International Journal of Computer and Information Technology(2279-0764)最新文献

{"title":"A Computer Model of the Spread of the Pandemic and its Analysis","authors":"A. Bardavelidze, I. Basheleishvili, Khatuna Bradvelidze","doi":"10.24203/ijcit.v10i5.165","DOIUrl":"https://doi.org/10.24203/ijcit.v10i5.165","url":null,"abstract":"The paper describes and analyzes a mathematical model of the variable state of the incidence of epidemic diseases, which is of great importance for determining the quantity of vaccines and antiviral drugs to be produced.    The information model according to the system of differential equations of the spread of the pandemic is illustrated in a structural diagram. The model is presented in a vector-matrix form and the state of equilibrium of the model in the spatial state is proved.The model of the spread of the pandemic was developed, whose implementation with a Matlab software package resulted in obtaining the curves of variation of the state. The developed computer model of the incidence of epidemic diseases can be used to make a projection of the number of infected people, as well as intensity of the process of disseminating information and ideas in the community.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128010778","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":"Digital Video Watermarking for Copyright Labelling","authors":"Fitria Ilhami Ikromina Ami, Erik Iman Heri Ujianto Erik","doi":"10.24203/ijcit.v10i5.157","DOIUrl":"https://doi.org/10.24203/ijcit.v10i5.157","url":null,"abstract":"Penggunaan konten multimedia di internet kini semakin berkembang, terutama dalam video digital. Pemalsuan, penipuan, dan penjarahan konten video menyebabkan masalah karena pasokan sumber daya untuk berbagi konten. Hak cipta menjadi hal yang krusial dalam video digital untuk menghindari manipulasi dari pihak yang tidak bertanggung jawab. Ada banyak cara yang bisa dilakukan untuk melabeli hak cipta ke dalam sebuah video. Salah satunya adalah digital watermarking. Pembuatan air digital digunakan untuk mencegah replikasi ilegal atau eksploitasi konten digital, melindungi konten digital, dan menghindari manipulasi multimedia secara ilegal. Penggunaan beberapa metode seperti Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT), dan Discrete Fourier Transform (DFT) untuk pelabelan hak cipta video akan dibandingkan berdasarkan imperceptibility dan robustness setelah beberapa manipulasi diterapkan ke dalam video yang disisipkan-watermark. Dari segi imperceptibility, metode DWT menghasilkan nilai PSNR sebesar 45,62435 dB, metode DCT menghasilkan nilai PSNR sebesar 45.89422 dB, dan metode DFT menghasilkan nilai PSNR sebesar 45.77747 dB. Rerata PSNR dari ketiga metode tersebut adalah 45.76535 dB. Artinya, video yang disisipkan tanda air tampak mirip dengan yang disisipkan. Dengan demikian, dari percobaan dapat disimpulkan bahwa metode DWT, DCT, dan DFT yang diterapkan menunjukkan bahwa video yang diberi watermark masih dalam kualitas yang baik yaitu wajar dan memenuhi imperceptibility. Dari segi kekokohan, NC mean metode DCT adalah 0,63974, metode DCT adalah 0,755839, dan metode DFT adalah 0,745442. Hal ini menunjukkan bahwa hasil ekstraksi watermark dari ketiga metode tersebut sama dengan hasil watermark aslinya. Dengan kata lain, semua tanda air pada ketiga metode ini dapat diekstraksi dengan baik meskipun serangan dikirimkan kepada mereka. Dari tingkat uji imperceptibility dan robustness pada metode DWT, DCT, dan DFT, dapat dikatakan bahwa metode DCT lebih baik daripada metode DWT dan DFT karena performansinya yang tinggi pada PSNR dan NC.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115219639","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":"A Survey of Deep Learning Solutions for Anomaly Detection in Surveillance Videos","authors":"John Gatara Munyua, G. Wambugu, Stephen Thiiru Njenga","doi":"10.24203/ijcit.v10i5.166","DOIUrl":"https://doi.org/10.24203/ijcit.v10i5.166","url":null,"abstract":"Deep learning has proven to be a landmark computing approach to the computer vision domain. Hence, it has been widely applied to solve complex cognitive tasks like the detection of anomalies in surveillance videos. Anomaly detection in this case is the identification of abnormal events in the surveillance videos which can be deemed as security incidents or threats. Deep learning solutions for anomaly detection has outperformed other traditional machine learning solutions. This review attempts to provide holistic benchmarking of the published deep learning solutions for videos anomaly detection since 2016. The paper identifies, the learning technique, datasets used and the overall model accuracy. Reviewed papers were organised into five deep learning methods namely; autoencoders, continual learning, transfer learning, reinforcement learning and ensemble learning. Current and emerging trends are discussed as well.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129292125","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":"Deep Learning Methods In Predicting Indonesia Composite Stock Price Index (IHSG)","authors":"Arief Fadhlurrahman Rasyid, Dewi Agushinta R., Dharma Tintri Ediraras","doi":"10.24203/ijcit.v10i5.153","DOIUrl":"https://doi.org/10.24203/ijcit.v10i5.153","url":null,"abstract":"The stock price changes at any time within seconds. The stock price is a time series data. Thus, it is necessary to have the best analysis model in predicting the stock price to make decisions to avoid losses in investing. In this research, the method used two models Deep Learning namely Long Short Term Memory (LSTM) and Gated Recurrent Unit (GRU) in predicting Indonesia Composite Stock Price Index (IHSG). The dataset used is historical data from the Jakarta Composite Index (^JKSE) stock price in 2013-2020 obtained through Yahoo Finance. The results suggest that Deep learning methods with LSTM and GRU models can predict Indonesia Composite Stock Price Index (IHSG). Based on the test results obtained RMSE value of 71.28959454502723 with an accuracy rate of 92.39% for LSTM models and obtained RMSE value of 70.61870739073838 with an accuracy rate of 96.77% on GRU models.