Search results for: process risk assessment

Authors: Amit Kumar, Rajdeep Chakrabarty, Ganesh Gupta

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This paper illustrates the detailed accreditation process of Accreditation Board of Engineering and Technology (ABET) for accrediting engineering and Technology programs. ABET is a non-governmental agency that accredits engineering and technology, applied and natural sciences, and computing sciences programs. ABET was founded on 10th May 1932 and was founded by Institute of Electrical and Electronics Engineering. International industries accept ABET accredited institutes having the highest standards in their academic programs. In this accreditation, there are eight criteria in general; criterion 1 describes the student outcome evaluations, criteria 2 measures the program's educational objectives, criteria 3 is the student outcome calculated from the marks obtained by students, criteria 4 establishes continuous improvement, criteria 5 focus on curriculum of the institute, criteria 6 is about faculties of this institute, criteria 7 measures the facilities provided by the institute and finally, criteria 8 focus on institutional support towards staff of the institute. In this paper, we focused on the calculative part of each criterion with equations and suitable examples, the files and documentation required for each criterion, and the total workflow of the process. The references and the values used to illustrate the calculations are all taken from the samples provided at ABET's official website. In the final section, we also discuss the criterion-wise score weightage followed by evaluation with timeframe and deadlines.

Keywords: Engineering Accreditation Committee, Computing Accreditation Committee, performance indicator, Program Educational Objective, ABET Criterion 1 to 7, IEEE, National Board of Accreditation, MOOCS, Board of Studies, stakeholders, course objective, program outcome, articulation, attainment, CO-PO mapping, CO-PO-SO mapping, PDCA cycle, degree certificates, course files, course catalogue

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Authors: M. A. Mulatu, L. C. Chang, Y. S. Han

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Energy harvesting tags with cooperative communication capabilities are emerging as possible infrastructure for internet of things (IoT) applications. This paper studies about the \ cooperative transmission strategy for a network of energy harvesting active networked tags (EnHANTs), that is adapted to the available energy resource and identification request. We consider a network of EnHANT-equipped objects to communicate with the destination either directly or by cooperating with neighboring objects. We formulate the the problem as a Markov decision process (MDP) under synchronised On/Off keying (S-OOK) pulse modulation format. The simulation results are provided to show the the performance of the cooperative transmission policy and compared against the greedy and conservative policies of single-link transmission.

Keywords: cooperative communication, transmission strategy, energy harvesting, Markov decision process, value iteration

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Authors: Sabina-Adriana Floria, Marius Gavrilescu, Florin Leon, Silvia Curteanu, Costel Anton

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Neuroevolution is a subfield of artificial intelligence used to solve various problems in different application areas. Specifically, neuroevolution is a technique that applies biologically inspired methods to generate neural network architectures and optimize their parameters automatically. In this paper, we use different biologically inspired optimization algorithms in an ensemble strategy with the aim of training multilayer perceptron neural networks, resulting in regression models used to simulate the industrial chemical process of obtaining bricks from silicone-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. In addition, the initial conditions that were taken into account during the design and commissioning of the installation can change over time, which leads to the need to add new mixes to adjust the operating conditions for the desired purpose, e.g., material properties and energy saving. The present approach follows the study by simulation of a process of obtaining bricks from silicone-based materials, i.e., the modeling and optimization of the process. Optimization aims to determine the working conditions that minimize the emissions represented by nitrogen monoxide. We first use a search procedure to find the best values for the parameters of various biologically inspired optimization algorithms. Then, we propose an adaptive ensemble strategy that uses only a subset of the best algorithms identified in the search stage. The adaptive ensemble strategy combines the results of selected algorithms and automatically assigns more processing capacity to the more efficient algorithms. Their efficiency may also vary at different stages of the optimization process. In a given ensemble iteration, the most efficient algorithms aim to maintain good convergence, while the less efficient algorithms can improve population diversity. The proposed adaptive ensemble strategy outperforms the individual optimizers and the non-adaptive ensemble strategy in convergence speed, and the obtained results provide lower error values.

