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Human Stress Recognition from Facial Thermal-Based Signature:A Literature Survey

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Computer modeling in Engineering & Sciences 2022年第2期130卷 633-652页

作者： Darshan Babu L.Arasu Ahmad Sufril Azlan mohamed Nur Intan Raihana Ruhaiyem Nagaletchimee Annamalai Syaheerah Lebai Lutfi mustafa m.Al Qudah School of Computer Sciences Universiti Sains MalaysiaPenang11800Malaysia School of Distance Education Universiti Sains MalaysiaPenang11800Malaysia

Stress is a normal reaction of the human organism which triggered in situations that require a certain level of *** reaction has both positive and negative effects on everyone’s ***,stress management is of vital importance in maintaining the psychological balance of a ***-based imaging technique is becoming popular among researchers due to its non-contact conductive ***,thermal-based imaging has shown promising results in detecting stress in a non-contact and non-invasive *** to other non-contact stress detection methods such as pupil dilation,keystroke behavior,social media interaction and voice modulation,thermal-based imaging provides better features with clear boundaries and requires no heavy *** paper presented a brief review of previous work on thermal imaging related stress detection in *** paper also presented the stages of stress detection based on thermal face signatures such as dataset type,thermal image face detection,feature descriptors and classification performance comparisons are *** paper can help future researchers to understand stress detection based on thermal imaging by presenting the popular methods previous researchers use for stress detection based on thermal images.

关键词： Stress state stress recognition skin temperature thermal signature thermal imaging

malicious URL Classification Using Artificial Fish Swarm Optimization and Deep Learning

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Computers, materials & Continua 2023年第1期74卷 607-621页

作者： Anwer mustafa Hilal Aisha Hassan Abdalla Hashim Heba G.mohamed mohamed K.Nour mashael m.Asiri Ali m.Al-Sharafi mahmoud Othman Abdelwahed motwakel Department of Electrical and Computer Engineering International Islamic University Malaysia 53100 Kuala LumpurMalaysia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyUniversity of BishaSaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt

Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital *** Uniform Resource Locators(URLs)can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their *** may result in compromised security of the systems,scams,and other such *** attacks hijack huge quantities of the available data,incurring heavy financial *** the same time,machine Learning(mL)and Deep Learning(DL)models paved the way for designing models that can detect malicious URLs accurately and classify *** this motivation,the current article develops an Artificial Fish Swarm Algorithm(AFSA)with Deep Learning Enabled malicious URL Detection and Classification(AFSADL-mURLC)*** presented AFSADL-mURLC model intends to differentiate the malicious URLs from genuine *** attain this,AFSADL-mURLC model initially carries out data preprocessing and makes use of glove-based word embedding *** addition,the created vector model is then passed onto Gated Recurrent Unit(GRU)classification to recognize the malicious ***,AFSA is applied to the proposed model to enhance the efficiency of GRU *** proposed AFSADL-mURLC technique was experimentally validated using benchmark dataset sourced from Kaggle *** simulation results confirmed the supremacy of the proposed AFSADL-mURLC model over recent approaches under distinct measures.

关键词： malicious URL cybersecurity deep learning machine learning metaheuristics gated recurrent unit

Effect of Co substitution on the structural,electrical,and magnetic properties of Bi_(0.9)La_(0.1)FeO_3 by sol-gel synthesis

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International Journal of minerals,metallurgy and materials 2013年第2期20卷 166-171页

作者： ghulam Ali Saadat A.Siddiqi Shahid m.Ramay Shahid Atiq murtaza Saleem Centre of Excellence in Solid State Physics University of the Punjab Interdisciplinary Research Centre in Biomedical materials COMSATS Institute of Information Technology Chemical Engineering Department College of EngineeringKing Saud University

Cobalt （Co）-doped ***3 multiferroics were synthesized by a sol-gel method based on the auto- combustion technique. As-synthesized powder was examined using various characterization techniques to explore the effect of Co substitution on the properties of Bi0.9La0.1FeO3. X-ray diffraction reveals that Co-doped Bi0.9La0.1FeO3 preserves the perovskite-type rhombohedral structure of BiFeO3, and the composition without Co preserves the original structure of the phase; however, a second-phase Bi2Fe409 has been identified in all other compositions. Surface morphological studies were performed by scanning electron microscopy. Temperature-dependent resistivity of the samples reveals the characteristic insulating behavior of the multiferroic material. The resistivity is found to decrease with the increase both in temperature and Co content. Room temperature frequency-dependent dielectric measurements were also reported. magnetic measurements show the enhancement in magnetization with the increase in Co content.

