درخت حوزه‌های تخصصی

The application of machine learning technologies for cancer detection purposes are rising due to their ever-increasing accuracy. Melanoma is one of the most common types of skin cancer. Detection of melanoma in the early stages can significantly prevent illness and fetal death. The application of innovative machine learning technology is highly relevant and valuable due to medical practitioners' difficulty in early-stage diagnoses. This paper provides an open-source tutorial on the performance of an algorithm that helps to diagnose melanoma by extracting features from dermatoscopic images and their classification. First, we used a Dull-Razor preprocessing method to remove extra details such as hair. Next, histogram adjustments and lighting thresholds were used to increase the contrast and select lesion boundaries. After using a threshold, a binary-classified version of image was obtained, and the boundary of the lesion was determined. As a result, the features from skin tissue were extracted. Finally, a comparative study was conducted between three methods which are Artificial Neural Network (ANN), Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). The results show that ANN could achieve better accuracy (83.5%). In order to mitigate the biases in existing studies, the source code of this research is available at hadi-naghavipour.com/ml to serve aspiring researchers for improvement, correction and learning and provide a guideline for technology manager practitioners.

The adoption of E-learning in academic environments, particularly in Iran, has accelerated over the past decades. However, the lack of established guidelines for instructional design seems to have hindered the creation of effective online educational environments. Therefore, this study aimed to conduct a comprehensive qualitative research synthesis (QRS) to identify the criteria for an optimal online learning environment for Iranian university students. The study followed Major and Savin-Baden's three-phase QRS model and included 12 studies with 252 participants and 42 researchers. The synthesis integrated findings from multiple studies to gain insights into experts’ opinions and students’ perceptions, preferences, and experiences within online learning environments. The research identified four overarching themes: targeted learning, effective teaching management, socio-affective engagement, and learner empowerment. Targeted learning focuses on problem-oriented and need-oriented teaching; effective teaching management emphasizes balanced content and time management, clear objectives, and diverse presentation and evaluation methods; socio-affective engagement involves interactive feedback, social presence, and emotional communication; learner empowerment stresses autonomy, agency and active learning, including experiential and discovery learning. Applying these findings seems to offer a genuine contribution, leading to the development of culturally relevant and high-quality E-learning experiences and addressing the challenges posed by the nascent E-learning system in Iran.

Purpose: This research aims to identify the factors affecting social network marketing based on gaining a competitive advantage and designing a model related to the communication between them.Method: This research is applied in its purpose, and conducted using a mixed approach (qualitative and quantitative). In the qualitative phase, first by reviewing the literature in the field of social network marketing and using the meta-combination method, the factors affecting it were identified and divided into three categories. subsequently, the relationships between these factors were determined and analytically analyzed using the interpretative structural modeling approach. In the modeling section, a questionnaire was distributed among experts selected through snowball sampling.Findings: The results of this research led to the classification of factors affecting social network marketing based on gaining competitive advantage and designing a model of these factors. In this model, the categories of organizational and structural resources (responsiveness to customers, service quality), marketing (attracting more customers, efficiency), and competitive advantage based on social media (branding, profitability), indicate the factors and the way of communication and interaction of these factors.Conclusion: Finally, the interpretation of the model, analysis of its levels, and the relationships among dimensions were discussed and solutions were provided in this regard.

Purpose: The main purpose of this research is to assess the feasibility of using VSAT satellites in the information services of university libraries.Method: The research method is a survey using the TOPSIS model, which indicates that the optimal method of providing the Internet is the method that has the greatest distance from negative factors and the least distance from positive factors. The opinions of user organizations, i.e. academic libraries and information centers, have been examined to clarify the necessity of using this method as well as its characteristics and advantages compared to other ways of providing the Internet.Findings: The findings show that VSAT satellite internet can have better conditions for providing services compared to other services such as ADSL, optical fiber, Wi-Fi and Wi-MAX. Also, their assessment determined that VSAT satellite internet is currently the best way to provide internet based on the criteria of service, support, cost, trust and quality, and ranks second in criteria such as security, confidentiality and service. In conclusion, the priority of solutions to provide library internet using TOPSIS analysis is: VSAT service; Optical fiber; ADSL service; Wi-Max services and wireless services.Conclusion: The results indicate that the VSAT satellite network, with advantages in the use of Internet services by libraries, plays an important role in improving the quality of these services.

