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7th International Conference on Web Research, ICWR 2021

作者： Khalilipour, Alireza Challenger, Moharram Islamic Azad University Faculty of Computer and Information Technology Engineering Qazvin Branch Qazvin Iran University of Antwerp and Flanders Make Department of Computer Science Flanders Belgium

ISBN: (纸本)9781665404266

One of the approaches for software re-modularization is to transform sequential codes into distributed ones. Code clustering as a technique for software re-modularization is used on object-oriented codes. By clustering, the classes in a program are separated into several clusters, each of which contains cohesive classes. In the state of the art, the type of invocation or message passing between classes and objects is not considered in the clustering, which can impact the quality of the clusters. This paper presents an approach in which the types of invocations between classes and objects such as synchronous, one-way, or asynchronous will also be considered in the clustering. The aim is to separate asynchronous and one-way services from the clusters and move them to new clusters, automatically. So that, by running these services in parallel, extra waiting times for service invocations can be eliminated. Also, by transferring these services to new clusters, load distribution has taken place, which can reduce response time. The experiment results confirm that the proposed approach has a significant effect in reducing the overall waiting time. © 2021 IEEE.

关键词： Modular construction

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Everything you wanted to know about ChatGPT: Components, capabilities, applications, and opportunities

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Internet technology Letters 2024年第6期7卷

作者： Heidari, Arash Navimipour, Nima Jafari Zeadally, Sherali Chamola, Vinay Department of Software Engineering Haliç University Istanbul Turkey Department of Computer Engineering Faculty of Engineering and Natural Science İstanbul Atlas University Istanbul Turkey Department of Computer Engineering Faculty of Engineering and Natural Sciences Kadir Has University Istanbul Turkey Future Technology Research Center National Yunlin University of Science and Technology Douliou Taiwan College of Communication and Information University of Kentucky LexingtonKY United States Pilani India

Conversational Artificial Intelligence (AI) and Natural Language Processing have advanced significantly with the creation of a Generative Pre-trained Transformer (ChatGPT) by OpenAI. ChatGPT uses deep learning techniques like transformer architecture and self-attention mechanisms to replicate human speech and provide coherent and appropriate replies to the situation. The model mainly depends on the patterns discovered in the training data, which might result in incorrect or illogical conclusions. In the context of open-domain chats, we investigate the components, capabilities constraints, and potential applications of ChatGPT along with future opportunities. We begin by describing the components of ChatGPT followed by a definition of chatbots. We present a new taxonomy to classify them. Our taxonomy includes rule-based chatbots, retrieval-based chatbots, generative chatbots, and hybrid chatbots. Next, we describe the capabilities and constraints of ChatGPT. Finally, we present potential applications of ChatGPT and future research opportunities. The results showed that ChatGPT, a transformer-based chatbot model, utilizes encoders to produce coherent responses. © 2024 John Wiley & Sons Ltd.

关键词： Taxonomies

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Blind Write Protocol Throughput 2

Blind Write Protocol Throughput

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2021 2nd International Symposium on Automation, information and Computing, ISAIC 2021

作者： Herman, Nanna Suryana Anshar, Khairul Andono, Pulung Nurtantio University Malaysia of Computer Science and Engineering Cyberjaya Malaysia Faculty of Information and Technology Universiti Teknikal Malaysia Melaka Hang Tuah Jaya Durian Tunggal Melaka76100 Malaysia Universitas Dian Nuswantoro UDINUS Semarang Indonesia

Blind Write Protocol allows more transactions to be executed at the same time. It is achieved by removing the locking phase to any entity while the write operation is performed. To have a fair throughput comparison with the Locking Protocol then this paper introduces three different approaches using Blind Write Protocol that can preserve consistency. The throughputs are presented and compared with Locking Protocol. We found that preserving consistency using Blind Write Protocol needs more operations. As a result, it consumes more resources and makes the response times much slower compared to Locking Protocol. If Blind Write Protocol ignores consistency, then it shows better response time compared to Locking Protocol. The Blind Write Protocol aims to achieve availability rather than consistency. © Published under licence by IOP Publishing Ltd.

关键词： Locks (fasteners)

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Conditional Cascaded Networks (Ccn) Approach for Diagnosis of Covid-19 in Chest X-Ray and Ct Images Using Transfer Learning

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SSRN 2023年

作者： Rashed, Amr Ez Eldin Bahgat, Waleed M. Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif Saudi Arabia Information Technology Department Faculty of Computer and Information Sciences Mansoura University 35516 Egypt Department of Computer Science and Informatics Taibah University Al Medina Al Munawara Medina Saudi Arabia

The COVID-19 pandemic has caused significant global health and economic damage, with over five million confirmed cases worldwide. The importance of rapid and accurate diagnosis of infected patients has been underscored. However, due to the shortage of testing kits and the time-consuming and troublesome nature of the manual RT-PCR test, an automated and efficient diagnosis system using chest medical images for early screening of COVID-19 is crucial. In this paper, we present an automated approach for rapid and accurate diagnosis of COVID-19 in chest X-ray and CT images using transfer learning. The proposed technique leverages the Conditional Cascaded Networks (CCN) approach, which employs multiple levels of networks to analyze images with high confidence. Transfer learning is employed with seven commonly used existing CNN architectures and four datasets for X-ray and CT images. Various regularization, optimization, dropout, and data augmentation techniques are examined through a series of experiments with three optimizers. Our technique is compared with other state-of-the-art techniques, and the achieved results demonstrate highly promising performance metrics. Additionally, occlusion specificity and Grad-CAM techniques are employed to better understand the network output. The proposed technique is highly adaptable and scalable and does not require manual hyperparameter tuning. © 2023, The Authors. All rights reserved.