Keywords: optimization, biologically inspired algorithm, neuroevolution, ensembles, bricks, emission minimization

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Authors: Evgeni Baratashvili, Nino Pailodze, Ana Bolkvadze, Giorgi Sulashvili

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At the present stage in our country intensifies cooperation with different business cultures, actively developing the process of implementation of Georgia in the global business system that requires us to develop a specific concept, including in the field of management. With the entry of Georgia into the international community, exchange of experience will only intensify. It is clear that the achievement of goals such as the doubling of the National Product increase the competitiveness of Georgian enterprises can’t be recorded without foreign management experience. On the other hand, knowledge of the areas of comparative management can be used in the process of choosing the path of socio-economic development of Georgia.

Keywords: business cultures, comparative management, corporate culture, Georgian business, Anglo-Saxon model, Georgian civilization, anti-capitalist mentality, culture management

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Authors: Murali Aarthy, Sanjeev Kumar Singh

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High risk human papillomaviruses are highly associated with the carcinoma of the cervix and the other genital tumors. Cervical cancer develops through the multistep process in which increasingly severe premalignant dysplastic lesions called cervical intraepithelial neoplastic progress to invasive cancer. The oncoprotein E7 of human papillomavirus expressed in the lower epithelial layers drives the cells into S-phase creating an environment conducive for viral genome replication and cell proliferation. The replication of the virus occurs in the terminally differentiating epithelium and requires the activation of cellular DNA replication proteins. To date, no suitable drug molecule is available to treat HPV infection whereas identification of potential drug targets and development of novel anti-HPV chemotherapies with unique mode of actions are expected. Hence, our present study aimed to identify the potential inhibitors analogous to EGCG, a green tea molecule which is considered to be safe to use for mammalian systems. A 3D similarity search on the natural small molecule library from natural product database using EGCG identified 11 potential hits based on their similarity score. The structure based docking strategies were implemented in the potential hits and the key interacting residues of protein with compounds were identified through simulation studies and binding free energy calculations. The conformational changes between the apoprotein and the complex were analyzed with the simulation and the results demonstrated that the dynamical and structural effects observed in the protein were induced by the compounds and indicated the dominance to the oncoprotein. Overall, our study provides the basis for the structural insights of the identified potential hits and EGCG and hence, the analogous compounds identified can be potent inhibitors against the HPV 16 E7 oncoprotein.

Keywords: EGCG, oncoprotein, molecular dynamics simulation, analogues

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Authors: Viktor R. Stoynov, Zlatka V. Valkova-Jarvis

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The intelligent management and optimisation of radio resource technologies will lead to a considerable improvement in the overall performance in Next Generation Networks (NGNs). Carrier Aggregation (CA) technology, also known as Spectrum Aggregation, enables more efficient use of the available spectrum by combining multiple Component Carriers (CCs) in a virtual wideband channel. LTE-A (Long Term Evolution–Advanced) CA technology can combine multiple adjacent or separate CCs in the same band or in different bands. In this way, increased data rates and dynamic load balancing can be achieved, resulting in a more reliable and efficient operation of mobile networks and the enabling of high bandwidth mobile services. In this paper, several distinct CA deployment strategies for the utilisation of spectrum bands are compared in indoor-outdoor scenarios, simulated via the recently-developed Realistic Indoor Environment Generator (RIEG). We analyse the performance of the User Equipment (UE) by integrating the average throughput, the level of fairness of radio resource allocation, and other parameters, into one summative assessment termed a Comparative Factor (CF). In addition, comparison of non-CA and CA indoor mobile networks is carried out under different load conditions: varying numbers and positions of UEs. The experimental results demonstrate that the CA technology can improve network performance, especially in the case of indoor scenarios. Additionally, we show that an increase of carrier frequency does not necessarily lead to improved CF values, due to high wall-penetration losses. The performance of users under bad-channel conditions, often located in the periphery of the cells, can be improved by intelligent CA location. Furthermore, a combination of such a deployment and effective radio resource allocation management with respect to user-fairness plays a crucial role in improving the performance of LTE-A networks.

