درخت حوزه‌های تخصصی

Developed an integrated intellectual computerized system of ecological-economic monitoring, modeling, and managing the life cycle of the products of technogenic enterprises of transport engineering, which is presented in the form of a 3-equation structure, functioning in conditions of instability. The proposed paradigm system life cycle management applicable to any other control system of large and complex systems, such as techno-genic type. This new paradigm of complex systems and process management, including technical systems. The system is based on the following findings: concepts, principles, a set of non-linear models, decision-making methods, and the environmental and economic governance, integral criteria. As an example, in this paper offer solution to the problem of estimating the cost of the product life cycle of railway transport.

Sentiment analysis is the process of analyzing a person’s perception or belief about a particular subject matter. However, finding correct opinion or interest from multi-facet sentiment data is a tedious task. In this paper, a method to improve the sentiment accuracy by utilizing the concept of categorized dictionary for sentiment classification and analysis is proposed.  A categorized dictionary is developed for the sentiment classification and further calculation of sentiment accuracy. The concept of categorized dictionary involves the creation of dictionaries for different categories making the comparisons specific. The categorized dictionary includes words defining the positive and negative sentiments related to the particular category. It is used by the mapper reducer algorithm for the classification of sentiments. The data is collected from social networking site and is pre-processed. Since the amount of data is enormous therefore a reliable open-source framework Hadoop is used for the implementation. Hadoop hosts various software utilities to inspect and process any type of big data. The comparative analysis presented in this paper proves the worthiness of the proposed method.

The worldwide Covid-19 epidemic while affecting numerous places, has had a profound effect on virtual advertising and advertising and, globally, in the provinces and at the neighborhood level. except, this effect for the most element become positive, in contrast to what has seen in exclusive sectors which include economy, human sources, etc., whilst contamination reasons a variety of incapacity amongst clients and advertisers alike, in phrases of welfare, social work, inflation, business, and many others., the equal shifted conduct goes as a long way as running. , investing strength, getting into self-schooling, adopting new programs from the internet, expanding social and hygiene concerns, retaining distance strategies from complete regions, internet-based media willpower, get right of entry to online sources, etc., and this has greatly impacted the display and endorsed efforts. The moral movement has moved past the PC and digital international, which places open doors for advertisers and products to connect with clients more efficiently than ever before. With the arrival of expanded online media and the call for pc-generated content material, the evolved Media have given advertisers a part of the monetary freedom. At the equal time, this has, in turn, enabling advertisers to be extra proactive and to engage with the public at the same time as appearing excessive excellent demonstration programs. The purpose of this study is to explore, investigate, and recognize the effect of coronavirus on the digital market and businesses.

The Internet of things has become an interesting area of research in the last few years due to its ability to make human life simple and easier. Quality of Services (QoS) has gained a lot of importance due to the increasing popularity of the technology. QoS metrics help the IoT users to understand and express their requirements for the selection of services provided by IoT. Researchers in this field have come up with different types of architectures to provide a better view and define all the functions of the technology. In this paper, we have defined a few of the architectures and QoS metrics related to these architectures.

The human machine interface research in the light of modern fast computers and advanced sensors is taking new heights. The classification and processing of neural activity in the brain accessed by Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET), functional Magnetic Resonance Imaging (fMRI), Electrocorticography (ECoG), EEG Electroencephalogram (EEG) etc., are peeling off new paradigms for pattern recognition in human brain-machine interaction applications. In the present paper, an effective novel scheme based upon a synergetic approach employing the Genetic Algorithm (GA), Support Vector Machine and Wavelet packet transform for motor imagery classification and optimal Channel selection is proposed. GA with SVM acting as the objective function is employed for simultaneous selection of features and channels optimally. The binary population of GA is uniquely represented in three-dimensional structure and a new cross-over operator for GA are introduced. The new modified cross-over operator is proposed for the modified three-dimensional population. The ‘data set I’ of ‘BCI Competition IV’ is taken for evaluation of the efficacy of the proposed scheme. For subject ‘a’ accuracy is 88.9 6.9 with 10 channels, for subject ‘b’ accuracy is 79.20±5.36with 11 channels, for subject ‘f’ accuracy is 90.50±3.56 with 13 channels, and for subject ‘g’ accuracy is 92.23±3.21with 12 channels. The proposed scheme outperforms in terms of classification accuracy for subjects ‘a, b, f, g’ and in terms of number of channels for subject ‘a’ and that for subject ‘b’ is same as reported earlier in literature. Therefore, proposed scheme contributes a significant development in terms of new three-dimensional representation of binary population for GA as well as significant new modification to the GA operators. The efficacy of the scheme is evident from the results presented in the paper for dataset under consideration.

