ترتیب بر اساس: جدیدترینپربازدیدترین
فیلترهای جستجو: فیلتری انتخاب نشده است.
نمایش ۱۶۱ تا ۱۸۰ مورد از کل ۲٬۹۱۷ مورد.
۱۶۱.

Understanding Customer Satisfaction of Chatbots Service and System Quality in Banking Services(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Chatbots System quality service quality Customer Satisfaction

حوزه‌های تخصصی:
تعداد بازدید : ۵۷۶ تعداد دانلود : ۳۲۸
Chatbots is a computer software powered by artificial intelligence designed to replicate human interaction. It is also possible to refer to them as digital assistants that comprehend the capacities of humans. The bot interprets the user's intent, then processes their queries and provides prompt responses. Chatbots perform their most crucial role: to analyse and detect the intent of the user's request to extract relevant entities. AI-powered chatbots were introduced to improve operational efficiency, eventually saving organisational costs. This study investigates the role of system and service quality in customer satisfaction in banking services. One hundred forty-five usable data were used for analysis. Data were analysed using the Smart PLS. The results revealed that response time, usability, adaptability, empathy and responsiveness were insignificant for customer satisfaction. The result is important as it gave the insight point of customers with regards to the new services. Business organisations may need to introduce chatbots and perhaps make some improvements from time to time to provide better services.
۱۶۲.

Bibliometric Analysis of Government Venture Capital(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Venture Capital Government Investments Innovation Entrepreneurship

حوزه‌های تخصصی:
تعداد بازدید : ۴۳۷ تعداد دانلود : ۳۱۹
The bibliometric study aims to map and expand respective knowledge by establishing connections between important actors in academic research regarding the government venture capitals (GVCs). The scope is to analyze documents published on Scopus database starting from 2011 to 2020.  Accordingly, the United States (U.S.) is the top country in all categories with China catching up. Alperovych, Quas, and Colombo are top co-authors. On the other hand, Leleux, Grilli, Lerner and Cumming are prolific authors. Articles by Grilli and Li Y are two most cited documents. Investments, venture capital, economics, public policy, and government are most co-occurrence index keywords. Research policy, venture capital, and journal of technology transfer, journal of business venturing and small business economics are top sources of cited documents. Closely associated themes with respect to the study of GVCs are government role in venture capital support, effective Innovation financing policies, performance differential, performance of portfolio companies, funding challenges and investment strategy, decision making model and critical success factors for IT startups. The analysis generated gaps and directions for future research consisting of fund’s structure and characteristics, key personnel’s work experience and network, geographic location, investment horizon, shareholding rights.
۱۶۳.

Investment Project Risk Simulation on the Use of Information Technologies as a Factor for Improving the Financial Safety of the Enterprise(مقاله علمی وزارت علوم)

نویسنده:

کلیدواژه‌ها: Financial security risk Investment Investment project Simulation Modelling information technologies

حوزه‌های تخصصی:
تعداد بازدید : ۲۷۰ تعداد دانلود : ۱۹۳
The article justified the feasibility of an investment project by analysing the performance indicators while taking into account risk and uncertainty of the use of information technologies. The impact of the above calculations of the investment project results is due to the fact that the evaluation of the investment performance depends on the projected cash flows. The purpose of the article is to assess the impact of risks on making investment decisions using information technologies in order to increase the financial security of enterprises. Methodological and practical aspects of risk modelling of the investment project were further developed, using the Monte Carlo method, which allows to construct a model by minimizing data, as well as to maximize the value of data used in the model. This model involves the use of probability theory and random number tables. The results show the distribution of probabilities of the successful project variable and the coefficient of variation of the performance indicator, allowing the investor to take uncertainty into account when making a decision.
۱۶۴.

Multi- Objective Fuzzy Software Release Problem with learning capacities for fault detection and correction processes(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Software Reliability Software Reliability Growth Models Fuzzy Release Time Problem Software Development Life Cycle

حوزه‌های تخصصی:
تعداد بازدید : ۳۴۹ تعداد دانلود : ۱۸۷
Without utilization of computer and its related technology, modern day’s life cannot be headway. It has also transformed into an incredibly troublesome task. The genuine challenges included are shorter life cycles, cost effective and higher software quality goals. Despite these challenges the software developers have started to give cautious thought on to the procedure to develop software, testing and reliability investigation of software and to reinforce the method. Developer most fundamental decisions related to the perfect release time of Software. Software development method incorporates a piece of vulnerabilities and ambiguities. We have proposed a multi objective software release time issue under fuzzy environment using a software reliability growth model to overcome such vulnerabilities and ambiguities. Further we have discussed the fuzzy environment framework to deal with the issue. Considering model and issue, we can especially address the issue of when to release software under these conditions. Results are illustrated numerically.
۱۶۵.

