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arXiv 2021年

作者： Mohammed, Najib Ahmed Mansoor, Ali Mohammed Ahmad, Rodina Binti Azzuhri, Saaidal Razalli Bin Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia Department of Computer System & Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia

Mission critical Machine-type Communication (mcMTC), also referred to as Ultra-reliable Low Latency Communication (URLLC), has become a research hotspot. It is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected devices. While the reduction in physical (PHY) layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability, the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper layers. The mcMTC has a significant technical impact on the design of all layers of the communication protocol stack. In this paper, an innovative bottom-up approach has been proposed for mcMTC applications through PHY layer targeted at improving the transmission reliability by implementing ultra-reliable channel coding scheme in the PHY layer of IEEE 802.11a standard bearing in mind short packet transmission system. To achieve this aim, we analyzed and compared the channel coding performance of convolutional codes (CCs), low-density parity-check (LDPC) codes, and polar codes in wireless network on the condition of short data packet transmission. The Viterbi decoding algorithm (VA), logarithmic belief propagation (Log-BP) algorithm, and cyclic redundancy check (CRC) successive cancellation list (SCL) (CRC-SCL) decoding algorithm were adopted to CC, LDPC codes, and polar codes, respectively. Consequently, a new PHY layer for mcMTC has been proposed. The reliability of the proposed approach has been validated by simulation in terms of Bit error rate (BER) and packet error rate (PER) ***-to-noise ratio (SNR). The simulation results demonstrate that the reliability of IEEE 802.11a standard has been significantly improved to be at PER = 10-5or even better with the implementation of polar codes. The results als

关键词： Wireless networks

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Hybrid Rider Optimization with Deep Learning Driven Biomedical Liver Cancer Detection and Classification

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Computational Intelligence and Neuroscience 2022年第0期2022卷 6162445页

作者： Al Duhayyim, Mesfer Mengash, Hanan Abdullah Marzouk, Radwa Nour, Mohamed K Mahgoub, Hany Althukair, Fahd Mohamed, Abdullah Department of Computer Science College of Sciences and Humanities-Aflaj Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia Department of Information Systems College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia Department of Computer Sciences College of Computing and Information System Umm Al-Qura University Mecca Saudi Arabia Department of Computer Science College of Science & Art at Mahayel King Khalid University Abha Saudi Arabia Department of Computer Science Faculty of Computers and Information Menoufia University Shibin Al Kawm Egypt Department of Electrical Engineering and Computer Sciences College of Engineering University of CA Berkeley United States Research Center Future University in Egypt New Cairo11845 Egypt

Biomedical engineering is the application of the principles and problem-solving methods of engineering to biology along with medicine. Computation intelligence is the study of design of intelligent agents which are systems acting perceptively. The computation intelligence paradigm offers more advantages to the enhancement and maintenance of the field of biomedical engineering. Liver cancer is the major reason of mortality worldwide. Earlier-stage diagnosis and treatment might increase the survival rate of liver cancer patients. Manual recognition of the cancer tissue is a time-consuming and difficult task. Hence, a computer-aided diagnosis (CAD) is employed in decision making procedures for accurate diagnosis and effective treatment. In contrast to classical image-dependent "semantic"feature evaluation from human expertise, deep learning techniques could learn feature representation automatically from sample images using convolutional neural network (CNN). This study introduces a Hybrid Rider Optimization with Deep Learning Driven Biomedical Liver Cancer Detection and Classification (HRO-DLBLCC) model. The proposed HRO-DLBLCC model majorly focuses on the identification of liver cancer in the medical images. To do so, the proposed HRO-DLBLCC model employs preprocessing in two stages, namely, Gabor filtering (GF) based noise removal and watershed transform based segmentation. In addition, the proposed HRO-DLBLCC model involves NAdam optimizer with DenseNet-201 based feature extractor to generate an optimal set of feature vectors. Finally, the HRO algorithm with recurrent neural network-long short-term memory (RNN-LSTM) model is applied for liver cancer classification, in which the hyperparameters of the RNN-LSTM model are tuned by the use of HRO algorithm. The HRO-DLBLCC model is experimentally validated and compared with existing models. The experimental results assured the promising performance of the HRO-DLBLCC model over recent approaches. © 2022 Mesfer Al Duhayyi

关键词： Diseases

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Soft Set Based Clustering and Its Comparison on Categorical Data

Soft Set Based Clustering and Its Comparison on Categorical ...

