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1st Mohammad Ali Jinnah university International Conference on Computing, MAJICC 2021

作者： Waheed, Tabassum Aqeel-Ur-Rehman Shaikh, Faisal Karim Hamdard University Dept. of Computer Engineering Karachi Pakistan Sir Syed University of Engineering Technology Dept. of Software Engineering Karachi Pakistan Mehran University of Engieneering Technology Dept. of Telecommmunication Engineering Jamshoro Pakistan

ISBN: (纸本)9781665424134

During the recent COVID-19 pandemic, Medical Body area networks (MBANs) emerged as an essential tool for the early diagnosis and treatment of infected patients. MBANs played an instrumental role in the remote treatment of COVID patients through early diagnosis using machine learning and IoT (Internet of Things). MBANs have paved their way in the health care industry and are being used in remote monitoring, emergency handling, and elderly assistance. The availability of the IEEE 802.15.6 standard has opened doors for new wearable consumer devices and IoMT (Internet of Medical Things) enabled applications to facilitate disease management. This standard was developed for wireless communication at a short-range, around the human body with low power requirements. This standard allows 2hop star topology within an intra-MBAN so that when direct communication is not possible, alternate routes are available through relays. This paper proposes a protocol for an intra-MBAN topology, which is a novel T-Relay mechanism that implements the 2-hop star topology. To validate the proposed protocol, it was tested on OMNeT ++ framework with Castalia Simulator for various scenarios. The simulation results show that the T-Relay mechanism enhances the PDR when the channel has variations. © 2021 IEEE.

关键词： Wireless local area networks (WLAN)

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Wireless sensor network (WSN) based early flood warning system

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International Journal of Information technology (Singapore) 2020年第2期12卷 567-570页

作者： Siddique, Ali Akbar Qadri, M. Tahir Department of Telecommunication Engineering Sir Syed University of Engineering and Technology Karachi Pakistan Department of Electronics Engineering Sir Syed University of Engineering and Technology Karachi Pakistan

Water is one of the most essential and necessary element that we require in our daily life, although it may become life threatening for the people living near to the river bank. In many cities of Pakistan, controlling the flood situation is a major problem. Due to the poor management and lack of dams, the chances of flood may increase exponentially. First priority is to save the lives of the people living close to the river bank, hence technology can play an important role in this regard to solve this problem at some extent. In this paper, a Wireless sensor network (WSN) based system is proposed to warn the nearby villages about the impending flood situation so they may take precautionary step to save their lives. Four nodes are introduced for four different river locations to constantly monitor the flow and the level of the river water. These four nodes will deliver their information to a master node holding all the necessary information and will generate a warning in case of flood. © 2018, Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Arduino MEGA 2560 Flow sensors Wireless sensor node (WSN)

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Mechanical and environmental performance evaluation of meta-kaolin and silica fume-modified steel fiber embedded concrete: A sustainable construction

Environmental Challenges

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Environmental Challenges 2025年 19卷

作者： Zada, Nawab Sameer Shafiq, Nasir Khan, Muhammad Basit Imran, Muhammad Department of Civil and Environmental Engineering Universiti Teknologi PETRONAS Bandar Seri Iskandar Perak Tronoh 32610 Malaysia Sir Syed University of Engineering and Technology Karachi Pakistan

In this experimental study, mechanical strength, and environmental characteristics of concrete were evaluated. Concrete was prepared by replacing cement with green cementitious material silica fume and meta-kaolin, Additionally, concrete is blended with steel fiber as a means to enhance the concrete characteristics. Response surface methodology was employed for designing the series of experiment and proportions. Two models were constructed in RSM separately, one model consists of meta-kaolin (MK) and steel fiber, while other consists of silica fume (SF) and steel fiber. Findings of both models were compared to each other to study the effects of SF and MK on concrete through the addition of steel fiber. Concrete was tested for compressive strength (CS), split tensile strength (STS), FS (FS), modulus of elasticity (MoE), ultra-sonic pulse velocity (UPV) and symbolized carbon (EC) with eco-strength efficiency (ESE) remained likewise estimated. As per the investigation, it was concluded that addition of 10 % MK with 1 % steel fiber in concrete offers the extreme mechanical strength among the mixes containing MK as a cementitious replacement material and concrete containing 10 % of SF with 1 % of steel fiber exhibits the maximum mechanical strengths among the proportions containing SF in concrete. It was found that concrete containing SF exhibit higher mechanical strength in comparison to concrete in which MK is used as cement supplementary material. Concrete containing 10 % MK or SF reinforced with 1 % steel fiber has the highest ESE. Concrete containing 10 % MK and 1 % steel fiber increases CS, STS, FS and MOE by 14 %, 7.29 %, 8 % and 7.29 % respectively. While concrete mixes containing 10 % SF and 1 % steel fiber enhances the CS, STS, FS and MOE by 19.11 %, 17.23 %, 10 % and 10.06 % respectively in comparison to control mix. Finally, Statistical equations were developed for anticipating the value of each response by using independent variables (MK, SF and steel fiber)

