Search results for: network user rules
7402 Virtual Routing Function Allocation Method for Minimizing Total Network Power Consumption
Authors: Kenichiro Hida, Shin-Ichi Kuribayashi
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In a conventional network, most network devices, such as routers, are dedicated devices that do not have much variation in capacity. In recent years, a new concept of network functions virtualisation (NFV) has come into use. The intention is to implement a variety of network functions with software on general-purpose servers and this allows the network operator to select their capacities and locations without any constraints. This paper focuses on the allocation of NFV-based routing functions which are one of critical network functions, and presents the virtual routing function allocation algorithm that minimizes the total power consumption. In addition, this study presents the useful allocation policy of virtual routing functions, based on an evaluation with a ladder-shaped network model. This policy takes the ratio of the power consumption of a routing function to that of a circuit and traffic distribution between areas into consideration. Furthermore, the present paper shows that there are cases where the use of NFV-based routing functions makes it possible to reduce the total power consumption dramatically, in comparison to a conventional network, in which it is not economically viable to distribute small-capacity routing functions.Keywords: NFV, resource allocation, virtual routing function, minimum power consumption
Procedia PDF Downloads 3417401 Scheduling Method for Electric Heater in HEMS considering User’s Comfort
Authors: Yong-Sung Kim, Je-Seok Shin, Ho-Jun Jo, Jin-O Kim
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Home Energy Management System (HEMS) which makes the residential consumers contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it also represents impacts of the comfort level on the scheduling result.Keywords: load scheduling, usage pattern, user’s comfort, copula function, branch and bound, electric heater
Procedia PDF Downloads 5847400 A Survey of Recognizing of Daily Living Activities in Multi-User Smart Home Environments
Authors: Kulsoom S. Bughio, Naeem K. Janjua, Gordana Dermody, Leslie F. Sikos, Shamsul Islam
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The advancement in information and communication technologies (ICT) and wireless sensor networks have played a pivotal role in the design and development of real-time healthcare solutions, mainly targeting the elderly living in health-assistive smart homes. Such smart homes are equipped with sensor technologies to detect and record activities of daily living (ADL). This survey reviews and evaluates existing approaches and techniques based on real-time sensor-based modeling and reasoning in single-user and multi-user environments. It classifies the approaches into three main categories: learning-based, knowledge-based, and hybrid, and evaluates how they handle temporal relations, granularity, and uncertainty. The survey also highlights open challenges across various disciplines (including computer and information sciences and health sciences) to encourage interdisciplinary research for the detection and recognition of ADLs and discusses future directions.Keywords: daily living activities, smart homes, single-user environment, multi-user environment
Procedia PDF Downloads 1417399 Credit Risk Assessment Using Rule Based Classifiers: A Comparative Study
Authors: Salima Smiti, Ines Gasmi, Makram Soui
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Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.Keywords: credit risk assessment, classification algorithms, data mining, rule extraction
Procedia PDF Downloads 1817398 A Survey of Attacks and Security Requirements in Wireless Sensor Networks
Authors: Vishnu Pratap Singh Kirar
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Wireless sensor network (WSN) is a network of many interconnected networked systems, they equipped with energy resources and they are used to detect other physical characteristics. On WSN, there are many researches are performed in past decades. WSN applicable in many security systems govern by military and in many civilian related applications. Thus, the security of WSN gets attention of researchers and gives an opportunity for many future aspects. Still, there are many other issues are related to deployment and overall coverage, scalability, size, energy efficiency, quality of service (QoS), computational power and many more. In this paper we discus about various applications and security related issue and requirements of WSN.Keywords: wireless sensor network (WSN), wireless network attacks, wireless network security, security requirements
Procedia PDF Downloads 4917397 Developing a Secure Iris Recognition System by Using Advance Convolutional Neural Network
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
Procedia PDF Downloads 2187396 Usability Guidelines for Arab E-Government Websites
Authors: Omyma Alosaimi, Asma Alsumait