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information Technology International Seminar (ITIS)

作者： Iwan Tri Riyadi Yanto Cheah WaiShiang Rahmat Hidayat Rofiul Wahyudi Suprihatin Ani Apriani Information System Department Universitas Ahmad Dahlan Yogyakarta Indonesia Faculty of Computer Science & IT Universiti Malaysia Sarawak Samarahan Sarawak Malaysia Information Technology Department Politeknik Negeri Padang Padang Indonesia Islamic Banking Department Universitas Ahmad Dahlan Yogyakarta Indonesia Institute Teknologi Nasional Yogyakarta Yogyakarta Indonesia

Categorical data clustering is problematic since it is difficult or complex to determine how comparable the data is. Several methods, most recently centroid-based strategies, have been developed to reduce the complexity of the similarity of categorical data. These methods nevertheless result in lengthy processing durations. Another method, soft set-based clustering (SSC), based on the probability function of multivariate multinomial distributions, is suggested in this article. Soft sets are used to represent the data, and each soft set has a probability for each object. The joint cluster distribution function determines the probability for each object after the multivariate multinomial distribution function. The connected cluster would receive the highest likelihood. Benchmark data sets from UCI machine learning are used to compare the performance of the approach to the baseline techniques. The outcomes demonstrate that the suggested strategy performed better in purity, rank index, and calculation time.

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Utilization of GPS Technology in the Maritime Sector on Motor Sailing Yachts 8

Utilization of GPS Technology in the Maritime Sector on Moto...

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8th International Seminar on Ocean and Coastal Engineering, Environmental and Natural Disaster Management, ISOCEEN 2020

作者： Quintania, Melani Faturachman, Danny Husain, T. Pasupati, Bayu Taufik, Ahmad Management Department Faculty of Economy Darma Persada University Indonesia Marine Engineering Department Faculty of Marine Technology Darma Persada University Indonesia Information System Department School of Management and Computer Science STMIK Widuri Jakarta Indonesia Student of Doctoral Management YAI Persada University Indonesia

The utilization of technology only aims to be fast, precise, and accurate in each implementation and find a better solution at that time in several sectors. This study aims to identify the use of Global Positioning Technology (GPS) technology to track the position of the motor sailing yachts, specifically with the features used on a device or smart-phone during a trip or expedition. This research uses a type of applied research to solve problems that are faced clearly, and the results can be used as a basis for solving corrective steps. The results found that GPS-Technology on motor sailing yachts in "Pelayaran Rakyat"maritime can receive coordinates point and then send these coordinates to the vessel-tracking systems to determine the position of the motor sailing yachts between users. © Published under licence by IOP Publishing Ltd.

关键词： Yachts

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AI-Enabled Blockchain for Supply Chain in Agriculture

AI-Enabled Blockchain for Supply Chain in Agriculture

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Creative Communication and Innovative Technology (ICCIT), IEEE

作者： Ankur Singh Bist Bhupesh Rawat Anggy Giri Prawiyogi Wahyuningsih Nanda Septiani Muhammad Fakhrezzy Dimas Bagus Saputra Computer Science Graphic Era Hill University India Faculty of Teacher Training and Education Buana Perjuangan University Karawang Indonesia Management Information System University of Raharja Indonesia Department of Management University of Raharja Indonesia Computer System University of Raharja Jakarta Indonesia Technical Information University of Raharja Indonesia

The supply chain is a critical process involving farmers, buyers, suppliers, and many more entities. The entire system of farming and agriculture is based on it. The conventional method is very tedious and causes issues at multiple levels. AI and Blockchain are the two most used technologies nowadays. We are proposing an AI-enabled Blockchain ecosystem for the supply chain in Agriculture. A case study is given to explain the possibilities of the proposed model. The entire process of supply chain management has been transformed by artificial intelligence. AI plays a vital role in the warehousing process in collecting and analyzing information and inventory processes, enabling companies to increase efficiency and boost revenue. Precisely, AI predicts demand, modifying orders and rerouting products in transit. Major companies such as Google and Amazon have invested considerably in AI. Blockchain technology has been used in several areas, such as insurance, natural state, and securing personal information. Agriculture is one such field where Blockchain is being used extensively for the development and reformation of its various aspect. Unlike conventional, centralized and monopolistic agricultural management systems have been evolved. Blockchain provides a decentralized data structure to store and retrieve shared data with multiple un-trusted parties. The technology offers several advantages, including eliminating the dependenon the centralized supply chain management database, which is also referred to as single point failure, and the high cost due to verifying and monitoring transactions by third-party users. Figure.4 explains the blockchain process.