Keywords: comparative factor, carrier aggregation, indoor mobile network, resource allocation

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Authors: Hyunsun Lee, Yi Zhu

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Wireless ad-hoc network is a decentralized type of temporary machine-to-machine connection that is spontaneous or impromptu so that it does not rely on any fixed infrastructure and centralized administration. As unmanned aerial vehicles (UAVs), also called drones, have recently become more accessible and widely utilized in military and civilian domains such as surveillance, search and detection missions, traffic monitoring, remote filming, product delivery, to name a few. The communication between these UAVs become possible and materialized through Flying Ad-hoc Networks (FANETs). However, due to the high mobility of UAVs that may cause different types of transmission interference, it is vital to design robust routing protocols for FANETs. In this talk, the multicast routing method based on a modified stochastic branching process is proposed. The stochastic branching process is often used to describe an early stage of an infectious disease outbreak, and the reproductive number in the process is used to classify the outbreak into a major or minor outbreak. The reproductive number to regulate the local transmission rate is adapted and modified for flying ad-hoc network communication. The performance of the proposed routing method is compared with other well-known methods such as flooding method and gossip method based on three measures; average reachability, average node usage and average branching factor. The proposed routing method achieves average reachability very closer to flooding method, average node usage closer to gossip method, and outstanding average branching factor among methods. It can be concluded that the proposed multicast routing scheme is more efficient than well-known routing schemes such as flooding and gossip while it maintains high performance.

Keywords: Flying Ad-hoc Networks, Multicast Routing, Stochastic Branching Process, Unmanned Aerial Vehicles

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Authors: Abigaba Sophia

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Artificial intelligence (AI) has transformed the education sector by revolutionizing educational frameworks by providing new opportunities and innovative advanced platforms for language translation during the teaching and learning process. In today's education sector, the primary key to scholarly communication is language; therefore, translation between different languages becomes vital in the process of communication. KIU-T being an International University, admits students from different nations speaking different languages, and English is the official language; some students find it hard to grasp a word during teaching and learning. This paper explores the practical aspect of using artificial intelligence technologies in an advanced language translation manner during teaching and learning. The impact of this technology is reflected in the education strategies to equip students with the necessary knowledge and skills for professional activity in the best way they understand. The researcher evaluated the demand for this practice since students have to apply the knowledge they acquire in their native language to their countries in the best way they understand. The main objective is to improve student's language competence and lay a solid foundation for their future professional development. A descriptive-analytic approach was deemed best for the study to investigate the phenomena of language translation intelligence alongside Microsoft Office during the teaching and learning process. The study analysed the responses of 345 students from different academic programs. Based on the findings, the researcher recommends using the artificial intelligence language translation technique during teaching, and this requires the wisdom of human content designers and educational experts. Lecturers and students will be trained in the basic knowledge of this technique to improve the effectiveness of teaching and learning to meet the student’s needs.

Keywords: artificial intelligence, language translation technique, teaching and learning process, Microsoft Office

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Authors: Andrea Palazzo, Daniel Macek, Veronika Malinova

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Contour processing is the new technology challenge for architects and construction companies. The many advantages it promises make it one of the most interesting solutions for construction in terms of automation of building processes. The technology for 3D printing houses offers many application possibilities, from low-cost construction, to being considered by NASA for visionary projects as a good solution for building settlements on other planets. Another very important point is that clients, as architects, will no longer have many limits in design concerning ideas and creativity. The prices for real estate are constantly increasing and the lack of availability of construction materials as well as the speculation that has been created around it in 2021 is bringing prices to such a level that in the future real estate developers risk not being able to find customers for these ultra-expensive homes. Hence, this paper starts with the introduction of 3D printing, which now has the potential to gain an important position in the market, becoming a valid alternative to the classic construction process. This technology is not only beneficial from an economic point of view but it is also a great opportunity to have an impact on the environment by reducing CO2 emissions. Further on in the article we will also understand if, after the COP 26 (2021 United Nations Climate Change Conference), world governments could also push towards building technologies that reduce the waste materials that are needed to be disposed of and at the same time reduce emissions with the contribution of governmental funds. This paper will give us insight on the multiple benefits of 3D printing and emphasise the importance of finding new solutions for materials that can be used by the printer. Therefore, based on the type of material, it will be possible to understand the compatibility with current regulations and how the authorities will be inclined to support this technology. This will help to enable the rise and development of this technology in Europe and in the rest of the world on actual housing projects and not only on prototypes.

Keywords: additive manufacturing, contour crafting, development, new regulation, printing material

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Authors: Maitree Thamma, Witchupong Wiboonjaroen, Thanat Suknuan, Karan Homchat

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First order plus dead time (FOPDT) is a high dynamic system. Therefore, the controller must be intelligent. This paper presents the development and implementation of self-tuning Fuzzy-PID controller for controlling the FOPDT system. The water level process used represented FOPDT system and the mathematical model of the system was approximated by using System Identification toolbox in Matlab. The control programming and Fuzzy-PID algorithm used Matlab/Simulink and run on Microcontroller STM32.

