Global Journal of Computer Science and Technology (GJCST)
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An Efficient Automated Attendance Entering System by Eliminating Counterfeit Signatures using Kolmogorov Smirnov Test
Get PDFMaintaining the attendance database of thousands of students has become a tedious task in the universities in Sri Lanka This paper comprises of 3 phases signature extraction signature recognition and signature verification to automate the process We applied necessary image processing techniques and extracted useful features from each signature Support Vector Machine SVM multiclass Support Vector Machine and Kolmogorov Smirnov test is used to signature classification recognition and verification respectively The described method in this report represents an effective and accurate approach to automatic signature recognition and verification It is capable of matching classifying and verifying the test signatures with the database of 83 33 100 and 100 accuracy respectivel
Machine Learning Approach to Forecast Average Weather Temperature of Bangladesh
Get PDFWeather prediction is gaining popularity very rapidly in the current era of Artificial Intelligence and Technologies It is essential to predict the temperature of the weather for some time In this research paper we tried to find out the pattern of the average temperature of Bangladesh per year as well as the average temperature per season We used different machine learning algorithms to predict the future temperature of the Bangladesh region In the experiment we used machine learning algorithms such as Linear Regression Polynomial Regression Isotonic Regression and Support Vector Regressor Isotonic Regression algorithm predicts the training dataset most accurately but Polynomial Regressor and Support Vector Regressor predicts the future average temperature most accuratel
The Human Side of Information Technology when Technical Controls Fails
No full textThe misuse of information has significantly impacted negatively on both individuals and organizations security. The technical side of security controls is critical in an organization2019;s security system. This paper provides insight into some information security using the human side and other measures to protect the system. The paper also describes the technical control measures that are intended to meet the protection requirements of a system. Technical controls are security controls executed in the computer system. The controls provide automated protection from unauthorized access or misuse, facilitate detection of security violations, and support security requirements for applications and data. Since Implementation of technical controls, however, requires significant operational considerations it should, therefore, be consistent with the management of security
Performance Expectations for IT Graduates in Software Development
Get PDFTechnology makes the world more connected than it did yesterday, and it integrates worldwide activities in a blink of an eye. In the IT sector, there are several job roles as identified under software development. These job roles have different duties and tasks which requires employees, with a unique set of skills to match the specific requirements in the field. During the past few decades, the employment landscape has changed, and new occupations are rising in the field of software development, yet no satisfactory evidence has been provided by existing literature on the performance expectations in the industry, for IT graduates in software development, in the Sri Lankan context. Therefore, this research objectives to ascertain the expectations of employers on the technical, personal, educational, and general competencies of employees, holding an IT degree and to draw differences among individual and teamwork settings according to the identified competencies
Analyzing Political Opinions and Prediction of Voting Patterns in the US Election with Data Mining Approaches
Get PDFData is the precious resources. Data contains the useful patterns which provide the crucial information about the prediction of what is going to be happened in the next. In this paper, we aim to identify the political preferences and tendency of the US populations using classification and data mining techniques. To provide the usefulness of proposed model we analyze the electoral data sets in US election obtained from the official website which contains the information about 1984 United States Congressional voting records. This paper shows the classification techniques that can be used to predicting voting patterns in the US House of Representatives and shows the close correspondence between election results and extracted opinion. This paper also shows the political support of the voters and prediction the characteristics of the voter with their political tendency
Diagnosis of Prostate Cancer using Soft Computing Paradigms
Get PDFThe process of diagnosing of prostate cancer using traditional methods is cumbersome because of the similarity of symptoms that are present in other diseases. Soft Computing (SC) paradigms which mimic human imprecise data manipulation and learning capabilities have been reviewed and harnessed for diagnosis and classification of prostate cancer. SC technique based on Adaptive Neuro-Fuzzy Inference System (ANFIS) facilitated symptoms analysis, diagnosis and prostate cancer classification. Age of Patient (AP), Pains in Urination (PU), Frequent Urination (FU), Blood in Semen (BS) and Pains in Pelvic (PP) served as input attributes while Prostate Risk (PR) served as output. Matrix laboratory provided the programming tools for system implementation. The practical function of the system was assessed using prostate cancer data collected from the University of Uyo Teaching Hospital. A 95% harmony observed between the computed and the expected output in the ANFIS model, showed the superiority of the ANFIS model over the fuzzy model. The system is poised to assist medical professionals in the domain of diagnosis and classification of prostate cancer for the promotion of management and treatment decisions
