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Telecommunications reforms in Pakistan-lessons and suggestions for China

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China Communications 2007年第2期4卷 106-114页

作者： muhammad khalil shahid Tang Shou-lian School of Economics and Management Beijing University of Posts and TelecommunicationsBeijingChina

The worldwide strategy for the development of telecommunications has been the opening of the telecom sector to competition and private *** paper focuses on telecommunications reforms and its outcomes in Pakistan and discusses some lessons and suggestions for China who is still in the process of formulating telecom *** liberalization and deregulation,telecom industry in Pakistan is tremendously growing and is in a transition phase from the monopoly to the *** policies and independent regulator is playing critical role in this *** paper suggests that speed up formulation of Telecom Law,establishment of independent regulatory and antitrust agencies are need of time for the China telecom ***,China will have to give special attention to accommodate convergence in its coming model of telecommunications reforms.

关键词： Pakistan China reforms telecommunications regulations competition

Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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Computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： khalil Ullah Song Jian muhammad Naeem Ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan Department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman Department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

Correction:Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space

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Computers, Materials & Continua 2025年第1期82卷 1461-1461页

作者： Mudassir khalil muhammad Imran Sharif Ahmed Naeem muhammad Umar Chaudhry Hafiz Tayyab Rauf Adham E.Ragab Department of Computer Engineering Bahauddin Zakariya UniversityMultan60000Pakistan Department of Computer Science Kansas State UniversityManhattanKS 66506USA Department of Computer Science University of Management and TechnologyLahore54000Pakistan Independent Researcher BradfordBD80HSUK Industrial Engineering Department Collage of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia

In the article“Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space”by Mudassir khalil,muhammad Imran Sharif,Ahmed Naeem,muhammad Umar Chaudhry,Hafiz Tayyab Rauf,Adham *** Computers,Materials&Continua,2023,Vol.77,No.2,pp.2031–***:10.32604/cmc.2023.043687,URL:https://***/cmc/v77n2/54831,there was an error regarding the affiliation for the author Hafiz Tayyab *** of“Centre for Smart Systems,AI and Cybersecurity,Staffordshire University,Stoke-on-Trent,ST42DE,UK”,the affiliation should be“Independent Researcher,Bradford,BD80HS,UK”.

关键词： Deep Code CIELAB

Einstein Hybrid Structure of q-Rung Orthopair Fuzzy Soft Set and Its Application for Diagnosis of Waterborne Infectious Disease

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Computer Modeling in Engineering & Sciences 2024年第5期139卷 1863-1892页

作者： Rana muhammad Zulqarnain Hafiz khalil ur Rehman Imran Siddique HijazAhmad Sameh Askar shahid Hussain Gurmani School of Mathematical Sciences Zhejiang Normal UniversityJinhua321004China Department of Mathematics Government College UniversityFaisalabad38000Pakistan Department of Mathematics University of SargodhaSargodha40100Pakistan Section of Mathematics International Telematic University UninettunoCorso Vittorio Emanuele IIRoma3900186Italy Near East University Operational Research Center in HealthcareNear East BoulevardNicosia/Mersin 1099138Turkey Department of Statistics and Operations Research College of ScienceKing Saud UniversityPO Box 2455Riyadh11451Saudi Arabia

This research is devoted to diagnosing water-borne infectious diseases caused by floods employing a novel diagnosis approach,the Einstein hybrid structure of q-rung orthopair fuzzy soft *** approach integrates parts of fuzzy logic and soft set theory to develop a robust alternative for disease detection in stressful situations,especially in areas affected by *** to the traditional intuitionistic fuzzy soft set and Pythagorean fuzzy soft set,the q-rung orthopair fuzzy soft set(q-ROFSS)adequately incorporates unclear and indeterminate *** major objective of this investigation is to formulate the q-rung orthopair fuzzy soft Einstein hybrid weighted average(q-ROFSEHWA)operator and its specific ***,our stated operator is implementing intelligentmulti-criteria group decision-making(MCGDM)*** are severe natural catastrophes that raise the risk of diseases and epidemics,particularly those caused by contaminants in the water,such as gastrointestinal diseases,respiratory infections,vector-borne diseases,skin infections,and water-borne *** designed MCGDM strategy tackles the prevalence of certain conditions in flood-affected patients.A comparative investigation determined that the suggested method for detecting water-borne infectious disease due to floods is more effective and productive than conventional methods because of its logical structure.

