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2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Moubayed, Abdallah Injadat, MohammadNoor Abdellatif Mohamed, Tamer Mohamed Almatarneh, Sattam Al-Mashagbeh, Malak Aljaidi, Mohammad School of Computing and Augmented Intelligence Arizona State University GilbertAZ United States Lebanese American University Electrical and Computer Engineering Department Byblos Lebanon Western University Electrical and Computer Engineering Department LondonON Canada Zarqa University Data Science and Artificial Intelligence Department Zarqa Jordan School of Engineering Applied Science and Technology Canadian University Dubai Dubai United Arab Emirates Zarqa University Cyber Security Department Zarqa Jordan Zarqa University Computer Science Department Zarqa Jordan

ISBN: (纸本)9798350373363

The added deployment of Internet-of-Things (IoT) devices in various environments has led to people increasingly adding this technology to their homes to make them more comfortable and have a more convenient living environment. Despite the promise and the growth potential of the smart home market, one main concern is the security and privacy of smart home devices. This is because smart home devices equipped with IoT technology are prone to various network-based attacks. With smart home devices having limited computation and memory capabilities, many IoT manufacturers often overlook the security aspect by focusing more on the functionality. To address this issue, the concepts of machine learning (ML) and deep learning (DL) have emerged as viable and promising solutions. To that end, this paper proposes a hybrid stacking ensemble DL-enabled framework that combines both classical ML models with sophisticated DL models. The goal is to make use of the simplicity and interpretability of the classical ML models with the superior time-dependent patterns that DL models can detect. The proposed framework's performance is evaluated using multiple datasets representing different smart home devices. Experimental results show that the proposed framework achieved better detection accuracy, precision, recall, and F-score. © 2023 IEEE.

关键词： Intrusion detection

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Optimized Image Dehazing using Dark Channel Prior with Minimum Fusion and Improved Atmospheric Light Handling

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IEEE Access 2025年 13卷 100720-100730页

作者： Hussain, Ahmad Iqbal, Mansoor Aslam, Sheraz Alahmari, Saad Alkharashi, Abdulwahab University of Wah Department of Computer Science Cantt Wah Pakistan CTL eurocollege Department of Computer Science Limassol 3077 Cyprus Cyprus University of Technology Department of Electrical Engineering Computer Engineering and Informatics Limassol 3036 Cyprus Northern Border University Applied College Department of Computer Science Arar Saudi Arabia Saudi Electronic University College of Computing and Informatics Department of Computer Science Saudi Arabia

Haze-induced image degradation in outdoor scenes, caused by atmospheric scattering and absorption, poses significant challenges for applications such as surveillance, autonomous navigation, and remote sensing. This research focuses on improving image dehazing by enhancing two key components: Dark Channel Prior (DCP) and Atmospheric Light Estimation (ALE). DCP exploits the statistical property that haze-free regions exhibit low minimum intensity values, aiding in accurate haze detection. ALE estimates atmospheric light from distant, less-scattered sources, ensuring precise haze removal. To further enhance dehazing performance, this study introduces a Minimum Fusion Technique, which selects the minimum intensity value for each pixel across multiple dehazed outputs, effectively preserving fine details and reducing artifacts. The proposed method is evaluated on the SOTS Outdoor dataset from the RESIDE benchmark, comprising 500 pairs of real-world hazy and clear images. By integrating optimized DCP, ALE, and the Minimum Fusion Technique, the approach achieves superior performance with a PSNR of 35.45 dB and an SSIM of 0.97, outperforming existing methods such as Scene-Specific DCP, TON, and FFA_NET. Additionally, it demonstrates reduced execution time and enhanced visual quality, making it a more efficient and reliable solution for real-world dehazing applications. These improvements establish the proposed method as a state-of-the-art approach for restoring clarity in outdoor images, contributing to more effective and accurate image reconstruction in challenging environments. © 2013 IEEE.

