Pub Date : 2023-01-09DOI: 10.54692/lgurjcsit.2023.0701316
Sharoon Nasim, Zainab Zahid, Nosheen Sabahat
—This paper is the outcome of the research conductedto investigate the affective requirement engineering techniquesproposed and used for developing software projects. We haveassessed traditional methods and proposed an approach thatcovers various aspects for generating a successful project. AnNLP-based model is designed that takes input from the user andgives the output in the form of a text document after processingit. We have set a 62% similarity index to achieve the maximumrequirements of the required system. These requirements, inreturn, help the developers to develop the product with morefunctionality and productivity.
{"title":"Requirement Elicitation using Natural Language Processing","authors":"Sharoon Nasim, Zainab Zahid, Nosheen Sabahat","doi":"10.54692/lgurjcsit.2023.0701316","DOIUrl":"https://doi.org/10.54692/lgurjcsit.2023.0701316","url":null,"abstract":"—This paper is the outcome of the research conductedto investigate the affective requirement engineering techniquesproposed and used for developing software projects. We haveassessed traditional methods and proposed an approach thatcovers various aspects for generating a successful project. AnNLP-based model is designed that takes input from the user andgives the output in the form of a text document after processingit. We have set a 62% similarity index to achieve the maximumrequirements of the required system. These requirements, inreturn, help the developers to develop the product with morefunctionality and productivity.","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126944653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-15DOI: 10.54692/lgurjcsit.2022.0604359
Muhammad Waheed ul Hassan, Engr. Dr. Muhammad Farhan, Z. Ahmed, Toseef Abid, Muhammad Azeem Iqbal, Muhammad Saqib Ashraf
A microgrid is widely accepted as a prominent solution to enhance resilience and performance in distributed power systems. Microgrids are flexible for adding distributed energy resources in the ecosystem of the electrical networks. Control techniques are used to synchronize distributed energy resources (DERs) due to their turbulent nature. DERs including alternating current, direct current and hybrid load with storage systems have been used in microgrids quite frequently due to which controlling the flow of energy in microgrids have been complex task with traditional control approaches. Distributed as well central approach to apply control algorithms is well-known methods to regulate frequency and voltage in microgrids. Recently techniques based of artificial intelligence are being applied for the problems that arise in operation and control of latest generation microgrids and smart grids. Such techniques are categorized in machine learning and deep learning in broader terms. The objective of this research is to survey the latest strategies of control in microgrids using the deep reinforcement learning approach (DRL). Other techniques of artificial intelligence had already been reviewed extensively but the use of DRL has increased in the past couple of years. To bridge the gap for the researchers, this survey paper is being presented with a focus on only Microgrids control DRL techniques for voltage control and frequency regulation with distributed, cooperative and multi agent approaches are presented in this research.