关键词： q-rung orthopair fuzzy soft set q-ROFSEHWA operator MCGDM environmental disaster water-born infection disease

Enhancing active reconfigurable intelligent surface

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Intelligent and Converged Networks 2022年第4期3卷 351-363页

作者： muhammad I.khalil School of Electrical and Electronic Engineering University of Royal Melbourne Institute of Technology(RMIT)MelbourneVIC 3000Australia

A Reconfigurable Intelligent Surface(RIS)panel comprises many independent Reflective Elements(REs).One possible way to implement an RIS is to use a binary passive load impedance connected to an antenna element to achieve the modulation of reflected radio *** RE reflects incoming waves(incident signal)by using on/off modulation between two passive loads and adjusting its phase using a Phase Shifter(PS).However,this modulation process reduces the amplitude of the reflected output signal to less than ***,recent RIS works have employed Reflection Amplifiers(RAs)to compensate for the losses incurred during the modulation ***,these systems only improve the reflection coefficient for a single modulation state,resulting in suboptimal RE ***,this paper proposes a strategy for optimising RE by continuously activating the RA regardless of the switching load *** performance of the proposed scheme is evaluated in two scenarios:(1)In the first scenario(Sc1),the RA only operates to compensate for high-impedance loads,and(2)in the second scenario(Sc2),the RA runs continuously regardless of the RE *** benchmark the performance of Sc1 and Sc2,various metrics are compared,including signal-to-noise ratio,insertion loss,noise figure,communication range,and power-added *** examples are provided to demonstrate the effectiveness of the proposed *** is found that the proposed system in Sc2 leads to better overall performance compared to Sc1 due to the increased gain of the RIS reflection.

关键词： reflection amplifiers reflection coefficient phase-shifter Reconfigurable Intelligent Surface(RIS)

Security Threat and Vulnerability Assessment and Measurement in Secure Software Development

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Computers, Materials & Continua 2022年第6期71卷 5039-5059页

作者： Mamoona Humayun NZ Jhanjhi Maram Fahhad Almufareh muhammad Ibrahim khalil Department of Information Systems College of Computer and Information SciencesJouf UniversityAl-JoufKSA School of Computer Science and Engineering(SCE) Taylor’s UniversitySelangorMalaysia Department of Computer Science Bahria UniversityIslamabadPakistan

Security is critical to the success of software,particularly in today’s fast-paced,technology-driven *** ensures that data,code,and services maintain their CIA(Confidentiality,Integrity,and Availability).This is only possible if security is taken into account at all stages of the SDLC(Software Development Life Cycle).Various approaches to software quality have been developed,such as CMMI(Capabilitymaturitymodel integration).However,there exists no explicit solution for incorporating security into all phases of *** of the major causes of pervasive vulnerabilities is a failure to prioritize *** the most proactive companies use the“patch and penetrate”strategy,inwhich security is accessed once the job is *** cost,time overrun,not integrating testing and input in SDLC,usage of third-party tools and components,and lack of knowledge are all reasons for not paying attention to the security angle during the SDLC,despite the fact that secure software development is essential for business continuity and survival in today’s ICT *** is a need to implement best practices in SDLC to address security at all *** fill this gap,we have provided a detailed overview of secure software development practices while taking care of project costs and *** proposed a secure SDLC framework based on the identified practices,which integrates the best security practices in various SDLC phases.A mathematical model is used to validate the proposed framework.A case study and findings show that the proposed system aids in the integration of security best practices into the overall SDLC,resulting in more secure applications.

