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The focus of this study is on lecturer’s use of online technology in the higher education context. Precisely, this study aims to understand the effect of personal innovativeness in IT (PI) in determining technology adoption behavior of lecturers in the higher education institutes in Sri Lanka. In this study, the variable of personal innovativeness in IT is integrated with the UTAUT framework and thereby the causal paths which effects VLE adoption intention of individuals is examined. Literature suggests that domain-specific innovativeness is a crucial factor in determining an individual’s adoption of technological innovations. Therefore, understanding the multifaceted effects of this factor along with other significant factors can help higher education institutes to effectively endorse online technology among lectures, generating productive payoffs in the long run. The quantitative method was used for data collection, which yielded # 1253 responses through the Question Pro online survey tool. The targeted respondents were the registered lecturers in higher education institutes of Sri Lanka, selected based on simple random sampling method. Structural equation modelling (SEM) procedure was employed for data analysis using IBM SPSS (ver.21) and AMOS (Ver.26). The structural path analysis resulted in partial mediation, confirming that “lecturer’s innovativeness in IT” exerts its influence on VLE adoption intention by altering the mediators set in the study. Further, the study validated a unique set of factors that determine lecturer’s acceptance of VLE in a higher education setting.

Finance and indebtedness remain major problems for most countries, especially developing countries it therefore requests to stand in front of them to reduce them and prevent their exacerbation, Global rating agencies are a reflection of the urgent need for investors and borrowers to identify factors affecting creditworthiness to bridge the existing information gap. Iraq was approved for the period 2004-2017 using a model (Toda Yamamota Causility) The desire to provide information on the level of risk before lending to the government or financial and banking institutions to assess the solvency and the desire to meet debts to meet current and future financial obligations in a timely manner, and the degree of rating is not an absolute fact, but expect to the current financial situation may err and may infect, However, creditworthiness indicators remain the most important criteria for assessing the likelihood of the borrower not repaying the loan amount. The researcher concluded that the most important variable affecting the sovereign creditworthiness of Iraq is debt service, especially in the short term On the other hand, the availability of liquidity gives great flexibility to Iraq in the payment of its obligations. 

Information Management and Analysis (IMA) implies the single data and knowledge base of the business organization whose algorithm and software complex is designed to solve functional problems of operating and dispatch management, marketing, financial arrangements, accounting, strategic planning and organizing e-document flow between the sources and users of information. The “information – communication - control” vector is directed at the achievement of corporate objectives. Assessment of IMA implementation efficiency is complicated by the fact that implementation of managerial (informational) solutions is possible indirectly, with the flows of material, financial and informational resources; the IMA algorithms are valid for a certain range of situations and modes, whose frequency and duration of action are not known in advance. The study is aimed at formalizing compatibility conditions for a set of economic and technical, actual, and probabilistic indicators applied for justifying the IMA implementation efficiency for industrial entrepreneurship. The IMA effectiveness is expected to be calculated as a total of network (communication) effects per each block of IMA algorithms, factored the presentation of information operability; to calculate cost-effectiveness (recoupment of investment) it is supposed to modernize the structural capital evaluation procedure according to A.Puliс. The article contains an introduction, concept of IMA, application of system efficiency theory to IMA, building the structure of IMA efficiency indicators, and conclusion. The main method of study: system approach.

Achieved wireless networks since its beginning the prevalent wide due to the increasing wireless devices represented by smart phones and laptop, and the proliferation of networks coincides with the high speed and ease of use of the Internet and enjoy the delivery of various data such as video clips and games. Here's the show the congestion problem arises and represent   aim of the research is to avoid congestion at APs to wireless networks by adding a control before congestion occurs. A wireless connection was made using the Android system, and congestion was predicted based on the analysis of wireless communication packages around the access point using the LSTM deep learning model. The results show that if the amount of information in the input data is large, a more accurate prediction can be made.

Persian language is one of the most widely used languages in the Web environment. Hence, the Persian Web includes invaluable information that is required to be retrieved effectively. Similar to other languages, ranking algorithms for the Persian Web content, deal with different challenges, such as applicability issues in real-world situations as well as the lack of user modeling. CF-Rank, as a recently proposed learning to rank data, aims to deal with such issues by the classifier fusion idea. CF-Rank generates a few click-through features, which provide a compact representation of a given primitive dataset. By constructing the primitive classifiers on each category of click-through features and aggregating their decisions by the use of information fusion techniques, CF-Rank has become a successful ranking algorithm in English datasets. In this paper, CF-Rank is customized for the Persian Web content. Evaluation results of this algorithm on the dotIR dataset indicate that the customized CF-Rank outperforms baseline rankings. Especially, the improvement is more noticeable at the top of ranked lists, which are observed most of the time by the Web users. According to the NDCG@1 and MAP evaluation criteria, comparing the CF-Rank with the preeminent baseline algorithm on the dotIR dataset indicates an improvement of 30 percent and 16.5 percent, respectively.

