Uroosa Rahat, Ammar Ahmed Siddiqui, Khurram Pervez, Muhammad Hasan
{"title":"Impediment in Adaptation of Algorithm Trading: A Case of Frontier Stock Exchange","authors":"Uroosa Rahat, Ammar Ahmed Siddiqui, Khurram Pervez, Muhammad Hasan","doi":"10.51153/kjcis.v6i2.192","DOIUrl":"https://doi.org/10.51153/kjcis.v6i2.192","url":null,"abstract":"The global financial markets have been significantly affected by the rapid change in technology. The study is an attempt to get to know the barriers to not adopting algorithmic trading in conventional stock exchanges. This research aims to plan and analytically proposed a model for explaining the reasons why frontier stock exchange traders and investors are hesitant to adopt algorithmic trading as a tool. The research includes variables; Lack of awareness, Trust, Lack of Government interest, unemployment, and unnecessary investment, which were extracted from previously available literature based on the theory of reason and technology acceptance model (TAM). A sample of 50 traders/investors from Pakistan stock markets was taken by using convenience sampling. Data was collected through a questionnaire and analyzed using correlation and linear regression techniques. The results show trust factor is the biggest hurdle in implementing Algorithm Trading which means countries like Pakistan which are following conventional methods for trading in stock markets have great doubts about the efficiency of Algorithm base trading because of the less human interaction and dependency on machines. Fear of miscalculation and the inexperience of data engineers are also one of the reasons conventional stock exchanges are reluctant to adopt algorithm trading. Similarly, variables like Lack of Government interest, unnecessary investment, and employment have a significant effect on the implementation of algorithm trading. Moreover, lack of awareness is the least significant factor, which shows the traders and investors in the Pakistan Stock Exchange are well aware of algorithm trading but the results cannot be generalized to the population due to a limited sample size of the study.","PeriodicalId":299009,"journal":{"name":"KIET Journal of Computing and Information Sciences","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128214392","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}
{"title":"SD-ALB: Software Defined Adaptive load balancing in Data Center Network","authors":"Riwan Fazal, S. Gilani, Muuhammad Junaid Khalid","doi":"10.51153/kjcis.v6i2.181","DOIUrl":"https://doi.org/10.51153/kjcis.v6i2.181","url":null,"abstract":"Network monitoring has crucial importance in data center networks to analyze the behavior of the underlying network. This analysis is used for working on multiple network parameters and load balancing is one of them. This article proposes an adaptive load-balancing approach to balance the load between the servers while changing its behavior with a change in traffic. Software Defined Networking (SDN) provides the single point of network configuration called SDN controller. This approach is facilitating the easy implementation of adaptive load balancing in Data Center Networks. The proposed approach is an extension to the LBBCLT load balancing approach that uses a dynamic probe generator to probe the servers about the response time and link bandwidth. We incorporate a path selection module in it and the path is selected using the Ant Colony Optimization. The results show that the bandwidth consumption and throughput have been improved and servers are receiving the load according to their capacities.","PeriodicalId":299009,"journal":{"name":"KIET Journal of Computing and Information Sciences","volume":"37 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114036522","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}
{"title":"Statistical Analysis for the Traffic Police Activity: Nashville, Tennessee, USA","authors":"M. Tufail, S. Gul","doi":"10.51153/kjcis.v5i2.135","DOIUrl":"https://doi.org/10.51153/kjcis.v5i2.135","url":null,"abstract":"Data Science is one of the fastest growing interdisciplinary field and has many applications in various disciplines. The actual motivation of data science came from John Tukey. In his seminal paper, in 1962, he presented the idea of data analysis which is now the field of data science. Several algorithms for data science related to statistical analysis have been developed and applied over variety of datasets since 1962. In this field, the significant development began with the aid of high performance computers that help to analyse a massive datasets. In this paper, we study the statistical analysis of the traffic stops in Nashville, Tennessee, USA for the year 2011--2021. Data is taken from the Stanford open policing project. Analysis is based on total number of 3071706 traffic stops. In this paper, we consider and investigate various aspects. This study comprises gender comparison (male vs female) and race comparison (black vs white) for different traffic offences. Complete findings and possible gaps are discussed in the conclusion.","PeriodicalId":299009,"journal":{"name":"KIET Journal of Computing and Information Sciences","volume":"270 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134189733","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}