关键词： Atmospheric Light Estimation Dark Channel Prior Image Dehazing Minimum Fusion Technique Visual Clarity

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Modified Sine Cosine Optimization with Adaptive Deep Belief Network for Movie Review Classification

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Intelligent Automation & Soft computing 2023年第7期37卷 283-300页

作者： Hala J.Alshahrani Abdulbaset Gaddah Ehab S.Alnuzaili Mesfer Al Duhayyim Heba Mohsen Ishfaq Yaseen Amgad Atta Abdelmageed Gouse Pasha Mohammed Department of Applied Linguistics College of LanguagesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of English College of Science&Art at MahayilKing Khalid UniversityMuhayel Aseer63311Saudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Aflaj16828Saudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Sentiment analysis(SA)is a growing field at the intersection of computer science and computational linguistics that endeavors to automati-cally identify the sentiment presented in *** linguistics aims to describe the fundamental methods utilized in the formation of computer methods for understanding natural *** is classified as a negative or positive assessment articulated through *** can be commonly used for the movie review classification that involves the automatic determination that a review posted online(of a movie)can be negative or positive toward the thing that has been *** learning(DL)is becoming a powerful machine learning(ML)method for dealing with the increasing demand for precise *** this motivation,this study designs a computational intelligence enabled modified sine cosine optimization with a adaptive deep belief network for movie review classification(MSCADBN-MVC)*** major intention of the MSCADBN-MVC technique is focused on the identification of sentiments that exist in the movie review ***,the MSCADBN-MVC model follows data pre-processing and the word2vec word embedding *** the classification of sentiments that exist in the movie reviews,the ADBN model is utilized in this *** last,the hyperparameter tuning of the ADBN model is carried out using the MSCA technique,which integrates the Levy flight concepts into the standard sine cosine algorithm(SCA).In order to demonstrate the significant performance of the MSCADBN-MVC model,a wide-ranging experimental analysis is performed on three different *** comprehensive study highlighted the enhancements of the MSCADBN-MVC model in the movie review classification process with maximum accuracy of 88.93%.

关键词： Computational linguistics movie review analysis sentiment analysis sentiment classification deep learning

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Advancing Simulations of Coupled Electron and Phonon Nonequilibrium Dynamics Using Adaptive and Multirate Time Integration

arXiv

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arXiv 2024年

作者： Yao, Jia Maliyov, Ivan Gardner, David J. Woodward, Carol S. Bernardi, Marco Department of Applied Physics and Materials Science Department of Physics California Institute of Technology PasadenaCA91125 United States Mathematics for Materials Modeling Institute of Mathematics Institute of Materials EPFL LausanneCH-1015 Switzerland Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA94550 United States

Electronic structure calculations in the time domain provide a deeper understanding of nonequilibrium dynamics in materials. The real-time Boltzmann equation (rt-BTE), used in conjunction with accurate interactions computed from first principles, has enabled reliable predictions of coupled electron and lattice dynamics. However, the timescales and system sizes accessible with this approach are still limited, with two main challenges being the different timescales of electron and phonon interactions and the cost of computing collision integrals. As a result, only a few examples of these calculations exist, mainly for two-dimensional (2D) materials. Here we leverage adaptive and multirate time integration methods to achieve a major step forward in solving the coupled rt-BTEs for electrons and phonons. Relative to conventional (non-adaptive) time-stepping, our approach achieves a 10x speedup for a given target accuracy, or greater accuracy by 3–6 orders of magnitude for the same computational cost, enabling efficient calculations in both 2D and bulk materials. This efficiency is showcased by computing the coupled electron and lattice dynamics in graphene up to ∼100 ps, as well as modeling ultrafast lattice dynamics and thermal diffuse scattering maps in a bulk material (silicon). These results open new opportunities for quantitative studies of nonequilibrium physics in materials. Copyright © 2024, The Authors. All rights reserved.

关键词： Boltzmann equation

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Boosting generation rate of squeezed single photon states by generalized photon subtraction

Boosting generation rate of squeezed single photon states by...

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CLEO: Fundamental Science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Tomoda, Hiroko Machinaga, Akihiro Takase, Kan Harada, Jun Kashiwazaki, Takahiro Umeki, Takeshi Miki, Shigehito Terai, Hirotaka Yabuno, Masahiro China, Fumihiro Okuno, Daichi Takeda, Shuntaro Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan NTT Device Technology Labs NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan Advanced ICT Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi Kobe651-2492 Japan Graduate School of Engineering Kobe University 1-1 Rokko-dai Kobe Nada657-0013 Japan

We theoretically and experimentally proved that the generation rate of squeezed single photon states can be increased by generalized photon subtraction method. Our work will encourage universal and fault-tolerant cont... 详细信息

ISBN: (纸本)9781957171395

关键词： Squeezed light

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Virtual Network Embedding: Literature Assessment, Recent Advancements, Opportunities, and Challenges

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IEEE Communications Surveys and Tutorials 2025年