{"title":"Deep Reinforcement Learning for Control of Microgrids: A Review","authors":"Muhammad Waheed ul Hassan, Engr. Dr. Muhammad Farhan, Z. Ahmed, Toseef Abid, Muhammad Azeem Iqbal, Muhammad Saqib Ashraf","doi":"10.54692/lgurjcsit.2022.0604359","DOIUrl":"https://doi.org/10.54692/lgurjcsit.2022.0604359","url":null,"abstract":"A microgrid is widely accepted as a prominent solution to enhance resilience and performance in distributed power systems. Microgrids are flexible for adding distributed energy resources in the ecosystem of the electrical networks. Control techniques are used to synchronize distributed energy resources (DERs) due to their turbulent nature. DERs including alternating current, direct current and hybrid load with storage systems have been used in microgrids quite frequently due to which controlling the flow of energy in microgrids have been complex task with traditional control approaches. Distributed as well central approach to apply control algorithms is well-known methods to regulate frequency and voltage in microgrids. Recently techniques based of artificial intelligence are being applied for the problems that arise in operation and control of latest generation microgrids and smart grids. Such techniques are categorized in machine learning and deep learning in broader terms. The objective of this research is to survey the latest strategies of control in microgrids using the deep reinforcement learning approach (DRL). Other techniques of artificial intelligence had already been reviewed extensively but the use of DRL has increased in the past couple of years. To bridge the gap for the researchers, this survey paper is being presented with a focus on only Microgrids control DRL techniques for voltage control and frequency regulation with distributed, cooperative and multi agent approaches are presented in this research.","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127638083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-04DOI: 10.54692/lgurjcsit.2022.0604402
Dr. Ejaz Sandhu
The worldwide mechanical advancement in medical services digitizes the copious information, empowering the guide of the different types of human science all the more precisely than conventional estimating strategies. AI (ML) has been certified as a productive approach for dissecting the enormous measure of information in the medical services area. ML strategies are being used in emotional well-being to anticipate the probabilities of mental problems and, subsequently, execute potential treatment results. In the speedy present-day world, mental medical problems like depression and anxiety have become exceptionally normal among the majority. In this paper, forecasts of depression and anxieties were made utilizing AI calculations. Depression and anxiety have become emergent hindrances in the lives of human beings. It not only disturbs their daily decorum but has also become a prominent cause for their downfall in health. All around the world people are getting affected by this mental disorder yet the majority of such cases lie between ages 18-25 making university-going students a prime target for such mental diseases. Though the mental health of university students is known globally as a momentous public health matter. Academicals, social depression, and anxieties are playing quite a negative role in university student’s life, especially in forms of mental illness like depression and anxiety. These mental health issues are becoming a major constraint on their studies and career. Hence, this research is being conducted to develop a technological solution for mentally distorted students. This paper analyzes depression and anxiety amongst university students by effectively utilizing the k-nn algorithm (a conspicuous technique for detecting and analyzing mental depression and anxiety) and providing a technical solution for this mental hindrance. The experimental results show up to 76.5% accuracy in results after using k-nn without PCA while the accuracy was increased up to 76.6% when the results were generated with PCA.
{"title":"COMPUTE DEPRESSION AND ANXIETY AMONG STUDENTS IN PAKISTAN, USING MACHINE LEARNING","authors":"Dr. Ejaz Sandhu","doi":"10.54692/lgurjcsit.2022.0604402","DOIUrl":"https://doi.org/10.54692/lgurjcsit.2022.0604402","url":null,"abstract":"The worldwide mechanical advancement in medical services digitizes the copious information, empowering the guide of the different types of human science all the more precisely than conventional estimating strategies. AI (ML) has been certified as a productive approach for dissecting the enormous measure of information in the medical services area. ML strategies are being used in emotional well-being to anticipate the probabilities of mental problems and, subsequently, execute potential treatment results. \u0000In the speedy present-day world, mental medical problems like depression and anxiety have become exceptionally normal among the majority. In this paper, forecasts of depression and anxieties were made utilizing AI calculations. Depression and anxiety have become emergent hindrances in the lives of human beings. It not only disturbs their daily decorum but has also become a prominent cause for their downfall in health. All around the world people are getting affected by this mental disorder yet the majority of such cases lie between ages 18-25 making university-going students a prime target for such mental diseases. \u0000Though the mental health of university students is known globally as a momentous public health matter. Academicals, social depression, and anxieties are playing quite a negative role in university student’s life, especially in forms of mental illness like depression and anxiety. These mental health issues are becoming a major constraint on their studies and career. Hence, this research is being conducted to develop a technological solution for mentally distorted students. \u0000This paper analyzes depression and anxiety amongst university students by effectively utilizing the k-nn algorithm (a conspicuous technique for detecting and analyzing mental depression and anxiety) and providing a technical solution for this mental hindrance. The experimental results show up to 76.5% accuracy in results after using k-nn without PCA while the accuracy was increased up to 76.6% when the results were generated with PCA.","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115194505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-27DOI: 10.54692/lgurjcsit.2022.0604399
D. M. U. Ashraf
In a retail industry, sales forecasting is an important part related to supply chain management and operations between the retailer and manufacturers. The abundant growth of the digital data has minimized the traditional system and approaches to do a specific task. Sales forecasting is the most challenging task for the inventory management, marketing, customer service and Business financial planning for the retail industry. In this paper we performed predictive analysis of retail sales of Citadel POS dataset, using different machine learning techniques. We implemented different regression (Linear regression, Random Forest Regression, Gradient Boosting Regression) and time series models (ARIMA LSTM), models for sale forecasting, and provided detailed predictive analysis and evaluation. The dataset used in this research work is obtained from Citadel POS (Point Of Sale) from 2013 to 2018 that is a cloud base application and facilitates retail store to carryout transactions, manage inventories, customers, vendors, view reports, manage sales, and tender data locally. The results show that Xgboost outperformed time series and other regression models and achieved best performance with MAE of 0.516 and RMSE of 0.63.
