23 research outputs found

    Computational Intelligence and Human- Computer Interaction: Modern Methods and Applications

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    The present book contains all of the articles that were accepted and published in the Special Issue of MDPI’s journal Mathematics titled "Computational Intelligence and Human–Computer Interaction: Modern Methods and Applications". This Special Issue covered a wide range of topics connected to the theory and application of different computational intelligence techniques to the domain of human–computer interaction, such as automatic speech recognition, speech processing and analysis, virtual reality, emotion-aware applications, digital storytelling, natural language processing, smart cars and devices, and online learning. We hope that this book will be interesting and useful for those working in various areas of artificial intelligence, human–computer interaction, and software engineering as well as for those who are interested in how these domains are connected in real-life situations

    Time-Shifted Prefetching and Edge-Caching of Video Content: Insights, Algorithms, and Solutions

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    Video traffic accounts for 82% of global Internet traffic and is growing at an unprecedented rate. As a result of this rapid growth and popularity of video content, the network is heavily burdened. To cope with this, service providers have to spend several millions of dollars for infrastructure upgrades; these upgrades are typically triggered when there is a reasonably sustained peak usage that exceeds 80% of capacity. In this context, with network traffic load being significantly higher during peak periods (up to 5 times as much), we explore the problem of prefetching video content during off-peak periods of the network even when such periods are substantially separated from the actual usage-time. To this end, we collected YouTube and Netflix usage from over 1500 users spanning at least a one-year period consisting of approximately 8.5 million videos collectively watched. We use the datasets to analyze and present key insights about user-level usage behavior, and show that our analysis can be used by researchers to tackle a myriad of problems in the general domains of networking and communication. Thereafter, equipped with the datasets and our derived insights, we develop a set of data-driven prediction and prefetching solutions, using machine-learning and deep-learning techniques (specifically supervised classifiers and LSTM networks), which anticipates the video content the user will consume based on their prior watching behavior, and prefetches it during off-peak periods. We find that our developed solutions can reduce nearly 35% of peak-time YouTube traffic and 70% of peak-time Netflix series traffic. We developed and evaluated a proof-of-concept system for prefetching video traffic. We also show how to integrate the two systems for prefetching YouTube and Netflix content. Furthermore, based on our findings from our developed algorithms, we develop a framework for prefetching video content regardless of the type of video and platform upon which it is hosted.Ph.D

    Telecommunications Networks

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    This book guides readers through the basics of rapidly emerging networks to more advanced concepts and future expectations of Telecommunications Networks. It identifies and examines the most pressing research issues in Telecommunications and it contains chapters written by leading researchers, academics and industry professionals. Telecommunications Networks - Current Status and Future Trends covers surveys of recent publications that investigate key areas of interest such as: IMS, eTOM, 3G/4G, optimization problems, modeling, simulation, quality of service, etc. This book, that is suitable for both PhD and master students, is organized into six sections: New Generation Networks, Quality of Services, Sensor Networks, Telecommunications, Traffic Engineering and Routing

    An Embedded Platform for Testbed Implementation of Multi-Agent System in Building Energy Management System

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    This paper presents a hardware testbed for testing the building energy management system (BEMS) based-on the multi agent system (MAS). The objective of BEMS is to maximize user comfort while minimizing the energy extracted from the grid. The proposed system implements a multi-objective optimization technique using a genetic algorithm (GA) and the fuzzy logic controller (FLC) to control the room temperature and illumination setpoints. The agents are implemented on the low cost embedded systems equipped with the WiFi communication for communicating between the agents. The photovoltaic (PV)-battery system, the air conditioning system, the lighting system, and the electrical loads are modeled and simulated on the embedded hardware. The popular communication protocols such as Message Queuing Telemetry Transport (MQTT) and Modbus TCP/IP are adopted for integrating the proposed MAS with the existing infrastructures and devices. The experimental results show that the sampling time of the proposed system is 16.50 s. Therefore it is suitable for implementing the BEMS in a real-time where the data are updated in an hourly or minutely basis. Further, the proposed optimization technique shows better results in optimizing the comfort index and the energy extracted from the grid compared to the existing methods. Keywords: BEMS; MAS; embedded system; multi-objective optimization; genetic algorith

    Channel sharing utility function of power control game in cognitive femtocell network

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    The use of sharing channel simultaneously has become the trend in telecommunication technology particularly in network with distributed users as the allocation of frequency spectrum becomes more crowded. The proposed power control method in cognitive femtocell network is based on game theory (commonly known as power control game, PCG). This method uses utility function formula as the goal of game theory for power strategy in power update process. Utility function formula of Proposed PCG includes channel sharing factor that aimed to accommodate the system requirement of channel sharing. The result showed that the implementation of channel factor is inversely proportional to the signal to noise and interference ratio (SINR) and transmit power, but proportional to utility function. In comparison of user transmit power and SINR with two other methods, can also be conclude that Proposed PCG was able to achieve SINR of 5.49 dB and above the SINR target 5 dB, while the Thalabani (TB) and Koskie-Gajic (KG) were only able to achieve respective SINR of 4.87 dB and 4.98 dB. It can be concluded that the Proposed PCG was better in achieving the SINR target. It means that the quality of service in this system can be fulfilled properly

    Sistem Smart Grid Untuk Optimalisasi Pemakaian Daya Listrik Pada Perumahan Dan Gedung Dengan Pemanfaatan Energi Surya

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    Sistem Smart Grid merupakan teknologi kelistrikan terkini yang mampu mengalirkan arus listrik dan informasi secara dua arah, dari pembangkit ke konsumen dan sebaliknya. Kemajuan teknologi ini mulai banyak diimplementasikan dalam pengelolaan energi listrik, salah satunya integrasi dengan sumber energi terbarukan. Salah satu permasalahan yang banyak ditemui dalam bidang kelistrikan adalah manajemen energi listrik. Pada penelitian ini, peneliti merancang model kelistrikan modern (Smart Grid) untuk manajemen energi di perumahan dan gedung-gedung dalam rangka pengembangan sistem Smart Home dan Smart Building. Penelitian yang dikembangkan akan mengoptimalkan pemakaian energi listrik secara real-time tergantung kondisi beban dan pembangkit energi yang ada saat itu. Pada tahun pertama dirancang model sistem Smart Grid untuk optimalisasi pemakaian daya listrik rumah (TKT-3). Sedangkan pada tahun kedua dirancang model sistem Smart Grid untuk optimalisasi pemakaian daya listrik gedung (TKT-3). Dengan sistem yang dikembangkan ini, diharapkan pemanfaatan, pengelolaan energi listrik utamanya yang bersumber dari energi surya dapat dimaksimalkan, dan sekaligus merupakan upaya pencapaian sasaran Renstra penelitian perguruan tinggi terutama pada bidang unggulan energi baru dan terbarukan
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