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ROBO-SPOT:Detecting Robocalls by Understanding User Engagement and Connectivity Graph

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Big Data Mining and Analytics 2024年第2期7卷 340-356页

作者： muhammad Ajmal Azad Junaid Arshad farhan Riaz College of Comnputer Science Birmingham City UniversityBirminghamB55JUUK School of Computer Science University of LincolnLincolnLN67TSUK

Robo or unsolicited calls have become a persistent issue in telecommunication networks,posing significant challenges to individuals,businesses,and regulatory *** calls not only trick users into disclosing their private and financial information,but also affect their productivity through unwanted phone ringing.A proactive approach to identify and block such unsolicited calls is essential to protect users and service providers from potential ***,this paper proposes a solution to identify robo-callers in the telephony network utilising a set of novel features to evaluate the trustworthiness of callers in a *** trust score of the callers is then used along with machine learning models to classify them as legitimate or *** use a large anonymized dataset(call detailed records)from a large telecommunication provider containing more than 1 billion records collected over 10 *** have conducted extensive evaluation demonstrating that the proposed approach achieves high accuracy and detection rate whilst minimizing the error ***,the proposed features when used collectively achieve a true-positive rate of around 97%with a false-positive rate of less than 0.01%.

关键词： social network analysis reputation unwanted calls robo-callers telephone network Spam Over Internet Technology(SPIT)

A Novel Hybrid Ensemble Learning Approach for Enhancing Accuracy and Sustainability in Wind Power Forecasting

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Computers, Materials & Continua 2024年第5期79卷 3373-3395页

作者： farhan Ullah Xuexia Zhang Mansoor Khan muhammad Abid Abdullah Mohamed School of Electrical Engineering Southwest Jiaotong UniversityChengdu611756China College of Intelligent Manufacturing and Control Engineering Qilu Institute of TechnologyJinan250200China College of Aerospace and Civil Engineering Harbin Engineering UniversityHarbin150001China Research Centre Future University in EgyptNew Cairo11835Egypt

Accurate wind power forecasting is critical for system integration and stability as renewable energy reliance *** approaches frequently struggle with complex data and non-linear connections. This article presentsa novel approach for hybrid ensemble learning that is based on rigorous requirements engineering *** approach finds significant parameters influencing forecasting accuracy by evaluating real-time Modern-EraRetrospective Analysis for Research and Applications (MERRA2) data from several European Wind farms usingin-depth stakeholder research and requirements elicitation. Ensemble learning is used to develop a robust model,while a temporal convolutional network handles time-series complexities and data gaps. The ensemble-temporalneural network is enhanced by providing different input parameters including training layers, hidden and dropoutlayers along with activation and loss functions. The proposed framework is further analyzed by comparing stateof-the-art forecasting models in terms of Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE),respectively. The energy efficiency performance indicators showed that the proposed model demonstrates errorreduction percentages of approximately 16.67%, 28.57%, and 81.92% for MAE, and 38.46%, 17.65%, and 90.78%for RMSE for MERRAWind farms 1, 2, and 3, respectively, compared to other existingmethods. These quantitativeresults show the effectiveness of our proposed model with MAE values ranging from 0.0010 to 0.0156 and RMSEvalues ranging from 0.0014 to 0.0174. This work highlights the effectiveness of requirements engineering in windpower forecasting, leading to enhanced forecast accuracy and grid stability, ultimately paving the way for moresustainable energy solutions.

关键词： Ensemble learning machine learning real-time data analysis stakeholder analysis temporal convolutional network wind power forecasting

An Empirical Study on Attention Factors to Massive Open Online Courses

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An Empirical Study on Attention Factors to Massive Open Onli...

作者： muhammad farhan mughal 华中师范大学

学位级别：硕士

随着时代的进步,日新月异的科技不但改变了人们的生活与出行的方式,甚至改变了人们的思考方式。科技的进步不仅体现在各个领域,其对教育与治学方法也影响深远。因此,研究各种科技辅助技术如何提升高校知识传递效益具有重要意义。不管是... 详细信息