在零售业中，销售预测是供应链管理和零售商与制造商之间运作的重要组成部分。数字数据的大量增长使传统的系统和方法最小化，以完成特定的任务。销售预测是零售行业库存管理、市场营销、客户服务和商业财务规划中最具挑战性的任务。在本文中，我们使用不同的机器学习技术对Citadel POS数据集的零售额进行了预测分析。采用不同的回归(线性回归、随机森林回归、梯度增强回归)和时间序列模型(ARIMA LSTM)进行销售预测，并进行详细的预测分析和评价。本研究使用的数据集来自Citadel POS (Point Of Sale) 2013年至2018年的数据集，该数据集是一个云基础应用程序，可帮助零售商店在本地进行交易、管理库存、客户、供应商、查看报告、管理销售和招标数据。结果表明，Xgboost优于时间序列和其他回归模型，MAE为0.516,RMSE为0.63，达到最佳性能。
{"title":"A Predictive Analysis of Retail Sales Forecasting using Machine Learning Techniques","authors":"D. M. U. Ashraf","doi":"10.54692/lgurjcsit.2022.0604399","DOIUrl":"https://doi.org/10.54692/lgurjcsit.2022.0604399","url":null,"abstract":"In a retail industry, sales forecasting is an important part related to supply chain management and operations between the retailer and manufacturers. The abundant growth of the digital data has minimized the traditional system and approaches to do a specific task. Sales forecasting is the most challenging task for the inventory management, marketing, customer service and Business financial planning for the retail industry. In this paper we performed predictive analysis of retail sales of Citadel POS dataset, using different machine learning techniques. We implemented different regression (Linear regression, Random Forest Regression, Gradient Boosting Regression) and time series models (ARIMA LSTM), models for sale forecasting, and provided detailed predictive analysis and evaluation. The dataset used in this research work is obtained from Citadel POS (Point Of Sale) from 2013 to 2018 that is a cloud base application and facilitates retail store to carryout transactions, manage inventories, customers, vendors, view reports, manage sales, and tender data locally. The results show that Xgboost outperformed time series and other regression models and achieved best performance with MAE of 0.516 and RMSE of 0.63.","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133614471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-03DOI: 10.54692/lgurjcsit.2022.0604383
Hana Sharif, Faisal Rehman, Naveed Riaz, Awais Salman Qazi, Rana Mohtasham Aftab, M. Hussain
Tuberculosis is one of the most dangerous health conditions on the globe. As it affects the human body, tuberculosis is an infectious illness. According to the World Health Organization, roughly 1.7 million individuals get TB throughout the course of their lifetimes. Pakistan ranks fifth among high-burden nations and is responsible for 61% of the TB burden within the WHO Eastern Mediterranean Region. Various methods and procedures exist for the early identification of TB. However, all methods and techniques have their limits. The bulk of currently known approaches for detecting TB rely on model-based segmentation of the lung. The primary purpose of the proposed study is to identify pulmonary TB utilising chest X-ray (Poster Anterior) lung pictures processed using image processing and machine learning methods. The recommended study introduces a unique model segmentation strategy for TB identification. For classification, CNN, Google Net, and other systems based on deep learning are used. On merged datasets, the best accuracy attained by the suggested method utilising Google Net was 89.58 percent. The recommended study will aid in the detection and accurate diagnosis of TB.
