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4th International Conference on Inventive Computation and information Technologies, ICICIT 2022

作者： Pradanang, Riyan Aditya, Bima Rayhan, Adhitya Winarlie, Michael Adrian Gaol, Ford Lumban Matsuo, Tokuro School of Information System Bina Nusantara University Alam Sutera Tangerang Indonesia Computer Science Binus Graduate Program Jakarta Indonesia Advanced Institute of Industrial Technology Tokyo Japan

ISBN: (纸本)9789811974014

People’s perspectives and behaviors altered in a variety of ways during the pandemic period, most notably in areas related to health, environment, and most notably waste management. Many people still prefer to work from home and this in turn leads to a large accumulation of garbage without having any proper means of disposal. As a result, the garbage area will serve as a breeding ground for illness. Garbage is usually composed of a residual waste generated from a product or object that has outlived its useful life, but can still be recycled into a valuable item. On this basis, the solution is to use a waste bank;it is a collection point for sorted garbage. It is claimed that using a waste bank can help in preventing the garbage accumulation. The main purpose of this study is to determine the contribution of the waste bank to end garbage accumulation. The information gathered through a review of the literature and direct interviews with multiple informants. According to the findings of the literature review, waste banks can provide a variety of benefits to users, as well as the community and surrounding environment. The proposed research study's findings show that the changes in community activity patterns contribute to an increase in garbage, and that the community plays an important role in waste control. From the performed research study, it is evident that m any individuals are interested about garbage banks and their benefits based on this presumption. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Recycling

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Bibliometric Analysis of Image Segmentation with Deep Learning: An Analytical Study 1

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International Conference on Intelligent Manufacturing and Robotics, ICIMR 2023

作者： Windarto, Agus Perdana Yuhandri, Y. Bukhori, Saiful Information Technology Study Program Universitas Putra Indonesia YPTK Padang Indonesia STIKOM Tunas Bangsa Pematangsiantar Indonesia Universitas Putra Indonesia YPTK Padang Indonesia Computer Science Department University of Jember Jember Indonesia

ISBN: (数字)9789819984985

ISBN: (纸本)9789819984978

This study presents a comprehensive bibliometric analysis of research pertaining to the utilization of deep learning techniques for image segmentation using CNN algorithms. A dataset comprising 1078 publications from journals and conference proceedings between 2018 and 2022 was examined through keyword search, co-occurrence network analysis, and keyphrase analysis. The study offers valuable insights into the present research landscape and identifies prominent areas of investigation, encompassing deep learning's application in medical imaging, disease detection, and object detection. Our analysis reveals China as a leading contributor to deep learning research for image segmentation, with 279 publications and 4,380 citations in Scopus. Advances in Biomedical Optics and Imaging—Proceedings of SPIE are pinpointed as the most productive source for deep learning research in image segmentation, with a specific emphasis on biomedical optics and imaging. The co-occurrence network analysis highlights the red cluster primarily focusing on methods and algorithms associated with deep learning in image segmentation. In contrast, the blue cluster demonstrates the application of these methods and algorithms to other objects or methods, with the "human" node standing out in terms of frequency and centrality. Our keyphrase analysis reveals the growing trend of Cellular Artificial Neural Networks over the past five years, indicating a shift in research focus toward this domain. Overall, this study's findings demonstrate the potential of deep learning to deliver precise and efficient segmentation of medical images, thereby enhancing clinical outcomes and patient care. Furthermore, our study contributes to an enhanced understanding of the current research landscape and identifies avenues for future exploration in deep learning techniques for image segmentation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Image segmentation

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Globally Harmonized System Label detection using Color Segmentation 2

Globally Harmonized System Label detection using Color Segme...

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Pinthong, Thidarat Ketcham, Mahasak Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Chumuang, Narumol Phetchaburi Rajabhat University Department. of Business Information Management Phetchaburi Thailand King Mongkut's University of Technology North Bangkok Department of Information Technology Management Bangkok Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand King Mongkut's University of Technology Thonburi Media Technology Program Bangkok Thailand Muban Chombueng Rajabhat University Department of Digital Media Technology Ratchaburi Thailand

ISBN: (纸本)9798350336573

This paper presents an approach for color detection and segmentation based on Image Processing Process to retrieve candidate regions of GHS Sign. For color classification, where the dimension of each vector can be extended by a group of neighboring pixels. The experimental results are highly accurate and robust for our testing database, where samples are recorded on various states of environment. But in the meantime, it was found that the error processing. It is an image that looks asymmetrical image. It is impossible to detect the symbol GHS. © 2023 IEEE.

关键词： Geographic information systems

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Pillow for Detecting Snoring with Embedded Techniques for Elderly People with Snoring Problems 2

Pillow for Detecting Snoring with Embedded Techniques for El...

