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Intrusion Detection using Deep Neural Network Algorithm on the Internet of Things

Intrusion Detection using Deep Neural Network Algorithm on t...

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Syariful Ikhwan Adi Wibowo Budi Warsito Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia D3 Telecommunication Engineering Institut Teknologi Telkom Purwokerto Banyumas Indonesia Computer Science Informatics Department of Science and Mathematics Faculty Diponegoro University Semarang Indonesia Statistics Department of Science and Mathematics Faculty Diponegoro University Semarang Indonesia

ISBN: (数字)9781665460309

ISBN: (纸本)9781665460316

The increasing use of IoT devices on future networks is very helpful for humans in their lives. However, the increase in devices connected to IoT networks also increases the potential for attacks against those networks. Vulnerabilities in Internet of Things (IoT) networks can be exposed at any time. Artificial intelligence can be used to protect the IoT network by being able to detect attacks on the network so that they can be prevented. In this study, network detection was carried out using the Deep Neural Network (DNN) algorithm. The test was carried out using the UNSW Bot-IoT dataset with a comparison of training data of 75% of the overall data. The results obtained show the ability of the algorithm to detect attacks on average with 99.999% accuracy. The validation loss and training loss look very small. In this study, there is a validation loss that still occurs in overfitting, but the difference is very small.

关键词： Deep learning Training Satellites Neural networks Intrusion detection Training data Feature extraction

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The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Vishakha D Bhandarkar Aruna Sri Rongali Mohamed Dawood Shamout Prof. Sachin Pund Gigih Forda Nama Shrishailappa Patil Applied Mathematics and Humanities Yeshwantrao Chavan College of Engineering India Graduate Doctoral Information Technology/Graduate (Information Technology Emphasis/Information Technology Ph.D.) University of The Cumberlands US Department of Management College of Business Administration University of Sharjah Sharjah United Arab Emirates Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India Department of Informatics Doctoral Program of Environtmental Science University of Lampung Bandar Lampung Computer engineering Vishwakarma Institute of Technology Pune

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way..

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A Novel Blockchain-Based Strategy for Energy Conservation in Cognitive Wireless Sensor Networks

A Novel Blockchain-Based Strategy for Energy Conservation in...

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Blockchain Technology and Information Security (ICBCTIS), International Conference on

作者： Khemraj Sharma Rohit Goyal Sukesh Kumar Bhagat Sheenu Agarwal Girish Singh Bisht Mohemmed Hussien Department of Business Administration Doctoral Program in Management Sciences Nanhua University Dalin Taiwan School of Engineering and Computing Dev Bhoomi Uttarakhand University Dehradun India Department of Computer Science & Engineering Uttaranchal University Dehradun India Department of Electronics and Communication Engineering Uttarakhand Technical University Dehradun India Department of Computer Science and Engineering Tula's Institute Dehradun India Dehradun India The Islamic university Najaf Iraq

ISBN: (数字)9798331528324

ISBN: (纸本)9798331528331

Internet of Things (IoT) industrial applications have increased in internet-connected devices. As a result, accessibility, scalability, connectivity, and adaptability have become major challenges. It is possible to create connections between loT devices over the wireless medium, but efficiently utilizing scarce spectrum is the biggest concern. The paper proposes a novel method for selecting sensing nodes with the goal of reducing energy usage and increasing sensing efficiency. In order to ensure that node trust values conform to each other without any ambiguity, cryptography encrypts all information that relates to a node in a central node (CN). Nodes participating in CSS are selected based on their performance. Based on a comparison of various algorithms using varying numbers of nodes, the proposed algorithm achieves a 10% sensing efficiency.

关键词： Wireless communication Wireless sensor networks Adaptation models Machine learning algorithms Heuristic algorithms Scalability Sensors Blockchains Internet of Things Reliability

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Surface Structure of Soy Protein and Mungbean Protein Film Observed Using Atomic Force Microscopy

Surface Structure of Soy Protein and Mungbean Protein Film O...

