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1st International Conference on Cyber Security and Computing, CyberComp 2024

作者： Saleem, Muhammad Asif Senan, Norhalina Aamir, Muhammad Universiti Tunn Hussein Onn Malaysia Faculty of Computer Science and Information Technology Batu Pahat Malaysia University of Oxford Department of Computer Science United Kingdom

ISBN: (纸本)9798350387728

Recent improvements in Convolution Neural Networks (CNN) have demonstrated extraordinary performance in solving real-world problems. However, the performance of CNN depends purely on its architectural parameters and their arrangements. Designing CNN architecture for a particular problem is time consuming and requires a deep understanding of Neural networks, which is not possible for each researcher. In this research, an automated CNN architecture based on the Particle Swarm Optimization algorithm empowered with an iterative mutation operator and Opposition-based Learning strategy is proposed for image classification problems. The proposed technique significantly enhances performance in terms of accuracy, precision-recall, and convergence rate. The effectiveness of the proposed method is evaluated on benchmark datasets, including CIFAR-10, MNIST-Fashion, and Paddy Doctor Dataset. It demonstrates superior performance compared to traditional models which are Alex-Net, VGG19, GA-CNN, and PSO-CNN. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Age-Based Ranking of YouTube Videos for Improved Parental Controls in Smart TV Environment

Age-Based Ranking of YouTube Videos for Improved Parental Co...

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2022 International Conference on Emerging Technologies in Electronics, Computing and Communication, ICETECC 2022

作者： Alam, Iftikhar Uddin, Azhar Khusro, Shah City University of Science & Information Technology Department of Computer Science Peshawar Pakistan University of Peshawar Department of Computer Science Peshawar Pakistan

ISBN: (纸本)9781665490870

YouTube is a popular social media networking site that contains billions of videos. Many YouTube videos target children of different ages with offensive, inappropriate, violent, etc. Numerous one-size-fits-all countermeasures and research work have been deployed and suggested. However, these solutions are ineffective in accurately detecting inappropriate content for a diverse audience of different needs and requirements. In this research work, instead of one-size-fits-all, we consider a mutable age-based context, where different Age-Groups (AG) have different choices and needs. A novel and real-time approach have been proposed to prevent and allow the audience of varying AG towards the diverse content of YouTube, specifically in a smart TV-watching scenario. The proposed system analyses the running video through its metadata for teenagers, children, and adults. In parallel with data, the proposed model captures the viewers in real-time, detects their age, and checks the displayed video against the detected AG for appropriateness. The same system responds to parental consent and overrides its stop/play policies according to the direct input provided by parents/guardians with a diverse psychological setup, developed by their beliefs, religion, and cultural sensitivities. The proposed solution leverages Random Forest Classifier-a supervised text classification approach with 80% accuracy and Convolutional Neural Network for age determination using the Caffe model. © 2022 IEEE.

关键词： Convolutional neural networks

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Implementation of secure email server in cloud environment

Implementation of secure email server in cloud environment

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2012 International Conference on computer and Communication Engineering, ICCCE 2012

作者： Madi, Nadim K. M. Salehian, Solmaz Masoumiyan, Farzaneh Abdullah, Azizol Department of Communication Technology and Networks Faculty of Computer Science and Information Technology University Putra Malaysia 43400 UPM Serdang Selangor Malaysia

ISBN: (纸本)9781467304788

In the recent virtual communication world, the email services play a vital role as a basic content of heterogeneous networking infrastructure. Whereby, multiple platforms are connecting each other. Mail Server refers to computer performing Mail Transfer Agent functions. MTA is software that delivers electronic mail messages from one computer to another, by using client-server application architecture. MTA implements both sender and receiver portions of SMTP (Simple Mail Transfer Protocol). Postfix is a free and open-source MTA which is fast, easy-to-administrator and provide secure communication over Internet. In this paper we focus on the problem of email contents disclosure, and establish a secure mail server by using Postfix in Linux platform and then implement it into a cloud service provider as IaaS (Infrastructure as a Service). Security is provided by tuning a Transport Layer Security (TLS), and SMTP-AUTH which use Simple Authentication and Security Layer (SASL) as a security mechanism and platform. © 2012 IEEE.

