with medical devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The Cyber-Med detection framework will consist of two independent, but complementary detection approaches: one for known attacks, and the other for unknown attacks. These modules incorporate novel ideas and algorithms inspired by our team's domains of expertise, including cyber security, biomedical informatics, and advanced machine learning, and temporal data mining techniques. The establishment and maintenance of Cyber-Med’s up-to-date attack repository will strengthen the capabilities of Cyber-Med’s detection framework. Major Findings: Based on our initial survey, we have already found more than 15 types of vulnerabilities and possible attacks aimed at MDs and their eco-system. Many of these attacks target individual patients who use devices such pacemakers and insulin pumps. In addition, such attacks are also aimed at MDs that are widely used by medical centers such as MRIs, CTs, and dialysis engines; the information systems that store patient information; protocols such as DICOM; standards such as HL7; and medical information systems such as PACS. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched against MDs. Very little research has been conducted in order to protect these devices from cyber-attacks, since most of the development and engineering efforts are aimed at the devices’ core medical functionality, the contribution to patients’ healthcare, and the business aspects associated with the medical device.

Keywords: medical device, cyber security, attack, detection, machine learning

Procedia PDF Downloads 326

Authors: Jonathon Bailey, Neil Bressloff, Nick Curzen

Abstract:

Transcatheter Aortic Valve Implantation (TAVI) devices are stent-like frames with prosthetic leaflets on the inside, which are percutaneously implanted. The device in a crimped state is fed through the arteries to the aortic root, where the device frame is opened through either self-expansion or balloon expansion, which reveals the prosthetic valve within. The frequency at which TAVI is being used to treat aortic stenosis is rapidly increasing. In time, TAVI is likely to become the favoured treatment over Surgical Valve Replacement (SVR). Mortality after TAVI has been associated with severe Paravalvular Aortic Regurgitation (PAR). PAR occurs when the frame of the TAVI device does not make an effective seal against the internal surface of the aortic root, allowing blood to flow backwards about the valve. PAR is common in patients and has been reported to some degree in as much as 76% of cases. Severe PAR (grade 3 or 4) has been reported in approximately 17% of TAVI patients resulting in post-procedural mortality increases from 6.7% to 16.5%. TAVI devices, like SVR devices, are circular in cross-section as the aortic root is often considered to be approximately circular in shape. In reality, however, the aortic root is often non-circular. The ascending aorta, aortic sino tubular junction, aortic annulus and left ventricular outflow tract have an average ellipticity ratio of 1.07, 1.09, 1.29, and 1.49 respectively. An elliptical aortic root does not severely affect SVR, as the leaflets are completely removed during the surgical procedure. However, an elliptical aortic root can inhibit the ability of the circular Balloon-Expandable (BE) TAVI devices to conform to the interior of the aortic root wall, which increases the risk of PAR. Self-Expanding (SE) TAVI devices are considered better at conforming to elliptical aortic roots, however the valve leaflets were not designed for elliptical function, furthermore the incidence of PAR is greater in SE devices than BE devices (19.8% vs. 12.2% respectively). If a patient’s aortic root is too severely elliptical, they will not be suitable for TAVI, narrowing the treatment options to SVR. It therefore follows that in order to increase the population who can undergo TAVI, and reduce the risk associated with TAVI, non-circular devices should be developed. Computational simulations were employed to further advance our understanding of non-circular TAVI devices. Radial stiffness of the TAVI devices in multiple directions, frame bending stiffness and resistance to balloon induced expansion are all computationally simulated. Finally, a simulation has been developed that demonstrates the expansion of TAVI devices into a non-circular patient specific aortic root model in order to assess the alterations in deployment dynamics, PAR and the stresses induced in the aortic root.

Keywords: tavi, tavr, fea, par, fem

Procedia PDF Downloads 417