-5171ffc0182b6af927f-279d 20221104073653778 beie:beie director@blueeyesintelligence.org WEB-FORM International Journal of Innovative Technology and Exploring Engineering IJITEE 22783075 10.35940/ijitee https://www.ijitee.org/ 11 30 2022 11 12 Faculty, Department of Electronics and Instrumentation Technology, University of Kashmir, Srinagar (Jammu and Kashmir), India Dr. Aadil T. Shora Mujtaba Y Kathjoo Scholar, Department of Electronics and Instrumentation Technology, University of Kashmir, Srinagar (Jammu and Kashmir), India Masrat M. Khan Student, Department of Electronics and Instrumentation Technology, University of Kashmir, Srinagar (Jammu and Kashmir), India In this paper, a three dimensional (3-D) analytical model of surface potential has been derived for gate engineered trapezoidal trigate Tunnel Field Effect Transistor (TFET). The model has been obtained by assuming parabolic approximation of the potential profile and solving 3-D Poisson equation using appropriate boundary conditions. The device considered in this work is silicon based TFET with gate composed of two materials with different work functions. The low work-function material is placed close to source and drain region while high work-function material is placed in between them. This will result in enhancing the tunneling in the source/channel interface region while reducing the electric field in the drain region. Trigate devices have been found to enhance the device performance at nanoscale, however, Trigate device fabricated by Intel have been found to have trapezoidal shape rather than expected rectangular shape. In this work, we have included the effect of different inclination angles of sides on the device performance. The model has been verified by comparing the results with the simulation results obtained in ATLAS software. 11 30 2022 33 37 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.L9321.11111222 https://www.ijitee.org/portfolio-item/l932111111222/ Department of Ship Automation, Gdynia University Maritime Gdynia, Poland Monika Rybczak Michał Ziemiński Department of Ship Automation, Gdynia University Maritime Gdynia, Poland Technology 5.0 combines analytical thinking algorithms with leading technologies such as the Internet of Things, smart factory, cobots and artificial intelligence. With the growth of manufacturing, the digitization process is the only way to ensure further growth opportunities in the future. The article presents the most important features of technology 5.0, according to the authors. They found several examples in the literature related to artificial intelligence. Two extreme examples are then presented. An academic testbed using an artificial intelligence module built at the Maritime University of Gdynia, Faculty of Electrical Engineering. We propose a testbed configuration based on image recognition based on the S7-1500 controller and Intel RealSense camera. The first example shows how to configure the Linux environment and Phyton language needed for teaching artificial intelligence. Steps for implementing the learned AI model into a Siemens Neutral Processing Unit (NPU) module are given. This provides a glimpse of academic solutions. Recognized as the theoretical methods needed for artificial intelligence module research. The second example provides general information about the application of 5.0 technology at GPEC (Thermal Energy Company - Gdansk ). It provides a broader view of the application of 5.0 technology in industry. The results chapter compares the proposed two solutions based on the described technology, showing the potential of both solutions, which are closely related to artificial intelligence algorithms. According to the authors, they are based on image recognition based on a classification algorithm and machine learning techniques. The authors propose a prototype of the test bed needed for Internet 5.0 research in laboratory conditions while giving general applications in industrial conditions. 11 30 2022 22 25 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.L9325.11111222 https://www.ijitee.org/portfolio-item/l932511111222/ Department of Information Technology, CVR College of Engineering, Mangalpally, Rangareddy District, Telangana, India Siddhartha Malladi* Dr. S. Suguna Mallika Professor, Department of Computer Science and Engineering, CVR College of Engineering, Mangalpally, Rangareddy District (Telangana), India. Krishna Sai Prahlad M Department of Computer Science and Engineering, CVR College of Engineering, Mangalpally, Rangareddy District, Telangana, India Sai Madhav Reddy Nomula University of Texas at Dallas, Campbell Rd, Richardson, TX 75080, USA. Aadesh Pandiri Department of Computer Science and Engineering, CVR College of Engineering, Mangalpally, Rangareddy District, Telangana, India. Diabetic Retinopathy is eye condition caused by high sugar levels inside the blood, which is the origin of excessive pressure inside blood vessels inside the eye, with the smallest vessels being the most vulnerable. This condition does not appear suddenly; rather, it develops gradually over time. After the disease progress, it can show symptoms like blurry vision, changes in vision from blurry to clear, and vice versa, blackspots or dark areas in the vision, poor night vision, fading out of colours, etc. Therefore, pre-emptive identification of disease is one of the beneficial tactics to prevent or get cured of this disease. This technique is also susceptible to human misjudgement, which exists in many clinical diagnoses. An Image Classification Model can accelerate the process of blindness detection in patients. We accomplish this by constructing a classifier using transfer learning that can extract key features from pictures and categorise them into separate stages. This work focused on making an efficient classifier with high accuracy and providing the patient with advance notice of their disease using an easy-to-use mobile application. Our model gave a 0.907 quadratic weighted kappa (QWK) score on independent test dataset and 93.2% accuracy on test time augmented data in multi-class classification. Furthermore, providing the necessary use cases with which the patient can track the diabetic retinopathy screening diagnosis 11 30 2022 38 48 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.L9335.11111222 https://www.ijitee.org/portfolio-item/l933511111222/ Master Student, College of Computing & Informatics, Uniten University, Selangor, Malaysia Amjed Ahmed Srasyih Zainuddin bin Hassan Professor and Dean, College Computing & Informatics, Uniten University, Selangor, Malaysia. Knowledge management (KM) is the driving force for economic and social progress in organizations. The growth of any organization in any sector depends on the application and improvement of knowledge management. It is not easy to implement knowledge management as a task of an organization due to the culture of the individual, the roles of the organization and the lack of infrastructure available to support the processes of knowledge management. Besides, the application of knowledge management in an organization requires expert in human resource development and strong managers to encourage employees to adopt the processes of knowledge management. For this reason, this review attempts to review the use of IT tools in the knowledge management process. This improves the organization's culture, the organization's performance, and the organization's infrastructure. This paper also discusses the KM model of each organization to apply KM in its work. This model can be generalized to any organization that wants to improve its work. The impact of the model can be seen on the financial issues of the organization, leadership and innovation within the organization, and improving productivity. The advantages of using IT in KM are mentioned and discussed. This review shows that there are six advantages of applying IT tools with knowledge management in organizational work and that is to improve understanding of data, especially when dealing with decision-making and data management. At the end of this paper, tools commonly used in knowledge management are discussed. Applying IT tools to the work of an organization can enhance knowledge sharing among employees. It can also enhance productivity and innovation in the organization. 11 30 2022 26 32 CC BY-NC-ND 4.0 10.35940/BEIESP.CrossMarkPolicy www.ijitee.org true 10.35940/ijitee.L9337.11111222 https://www.ijitee.org/portfolio-item/l933711111222/