On a global scale, one of the prevalent causes of dementia is Alzheimer’s disease (AD). It will cause a steady deterioration in the individual from the mild stage to the severe stage, and thus impair their capacity to finish any tasks with no aid. The diagnosis is done with the utilization of existing methods which include medical history; neuropsychological testing as well as MRI (Magnetic Resonance Imaging), a lack of sensitivity as well as precision does affect the consistency of efficient procedures. With the deep learning network’s utilization, it is possible to create a framework for detecting specific AD characteristics from the MRI images. While automatic diagnosis is done with the application of diverse machine learning techniques, the existing ones do suffer from certain constraints with regards to accuracy. Thus, this work’s key goal is to increase the classification’s accuracy through the inclusion of a pre-processing approach prior to the deep learning model. The Alzheimer's disease Neuroimaging Initiative (ADNI) database of AD patients was used to develop a deep learning approach for AD identification. In addition, this study will present ideas for Haralick features, feature extraction from Local Binary Pattern (LBP), Artificial Neural Network (ANN), and Visual Geometry Group (VGG)-19 network techniques. The results of the experiments show that the deep learners offered are more effective than other systems already in use.

This paper focuses on the contribution of digital government (DGOV) to Whistleblowing (WB). While considerable efforts have been devoted to DGOV and WB separately, research work at the intersection of these two domains is very scarce; hence and a systematic DGOV for WB (DGOV4WB) research framework has yet to emerge. This paper aims to identify the potential issues in whistleblowing and explore how digital government has been used to address these issues. To this end, this paper uses explanatory case study research methodology and analyses four case studies of existing DGOV initiatives with explicit WB dimensions. The result of the cross-case analysis shows that DGOV4WB initiatives contribute to address goals of the different dimensions of whistleblowing. The most common WB problems addressed are: easily accessible reporting and response whistleblowing channels (Whistleblowing Procedure), easy and timely communication channel with top management (Whistleblowing Organizational culture), and anonymous and confidential communication platforms (Whistleblower Protection). In addition, based on the analysis of the case studies, all the initiatives are classified as either engagement or contextualization stage of the digital government evolution model.

Enterprise Social Media (ESM) has been normally embraced by companies to boost team performance and agility for workers. The goal of this study is to investigate the mediating effect of workplace isolation on the relationships among usage ESM, employee agility and Team Performance along with exploration of the moderating influence of workplace Integrational study model. This research adds to corporate awareness in illustrating the impact of ESM use on team performance and employee agility based on theory of social exchange, theory of information processing and the theory of transactive memory. Cross-sectional survey was employed to collect data from telecommunication firms (public & private). 400 respondents were selected through purposive sampling technique and given close ended questionnaires, 348 questionnaires were selected for further analysis; through a number of statistical tools, after screening out the filled responses. It resulted in Suggesting ESM has a favorable effect on Employee Agility and Team Performance, but the negative relationships were observed among workplace isolation and employee agility and team performance. Further, Workplace Isolation mediated the relationship among ESM, Employee Agility and Team performance. Additionally, Workplace Integration strongly moderated the relationship between ESM and Workplace Isolation.  Experts and/or administrators should pay consideration to the impact of using ESM on agility and team performance of the workers. In addition, when implementing ESM to increase team performance they should concentrate on the extent of team diversity. By presenting the relationship between use of ESM, isolation in the workplace, workplace integration, agility of workers and performance of teams; it enriches the ESM use works by exploring the moderating functions of workplace integration while describing the beneficial consequences of workplace integration.

The article explores approaches to assessing the quality of health care sites. The main components of evaluation are identified. The author's toolkit for health site evaluation is offered. It is based on the three branches of resource competitiveness (content, technical and marketing components). Twenty parameters of site quality calculation are defined, which have the scale and are supported by determining the weights of components. The scaling of the resulting indicator is proposed. It allows designation of the level of development of the particular site in the field of health. The practical approbation of the proposed method was carried out on the example of Ukrainian sites on the topic of rehabilitation and disease prevention. The diagram of the grouping of websites on a level of development of separate components is constructed to define the further directions of work with these sites to strengthen their competitive positions in the "Health" category. The author's typology of health sites depending on the calculated numerical combinations of the quality assessment level of components is given. It also describes the state of the "ideal" mix of components of the health site, which is formed based on the balance of individual elements.

