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2023 International Conference on Sustainable Emerging Innovations in Engineering and Technology, ICSEIET 2023

作者： Fatmawati, Maylia Novita, Mega Saputro, Nugroho Dwi Chauhan, Alok Singh Nada, Noora Qotrun Sinha, Amit Herlambang, Bambang Agus Gupta, Shruti Universitas Pgri Semarang Faculty of Engineering and Informatics Department of Informatics Semarang Indonesia Universitas Pgri Semarang Postgraduate Program of Science Education Semarang Indonesia School of Computing Science & Engineering Galgotias University Greater Noida India ABES Engineering College Department of Computer Science & Engineering Uttar Pradesh Ghaziabad201009 India

ISBN: (纸本)9798350329186

Maternal health is a critical concern, particularly for individuals who are pregnant and will shape the future generations. However, not all expectant mothers receive tailored attention and care for their unique health needs. Consequently, many mothers face high levels of health risks during pregnancy, highlighting the importance of classifying maternal health risks. Classification can help identify influential factors affecting maternal health and predict risk levels for individual mothers. In the field of data mining, various classification methods exist for analyzing complex datasets. This study focuses on two widely used algorithms: decision tree and k-Nearest Neighbor (kNN). By employing these algorithms, we aim to classify a dataset comprising 1,014 records of maternal health risk levels. Through cross-validation and T-tests, we rigorously evaluate the performance of the decision tree and kNN algorithms in this context. Our findings indicate that the kNN algorithm is more suitable for classifying maternal health risks, achieving a significantly higher accuracy of 71.50% compared to the decision tree algorithm's accuracy of 70.71%. This result establishes the superiority of the kNN algorithm in accurately classifying maternal health risks. These findings have implications for developing targeted interventions and tailored healthcare strategies to mitigate identified risks. © 2023 IEEE.

关键词： Health risks

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Wireless-Powered UAV assisted Communication System in Nakagami-m Fading Channels 17

Wireless-Powered UAV assisted Communication System in Nakaga...

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17th IEEE Annual Consumer Communications and Networking Conference, CCNC 2020

作者： Ponnimbaduge Perera, Tharindu D. Jayakody, Dushantha Nalin K. Garg, Sahil Kumar, Neeraj Cheng, Ling School of Computer Science and Robotics National Research Tomsk Polytechnic University Russia School of Postgraduate Studies Research Sri Lanka Technological Campus Padukka Sri Lanka Ecole de Technologie Supérieure Electrical Engineering Department MontrealQCH3C 1K3 Canada Thapar Institute of Engineering and Technology Department of Computer Science and Engineering India School of Electrical and Information Engineering University of the Witwatersrand South Africa

ISBN: (纸本)9781728138930

Recently, the use of unmanned aerial vehicles (UAVs) as a relay node has been envisaged as an enabling technology in the upcoming wireless communication era. Thus, in this paper, we consider a full-duplex (FD) cooperative communication system with a source and a destination, where UAV serves as a mobile relay. Here, the transmission power cost is debited to energy harvested using simultaneous wireless information and power transfer (SWIPT) and self-interference energy harvesting (EH) via power-splitting (PS) protocol. In poor channel conditions, UAV uses a soft angular modulation scheme to perceive the soft information. In this proposed system, we present the outage probability over the Nakagami-m fading channels. A closed-form solution for the outage probability is derived. In addition, we formulate an optimization problem to minimize end-to-end outage probability subject of the UAV's power profile. The KKT conditions have been used to obtain a closed-form solution of the proposed optimization problem. Finally, numerical results are provided to evaluate the proposed system under various setups. © 2020 IEEE.

关键词： Cooperative communication

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Characteristics and Generation of Household Hazardous Waste (HHW) in Semarang City Indonesia 2

Characteristics and Generation of Household Hazardous Waste ...

