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

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

ISBN: (纸本)9798350389654

This study focuses on the design and implementation of a Real-time Vehicular Sensing System (RVSS) aimed at enhancing air quality monitoring in smart cities. By integrating advanced sensors into moving vehicles, the system captures real-time environmental data across diverse urban areas. This research addresses the limitations of static monitoring stations, offering broader geographical coverage and greater data collection flexibility. The proposed system includes low-cost components, enhanced sensor calibration, and optimized data processing algorithms to ensure accurate and reliable data. It also features real-time data transmission and a user-friendly dashboard for dynamic monitoring. The primary contribution of this study is to establish a robust foundation for an effective Vehicular Sensing system, providing valuable insights for researchers and policymakers to improve air quality management in smart cities. © 2024 IEEE.

关键词： Air quality

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OpenJava: A class-based macro system for Java

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1st OOPSLA Workshop on Reflection and Software engineering, OORaSE 1999

作者： Tatsubori, Michiaki Chiba, Shigeru Killijian, Marc-Olivier Itano, Kozo Doctoral Program in Engineering University of Tsukuba Tennohdai 1-1-1 Tsukuba Ibaraki Japan Department of Information Science and Electronics University of Tsukuba Japan LAAS-CNRS 7 Avenue du Colonel Roche 31077 Toulouse cedex 04 France

ISBN: (纸本)3540677615

This paper presents OpenJava, which is a macro system that we have developed for Java. With traditional macro systems designed for non object-oriented languages, it is difficult to write a number of macros typical in object-oriented programming since they require the ability to access a logical structure of programs. One of the drawbacks of traditional macro systems is that abstract syntax trees are used for representing source programs. This paper first points out this problem and then shows how OpenJava addresses this problem. A key idea of Open-Java is to use metaobjects, which was originally developed for reflective computing, for representing source programs. © Springer-Verlag Berlin Heidelberg 2000.

关键词： Object oriented programming

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The Effect of Mangrove on Fish Catch Using Belat at Teluk Pemedas and Sanipah of Kutai Kartanegara Regency, East Kalimantan Province, Indonesia 2

The Effect of Mangrove on Fish Catch Using Belat at Teluk Pe...

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

作者： Sulaiman, Bustam Bambang, Azis Nur Purnaweni, Hartuti Lutfi, Mohammad Doctoral Program of Environmental Science School of Postgraduate Studies Diponegoro University Semarang Indonesia Faculty of Fishery and Ocean Diponegoro University Semarang50275 Indonesia Master Program of Environmental Science School of Post Graduate Studies Diponegoro University Semarang50275 Indonesia Faculty of Social Science and Political Science Diponegoro University Semarang50275 Indonesia Department of Oil and Gas Processing Engineering STT MIGAS Balikpapan76127 Indonesia Department of Petroleum Engineering STT MIGAS Balikpapan76127 Indonesia

The increasing population at Teluk Pemedas and Sanipah coastal areas of Kutai Kartanegara Regency, East Kalimantan Province, has led to coastal degradation. The problem was mainly caused by conversion of mangrove into aquaculture, agriculture, plantation industrial, and residential areas. This research was a study case, used descriptive analysis to describe the local fishermen activity using belat traditional device to catch fish. The results revealed that there were many fishermen still did not know the benefits of mangrove for economy growth, ecological, ecotourism etc. This condition affects to the decline of the mangrove function. Fisherman who used belat often move from one location to another location in order to find places that have many catches. The belat which are placed in good environment mangrove areas produces lots of catches that greatly benefit the fisherman, therefore mangrove ecosystem must be well preserved for the sustainability of fishermen's efforts to earn a living. © 2018 The Authors, published by EDP sciences.

关键词： Fish

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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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Ohmic Hetero-Junction of n-Type Silicon and Tungsten Trioxide for Visible-Light Sensitive Photocatalyst

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Journal of Materials science and Chemical engineering 2017年第8期5卷 33-43页

作者： Masaharu Yoshimizu Yuki Hotori Hiroshi Irie Special Doctoral Program for Green Energy Conversion Science and Technology Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Yamanashi Japan Special Doctoral Program on Clean Energy Interdisciplinary Graduate School of Medicine and Engineering University of Yamanashi Yamanashi Japan Clean Energy Research Center University of Yamanashi Yamanashi Japan

Visible light-sensitive photocatalyst was developed by combining n-type silicon (n-Si) and tungsten trioxide (WO3, n-Si/WO3), yielding an ohmic contact in between. In this system, the ohmic contact acted as an electron-and-hole mediator for the transfer of electrons and holes in the conduction band (CB) of WO3 and in the valence band (VB) of n-Si, respectively. Utilizing thus- constructed n-Si/WO3, the decomposition of 2-propanolto CO2 via acetone was achieved under visible light irradiation, by the contribution of holes in the VB of WO3 to decompose 2-propanol and the consumption of electrons in the CB of n-Si to reduce O2. The combination of p-type Si (p-Si) and WO3 (p-Si/ WO3), not the ohmic contact but the rectifying contact, was much less effective, compared to n-Si/WO3.