Unpacking the Dynamics of Digital Entrepreneurship: Managing Work-Family Boundaries among Women Entrepreneurs(مقاله علمی وزارت علوم)

نویسنده:

کلیدواژه‌ها: Digital entrepreneurship Women Entrepreneurs Degrees of digitalization Work-Family Boundary management

حوزه‌های تخصصی:
تعداد بازدید : ۴۱۳ تعداد دانلود : ۲۵۶
The global spread of internet technology and the associated advancements are making it easier for women entrepreneurs to manage the work-family boundary. However, there is a need for more research on digital entrepreneurship (DE), especially on how different degrees of DE influence the success of work-family boundary management (WFBM). This study explores the effect of extreme, moderate, and mild pursuit of DE on women’s abilities to manage the boundary between work and family. This study uses a quantitative research method and collected data from 312 women entrepreneurs. The results show that DE enables women entrepreneurs to manage the work-family boundary. We found that with extreme DE, women are more likely to experience high levels of cross-role interruption behaviours and perceived boundary control, while with moderate DE, women experience high levels of identity centrality of work and family roles. Therefore, this study contributes to the literature on women’s DE by investigating different degrees of DE and its effects on work-family boundary management. The study also contributes to the literature on WFBM through examining the dynamics of DE in enabling women entrepreneurs to manage work-family boundaries to different extents. Therefore, this study captures the interplay between DE and managing work-family boundaries, which facilitates our understanding of women entrepreneurship and the role DE has in enabling the agentic potential of entrepreneurial actors.
۱۶۶.

Range of Publications for E-Government Services: a Review and Bibliometric Analysis(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Government Public e-services bibliometric analysis Network analysis E-government Researchv

حوزه‌های تخصصی:
تعداد بازدید : ۳۰۴ تعداد دانلود : ۱۹۳
With the rapid advancement of information and communication technology (ICT), public administration has adopted the concept of e-government. The academic literature produced many studies in the field of E-government (E-GOV) services, however, there is limited research on such services from the perspective of bibliometric and Network analysis. Therefore, this study aims to present a bibliometric and network analysis of the E-government services literature review obtained from the Scopus database, published between 2011 to 2021. This study uses a five-step method including (1) defining keywords, (2) initializing search outcomes, (3) inclusion and exclusion of some elements of the initial result, (4) compiling initial data statistics, and (5) undertaking analysis of data. The analysis starts by identifying more than 4,880 published articles related to E-government services published between 2011 and 2021. The study findings revealed that the highest number of publications on the E-government Service was in 2019 (102 articles), the top contributing affiliation was Brunel University London, the leading influential country was the USA, and the top contributing Source was Electronic Government. Furthermore, Lu J. occupied the first rank in the list of the most influential authors in terms of citations, while Weerakkody V. occupied the list of the top authors with high publications 20 papers. Likewise, this study showed that there is a collaboration among some authors. This research identified four research clusters by which researchers could be encouraged to widen the research of E-government services in the future. The bibliometric and network analysis of E-government services helps to graphically display the publication's assessment over time and identify domains of current studies' interests and potential directions for further studies. Finally, this research draws a roadmap for future investigation into E-government services.
۱۶۷.

Cucumber Leaf Disease Detection and Classification Using a Deep Convolutional Neural Network(مقاله علمی وزارت علوم)

کلیدواژه‌ها: DCNNs (Deep Convolution Neural Network) CNNs (Convolution Neural Network) Classification

