Journal of Independent Studies and Research Computing最新文献_第4页

A Machine Learning Approach for Personality Type Identification using MBTI Framework 基于MBTI框架的人格类型识别的机器学习方法

Journal of Independent Studies and Research Computing Pub Date : 2022-01-27 DOI: 10.31645/jisrc.43.19.2.2

Hira A. Shafi, Ahmed Sikander, Ismail Mohamed Jamal, Jawwad Ahmad, M. Aboamer

{"title":"A Machine Learning Approach for Personality Type Identification using MBTI Framework","authors":"Hira A. Shafi, Ahmed Sikander, Ismail Mohamed Jamal, Jawwad Ahmad, M. Aboamer","doi":"10.31645/jisrc.43.19.2.2","DOIUrl":"https://doi.org/10.31645/jisrc.43.19.2.2","url":null,"abstract":"In recent times, the prediction of personality traits with automated and programmed systems has caught human attention. Specifically, the use of multimodal data to predict personality types is the most considerable talk in artificial intelligence. There are a variety of techniques and methods available for personality type identification. The most popular and highly used personality type identifier is the Myers Briggs Type Indicator (MBTI) type indicator among all methods. In this paper, an exhaustive comparative analysis of all machine learning classical algorithms implementing the MBTI framework will be presented by giving a numerical and graphical representation of performance measures. To experience this study, a supervised machine learning approach is used to perform and analyze different classifiers using the phenomena of MBTI. The models are learned from a dataset to make predictions. The results show that the Ensemble Bagged Trees algorithm gives an overall good training accuracy of 98.4% and test accuracy of 70.75% at a moderate prediction speed of 11 K - Obs/sec by taking a training time of 14 sec. Other than that Coarse Tree algorithm in training time is 0.94009/sec and prediction speed 390 (K - Obs/sec), Fine KNN and Weighted KNN algorithm in training accuracy of 99.20% and Ensemble Boosted Trees algorithm in testing accuracy of 75.51% shows the efficient outcome respectively.","PeriodicalId":412730,"journal":{"name":"Journal of Independent Studies and Research Computing","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127002972","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}

引用次数: 2

Impact Estimation of Offshore Floating Solar Parks on Algae using Ordinary Differential Equations 利用常微分方程估计海上浮动太阳能公园对藻类的影响

Journal of Independent Studies and Research Computing Pub Date : 2022-01-27 DOI: 10.31645/jisrc.38.19.2.6

Basit Ali, Kaniz Fatima, Rashida Qari, Abdul Attayyab Khan, Mahnoor Arshad

引用次数: 2

Effect of Imperfect Artificial Noise on the Performance of Physical Layer Security for MU-Massive MIMO System 不完全人工噪声对MU-Massive MIMO系统物理层安全性能的影响

Journal of Independent Studies and Research Computing Pub Date : 2022-01-27 DOI: 10.31645/jisrc.26.19.2.5

Yazeed Abdulaziz Alhaqbani

引用次数: 0

Efficient Face Re-Identification through PSO Based Adaptive Deep Learning Models 基于粒子群自适应深度学习模型的人脸再识别

Journal of Independent Studies and Research Computing Pub Date : 2022-01-27 DOI: 10.31645/jisrc.37.19.2.4

Muhammad Saddam Khokhar, Misbah Ayoub, Jamali Zakria, Waqas Rasheed

{"title":"Efficient Face Re-Identification through PSO Based Adaptive Deep Learning Models","authors":"Muhammad Saddam Khokhar, Misbah Ayoub, Jamali Zakria, Waqas Rasheed","doi":"10.31645/jisrc.37.19.2.4","DOIUrl":"https://doi.org/10.31645/jisrc.37.19.2.4","url":null,"abstract":"Face plays a vital role in the Recognition or Re-Identification of a person. Therefore, it is significant to identify and extract the facial visual features that automatically lead to face identification-based classification. Facial features comprise different ways of detection, for instance, they could be located at corners or midpoints of the facial features that rely on multiple components such as eyes, lips, nose with different emotions and expressions used in face recognition. This paper introduced a robust and efficient deep learning model with the use of a transfer learning approach for PSO for extraction and selection of the best facial features. Deep learning models “Openface via PSO and introduced customized Inception-V3 model via PSO is used and present detailed comparative accuracy of both models in terms of classification recognition. For this, the paper presents seven different algorithms to evaluate the efficiency of the model with four different face databases. It is evident from the result; neural network classifier shows a gradual hike to calculate accuracy with the proposed PSO-based OpenFace deep learning approach. On the other hand, random forest and AdaBoost algorithm were observed most compatible with the customized PSO-based Inception-V3 model.","PeriodicalId":412730,"journal":{"name":"Journal of Independent Studies and Research Computing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128314773","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}