{"title":"Deep learning to predict Pulmonary Tuberculosis from Lung Posterior Chest Radiographs","authors":"Hana Sharif, Faisal Rehman, Naveed Riaz, Awais Salman Qazi, Rana Mohtasham Aftab, M. Hussain","doi":"10.54692/lgurjcsit.2022.0604383","DOIUrl":"https://doi.org/10.54692/lgurjcsit.2022.0604383","url":null,"abstract":"Tuberculosis is one of the most dangerous health conditions on the globe. As it affects the human body, tuberculosis is an infectious illness. According to the World Health Organization, roughly 1.7 million individuals get TB throughout the course of their lifetimes. Pakistan ranks fifth among high-burden nations and is responsible for 61% of the TB burden within the WHO Eastern Mediterranean Region. Various methods and procedures exist for the early identification of TB. However, all methods and techniques have their limits. The bulk of currently known approaches for detecting TB rely on model-based segmentation of the lung. The primary purpose of the proposed study is to identify pulmonary TB utilising chest X-ray (Poster Anterior) lung pictures processed using image processing and machine learning methods. The recommended study introduces a unique model segmentation strategy for TB identification. For classification, CNN, Google Net, and other systems based on deep learning are used. On merged datasets, the best accuracy attained by the suggested method utilising Google Net was 89.58 percent. The recommended study will aid in the detection and accurate diagnosis of TB. ","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122755939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-15DOI: 10.54692/lgurjcsit.2022.0604375
Atif Alvi
Google Maps is becoming popular in digital maps because of its user friendly human computerinteraction and easy to use Application Programming Interface (API) as a plugin to onlineapplications. Vehicular Ad-hoc Network (VANET) is conceptualizing moving cars as nodes ina dynamic road network. VANETs help manage the traffic through communication messagesamong the vehicles. In huge traffic loads too many messages create network congestion andstarvation. The basic objective of this research is to augment conventional VANET by addingmessage prioritization methodology, i.e. messages for top priority vehicles will be transmittedprior to the ones with lower priority. To this end, an algorithm has been developed andimplemented in a web application that incorporates Google maps for getting and displayingvehicle information. The proposed algorithm has been evaluated using experiments forthroughput and congestion avoidance in the network.
{"title":"Priority Based Technique and Vehicle Location in VANET Using Google Maps","authors":"Atif Alvi","doi":"10.54692/lgurjcsit.2022.0604375","DOIUrl":"https://doi.org/10.54692/lgurjcsit.2022.0604375","url":null,"abstract":"Google Maps is becoming popular in digital maps because of its user friendly human computerinteraction and easy to use Application Programming Interface (API) as a plugin to onlineapplications. Vehicular Ad-hoc Network (VANET) is conceptualizing moving cars as nodes ina dynamic road network. VANETs help manage the traffic through communication messagesamong the vehicles. In huge traffic loads too many messages create network congestion andstarvation. The basic objective of this research is to augment conventional VANET by addingmessage prioritization methodology, i.e. messages for top priority vehicles will be transmittedprior to the ones with lower priority. To this end, an algorithm has been developed andimplemented in a web application that incorporates Google maps for getting and displayingvehicle information. The proposed algorithm has been evaluated using experiments forthroughput and congestion avoidance in the network.","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123252691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-01DOI: 10.54692/lgurjcsit.2022.0604314
Ayesha Abubakar, Sidra Minhas
Every technology with its powerful uses has issues connected to it and security is at the top of it. As for the changing environment, the world has been shifting to Virtual Reality, the new coming world seems to be the internet and blockchain technology which is more powerful than others and has its applications in every field, be it quantum computing, internet of things, security or others. This survey paper covers the blockchain and its security in different fields of sciences and technology. We begin with the introduction of blockchain and then discuss its structure. After that security issues have been highlighted which include attacks and their behavior in quantum computing, internet of things, cloud computing. Furthermore, we have discussed the most common types of attacks and the SRM model of blockchain followed by the conclusion.
