مطالب

Extracting sentiments from the English-Telugu code-mixed data can be challenging and is still a relatively new research area. Data obtained from the Twitter API has to be in English-Telugu code-mixed language. That data is free-form text, noisy, lexicon borrowings, code-mixed, phonetic typing and misspelling data. The initial step is language identification and sentiment class labels assigned to each tweet in the dataset. The second step is the data normalization task, and the final step is classification, which can be achieved using three different methods: lexicon, machine learning, and deep learning. In the lexicon-based approach, tokenize each tweet with its language tag. If the language tag is in Telugu, transliterate the roman script into native Telugu words. Words are verified with TeluguSentiWordNet, and the Telugu sentiments are extracted, and English SentiWordNets are used to extract sentiments from the English tokens. In this paper, the aspect-based sentiment analysis approach is suggested and used with normalized data. In addition, deep learning and machine learning techniques are applied to extract sentiment ratings, and the results are compared to prior work.

Measurement of soil moisture and control of irrigation according to the measured data is crucial in agriculture fields where water scarcity is always a serious issue. For this purpose, a cost-effective distributive network system has been proposed and developed using technology like IoT to control complex irrigation processes. An internet-enabled embedded moisture sensing unit was designed that consists of a capacitive sensor probe and electronic system to process the soil moisture value. The sensor probe was calibrated for six different varieties of soil using the Thermo gravimetric method. The output response is inspiring, with a goodness of fit value of 0.99. Algorithms are developed for irrigation control that operates by a developed web-based application from the control station. The system was implemented at a total cost of 122.37 US dollars and tested in cassava agriculture field for loam soil in Nagaland, India, for 91 days and showed magnificent water saving of up to 95% compared with traditional approaches.

The main challenging issues for e-commerce operators are building trust in customers to make purchases and gaining a suitable position in the minds of consumers to repeat purchases. Therefore, this research aims to identify the effective factors of word of oral electronic marketing on brand equity. For this purpose, the researcher tried to use the grounded qualitative research method (Glaserian grounded theory) and, with the help of MAXQDA software, to identify and present the dimensions, components, and indicators of oral electronic marketing effective on "brand equity" from the analysis of theoretical bases, upstream documents, and interviews with experts. This research is in the category of applied-developmental research, and in terms of method, strategy, and nature, it is part of exploratory qualitative research, whose philosophy is based on the interpretative-constructive paradigm. It has a single time horizon, collects data from both documentary and field methods, and its tool is recording in the documentary (library) section and interviews in the field section. The statistical population of this research is experts in the fields of human resources management, marketing, and branding; managers and vice-presidents; and employees of e-commerce companies. Based on research findings, oral electronic marketing has two dimensions: technical and technological factors and individual factors, and the dimension of technical and technological factors includes the components of electronic marketing tools and situational features, message features, and the dimension of human factors includes the components of individual factors and interpersonal factors. The special value of the brand also has two dimensions of consumer perception and consumer behavior. The dimension of consumer perception includes the components of brand association, perceived quality, and brand awareness, and the dimension of consumer behavior includes the components of brand loyalty, customer relationships, and brand consistency.

The automotive industry, as a job-creating and infrastructure industry, needs an executive model for success in the domestic and international markets. In this regard, the present study has been conducted with the aim of designing a model for implementing the fourth generation industry to achieve sustainable development goals in Iran Khodro Company. The study is an applied-developmental study in terms of purpose and cross-sectional survey research. Also, in this study, a mixed research method (qualitative-quantitative) was used. Content analysis method and MaxQDA software were used for data analysis in the qualitative section. Then, using Interpretive Structural Modeling (ISM) with MICMAC software, the initial pattern was drawn. In the quantitative section, one-sample t-test and SPSS software were used to measure the current situation. The research findings showed that the Collection and Analysis of Big Data affects the Simulation and Automatic Robots. These factors affect horizontally and vertically integration systems and thus lead to the Internet of Industrial Things, Augmented Reality and Cyber Security. Further, through the Cloud Computing system, Additive Manufacturing is affected and this Additive Manufacturing leads to Sustainable Development.

