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2023 international Conference on iT and industrial Technologies, iCiT 2023

作者： Shabbir, Attia Ali, Raja Hashim Shabbir, Muhammad Zeeshan Abideen, Zain Ul Khan, Talha Ali ijaz, Ali Zeeshan Ali, Nisar imad, Muhammad Bakar, Muhammad Abu Gik Institute of Engg. Sciences & Technology Faculty of Computer Science & Engineering Topi Pakistan University of Europe for Applied Sciences Dept. of Technology & Software Engineering Berlin Germany Department of Electrical Engineering Lahore Pakistan BCMaterials Basque Center for Materials Applications & Nanostructure Basque Country Leioa Spain University of Regina Faculty of Electronic Systems Engineering Regina Canada

ISBN: (纸本)9798350315974

Breast cancer is a significant global healthcare challenge, particularly in developing and underdeveloped countries, with profound physical, emotional, and psychological consequences, including mortality. Timely diagnosis and accurate treatment are crucial in addressing this issue. We propose the utilization of a feature selection technique to identify the most relevant features from among all features for breast cancer diagnosis, and show that Genetic Algorithms are impressive for this task. The study compares the results of GA with no selection and an alternative method, Principle Component Analysis (PCA). Three machine learning models, all based on supervised learning with data split into training and test data, are employed for binary classification using the selected feature subset. The evaluation metrics employed encompass accuracy, precision, recall, and F1-score. Among the selected models, Random Forest demonstrates the most favorable outcomes, achieving an accuracy score of 0.96, precision score of 0.96, recall value of 0.98, and an F1-score of 0.97. These results underscore the effectiveness of GA in feature selection for breast cancer diagnosis. Consequently, the integration of Genetic Algorithms (GA) with Random Forest showcases the superior performance among the evaluated models. © 2023 iEEE.

关键词： Genetic algorithms

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Parkinson’s Detection Using RNN-Graph-LSTM with Optimization Based on Speech Signals

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computers, Materials & Continua 2022年第7期72卷 871-886页

作者： Ahmed S.Almasoud Taiseer Abdalla Elfadil Eisa Fahd N.Al-Wesabi Abubakar Elsafi Mesfer Al Duhayyim ishfaq Yaseen Manar Ahmed Hamza Abdelwahed Motwakel Department of Information Systems College of Computer and Information SciencesPrince Sultan UniversityMahayil62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia Department of Computer Science College of Science and Artsat MahayilKing Khalid UniversityMahayil62529Saudi Arabia Faculty of Computer and IT Sana’a UniversitySana’aYemen Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahSaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversityMahayil62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj62529Saudi Arabia

Early detection of Parkinson’s Disease(PD)using the PD patients’voice changes would avoid the intervention before the identification of physical *** machine learning algorithms were developed to detect PD ***,these ML methods are lack in generalization and reduced classification performance due to subject *** overcome these issues,this proposed work apply graph long short term memory(GLSTM)model to classify the dynamic features of the PD patient speech *** proposed classification model has been further improved by implementing the recurrent neural network(RNN)in batch normalization layer of GLSTM and optimized with adaptive moment estimation(ADAM)on network hidden *** consider the importance of feature engineering,this proposed system use Linear Discriminant analysis(LDA)for dimensionality reduction and SparseAuto-Encoder(SAE)for extracting the dynamic speech *** on the computation of energy content transited from unvoiced to voice(onset)and voice to voiceless(offset),dynamic features are *** PD datasets is evaluated under 10 fold cross validation without sample *** proposed smart PD detection method called RNN-GLSTM-ADAM is numerically experimented with persistent phonations in terms of accuracy,sensitivity,and specificity andMatthew correlation *** evaluated result of RNN-GLSTM-ADAM extremely improves the PD detection accuracy than static feature based conventional ML and DL approaches.