حوزه‌های تخصصی:
تعداد بازدید : ۳۳۲ تعداد دانلود : ۱۳۹
Due to obstruction in photosynthesis, the leaves of the plants get affected by the disease. Powdery mildew is the main disease in cucumber plants which generally occurs in the middle and late stages. Cucumber plant leaves are affected by various diseases, such as powdery mildew, downy mildew and Alternaria leaf spot, which ultimately affect the photosynthesis process; that’s why it is necessary to detect diseases at the right time to prevent the loss of plants. This paper aims to identify and classify diseases of cucumber leaves at the right time using a deep convolutional neural network (DCNN). In this work, the Deep-CNN model based on disease classification is used to enhance the performance of the ResNet50 model. The proposed model generates the most accurate results for cucumber disease detection using data enhancement based on a different data set. The data augmentation method plays an important role in enhancing the characteristics of cucumber leaves. Due to the requirements of the large number of parameters and the expensive computations required to modify standard CNNs, the pytorch library was used in this work which provides a wide range of deep learning algorithms. To assess the model accuracy large quantity of four types of healthy and diseased leaves and specific parameters such as batch size and epochs were compared with various machine learning algorithms such as support vector machine method, self-organizing map, convolutional neural network and proposed method in which the proposed DCNN model gave better results.
۱۶۸.

F-MIM: Feature-based Masking Iterative Method to Generate the Adversarial Images against the Face Recognition Systems(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Adversarial attack Black-box attack Dodging attack Face Recognition Feature based attack

حوزه‌های تخصصی:
تعداد بازدید : ۳۴۲ تعداد دانلود : ۱۴۶
Numerous face recognition systems employ deep learning techniques to identify individuals in public areas such as shopping malls, airports, and other high-security zones. However, adversarial attacks are susceptible to deep learning-based systems. The adversarial attacks are intentionally generated by the attacker to mislead the systems. These attacks are imperceptible to the human eye. In this paper, we proposed a feature-based masking iterative method (F-MIM) to generate the adversarial images. In this method, we utilize the features of the face to misclassify the models. The proposed approach is based on a black-box attack technique where the attacker does not have the information related to target models. In this black box attack strategy, the face landmark points are modified using the binary masking technique. In the proposed method, we have used the momentum iterative method to increase the transferability of existing attacks. The proposed method is generated using the ArcFace face recognition model that is trained on the Labeled Face in the Wild (LFW) dataset and evaluated the performance of different face recognition models namely ArcFace, MobileFace, MobileNet, CosFace and SphereFace under the dodging and impersonate attack. The F-MIM attack is outperformed in comparison to the existing attacks based on Attack Success Rate evaluation metrics and further improves the transferability.
۱۶۹.

Net Asset Value (NAV) Prediction using Dense Residual Models(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Net Asset Value NAV prediction Mutual Funds N-BEATS FLANN LSTM

حوزه‌های تخصصی:
تعداد بازدید : ۳۷۶ تعداد دانلود : ۱۷۱
Net Asset Value (NAV) has long been a key performance metric for mutual fund investors. Due to the considerable fluctuation in the NAV value, it is risky for investors to make investment decisions. As a result, accurate and reliable NAV forecasts can help investors make better decisions and profit. In this research, we have analysed and compared the NAV prediction performance of our proposed deep learning models, such as N-BEATS and NBSL, with the FLANN model in both univariate and multivariate settings for five Indian mutual funds for forecast periods of 15, 20, 45, 63, 126, and 252 days using RMSE, MAPE, and R2 as evaluation metrics. A large forecast horizon was chosen to assess the model's consistency, reliability, and accuracy. The result reveals that the N-BEATS model outperforms the FLANN and NBSL models in the univariate setting for all datasets and all prediction horizons. In a multivariate setting, the outcome demonstrates that the N-BEATS model outperforms the FLANN model across all datasets and prediction horizons. The result also shows that, as the number of forecast days grew, our suggested models, notably N-BEATS, maintained consistency and attained the highest R2 value throughout the longest forecast duration.
۱۷۰.

Forensic Research of the Computer Tools and Systems in the Fight against Cybercrime(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Forensic research Computer tools and systems cybercrime

حوزه‌های تخصصی:
تعداد بازدید : ۴۰۳ تعداد دانلود : ۳۰۹
The cybersecurity in the modern world has become global, and cyber attacks are becoming more complex and large-scale. In the system of civil and criminal justice, computer forensics helps to ensure the integrity of digital evidence presented in court cases. The purpose of this study is to develop scientifically sound proposals and recommendations for the implementation of tools for forensic research of computer tools and systems in the fight against cybercrime. The relevance of this study is due to the need to implement active ways to protect and combat cybercrime. To achieve the goal of the study, methodological principles and approaches of legal science were used. It is proposed to use computer forensic methods more widely research in the fight against cybercrime.This study identifies the types of computer forensics: forensics database; electronic forensics; malware forensics; criminology of memory; mobile forensics; network forensics. The authors foundlack of a regulatory mechanism to regulate cybersecurity, capture and use of digital evidence and the regulatory framework for international cooperation. To brought need in strengthening international cooperation and in developing appropriate policies and legislative initiatives of security and network and information systems, improvement legislation in the field countering cybercrime.
۱۷۱.