{"title":"A survey paper on blockchain and its implementation to reduce security risks in various domains","authors":"Ayesha Abubakar, Sidra Minhas","doi":"10.54692/lgurjcsit.2022.0604314","DOIUrl":"https://doi.org/10.54692/lgurjcsit.2022.0604314","url":null,"abstract":"Every technology with its powerful uses has issues connected to it and security is at the top of it. As for the changing environment, the world has been shifting to Virtual Reality, the new coming world seems to be the internet and blockchain technology which is more powerful than others and has its applications in every field, be it quantum computing, internet of things, security or others. This survey paper covers the blockchain and its security in different fields of sciences and technology. We begin with the introduction of blockchain and then discuss its structure. After that security issues have been highlighted which include attacks and their behavior in quantum computing, internet of things, cloud computing. Furthermore, we have discussed the most common types of attacks and the SRM model of blockchain followed by the conclusion.","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130302522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-09-16DOI: 10.54692/lgurjcsit.2022.0603334
Kausar Parveen, Maryam Daud, Shahan Yamin Siddiqu
The Internet of Medical Things (IoMT) is the networking of health things or equipment that communicate data over the internet without the need for human involvement in the healthcare field. A large quantity of data is collected from numerous sensors in the health field, and it is all transferred and stored on the cloud. This data is growing bigger here all time, and it's becoming increasingly challenging to secure it on the cloud with real-time storage and computing. Data security problem can be addressed with the aid of machine algorithms and fog computing. For data security in IoMT gadgets correspondence in an intelligent fashion, an intelligent encryption algorithm (IEA) is proposed using blockchain technology in cloud based system framework (CBSF). It is applied on patient’s database to provide immutable security, tampering prevention and transaction transparency at the fog layer in IoMT. The suggested expert system's results indicate that it is suitable for use in for the security. In the fog model, the blockchain technology approach also helps to address latency, centralization, and scalability difficulties.
{"title":"Smart Detection of Cardiovascular Disease Using Gradient Descent Optimization","authors":"Kausar Parveen, Maryam Daud, Shahan Yamin Siddiqu","doi":"10.54692/lgurjcsit.2022.0603334","DOIUrl":"https://doi.org/10.54692/lgurjcsit.2022.0603334","url":null,"abstract":"The Internet of Medical Things (IoMT) is the networking of health things or equipment that communicate data over the internet without the need for human involvement in the healthcare field. A large quantity of data is collected from numerous sensors in the health field, and it is all transferred and stored on the cloud. This data is growing bigger here all time, and it's becoming increasingly challenging to secure it on the cloud with real-time storage and computing. Data security problem can be addressed with the aid of machine algorithms and fog computing. For data security in IoMT gadgets correspondence in an intelligent fashion, an intelligent encryption algorithm (IEA) is proposed using blockchain technology in cloud based system framework (CBSF). It is applied on patient’s database to provide immutable security, tampering prevention and transaction transparency at the fog layer in IoMT. The suggested expert system's results indicate that it is suitable for use in for the security. In the fog model, the blockchain technology approach also helps to address latency, centralization, and scalability difficulties.","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114518587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-21DOI: 10.54692/lgurjcsit.2022.0603277
Umber Noureen Abbas, Umair Waqas, Dr. Shafiq Hussain, Dr. Muhammad Amin Abid
we are living in an era full of technology and the most powerful feature behind this technology is the communication between two or more things. We achieved globalization with the power of digital computers and their ability to communicate. The next shape of computers for interactive remote processing is internet of things or wireless sensors network and for data storage it is cloud. These tiny computers with heterogeneous characteristics are very helpful in making environment smart and interactive in different ways. In this paper, we are proposing an Ambient Intelligence architecture for safety and energy efficiency using sensors, further we are formalizing the architecture for its accuracy and reliability. The three major sensors are smoke sensor for safety, glass break detector sensor for security, motion sensor for energy efficiency. In addition, the working of all sensors is also formalized for its correctness.