关键词： Supply chain management Supply chains Warehousing Companies Agriculture Blockchains Mobile applications

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The intention of using mobile ticketing in online travel agent

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Procedia computer science 2022年 197卷 273-281页

作者： Andre Parvian Aristio Muhammad Al Farisi Iskandar Mudjahidin Arrindika Pradana Ramadhansyah S. Supardi Gatut Prijo Utomo Anggraini Naya Parahita Information System Department Institut Teknologi Sepuluh Nopember (ITS) Surabaya 60111 Indonesia Department of Mechanical Engineering University of 17 Agustus 1945 Semolowaru 45 Surabaya 60118 Indonesia Magister of Information Technology Faculty of Computer Science Universitas Indonesia (UI) Jakarta 16424 Indonesia

The mobile ticketing service application is a promising technology for an online travel agent in Indonesia. However, its adoption is low and not evenly distributed, this is due to the lack of understanding regarding the use of mobile ticketing. The purpose of this study aims to identify and analyses the structural relationship of the factors influencing user intentions in mobile ticketing, previous research was conducted in Malaysia with different user characteristics and adoption acceleration, in this study adjustments will be made to different characteristics and conditions in Indonesia. This study conducted using the Structural Equation Modelling (SEM) Method through the questionnaires’ distributions to 531 respondents using mobile ticketing services in an online travel agent, Indonesia. The study findings suggest that capability and use context that mediated mobility and perceived use significantly affect use intention. This study provides evaluation and recommendations for online travel agent services to increase user intentions and retain mobile ticketing services users.

关键词： Use intention mobile ticketing structural equation modeling online travel agent

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An Automated Platform for Gathering and Managing Open-Source Cyber Threat Intelligence

An Automated Platform for Gathering and Managing Open-Source...

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Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Nidal A. Al-Dmour Mohammad Kamrul Hasan Masood Ajmal Muhammad Ali Iftikhar Naseer Atif Ali Hussam Al Hamadi Nasir Ali Department of Computer Engineering College of Engineering Mutah University Jordan Center for Cyber Security Universiti Kebangsaan Malaysia (UKM) Malaysia Riphah International University Islamabad University of Central Punjab Faculty of Computer Science & Information Technology the Superior University Lahore Pakistan Research Management Centre (RMC) Multimedia University Cyberjaya Malaysia College of Engineering and IT University of Dubai School of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan

The community has begun paying more attention to source OSCTI Cyber Threat Intelligence to stay informed about the rapidly changing cyber threat landscape. Numerous reports from the OSCTI frequently provide information about dangers. However, current OSCTI gathering and management tools have mainly concentrated on individual minor compromise indicators, despite the urgent need for high-quality OSCTI. The relationship between higher-level notions (including the strategies, methods, and processes) and the connections between them, which hold crucial information about dangerous behaviors and are crucial to revealing the full dangerous situation, have been disregarded. Therefore, we present SecurityKG, an automated OSCTI collection and administration system. SecurityKG collects OSCTI to extract high-fidelity knowledge about threat behaviours to address the void. Using a mixture of AI and NLP approaches, a security know-how graph is then constructed from a wide variety of sources. To facilitate knowledge graph exploration, SecurityKG provides a user interface (UI) that supports multiple forms of interactivity.

关键词： Cloud computing Knowledge graphs User interfaces Cyber threat intelligence Behavioral sciences Artificial intelligence computer security

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Asymmetric Windowing Recurrence Plots on Input Formulation for Human Emotion Recognition

TechRxiv

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TechRxiv 2023年

作者： Prabowo, Dwi Wahyu Setiawan, Noor Akhmad Debayle, Johan Nugroho, Hanung Adi Department of Electrical and Information Engineering Faculty of Engineering Universitas Gadjah Mada Jl. Grafika No. 2 Kampus UGM Yogyakarta55281 Indonesia Department of Information System Faculty of Computer Science Universitas Darwan Ali Sampit Indonesia MINES Saint-Etienne CNRS UMR 5307 LGF Centre SPIN Saint-Etienne France