Keywords: real-time control, self-tuning fuzzy-PID, FOPDT system, the water lever process

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Authors: Ola Jon Mork, Lars Andre Giske, Emil Bjørlykhaug

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Stabilization of critical processes in order to have the right quality of the products, more efficient production and smoother flow is a key issue in lean production. This paper presents how simulation of key welding processes can stabilize complicated welding processes in small scale production, and how simulation can impact the entire production concept seen from the perspective of lean production. First, a field study was made to learn the production processes in the factory, and subsequently the field study was transformed into a value stream map to get insight into each operation, the quality issues, operation times, lead times and flow of materials. Valuable practical knowledge of how the welding operations were done by operators, appropriate tools and jigs, and type of robots that could be used, was collected. All available information was then implemented into a simulation environment for further elaboration and development. Three researchers, the management of the company and skilled operators at the work floor where working on the project over a period of eight months, and a detailed description of the process was made by the researchers. The simulation showed that simulation could solve a number of technical challenges, the robot program can be tuned in off line mode, and the design and testing of the robot cell could be made in the simulator. Further on the design of the product could be optimized for robot welding and the jigs could be designed and tested in simulation environment. This means that a key issue of lean production can be solved; the welding operation will work with almost 100% performance when it is put into real production. Stabilizing of one key process is critical to gain control of the entire value chain, then a Takt Time can be established and the focus can be directed towards the next process in the production which should be stabilized. Results show that industrial parameters like welding time, welding cost and welding quality can be defined on the simulation stage. Further on, this gives valuable information for calculation of the factories business performance, like manufacturing volume and manufacturing efficiency. Industrial impact from simulation is more efficient implementation of lean manufacturing, since the welding process can be stabilized. More research should be done to gain more knowledge about simulation as a tool for implementation of lean, especially where there complex processes.

Keywords: simulation, lean, stabilization, welding process

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Authors: A. R. Shakura, A. B. Elistina, M. S. Aini, S. Norhasmah, A. Fakhru’l-Razi

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Tsunami 2004 was an unforeseeable event that caught Malaysia of guard resulting with 68 losses of lives and with an estimated economic loss of about 55.15billion US dollar. Scientists predict that if the earthquake epicentre originates from the Andaman-Nicobar region, the coastal population of Penang will have about 30 minutes to evacuate to safety. Thus, a study was conducted to enhance resiliency of Penang community as the area was the worst affected region during 2004 tsunami disaster. This paper is intended to examine the factors that influence intention to prepare for future tsunami among the coastal residence in Penang. The differences in the level of intention to prepare were also examined between those who experience and did not experience the 2004 tsunami. This study utilized a cross-sectional research design using a survey method. A total of 503 respondents were chosen systematically and data gathered were analysed using SPSS. Both genders, male and female were equally represented with a mean age of 44 years. Data indicated that the level of intention to prepare for tsunami disaster was moderate (M=3.72) with no significant difference in intention to prepare between those who had experienced or had not experienced the 2004 tsunami. Subsequently, results from a multiple regression analysis found that sense of community to be the most influential factor followed by subjective norm, trust, positive outcome expectancy and risk perception, explaining the 57% variance in intention to prepare. These factors reflect the influence of the collectivistic culture in Malaysia whereby households plus communities have a central role in encouraging each other. Therefore, the findings highlights the potential of adopting a community based disaster risk management as recommended by the United Nations International Strategy Disaster Reduction (UNISDR) which encompasses the cooperation between the local community and relevant stakeholders in preparing for future tsunami disaster.