随着时代的进步,日新月异的科技不但改变了人们的生活与出行的方式,甚至改变了人们的思考方式。科技的进步不仅体现在各个领域,其对教育与治学方法也影响深远。因此,研究各种科技辅助技术如何提升高校知识传递效益具有重要意义。不管是现在或将来,科技势必对高校带来变革。信息技术的应用对高校教育已带来广泛的影响,这也是为什么需要关注科技如何促进高校教学与改进学习方式的原因。每当论及高教的未来发展趋势时,出于学术潜力与技能的考量,“大规模开放式在线课程”(MOOCs)往往被视为是新一波的教育革命为了研究MOOCs的实践及任何影响其实践的原因,本研究的目的是在技术准备和科技接受模型框架之下,检视学生使用MOOCs系统的动机,并且理解何种因素将影响学生对该系统的接纳。这项研究的主要是要找出能提升个人使用MOOCs意愿的原因。本研究结合技术准备指数模式(TRI)与技术接受模式(TAM),探讨影响MOOCs采用的因素。在TRI和TAM的基础之上,本研究编制了一份包含35个问题的调查问卷,从巴基斯坦的学生群中收集研究数据。本研究的数据样本为237份,并且从中得到了不同的假设。研究模型解释了MOOCs的使用者意向出现很大的差异。结果表明,TRI模型的两个因素,即个人创新和乐观性与MOOCs的认知易用性(PEU)以及认知实用性(PU)呈正相关。另外两个维度,即不安全感和不适感对PEU及PU产生了负面影响。然而,不安全感的负面影响不显著,而不适感对PU与PEU有着更显著的影响。此外,在TAM模式的基本命题下,本研究还肯定PEU对PU有着正面的影响,进而促使PU对使用MOOCs意愿产生积极影响。

关键词：教育科技大规模开放在线课程技术准备技术接受意愿认知实用性认知易用性

Autologous hematopoietic stem cell transplantation conditioning regimens and chimeric antigen receptor T cell therapy in various diseases

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World Journal of Transplantation 2024年第1期14卷 32-41页

作者： Shahzaib Maqbool Maryam farhan Baloch muhammad Abdul Khaliq Khan Azeem Khalid Kiran Naimat Department of Medicine Holy Family HospitalRawalpindi 46000Pakistan Department of Community Medicine Allama Iqbal Medical CollegeLahore 45000Pakistan Department of Community Dentistry Baqai Medical UniversityKarachi 43000Pakistan Department of Medicine Allama lqbal Medical CollegeLahore 45000Pakistan Department of MedicineLiaquat University of Medical and Health Sciences Karachi 43000Pakistan

Conditioning regimens employed in autologous stem cell transplantation have been proven useful in various hematological disorders and underlying malignancies;however,despite being efficacious in various instances,negative consequences have also been *** conditioning regimens were extracted from various literature searches from databases like PubMed,Google scholar,EMBASE,and *** regimens for each disease were compared by using various end points such as overall survival(OS),progression free survival(PFS),and leukemia free survival(LFS).Variables were presented on graphs and analyzed to conclude a more efficacious conditioning *** multiple myeloma,the most effective regimen was high dose melphalan(MEL)given at a dose of 200/mg/*** comparative results of acute myeloid leukemia were presented and the regimens that proved to be at an admirable position were busulfan(BU)+MEL regarding OS and BU+VP16 regarding *** case of acute lymphoblastic leukemia(ALL),BU,fludarabine,and etoposide(BuFluVP)conferred good disease control not only with a paramount improvement in survival rate but also low risk of ***,for ALL,chimeric antigen receptor(CAR)T cell therapy was preferred in the context of better OS and *** respect to Hodgkin’s lymphoma,mitoxantrone(MITO)/MEL overtook carmustine,VP16,cytarabine,and MEL in view of PFS and vice versa regarding ***-Hodgkin’s lymphoma patients were administered MITO(60 mg/m2)and MEL(180 mg/m2)which showed promising ***,amyloidosis was considered,and the regimen that proved to be competent was MEL 200(200 mg/m2).This review article demonstrates a comparison between various conditioning regimens employed in different diseases.

关键词： Conditioning regimens Multiple myeloma Lymphoma Hodgkin Non-Hodgkin Acute leukemia

Plant Nitrogen Metabolism: Balancing Resilience to Nutritional Stress andAbiotic Challenges

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Phyton-International Journal of Experimental Botany 2024年第3期93卷 581-609页

作者： muhammad farhan Manda Sathish Rafia Kiran Aroosa Mushtaq Alaa Baazeem Ammarah Hasnain Fahad Hakim Syed Atif Hasan Naqvi Mustansar Mubeen Yasir Iftikhar Aqleem Abbas muhammad Zeeshan Hassan Mahmoud Moustafa Department of Plant Pathology Faculty of Agricultural Sciences&TechnologyBahauddin Zakariya UniversityMultan60800Pakistan Centro de Investigación de Estudios Avanzados del Maule(CIEAM) Vicerrectoría de Investigación y PostgradoUniversidad Católica del MauleTalca3460000Chile College of Food Science and Nutritional Engineering China Agricultural UniversityBeijingChina Department of Biology College of ScienceTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Biotechnology Faculty of Biological SciencesLahore University of Biological and Applied SciencesLahorePakistan Department of Plant Pathology College of AgricultureUniversity of SargodhaSargodha40100Pakistan Department of Agriculture and Food Technology Karakorum International UniversityGilgitPakistan Department of Biology Faculty of ScienceKing Khalid UniversityAbhaSaudi Arabia