关键词： Dimensionality reduction LDA feature extraction auto encoder classification recurrent neural network LSTM and optimization

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Hybrid Techniques of Multi-CNN and Ensemble Learning to Analyze Handwritten Spiral and Wave Drawing for Diagnosing Parkinson's Disease

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computer Modeling in engineering & sciences 2025年第5期143卷 2429-2457页

作者： Mohammed Al-Jabbar Mohammed Alshahrani Ebrahim Mohammed Senan ibrahim Abunadi Sultan Ahmed Almalki Eman A Alshari Computer Department Applied CollegeNajran UniversityNajran66462Saudi Arabia Department of Computer Science College of Applied SciencesHajah UniversityHajah9671Yemen Department of Artifcial Intelligence Faculty of Computer Science and Information TechnologyAl-Razi UniversitySanaa9677 Yemen Department of Sofware Engineering Cllege of Computer and Information SciencesKing Saud UniversityRiyadhI1543Saudi Arabia Computer Science and Information Technology Department Thamar UniversityDhamar9676Yemen

Parkinson’s disease(PD)is a progressive neurodegenerative disorder characterized by tremors,rigidity,and decreased *** poses risks to individuals’lives and *** detection of PD is essential because it allows timely intervention,which can slow disease progression and improve *** diagnosis of PD is problematic because it is difficult to capture the subtle patterns and changes that help diagnose *** addition,the subjectivity and lack of doctors compared to the number of patients constitute an obstacle to early *** intelligence(Ai)techniques,especially deep and automated learning models,provide promising solutions to address deficiencies in manual *** study develops robust systems for PD diagnosis by analyzing handwritten helical and wave graphical *** graphic images of the PD dataset are enhanced using two overlapping filters,the average filter and the Laplacian filter,to improve image quality and highlight essential *** enhanced images are segmented to isolate regions of interest(ROis)from the rest of the image using a gradient vector flow(GVF)algorithm,which ensures that features are extracted from only relevant *** segmented ROis are fed into convolutional neural network(CNN)models,namely DenseNet169,MobileNet,and VGG16,to extract fine and deep feature maps that capture complex patterns and representations relevant to PD *** and deep feature maps extracted from individual CNN models are combined into fused feature vectors for DenseNet169-MobileNet,MobileNet-VGG16,DenseNet169-VGG16,and DenseNet169-MobileNet-VGG16 *** fusion technique aims to combine complementary and robust features from several models,which improves the extracted *** feature selection algorithms are considered to remove redundancy and weak correlations within the combined feature set:Ant Colony Optimization(ACO)and Maximum Entropy Score-based Selection(MESbS).These algorithms i

关键词： CNN XGBoost RF GVF fusion feature PD

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software Testing issues improvement in Quality Assurance 2

Software Testing Issues Improvement in Quality Assurance

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2nd international Conference on Business Analytics for Technology and Security, iCBATS 2023

作者： Salahat, Mohammed Said, Raed A. Hamid, Khalid Haseeb, Usama Abdel Maguid Abdel Ghani, Elsaid Abualkishik, Abedallah iqbal, Muhammad Waseem inairat, Mohammad University of Science and Technology of Fujairah College of Engineering and Technology Fujairah United Arab Emirates Canadian University Dubai Faculty of Management Dubai United Arab Emirates Superior University Department of Computer Science Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan Superior University Department of Software Engineering Lahore Pakistan Canadian University Dubai Dubai United Arab Emirates American University in the Emirates College of Computer and Information Technology Dubai United Arab Emirates VICE CHANCELLOR Skyline University College Dubai United Arab Emirates

ISBN: (纸本)9798350335644

Quality assurance ensures that the project is carried out following the agreed-upon supplies, principles, and then purposes. The goal of type and its calibration investigation remains to better comprehend the multifaceted course of software analysis. Current software rehearses have some errors such as analysis techniques, user arrogances, and logistic culture. Altogether of these subjects, including such rushed testing, way to quickly times, totally inadequate supporting documents, and so on others must be addressed together. Describe a solution to the significant trouble of product testing in quality managing. We will discuss about the solutions of testing problems in quality management. propose a solution to the glitches mentioned above. © 2023 iEEE.

