درخت حوزه‌های تخصصی

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.

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.

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.

Purpose: The Purpose of this paper is to explain the nature and process of digital transformation.Methodology: Its methodology is based on a structured literature review (SLR) and searching scientific sites and specialized resources. One roadmap model, six maturity assessment models, three digital business model transformation approaches and eight digital transformation frameworks are explained interpretively.Findings: Digital transformation is  a strategy and an operating model change, in which technological advancements are leveraged to improve human experiences and operating efficiencies and to evolve the products and services to which customers will remain loyal. A review of research in this field shows that the nature of digital transformation depends on knowledge and knowledge is formed as a valuable asset in people's minds. Therefore, the role of human resources in creating and achieving the transformation is important and fundamental. Findings show that no digital transformation is only technological, it is organizational and requires its own planning, resources and rules. It is clear that we need a model in this kind of transformation journey. Staff capital and its empowerment by knowledge and fundamental requirements are important for success in the digital transformation program. Transformation in culture, in structure, in processes and methods, along with the benefits of the frontier technologies, will lead to a dramatic transformation in the field of business. The environment of organizations is changing faster and has become more volatile, uncertain and complex than in the past. Rapid changes in competition, demand, technology and regulations make it more important than ever for organizations to be able to respond and adapt to their environment. In this context, the pressure on firms to align their business strategy with the technological changes in the environment has significantly increased with the emergence and growing importance of new digital technologies, such as Social Media, Cloud Computing, Big Data and Analytics, Embedded Devices, 3D-Printing, the Internet of Things and Artificial Intelligence. They are profoundly transforming the strategic context of organizations: changing the structure of competition, the behavior and expectations of customers, the way business is conducted, the way products are manufactured and services are delivered, the way of working and, ultimately, entire industries. The growth of technology, in addition to transforming organizational boundaries, has also improved knowledge sharing. As the results indicate, the digital age refers to a time in history when the use of digital technology was generalized throughout the world. We are on the verge of a technological revolution that will fundamentally change the way we live, work and communicate with each other. In terms of scale, scope, and complexity, this transformation will be different from what mankind has already experienced.Conclusion: Digital transformation has affected the work processes of individuals in organizational environments. New methods in combining digital innovations and intensifying inter-organizational collaboration are among the key features of success. Because the goal of digital transformation is a business transformation, it requires different organizational elements, which are explained in the frameworks, to work together like a piece of music in a concert with different instruments played harmoniously and simultaneously