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Fundamental Basic Wind Speed in Albania: An Adoption in Accordance with Eurocodes
No full textNon-EU states are in the process of adopting and implementing Eurocodes as design standards. The majority of Eurocodes have been translated in Albania; however, their National Annexes are incomplete. Fundamental basic wind velocity is one of the topics in the Eurocodes for structural design, and this study presents a method for calculating it, based on available wind velocity data as well as past studies and technical design codes. Existing wind speed maps with a 2 percent chance of exceedance (PoE) have insufficient information about wind speed duration, orography, and the data they were derived from, as well as other references. A correlation must be conducted in order to utilise current maps, studies, and wind data in compliance with Eurocodes. The purpose of this work is to investigate the nature of the data included in existing wind maps and other available wind velocity sources, as well as to construct a fundamental wind speed map of Albania compliant with Eurocodes.
 
A Sustainable Evolution of Indian Railway
No full textThis paper explores the transformative journey of Indian Railways (IR) since 1853, emphasizing restructuring, digitalization, and safety measures. IR\u27s commitment to sustainability is evident in initiatives like e-ticketing, radio frequency-based identification (RFID)-based maintenance, safety, and disaster management. Innovations like level crossing automation and real-time information systems contribute to a safer railway ecosystem. IR\u27s dedication to reducing greenhouse gas emissions aligns with global environmental objectives, utilizing solar and wind energy initiatives. Challenges in balancing financial performance persist and have been addressed by national government policies. As IR strives for a sustainable future, collective efforts from stakeholders, including employees and passengers, are pivotal. The vision is a modern, efficient, and environmentally conscious railway system
Artificial Intelligence and Computational Psychological Science Connections
No full textComputational Psychological Science (CPS) is a rapidly growing field that uses computational models to study human behaviour and cognition. The development of artificial intelligence (AI) algorithms has greatly expanded the potential of CPS by providing powerful tools for modelling complex and dynamic processes in the brain. One area where AI has had a major impact on CPS is in the field of emotion recognition. Researchers can now collect large datasets of emotional facial expressions and use AI algorithms, such as convolutional neural networks (CNNs), to learn how to recognize different emotions from these images. These models can be used to generate predictions about how emotions are represented in the brain and how they are influenced by social and contextual factors. AI algorithms can also be used to optimize the parameters of computational models and improve their accuracy and predictive power. For example, evolutionary algorithms can be used to search for the set of model parameters that best fit the experimental data, while reinforcement learning algorithms can be used to optimize the model\u27s decision-making policies in complex and dynamic environments. In addition to emotion recognition, AI has also been used in CPS to model other cognitive processes, such as decision-making, learning, and memory. For example, deep learning algorithms have been used to develop models of how the brain learns and represents visual and auditory stimuli, while reinforcement learning algorithms have been used to model how the brain makes decisions in uncertain and changing environments. Overall, the connection between AI and CPS has the potential to provide new insights into the computational basis of human behaviour and cognition and to develop new interventions and technologies that can improve human well-being. However, this field also raises important ethical and social issues, such as the potential impact of AI on privacy, social inequality, and the future of work. As AI and CPS continue to develop, it is important to carefully consider these issues and ensure that these technologies are used in ways that benefit society as a whole
A Smart Bioreactor-based Production and Distribution System for Spirulina Algae in Developed Countries
No full textSpirulina is a beneficial algae for delivering food security, preventing poverty, and managing malnutrition. Given the scientific data, it is possible to get all of the essential amino acids and proteins for the human diet from sources other than animal flesh, and spirulina has emerged as a plausible substitute. The coordinated, intelligent production and distribution system for spirulina algae proposed in this research may be used in developed countries. From a technological standpoint, a photobioreactor is suggested and utilized to produce algae in an appropriate environment. A dynamic mechanism for distributing spirulina is also envisaged. The last step is the offering of a management system based on transformative involvement
Influence of Filler on Asphalt Dispersions with Recycled Tire Rubber for Hot Asphalt Mix
No full textMineral filler additions change the rheological behavior of the asphalt binder, which has a big impact on the properties of asphalt mixtures like rutting resistance, fatigue resistance, and thermal susceptibility. There is currently no specification in Argentina that specifies the ideal filler content to be added to hot asphalts modified with recycled tire rubber (RTR). In the current study, an analysis of the behavior of asphalt dispersions with varying amounts of RTR—from 15% to 25% of the binder weight—is done when mineral filler is incorporated in various concentrations. By measuring how the dispersion reacts to the softening point test and temperature sweep using a dynamic shear rehometer (DSR), it aims to establish a standard for the ideal amount of filler to incorporate and show how the RTR residue and filler work together to produce the desired results. The amount of rutting resistance offered by the asphalt has been found to increase by up to 200 percent when measured with DSR for the highest contents of RTR and filler
A Comprehensive Study of Causal Factors and Their Effects on the Human Body for the Design of a Smart Bedsore Prevention System