The grounded theory and structural analysis were employed in this study to propose an optimal policy model for cultural organizations at Iran’s Ministry of Cultural Heritage, Handicrafts, and Tourism in the dimensions of flexibility, ethical appropriateness, and organizational benefit. This is a fundamental study with exploratory research designs. The statistical population of the qualitative section includes all faculty members, professors, and managers, whereas that of the quantitative section includes all the second-rate managers and employees of Iran’s Ministry of Cultural Heritage Data collection tools were interviews and questionnaires. According to the research findings, the optimal policy model for cultural organizations had a positive effect on flexibility. also had a positive effect on ethical appropriateness, through the grounded theory and structural analysis at the Ministry of Cultural Heritage and Tourism. Finally, it had a positive effect on organizational benefit through the grounded theory and structural analysis at the Ministry of Cultural Heritage, Handicrafts, and Tourism.

The phenomenon of accelerating start-ups in Iran is a new procedure in the field of entrepreneurship that is affecting universities, policymakers, and economic activists as well as the entrepreneurial ecosystem in society. It is an organization with a systematic review method. According to this technique, a detailed and in-depth review of the research literature on the issue of factors affecting the performance of organizations and especially accelerators has been done and finally, the findings of related qualitative and quantitative research have been integrated together. The research findings based on 26 final reviewed articles led to the extraction of 52 open codes for all organizational factors and seven central codes including 1- Establishing organizational communication 2. Team building 3. Performance improvement 4. Leadership ability 5. Improvement and development of managerial ability 6. Participatory management 7. The administrative capability has become. In the end, it is suggested that in order to improve the performance of organizational accelerators, it is necessary to pay practical attention to these main variables and related sub-variables.

This research has explained the competence components of the managers of ports and maritime organization of the country by using a mixed research design (qualitative and quantitative). To collect data in the qualitative step, interviews with experts and in the quantitative step, a questionnaire from the qualitative step the research was used. The statistical population of the research was the directors of the Ports and Shipping Organization of the country. In order to select research samples, research data was collected using the snowball method and based on 20 in-depth interviews with experts related to the subject. Brown and Clark's (2006) theme and pattern analysis method was used to analyze the data in the qualitative step and the content validity ratio index (CVR & CVI) was used in the quantitative step. Findings of theme analysis about the competencies of the country's Ports and Maritime Organization managers in 4 main themes, 1- Specialized competencies, 2- Personality competencies, 3- Executive competencies, 4- Managerial competencies, and 25 sub-themes. have been introduced In the quantitative step, the percentage of the appropriateness of open codes for 15 experts is 0.49%, according to the CVR statistics, all competency themes had good content validity from the experts' point of view. The results of this research showed that the managers of the Ports and Maritime Organization of the country, by accepting the issue that success in today's conditions of the maritime transport industry is the use of existing human resources competencies, should pay attention to the improvement of the four competencies of the present research. And have intellectual and far-sighted thoughts in the conditions of crisis and challenges ahead.

The current research seeks to identify the influencing factors on implementation of smart city plans based on approach of technical and social systems. For this goal, the library study is done and then based on that a research plan is written that include using expert opinions and data mining technique, feature selection ,clustering and also Delphi technique to identify and screen factors and then using clustering, the final factors are leveled. Here the aim is not ranking but is leveling. Meanwhile because of high numbers of factors, screening them in both steps using Delphi and feature selection is conducted. Delphi is one of the classic tests in qualitative approaches and feature selection include data mining techniques. Finally leveling factors include technical and social factors and the most influencing ones are determined. technical factors including digital infrastructure, ICT base transportation, ICT based logistic, building alarm systems, energy consumption adjustment, ICT based process are placed in level one. Social factors including digital and smart innovation, knowledge sharing, smart education, participation in sustainable development, access to educational plans, waste recycling, pollution control, productivity and flexibility of labor market are placed in level one.

The article examines the nature of the relationship between environmental pollution and economic growth in Ukraine. An Data intelligence analysis of the dependence of pollutant emissions on GDP per capita and other factors of Ukraine's economy for the period from 1996 to 2018. The results of the econometric analysis confirm the theory of the Environmental Kuznets Curve. To prevent environmental and economic catastrophes, it is necessary to increase the gross regional product per capita, and this should be done by diversifying the economy, investing in clean production, and modernized equipment.