关键词： Quality control

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internet of Things (ioT) in Smart Cities: A Statistical Survey

Internet of Things (IoT) in Smart Cities: A Statistical Surv...

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Business Analytics for Technology and Security (iCBATS), international Conference on

作者： Muhammad Waseem iqbal Khowla Khaliq Nidal A. Al-Dmour Muhammad Aqeel Nasir Ali K. Hamid Department of Software Engineering Superior University Lahore Pakistan Department of Computer Sciecnce Superior University Lahore Pakistan Department of Computer Engineering College of Engineering Mutah University Jordan School of Computer Science NCBA&E Lahore Pakistan Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Science Superior University Lahore Pakistan

internet of things is progressing very rapidly and involving multiple domains of everyday life including environment, governance, healthcare system, transportation system, energy management system, etc. smart city is a platform for collecting and storing the information that is accessed through various sensor-based ioT devices and make their information available in required and authorized domains. This interoperability can be achieved by semantic web technology. in this paper, i have reviewed multiple papers related to ioT in Smart Cities and presented a comparison among the semantic parameters. Moreover, i’ve presented my future domain of research which is about delivering the COViD-19 patients report to the concerned domains by the healthcare system domain.

关键词： Semantic Web COViD-19 Smart cities Scalability Semantics Transportation Medical services

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improving Local Search for Pseudo Boolean Optimization by Fragile Scoring Function and Deep Optimization 29

Improving Local Search for Pseudo Boolean Optimization by Fr...

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29th international Conference on Principles and Practice of Constraint Programming, CP 2023

作者： Zhou, Wenbo Zhao, Yujiao Wang, Yiyuan Cai, Shaowei Wang, Shimao Wang, Xinyu Yin, Minghao School of Information Science and Technology Northeast Normal University Changchun China Key Laboratory of Applied Statistics of MOE Northeast Normal University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of MOE Jilin University Changchun China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783959773003

Pseudo-Boolean optimization (PBO) is usually used to model combinatorial optimization problems, especially for some real-world applications. Despite its significant importance in both theory and applications, there are few works on using local search to solve PBO. This paper develops a novel local search framework for PBO, which has three main ideas. First, we design a two-level selection strategy to evaluate all candidate variables. Second, we propose a novel deep optimization strategy to disturb some search spaces. Third, a sampling flipping method is applied to help the algorithm jump out of local optimum. Experimental results show that the proposed algorithms outperform three state-of-the-art PBO algorithms on most instances. © Wenbo Zhou, Yujiao Zhao, Yiyuan Wang, Shaowei Cai, Shimao Wang, Xinyu Wang, and Minghao Yin.

关键词： Combinatorial optimization

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Privacy-Preserving Periodic Frequent Pattern Model in AioT Applications

Privacy-Preserving Periodic Frequent Pattern Model in AIoT A...

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2021 international Symposium on intelligent Signal Processing and Communication Systems, iSPACS 2021

作者： Ahmed, Usman Lin, Jerry Chun-Wei Fournier-Viger, Philippe Cheng, Chien-Fu Western Norway University of Applied Sciences Electrical Engineering and Mathematical Sciences Department of Computer Science Bergen Norway Shenzhen University College of Computer Science and Software Engineering Shenzhen China Ntaional Taiwan Ocean University Department of Computer Science and Engineering Taiwan

ISBN: (纸本)9781665419512

We begin with a sanitization strategy for concealing sensitive periodic frequent patterns in this study. The developed method employs the Term Frequency and inverse Document Frequency (TF-iDF) to determine which transactions and objects should be sanitized based on user-defined sensitive periodic frequent patterns. Using the designed approach, it is possible to correctly and properly choose victim items in the transactional database for data sanitization. © 2021 iEEE.