关键词： COVID-19

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Surface Electric Field Measurement of Composite Insulator Using an Optical Waveguide Sensor

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SSRN 2023年

作者： Zhang, Jiahong Li, Weichang Shi, Jiali Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650000 China Yunnan Key Laboratory of Computer Technology Applications Kunming University of Science and Technology Kunming650000 China

In this paper, an integrated optical waveguide sensor is designed and developed to comprehensively analyze the surface electric field distribution characteristics of composite insulators. Based on the optical waveguide electric field sensor, a measuring system for the surface axial and radial electric fields of composite insulators is built, and the axial and radial electric fields along the surface of composite insulator is measured under normal, damaged and internally defects. Based on the optical waveguide electric field sensor, an experimental system is setup for measuring the axial and radial electric fields along surface of composite insulators under normal, damaged and internally defective conditions. The experimental results showed that when a 10 kV power frequency voltage is connected, the radial and axial electric fields at the low and high voltage ends of the normal insulator are 21.53 kV/m, 53.07 kV/m and 47.55 kV/m, 105.12 kV/m respectively. When the insulator surface is damaged, the radial and axial electric field intensities at the damaged locations increased by 37.59%-204.85% and 12.89%-32.69%, respectively. When an internal defect occurred, the radial and axial electric field along the defect area increased by 18% and decreased by 127.72%, respectively. The radial electric field is more affected by the defect. The comparison with the calculated results shows that the integrated optical waveguide electric field sensor has great potential capability to be used for measuring the surface electric field of insulators. © 2023, The Authors. All rights reserved.

关键词： Electric fields

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Energy management system based on wireless sensor networks and power line communications

Energy management system based on wireless sensor networks a...

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2022 International Conference Automatics and Informatics, ICAI 2022

作者： Omar, Azhar-Husain Malekian, Reza Bogatinoska, Dijana Capeska University of Pretoria Department of Electrical Electronic and Computer Engineering Pretoria082 South Africa Malmö University Department of Computer Science and Media Technology Malmö205 06 Sweden Mach. Intell. and Robotics University of Information Science and Technology St. Paul the Apostle Faculty of Applied IT Ohrid Macedonia

ISBN: (数字)9781665476256

ISBN: (纸本)9781665476256

In this paper, we developed a power line communication (PLC) system design, power measurement sensor design, light sensor design, temperature sensor design, and the integration of these components into an advanced sensor network to allow for energy metering and environment monitoring. A power measurement sensor was implemented through a current and voltage sensing circuitry was interfaced multi-plug power adapter to allow for non-invasive measurement of power usage of appliances. The sensors produce signals corresponding to the drawn voltage and current, which are then sampled and processed to estimate power usage. The PLC communications operated at an average accuracy of 95%. The power measurement sensor had an accuracy of 92%, which made it appropriate for home user estimations. The light sensor had an accuracy of between 91-97%, which was suitable for home lighting measurement. © 2022 IEEE.

关键词： Wireless sensor networks

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STDP-Driven Automated Retinal Circuit with 7nm FinFET for Motion and Looming Detection: A Hybrid Model with Image Analysis

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IEEE Access 2025年 13卷 95594-95608页

作者： Rabeya, Rubina Akter Islam, Md Turiqul Uddin, Shah Muhammad Imtiyaj Al-Shidaifat, Alaaddin Song, Hanjung Choi, Heung-Kook Kim, Hee-Cheol Department of Digital Anti-Aging Healthcare Inje university Gimhae50834 Korea Republic of Department of Nanoscience and Engineering Centre for Nano Manufacturing Inje university Gimhae50834 Korea Republic of Middle East University Faculty of Information Technology Computer Science Department Amman11831 Jordan Department of Computer Engineering Inje university Gimhae50834 Korea Republic of

This paper presents a spike-timing-dependent plasticity (STDP) driven silicon retina designed using 7nm FinFET technology for detecting object motion and looming threats inspired by the biological visual system. The proposed neuromorphic architecture integrates an automated motion spiking circuit with STDP and advanced image analysis, mimicking natural retinal processing to identify potential hazards. Two specialized circuits are introduced to generate bipolar spiking signals for object motion and looming detection. These spikes are processed by an STDP-based spiking neural network, qualifying real-time distance estimation of approaching objects. Model Results demonstrate accurate collision time prognosis based on object dynamics. YOLOv5 and MiDaS enhance object recognition and depth perception, improving situational awareness. The proposed model uses a hybrid strategy combining object detection and depth estimation to identify objects with different spatial distances and confidence levels accurately. Experimental results show a motion detection accuracy of 93.2% and an average latency of around 15 ms, 66 frames per second, which proves this is suitable for time-sensitive applications. Because the 7nm FinFET technology improves system efficiency and responsiveness, it can be used in real-time applications where high-precision motion detection is necessary in dynamic conditions. However, potential challenges include scalability for large-scale deployment and hardware constraints associated with real-time processing on FinFET-based circuits. The proposed system can be used for robotic vision systems, autonomous vehicles, and other contexts where real-time visual processing and threat detection are needed. © 2013 IEEE.