关键词： Infrastructure as a service (IaaS)

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Fuzzy Logic-based Routing Adaptation for QoS Support in WSNs 1

Fuzzy Logic-based Routing Adaptation for QoS Support in WSNs

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1st International Conference on Emerging Technologies for Dependable Internet of Things, ICETI 2024

作者： Abdulmoghni, Yosef A. Alhomdy, Sharaf A. Al-Ashmoery, Yahya Department of Information Technology Faculty of Computer Science and IT Sana’a University Sana’a Yemen Department of IT Al-Razi University Dept. Mathematics & Computer Faculty of Science Sana’a University Sana’a Yemen

ISBN: (纸本)9798331533557

Wireless sensor networks (WSNs) have been widely used in dynamic environments where node failure, node mobility, or external events can cause frequent changes to the network architecture. As a result, WSNs cannot use conventional routing techniques created for wired networks. Rather, flexible routing algorithms are required, which can be adjusted according to the network circumstances and maximize a variety of parameters such as latency, productivity, power, and dependability. The objective of adaptation technique is to enhance the performance and efficiency of WSNs by adjusting them to changing conditions. Despite several studies on enhancing the quality of service (QoS) in WSNs, satisfying one of the QoS metrics has often a detrimental impact on the other metrics. The adaptation model combines artificial intelligence and cross-layer techniques for balancing energy consumption. This balancing aims to prevent gaps in the routing path that could impede data delivery or, at most, cause additional delay due to the consideration of alternative paths. It also aims to ensure that the other QoS metrics are stratified as much as possible. This is achieved by dynamically adjusting network routing protocol parameters using a fuzzy controller according to the instantaneous network conditions. The model is evaluated by simulating real multimedia data (real images) using the Omnet++ simulator. The simulation results demonstrate the effectiveness of the adaptation model in balancing QoS requirements, particularly in terms of network lifetime and the quality of the received data as represented by the peak signal-to-noise ratio (PSNR), as well as network delay and data loss rate. © 2024 IEEE.

关键词： Internet of things

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Evolutionary algorithms for many-objective ground station scheduling problem 11th

Evolutionary algorithms for many-objective ground station sc...

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11th International Conference on Bio-inspired Computing – Theories and Applications, BIC-TA 2016

作者： Zhang, Zhongshan Xing, Lining Chen, Yuning Wang, Pei College of Information System and Management National University of Defense Technology Changsha China Department of Computer Science and Technology University d’Angers Angers France

ISBN: (纸本)9789811036132

The task planning of satellite-ground time synchronization (SGTSTP) is a complex many-objective ground station scheduling problem. In this paper, we first provide a mathematical formulation of SGTSTP. To solve this problem, we propose a decomposition-and-integration (DI) based method. In DI method, the plan horizon is evenly divided into many disjoint plan periods and all time windows are distributed to each period, based on which the task planning problem turns into a multi-period 0-1 programming problem. Then we embed DI method into evolutionary algorithm framework and propose DI based evolutionary many-objective algorithm (DI-EMOA). At last, the computational results show that the DI-EMOAs have obvious performance promotion compared with heuristic algorithm. © Springer Nature Singapore Pte Ltd. 2016.

关键词： Evolutionary algorithms

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Wireless Backhaul Network Optimization Using Automated KPIs Monitoring system Based on Time Series Forecasting

Wireless Backhaul Network Optimization Using Automated KPIs ...

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2018 IEEE World Symposium on Communication Engineering, WSCE 2018

作者： Mahmood, Atif Kiah, Miss Laiha Binti Mat Azzuhri, Saaidal Razalli Bin Qureshi, Adnan N. Faculty of Computer Science University of Malaya Malaysia Faculty of Information Technology University of Central Punjab Pakistan