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国际农业工程大会

作者： Keo INTABON Wimolrat CHEAPPIMOLCHAI Takaaki MAEKAWA Institute of Agricultural and Forestry Engineering University of Tsukuba 305-8577 Japan.Assistant Professor Doctoral Program Institute of Agricultural Science University of Tsukuba 1-1-1 Tennodai Tsukuba 305-8577 Japan Institute of Agricultural and Forestry Engineering University of Tsukuba 305-8577 Japan.professor

The relationship between surface structure and permeability property of soy protein and mungbean protein film was carried out using atomic force microscopy (AFM). The increasing of film porosity resulting in increasing of water vapor permeability (WVP) of films. AFM images showed that the surface of soy protein film was rougher than that of mungbean protein. Films with high glycerol concentration has a rough surface because of the lower evaporation

关键词： Soy protein film, Mungbean protein film, Atomic force microscopy (AFM), Film surface structure

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Sensing Architecture in Smart City: A Review Paper

Sensing Architecture in Smart City: A Review Paper

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International Conference on ICT For Smart Society (ICISS)

作者： Mindit Eriyadi Suhono Harso Supangkat Fadhil Hidayat Doctoral Program of Instiut Teknologi Bandung Bandung Indonesia School of Applied Science Universitas Telkom Bandung Indonesia School of Electrical Engineering and Informatics Instiut Teknologi Bandung Bandung Indonesia Smart City and Community Innovation Center Institut Teknologi Bandung Bandung Indonesia

Relevant smart city research involves many highly futuristic applications, such as smart transportation, in which smart roads warn drivers of impending traffic jams, smart parking, which communicates the location of available parking spaces to drivers, and smart environments, which allow homes and workplaces to fully automatically adjust their temperature to save energy. Complexity in the city sensing section is caused by the complexity of urban systems. The enormous number of sensor types and technologies utilized for municipal data collecting provide a problem. Some of the issues in city sensing are node deployment, sensing management, sensor network types, and their derivative variables, necessitating the development of a city sensing architecture capable of contributing to advances in efficiency, accuracy, and real-timeness.

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Multiscale modeling in rodent ventricular myocytes

Multiscale modeling in rodent ventricular myocytes

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作者： Lu, Shaoying Michailova, Anushka Saucerman, Jeffrey Cheng, Yuhui Yu, Zeyun Kaiser, Timothy Li, Wilfred Bank, Randolph Holst, Michael McCammon, J. Hayashi, Takeharu Hoshijima, Masahiko Arzberger, Peter McCulloch, Andrew Bioengineering Department University of Illinois United States Bioengineering Department UCSD United States Department of Biomedical Engineering University of Virginia United States Department of Mathematics UCSD United States UCSD United States College of Computer Science and Technology Jilin University China Department of Mathematics Center for Computational Mathematics and the Computational Science Mathematics and Engineering Doctoral Program at UCSD Department of Pharmacology UCSD United States Center for Research in Biological Systems UCSD United States Department of Bioengineering UCSD United States Department of Bioengineering PFBH 241 University of California San Diego 9500 Gilman Drive San Diego CA 92093-0412 United States

There is a growing body of experimental evidence suggesting that the Ca2+ signaling in ventricular myocytes is characterized by a high gradient near the cell membrane and a more uniform Ca2+ distribution in the cell interior [1]--[7]. An important reason for this phenomenon might be that in these cells the t-tubular system forms a network of extracellular space, extending deep into the cell interior. This allows the electrical signal, that propagates rapidly along the cell membrane, to reach the vicinity of the sarcoplasmic reticulum (SR), where intracellular Ca2+ required for myofilament activation is stored [1], [8]--[11]. Early studies of cardiac muscle showed that the t-tubules are found at intervals of about 2 lm along the longitudinal cell axis in close proximity to the Z-disks of the sarcomeres [12]. Subsequent studies have demonstrated that the t-tubular system has also longitudinal extensions [9]--[11], [13].