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2nd International Conference on Energy, Environmental and Information System, ICENIS 2017

作者： Fikri, Elanda Purwanto, Purwanto Sunoko, Henna Rya Department of Environmental Health Bandung Health Polytechnic Cimahi Utara Bandung Indonesia Doctoral Program of Environmental Science School of Postgraduate Studies Universitas Diponegoro Semarang Indonesia Department of Chemical Engineering Faculty of Engineering Universitas Diponegoro Semarang Indonesia Faculty of Medicine Universitas Diponegoro Semarang Indonesia

Most of Household Hazardous Waste (HHW) is currently mixed with domestics waste. So that, it can impact human health and environmental quality. One important aspect in the management strategy is to determine the quantity generated and characteristics of HHW. The method used to determine the characteristics HHW refers to SNI 19-2454-2002, while the HHW generation refers to the SNI 19-3694-1994 calculated based on weight and volume. Research was conducted in four districts of Semarang. The samples used in this study were 400 families calculated based on the proportion of Slovin Formula. The characteristic of HHW in Semarang City is mainly infectious (79%), then poisonous (13%), combustible (6%) and corrosive materials (2%). The quantity HHW generated is 0.01 kg/person/day equivalent with 5.1% of municipal solid waste (MSW) in Semarang (linear equations: Y=1,278x+82,00 (volume), y=0,216x+13,89 (weight). © 2018 The Authors, published by EDP sciences.

关键词： Municipal solid waste

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Fast, accurate, and versatile data analysis platform for the quantification of molecular spatiotemporal signals

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Cell 2025年第10期188卷 2794-2809.e21页

作者： Mi, Xuelong Chen, Alex Bo-Yuan Duarte, Daniela Carey, Erin Taylor, Charlotte R. Braaker, Philipp N. Bright, Mark Almeida, Rafael G. Lim, Jing-Xuan Ruetten, Virginia M.S. Wang, Yizhi Wang, Mengfan Zhang, Weizhan Zheng, Wei Reitman, Michael E. Huang, Yongkang Wang, Xiaoyu Li, Lei Deng, HanFei Shi, Song-Hai Poskanzer, Kira E. Lyons, David A. Nimmerjahn, Axel Ahrens, Misha B. Yu, Guoqiang Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Arlington 22203 VA United States Janelia Research Campus Howard Hughes Medical Institute Ashburn 20147 VA United States Department of Molecular and Cellular Biology Harvard University Cambridge 02138 MA United States Graduate Program in Neuroscience Harvard Medical School Boston 02115 MA United States Waitt Advanced Biophotonics Center The Salk Institute for Biological Studies La Jolla 92037 CA United States Department of Biochemistry & Biophysics University of California San Francisco San Francisco CA United States Neuroscience Graduate Program University of California San Francisco San Francisco CA United States Centre for Discovery Brain Sciences University of Edinburgh Edinburgh BioQuarter Edinburgh EH16 4SB United Kingdom Gatsby Computational Neuroscience Unit UCL London W1T 4JG United Kingdom Kavli Institute for Fundamental Neuroscience San Francisco CA United States Department of Automation Tsinghua University Beijing 100084 China IDG/McGovern Institute for Brain Research Tsinghua University Beijing 100084 China New Cornerstone Science Laboratory Tsinghua-Peking Center for Life Sciences Beijing Frontier Research Center for Biological Structure School of Life Sciences Tsinghua University Beijing 100084 China State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science Institutes of Brain Science Fudan University Shanghai 200032 China Beijing National Research Center for Information Science and Technology Beijing 100084 China

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful spatiotemporal patterns embedded within complex and rich data sources, many of which cannot be captured with existing methods. Here, we introduce activity quantification and analysis (AQuA2), a fast, accurate, and versatile data analysis platform built upon advanced machine-learning techniques. It decomposes complex live-imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a wide range of biosensors, cell types, organs, animal models, microscopy techniques, and imaging approaches. As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, as well as distinct sensorimotor signal propagation patterns in the mouse spinal cord. © 2025 The Author(s)

关键词： AQuA2 astrocytes cell interaction analysis functional units glial cells image analysis machine learning molecular spatiotemporal signals neurons time-lapse imaging

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Devising adaptive migration policies for cooperative distributed genetic algorithms

Devising adaptive migration policies for cooperative distrib...