Mamoona Atif Swati, Dr. Mustafa Madni, Dr. Uzair Iqbal Janjua, Dr. Iftikhar Ahmed Khan
{"title":"Enhanced Accessibility of Facebook Messenger for Blind Users","authors":"Mamoona Atif Swati, Dr. Mustafa Madni, Dr. Uzair Iqbal Janjua, Dr. Iftikhar Ahmed Khan","doi":"10.51153/kjcis.v5i2.125","DOIUrl":"https://doi.org/10.51153/kjcis.v5i2.125","url":null,"abstract":"With the growth in technology, social networking became an important factor of human life. People connect and share information through social media applications, such as Twitter, Facebook, and Instagram. Though, it is witnessed that using such applications is challenging for blind users. Such applications are also stated as highly inaccessible. The purpose of this study is to examine the worth of the Facebook Messenger application by using smartphone devices for blind users. Firstly, an experiment is conducted with five selected blind people and their performance and interaction is observed with the existing Facebook Messenger application. To minimize the difficulties observed during initial experiment Phase I, a prototype is designed and implemented based on existing WCAG guidelines. Twenty-one blind users experienced both the proposed prototype as well as the Existing Messenger Application. The efficiency is measured by applying a t-test whereas the SUS questionnaires are used to measure the satisfaction. The findings have shown the proposed design of the prototype fulfills the efficiency and user satisfaction for blind users. Finally, future work is recommended based on the acquired outcome to enhance the usability of social media applications.","PeriodicalId":299009,"journal":{"name":"KIET Journal of Computing and Information Sciences","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125811046","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}
M. Amin, Syed Tahir Hussain Rizvi, Sameer Malik, Muhammad Awais Yousaf, Sadaf Mehmood
{"title":"An Autonomous Follow Me Platform for Carrying and Moving Objects","authors":"M. Amin, Syed Tahir Hussain Rizvi, Sameer Malik, Muhammad Awais Yousaf, Sadaf Mehmood","doi":"10.51153/kjcis.v4i2.59","DOIUrl":"https://doi.org/10.51153/kjcis.v4i2.59","url":null,"abstract":"The technology of An Autonomous \"follow me\" platform for carrying and moving objects has gone through rapid technological advancements. Numerous follow me robots are accessible with various running advancements, yet the expense is high. These robots are not user-friendly and therefore not much successful. In this research, a fully automated, economical, fast, efficient and smart “Follow Me” robot is designed. This robot has the ability to carry luggage or move objects from one place to another place. It will help pregnant women and elder people to carry their things. An autonomous follow me robot has two working modes, the first one is the default mode and the second one is Bluetooth mode or remote mode. In default mode, the user will walk in the front of the ultrasonic sensor and it will follow the user until it goes beyond the range. In Bluetooth mode, the customer needs to interact with the robot with the help of a mobile application. The customer by then has the Graphical User Interface (GUI) to control the robot. This framework enables the client to vigorously communicate with the robot at various dimensions of the control (left, right, forward, backward, and stop). The application interface is built as simple as it can be used by a wide range of patients.","PeriodicalId":299009,"journal":{"name":"KIET Journal of Computing and Information Sciences","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129586403","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}
Muhammad Faisal Sultan, Mehwish Jabeen, Muhammad Adeel Mannan
{"title":"Sentiment Analysis through Big Data in online Retail Industry: A Conceptual Quantitative Study on linkage of Big-Data and Assortment Proactive of Online Retailers","authors":"Muhammad Faisal Sultan, Mehwish Jabeen, Muhammad Adeel Mannan","doi":"10.51153/KJCIS.V3I2.47","DOIUrl":"https://doi.org/10.51153/KJCIS.V3I2.47","url":null,"abstract":"Big-Data is the recent trend in data sciences prevailing all over the globe. The tool aids significantly in optimization of knowledge and has predominant use in optimization of knowledge and productivity. However, there is lack of understanding of concept and its application in Pakistan as indicated by Gallup Pakistan (2018) and stream of data is going to be doubled in two years’ time Tankard (2012). Therefore, there is a definite need of research which optimizes understanding associated with technology and its application from the context of Pakistan. Hence considering the application of big-data in retail sector this study aims to explore the impact of sentiment analysis through relating impact of big-data with effective assortment s of online stores. Although data has been collected from IT experts associated with online retail sector via quota sampling and SMART-PLS has been incorporated for the purpose of analysis. Results of the study highlights that big-data is perceived as the major tool for the betterment of assortment in online retail stores although data scientist and their applicability might diminish the impact of the use of big-data.","PeriodicalId":299009,"journal":{"name":"KIET Journal of Computing and Information Sciences","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132129026","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}