Efficient Machine Learning Algorithms in Hybrid Filtering Based Recommendation System(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Recommender System Content-Based Filtering collaborative filtering Movie Recommendation deep learning

حوزه‌های تخصصی:
تعداد بازدید : ۳۱۵ تعداد دانلود : ۱۷۹
The widespread use of E-commerce websites has drastically increased the need for automatic recommendation systems with machine learning. In recent years, many ML-based recommenders and analysers have been built; however, their scope is limited to using a single filtering technique and processing with clustering-based predictions. This paper aims to provide a systematic year-wise survey and evolution of these existing recommenders and analysers in specific deep learning-based hybrid filtering categories using movie datasets. They are compared to others based on their problem analysis, learning factors, data sets, performance, and limitations. Most contributions are found with collaborative filtering using user or item similarity and deep learning for the IMDB datasets. In this direction, this paper introduces a new and efficient Hybrid Filtering based Recommendation System using Deep Learning (HFRS-DL), which includes multiple layers and stages to provide a better solution for generating recommendations.
۱۷۲.

نقش تفکر انتقادی در فرایند مدیریت دانش(مقاله علمی وزارت علوم)

کلیدواژه‌ها: مدیریت دانش تفکر انتقادی مرور انتقادی

حوزه‌های تخصصی:
تعداد بازدید : ۵۶۸ تعداد دانلود : ۳۹۱
مدیریت دانش[1] و تفکر انتقادی[2] دو پدیده گسترده و مهم برای سازمان ها و جامعه معاصر هستند و به خوبی مفاهیم مرتبط با آنها در ادبیات نظری علم مدیریت دانش و تفکر انتقادی بحث شده است. بااین حال، پیوندهای مفهومی موجود بین مدیریت دانش و تفکر انتقادی کمتر مورد تجزیه وتحلیل قرار گرفته و نقش تفکر انتقادی در فرایند مدیریت دانش به خوبی تبیین نشده است. هدف از این نوشتار، پر کردن این شکاف نظری و ارائه ارتباطات مفهومی بین مدیریت دانش و تفکر انتقادی است. تجزیه وتحلیل مفاهیم تفکر انتقادی و مدیریت دانش امکان شناسایی پیوندها را در سه بعد فراهم می کند.
۱۷۳.

Analyzing Hospital Services Quality Using a Hybrid Approach: Evidence from Information Technology(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Health information technology Patient satisfaction Kano Model AHP technique QFD model

حوزه‌های تخصصی:
تعداد بازدید : ۳۵۷ تعداد دانلود : ۲۱۳
Hospitals are the most important part of the healthcare system. Statistics show that a significant portion of health budgets are allocated to hospitals. The continuous impact of information technology on hospitals’ performance has led to perfect competition. Accordingly, this study aimed to evaluate the quality indicators of hospital services considering information technology using a hybrid approach of the Kano model, Analytical Hierarchy Process (AHP), and Quality Function Deployment (QFD). In this regard, based on related studies, a total of 18 needs were recognized to evaluate the service quality of a hospital. The statistical population of the study consisted of patients of the hospital and due to the difficulty of access to the patient, a limited sample of 50 patients was selected. After collecting data, the identified needs were classified into three categories called basic, functional, and motivational using the Kano model, and 7 needs were set as basic needs. Then, using the AHP technique, the importance of the basic needs was calculated and considered as the input of the QFD model in the next phase. After providing some solutions based on the literature to meet these 7 needs, solutions were ranked and prioritized using the QFD model. Since the organization had limited resources, the Pareto technique was used to respond to 20% of these strategies and achieve 80% satisfaction. The results of the study showed that the hospitals can achieve 80% satisfaction by implementing the strategies of “holding ethics training courses online” and “creating team spirit and using health information technology in the hospital”, respectively.
۱۷۴.