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116062312","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":"Object Tracking in Video Using the TLD and CMT Fusion Model","authors":"H. Tran","doi":"10.24203/ijcit.v10i5.151","DOIUrl":"https://doi.org/10.24203/ijcit.v10i5.151","url":null,"abstract":"Object tracking has been an attractive study topic in computer vision in recent years, thanks to the development of video monitoring systems. Tracking-Learning Detection (TLD), Compressive Tracking (CT), and Clustering of Static-Adaptive Correspondences for Deformable Object Tracking are some of the state-of-the-art methods for motion object tracking (CMT). We present a fusion model that combines TLD and CMT in this study. To restrict the calculation time of the CMT technique, the fusion TLD CMT model enhanced the TLD benefits of computation time and accuracy on t no deformable objects. The experimental results on the Vojir dataset for three techniques (TLD, CMT, and TLD CMT) demonstrated that our fusion proposal successfully trades off CMT accuracy for computing time.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125875004","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":"Neutrosophic Triangular Fuzzy Travelling Salesman Problem Based on Dhouib-Matrix-TSP1 Heuristic","authors":"S. Dhouib","doi":"10.24203/ijcit.v10i5.154","DOIUrl":"https://doi.org/10.24203/ijcit.v10i5.154","url":null,"abstract":"In this paper, the Travelling Salesman Problem is considered in neutrosophic environment which is more realistic in real-world industries. In fact, the distances between cities in the Travelling Salesman Problem are presented as neutrosophic triangular fuzzy number. This problem is solved in two steps: At first, the Yager’s ranking function is applied to convert the neutrosophic triangular fuzzy number to neutrosophic number then to generate the crisp number. At second, the heuristic Dhouib-Matrix-TSP1 is used to solve this problem. A numerical test example on neutrosophic triangular fuzzy environment shows that, by the use of Dhouib-Matrix-TSP1 heuristic, the optimal or a near optimal solution as well as the crisp and fuzzy total cost can be reached.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130286898","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":"The Impact of Coporate Website on Dissemination of Research Information Among Stakeholders in Nigeria","authors":"C. E. Chibudike, Haruna Abdu, H. O. Chibudike, Viola Nwachukwu Nichola Okpara, Nkemdilim Obi, O. Adeyoju","doi":"10.24203/ijcit.v10i3.102","DOIUrl":"https://doi.org/10.24203/ijcit.v10i3.102","url":null,"abstract":"This study accesses the influence of an official website as one that has been licensed by using an authority to signify itself or its houses online. Individuals, companies, governments, and different organizations can be such an authority. An internet portal is a web-based platform that gives employees, clients and suppliers with a single get right of entry to factor to information.8 A web portal can be used to supply the consumer with customized data such as employee training, protection manuals or a customer profile. A web portal can additionally be used to beautify the collaboration of information and improve the way employees, customers and suppliers interact with your commercial enterprise [7]. There are couple of reasons why an MSMEs will seem toward net portal development. This study was once made in two classes of lookup institutes: Health institutes and economic/social institutes. Comparison figures point out that there is no sizable difference in phrases of presence of a respectable website of Health Institutes and Economic/social institutes. Health Institutes have extra capability to diffuse their improvements to public than Economic/social institutes, using their website as a verbal exchange device of lookup findings dissemination. The comparisons of use of professional website, goal audiences were carried out as well as reliability check in percentages to allow conclusive results.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129930457","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 Growth of e-Commerce using Trendline Analysis: A Case Study of Ogun State, Nigeria","authors":"Ebenezer N. Igwe, Olumuyiwa Bamidele Alaba, Olalere. A. Abass","doi":"10.24203/IJCIT.V10I2.69","DOIUrl":"https://doi.org/10.24203/IJCIT.V10I2.69","url":null,"abstract":"There is a growing interest from e-commerce planners and other planning agencies in the Information Technology world to measure and forecast the growth of e-commerce in developing countries like Nigeria. The difficulties lie in finding the best forecasting model that can incorporate both the internal and external barriers that influence the full adoption and diffusion of e-commerce. This study attempts to identify the relevant e-commerce tools and its spread in Ogun East Senatorial District as well as formulating a mathematical model for e-commerce adoption and diffusion. A well-structured questionnaire was used to collect data from 126 respondents and analyzed using Trendline, a