关键词： Security secure software development software development life cycle(SDLC) confidentiality integrity availability

Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： muhammad Umar Nasir Omar Kassem khalil Karamath Ateeq Bassam SaleemAllah Almogadwy muhammad Adnan Khan muhammad Hasnain Azam Khan muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of Information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of Computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

Ethnobotanical profiling of the medicinal flora of Kotli,Azad Jammu and Kashmir,Pakistan:Empirical reflections on multinomial logit specifications

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Asian Pacific Journal of Tropical Medicine 2017年第5期10卷 478-488页

作者： muhammad Shoaib Amjad muhammad Arshad Abdul Saboor Sue Page Sunbal khalil Chaudhari Department of Botany PMAS-Arid Agriculture University Department of Botany Women University of Azad Jammu & Kashmir Department of Economics PMAS-Arid Agriculture University Department of Geography University of Leicester

Objective:To report the indigenous people's uses of plants from a multidimensional perspective in a remote area where strong ethnobotanical cultural practices prevail. Methods:An ethnobotanical survey was conducted in the field during 2014-2016. Ethnobotanical data were gathered from 182 informants through oral interviews and semi-structured questionnaires. The distribution of plants was explored using both descriptive and graphical methods. Further,a Multinomial Logit Specification was applied to find out the probability of the occurrence of diverse utilization of plants in multipurpose domains. Results:The study identified 202 plant species distributed among 71 families and 156 genera. Ethnobotanical data indicate that there are more medicinal(36.96%) uses of plants as compared to all other use categories. The output from the Multinomial Logit Specifications(MLS) model reveals that perennial and non-woody plants are exploited more for medicinal and food uses than annual and woody plants. In the context of ethnomedicinal uses,aerial plant parts particularly leaves are more extensively used for the preparation of herbal recipes as compared to underground parts. Conclusions:The results of the study emphasize the need to create awareness among the local communities about the conservation status of plant species in order to maintain a sustainable resource of plant-derived materials into the future. The novel econometric approach employed in this study adds a new insightful methodology to the existing body of literature in the field of ethnobotany. We strongly recommend conservation measures,alongside phytochemical and pharmacological studies on the useful plant species identified in this study in order to ensure their sustainable and effective utilization.

关键词： Ethnobotany Medicinal uses Multinomial logit Kotli Azad Kashmir Pakistan

Classifying Misinformation of User Credibility in Social Media Using Supervised Learning

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Computers, Materials & Continua 2023年第5期75卷 2921-2938页

作者： muhammad Asfand-e-Yar Qadeer Hashir Syed Hassan Tanvir Wajeeha khalil Department of Computer Science Center of Excellence in Artificial Intelligence(CoE-AI)Bahria UniversityIslamabad44000Pakistan Department of Computer Science and Information Technology University of Engineering and TechnologyPeshawar25000Pakistan

The growth of the internet and technology has had a significant effect on social *** information has become an important research topic due to the massive amount of misinformed content on social *** is very easy for any user to spread misinformation through the ***,misinformation is a problem for professionals,organizers,and ***,it is essential to observe the credibility and validity of the News articles being shared on social *** core challenge is to distinguish the difference between accurate and false *** studies focus on News article content,such as News titles and descriptions,which has limited their ***,there are two ordinarily agreed-upon features of misinformation:first,the title and text of an article,and second,the user *** the case of the News context,we extracted different user engagements with articles,for example,tweets,i.e.,read-only,user retweets,likes,and *** calculate user credibility and combine it with article content with the user’s *** combining both features,we used three Natural language processing(NLP)feature extraction techniques,i.e.,Term Frequency-Inverse Document Frequency(TF-IDF),Count-Vectorizer(CV),and Hashing-Vectorizer(HV).Then,we applied different machine learning classifiers to classify misinformation as real or ***,we used a Support Vector Machine(SVM),Naive Byes(NB),Random Forest(RF),Decision Tree(DT),Gradient Boosting(GB),and K-Nearest Neighbors(KNN).The proposed method has been tested on a real-world dataset,i.e.,“fakenewsnet”.We refine the fakenewsnet dataset repository according to our required *** dataset contains 23000+articles with millions of user *** highest accuracy score is 93.4%.The proposed model achieves its highest accuracy using count vector features and a random forest *** discoveries confirmed that the proposed classifier would effectively classify misinformat

关键词： Misinformation user credibility fake news machine learning