ISBN: (纸本)9781538679869

Owing to the advancement of a communication network to the fourth generation and soon moving towards the fifth generation, the capacity demand has substantially increased in recent years. Currently, 'point-to-point microwave' an imperative technology is used in wireless backhaul networks around the globe that bequeaths interconnectivity amid the core network and the base stations. Because of this high demand, the wireless backhaul network optimization is a very important factor and has become the iterative process for better coverage and delivering high Quality of Service (QoS). To facilitate this process, traffic projections execute a significant job to enrich the network excellence resulted in better network capacity planning and frequency reuse. We proposed an adaptive solution for network Key Performance Indicators (KPIs) monitoring based on time series forecasting. The forecasting is grounded on Autoregressive Integrated Moving Average (ARIMA) models, Autoregressive (AR) and Multilayer perceptrons (MLP) neural network method. It analyzes the network utilization on specific time intervals (past and current data) and forecasts future requirements. It investigates observed unbalanced resources allocations in both ways underutilize and overutilize links based on real network utilization. Based on the proposed system forecasted results, the optimal solution for network capacity planning and frequency channel reuse will be suggested to reduce the resource wastage. We have observed that in the context of convergence time the AR is best and MLP with 10 hidden nodes takes longest. But when we discuss the results the MLP with 10 hidden nodes gives the best. The one analysis was done on 181 days observations, we used AR(16), SARIMA(1,0,0)(1,1,0) [7] and MLP 10 hidden nodes with RMSE 37.87, 40.00 and 13.54 respectively it indicates that MLP was best. Conclusively, we evaluated the performance of methods using RMSE. On the grounds of experiments, we perceived that MLP was g

关键词： Benchmarking

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Proposing a novel artificial neural network prediction model to improve the precision of software effort estimation

Proposing a novel artificial neural network prediction model...

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5th International ICST Conference on Bio-Inspired Models of Network, information, and Computing systems, BIONETICS 2010

作者： Attarzadeh, Iman Ow, Siew Hock Department of Software Engineering Faculty of Computer Science and Information Technology University of Malaya 50603 Kuala Lumpur Malaysia

ISBN: (纸本)9783642326141

Nowadays, software companies have to mange different software development processes based on different time, cost, and number of staff sequentially, which is a very complex task and supports project planning and tracking. Software time, cost and manpower estimation for separate projects is one of the critical and crucial tasks for project managers. Accurate software estimation at an early stage of project planning is counted as a great challenge in software project management, in the last decade, as it allows considering project financial, controlling, and strategic planning. Software effort estimation refers to the estimations of the likely amount of cost, schedule, and manpower required to develop software. This paper proposes a novel artificial neural network prediction model incorporating Constructive Cost Model (COCOMO). The new model uses the desirable features of artificial neural networks such as learning ability, while maintaining the merits of the COCOMO model. This model deals efficiently with uncertainty of software metrics to improve the accuracy of estimates. The experimental results show that using the proposed model improves the accuracy of the estimates, 8.36% improvement, when the obtained result compared to the COCOMO model. © 2012 ICST Institute for computer science, Social Informatics and Telecommunications Engineering.

关键词： Neural networks

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Heart sounds monitor and analysis in noisy environments

Heart sounds monitor and analysis in noisy environments

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2012 International Conference on systems and Informatics, ICSAI 2012

作者： Song, Dandan Jia, Lijuan Lu, Yao Tao, Linmi Beijing Lab of Intelligent Information Technology School of Computer Science Beijing Institute of Technology Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781467301992

Changes and murmurs of heart sounds often provide the earliest information of abnormal heart status, which makes heart sound monitor and diagnose an important mean for cardiovascular disease. Compared to other heart monitoring approaches, such as EGG, Color Doppler and Magnetic Resonance Imaging Diagnosis, heart sound detection is more portable, much safer and cheaper, and needs lower professional requirements, thus has a broader applicability. This paper aims to design a system for monitoring and analyzing heart sounds in noisy environments, which can achieve signal acquisition, automatic analysis and classification. For the signal acquisition part, a novel equipment prototype is designed by separately using the two channels of a digital sound, one to record mixed signals of heart sounds and some environmental noises, and the other to record only environmental noises as a reference, then the environmental noise can be filtered out based on Least Mean Square (LMS) adaptive noise cancellation to get purified heart sound. By disassembling and assembling a stethoscope and a recorder, this design is realized and verified. For the signal analysis and classification part, with the features extracted by wavelet decomposition and Normalized Average Shannon Energy, a novel fuzzy neural network method with structure learning is used for the heart sound classification. Experiments with real and simulated data demonstrated that our approach can correctly classify all the tested heart sounds with noises even for the ones with previous unseen heart diseases. © 2012 IEEE.