State Regulation Improvement of the Military-Industrial Complex Development in Ukraine in Terms of Transition to Modern Information Technologies(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Defense and Security of the State State Regulation military-industrial complex information technologies Scientific and Technical Potential Innovative development

حوزه‌های تخصصی:
تعداد بازدید : ۲۵۲ تعداد دانلود : ۱۷۷
The military and political leadership of Ukraine considers the domestic military-industrial complex as an important component of the country's national security and defense strategy and pays special attention to increasing the efficiency of production and scientific and technical activities of defense industry enterprises and organizations. The study represents directions for improving the state regulation for the further development of the military-industrial complex in Ukraine under the conditions of the transition to modern information technologies. Proposals have been made for the formation of the organizational and economic mechanism for state regulation development of the military-industrial complex, aimed at ensuring its innovativeness, stimulating scientific and technical activity, and implementing modern information technologies systematically during the production of weapons, ammunition and military goods.
۱۷۵.

Informational and Analytical Systems for Forecasting the Indicators of Financial Security of the Banking System of Ukraine(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Financial security Information–Analytical System banking system Banking Security Forecast Models Financial Stability State

حوزه‌های تخصصی:
تعداد بازدید : ۲۹۶ تعداد دانلود : ۱۹۵
The article is devoted to the modern development of high technologies and computer technology greatly enhanced the development of automated banking systems of banking sector organizations and allowed the synthesis of information and communication technologies for their formation. The main purpose of the article is to select the main indicators for assessing the level of financial security of the banking system of the state and identify promising areas of its development using forecasting models. In the process of research such analytical functions have been used: polynomial, exponential, power and logarithmic. The authors believe that the information and analytical provision of the financial security of the bank is an information provision that combines, on the one hand, information work, that is, ways, means and methods of collecting the necessary information, and on the other - analytical work, which includes forms and methods of information analysis and processing, which ensures an objective assessment of the situation and the adoption of a balanced management decision. As a result, forecast models were built for each of the indicators and also, it has been found that most indicators of the banking system of Ukraine in 2021-2023 will remain at “unsatisfactory” and “critical” levels. In conclusions it was proposed to introduce measures that would be aimed at improving the reliability and stability of the banking system of Ukraine.
۱۷۶.

The Digital Transformation of Creative Industries as a Management Imperative of Information Security of Society on a Parity-Legal Basis(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Digital Transformation Creative Industries Imperatives System-Reflexive Management Information security

حوزه‌های تخصصی:
تعداد بازدید : ۳۵۱ تعداد دانلود : ۱۸۷
The article defines that the composition and structure of creative industries, their branch specialization and cooperation, the scale and directions of development of industrial and other relations are determined by means of solving spatial problems and are conditioned by the level of digital transformation as imperative system-reflex management of information security of society at parity-legal principles. The process of formation of digital transformation of creative industries as an imperative of system-reflexive management of information security of society on a parity-legal basis in modern conditions today must meet globalization challenges that dictate the development of the country's economy as a whole. This should be manifested in the application of modern integration models for the formation and development of creative industries. It is substantiated that the main tasks of the strategy of financial capacity for digital transformation of creative industries as an imperative of system-reflexive management of information security of society on a parity-legal basis are to achieve balance of financial opportunities and needs of industries, efficiency of their financial relations, efficiency of processes of formation, movement, allocation and use of financial resources, rational structure of sources of financial resources, under which is possible stable financial support of digital transformation.
۱۷۷.

Generation of Syntax Parser on South Indian Language using Bottom-Up Parsing Technique and PCFG(مقاله علمی وزارت علوم)

کلیدواژه‌ها: Natural Language Processing Artificial Intelligence Syntax Parser CYK Parsing Algorithm Probabilistic Context Free Grammar

حوزه‌های تخصصی:
تعداد بازدید : ۶۰۴ تعداد دانلود : ۳۰۱
In our research, we provide a statistical syntax parsing method experimented on Kannada texts, which is an official language of Karnataka, India. The dataset is downloaded from TDIL website. Using the Cocke-Younger-Kasami (CYK) parsing technique, we generated Kannada Treebank dataset from 1000 annotated sentences in the first stage. The Treebank generated in this stage contains 1000 syntactically structured sentences and it is used as input to train the syntax parser model in the second stage. We have adopted Probabilistic Context Free Grammar (PCFG) while training the parser model and extracting the Chmosky Normal Form (CNF) grammar from a Treebank dataset. The developed syntax parser model is tested on 150 raw Kannada sentences. It outputs with the most likely parse tree for each sentence and this is verified with golden Treebank. The syntax parser model generated 74.2% precision, 79.4% recall, and 75.3% F1-score respectively. The similar technique may be adopted for other low resource languages.
۱۷۸.