关键词： Mechanical strength Meta-kaolin RSM Silica fume Steel fiber Sustainable concrete

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Rain Predictive Model using Machine learning Techniques

Rain Predictive Model using Machine learning Techniques

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Multi-disciplinary Conference in Emerging Research Trends (IMCERT), International

作者： Muhammad Shahbaz Muneer syed Muhammad Nabeel Mustafa syeda Sundus Zehra Haniya Maqsood Dpertment of Computational Finance NED University of Engineering and Technology Karachi Pakistan Dept. of Computer Science & I.T NED University of Engineering and Technology Karachi Pakistan Dept. of Software Engineering Sir Syed Uuniversity of Engineering and Technology Karachi Pakistan Department of Computer and Information Systems Engineering NED University of Engineering and Technology Karachi Pakistan

Climate is rapidly changing around the world. Over time, there have been significant changes in the weather. Rainfall is now erratic due to climate change. The frequency of extreme weather events like droughts and floods has increased due to climate change, necessitating the need for more precise and timely rainfall forecasts. For strategic reasons including agriculture, water resource management, and architectural design, rain forecasting is crucial. The naturally occurring non-stationary component in the rainfall time series impairs model performance for practical hydrologists and drought risk assessors. We present a rain predicting model based on machine learning to address the forecasting issue. In our work, we predict the possibility of rain the next day on the basis of last 10 years' data. The variables that were calculated during the experiments were humidity, pressure, evaporation, sunshine, rainfall, and so on. Random Forest gave the 90% accuracy with 0.904 Area under Curve, highest out of all the algorithms. The model's performance will significantly aid in the rain forecast.

关键词： Climate change Rain Machine learning algorithms Droughts Weather forecasting Predictive models Prediction algorithms

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An experimental study on early age compression and shear strength properties of mixed clay soil

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Arabian Journal of Geosciences 2024年第2期17卷 1-14页

作者： Abbas, Azhar Akbar, Muhammad Huali, Pan Zar, Ali Ramzan, Samar Hussain, Zahoor Department of Geotechnical Engineering Tongji University Shanghai China Institute of Mountain Hazards and Environment Chinese Academy of Sciences Chengdu China Sir Syed University of Engineering & Technology Karachi Pakistan Key Lab of Structures Dynamic Behavior and Control of the Ministry of Education Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of Technology Harbin China Department of Civil Engineering University of Engineering and Technology Lahore Lahore Pakistan Zhengzhou University Zhengzhou China

Clay mixed soil is a combination of clay and soil components that may be used as the core of earth dams and the foundation for building and road construction. Up until now, significant research work has been carried out to design cement-based clay materials; however, only a couple of studies have been reported in the literature on earth-based materials. The methodology portion provides an overview of the different materials, tools, and protocols used during work to develop ways to earth-based materials and study their early age compression strength along with their shear strength. Finally, it summarizes all the results and the outcome of the experimental work done. The probability of producing an object using earth-based material was examined. Improvement in the compressive strength in the early age of strength by adding additives like bentonite and rice husk was assessed in this study. Three clayey soil samples were investigated. The undrained shear strength based on an unconfined compression test (UCT) over those samples was measured by varying the moisture content (MC). After performing all these tests, a relationship was developed between the UCT and vane shear test (VST) undrained shear strengths of the selected soil samples. Clay samples with different mix designs were investigated, and building components were printed out to check the early age shear strength development and printable properties of different mix designs. This study will lay the foundation for further research on different aspects relating to the emerging technology of 3D clay printing in Pakistan.

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Disease Diagnosis System Using IoT Empowered with Fuzzy Inference System

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Computers, Materials & Continua 2022年第3期70卷 5305-5319页

作者： Talha Mahboob Alam Kamran Shaukat Adel Khelifi Wasim Ahmad Khan Hafiz Muhammad Ehtisham Raza Muhammad Idrees Suhuai Luo Ibrahim A.Hameed Department of Computer Science and Information Technology Virtual University of PakistanLahorePakistan School of Information and Physical Sciences The University of NewcastleAustralia Department of Computer Science and Information Technology Abu Dhabi UniversityAbu DhabiUnited Arab Emirates School of Computer Science National College of Business Administration&EconomicsLahorePakistan Sir Syed College of Computer Science University of Engineering and TechnologyLahorePakistan Department of Data Science University of the PunjabLahorePakistan Department of ICT and Natural Sciences Norwegian University of Science and TechnologyTrondheimNorway