作者： Satpathy, Anurag Sahoo, Manmath Narayan Swain, Chittaranjan Bellavista, Paolo Guizani, Mohsen Muhammad, Khan Bakshi, Sambit Missouri University of Science and Technology Department of Computer Science RollaMO United States National Institute of Technology Visual Surveillance Laboratory Department of Computer Science and Engineering Odisha Rourkela769008 India Atal Bihari Vajpayee Indian Institute of Information Technology and Management Department of Computer Science and Engineering Gwalior India Department of Computer Science and Engineering Italy Machine Learning Department Abu Dhabi United Arab Emirates Department of Applied Artificial Intelligence School of Convergence College of Computing and Informatics Seoul03063 Korea Republic of

Network virtualization (NV) allows service providers (SPs) to instantiate logically isolated entities called virtual networks (VNs) on top of a substrate network (SN). Though VNs bring about multiple benefits, particularly in terms of economic costs and elasticity, they also force various technical challenges to be addressed. The primary one is the issue of optimally allocating resources to VNs, also termed virtual network embedding (VNE). This paper presents an exhaustive survey of VNE by extensively covering the state-of-the-art research field in this very active field and focusing on the emerging research trends in industry and academia over the last decade. In addition, this survey originally contributes to the literature by proposing a novel taxonomy for existing VNE solutions and providing a thorough comparative study of their strategies. © 1998-2012 IEEE.

关键词： Virtual machine

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Characterization and Assessment of Cold Plasma for Cancer Treatment

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Plasma Medicine 2022年第2期12卷 1-14页

作者： Shakya, Aavash Pradhan, Suman Prakash Basnet, Niroj Shrestha, Rajendra Joshi, Pusp Raj Gautam, Roshan Paneru, Aakash Ashok, G.C. Shah, Arun Kumar Adhikari, Rameshwar Subedi, Deepak Prasad Regmi, Sagar Department of Physics School of Science Kathmandu University Dhulikhel Nepal Department of Environmental Science and Engineering School of Science Kathmandu University Dhulikhel Nepal Department of Physics Nepal Banepa Polytechnic Institute Kavre Banepa Nepal Department of Physics Tribhuvan University Patan Multiple Campus Lalitpur Nepal Annapurna Research Center Kathmandu Nepal School of Computing and Digital Technology Birmingham City University United Kingdom Department of Chemical Science and Engineering School of Engineering Kathmandu University Dhulikhel Nepal Research Centre for Applied Science and Technology Tribhuvan University Kathmandu Nepal Nepal Academy of Science and Technology Lalitpur Nepal Department of Pharmacology School of Medicine Case Western Reserve University ClevelandOH44106 United States

The unbalanced lifestyle and rampant use of modern medicine are the lead-ing causes of life-threatening cancer disease prevalence. In the last few decades, chemotherapy and other medication techniques promised to cure cancer. However, cold plasma on cancer cell lines gets little attention due to a lack of understanding of the detailed mech-anism of action. In the contemporary time frame, it is well established that cold plasma therapy is one of the best alternatives for treating cancer. The selectivity of cancer cells by plasma treatment has a unique potential as therapeutics in future clinical practices. In this study, we analyzed the potential of cold atmospheric plasma (CAP) irradiated medium as a promising anti-cancer tool by using a high-voltage power source with a 20 kHz operat-ing frequency. The discharge was generated with argon as working gas and characterized by optical emission spectroscopy. Eagle’s minimum essential medium (EMEM) was treated with CAP utilizing argon as a plasma source at 2–3 kV for varied time durations (0 min, 1 min, 2 min, 3 min, 4 min, and 5 min) to demonstrate the anti-cancer capabilities of CAP treated media. The treated media culture grows cervical cancer cells (HeLa), breast cancer cells (MCF-7), mouse fibroblast cell line (3T3), and the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay was carried out to determine the cell viability and inhibition rate. Our results revealed a considerable difference in viability between cancer cells and normal cells as treatment time increases from 1 to 5 min. The cell viability for HeLa (15.23%) and MCF-7 (16.18%) as compared to 3T3 cells (134.56%). This study provides evidence for the potential of CAP-treated media as an avenue for an anti-cancer representative. © 2022 by Begell House, Inc.

关键词： Argon

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Bi-Directional Transformers vs. word2vec: Discovering Vulnerabilities in Lifted Compiled Code

Bi-Directional Transformers vs. word2vec: Discovering Vulner...