No full textBedsores, also known as pressure ulcers, represent a significant healthcare concern, particularly among immobile or bedridden patients. These wounds not only lead to considerable pain and discomfort but also pose a risk of severe complications. The development of an effective smart bedsore prevention system requires a profound understanding of the causal factors contributing to bedsore formation and their intricate effects on the human body. This comprehensive study investigates key causal factors associated with bedsore development, with a specific focus on temperature, humidity, and pressure. By examining their interplay and relationships with patient-specific variables, we aim to shed light on the underlying mechanisms that contribute to bedsore formation. Our research employs a multifaceted approach, integrating extensive literature reviews, data collection from diverse patient populations, and advanced statistical analysis techniques. Through this multidimensional investigation, we identify correlations and patterns between temperature, humidity, pressure, and individual patient characteristics. The results of this study highlight the intricate web of relationships between these factors and their collective impact on bedsore susceptibility. Furthermore, we provide insights into how patient-specific attributes, such as mobility and medical conditions, modulate the risk of developing bedsores. The implications of our findings are profound, laying the groundwork for the development of a smart bedsore prevention system that can proactively monitor and mitigate these causal factors. Such a system has the potential to revolutionize bedsore management by tailoring interventions to individual patient needs, optimizing care protocols, and ultimately enhancing patient comfort and well-being
An Evaluation of Dispersion Coefficient Models for Rivers
No full textThis article intends to evaluate a few mathematical and empirical models of river dispersion coefficients from previous studies. Two problems were cited as the causes of their shortcomings: the significant discrepancy between measured and predicted values of the phenomenon. The models based on previous research fail to take into account some of the geometric and hydraulic facts of dispersive flows, such as dead zones and bend effects, because they were made under assumptions that are false in real rivers. The empirical models omit some of the most significant parameters known to affect dispersion, whereas the mathematical models demand cumbersome, time-consuming, and labour-intensive tracer experiments. Although the accuracy of more recent machine learning techniques has increased, they are still very expensive, prone to error, and require a high level of expertise. All the equations fall short of the two crucial criteria for scientific acceptance: reproducibility and strong predictive power. A form for a new equation is proposed that will take into account many of the omitted parameters and, as a result, improve accuracy. Poor prediction accuracy should be addressed by the new equation. It is possible to derive the equation using dimensional analysis
Capacity Evaluation and Spectral Analysis of Damaged Low-Rise Reinforced Concrete Building
No full textNumerous buildings sustained damage during the November 26, 2019, earthquake in Durres, particularly in the cities of Durres, Kruja, and Tirana. The majority of existing older buildings in these regions lack adequate seismic safety measures due to deficiencies in their original designs. Furthermore, these structures were often constructed with substandard workmanship and, in many cases, without the involvement of professional engineers. This paper focuses on the in-situ investigation of one such building to assess the extent of damage. A comprehensive analysis is performed, encompassing material tests, geological assessments, and seismic hazard evaluations conducted on both the building and its construction site. The building is then modeled using existing material properties through specialized software, and various analyses, including modal analysis, capacity evaluation, and spectrum analysis, are carried out. The empirical results derived from these analyses are subsequently compared with the observed damage to the building. In light of the findings, the paper explores potential retrofitting techniques aimed at repairing the current structural deficiencies. The proposed strategies are discussed with the goal of aligning the structure with the requirements outlined in Eurocode 8
Assessment of Vjosa River Water Quality Using Chemical Parameters
No full textAlbania possesses a diverse range of water ecosystems. The objective of water quality assessment is to identify sources of pollution and develop sustainable strategies for managing water resources. Pollution from both natural and anthropogenic sources has the potential to cause harm to aquatic ecosystems. Of particular concern is nutrient enrichment, which can have adverse effects on surface water quality. Excessive nutrients can lead to eutrophication in surface waters, causing algae blooms and significant alterations in the water ecosystem\u27s biodiversity. Our study aimed to evaluate the Vjosa River\u27s water quality based on chemical parameters. The Vjosa River is a vital water ecosystem in Albania, the Balkans, and Europe, renowned for its biodiversity and water quality. Our investigation was carried out from November 2021 to May 2023. Five water sampling points were chosen in the Vjosa River and water samples were analysed for nutrient forms such as nitrogen and phosphorus. The values of ammonium ranged from 0.06 mg/l to 0.14 mg/l, while NO2 ranged from 0.014 to 0.066 mg/l, and NO3 range from 0.47 mg/l to 0.66 mg/l. The concentration of phosphates ranged from 0.024 to 0.068mg/l. Based on most of the chemical parameters analysed, water quality in the Vjosa River is of high quality when compared to the WFD standards
Spliced Image Forgery Detection Using Adaptive Over-Segmentation Combined With AKAZE, ORB, and SIFT Feature Descriptors
No full textThe detection of digital image forgery is an essential component in the process of safeguarding the authenticity and integrity of visual data. Image forgery can be accomplished through a variety of tools. One of these techniques is called splicing, and it involves combining the contents of multiple images in order to create a composite image that has been forged. The identification of digital forgeries of this kind presents a significant challenge. One of the tried-and-true methods that is utilized in the process of forgery detection is called Adaptive Over Segmentation (AOS). Within the scope of this paper, we are integrating adaptive over-segmentation with effective feature extraction methods such as AKAZE, ORB, and SIFT. With the assistance of parameters like precision, recall, and F1 measures, the proposed method intends to enhance the outcomes in order to achieve the desired results