Keywords: disaster management, experience, intention to prepare, tsunami

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Beata Ślusarczyk, Sebastian Kot

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In subjective terms, Polish SME sector occupies a prominent position in the national economic development, in which planning of the management strategies should be primarily based on identifying and meeting the innovation needs. As a research sample, there is chosen a printing sector of industry. SMEs share in printing sector in Poland is estimated at the level of 81% of all enterprises. In recent years, the printing industry achieved one of the highest levels of EU support in Poland. There is a relatively high increase in the development of technological innovations in equipment and the associated significant increase in production capacity. It can be also noticed that on average, every third enterprise belonging to the printing industry has implemented innovations, but not all of them effected in better economic results. Therefore, the aim of this article is to evaluate the impact of the implementation of innovation projects financed from the EU funds for performance of SMEs in the printing industry. As the results of research of EU funds co-financing effects on the development of innovation in the printing industry, it was specified that examined SMEs prefer to implement product innovation to receive a grant to the project at a level between 40% to 60%, the remaining part of the investment is usually covered with equity. The most common type of innovation had indicated a single implementation, related only to the change in process, technology, or organization. The relationship between variables of the EU funds and management of innovative activities was verified. It has been observed that the identified variables arising from the support in a form of the EU funds had a positive effect on the level of earned revenue, the increase in margin and in increase in employment as well. It was confirmed that the implemented innovations supported by the European funds have a positive impact on the performance of the printing companies. Although there is a risk that due to the decreasing demand for printing services such a high level of funding the companies in this sector will significantly increase competition in the long term, that may also contribute to the economic problems of the enterprises belonging to the analyzed branch.

Keywords: innovations, SMEs, performance, results

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Authors: Samir Ranjbar, Nasrullah Istanekzai

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According to a report published in The Guardian, Kabul, the capital city of Afghanistan is the fifth fastest growing city in the world, whose population has increased fourfold since 2001 from 1.2 million to 4.8 million people. The main reason for this increment is identified as the return of Afghans migrated during the civil war. In addition to the return of immigrants, a steep economic growth due to foreign assistance in last decade creating lots of job opportunities in Kabul resulted in the attraction of individuals from the neighboring provinces as well. However, the development of urban facilities such as water supply system, housing transportation and waste management systems has yet to catch up with this rapid increase in population. Since Kabul city has developed traditionally and municipal governance had very limited capacity to implement municipal bylaws. As an unwanted consequence of this growth 70% of Kabul citizens contributed to developing informal settlement for which we can say that around three million people living in informally settled areas, lacking the very vital social and physical infrastructures of livelihood. This research focuses on a region with 30 ha area and 2100 people residents in the center of Kabul city. A comprehensive land readjustment concept plan has been formulated for this area. Through this concept plan, physical and social infrastructure has been demonstrated and analyzed. Findings of this paper propose a solution for the problems of this unplanned area in Kabul which is readjusting of unplanned area by a self-supporting process. This process does not need governmental budget and can be applied by government, private sectors and landowner associations. Furthermore, by implementing the Land Readjustment process, conceptual plans can be built for unplanned areas, maximum facilities can be brought to the residents’ urban life, improve the environment for the users’ benefit, promote the culture and sense of cooperation, participation and coexistence in the mind of people, improving the transport system, improvement in economic status (the value of land increases due to infrastructure availability and land legalization). In addition to all these benefits for the public, we can raise the revenue of government by collecting the taxes from landowners. This process is implemented in most of countries of the world, it was implemented for the first time in Germany and after that in most cities of Japan as well, and is known as one of the effective processes for infrastructural development. To sum up, the notable characteristic of the Land readjustment process is that it works on the concept of mutual interest in which both landowners and the government take advantage. However, in this process, the engagement of community is very important and without public cooperation, this process can face the failure.

Keywords: land readjustment, informal settlement, Kabul, Afghanistan

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Authors: Lucia Antonela Mitidieri

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This research analyzes the application of a model of settlements management based on networks of territorial integration that advocates planning as a cyclical and participatory process that engages early on with civic society, the private sector and the state. Through qualitative methods such as participant observation, interviews with snowball technique and an active research on territories, concrete results of community empowerment are obtained from the promotion of productive enterprises and community spaces of encounter and exchange. Studying the cultural and organizational dimensions of empowerment allows building indicators such as increase of capacities or community cohesion that can lead to support local governments in achieving sustainable urban development for a reduction of urban poverty.