{"title":"Predicting the Visibility of the First Crescent","authors":"Tafseer Ahmed","doi":"10.51153/kjcis.v3i2.52","DOIUrl":"https://doi.org/10.51153/kjcis.v3i2.52","url":null,"abstract":"This study presents an application of machine learning to predict whether the first crescent of the lunar month will be visible to naked eye on a given date. The study presents a dataset of successful and unsuccessful attempts to find the first crescent at the start of the lunar month. Previously, this problem was solved by analytically deriving the equations for visibility parameter(s) and manually fixing threshold values. However, we applied supervised machine learning on the independent variables of the problem, and the system learnt about the criteria of classification. The system gives precision of 0.88 and recall of 0.87 and hence it treats both false positives and false negatives equally well.","PeriodicalId":299009,"journal":{"name":"KIET Journal of Computing and Information Sciences","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122525598","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}
K. Nisar, Shamsuddeen Bala, A. Mu'azu, Ibrahim A. Lawal
{"title":"Improved User Authentication Process for Third-Party Identity Management in Distributed Environment","authors":"K. Nisar, Shamsuddeen Bala, A. Mu'azu, Ibrahim A. Lawal","doi":"10.51153/kjcis.v3i2.51","DOIUrl":"https://doi.org/10.51153/kjcis.v3i2.51","url":null,"abstract":"Third-party identity management user authentication process using single sign-on (SSO) in distributed computer networks requires modification as the process of authenticating user to log into relying party (RP) resources by either identity provider (IDP) or hybrid relying party (HRP) depend always on the authentication of user logins. In this research an algorithm is proposed to authenticate user only once by recording and encrypting user credential with one-way hashing algorithm (SHA2), this simplifies user subsequent logins into relying party by confirming user credentials without other authentication by IDP or HRP. Authentication time and response time continuous time plot of the proposed algorithm was plotted with respect to the arrival time of users in which we show the relationship of authentication time and response time with random arrival rate of users.","PeriodicalId":299009,"journal":{"name":"KIET Journal of Computing and Information Sciences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131991927","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}
Tariq Mahmood, M. Riaz, M. Nasir, U. Afzal, Sohaib Tariq, M. Siddiqui
{"title":"PSL Eye: Predicting the Winning Team in Pakistan Super League (PSL) Matches","authors":"Tariq Mahmood, M. Riaz, M. Nasir, U. Afzal, Sohaib Tariq, M. Siddiqui","doi":"10.51153/kjcis.v4i2.64","DOIUrl":"https://doi.org/10.51153/kjcis.v4i2.64","url":null,"abstract":"Pakistan Super League (PSL) is a well-known T20 cricket league with millions of viewers. With this large viewer base, predicting the outcome of PSL matches opens a new research avenue for academic researchers. In this paper, we collect PSL data from relevant sources and generate a validated data set for machine learning experiments. We implement the “PSL Eye” solution which employs Neural Networks (NNs) to predict the match winning team. We preprocess the dataset to eliminate the extra variables then we tune the hyper parameters of NN. After acquiring the optimal values of hyper parameters, we run our NN based PSL Eye to obtain the final results. The overall accuracy of PSL-Eye with testing data set is 82% which is very promising and shows the importance of NN in predicting PSL match outcome.","PeriodicalId":299009,"journal":{"name":"KIET Journal of Computing and Information Sciences","volume":"61 10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116159224","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}
{"title":"Poet Attribution for Urdu: Finding Optimal Configuration for Short Text","authors":"M. A. Rao, Tafseer Ahmed","doi":"10.51153/kjcis.v4i2.58","DOIUrl":"https://doi.org/10.51153/kjcis.v4i2.58","url":null,"abstract":"\u0000 \u0000 \u0000 \u0000This study presents a machine learning system to identify the poet of a given poetic piece consisting of 2 lines (i.e. a couplet) or more. The task is more difficult than the general task of author attribution, as the number of words in verses and poems are usually less than the number of articles present in author attribution datasets. We applied classification algorithms with different sets of feature configurations to run several experiments and found that the system performs best when support vector machine using a combination of unigram and bigram are used . The best system (for 5 Urdu poets) has the accuracy of 88.7%. \u0000 \u0000 \u0000 \u0000","PeriodicalId":299009,"journal":{"name":"KIET Journal of Computing and Information Sciences","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131624545","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}