关键词： Diagnosis

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The Relationship Between Nomophobia, Emotional Intelligence, Interpersonal Problem-Solving, Perceived Stress, and Self-esteem Among Undergraduate Students

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Journal of technology in Behavioral science 2023年第1期8卷 27-35页

作者： Karaoglan Yilmaz, Fatma Gizem Yilmaz, Ramazan Erdogdu, Fatih Faculty of Science Department of Computer Technology & Information Systems Bartin University Bartin Turkey Department of Computer Technologies Ereğli Vocational School Bulent Ecevit University Zonguldak Turkey

Nomophobia is derived from “no mobile phobia”;it is defined as the fear of being away from the possibility of communication by mobile phone. Since mobile phones are used actively in many fields, from communication to social media, from the stock market to e-commerce, users can practically follow developments in their areas of interest with their mobile phones. This situation reveals the need for users to keep their phones with them all the time and can trigger the development of nomophobia feelings. This fear can become increasingly common among mobile phone users today and may require clinical interventions due to its consequences. Researchers state that the investigation of factors that cause nomophobia can inform subsequent interventions and guidance studies to overcome this fear. Various studies have been carried out to determine the causes of nomophobia. In these studies, the importance of individual psycho-social factors is revealed. However, it is emphasized that dimensions related to psycho-social factors need to be explored. One of them is the relationship of nomophobia with emotional intelligence, interpersonal problem-solving, perceived stress, and self-esteem. This study investigated the structural relationships between university students’ nomophobia and emotional intelligence, interpersonal problem-solving, perceived stress, and self-esteem. The research was carried out on 543 university students. Fifty-seven percent of the students participating in the study were female, and 43% were male. Path analysis was performed in the analysis of the data. The results of the research reveal that as the interpersonal problem-solving skills of university students improve, nomophobia decreases. Depending on the development of emotional intelligence, students’ interpersonal problem-solving skills increase. In addition, the development of emotional intelligence reduces the level of perceived stress. In line with the findings obtained from the research, various sugges

关键词： Emotional intelligence Interpersonal problem-solving Nomophobia Perceived stress Self-esteem Undergraduate students

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Exploring inhibitor release pathways in histone deacetylases using random acceleration molecular dynamics simulations

Exploring inhibitor release pathways in histone deacetylases...

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作者： Kalyaanamoorthy, Subha Chen, Yi-Ping Phoebe Department of Computer Science and Computer Engineering Faculty of Science Technology and Engineering La Trobe University Melbourne Australia

Molecular channel exploration perseveres to be the prominent solution for eliciting structure and accessibility of active site and other internal spaces of macromolecules. The volume and silhouette characterization of these channels provides answers for the issues of substrate access and ligand swapping between the obscured active site and the exterior of the protein. Histone deacetylases (HDACs) are metal-dependent enzymes that are involved in the cell growth, cell cycle regulation, and progression, and their deregulations have been linked with different types of cancers. Hence HDACs, especially the class I family, are widely recognized as the important cancer targets, and the characterizations of their structures and functions have been of special interest in cancer drug discovery. The class I HDACs are known to possess two different protein channels, an 11 Å and a 14 Å (named channels A and B1, respectively), of which the former is a ligand or substrate occupying tunnel that leads to the buried active site zinc ion and the latter is speculated to be involved in product release. In this work, we have carried out random acceleration molecular dynamics (RAMD) simulations coupled with the classical molecular dynamics to explore the release of the ligand, N-(2-aminophenyl) benzamide (LLX) from the active sites of the recently solved X-ray crystal structure of HDAC2 and the computationally modeled HDAC1 proteins. The RAMD simulations identified significant structural and dynamic features of the HDAC channels, especially the key 'gate-keeping' amino acid residues that control these channels and the ligand release events. Further, this study identified a novel and unique channel B2, a subchannel from channel B1, in the HDAC1 protein structure. The roles of water molecules in the LLX release from the HDAC1 and HDAC2 enzymes are also discussed. Such structural and dynamic properties of the HDAC protein channels that govern the ligand escape reactions will provide further m

关键词： Ligands

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