Scientific sources demonstrate different attitudes of researchers to cryptocurrencies because they treat them as a category of currency, virtual money, commodity, etc. Accordingly, the relation to the valuation and risk of cryptocurrency as an investment object is different. The purpose of the article is to identify cryptocurrency value formation factors and determine the risks of investing in cryptocurrency. Cryptocurrency is simultaneously considered a currency, an asset with uncertain income, and a specific product, the price of which is determined by the energy costs for mining new cryptocurrency blocks. Thus, the paper examines the risks of investing in cryptocurrency from several positions. First, the study identifies the factors of formation of the value and risk of cryptocurrency as ordinary money based on comparing cryptocurrency with traditional money. Unlike traditional money, cryptocurrency is not tied to the economic performance of a particular country; also, central banks do not control or regulate their mining. Instead, the cryptocurrency emissions depend on the computational capacity of the equipment used for their mining. As a financial asset, cryptocurrency can be a “financial bubble” because their value increasing often exceeds the cost of mining. On the other hand, given the emergence of cryptocurrency as a phenomenon of the information economy, the paper analyses the impact of specific technical features (cryptographic hashing algorithm, the complexity of creating new blocks, the technology of verification of mining operations, etc.) on the risk of investing in cryptocurrency assets.

This paper presents implementation of cost-effective solar powered hydroponic system with Internet of Things (IoT) for online and remote checking and controlling the system operation. The objective was to take advantage of the abundant solar energy while incorporating IoT platform into the system. The system is made up of power supply unit, control unit, Wi-Fi unit, input unit and output unit. The system monitored temperature, humidity and volume of the nutrient solution and at the same time sent online messages to the farmer. The test carried out showed that the system is working and the readings obtained online showed a ± 1% variation from the physical measurement done remotely with meters. This implies that the online control of the system operation was effective

The purpose of this paper is to identify and prioritise mobile wallet (m-wallet) key adoption factors (KAFs). 9 KAFs are proposed by authors on the basis of a systematic literature review. Authors have proposed one novel factor influencing adoption called 'contactless transactions' due to pandemic and new normal post-Covid-19. This has resulted in a total of 10 KAFs. The fuzzy TOPSIS approach is proposed to rank these key adoption factors (KAFs). Sensitivity analysis has also been conducted to check the robustness of the study. Examining the literature indicates that this study is among the first attempts to prioritise key adoption factors (KAFs) using fuzzy TOPSIS. The results show that perceived security, trust, performance expectancy, perceived ease of use and contactless transactions are among the top 5 adoption factors. The findings of this research will be beneficial for both academicians and practitioners. The key adoption factors (KAFs) proposed in the paper will help practitioners develop strategies for building a wider acceptance of m-wallet among customers. Moreover, the fuzzy TOPSIS technique discussed in this paper will apprise managers about critical factors to be focused upon. This study will provide an integrated framework for academicians to carry out further research in the field of mobile wallets.

This study aims at investigating the factors that affect a user’s satisfaction of accounting information systems based on the quality and the perceived usefulness of such systems, and the quality of data involved. The paper analyses the given factors on data collected from Bank Sumut,  Indonesia. In addition, this research also aims to find out whether the influence of perceived ease of use can be utilized as a moderating variable or not. the research is quantitative in terms of methodology and the sample pool consists of 112 people. The data used is primary data, which has been collected through the distribution of a questionnaire. Data has been analyzed through the Multiple Linear Regression and moderator test has been done using the Eviews 9 and SPSS software. The results contained in this study show that the variables can influence the accounting information system (AIS) user satisfaction significantly and that the information system quality plays an important role in the process. In addition, the quality of information systems, the information quality and perceived usefulness simultaneously affect the AIS of user satisfaction.

This research aims to evaluate the effect of consumer traits, service quality, perception-based factors, customer satisfaction, and e-trust on electronic brand love and e-loyalty. In this study, a cross-sectional survey is conducted based on the questionnaire method to collect data from a sample of 300 customers of the Digikala Website in Isfahan, Iran. Structural equation modeling (SEM) is used to test the research hypotheses. According to the results, the service quality, consumer traits, and perception-based factors significantly affected customer satisfaction. Also, e-brand love had a significant impact on e-trust and e-loyalty; e-trust significantly affected e-brand love and e-loyalty, and e-brand love had a significant impact on e-loyalty. To the best of the authors’ knowledge, this research stands among the first to evaluate the factors affecting electronic brand love and loyalty. The evaluation of brand love on loyalty demonstrated that the greater the amount of love and fascination with a brand, the higher the positive effect on consumer loyalty. Overall, managers are recommended to do their best to eliminate misunderstandings and create an interest in consumers, ultimately leading to greater customer loyalty. Managers should pay more attention to brand experience dimensions, such as sensory marketing. In this regard, creating a brand community by e-retailers is very helpful.