关键词： Cells

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Complex thermal evaluation for 2,2′-azobis(isobutyronitrile) by non-isothermal and isothermal kinetic analysis methods

Complex thermal evaluation for 2,2′-azobis(isobutyronitrile...

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作者： Liu, Shang-Hao Yu, Yen-Pin Lin, Yu-Chi Weng, Sheng-Yi Hsieh, Tung-Feng Hou, Hung-Yi Doctoral Program Department of Safety Health and Environmental Engineering National Yunlin University of Science and Technology YunTech 123 University Rd. Sec. 3 Douliou Yunlin 64002 Taiwan Department of Safety Health and Environmental Engineering National Yunlin University of Science and Technology YunTech 123 University Rd. Sec. 3 Douliou Yunlin 64002 Taiwan Department of General Education Center Chienkuo Technology University 1 Chiehshou North Rd. Changhua 50046 Changhua Taiwan Department of Occupational Safety and Health Jen-Teh Junior College of Medicine Nursing and Management 1 Jen-Teh Rd. Houlong Miaoli 35665 Taiwan

Azo compounds are widely used in dyes, pigments, blowing agents, and initiators. Unfortunately, these compounds contain the bivalent -N-N- composition which might be cleavaged readily even under high ambient temperature. The self-accelerating decomposition might cause a runaway reaction and lead to a fire or explosion when the cooling system fails or other upsets occur. To investigate the thermal stability parameters of 2,2′- azobis(isobutyronitrile) with thermal hazard and mechanism, differential scanning calorimetry and thermal activity monitor III were applied with non-isothermal method and isothermal method to obtain onset temperature (T 0), maximum temperature (Tmax), and heat of decomposition (ΔHd). Thermal stability parameters play a pivotal role in thermal analysis, leading particularly to complex evaluation of the inherently safer design during preparation, processing, transport, or storage. The results provide sufficient thermokinetic parameters for process safety in terms of proactive loss prevention program. © Akadémiai Kiadó, Budapest, Hungary 2014.

关键词： Differential scanning calorimetry

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Design of a Multilingual Translation System with Personalized Voice Characteristics

Design of a Multilingual Translation System with Personalize...

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International SoC Design Conference, ISOCC

作者： Chen-Hua Chen Guan-Yu Lai Chuan Lee Chang-Yu Wu Kuan-Lin Liu Shin-Chi Lai Doctoral Degree Program in Smart Industry Technology Research and Development Huwei Taiwan Dept. of Automation Engineering National Formosa University Huwei Taiwan Dept. Electronics Engineering National Yunlin University of Science and Technology Douliu Taiwan Dept. Automation Engineering & Smart Machinery and Intelligent Manufacturing Research Center National Formosa University Huwei Taiwan

ISBN: (数字)9798350377088

ISBN: (纸本)9798350377095

This study combines AI voice synthesis with IoT to create a real-time multilingual translation system. Front-end devices capture the speaker's voice, which is then played back in both original and translated forms, enabling consecutive interpreting. This system is ideal for multilingual scenarios. After digitization, audio signals undergo speech-to-text conversion, multilingual translation, and text-to-speech processing. Speech synthesis matches the speaker's voice characteristics, allowing listeners to hear the translation in the speaker's voice. Both voice-to-text conversion and translated audio playback use Wi-Fi for data transmission, facilitating future applications. In validation, the average translation and transmission time for each speech segment were 410 ms and 3.38 s, respectively. The synthesized voice similarity analysis achieved an accuracy of 88%, showcasing the method's potential for system integration and development.

关键词： Accuracy System integration Real-time systems Text to speech Data communication Artificial intelligence Wireless fidelity Speech to text

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Q-Learning Energy Management System (Q-EMS) in Wireless Sensor Network

Q-Learning Energy Management System (Q-EMS) in Wireless Sens...