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

作者： Yimyam, Worawut Ketcham, Mahasak Ganokratanaa, Thittaporn Pramkeaw, Patiyuth Chumuang, Narumol Phetchaburi Rajabhat University Department. of Business Information Management Phetchaburi Thailand King Mongkut's University of Technology North Bangkok Department of Information Technology Management Bangkok Thailand King Mongkut's University of Technology Thonburi Applied Computer Science Program Bangkok Thailand King Mongkut's University of Technology Thonburi Media Technology Program Bangkok Thailand Muban Chombueng Rajabhat University Department of Digital Media Technology Ratchaburi Thailand

ISBN: (纸本)9798350336573

This research aimed to design, produce, and assess a snoring detection neck pillow for elderly individuals with snoring symptoms. The research process began with finding information on snoring. The data obtained were used to design a snore detection neck pillow in the form of a U-shaped neck pillow. The functional principle was that when the microphone module detects the snoring sound, it activates a vibrating motor to alert the snorer to awake or change sleeping positions and stop snoring. There was a program to control the operation. The results of the snoring detection neck pillow test with a sample size of 20 people showed an average efficiency of 80%. © 2023 IEEE.

关键词： Internet of things

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Smart Agricultural Greenhouses for Earthworm Farming 2

Smart Agricultural Greenhouses for Earthworm Farming

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2nd International Conference on Cybernetics and Innovations, ICCI 2023

ISBN: (纸本)9798350336573

In this research, the design of the earthworm rearing house was presented. Internet of Things, in which the research has designed houses and various equipment to be designed. The results showed that the traditional way of raising earthworms by walking to check the humidity in the cultured basin by touching and regularly watering compared to using the IOT system to measure the moisture. And there is a notification when the humidity drops below or above the specified threshold. and has an automatic watering system when the humidity is below a specified threshold It was found that the IOT-based method was more productive than the traditional method. © 2023 IEEE.

关键词： Greenhouses

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Comments on a Computation-Transferable Authenticated Key Agreement Protocol for Smart Healthcare

Comments on a Computation-Transferable Authenticated Key Agr...

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9th International Conference on Applied System Innovation, ICASI 2023

作者： Chang, Ya-Fen Tsai, Chung-Yi Tai, Wei-Liang National Taichung University of Science and Technology Department of Computer Science and Information Engineering Taichung Taiwan National Taichung University of Science and Technology Bachelor Degree Program of Artificial Intelligence Taichung Taiwan

ISBN: (纸本)9798350398380

Recently, Wang et al. proposed a computationally transferable authenticated key agreement protocol for smart healthcare by adopting the certificateless public-key cryptography. They claimed that their protocol could ensure privacy, resist various attacks, and possess superior properties. After analyzing their protocol, we find that it suffers from some flaws. Firstly, user privacy is not ensured as claimed. Secondly, some statements are inaccurate or missing. Thirdly, it cannot resist DoS attack. In this paper, the details of how these flaws threaten Wang et al.'s protocol are shown. © 2023 IEEE.

关键词： Denial-of-service attack

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Analysis Implementation of Chatbots to Increase Knowledge of Stunting Prevention in Indonesian Society with Bibliometric 9

Analysis Implementation of Chatbots to Increase Knowledge of...

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9th International Conference on information Management and technology, ICIMTech 2024

作者： Sutedja, Indrajani Handayani, Lutfi Maryuni Hendry Faisal, Mohammad Reza School of Information Sytems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Midwifery Study Program Binawan University Faculty of Nursing and Midwifery Jakarta13630 Indonesia Satya Wacana Christian University Faculty of Information Technology Salatiga50711 Indonesia FMIPA Lambung Mangkurat University Department of Computer Science Banjarmasin70123 Indonesia

ISBN: (纸本)9798350390025

The healthcare industry uses AI, because it is more efficient. In Indonesia, the accuracy of measurements and transmission of children's growth and development is often wrong. Many small hospitals usually don't have length measuring equipment, so the results are inaccurate. This research aims to determine the effectiveness of the stunting prevention program in Indonesia using an information system. The methodology used is a qualitative method, to conduct subjective research and analysis. The results of the research are to improve the website/mobile application information system which can display a child's growth and development history and simple educational information related to nutrition. Digital recording methods can speed up the process of updating data with a central database in real time. The value of this research is to reach the public to utilize technology and obtain personalized and interactive information directly to individuals. The theoretical implications of this research focus on information dissemination and understanding how chatbots influence knowledge acquisition and behavior change in the context of stunting prevention can contribute to advancing these theories in the field of public health. Managerial implications can provide cost effectiveness as Chatbots offer potentially cost-effective solutions and data-driven insights where managers can leverage chatbot analytics. © 2024 IEEE.