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The website developer and designer should follow usability guidelines to provide a user-friendly interface. Many guidelines and heuristics have been developed by previous studies to help both the developer and designer in this task, but E-government websites are special cases that require specialized guidelines. This paper introduces a set of eighteen guidelines for evaluating the usability of e-government websites in general and Arabic e-government websites specifically, along with a check list of how to apply them. The validity and effectiveness of these guidelines were evaluated against a variety of user characteristics. The results indicated that the proposed set of guidelines can be used to identify qualitative similarities and differences with user testing and that the new set is best suited for evaluating general and e-governmental usability.Keywords: e-government, human computer interaction, usability evaluation, usability guidelines
Procedia PDF Downloads 3957395 Assessment on the Conduct of Arnis Competition in Pasuc National Olympics 2015: Basis for Improvement of Rules in Competition
Authors: Paulo O. Motita
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The Philippine Association of State Colleges and University (PASUC) is an association of State owned and operated higher learning institutions in the Philippines, it is the association that spearhead the conduct of the Annual National Athletic competitions for State Colleges and Universities and Arnis is one of the regular sports. In 2009, Republic Act 9850 also known as declared Arnis as the National Sports and Martial arts of the Philippines. Arnis an ancient Filipino Martial Arts is the major sports in the Annual Palarong Pambansa and other school based sports events. The researcher as a Filipino Martial Arts master and a former athlete desired to determine the extent of acceptability of the arnis rules in competition which serves as the basis for the development of arnis rules. The study aimed to assess the conduct of Arnis competition in PASUC Olympics 2015 in Tugegarao City, Cagayan, Philippines.the rules and conduct itself as perceived by Officiating officials, Coaches and Athletes during the competition last February 7-15, 2015. The descriptive method of research was used, the survey questionnaire as the data gathering instrument was validated. The respondents were composed of 12 Officiating officials, 19 coaches and 138 athletes representing the different regions. Their responses were treated using the Mean, Percentage and One-way Analysis of Variance. The study revealed that the conduct of Arnis competition in PASUC Olympics 2015 was at the low extent to moderate extent as perceived by the three groups of respondents in terms of officiating, scoring and giving violations. Furthermore there is no significant difference in the assessment of the three groups of respondents in the assessment of Anyo and Labanan. Considering the findings of the study, the following conclusions were drawn: 1). There is a need to identify the criteria for judging in Anyo and a tedious scrutiny on the rules of the game for labanan. 2) The three groups of respondents have similar views towards the assessment on the overall competitions for anyo that there were no clear technical guidelines for judging the performance of anyo event. 3). The three groups of respondents have similar views towards the assessment on the overall competitions for labanan that there were no clear technical guidelines for majority rule of giving scores in labanan. 4) The Anyo performance should be rated according to effectiveness of techniques and performance of weapon/s that are being used. 5) On other issues and concern towards the rules of competitions, labanan should be addressed in improving rules of competitions, focus on the applications of majority rules for scoring, players shall be given rest interval, a clear guidelines and set a standard qualifications for officiating officials.Keywords: PASUC Olympics 2015, Arnis rules of competition, Anyo, Labanan, officiating
Procedia PDF Downloads 4587394 Detection of Important Biological Elements in Drug-Drug Interaction Occurrence
Authors: Reza Ferdousi, Reza Safdari, Yadollah Omidi
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Drug-drug interactions (DDIs) are main cause of the adverse drug reactions and nature of the functional and molecular complexity of drugs behavior in human body make them hard to prevent and treat. With the aid of new technologies derived from mathematical and computational science the DDIs problems can be addressed with minimum cost and efforts. Market basket analysis is known as powerful method to identify co-occurrence of thing to discover patterns and frequency of the elements. In this research, we used market basket analysis to identify important bio-elements in DDIs occurrence. For this, we collected all known DDIs from DrugBank. The obtained data were analyzed by market basket analysis method. We investigated all drug-enzyme, drug-carrier, drug-transporter and drug-target associations. To determine the importance of the extracted bio-elements, extracted rules were evaluated in terms of confidence and support. Market basket analysis of the over 45,000 known DDIs reveals more than 300 important rules that can be used to identify DDIs, CYP 450 family were the most frequent shared bio-elements. We applied extracted rules over 2,000,000 unknown drug pairs that lead to discovery of more than 200,000 potential DDIs. Analysis of the underlying reason behind the DDI phenomena can help to predict and prevent DDI occurrence. Ranking of the extracted rules based on strangeness of them can be a supportive tool to predict the outcome of an unknown DDI.Keywords: drug-drug interaction, market basket analysis, rule discovery, important bio-elements