For the last three decades, research on Information Technology Business Value (ITBV) has highlighted how organizations can create greater value from IT investments in different industries, including the healthcare sector. There has been some research investigating the business value of Health Information Systems (HIS). However, the current body of knowledge regarding the challenges in front of proper business value realization of these systems is limited. This study investigates the challenges of HIS business value creation using a combination of the Fuzzy Analytic Hierarchy Process (FAHP) and fuzzy Decision-making Trial and Evaluation Laboratory (DEMATEL). First, this study reviews the literature to identify the main challenges in the field. The outcome of this step revealed three main categories and 22 challenges, including technological (ten challenges), organizational (eight challenges), and environmental (four challenges). Then, this study first uses FAHP to evaluate the weighting for each criterion and then adopts the fuzzy DEMATEL method to establish contextual relationships among those criteria. We find out that technological challenges are the most crucial dimension. Moreover, we observed that “infrastructure costs” has the highest priority. Under the technological dimension, “maintenance costs” and “systems compatibility” challenges are the most critical since they are in the cause area and directly influence the HIS outcomes. Under the organizational dimension, “Change in strategic objectives” is the most important challenge. Moreover, “inter-departmental coordination”, “training costs”, “proficiency”, and “users’ knowledge” are affected by each other as well as influenced by the net causes. The outcome of this study shows that to handle HIS business value creation challenges, healthcare executives should start with infrastructure costs, maintenance costs, and systems compatibility challenges.

Smart applications with interconnected intelligent devices for sharing services arise serious security problems to the stability of this IoT complex and heterogeneous environment. Unless security considerations are analyzed and implemented properly in real time then IoT cannot be perceived as a pervasive network for the possible stakeholders. Current state of the art has analyzed trust-based security solutions as additional feature to application layer of the system which can identify and filter out the malicious nodes. In this paper we are proposing holistic trust management with edge computing mechanism to create trustworthy zones comprising different clusters, where Gateway on behalf of clusters will initiate migration of their nodes if falls below the defined Zone trust threshold level. The created zones are self-resilient against any malicious attacks and saves lots processing usage time and energy to address the security issues. By analyzing our proposed algorithm with other contemporary approaches to handle IoT security issues using trust mechanism, this approach is more precise in terms of protecting system against incurring malicious behavior, and also prolong the application operation duration by reducing communication and processing overhead.

The coronavirus pandemic has compelled academic institutions across the globe to initiate online teaching, impacting thereby the teaching-learning process to undergo a structural change. Among various pedagogical techniques that have been adopted, organizing synchronous classes has been found to be the most beneficial. It simulates the classroom environment, facilitating thereby parallel knowledge dissemination to a broader audience. This study measures the efficacy of synchronous web-based learning during this ongoing pandemic, among postgraduate Library and Information Science (LIS) students of Bangladesh. Using an online questionnaire, a survey was conducted among the postgraduate students of the Department of Information Science Library Management (ISLM) of the University of Dhaka. The results revealed that limitation of internet data, unstable internet, along with power blackouts were some of the primary inhibitors blocking the participants to attend classes online. Finally, this study concludes that as most students do not seem to be ready yet to study in a synchronous delivery mode, it recommends educational institutions in Bangladesh to provide an alternative delivery method, in order to sustain academic excellence in these challenging times.

The continuing outbreak of COVID-19 pneumonia is globally concerning. Timely detection of infection ensures prompt quarantine of patient which is crucial for preventing the rapid spread of this contagious disease and also supports the patient with necessary medication. Due to the high infection rate of COVID-19, our health management system needs an automatic diagnosis tool that equips the health workers to pay immediate attention to the needy person. Chest CT is an essential imaging technique for diagnosis and staging of 2019 novel coronavirus disease (COVID-19). The identification of COVID-19 CT findings assists health workers on further clinical evaluation, especially when the findings on CT scans are trivial, the person may be recommended for Reverse-transcription polymerase chain reaction (RT-PCR) tests. Literature reported that the ground-glass opacity (GGO) with or without consolidation are dominant CT findings in COVID-19 patients. In this paper, the U-Net based segmentation approach is proposed to automatically segment and analyze the GGO and consolidation findings in the chest CT scan. The performance of this system is evaluated by comparing the auto-segmented infection regions with the manually-outlines ones on 100 axial chests CT scans of around 40 COVID-19 patients from SIRM dataset. The proposed U-Net with pre-process approach yields specificity of 0.91 ± 0.09 and sensitivity of 0.87 ± 0.07 on segmenting GGO region and specificity of 0.81 ± 0.13 and sensitivity of 0.44 ± 0.17 on segmenting consolidation region. Also the experimental results confirmed that the automatic detection method identifies the CT finding with a precise opacification percentage from the chest CT image.