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Cyber Awareness and Research Symposium (CARS)

作者： Gary A. McCully John D. Hastings Shengjie Xu Adam Fortier The Beacom College of Computer and Cyber Sciences Dakota State University Madison SD USA Department of Cyber Intelligence and Information Operations College of Applied Science & Technology University of Arizona Tucson AZ USA College of Computing Georgia Institute of Technology Atlanta GA USA

ISBN: (数字)9798350386417

ISBN: (纸本)9798350386424

Detecting vulnerabilities within compiled binaries is challenging due to lost high-level code structures and other factors such as architectural dependencies, compilers, and optimization options. To address these obstacles, this research explores vulnerability detection using natural language processing (NLP) embedding techniques with word2vec, BERT, and RoBERTa to learn semantics from intermediate representation (LLVM IR) code. Long short-term memory (LSTM) neural networks were trained on embeddings from encoders created using approximately 48k LLVM functions from the Juliet dataset. This study is pioneering in its comparison of word2vec models with multiple bidirectional transformers (BERT, RoBERTa) embeddings built using LLVM code to train neural networks to detect vulnerabilities in compiled binaries. Word2vec Skip-Gram models achieved 92% validation accuracy in detecting vulnerabilities, outperforming word2vec Continuous Bag of Words (CBOW), BERT, and RoBERTa. This suggests that complex contextual embeddings may not provide advantages over simpler word2vec models for this task when a limited number (e.g. 48K) of data samples are used to train the bidirectional transformer-based models. The comparative results provide novel insights into selecting optimal embeddings for learning compiler-independent semantic code representations to advance machine learning detection of vulnerabilities in compiled binaries.

关键词： Codes Accuracy Semantics Neural networks Bidirectional control Transformers Encoding Natural language processing Long short term memory Context modeling

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Docker Containerized Infrastructure Orchestration with Portainer Container-native Approach 3

Docker Containerized Infrastructure Orchestration with Porta...

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3rd International Conference for Emerging technology, INCET 2022

作者： Kithulwatta, W.M.C.J.T. Jayasena, K.P.N. Kumara, B.T.G.S. Rathnayaka, R.M.K.T. Sabaragamuwa University of Sri Lanka Faculty of Graduate Studies Belihuloya Sri Lanka Uva Wellassa University of Sri Lanka Faculty of Technological Studies Badulla Sri Lanka Sabaragamuwa University of Sri Lanka Faculty of Applied Sciences Department of Computing and Information Systems Belihuloya Sri Lanka Sabaragamuwa University of Sri Lanka Faculty of Applied Sciences Department of Physical Sciences and Technology Belihuloya Sri Lanka

ISBN: (纸本)9781665494991

Virtualization is an old technology that facilitates launching a computer infrastructure on another computer infrastructure. Very recently a containerized approach arrived in the computing world. Among most container vendors, Docker is the most trending and highly used container classification. To interact, orchestrate, govern and manage any Docker platform, a command-line-oriented approach was used. Portainer is a container-oriented approach, which provides the capability to orchestrate, govern and manage the whole Docker farm. Still, there is no such kind of evaluations for Portainer oriented orchestrations for Docker farms. This research study aims to evaluate Portainer oriented approaches to orchestrate Docker farms than traditional Docker command line approaches. The command-line-based approach brings plenty of complexity for the users to make interactions with Docker. Therefore, according to the observed facilities and capacities of the Portainer, Portainer is with very less overhead to the host infrastructure. As well interactive graphical user interfaces, easy accessibility, high platform security integration, and versatile monitoring features are beneficial to the end-users. © 2022 IEEE.

关键词： Containers

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Performance Evaluation of Docker-based Apache and Nginx Web Server 3

Performance Evaluation of Docker-based Apache and Nginx Web ...

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3rd International Conference for Emerging technology, INCET 2022

ISBN: (纸本)9781665494991

Containerization is the modern trending concept for net-centric software application deployments other than the traditional virtualization. Among many container vendors, Docker is the most popular one in the industry. Launching all kinds of software based services and software applications on the Docker farm, is available. Apache and Nginx are the most highly used web servers in the practitioner. This research study aims to evaluate Apache and Nginx web server performances on the Docker platform. By using two separate Docker containers, the experimental study was conducted. Basically, six web server performance criteria were evaluated: requests per second, failed requests, availability, failed transactions, response time and transaction rate. For the requests per second measurement, Apache web server was presented with higher features than Nginx web server on the Docker farm with default configurations. But other evaluation measurements were approximately the same values for both servers. Both web servers with 100% availability and according to the all evaluated criteria, both Apache and Nginx web servers are recommended to use with default configurations on the Docker farms. © 2022 IEEE.

关键词： Containers

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