Plant growth and resilience to abiotic stresses,such as soil salinity and drought,depend intricately on nitrogen *** review explores nitrogen’s regulatory role in plant responses to these challenges,unveiling a dynamic interplay between nitrogen availability and abiotic *** the context of soil salinity,a nuanced rela-tionship emerges,featuring both antagonistic and synergistic interactions between salinity and nitrogen ***-induced chlorophyll depletion in plants can be alleviated by optimal nitrogen supplementation;however,excessive nitrogen can exacerbate salinity *** delve into the complexities of this interaction and its agri-cultural ***,a vital element within essential plant structures like chloroplasts,elicits diverse responses based on its *** review comprehensively examines manifestations of nitrogen deﬁciency and toxicity across various crop types,including cereals,vegetables,legumes,and ***,we explore the broader consequences of nitrogen products,such as N_(2)O,NO_(2),and ammonia,on human ***-ing the intricate relationship between nitrogen and salinity,especially chloride accumulation in nitrate-fed plants and sodium buildup in ammonium-fed plants,is pivotal for optimizing crop nitrogen ***,prudent nitrogen use is essential,as overapplication can exacerbate nitrogen-related *** Use Efﬁ-ciency(NUE)is of paramount importance in addressing salinity challenges and enhancing sustainable crop *** this goal requires advancements in crop varieties with efﬁcient nitrogen utilization,pre-cise timing and placement of nitrogen fertilizer application,and thoughtful nitrogen source selection to mitigate losses,particularly urea-based fertilizer *** review article delves into the multifaceted world of plant nitrogen metabolism and its pivotal role in enabling plant resilience to nutritional stress and abiotic chall

关键词： Synthetic nitrogen nitrogen signaling sustainable agriculture eutrophication ammonium nitrate

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3D影像的光谱反射率矫正

3D影像的光谱反射率矫正

Analyzing the Impact of Scene Transitions on Indoor Camera Localization through Scene Change Detection in Real-Time

2015第四届中国印刷与包装学术会议

作者： muhammad farhan mughal 罗明王雨朝徐力豪 muhammad Safdar 中国浙江大学现代光学仪器国家重点实验室英国利兹大学设计学院

近年来,3D影像处理技术在许多场合中被广泛应用,例如医学,动画以及图形传播。把2D影像转换为3D影像存在很多种技术方法。本研究的目的在于通过开发一套程序,从而实现3D影像跨媒体颜色复制的准确颜色复制,以及模拟3D影像在不同光源下的... 详细信息

近年来,3D影像处理技术在许多场合中被广泛应用,例如医学,动画以及图形传播。把2D影像转换为3D影像存在很多种技术方法。本研究的目的在于通过开发一套程序,从而实现3D影像跨媒体颜色复制的准确颜色复制,以及模拟3D影像在不同光源下的色貌。本研究使用一个3dMD系统来抓取3D物体的影像,且实现了基于多项式模型的摄像头特性表征。为了进一步扩大研究范围,本研究通过两种不同的方法主成分分析法(PCA)和Wiener法把不同的3D影像转换为光谱影像。然后,光谱影像被用于转换影像在不同光源下的色貌。最终可以成功实现在显示器上展示3D影像在不同光源下的模拟色貌。

关键词： 3dMD 主成分分析法 Weiner 方法 3D影像光谱反射率

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Intelligent Automation & Soft Computing 2024年第3期39卷 417-436页

作者： muhammad S.Alam farhan B.Mohamed Ali Selamat Faruk Ahmed AKM B.Hossain Department of Emergent Computing School of ComputingUniversiti Teknologi MalaysiaJohor Bahru81310Malaysia Malaysia-Japan International Institute of Technology(MJIIT) Universiti Teknologi MalaysiaKuala Lumpur54100Malaysia Media and Game Innovation Centre of Excellence(MaGICX) Universiti Teknologi MalaysiaJohor Bahru81310Malaysia Department of Engineering Technology University of MemphisMemphisTN38152USA Department of Computer Science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia School of Computing Faculty of EngineeringUniversiti Teknologi MalaysiaJohor Bahru81310Malaysia Department of Information System and Cyber Security College of Computing and Information TechnologyUniversity of BishaBisha61922Saudi Arabia

Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance *** scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and *** research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image *** annotated image dataset trains the proposed system and predicts the camera pose in *** system mainly improved the localization performance of indoor cameras by more accurately predicting the camera *** also recognizes the scene changes during the sequence and evaluates the effects of these *** system achieved high accuracy and real-time *** scene change detection process was performed using visual rhythm and the proposed recurrent deep architecture,which performed camera pose prediction and scene change impact ***,this study proposed a novel real-time localization system for indoor cameras that detects scene changes and shows how they affect localization performance.