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IEEE International Conference on Systems, Man and Cybernetics

作者： E. Noda A.L.V. Coelho I.L.M. Ricarte A. Yamakami A.A. Freitas School of Electrical and Computer Engineering (FEEC) UNICAMP-State University of Campinas Brazil Postgraduate Program in Computer science Pontifical Catholic University of Paraná Brazil

Distributed genetic algorithms (DGAs) constitute an interesting approach to undertake the premature convergence problem in evolutionary optimization. This is done by spatial partitioning a huge panmitic population into several semi-isolated groups, called demes, each evolving in parallel by its own pace, and possibly exploring different regions of the search space. At the center of such approach lies the migratory process that simulates the swapping of individuals belonging to different demes, in such a way to ensure the sharing of good genetic material. In this paper, we model the migration step in DGAs as an explicit means to promote cooperation among genetic agents, autonomous entities encapsulating GA instances for possibly tackling different sub-problems of a complicated task. The focus is on the characterization of adaptive migration policies in which the choice of what individuals to migrate and/or replace is not defined a priori but according to a more knowledge-oriented rule. Comparative results obtained for a data-mining task were conducted, in order to assess the performance of adaptive migration according to efficiency/effectiveness criteria.

关键词： Genetic algorithms Identity-based encryption Inductors Search engines Dissolved gas analysis Parallel architectures Cloning

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Intrusion Detection using Deep Neural Network Algorithm on the Internet of Things 11

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

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11th IEEE International Conference on Communication, Networks and Satellite, COMNETSAT 2022

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

ISBN: (纸本)9781665460309

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. © 2022 IEEE.

关键词： Internet of things

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ResTP - A transport protocol for FI resilience 15

ResTP - A transport protocol for FI resilience

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10th International Conference on Future Internet, CFI 2015

作者： Nguyen, Truc Anh N. Rohrer, Justin P. Sterbenz, James P.G. Information and Telecommunication Technology Center Department of Electrical Engineering and Computer Science University of Kansas LawrenceKS66045 United States and InfoLab21 Lancaster University LA1 4WA United Kingdom Department of Computing Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong Department of Computer Science Naval Postgraduate School Monterey United States

ISBN: (纸本)9781450335645

To support emerging application classes and network use paradigms for Future Internet resilience, we are designing a new transport protocol: ResTP. ResTP overcomes the lim- itations of TCP and UDP that evolved in the context of the fixed, wired, connected, relatively reliable, and low-to- moderate delay Internet. ResTP is developed to efficiently carry trafic from various application types across a wide variety of network types. By supporting cross-layering, ResTP allows service tuning by the upper application layer while promptly reacting to network condition changes by using the feedback from the lower network layer. ResTP supports a set of transport-layer services, and each service is comprised of many mechanisms and algorithms that can be combined based on the specific mission requirement, application type, and underlying network characteristics. In addition, ResTP can exploit multiple available paths for its data transmission to increase redundancy while better utilizing network resources. With the design based on our ResiliNets frame- work, we believe that ResTP is the first transport-layer protocol that considers all disciplines related to resilience. © 2015 ACM.

关键词： Network layers

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Real Time Monitoring System of Drinking Water Quality Using Internet of Things 24

Real Time Monitoring System of Drinking Water Quality Using ...

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24th International Electronics Symposium, IES 2022

作者： Abidin, Zainul Maulana, Eka Nurrohman, Muhammad Yogi Wardana, Fitri Candra Warsito Universitas Brawijaya Faculty of Computer Science Department of Computer Engineering Malang Indonesia Universitas Brawijaya Faculty of Engineering Department of Electrical Engineering Malang Indonesia Universitas Brawijaya Master Program in Environmental Resources and Development Management Postgraduate School Malang Indonesia Universitas Brawijaya Faculty of Mathematics and Natural Sciences Department of Chemistry Malang Indonesia

ISBN: (数字)9781665489713

ISBN: (纸本)9781665489713

In order to reduce Polyethylene Terephthalate (PET) bottle plastic waste, Universitas Brawijaya (UB) provided reverse osmosis drinking water in some buildings. Water monitoring is needed to keep the water quality. Therefore, a water monitoring system based on Total Dissolved Solids (TDS), pH, and water flow was proposed. Since the UB buildings have good internet connection (WiFi), Internet of Things (IoT) was employed to the system to support real time monitoring. So, data of TDS, pH, and water flow can be periodically sent to cloud and displayed to a specific website. The system worked very well and the data can be summarized and used by operator as indicators of performance of the reverse osmosis machine. When water quality and performance decrease, operator must check filters membrane or water pump for further maintenance to support long life use. Although the sensors have been calibrated properly, some measurement errors occur. The measurement error percentages of TDS and pH are 0.62% and 0.94%, respectively. © 2022 IEEE.