Procedia PDF Downloads 3097393 Protection Plan of Medium Voltage Distribution Network in Tunisia
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The distribution networks are often exposed to harmful incidents which can halt the electricity supply of the customer. In this context, we studied a real case of a critical zone of the Tunisian network which is currently characterized by the dysfunction of its plan of protection. In this paper, we were interested in the harmonization of the protection plan settings in order to ensure a perfect selectivity and a better continuity of service on the whole of the network.Keywords: distribution network Gabes-Tunisia, continuity of service, protection plan settings, selectivity
Procedia PDF Downloads 5107392 Easily Memorable Strong Password Generation and Retrieval
Authors: Shatadru Das, Natarajan Vijayarangan
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In this paper, a system and method for generating and recovering an authorization code has been designed and analyzed. The system creates an authorization code by accepting a base-sentence from a user. Based on the characters present in this base-sentence, the system computes a base-sentence matrix. The system also generates a plurality of patterns. The user can either select the pattern from the multiple patterns suggested by the system or can create his/her own pattern. The system then performs multiplications between the base-sentence matrix and the selected pattern matrix at different stages in the path forward, for obtaining a strong authorization code. In case the user forgets the base sentence, the system has a provision to manage and retrieve 'forgotten authorization code'. This is done by fragmenting the base sentence into different matrices and storing the fragmented matrices into a repository after computing matrix multiplication with a security question-answer approach and with a secret key provided by the user.Keywords: easy authentication, key retrieval, memorable passwords, strong password generation
Procedia PDF Downloads 4007391 Quality and Quantity in the Strategic Network of Higher Education Institutions
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
Procedia PDF Downloads 3487390 Energy Efficient Firefly Algorithm in Wireless Sensor Network
Authors: Wafa’ Alsharafat, Khalid Batiha, Alaa Kassab
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Wireless sensor network (WSN) is comprised of a huge number of small and cheap devices known as sensor nodes. Usually, these sensor nodes are massively and deployed randomly as in Ad-hoc over hostile and harsh environment to sense, collect and transmit data to the needed locations (i.e., base station). One of the main advantages of WSN is that the ability to work in unattended and scattered environments regardless the presence of humans such as remote active volcanoes environments or earthquakes. In WSN expanding network, lifetime is a major concern. Clustering technique is more important to maximize network lifetime. Nature-inspired algorithms are developed and optimized to find optimized solutions for various optimization problems. We proposed Energy Efficient Firefly Algorithm to improve network lifetime as long as possible.Keywords: wireless network, SN, Firefly, energy efficiency
Procedia PDF Downloads 3897389 Employing Bayesian Artificial Neural Network for Evaluation of Cold Rolling Force
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
Procedia PDF Downloads 4437388 An Artificially Intelligent Teaching-Agent to Enhance Learning Interactions in Virtual Settings
Authors: Abdulwakeel B. Raji
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This paper introduces a concept of an intelligent virtual learning environment that involves communication between learners and an artificially intelligent teaching agent in an attempt to replicate classroom learning interactions. The benefits of this technology over current e-learning practices is that it creates a virtual classroom where real time adaptive learning interactions are made possible. This is a move away from the static learning practices currently being adopted by e-learning systems. Over the years, artificial intelligence has been applied to various fields, including and not limited to medicine, military applications, psychology, marketing etc. The purpose of e-learning applications is to ensure users are able to learn outside of the classroom, but a major limitation has been the inability to fully replicate classroom interactions between teacher and students. This study used comparative surveys to gain information and understanding of the current learning practices in Nigerian universities and how they compare to these practices compare to the use of a developed e-learning system. The study was conducted by attending several lectures and noting the interactions between lecturers and tutors and as an aftermath, a software has been developed that deploys the use of an artificial intelligent teaching-agent alongside an e-learning system to enhance user learning experience and attempt to create the similar learning interactions to those found in classroom and