引用次数: 1

Probabilistic Graph Models (PGMs) for Feature Selection in Time Series Analysis and Forecasting 概率图模型(PGMs)在时间序列分析和预测中的特征选择

Journal of Independent Studies and Research Computing Pub Date : 2022-01-27 DOI: 10.31645/jisrc.49.19.2.3

Syed Asil Ali Naqvi, T. Jilani

{"title":"Probabilistic Graph Models (PGMs) for Feature Selection in Time Series Analysis and Forecasting","authors":"Syed Asil Ali Naqvi, T. Jilani","doi":"10.31645/jisrc.49.19.2.3","DOIUrl":"https://doi.org/10.31645/jisrc.49.19.2.3","url":null,"abstract":"Time series or longitudinal analysis has a very important aspect in the field of research. Day by day new and better analyses are getting developed in this field. The main problem of the time series modeling is the presence of heteroskedasticity which was first identified as autoregressive conditional heteroskedasticitic (ARCH) effect by R. Engle (1969) [15] and then moderated by Bollerslev (1986) [7] in the more generalized form of generalized autoregressive conditional heteroskedasticitic (GARCH) models to explain the conditional dependence and can capture the systematizes evidence of the past variations of the time series variables. And on the other hand, J. Pearl (1985) [33] in the mid-eighties established the use of probabilistic graph models (PGMs), especially it's part where the causation cannot be reversed i.e. directed acyclic graphs (DAGs) as Bayesian Networks (BNs) to determine the conditional independence and is widely used in various fields of life with greater accuracy, precision, and fewer complexities. Fortunately, Bayesian Networks (BNs) are not used to to-date for the analysis of conditional dependencies or conditional independence analysis on the longitudinal data. This paper will review and summarize the uses of GARCH models and the uses of BNs in different fields and the responses of the researchers on the results accuracies and precision in comparison of the other available and applied analyses.","PeriodicalId":412730,"journal":{"name":"Journal of Independent Studies and Research Computing","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121068503","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}

引用次数: 0

Impact of Individual Life Assurance System (ILAS) on the Net Benefits of EFU Life in Pakistan 巴基斯坦个人人寿保险制度(ILAS)对EFU人寿净收益的影响

Journal of Independent Studies and Research Computing Pub Date : 2022-01-27 DOI: 10.31645/jisrc.55.19.2.7

I. Batada

{"title":"Impact of Individual Life Assurance System (ILAS) on the Net Benefits of EFU Life in Pakistan","authors":"I. Batada","doi":"10.31645/jisrc.55.19.2.7","DOIUrl":"https://doi.org/10.31645/jisrc.55.19.2.7","url":null,"abstract":"This case study explored the impact of the Individual Life Assurance System (ILAS) on the net benefits of EFU Life, a leading insurance company in Pakistan. EFU Life implemented ILAS to overcome the challenge of technical limitations and the unavailability of modules. The study surveyed people across all departments in EFU Life to assess the performance of ILAS on the company net benefits. The research framework was formulated based on the Delone Model of the Pakistan region [13]. This research study added the Service Quality to the existing System and Information Quality used to evaluate the Organizational Impact in the original Delone Model [13]. Moreover, our model also incorporates Top Management Support as an antecedent of Quality, User Satisfaction, and Net Benefit. The ultimate aim is to find a way to enhance Net Benefits. The research argues that improved Quality as a result of Top Management Support reduces /eliminates wastage of resources and helps the organization in achieving profits, hence, the increase in the Net Benefits. It is found that Top Management support enhances user benefit and therefore recommends top managers to be fully involved and support a suitable environment and culture for the positive change in the organization’s image that is extremely important for user satisfaction. It is suggested that there is a need for top managers to arrange resources required by the users and encourage a user-focused organizational environment to promote user satisfaction. Involvement and support of top managers can also make the overall organization succeed, and its evidence can be seen in current research in the form of top management support’s positive effect on the net benefit of organizations.","PeriodicalId":412730,"journal":{"name":"Journal of Independent Studies and Research Computing","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133116197","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}

引用次数: 0

Performance and Stability Margins Comparison of Pole Placement and Optimal Controllers using Cart-Inverted Pendulum System 推车-倒立摆系统极点配置与最优控制器性能及稳定裕度比较

Journal of Independent Studies and Research Computing Pub Date : 2022-01-27 DOI: 10.31645/jisrc.44.19.2.1

M. Ijaz

引用次数: 0

A Comprehensive Comparative Evaluation of Machine Learning Algorithms on Facebook Comment Dataset 基于Facebook评论数据集的机器学习算法的综合比较评价

Journal of Independent Studies and Research Computing Pub Date : 2022-01-27 DOI: 10.31645/jisrc.46.19.2.8

Muhammad Umair, Iffraah Rehman, Shamim Akhtar, Waqar Khan, Haider Abbas, R. Choudhary