Academicians' Acceptance of Online Learning Environments: A Review of Information System Theories and Models
Get PDFAim of this paper is to review technology IS acceptance theories and models recognizing empirical evidence available to support the suitability of each theoretical model in explaining academicians acceptance of online learning technology Understanding the factors influencing system usage is crucial for decision-makers to recognize potential user needs and concerns which could be addressed during the development phase of a system Thus for decades researchers have been trying to understand why people accept new technologies As a result a wide variety of theories and models explaining the concept of technology acceptance Some prominent theoretical models explaining technology acceptance are Theory of Reasoned Action Diffusion of Innovation theory Theory of Planned Behavior Social Cognitive Theory Technology Acceptance Model Model of PC Utilization Motivational Model Unified Theory of Acceptance and Use of Technology UTAUT 2 UTAUT 3 The concept of academic s acceptance of online learning technology can be explained through several determinants that are operationalized through above information systems model
Enabling Resesrchers to Make their Data Count
Get PDFOver the last years, many organizations have been working on infrastructure to facilitate sharing and reuse of research data. This means that researchers now have ways of making their data available, but not necessarily incentives to do so. Several Research Data Alliance (RDA) working groups have been working on ways to start measuring activities around research data to provide input for new Data Level Metrics (DLMs). These DLMs are a critical step towards providing researchers with credit for their work. In this paper, I describe the outcomes of the work of the Scholarly Link Exchange (Scholix) working group and the Data Usage Metrics working group. The Scholix working group developed a framework that allows organizations to expose and discover links between articles and datasets, thereby providing an indication of data citations. The Data Usage Metrics group works on a standard for the measurement and display of Data Usage Metrics. Here I explain how publishers and data repositories can contribute to and benefit from these initiatives. Together, these contributions feed into several hubs that enable data repositories to start displaying DLMs. Once these DLMs are available, researchers are in a better position to make their data count and be rewarded for their work
Development of Electronic Commerce Adoption Model based on Structural Equation Modeling Techniques
Get PDFAdvance Communication Technologies are playing a vital role in business today. In the world currently, many developing nations identified Small and Medium Scale organizations significantly important in counties2019; economic development. But the contribution from the SME sector is considerably low. Therefore, addressing this issue is important in business development. Among many reasons identified as barriers for SMEs to perform, studies have identified that low usage or not using technologies like E-commerce effected to this low performance. Therefore, studies are conducted to identify barriers to use technology in SMEs and many frameworks are tested and verified in different domains. In this study mainly tested and varied a framework which is considering Information Technological factors effecting the adoption of E-commerce technology and how it is effected for SME development. In this study framework is developed using literature analysis and hypothesis are developed based on past studies in terms of Information Technology factors as a main consideration. Model testing part is done using Structural Equation Molding using IBM AMOS. At the end of the study proposed framework is modified with statistical results and finally presented a framework which can be considered as a framework to understand the Information Technology factors effecting the E-commerce adoption and SME development
Implementation and Performance Analysis of Different Hand Gesture Recognition Methods
Get PDFIn recent few years, hand gesture recognition is one of the advanced grooming technologies in the era of human-computer interaction and computer vision due to a wide area of application in the real world. But it is a very complicated task to recognize hand gesture easily due to gesture orientation, light condition, complex background, translation and scaling of gesture images. To remove this limitation, several research works have developed which is successfully decrease this complexity. However, the intention of this paper is proposed and compared four different hand gesture recognition system and apply some optimization technique on it which ridiculously increased the existing model accuracy and model running time. After employed the optimization tricks, the adjusted gesture recognition model accuracy was 93.21% and the run time was 224 seconds which was 2.14% and 248 seconds faster than an existing similar hand gesture recognition model. The overall achievement of this paper could be applied for smart home control, camera control, robot control, medical system, natural talk, and many other fields in computer vision and human-computer interaction