lecture hall settings. Dialogflow has been used to implement a teaching-agent, which has been developed using JSON, which serves as a virtual teacher. Course content has been created using HTML, CSS, PHP and JAVASCRIPT as a web-based application. This technology can run on handheld devices and Google based home technologies to give learners an access to the teaching agent at any time. This technology also implements the use of definite clause grammars and natural language processing to match user inputs and requests with defined rules to replicate learning interactions. This technology developed covers familiar classroom scenarios such as answering users’ questions, asking ‘do you understand’ at regular intervals and answering subsequent requests, taking advanced user queries to give feedbacks at other periods. This software technology uses deep learning techniques to learn user interactions and patterns to subsequently enhance user learning experience. A system testing has been undergone by undergraduate students in the UK and Nigeria on the course ‘Introduction to Database Development’. Test results and feedback from users shows that this study and developed software is a significant improvement on existing e-learning systems. Further experiments are to be run using the software with different students and more course contents.Keywords: virtual learning, natural language processing, definite clause grammars, deep learning, artificial intelligence
Procedia PDF Downloads 1357387 How to Modernise the European Competition Network (ECN)
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
Procedia PDF Downloads 3157386 Training AI to Be Empathetic and Determining the Psychotype of a Person During a Conversation with a Chatbot
Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin
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The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a userKeywords: AI, empathetic, chatbot, AI models
Procedia PDF Downloads 927385 User Acceptance Criteria for Digital Libraries
Authors: Yu-Ming Wang, Jia-Hong Jian
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The Internet and digital publication technologies have brought dramatic impacts on how people collect, organize, disseminate, access, store, and use information. More and more governments, schools, and organizations spent huge funds to develop digital libraries. A digital library can be regarded as a web extension of traditional physically libraries. People can search diverse publications, find out the position of knowledge resources, and borrow or buy publications through digital libraries. People can gain knowledge and students or employees can finish their reports by using digital libraries. Since the considerable funds and energy have been invested in implementing digital libraries, it is important to understand the evaluative criteria from the users’ viewpoint in order to enhance user acceptance. This study develops a list of user acceptance criteria for digital libraries. An initial criteria list was developed based on some previously validated instruments related to digital libraries. Data were collected from user experiences of digital libraries. The exploratory factor analysis and confirmatory factor analysis were adopted to purify the criteria list. The reliabilities and validities were tested. After validating the criteria list, a user survey was conducted to collect the comparative importance of criteria. The analytic hierarchy process (AHP) method was utilized to derive the importance of each criterion. The results of this study contribute to an e understanding of the criteria and relative importance that users evaluate for digital libraries.Keywords: digital library, user acceptance, analytic hierarchy process, factor analysis
Procedia PDF Downloads 2537384 IEEE802.15.4e Based Scheduling Mechanisms and Systems for Industrial Internet of Things
Authors: Ho-Ting Wu, Kai-Wei Ke, Bo-Yu Huang, Liang-Lin Yan, Chun-Ting Lin
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With the advances in advanced technology, wireless sensor network (WSN) has become one of the most promising candidates to implement the wireless industrial internet of things (IIOT) architecture. However, the legacy IEEE 802.15.4 based WSN technology such as Zigbee system cannot meet the stringent QoS requirement of low powered, real-time, and highly reliable transmission imposed by the IIOT environment. Recently, the IEEE society developed IEEE 802.15.4e Time Slotted Channel Hopping (TSCH) access mode to serve this purpose. Furthermore, the IETF 6TiSCH working group has proposed standards to integrate IEEE 802.15.4e with IPv6 protocol smoothly to form a complete protocol stack for IIOT. In this work, we develop key network technologies for IEEE 802.15.4e based wireless IIoT architecture, focusing on practical design and system implementation. We realize the OpenWSN-based wireless IIOT system. The system architecture is divided into three main parts: web server, network manager, and sensor nodes. The web server provides user interface, allowing the user to view the status of sensor nodes and instruct sensor nodes to follow commands via user-friendly browser. The network manager is responsible for the establishment, maintenance, and management of scheduling and topology information. It executes centralized scheduling algorithm, sends the