关键词： multiferroics cobalt doping microstructure electric properties magnetic properties sol-gel process

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3^(1/2)细分曲面的误差界(英文)

中国科学技术大学学报 2009年第6期39卷 561-569页

作者： mustafa ghulam HASHmI Sadiq KHAN Faheem Department of mathematics The Islamia University of Bahawalpur

给出了3^(1/2)细分曲面和其k次细分后控制网之间的误差界估计.误差界是用初始控制点序列的一阶向前极大差分和常数表示的.采用的方法是对四边形细分框架中已有技术的推广.

关键词：细分曲线及曲面误差界

Construction and Application of 3-Point Tensor Product Scheme

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Applied mathematics 2013年第3期4卷 477-485页

作者： Abdul Ghaffar Ghulam.mustafa Kaihuai Qin The Islamia University of Bahawalpur Bahawalpur Pakistan Tsinghua University Beijing China

In this paper, we propose and analyze a tensor product subdivision scheme which is the extension of three point scheme for curve modeling. The usefulness of the scheme is illustrated by considering different examples ... 详细信息

关键词： Approximating Tensor Product Subdivision Scheme Binary Continuity Laurent Polynomial

The Odd-Point Ternary Approximating Schemes

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American Journal of Computational mathematics 2011年第2期1卷 111-118页

作者： Ghulam.mustafa Abdul Ghaffar Faheem Khan Department of mathematics The Islamia University of Bahawalpur Pakistan

We present a general formula to generate the family of odd-point ternary approximating subdivision schemes with a shape parameter for describing curves. The influence of parameter to the limit curves and the sufficient conditions of the continuities from C0 to C5 of 3- and 5-point schemes are discussed. Our family of 3-point and 5-point ternary schemes has higher order of derivative continuity than the family of 3-point and 5-point schemes presented by [Jian-ao Lian, On a-ary subdivision for curve design: II. 3-point and 5-point interpolatory schemes, Applications and Applied mathematics: An International Journal, 3(2), 2008, 176-187]. moreover, a 3-point ternary cubic B-spline is special case of our family of 3-point ternary scheme. The visual quality of schemes with examples is also demonstrated.

关键词： Approximating Subdivision Scheme Derivative Continuity Smoothness Convergence Shape Parameters and Laurent Polynomial

The 4-Point α-Ary Approximating Subdivision Scheme

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Open Journal of Applied Sciences 2013年第1期3卷 106-111页

作者： Abdul Ghaffar Ghulam.mustafa Kaihuai Qin Department of mathematics The Islamia University of Bahawalpur Bahawalpur Pakistan Dept. of Computer Science & Technology Tsinghua University Beijing 100084 P. R. China

A general formula for 4-point α-Ary approximating subdivision scheme for curve designing is introduced for any arity α≥2. The new scheme is extension of B-spline of degree 6. Laurent polynomial method is used to investigate the continuity of the scheme. The variety of effects can be achieved in correspondence for different values of parameter. The applications of the proposed scheme are illustrated in comparison with the established subdivision schemes.

