By, Prof. Asoc. Dr. Teuta XHINDI
As societies worldwide strive to balance progress with environmental stewardship, the integration of innovative technologies and sustainable solutions in engineering, informatics, and architecture has become essential. The theme “Innovative Technologies and Sustainable Solutions in Engineering, Informatics, and Architecture” highlights how these disciplines can lead transformative changes by adopting new technologies and fostering sustainable practices that support resilient, efficient, and responsible advancements.
By, Anxhela Feçanji
Abstract
This paper explores the design and development of an innovative information system aimed at boosting tourism in the city of Korça. The problem addressed is the need for a user-centred platform that provides potential visitors the essential information while promoting the city’s unique attractions. The study begins by examining relevant literature on information systems and their role in tourism, destination decision-making factors, and case studies of similar systems. It also analyzes Korça’s tourism landscape and visitor preferences, identifying gaps and opportunities for innovation. A hybrid research method combining qualitative and quantitative approaches was employed. Insights from scholarly literature informed the system’s design, with a focus on engaging visitors in tourism promotion through sharing experiences and recommendations. Technologically, the system was built using HTML, CSS, and JavaScript for the front end, and MySQL, and Python (Flask Framework) for the back end, following the Model-View-Controller (MVC) architecture for ease of management and scalability. The results demonstrate that the system effectively showcases Korça’s attractions and fosters interaction between visitors and local businesses. The research concludes that this information system not only provides valuable tourism information but also enhances community engagement. Future recommendations include additional features for further improving user experience and expanding the system’s reach.
By, Ditmira Tahiri, Ardiana Topi
Abstract
Communication serves as the foundation upon which societies are built, manifesting in various forms such as gestures, sounds, drawing, writing, and speech. However, for individuals with hearing impairments, traditional modes of communication like spoken language can pose substantial challenges. These challenges often result in barriers to effective interaction, not only in personal and social settings but also in educational and professional environments. To bridge this gap, sign language has emerged as an essential and empowering communication tool, enabling individuals with hearing impairments to express themselves with clarity and nuance. Sign language is not just a series of gestures but a fully developed language system. It serves as a vital channel through which individuals with hearing impairments can interact with the world around them, breaking down the barriers that their condition imposes. Despite technological advances, the recognition and interpretation of sign language remain complex tasks, especially given the inherent complexity of sign languages characterized by multiple channels, including manual gestures, facial expressions, and body language. This study leverages the Python programming language and the YOLOv8 object detection framework to develop a practical sign language recognition application. This system utilizes deep learning and computer vision to interpret sign language gestures in real-time, aiming to address the limitations of existing recognition systems. The developed system achieved a 95% accuracy rate in recognizing sign language gestures, demonstrating the effectiveness of combining Python with YOLOv8 for this application. This research contributes to the field of assistive technologies by providing a versatile and user-friendly tool that can be deployed across various platforms and environments, ultimately enhancing communication and social integration for individuals with hearing impairments.
By, MSc. Arch. Enkeleida Prifti
Abstract
This study came immediately when I think as an architect and a visual artist at the same time, about convergences between contemporary technologies, visual art and architecture. Technologies, visual art and architecture converge most widely in contemporary conceptual installations. The most important part of 21st century installations is the understanding of 20th century art as an intellectual project. The installation “absorbs” not only all the genres before it, but also the viewer himself. It is three-dimensional and is not just an “object”, but a space organized by the artist, addressing intimate personal experiences as a catalyst for the spiritual rebirth of society.
By, Enxhi Tagani, Erion Curaj, Flavio Koka, Joana Shehaj
Abstract
Phishing continues to be one of the most persistent and dangerous threats in modern cybersecurity. Attackers disguise themselves as legitimate entities to trick individuals into sharing sensitive information, such as login credentials and financial details. In the banking sector, phishing poses particularly significant risks due to the volume of sensitive data handled. While technological solutions like email filtering and multi-factor authentication (MFA) provide some protection, human error remains a critical vulnerability. A custom phishing simulation software was developed to replicate phishing attacks in a controlled environment, allowing researchers to evaluate employee readiness and response at Credins Bank. This mixed-method approach included quantitative data collected from simulated phishing attempts (spear phishing, vishing, and whaling) and qualitative data from employee surveys. These results were used to identify vulnerabilities and provide insights into the effectiveness of current cybersecurity measures. The phishing simulations revealed that 37% of employees clicked on phishing links, while 14% submitted sensitive information. The results highlighted a delay in reporting phishing attempts, with employees taking an average of four hours to notify the IT department. This finding underscores the need for continuous employee training, the integration of AI-based phishing detection tools, and the improvement of reporting mechanisms. The study suggests that a multi-layered approach—incorporating employee training, adaptive phishing simulations, and AI-driven detection systems—can significantly reduce the risks associated with phishing. This research serves as a foundation for future development in both phishing defense technology and employee awareness programs.