Time-series classification (TSC) has been widely utilized across various domains, including brain-computer interfaces (BCI) for emotion recognition through electroencephalogram (EEG) signals. However, traditional methods often struggle to capture the intricate emotional patterns present in the EEG data. Recent advancements in encoding techniques have provided promising avenues for improving emotion recognition. This study introduces asymmetric windowing recurrence plots (AWRP) as a novel encoding technique to efficiently encapsulate the dynamic characteristics of EEG signals into texture-rich image representations. This study systematically compares the impact of conventional thresholded and unthresholded Recurrence Plots (RP) versus the proposed AWRP in emotion recognition tasks. Empirical validations conducted across benchmark datasets such as DEAP and SEED demonstrate that the AWRP method achieves classification accuracies of 99.77% and 99.69%, respectively, outperforming existing state-of-the-art methodologies. This study emphasizes the significance of input formulation, highlighting that richer input textures, as provided by AWRP, significantly enhance emotion recognition performance while ensuring computational memory usage efficiency. These findings have significant implications for the domain of EEG-based emotion recognition and offer a novel perspective that can guide future research. © 2023, CC BY-SA.

关键词： Emotion Recognition

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Economic and environmental analysis of a solar-powered ev charging system in india—a case study 2nd

Economic and environmental analysis of a solar-powered ev ch...

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2nd International Conference on Electrical and Electronics Engineering, ICEEE 2021

作者： Shrivastava, Prashant Soon, Teykok Mekhilef, Saad Ahmad, Furkan Department of Computer System and Technology Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur50603 Malaysia Power Electronics and Renewable Energy Laboratory Department of Electrical Engineering Faculty of Engineering University of Malaya Kuala Lumpur50603 Malaysia School of Software and Engineering Faculty of Science Engineering and Technology Swinburne University of Technology MelbourneVIC3122 Australia Indian Institute of Technology New Delhi Delhi110016 India

ISBN: (纸本)9789811607486

With the growing environmental concern, the demand for electric vehicle is increasing in India. However, the limited existing charging facilities slow down the rate of adoption in the market. Presently, the solar-based charging system is gaining popularity, due to its low greenhouse gas emission. In this study, a case study for different solar charging systems suited in Delhi is presented. The economic and environmental analysis of different solar-based EV charging systems utilized for charging three types of commercial EVs such as 2, 3, and 4-W is explained. The cost of energy required for 100 km drive is lower with vehicle integrating PV charging system;however, it can act as a supportive system for driving range improvement. The analysis shows that the economically solar rooftop charging system is suitable for all types of EVs. The CO2 emission produced by all types of solar-based EV charging systems is lower than coal-based charging systems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021.

关键词： Solar energy

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Manufacturing A Low-Cost Telegram and Optical Character Recognition-Based Indoor Air Quality Monitoring Data Logger

Manufacturing A Low-Cost Telegram and Optical Character Reco...

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International Conference on information Management and Technology (ICIMTech)

作者： Andi Pramono Satrio Arif Budiman Muchammad Farchan Andi Baso Mappaturi Interior Design Department School of Design Bina Nusantara University Jakarta Indonesia Information System Computer Science Faculty Brawijaya University Malang Indonesia Department of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology Institut Teknologi Sepuluh Nopember Surabaya Indonesia Architecture Department Faculty of Science and Technology Islamic State University of Maulana Malik Ibrahim Malang Indonesia

Urban air is frequently contaminated with CO, CO2, VOC, HCHO, PM 2.5, and PM 10. Rural regions are at a lower risk than those near roads and industrial areas that produce emissions. Air pollutants negatively affect its inhabitants' health, particularly the respiratory system. Most people will spend more time indoors, requiring a method for monitoring indoor air quality (IAQ). Urban communities need IAQ monitoring instruments as an early warning system for their health. This research seeks to produce inexpensive IAQ that can be utilized by all levels of society, particularly urban communities. This research utilizes a qualitative, design-thinking-based methodology. The research diverged from Empatize, which asserts that urban communities require a method for determining the local air quality. Moreover, it is determined at the define stage that IAQ monitoring, which includes a data log feature, is still comparatively expensive, so a solution is developed at the ideate stage. Creating a prototype is the next step in realizing the specified solution. In this investigation, they decided to use IAQ monitoring, which is relatively inexpensive but lacks log data storage. The author uses the ESP32-cam microcontroller to capture the screen display device, and the resulting image is sent to a telegram and processed with optical character recognition (OCR) to generate a data log. The results of prototype testing are utilized for prototype development.

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