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Smart Computing, IoT and Machine Learning (SIML), International Conference on

作者： Deden Ardiansyah Mustafid Teddy Mantoro Doctoral Program of Information Systems School of Postgraduate Universitas Diponegoro Semarang Central Java Indonesia Computer Engineering Department Vocational School Universitas Pakuan Bogor West Java Indonesia Media-Tech-Lab Computer Science Department Sampoerna University DKI Jakarta Indonesia

ISBN: (数字)9798350364101

ISBN: (纸本)9798350364118

The energy control of a Wireless Sensor Network (WSN) often leads to an unbalanced state between the battery storage system, energy extraction through photovoltaic systems energy, and energy utilization in the WSN. These disparities result in suboptimal wireless sensor network performance. The reliance on batteries is a major factor contributing to this problem. The Q-Learning Energy Management System (Q-EMS) is designed to address these challenges and improve energy management strategies. The Q-EMS algorithm used a learning process resulting in optimal actions for sensor nodes in different situations. The rewards or punishments nodes receive determine their decisions, which are determined by the Q-EMS algorithm. The Q-learning model approach is aimed at reducing energy consumption and supply in WSNs. Energy supply is categorized into battery-based, transfer-based, and harvesting, while energy consumption can be classified into task-cycle, mobility-based, and data-driven. The development of the Q Learning algorithm model has three scenarios: determining energy needs for WSN, effective energy harvesting strategy, and effective energy transfer. As a result, effective energy demand, harvesting and transfer using the Q-learning algorithm are balanced. However, it needs to be studied in more depth using real data in the field. In future research, I will use real data and optimize the use of the Q-Learning algorithm.

关键词： Wireless communication Wireless sensor networks Energy consumption Q-learning Machine learning algorithms Energy resources Classification algorithms

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Monitoring System for Elderly Health Care Using Smart Band, Raspberry Pi, and Node-Red

Monitoring System for Elderly Health Care Using Smart Band, ...

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Electronic and Electrical engineering and Intelligent System (ICE3IS), International Conference on

作者： Yudhi Ardiyanto Kusworo Adi Kurnianingsih Karisma Trinanda Putra Pradityo Utomo Doctoral Program of Information System School of Postgraduate Studies Universitas Diponegoro Semarang Indonesia Department of Electrical Engineering Faculty of Engineering Universitas Muhammadiyah Yogyakarta Yogyakarta Indonesia Department of Physics Faculty of Science and Mathematics Universitas Diponegoro Semarang Indonesia Department of Electrical Engineering Faculty of Engineering Politeknik Negeri Semarang Semarang Indonesia Department of Informatics Management Faculty of Engineering Universitas Merdeka Madiun Madiun Indonesia

ISBN: (纸本)9781665465427

The decline in physical, cognitive, and sensory functions for most elderly people leads to the development of several health issues such as memory loss, a tendency to fall, dizziness, and reduced ability to care for oneself independently. These can be mitigated using devices designed to monitor vital signs and human activity such as a smart band. However, the application of a smart band is characterized by a disadvantage which involves storing user data in the vendor's cloud and only one device can access the client applications. Therefore, nurses, doctors, and family members cannot simultaneously analyze data and receive alerts when abnormal conditions occur in elderly patients. This study aims to develop a system capable of monitoring the health conditions of multiple elderly individuals and sending alerts during abnormal conditions based on the heart rate value read by the smart band sensor. The process involved installing a database on the Raspberry Pi to store data while a monitoring system was built on the Node-RED platform to display elderly health data and made it accessible locally. The detection of an abnormal heart rate condition in the elderly patient leads the system to send notifications via telegram to multiple receivers registered in the system using their telegram identity.

关键词： Heart rate Electrical engineering Cloud computing Databases Medical services Receivers Older adults

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