关键词： Motion estimation

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A novel medical case entity recognition method based on the BiSRU-TextCNN

A novel medical case entity recognition method based on the ...

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International Congress on Image and Signal Processing, BioMedical engineering and Informatics (CISP-BMEI)

作者： CAI Hongguo Norriza Hussin Peng Yizhong Faculty of Engineering Built Environment and Information Technology (FEBIT) The SEGI University Petaling Jaya Selangor Malaysia School of Logistics Management and Engineering Nanning Normal University China Department of Computer and Information Engineering Nanning Normal University China

the traditional BiLSTM neural network model can't extract local semantic features. What’s more, the model training focuses on relevant data and ignores irrelevant data as much as possible. Therefore, the novel medical case entity recognition called method called BiSRU-TextCNN solves the problem. This method fuses multivariate feature vectors, fully extracts local features and global features of related data. The experimental results show that the precision, recall rate and F1-Measure value of the new model are significantly improved, and the training time of the model is obviously shortened.

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Minute Level Ultra-Rapid and Thousand Copies Level Ultra-Sensitive Pathogen Nucleic Acid Identification Based on Contactless Impedance Detection Microsensor

SSRN

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SSRN 2024年

作者： Zhang, Zhikang Yuan, Haojun Yin, Jiawen Li, Min Cao, Xinyi Gao, Wanlei Jin, Qinghui The Faculty of Electrical Engineering and Computer Science Ningbo University Zhejiang Ningbo315211 China State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai200050 China

Nucleic acid testing (NAT) is a valuable method for keeping pathogens from spreading. However, the long detection time and large size of the instruments involved significantly limit the efficiency of detection. This work describes an integrated NAT micro-sensor that facilitates rapid and extremely sensitive detection based on nucleic acid amplification (NAA) on a chip. The biochip consists of two layers incorporating a heater, a thermometer, an interdigital electrode (IDE) and a reaction chamber. The heater and thermometer are utilized to maintain a specific temperature for the sample in the chamber. The thermometer exhibits a good linear correlation with a sensitivity of 9.36 Ω/°C and the heater achieves a heating efficiency of approximately 6.5 °C/s. IDE is employed for real-time monitoring of the in-chip reaction system impedance and NAA process. The IDE demonstrates strong linearity with a sensitivity of -1.20 kΩ/mM. Specific nucleic acids from two pathogens (SARS-CoV-2, Vibrio vulnificus) are detected with this micro-sensor. The samples are qualitatively analyzed on microchip within 3 minutes, with a limit of detection (LOD) of 103 copies/μL. The proposed sensor presents several advantages, including reduced NAT time and increased sensitivity. Consequently, it reveals significantly potential in the field of epidemic prevention. © 2024, The Authors. All rights reserved.

关键词： Nucleic acids

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Modeling of COVID-19 outbreak in Gaza Strip using SEIR model

Modeling of COVID-19 outbreak in Gaza Strip using SEIR model

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computer Science, information technology and engineering (ICCoSITE), International Conference on

作者： Akram M. Radwan Waleed Mortaja Husam Alzaq Information Technology Faculty University College of Applied Sciences Gaza Palestine Engineering & Smart Systems Faculty University College of Applied Sciences Gaza Palestine Computer Engineering Department Istinye University Istanbul Turkey

The novel coronavirus (COVID-19) pandemic is a major global health threat that was spreading very quickly around the world. Many mathematical models are being formulated to study the spread of COVID-19 and to predict its evolution, in order to help mitigating future outbreaks. The Susceptible-Exposed-Infectious-Recovered (SEIR) model is considered a prevalent model that describes various diseases outbreaks including COVID-19. The model divides the individuals into four groups; susceptible, exposed, infectious, recovered. To predict the evolution of the pandemic using the SEIR model, we first estimate the parameters as well as initial conditions. In this work, we model the spreading of COVID-19 pandemic using the SEIR in Gaza Strip to identify the better fitting model for forecasting future spread. The data required for estimation was collected between March 1st, 2021 and December 31st, 2021. The simulation results using SEIR model showed a significant model fitting, as there is no considerable difference from the real data compared to the respective model values. We also study the severity of the pandemic by identifying two important parameters; the basic reproduction rate (R o ), which determines the speed of the spread of COVID-19; and the infection fatality ratio (IFR) which estimates the proportion of deaths among all infected individuals. We obtained a value of R o = 0. 89. IFR value is ranged between 0.079% and 0.085%, which is less than the global average of about 0.15%.

关键词： COVID-19 Strips Pathogens Pandemics Simulation Fitting Predictive models

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