{"title":"A Comprehensive Comparative Evaluation of Machine Learning Algorithms on Facebook Comment Dataset","authors":"Muhammad Umair, Iffraah Rehman, Shamim Akhtar, Waqar Khan, Haider Abbas, R. Choudhary","doi":"10.31645/jisrc.46.19.2.8","DOIUrl":"https://doi.org/10.31645/jisrc.46.19.2.8","url":null,"abstract":"Data mining is an emerging technique with its application in various areas such as health care, education, travel, social media, and banking. The data can be either labeled or unlabeled. When it comes to social media, the various platforms generate an infinite amount of data. This data can be of immense importance as a lot of hidden information can be discovered after data mining. In this paper, machine-learning algorithms such as Decision Tress, SVM and Linear Regression and their variants are applied on Facebook comment dataset, obtained from UCI machine learning repository. The dataset has 40,949 instances and 54 attributes. The goal is to predict the number of comments a Facebook post will get based on various conditions. The results indicate that Fine Gaussian SVM variation of SVM yielded highest predication accuracy. The evaluation was done on different parameters such as average testing accuracy (%), Root Mean Square Error (RMSE), R- Squared, Mean Square Error (MSE), Mean Absolute Error (MAE), prediction speed (Obs/sec) and training time (Machine cycle). It is concluded that SVM is an ideal choice to solve prediction problems associated with social media data.","PeriodicalId":412730,"journal":{"name":"Journal of Independent Studies and Research Computing","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134213328","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}

引用次数: 0

Smart Beef-Quality Tracking In Malaysia Using Blockchain Technology 马来西亚使用区块链技术的智能牛肉质量跟踪

Journal of Independent Studies and Research Computing Pub Date : 2021-11-22 DOI: 10.31645/jisrc.36.19.1.3

Aisha Zahid Junejo, Aina Hamidi, M. Memon, M. Hashmani

{"title":"Smart Beef-Quality Tracking In Malaysia Using Blockchain Technology","authors":"Aisha Zahid Junejo, Aina Hamidi, M. Memon, M. Hashmani","doi":"10.31645/jisrc.36.19.1.3","DOIUrl":"https://doi.org/10.31645/jisrc.36.19.1.3","url":null,"abstract":"Concerns and awareness on beef quality and safety are increasing among the consumers. Beef that is being served to the customers has to be of good quality and safe to eat, as well as to prevent foodborne illnesses. Hence, it is important to ensure good meat quality during the process of beef production. The existing beef supply chain systems lack transparency, as a result, a hike in food frauds has been witnessed in Malaysia. Consequently, it is hard to infer if the beef reaching the consumers is safe and wholesome. Besides that, the existing supply chains have a time-consuming and tiring procedure of product tracking, which is not desirable for consumers and other various stakeholders involved. To mitigate this issue, in this paper, we propose the use of blockchain technology for beef supply chain to maintain the transparency of ingredients and processes used in beef production. This will strengthen the trust of consumer in the company and ensure that the produced beef is contamination free and healthy. The study comprehensively highlights the feasibility blockchain technology to be implemented in the beef supply chain to make it transparent, secure and easily trackable.","PeriodicalId":412730,"journal":{"name":"Journal of Independent Studies and Research Computing","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121127609","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}

引用次数: 0

Application of IoT for Power Controlling in Smart Home 物联网在智能家居电源控制中的应用

Journal of Independent Studies and Research Computing Pub Date : 2021-11-22 DOI: 10.31645/jisrc.28.19.1.1

Muhammad Rauf, A. Khan, A. Shaikh, Q. Ali

{"title":"Application of IoT for Power Controlling in Smart Home","authors":"Muhammad Rauf, A. Khan, A. Shaikh, Q. Ali","doi":"10.31645/jisrc.28.19.1.1","DOIUrl":"https://doi.org/10.31645/jisrc.28.19.1.1","url":null,"abstract":"The rapid growth in the population of major cities is causing an increase in energy consumption. Several approaches, including the use of recent technological advancements, are becoming increasingly important. IoT-based applications are becoming more common in addressing a variety of real-time issues. The central idea of the project in collaborating with this new technology is the human-machine interaction. Furthermore, the proposed architecture enables energy-saving applications that perform the following primary functions: estimating energy utilization of the home environment using metering devices; and applying user-defined limits that cut off boundaries providing if it exceeds energy limits. The Internet serves as an interactive medium between servers and home appliances, monitoring and controlling energy consumption remotely. For the purpose, android platform is used to design a mobile application. Raspberry Pi is dedicated for the server that maintains the database of each controllable unit. The proposed idea is successfully tested in the laboratory environment with synthetic load and in real-time over a running energy meter, to evaluate the efficiency and effectiveness.","PeriodicalId":412730,"journal":{"name":"Journal of Independent Studies and Research Computing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132441603","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}

引用次数: 0