关键词： Artificial Intelligent Indonesian information System Stunting stunting stunting chatbot and bibliometric stunting prevention VOS Viewer

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Optimal Synergic Deep Learning for COVID-19 Classification Using Chest X-Ray Images

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computers, Materials & Continua 2023年第6期75卷 5255-5270页

作者： JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Safa Alsafari Ayman Yafoz Romany F.Mansour Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080002Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080002Colombia Department of Computer Science and AI Faculty of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,widespread availability,low cost,and *** radiological investigations,computer-aided diagnostic tools are implemented to reduce intra-and inter-observer *** lately industrialized Artificial Intelligence(AI)algorithms and radiological techniques to diagnose and classify disease is *** current study develops an automatic identification and classification model for CXR pictures using Gaussian Fil-tering based Optimized Synergic Deep Learning using Remora Optimization Algorithm(GF-OSDL-ROA).This method is inclusive of preprocessing and classification based on *** data is preprocessed using Gaussian filtering(GF)to remove any extraneous noise from the image’s ***,the OSDL model is applied to classify the CXRs under different severity levels based on CXR *** learning rate of OSDL is optimized with the help of ROA for COVID-19 diagnosis showing the novelty of the *** model,applied in this study,was validated using the COVID-19 *** experiments were conducted upon the proposed OSDL model,which achieved a classification accuracy of 99.83%,while the current Convolutional Neural Network achieved less classification accuracy,i.e.,98.14%.

关键词： Artificial intelligence chest X-ray COVID-19 optimized synergic deep learning preprocessing public health

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Hybrid Cryptosystem with Cramer-Shoup and Spritz Algorithms for Securing Digital Documents

Hybrid Cryptosystem with Cramer-Shoup and Spritz Algorithms ...

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International Conference on Electrical, Telecommunication and computer Engineering (ELTICOM)

作者： Delisman Hulu Maya Silvi Lydia Mohammad Andri Budiman Master of Informatics Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

ISBN: (数字)9798331531249

ISBN: (纸本)9798331531256

Symmetric algorithms offer speed but have weaknesses in key distribution, while asymmetric algorithms are secure but less efficient for encrypting and decrypting large text messages. This research aims to secure data and digital documents through the implementation of a hybrid cryptosystem that combines the Cramer-Shoup algorithm and Spritz. This research also analyzes and evaluates the effectiveness and speed of encryption and decryption, as well as the efficiency of the system in protecting various types of data, including docx and pdf document files. The methodology of this research includes a literature review, analysis of the encryption-decryption process, and performance testing of the system using the Python programming language. The speed test results show that this hybrid cryptosystem provides fast encryption-decryption times, with an encryption time of 0.002607 milliseconds for 400 characters and a decryption time of 0.001537 milliseconds, while for digital documents of the pdf file type, the encryption time is 0.424478 milliseconds and the decryption time is 0.404343 milliseconds. In addition, the use of the SHA-3 hash function has proven effective in maintaining data integrity. In conclusion, this hybrid cryptosystem offers an efficient and secure solution for protecting various types of digital data, including text and documents.

关键词： Hash functions Resistance Data integrity Scalability Portable document format Encryption Testing Python Videos Systematic literature review

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Diversity-Optimized Group Extraction in Social Networks

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IEEE Transactions on Computational Social Systems 2024年第1期11卷 756-769页

作者： Hsu, Bay-Yuan Chen, Yi-Ling Ho, Ya-Chi Chang, Po-Yuan Chang, Chih-Chieh Shia, Ben-Chang Shen, Chih-Ya National Tsing Hua University Department of Industrial Engineering and Engineering Management Hsinchu30013 Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei10607 Taiwan Hsinchu31040 Taiwan Fu Jen Catholic University Department of Business Administration New Taipei City24205 Taiwan National Taiwan University of Science and Technology Management Undergraduate Program Taipei10607 Taiwan National Tsing Hua University Department of Computer Science Hsinchu30013 Taiwan

In this article, we propose to study a novel research problem to boost group performance, that is, social-aware diversity-optimized group extraction (SDGE), which takes into consideration the two important factors: 1) group diversity and 2) social tightness. We prove the NP-hardness of SDGE and propose an effective algorithm, named group shrinking for diversity maximization (GSDM) with a performance guarantee, that is, GSDM is a three-approximation algorithm to the SDGE problem studied in this article. We further propose three effective pruning strategies that are able to boost the efficiency of GSDM but do not deteriorate its performance. We conduct extensive experiments on multiple large-scale real datasets to evaluate the performance of GSDM. The experimental results show that our proposed GSDM outperforms the other baseline approaches significantly, in terms of solution quality and efficiency. Moreover, the experimental results also confirm that our proposed pruning strategies indeed boost the efficiency of the algorithm. © 2014 IEEE.

关键词： Costs

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