关键词： Camera pose estimation indoor camera localization real-time localization scene change detection simultaneous localization and mapping(SLAM)

Status and Social Capital:A Cross-Sectional Quantitative Investigation of Flood Survivors in South Punjab,Pakistan

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International Journal of Disaster Risk Science 2022年第4期13卷 549-560页

作者： muhammad Siddique Akbar muhammad Rizwan Safdar farhan Navid Yousaf Daniel P.Aldrich Institute of Social and Cultural Studies University of the PunjabLahore 054590Pakistan Security and Resilience Studies Program Department of Political ScienceNortheastern UniversityBostonMA 02115USA

A growing body of evidence underscores that social capital mitigates the impact of natural hazards such as *** we know less about the distribution of social ties in developing countries regularly hit by *** study examined the differences between demographic groups in South Punjab,Pakistan affected by the 2010 floods,comparing respondents'levels of social capital measured through proxies such as received social support,perceived community cohesion,accessibility to leadership,and general level of *** carried out univariate and multivariate analyses of factors including gender,education,occupation,landholding,family size,annual income,number of livestock,and home *** data collected in face-to-face interviews with 450 flood survivors,our analysis showed no statistically significant difference in the flood victims'scores on all four scales based on gender and family ***,education,occupation,landholding,annual income,and home stability statistically correlated with levels of social *** with high levels of education,high levels of land,higher home stability,and a government job typically had higher scores in all four measurements of social *** results show strong inequality in the distribution of social capital,with better connections and assistance coming to those who already have better socioeconomic positions in society.

关键词： Flood survivors Pakistan Social capital South Punjab

Data Fusion Architecture Empowered with Deep Learning for Breast Cancer Classification

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Computers, Materials & Continua 2023年第12期77卷 2813-2831页

作者： Sahar Arooj muhammad farhan Khan Tariq Shahzad muhammad Adnan Khan muhammad Umar Nasir muhammad Zubair Atta-ur-Rahman Khmaies Ouahada Faculty of Computing Riphah International UniversityIslamabad45000Pakistan Department of Forensic Sciences University of Health SciencesLahore54000Pakistan Department of Electrical and Electronic Engineering Science University of JohannesburgP.O.Box 524Johannesburg2006South Africa School of Computing Skyline University CollegeUniversity City SharjahSharjah1797United Arab Emirates Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Software Faculty of Artificial Intelligence&SoftwareGachon UniversitySeongnamGyeonggido13120Korea Department of Computer Science Bahria UniversityLahore CampusLahore54000Pakistan Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia

Breast cancer(BC)is the most widespread tumor in females worldwide and is a severe public health *** is the leading reason of death affecting females between the ages of 20 to 59 around the *** detection and therapy can help women receive effective treatment and,as a result,decrease the rate of breast cancer *** cancer tumor develops when cells grow improperly and attack the healthy tissue in the human *** are classified as benign or malignant,and the absence of cancer in the breast is considered *** learning,machine learning,and transfer learning models are applied to detect and identify cancerous tissue like *** research assists in the identification and classification of *** implemented the pre-trained model AlexNet and proposed model Breast cancer identification and classification(BCIC),which are machine learning-based models,by evaluating them in the form of comparative *** used 3 datasets,A,B,and *** fuzzed these datasets and got 2 datasets,A2C and *** A2C is the fusion of A,B,and C with 2 classes categorized as benign and *** B3C is the fusion of datasets A,B,and C with 3 classes classified as benign,malignant,and *** used customized AlexNet according to our datasets and BCIC in our proposed *** achieved an accuracy of 86.5%on Dataset B3C and 76.8%on Dataset A2C by using AlexNet,and we achieved the optimum accuracy of 94.5%on Dataset B3C and 94.9%on Dataset A2C by using proposed model BCIC at 40 epochs with 0.00008 learning *** proposed fuzzed dataset model using transfer *** fuzzed three datasets to get more accurate results and the proposed model achieved the highest prediction accuracy using fuzzed dataset transfer learning technique.

关键词： Breast cancer classification deep learning machine learning transfer learning learning rate