scheduling table to each node, as well as manages the sensing tasks of each device. Sensor nodes complete the assigned tasks and sends the sensed data. Furthermore, to prevent scheduling error due to packet loss, a schedule inspection mechanism is implemented to verify the correctness of the schedule table. In addition, when network topology changes, the system will act to generate a new schedule table based on the changed topology for ensuring the proper operation of the system. To enhance the system performance of such system, we further propose dynamic bandwidth allocation and distributed scheduling mechanisms. The developed distributed scheduling mechanism enables each individual sensor node to build, maintain and manage the dedicated link bandwidth with its parent and children nodes based on locally observed information by exchanging the Add/Delete commands via two processes. The first process, termed as the schedule initialization process, allows each sensor node pair to identify the available idle slots to allocate the basic dedicated transmission bandwidth. The second process, termed as the schedule adjustment process, enables each sensor node pair to adjust their allocated bandwidth dynamically according to the measured traffic loading. Such technology can sufficiently satisfy the dynamic bandwidth requirement in the frequently changing environments. Last but not least, we propose a packet retransmission scheme to enhance the system performance of the centralized scheduling algorithm when the packet delivery rate (PDR) is low. We propose a multi-frame retransmission mechanism to allow every single network node to resend each packet for at least the predefined number of times. The multi frame architecture is built according to the number of layers of the network topology. Performance results via simulation reveal that such retransmission scheme is able to provide sufficient high transmission reliability while maintaining low packet transmission latency. Therefore, the QoS requirement of IIoT can be achieved.Keywords: IEEE 802.15.4e, industrial internet of things (IIOT), scheduling mechanisms, wireless sensor networks (WSN)
Procedia PDF Downloads 1607383 Enhanced Constraint-Based Optical Network (ECON) for Enhancing OSNR
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
Procedia PDF Downloads 4887382 A Proposed Algorithm for Obtaining the Map of Subscribers’ Density Distribution for a Mobile Wireless Communication Network
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
Procedia PDF Downloads 3097381 Twitter Ego Networks and the Capital Markets: A Social Network Analysis Perspective of Market Reactions to Earnings Announcement Events
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
Procedia PDF Downloads 1217380 A Web-Based Self-Learning Grammar for Spoken Language Understanding
Authors: S. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno
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One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.Keywords: spoken dialog system, spoken language understanding, web semantic, name entity recognition
Procedia PDF Downloads 3387379 Memorabilia of Suan Sunandha through Interactive User Interface
Authors: Nalinee Sophatsathit
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The objectives of memorabilia of Suan Sunandha are to develop a general knowledge presentation about the historical royal garden through interactive graphic simulation technique and to employ high-functionality context in enhancing interactive user navigation. The approach infers non-intrusive display of relevant history in response to situational context. User’s navigation runs through the virtual reality campus, consisting of new and restored buildings. A flash back presentation of information pertaining to the history in the form of photos, paintings, and textual descriptions are displayed along each passing-by building. To keep the presentation lively, graphical simulation is created in a serendipity game play so that the user can both learn and enjoy the educational tour. The benefits of this human-computer interaction development are two folds. First, lively presentation technique and situational context modeling are developed that entail a usable paradigm of knowledge and information presentation combinations. Second, cost effective training and promotion for both internal personnel and public visitors to learn and keep informed of this historical royal garden can be furnished without the need for a dedicated public relations service. Future improvement on graphic simulation and ability based display can extend this work to be more realistic, user-friendly, and informative for all.Keywords: interactive user navigation, high-functionality context, situational context, human-computer interaction
Procedia PDF Downloads 3577378 Personalization of Context Information Retrieval Model via User Search Behaviours for Ranking Document Relevance
Authors: Kehinde Agbele, Longe Olumide, Daniel Ekong, Dele Seluwa, Akintoye Onamade