关键词： Internet of things

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Internet of Things for Smart Furniture: A Systematic Review 11

Internet of Things for Smart Furniture: A Systematic Review

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Maulana, Fairuz Iqbal Kurniawan, Bambang Kartono Pramono, Andi Purnomo, Agung Abdulah, Muhamad Ezran Bin Zainal Mohamed, Mustafa School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Design Bina Nusantara University Interior Design Department Jakarta11480 Indonesia Binus Business School Undergraduate Program Bina Nusantara University Entrepreneurship Department Jakarta11480 Indonesia Universiti Malaysia Kelantan Faculty of Creative Technology and Heritage Department of Design and Creative Technology Kelantan Bachok16300 Malaysia School of Technology of the Arts Republic Polytechnic Singapore

ISBN: (纸本)9798350389654

The research entitled 'Internet of Things for Smart Furniture: A Systematic Review' explores integrating IoT technology into smart furniture to improve functionality and user experience. By synthesizing existing literature, this research aims to discover how the Internet of Things (IoT) is leveraged to meet specific user needs with smart furniture and what hardware and sensor technologies are proposed for smart furniture design, considering factors such as scalability and need for users. Current research trends in securing user communications and data in the context of IoT-enabled smart furniture. This research involved a literature search which included journal articles and reviews from the Web of science (WOS) and the Scopus database (core collection) from 2014 to 2023, and the final results were 9 documents that would be reviewed. Several impactful means must be used to meet specific user needs, such as health monitoring, enhanced security, enhanced convenience and mobility, integration with smart home systems, and personalization and adaptability. Drawing insights from IoT data quality, machine learning applications in IoT, and smart furniture design for elderly care, this research provides a comprehensive picture of the current IoT-enabled smart furniture landscape. This research can explore existing IoT solutions for smart furniture, with a focus on cutting-edge technologies and design principles that can shape the future of this domain. © 2024 IEEE.

关键词： internet of things literature review scopus smart furniture web of science

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Trends in Scientific Research in Smart Furniture: A Bibliometric Analysis in Decade from 2014-2023 11

Trends in Scientific Research in Smart Furniture: A Bibliome...

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11th International Conference on ICT for Smart Society, ICISS 2024

ISBN: (纸本)9798350389654

Smart furniture has emerged as a significant area of interest in scientific research over the past decade. This bibliometric analysis aims to explore the trends in scientific research related to smart furniture from 2014 to 2023. By examining a range of scholarly articles, this study delves into the evolution of smart furniture technologies, applications, and implications. The research reveals a growing interest in integrating intelligent systems into furniture design, enabling network connectivity and user-controlled operations. Despite the growing number of studies, the research landscape remains fragmented, necessitating a comprehensive bibliometric analysis to consolidate existing research and identify trends. Data selection from the Scopus database yielded a total of 97 documents from 69 sources, with average citations per doc is 8.041. On the corresponding author's countries, China is the highest country. Moreover, terms like 'smart furniture' that expand in size and extend to the right of the chart indicate a growing emphasis in recent literature, signaling potential areas of increased research activity. Smart furniture is characterized as furniture that is connected to a network and equipped with intelligent technologies that make use of user data and energy sources. The study underscores the importance of addressing issues such as ease of use, privacy, security, and affordability in implementing smart furniture solutions. This study provides valuable insights into the current state and future prospects of smart furniture research, guiding further investigation and advancement in this rapidly evolving sector. © 2024 IEEE.

关键词： bibliometric Rstudio scopus smart furniture VOSviewer

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