By, MSc. Eng. Gazmir Hallaçi, Eng. Jona Liçi
Abstract
Buildings are listed as the biggest consumers of energy and therefore technology in the field of construction has been improved and oriented towards ecological, recyclable and energy efficient materials. One of the best findings in terms of energy efficiency is the use of ventilated facades in buildings. The facade is one of the main technological, functional and protective elements for construction facilities. By itself it represents the outer covering or envelope of a building. Since there are different typologies of facades that are used, then a special attention should be paid to its appropriate selection for buildings in different regions. Nowadays, climate change has become the biggest global concern, and one of the causes is the continuous use of exhaustible resources, therefore, ways are being sought to reduce the consumption of electricity and thus improve environmental conditions and we increase the quality of life. Based on the climatic conditions of a region, it is necessary to choose the right facade that protects the building from atmospheric agents, provides thermal comfort for the residents, is ecological and also has efficiency in energy efficiency.
By, MSc. Orges BESHKU
Abstract
This article focuses on the studying and improving of the capabilities of a Fanuc M-900iB, 6 degree of freedom industrial robot arm. The main objective is to increase its reach and expand its workspace in situations where parallel production lines in automated industries can use one robot with a wide work frame instead of two robots per each line. In order to achieve these objectives, a complete engineering study of the structural, mechanical, electrical, electronic and software components has been carried out. To make this analysis, evaluation and improvement, the maintenance and construction manuals of this robot, the computer program used in real life as well as its physical study and computer simulation were used as reference. In the mechanical aspect, the structure is studied with all the constituent components such as the base, the joints, the end effector and the links between them with the weight of each component, electrical consumption, ranges of motion, angular velocities, moments of inertia as well as internal components have been considered while the second part of the mechanics covers the kinematics and dynamics in mathematical aspects and computer simulations of the trajectory of its movement, considering the inertia created in the minimum and maximum capacity. In the electrical/electronic aspect, the configuration has been studied in detail including the control unit, main board, servo amplifier, servo motors, power supply unit and transformer. In the second part, the electronic control method, general control block diagrams as well as specific position, speed, and current control block diagrams are presented, explaining the filters and amplifiers associated with each, Bode diagrams, and characteristics of open and closed systems. In conclusion links 1 and 3 were extended by 0.3m and 0.25m, offering us a much wider and effective working frame of the robot in the workplace. According to the simulations performed the forces required by the change are affordable and within the safety factor for the supply unit with power, amplifier and servo motors.
By, Sildi Shahini, Ardiana Topi, Forsian Elezi
Abstract
Optical Character Recognition (OCR) is an essential technology for document digitization, enabling the conversion of scanned paper documents, PDFs and images into editable and searchable data. This paper focuses on the application of deep learning in OCR, particularly in digitizing handwritten medical prescriptions, where accuracy is critical for reducing errors and improving healthcare outcomes. Traditional OCR methods face challenges when dealing with handwritten texts due to the variability in handwriting styles and the quality of scanned documents. These limitations can result in recognition errors, which, in a medical context, may lead to serious consequences such as medication errors. To address the above issue, the study explores deep learning approaches, especially Convolutional Neural Networks (CNNs), that have shown significant promise in overcoming these challenges by learning from large datasets. The study involves collecting handwritten prescriptions, preprocessing the images, and training a deep learning-based OCR model. Performance evaluation metrics, including accuracy, 112 INGENIOUS No. 4, ISSUE 2/ 2024 precision, recall, and F1-score, indicate that the deep learning model significantly outperforms traditional OCR methods in recognizing handwritten prescriptions. The results demonstrate the deep learning model’s ability to handle the variability of handwriting more effectively, providing a more reliable solution for digitizing medical documents. This research underlines the transformative potential of deep learning in OCR technology, particularly for critical applications such as healthcare. The findings advocate for the wider adoption of deep learning in the healthcare sector, aiming to improve patient care, reduce human error, and enhance operational efficiency, especially in pharmacy management and medical record-keeping.