Disease diagnosis is a challenging task due to a large number of associated *** in the diagnosis process arises frominaccuracy in patient attributes,missing data,and limitation in the medical expert’s ability to define cause and effect relationships when there are multiple interrelated *** paper aims to demonstrate an integrated view of deploying smart disease diagnosis using the Internet of Things(IoT)empowered by the fuzzy inference system(FIS)to diagnose various *** Fuzzy Systemis one of the best systems to diagnose medical conditions because every disease diagnosis involves many uncertainties,and fuzzy logic is the best way to handle *** proposed system differentiates new cases provided symptoms of the ***,it becomes a time-sensitive task to discriminate symptomatic *** proposed system can track symptoms firmly to diagnose diseases through IoT and FIS smartly and *** coefficients have been employed to predict and compute the identified disease’s severity for each sign of *** study aims to differentiate and diagnose COVID-19,Typhoid,Malaria,and *** study used the FIS method to figure out the disease over the use of given data related to correlating with input *** tool is utilised for the implementation of *** procedure on the aforementioned given data presents that affectionate disease can derive from the *** results of our proposed method proved that FIS could be utilised for the diagnosis of other *** study may assist doctors,patients,medical practitioners,and other healthcare professionals in early diagnosis and better treat diseases.

关键词： Disease diagnosis system COVID-19 healthcare biomedical rules extraction

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A Computer Vision-Based System for Recognition and Classification of Urdu Sign Language Dataset for Differently Abled People Using Artificial Intelligence

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Mobile Information Systems 2023年第1期2023卷

作者： Zahid, Hira syed, Sidra Abid Rashid, Munaf Hussain, Samreen Umer, Asif Waheed, Abdul Nasim, Shahzad Zareei, Mahdi Mansoor, Nafees Biomedical Engineering Department and Electrical Engineering Department Ziauddin University Karachi74600 Pakistan Biomedical Engineering Department Sir Syed University of Engineering and Technology Karachi75300 Pakistan Software Engineering Department Sir Syed University of Engineering and Technology Karachi74600 Pakistan Electronic Engineering Department Dawood University of Engineering & Technology Karachi74800 Pakistan Department of Computer Science & IT Hazara University Mansehra23100 Pakistan Department of Computer Science Women University Swabi Swabi23430 Pakistan School of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Begum Nusrat Bhutto Women University Faculty of Management Information Science and Technology Sukkur Pakistan Tecnologico de Monterrey School of Engineering and Sciences Monterrey64849 Mexico Dhaka Bangladesh

Communication between normal people and deaf people is the most difficult part of daily life worldwide. It is difficult for a normal person to understand a word from the deaf one in their daily routine. So, to communicate with deaf people, different countries developed different sign languages to make communication easy. In Pakistan, for deaf people, the government developed Urdu Sign Language to communicate with deaf people. Physical trainers and experts are difficult to provide everywhere in society, so we need such a computer/mobile-based system to convert the deaf sign symbol into voice and written alphabet that the normal person can easily get the intentions of the deaf one. In this paper, we provided an image processing and deep learning-based model for Urdu Sign Language. The proposed model is implemented in Python 3 and uses different image processing and machine techniques to capture the video and transform the symbols into voice and Urdu writing. First, we get a video from the deaf person, and then the model crops the frames into pictures. Then, the individual picture is recognized for the sign symbol such as if the deaf showed a symbol for one, then the model recognizes it and shows the letter which he/she wants to tell. Image processing techniques such as OpenCV are used for image recognition and classification while TensorFlow and linear regression are used for training the model to behave intelligently in the future. The results show that the proposed model increased accuracy from 80% to 97% and 100% accordingly. The accuracy of the previously available work was 80% when we implemented the algorithms, while with the proposed algorithm, when we used linear regression, we achieved the highest accuracy. Similarly, when we used the TensorFlow deep learning algorithm, we achieved 97% accuracy which was less than that of the linear regression model. © 2023 Hira Zahid et al.

关键词： Image recognition

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Fuzzy Logic Enabled Stress Detection Using Physiological Signals 4th

Fuzzy Logic Enabled Stress Detection Using Physiological Sig...