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One major problem of most existing information retrieval systems (IRS) is that they provide even access and retrieval results to individual users specially based on the query terms user issued to the system. When using IRS, users often present search queries made of ad-hoc keywords. It is then up to IRS to obtain a precise representation of user’s information need, and the context of the information. In effect, the volume and range of the Internet documents is growing exponentially and consequently causes difficulties for a user to obtain information that precisely matches the user interest. Diverse combination techniques are used to achieve the specific goal. This is due, firstly, to the fact that users often do not present queries to IRS that optimally represent the information they want, and secondly, the measure of a document's relevance is highly subjective between diverse users. In this paper, we address the problem by investigating the optimization of IRS to individual information needs in order of relevance. The paper addressed the development of algorithms that optimize the ranking of documents retrieved from IRS. This paper addresses this problem with a two-fold approach in order to retrieve domain-specific documents. Firstly, the design of context of information. The context of a query determines retrieved information relevance using personalization and context-awareness. Thus, executing the same query in diverse contexts often leads to diverse result rankings based on the user preferences. Secondly, the relevant context aspects should be incorporated in a way that supports the knowledge domain representing users’ interests. In this paper, the use of evolutionary algorithms is incorporated to improve the effectiveness of IRS. A context-based information retrieval system that learns individual needs from user-provided relevance feedback is developed whose retrieval effectiveness is evaluated using precision and recall metrics. The results demonstrate how to use attributes from user interaction behavior to improve the IR effectiveness.Keywords: context, document relevance, information retrieval, personalization, user search behaviors
Procedia PDF Downloads 4637377 Reliability Factors Based Fuzzy Logic Scheme for Spectrum Sensing
Authors: Tallataf Rasheed, Adnan Rashdi, Ahmad Naeem Akhtar
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The accurate spectrum sensing is a fundamental requirement of dynamic spectrum access for deployment of Cognitive Radio Network (CRN). To acheive this requirement a Reliability factors based Fuzzy Logic (RFL) Scheme for Spectrum Sensing has been proposed in this paper. Cognitive Radio User (CRU) predicts the presence or absence of Primary User (PU) using energy detector and calculates the Reliability factors which are SNR of sensing node, threshold of energy detector and decision difference of each node with other nodes in a cooperative spectrum sensing environment. Then the decision of energy detector is combined with Reliability factors of sensing node using Fuzzy Logic. These Reliability Factors used in RFL Scheme describes the reliability of decision made by a CRU to improve the local spectrum sensing. This Fuzzy combining scheme provides the accuracy of decision made by sensornode. The simulation results have shown that the proposed technique provide better PU detection probability than existing Spectrum Sensing Techniques.Keywords: cognitive radio, spectrum sensing, energy detector, reliability factors, fuzzy logic
Procedia PDF Downloads 4867376 CERD: Cost Effective Route Discovery in Mobile Ad Hoc Networks
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
Procedia PDF Downloads 3477375 Estimating View-Through Ad Attribution from User Surveys Using Convex Optimization
Authors: Yuhan Lin, Rohan Kekatpure, Cassidy Yeung
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In Digital Marketing, robust quantification of View-through attribution (VTA) is necessary for evaluating channel effectiveness. VTA occurs when a product purchase is aided by an Ad but without an explicit click (e.g. a TV ad). A lack of a tracking mechanism makes VTA estimation challenging. Most prevalent VTA estimation techniques rely on post-purchase in-product user surveys. User surveys enable the calculation of channel multipliers, which are the ratio of the view-attributed to the click-attributed purchases of each marketing channel. Channel multipliers thus provide a way to estimate the unknown VTA for a channel from its known click attribution. In this work, we use Convex Optimization to compute channel multipliers in a way that enables a mathematical encoding of the expected channel behavior. Large fluctuations in channel attributions often result from overfitting the calculations to user surveys. Casting channel attribution as a Convex Optimization problem allows an introduction of constraints that limit such fluctuations. The result of our study is a distribution of channel multipliers across the entire marketing funnel, with important implications for marketing spend optimization. Our technique can be broadly applied to estimate Ad effectiveness in a privacy-centric world that increasingly limits user tracking.Keywords: digital marketing, survey analysis, operational research, convex optimization, channel attribution
Procedia PDF Downloads 1997374 Optimisation of the Hydrometeorological-Hydrometric Network: A Case Study in Greece
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
Procedia PDF Downloads 2877373 Improved Predictive Models for the IRMA Network Using Nonlinear Optimisation
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
Procedia PDF Downloads 156