This study critically examines the sustainability challenges within the lithium-ion battery (LIB) supply chain in India's electric vehicle (EV) sector, an area of growing importance due to the rapid expansion of EV adoption. While LIBs are essential for EVs due to their high energy density and reliability, their production and disposal pose significant environmental, social, and economic sustainability challenges. These include resource depletion, environmental degradation, ethical concerns in raw material sourcing, and inefficient recycling processes. This study adopts a qualitative case study approach, focusing on three leading Indian automotive companies, to explore these challenges in depth. Data were collected through semi-structured interviews with key stakeholders involved in various stages of the LIB supply chain, including production, waste management, and recycling. Key findings reveal that the primary environmental challenge is the lack of advanced green technologies for recycling and disposal, leading to high water and energy consumption, as well as hazardous waste emissions. Social challenges include unsafe labor practices, particularly in raw material extraction, and a shortage of skilled labor in battery recycling operations. On the economic front, the reliance on imported raw materials, coupled with high production and recycling costs, undermines the sector’s sustainability and profitability. The research contributes to the literature by providing a comprehensive understanding of the environmental, social, and economic dimensions of sustainability in the LIB supply chain. It also offers practical insights for stakeholders and policymakers aiming to foster a greener and more sustainable EV sector in India.  

The article proposes a methodical approach to assessing the competitiveness of enterprises in the logistics infrastructure of the Black Sea region in the context of the strategy of the development of the Black Sea. The article is presented is the author's interpretation of the steel development of the territory and injected into the logistic infrastructure. It was proposed of the methodical approach to assessing the competitiveness of enterprises-moving enterprises in the development of the territory, as one of the stages of the methodology for assessing the development of the territory in the region. It have been identified Indicators for assessing sustainable development in assessing the competitiveness of key enterprises in the region and in terms of using the TOPSIS model. The application of the TOPSIS model allows to assess the value of the aggregate indicator of sustainable development of a region or territory, taking into account the impact of the level of competitiveness of its key enterprises. In the context of this approach, it is studied and evaluated the level of competitiveness of powerful enterprises of the Black Sea region, which form the logistics infrastructure of the region. It was  determined their influence on the strategy of sustainable development of the territory. This approach allowed to expand the methodology for assessing the assessment of sustainable development of the territory through the methodology of assessing the competitiveness of enterprises-engines of development of the territory, as one of the stages of the overall methodology.

The paper considers the possibilities of optimizing the search for agricultural information based on Shannon information entropy criterion. A comparison of the degree of uncertainty of information search through the Internet – search systems with similar indicators of Ukrainian agricultural websites. According to the number of hit count in Ukraine in July 2020 to the search engine, which consists of 10 sources, and to agricultural websites (43 sources) by estimating entropy, a conclusion was made about the significant degree of dispersion of agricultural information sources. It should be emphasized that the artificial division into 4 categories (AgroMedia, Agrotrade web resources, Information and advisory resources, Specialized web resources) did not improve the situation according to the degree of uncertainty compared to the search engine system. As for the entropy index, for almost all 4 categories of entropy indices (heterogeneity or diversity) is close to the case of uniform distribution, i.e., the same hit count of all possible resources (their number for all categories is approximately the same 10-11). As a result of the analysis of the potential client base of electronic consulting, it can be quantified as 4,700,000 of agricultural households and about 50,000 small and medium-sized farms. The transition to the land market is likely to lead to a substantial increase in the number of the latter. It was demonstrated that the current educational level of household owners indicates both the need to increase this indicator and the presence of a close relationship with the existing system of professional advisory in Ukraine, which operates in recent years through self-sufficiency and uncertain financial support from central and regional authorities. The existing official database of advisors should be restructured in line with the call of the times to reduce the degree of uncertainty in finding a specialist of the desired profile.

After the Coronavirus diseases (COVID-19) outbreak, the Whole world witnessed the strangest buying behavior within the customers. Suddenly masks, hand sanitizers, and toilet papers became the priority list of the customers. High demand and lesser availability of essentials products like masks, toilet papers, and hand sanitizers create a chaotic situation inside the retail outlet's stores.  The buyer’s behavior and the chaotic scenario inside a retail outlet drew the attention of several consumer psychologists, academicians, and researchers. A panic buying situation is the most common behavior that exists in a time of crisis. This paper discusses the panic buying situation briefly during COVID-19. However, a few types of research and studies were captured in the panic buying behavior. The current study examined the factors that influenced the customers buying decisions during the COVID-19 outbreak and secondly, it examined to what extent the buying decision of a customer creates a panic situation. Furthermore, the study looked at the emotional and cognitive responses of the individuals which play a pivotal role in influencing customer decision making the journey. Qualitative content analysis and thematic methodology were considered for data analysis. The results indicated that fear and uncertainties were the key emotional responses; whereas rumors, fallacious thinking, and survivalist psychological were the key cognitive responses that influenced the customer decision journey.