{"title":"A Formal Model for Smart Living Room","authors":"Umber Noureen Abbas, Umair Waqas, Dr. Shafiq Hussain, Dr. Muhammad Amin Abid","doi":"10.54692/lgurjcsit.2022.0603277","DOIUrl":"https://doi.org/10.54692/lgurjcsit.2022.0603277","url":null,"abstract":"we are living in an era full of technology and the most powerful feature behind this technology is the communication between two or more things. We achieved globalization with the power of digital computers and their ability to communicate. The next shape of computers for interactive remote processing is internet of things or wireless sensors network and for data storage it is cloud. These tiny computers with heterogeneous characteristics are very helpful in making environment smart and interactive in different ways. In this paper, we are proposing an Ambient Intelligence architecture for safety and energy efficiency using sensors, further we are formalizing the architecture for its accuracy and reliability. The three major sensors are smoke sensor for safety, glass break detector sensor for security, motion sensor for energy efficiency. In addition, the working of all sensors is also formalized for its correctness.","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114845918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-08-03DOI: 10.54692/lgurjcsit.2022.0603324
Senaha Noor Kazmi Noor, Sidra Minhas
Democracy is the power vested in people to choose and elect their representatives. However, theprocess of election and voting is prone to rigging leading to undeserving people leading a nationwhich further causes mistrust and agitation amongst the people. Various methods have beenproposed and implemented towards free and fair elections. In this survey we list and discussdifferent methods proposed and adopted for voting. These include the techniques which wereintroduced in past and can be implied in future, the techniques by which voting system can bemade more secure are, the remote voting, internet/online voting, a RFID tags, a fingerprinttechnology and IOT for updating, two languages the extensible markup language and anotherone is the extensible style language are used to design a unique content and cannot be copied.Other technology like electronic voting machine with battery can be useful in rural areas whereinternet is not available and last one is the blockchain technology by which the voter can casttheir vote in no time, and can have trust on that as this technology is end-to-end encrypted, heredata can be saved in sealing blocks. All this work is to find a better way to make the votingsystem more reliable and trustable for the future. In the end we discuss the efficacy of thesesystems in current infrastructure and requirements of Pakistan.
{"title":"The Prospects of Computer-Enabled Voting Systems in Pakistan","authors":"Senaha Noor Kazmi Noor, Sidra Minhas","doi":"10.54692/lgurjcsit.2022.0603324","DOIUrl":"https://doi.org/10.54692/lgurjcsit.2022.0603324","url":null,"abstract":"Democracy is the power vested in people to choose and elect their representatives. However, theprocess of election and voting is prone to rigging leading to undeserving people leading a nationwhich further causes mistrust and agitation amongst the people. Various methods have beenproposed and implemented towards free and fair elections. In this survey we list and discussdifferent methods proposed and adopted for voting. These include the techniques which wereintroduced in past and can be implied in future, the techniques by which voting system can bemade more secure are, the remote voting, internet/online voting, a RFID tags, a fingerprinttechnology and IOT for updating, two languages the extensible markup language and anotherone is the extensible style language are used to design a unique content and cannot be copied.Other technology like electronic voting machine with battery can be useful in rural areas whereinternet is not available and last one is the blockchain technology by which the voter can casttheir vote in no time, and can have trust on that as this technology is end-to-end encrypted, heredata can be saved in sealing blocks. All this work is to find a better way to make the votingsystem more reliable and trustable for the future. In the end we discuss the efficacy of thesesystems in current infrastructure and requirements of Pakistan.","PeriodicalId":197260,"journal":{"name":"Lahore Garrison University Research Journal of Computer Science and Information Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133413317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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