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4th International Conference on Emerging Technologies in Computing, iCEtiC 2021

作者： Naqvi, Shabbar Shaikh, Aamir Zeb Altaf, Talat Singh, Saurabh Department of Computer Systems Engineering Balochistan University of Engineering and Technology Khuzdar Pakistan Department of Electronic Engineering NED University of Engineering and Technology Karachi Karachi Pakistan Department of Electrical Engineering Sir Syed University of Engineering and Technology Karachi Pakistan Department of Industrial and Systems Engineering Dongguk University Seoul Seoul Korea Republic of

ISBN: (纸本)9783030900151

Stress is attributed as the natural response of body towards unwanted and challenging conditions of society and environment. The consequences of stress are in general very harmful. However, in some specific situations, stress can be highly serious to the human health as it impacts the cardiovascular system in addition to other body sub systems. Timely Detection of stress through physiological sensors may help in arresting the disease. As the stress results in change of heart rate, skin conduction, temperature, blood pressure and oxygen levels, hence, measurement and assessment of these parameters is useful in deciding the stress levels into a candidate. In this paper, a fuzzy logic based automatic stress detection system is designed to timely detect the patients passing through this silent killer disease. The physiological signals of human body are used to assess the current state of person. The parameters used for the purpose are heart rate, Galvanic Skin Response (GSR), and temperature. The fuzzy logic is an exciting branch of artificial intelligence that is used to make useful decisions under uncertain and incomplete input knowledge. A synthetic data set of 500 patients is also developed to train and test the proposed architecture. The algorithms used for this purpose are Hill Climbing (HC) and Simulated Annealing (SA) for fuzzy membership functions training. The results show that Simulated Annealing gives a testing accuracy of 89% in comparison to Hill climbing with 81% accuracy. Future work is directed towards using new methods like type-2 fuzzy logic and deep learning etc. © 2021, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Fuzzy logic

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Leveraging Big Data for Effective Healthcare Management with Artificial Intelligence 1

Leveraging Big Data for Effective Healthcare Management with...

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1st International Conference on Artificial Intelligence for Innovations in Healthcare Industries, ICAIIHI 2023

作者： Dubey, Krati Kasar, Chaitali B. Thulluri, Guravaiah Yesugad, Anuradha Karishma, Mehaboob Padhi, Dipanjali Manipal University Jaipur Department of Information Technology Jaipur India Dr. D. Y. Patil Institute of Technology Department of Electronics and Telecommunication Engineering Pune411018 India Embedded Senior Software Developer Sak Informatics Hyderabad India Pune India Sir C R R College Department of Computer Application Eluru India Dhole Patil College of Engineering Department of Electronics & Telecommunication Engineering Pune India

ISBN: (纸本)9798350330915

To improve clinical judgment, resource allocation, and patient outcomes, this study investigates the integration of big data with artificial intelligence (AI) for medical management. Utilizing a descriptive design with an emphasis on secondary data collecting, the study adopts an interpretive perspective and a deductive approach. Data collection, AI algorithm implementation, integration into the system, and infrastructure issues are all included in the technical setup. Accuracy, sensitivity, quickness of processing, and scalability are examples of performance measures, and the influence on patients and healthcare providers is highlighted by user viewpoints and experiences. Informed permission, data security, and legal compliance are all included in the ethical considerations. The results highlight the potential advantages of data-driven medical services, but they also highlight how crucial ethical precautions and user acceptance are. Upcoming studies ought to concentrate on improving algorithms, protecting privacy, and evaluating long-term effects © 2023 IEEE.

关键词： artificial intelligence big data clinical decision support ethical considerations healthcare management

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Emergence of Advanced Multi-Terminal HVDC Transmission Systems and DC Grids 6

Emergence of Advanced Multi-Terminal HVDC Transmission Syste...

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6th International Multi-Topic ICT Conference, IMTIC 2021

作者： Ud Din, Ghulam Muhay Husain, Nusrat Arfeen, Zeeshan Ahmad Yahya, Ashraf Iqbal, Najeeb Shaukat, Fawad Electronics Power Engineering Department Islamabad Pakistan Universiti Teknologi Malaysia The Islamia University of Bahawalpur School of Electrical Engineering Bahawalpur Pakistan Sir Syed University of Engineering and Technology Electrical Engineering Department Karachi Pakistan

ISBN: (纸本)9781665482943

The transfer of bulk electrical power over long distances can be done by high voltage alternating current (HV AC) transmission systems. These HV AC power transmission systems have their perfections and imperfections. To enhance the existing power transmission systems, high voltage direct current (HVDC) power transmission systems are a sustainable solution. The emergence of advanced HVDC systems is so rapid that they are replacing their counterpart HV AC systems in many parts of the world. In this paper, the prominence of modern HVDC power transmission systems is highlighted. The topologies, converter assortments, contrasts, and modeling methods are discussed. The renewable energy sources (RES) including solar photovoltaic (PV) parks and mainland/ onshore/ offshore wind farms can be assimilated into the existing AC grids via advanced HVDC converters. The perceptions of multi-terminal HVDC systems and DC grids are presented, whereas, the challenges concomitant with the future DC grids are also emphasized. © 2021 IEEE.

关键词： Electric power transmission networks

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