关键词： Text processing

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Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore software Maintenance

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computers, Materials & Continua 2022年第11期73卷 3827-3845页

作者： Atif ikram Masita Abdul Jalil Amir Bin Ngah Nadeem iqbal Nazri Kama Azri Azmi Ahmad Salman Khan Yasir Mahmood Assad Alzayed Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of LahoreLahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi Malaysia54100Kuala LumpurMalaysia Computer Science and Information Systems Department College of Business Studies Public Authority for Applied Education and Training(PAAET)AdailiyaKuwait

Properly created and securely communicated,non-disclosure agreement(NDA)can resolve most of the common disputes related to outsourcing of offshore software maintenance(OSMO).Occasionally,these NDAs are in the form of *** the work is done offshore,these agreements or images must be shared through the internet or stored over the *** breach of privacy,on the other hand,is a potential threat for the image owners as both the internet and cloud servers are not void of *** article proposes a novel algorithm for securing the NDAs in the form of *** an agreement is signed between the two parties,it will be encrypted before sending to the cloud server or travelling through the public network,the *** the image is input to the algorithm,its pixels would be scrambled through the set of randomly generated rectangles for an arbitrary amount of *** confusion effects have been realized through an XOR operation between the confused image,and chaotic ***,5D multi-wing hyperchaotic system has been employed to spawn the chaotic vectors due to good properties of chaoticity it *** machine experimentation and the security analysis through a comprehensive set of validation metric vividly demonstrate the robustness,defiance to the multifarious threats and the prospects for some real-world application of the proposed encryption algorithm for the NDA images.

关键词： Non-disclosure agreement encryption decryption secret key chaoticmap confusion diffusion

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The Effectiveness of Advance Deep Learning Architectures for Classification of Stress using Raw EEG Data

The Effectiveness of Advance Deep Learning Architectures for...

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innovation in Technology (APCiT), Asia Pacific Conference on

作者： Ayush Tibrewal Shikha Divyashikha Sethia Department of Applied Physics Delhi Technological University Delhi India Department of Computer Science and Engineering Delhi Technological University Delhi India Department of Software Engineering Delhi Technological University Delhi India

ISBN: (数字)9798350361537

ISBN: (纸本)9798350361544

Understanding and detecting stress in today’s fast-paced world remains challenging. Previous research has explored various physiological signals, including EEG (Electroencephalography), to quantify stress. However, accurately assessing stress poses a significant challenge, particularly in preprocessing and feature extraction of EEG signals. Hence, this paper employs advanced deep learning algorithms, including ResNet18-1D, DenseNet-1D, and VGG16-1D, on raw EEG signals for automated stress classification. The study utilizes the publicly available EEG-based SAM40 dataset for stress classification and further validates the results on the EEG-based MAT dataset. The results demonstrate the efficacy of the ResNet18-1D model by achieving the highest of 98.73% and 97.24% on the SAM40 and MAT datasets, respectively. The findings pave the way for further exploration and utilization of raw EEG signals across diverse research domains beyond stress classification.

关键词： Deep learning Measurement Technological innovation Time series analysis Brain modeling Electroencephalography Data models

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A NovelMethod for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

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computer Modeling in engineering & sciences 2024年第2期138卷 1951-1979页

作者： Salma Khan Muhammad Gulistan NasreenKausar Seifedine Kadry Jungeun Kim Department of Mathematics and Statistics Hazara UniversityMansehra21120Pakistan Department of Mathematics Faculty of Arts and SciencesYildiz Technical UniversityEsenlerIstanbul34210Turkey Department of Applied Data Science Noroff University CollegeKristiansand4612Norway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjman346United Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityP.O.Box 13-5053ByblosLebanon Department of Software and CMPSI Konju National UniversityCheonan31080Korea

Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set(q−ROFHS)to enhance the formal representation of human thought processes and evaluate tourism carrying *** approach can capture the imprecision and ambiguity often present in human *** the advanced mathematical tools in this field,the study has also incorporated the Einstein aggregation operator and score function into the q−ROFHS values to supportmultiattribute decision-making *** implementing this technique,effective plans can be developed for social and economic development while avoiding detrimental effects such as overcrowding or environmental damage caused by tourism.A case study of selected tourism carrying capacity will demonstrate the proposed methodology.

关键词： q−Rung orthopair fuzzy hypersoft set decision-making tourism carrying capacity aggregation operator

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