Exemplary Growth Through Online Shopping With Satisfied Consumers In Vellore District(مقاله علمی وزارت علوم)

نویسنده:

کلیدواژه‌ها: Consumer behavior Fondness factors Online shopping Repurchase Satisfaction and Technology development

حوزه‌های تخصصی:
تعداد بازدید : ۳۸۱ تعداد دانلود : ۲۷۶
The rapid emergence and evolution of technology have greatly impacted the way people live their lives. The internet has become a vital part of our daily lives. E-commerce is a type of technology development that enables customers to buy and sell products online. It is a unique form of transaction that connects people from all around the world. Today, many consumers shop for products online and present their products along with their specifications. This is becoming more prevalent. This increases the number of consumers online, which can result in a drop in growth. This is one of the main factors that a company uses to measure its success. Growing business success is revealed with retained customers. Satisfied consumers are the assets for a growing business. The study investigates the factors that influence people's decisions when it comes to buying items online. It shows that the experiences they have while shopping online can affect their decisions. The following statistical tools were applied for this study: percentage analysis, mean score with rank correlation, and t-Test. The results reveal that the factors quality, cost, product variety, uniqueness, and safety payments were highlighted as important indicators of performance and that the companies that do online businesses had to take care of their main goal as per the proposal.
۱۷۹.

Prediction of Type - I and Type –II Diabetes: A Hybrid Approach using Fuzzy Logic and Machine Learning Algorithms(مقاله علمی وزارت علوم)

کلیدواژه‌ها: diabetes Blood sugar Machine Learning Algorithm Fuzzy Logic Disease Management risk factors insulin resistance polynomial regression Support vector regression

حوزه‌های تخصصی:
تعداد بازدید : ۲۵۴ تعداد دانلود : ۱۷۳
Diseases like diabetes are chronic and require long-term management. Inadequate production of insulin results in high blood sugar levels. Such diseases lead to serious health issues such as heart ailments, blood vessel complaints, eye ailments, kidney function disorders, and nerve ailments. Hence, accurate assessment and management of risk factors are crucial for the onset of diabetes. Our proposed approach combines fuzzy logic & machine learning algorithms for diabetes risk prediction. Three machine learning models were trained to classify patients into two categories of diabetes (Type-I and Type-II) based on their clinical dataset collected from Katihar Medical College & Hospital and Suvadhan Lab. The polynomial regression algorithm achieved a score of 0.947, while the support vector regression algorithm with the rbf kernel achieved a score of 0.954, with a linear kernel achieved a score of 0.73. Our proposed approach performed well with respect to the conventional approaches with improved accuracy by identifying the patients at diabetes risk. In future work, we further analyze the relationship between other ignored factors which contribute to diabetes risk.
۱۸۰.

Real-Time Deep Intelligence Analysis and Visualization of COVID-19 Using FCNN Mechanism(مقاله علمی وزارت علوم)

کلیدواژه‌ها: DNA RNA sequence COVID-19 SARS-CoV-2 Coronavirus pandemic

حوزه‌های تخصصی:
تعداد بازدید : ۴۵۹ تعداد دانلود : ۳۰۴
The Analytic visualization suggests representing knowledge during a visual type that may be charts, graphs, lists, or maps. The COVID 19 detection and analysis of spreading is very important for countries. Database management with respect to virus deep analysis is a critical task to the researcher through conventional algorithms. The RNA, DNA, and biological data are helping to the bio-inspired algorithm but its implementation can be complex by software tools. Therefore, an effective technique is required to cross over the above limitations. So that covid 19 pandemic data analysis is performed through FCNN (Fully conventional Neural Network) pre-training network. The dataset is collected from social media, Kaggle, and GitHub databases. At 1st stage, the auto stack encoding process is applied later same data is processed with FCNN deep learning classifier. In this research work, covid-pandemic affects parameters like infected persons, deaths, active cases, and recovering cases. The FCNN is take care of feature extraction, training, testing, and classification. Finally using a confusion matrix accuracy of 98.34%, sensitivity 97.63%, Recall 98.26%, and F measure 98.83% had been estimated.

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