关键词： Ohmic Contact Silicon Tungsten Trioxide Visible Light Oxidative Decomposition Two-Step Excitation

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An Improved Particle Swarm Approach for Energy-Aware Location-Aided Routing in Mobile Ad-Hoc Network 7

An Improved Particle Swarm Approach for Energy-Aware Locatio...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Kumar, Sandeep Sharma, Khemraj Ashok Kumar, P.M. Jain, Arpit Bhagat, Sukesh Kumar Singh, Pranita Tula's institute U.K Dehradun India Nanhua University Doctoral Program in Management Sciences Department of Business Administration Dalin Chiayi62248 Taiwan Koneru Lakshmaiah Education Foundation Department of Computer Science Engineering AP Vaddeswaram522502 India Uttaranchal University Department of Computer Science & Engineering Uttarakhand Dehradun India Roorkee Institute of Technology Department of Computer Science and Engineering Uttarakhand Roorkee India

ISBN: (纸本)9798350350067

A network with no infrastructure, multiple hops, and dispersed nodes called a MANET. Nodes can communicate directly or through intermediaries without the need for permanent infrastructure. In dynamic networks like MANETs, routing procedures enhance the overall appearance of the network by ensuring Quality of Service (QoS). A routing protocol may use a composite routing measure to determine the best path for transferring data. Optimal location-based routing for MANETs based on energy-awareness is presented in this paper. Optimal routes are selected using this fast algorithm. Particle swarm optimization (PSO) is used instead of location-aided routing to select the normal data transmission route. Last but not least, the network is tested by simulating its packet delivery ratio, its energy level, its delay, and its overhead. © 2024 IEEE.

关键词： Adversarial machine learning

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Exploring Regression and Classification in Big Data with Deep Learning

Exploring Regression and Classification in Big Data with Dee...

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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

作者： Pandey, Ravindra Rongali, Aruna Sri Gopinath, S. Anute, Nilesh Nama, Forda Pund, Sachin Hult International Business School United States University of the Cumberlands Doctoral Information Technology Information Technology Emphasis Information Technology United States Karpagam Institute of Technology Department of Electronics and Communication Engineering Coimbatore India ASM's Institute of Business Management and Research Pune India University of Lampung Doctoral Program of Environtmental Science Department of Informatics Bandar Lampung Indonesia Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India

ISBN: (纸本)9798350357769

Deep gaining knowledge is a synthetic intelligence approach used to recognize complex facts. It uses many facts to recognize the complicated relationships between various factors. With deep learning, models can be built which might be capable of understanding the complicated patterns within big datasets. In this paper, we can explore using deep mastering in regression and type tasks on large datasets. In particular, we can use deep learning strategies to build a regression model that predicts a target value primarily based on the functions in a massive dataset and a classification version that can classify an object into one of the many classes of an extensive dataset. We can then discuss the overall performance of the fashions in comparison to standard models and talk about capability areas for development. Moreover, we will analyze the scalability of deep mastering strategies used on large datasets and discuss exceptional practices for building deep mastering fashions on massive datasets. Finally, we will summarize our findings and offer our conclusions approximately the use of deep studying in regression and type obligations on large datasets. © 2023 IEEE.

关键词： approximately gaining knowledge mastering performance regression

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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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Enhanced Keypoint-Based Approach for Identifying Copy-Move Forgery in Digital Images 7

Enhanced Keypoint-Based Approach for Identifying Copy-Move F...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Bisht, Girish Singh Jain, Arpit Bansla, Vandna Sharma, Khemraj Bhutia, Rudramani Kumar, Vikas Tula's Institute Department of Computer Science & Engineering Dehradun248001 India Koneru Lakshamaiah Education Foundation Department of Computer Science & Engineering A.P. Vadessahwaram India Shivalik Engineering College Dehradun248001 India Nanhua University Doctoral Program in Management Sciences Department of Business Administration Dalin Chiayi62248 Taiwan Koneru Lakshmaiah Education Foundation Department of Computer Science & Engineering A.P. India Dev Bhoomi Uttrakhand University School Engineering and Computing Uttrakhand Dehradun India

ISBN: (纸本)9798350350067

Copy-move forgeries often exploit homogeneous regions in images with large-scale attacks to either highlight or conceal target objects. These manipulations are simple to execute but challenging to notice. Forgery detection techniques like Copy-Move Forgery Detection (CMFD) cannot detect these forged documents because they are unable to identify a sufficient number of effective keypoints in homogeneous areas, leading to inaccurate and inefficient results. SURF stands for Speeded-Up Robust Features and is used in this paper along with A-KAZE and Scale-Invariant Feature Transforms. According to our experiment, A-KAZE offers superior detection performance under diverse attacks, especially when it comes to large-scale attacks targeting homogeneous regions. A-KAZE is found to be more accurate than SIFT, SURF, and A-KAZE when applied to the NB-CASIA dataset, achieving detection accuracies of 89.2%, 93.9% and 98.98%.) © 2024 IEEE.

关键词： Image analysis

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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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2023 International Conference on Power Energy, Environment and Intelligent Control, PEEIC 2023

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

ISBN: (纸本)9798350357769

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.. © 2023 IEEE.

关键词： adjustments an a lytics automated preserves statistics

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