关键词： Approximating Subdivision Scheme Binary Ternary α-Ary Continuity Convergence and Shape Parameters

大气压等离子体射流辅助微铣削Inconel718

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大气压等离子体射流辅助微铣削Inconel718

作者： Ghulam.mustafa 大连理工大学

学位级别：硕士

镍基合金Inconel718因其优异的机械性能,在航空航天和汽车工业等领域被广泛用于制造不同的结构部件,如燃气轮机。但由于Inconel718较高的硬度和高温强度,其可加工性较差。干式加工是加工Inconel718最环保的方法之一。然而,该方法存在热... 详细信息

镍基合金Inconel718因其优异的机械性能,在航空航天和汽车工业等领域被广泛用于制造不同的结构部件,如燃气轮机。但由于Inconel718较高的硬度和高温强度,其可加工性较差。干式加工是加工Inconel718最环保的方法之一。然而,该方法存在热量过高、刀具寿命短、功耗高、表面光洁度差等问题,可通过使用各种切削液解决。除了干式加工,许多非传统加工技术也被开发出来,具有较高的加工性能。冷等离子体辅助加工是一种新的加工技术,在加工过程中采用大气压冷等离子体射流作为外部能场。大气压冷等离子体射流是由气体放电产生,被输送至切削区的材料表面,降低材料力学性能,并对冷却和润滑产生影响。大气压冷等离子体射流辅助微铣削技术可以显著提高切割区的冷却和润滑效果,具有良好的应用前景。本研究工作的目的是研究冷等离子体对微铣削Inconel718过程的影响规律及作用机理;第一部分介绍了等离子体的产生机理和冷等离子体射流的各种方法,研究了冷等离子体射流的各种放电参数对射流各特性的影响。试验发现,当放电形式为裸电极时,放电电压为1.53 kV,氮气流量为12 L/min,喷嘴出口直径为2.5 mm,可获得均匀、稳定和相对较长的冷等离子体射流,冷等离子体射流温度接近室温。为研究冷等离子体射流辅助切削作用机理,采用冷等离子体射流对Inconel718表面进行润湿性改性试验及拉伸试验。结果显示,大气压冷等离子体射流可在短时间内提高金属表面的润湿性,使表面改性为超亲水;同时,冷等离子体射流可有效降低金属材料的断裂强度,为冷等离子体射流辅助Inconel718微铣削改善切削加工性提供了理论依据。在机理研究的基础上,于不同气氛下开展了微铣削试验,比较了各种切削工艺处理的所有加工表面,以及大气压冷等离子体射流对切削力、切削温度、表面粗糙度、表面微观形态和残余应力的影响。分析结果表明,采用大气压冷等离子体射流可降低Inconel718镍合金微铣削过程中的切削力和温度,同时获得更好的表面质量。

关键词：微铣削表面完整性大气压冷等离子体射流 Inconel718

Deep Learning Enabled microarray Gene Expression Classification for Data Science Applications

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Computers, materials & Continua 2022年第11期73卷 4277-4290页

作者： Areej A.malibari Reem m.Alshehri Fahd N.Al-Wesabi Noha Negm mesfer Al Duhayyim Anwer mustafa Hilal Ishfaq Yaseen Abdelwahed motwakel Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

In bioinformatics applications,examination of microarray data has received significant interest to diagnose *** gene expression data can be defined by a massive searching space that poses a primary challenge in the appropriate selection of *** data classification incorporates multiple disciplines such as bioinformatics,machine learning(mL),data science,and pattern *** paper designs an optimal deep neural network based microarray gene expression classification(ODNN-mGEC)model for bioinformatics *** proposed ODNN-mGEC technique performs data normalization process to normalize the data into a uniform ***,improved fruit fly optimization(IFFO)based feature selection technique is used to reduce the high dimensionality in the biomedical ***,deep neural network(DNN)model is applied for the classification of microarray gene expression data and the hyperparameter tuning of the DNN model is carried out using the Symbiotic Organisms Search(SOS)*** utilization of IFFO and SOS algorithms pave the way for accomplishing maximum gene expression classification *** examining the improved outcomes of the ODNN-mGEC technique,a wide ranging experimental analysis is made against benchmark *** extensive comparison study with recent approaches demonstrates the enhanced outcomes of the ODNN-mGEC technique in terms of different measures.

关键词： Bioinformatics data science microarray gene expression data classification deep learning metaheuristics