built-in analysis tool in Microsoft® Office Excel version 2013. The study identified PCs/laptops, ATM cards, e-mail services, mobile money transfer, e-commerce Websites, and point-of-sales (POS) terminals as e-commerce tools used by the respondents. The results of the study show that majority of the e-commerce users/adopters were single female students between the ages of 21 and 30 years, with university education owing to a proportion of 63% of the respondents while the earliest adopted e-commerce tools in descending order were tablets/smartphones, PCs/laptops, ATM cards, and email services. The results further show that the most popularly-used tools were e-commerce websites (98% responses), email services (94% responses), mobile money transfer (94% responses), POS terminals (94% responses), tablets/smartphones (93% responses), PCs/laptops (87% responses) and ATM cards (80% responses). Based on the findings of this study, it is therefore recommended that government should promote the use and development of e-commerce, notably by reducing the costs of access to technology, through the liberation of trade in software and hardware.\u0000 ","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127336044","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":"Research Methods in Machine Learning: A Content Analysis","authors":"J. Kamiri, Geoffrey Wambugu Mariga","doi":"10.24203/IJCIT.V10I2.79","DOIUrl":"https://doi.org/10.24203/IJCIT.V10I2.79","url":null,"abstract":"Research methods in machine learning play a pivotal role since the accuracy and reliability of the results are influenced by the research methods used. The main aims of this paper were to explore current research methods in machine learning, emerging themes, and the implications of those themes in machine learning research.  To achieve this the researchers analyzed a total of 100 articles published since 2019 in IEEE journals. This study revealed that Machine learning uses quantitative research methods with experimental research design being the de facto research approach. The study also revealed that researchers nowadays use more than one algorithm to address a problem. Optimal feature selection has also emerged to be a key thing that researchers are using to optimize the performance of Machine learning algorithms. Confusion matrix and its derivatives are still the main ways used to evaluate the performance of algorithms, although researchers are now also considering the processing time taken by an algorithm to execute. Python programming languages together with its libraries are the most used tools in creating, training, and testing models. The most used algorithms in addressing both classification and prediction problems are; Naïve Bayes, Support Vector Machine, Random Forest, Artificial Neural Networks, and Decision Tree. The recurring themes identified in this study are likely to open new frontiers in Machine learning research.   ","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124293815","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":"Fast Visual Tracking Using Spatial Temporal Background Context Learning","authors":"Asif Mukhtar, Arslan Majid, Kashif Fahim","doi":"10.24203/IJCIT.V9I5.25","DOIUrl":"https://doi.org/10.24203/IJCIT.V9I5.25","url":null,"abstract":"Visual Tracking by now has gained much provenience among researchers in recent years due to its vast variety of applications that occur in daily life. Various applications of visual tracking include counting of cars on a high way, analyzing the crowd intensity in a concert or a football ground or a surveillance camera tracking a single person to track its movements. Various techniques have been proposed and implemented in this research domain where researchers have analyzed various parameters. Still this area has a lot to offer. There are two common approaches that are currently deployed in visual tracking. One is discriminative tracking and the other one is generative tracking. Discriminative tracking requires a pre-trained model that requires the learning of the data and solves the object recognition as a binary classification problem. On the other hand, generative model in tracking makes use of the previous states so that next state can be predicted. In this paper, a novel tacking based on generative tracking method is proposed called as Illumination Inavariant Spatio Temporal Tracker (IISTC). The proposed technique takes into account of the nearby surrounding regions and performs context learning so that the state of the object under consideration and its surrounding regions can be estimated in the next frame. The learning model is deployed both in the spatial domain as well as the temporal domain. Spatial domain part of the tracker takes into consideration the nearby pixels in a frame while the temporal model takes account of the possible change of object location. The proposed tracker was tested on a set of 50 images against other state of the art four trackers. Experimental results reveal that our proposed tracker performs reasonably well as compared with other trackers. The proposed visual tracker is both efficiently with respect to computation power as well as accuracy. The proposed tracker takes only 4 fast Fourier transform computations thus making it reasonably faster. The proposed trackers perform exceptionally well when there is a sudden change in back ground illumination.","PeriodicalId":359510,"journal":{"name":"International Journal of Computer and Information Technology(2279-0764)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129216277","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}