Keywords: community spaces, empowerment, network urbanism, participatory process

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Authors: Shane David van Zyl, A. J. Burger

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The global green energy shift has placed significant value on the production of green hydrogen and its derivatives. The study examines the impact on capital expenditure (CAPEX), operational expenditure (OPEX), levelized cost, and environmental impact, depending on the relationship between various production capacities of potable water, green hydrogen, and green ammonia. A model-based sensitivity analysis approach was used to determine the relevance of various process parameters in the production of potable water combined with green hydrogen or green ammonia production. The effects of changes on CAPEX, OPEX and levelized costs of the products were determined. Furthermore, a qualitative environmental impact analysis was done to determine the effect on the environment. The findings indicated the individual process unit contribution to the overall CAPEX and OPEX while also determining the major contributors to changes in the levelized costs of products. The results emphasize the difference in costs associated with potable water, green hydrogen, and green ammonia production, indicating the extent to which potable water production costs become insignificant in the complete process, which, therefore, can have a large social benefit through increased potable water production resulting in decreased water scarcity in the south-west African region.

Keywords: CAPEX and OPEX, desalination, green hydrogen and green ammonia, sensitivity analysis

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Authors: Abdullah Almlaki, Anamaria Berea

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Social media platforms, such as Twitter, reflect public opinion well on various topics. However, current methods demonstrate limited accuracy in automated processes reflecting aggregate crowd beliefs. For example, many tweets, especially in the Arabic region, include spam. We propose a revised methodology using machine learning techniques by applying two filters, removing news and spam, from Arabic tweets before the sentiment analysis process. Afterwards, during the classification process, we propose incrementing the polarity score by the retweets and favorites. We show our revision methodology improves the accuracy of automated real opinion detection.

Keywords: computing methodologies, artificial intelligence, natural language processing, social media analysis

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Authors: Jemini Vyas, Oluwatobi Adeyoe, Jenny Branagan, Chandran Tanabalan, John Beatty, Aakash Pai

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Introduction: The development of robotic surgery has accelerated centralisation to tertiary centres, where robotic radical prostatectomy (RP) is offered. The purpose of concentrating treatment in high volume specialist centres is to improve the quality of care and patient outcomes. The aim of this study was to assess the impact on clinical outcomes of centralisation for locally diagnosed patients undergoing RP. Methods: Clinical outcomes for 169 consecutive laparoscopic & open RP pre-centralisation were retrospectively compared with 50 consecutive robotic RP conducted over a similar period post-centralisation. Preoperative risk stratification and time to surgery were collected. Perioperative outcomes, including length of stay (LOS) and complications, were collated. Post-operative outcomes, including erectile dysfunction (ED), biochemical recurrence (BCR), and urinary continence, were assessed. Results: Preoperative risk stratification showed no difference between the two groups. The median time from diagnosis to treatment was similar between the two groups (pre-centralisation, 121 days, post-centralisation, 117 days). The mean length of stay (pre-centralisation, 2.1 days, post-centralisation, 1.6 days) showed no significant difference (p=0.073). Proportion of overall complications (pre-centralisation, 11.4%, post-centralisation, 8.7%) and complications, above Clavien-Dindo 2, were similar between the two groups (pre-centralisation1.2%, post-centralisation 2.2%). Post operative functional parameters, including continence and ED, were comparable. Five-year BCR free rate was 78% for the pre-centralisation group and 79% for the post centralisation group. Conclusion: For our cohort of patients, clinical outcomes have remained static during centralisation. It is imperative that centralisation is accompanied by increased capacity, streamlining of pathways, and training to ensure that improved quality of care is achieved. Our institution has newly acquired a robot, and prospectively studying this data may support the reversal of centralisation for RP surgery.

Keywords: prostate, cancer, prostatectomy, clinical

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Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

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Authors: Styliani Kotrotsiou, Evagelia Kotrotsiou, Fani Mokia, Theodosis Paralikas, Konstantinos Tsaras

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Objective: The objective of this study was the investigation of the mental health of patients undergoing chronic or transient hemodialysis at Artificial Kidney Unit, as well as its relationship to the demographic characteristic of patients. Material and Method: The study took place in Larisa during the month of December in 2016 and the sample was composed of 60 patients undergoing in chronic or transient hemodialysis at Artificial Kidney Unit of the University General Hospital of Larisa. For the investigation of the physical and mental health of patients who participated in the study, the tool measurement << General Health Questionnaire- 28 >> (GHQ-28) was used. The questionnaires were administered with the interview method during the hemodialysis. This survey is designed for the existence or not of a mental disorder. It examines four factors (physical symptoms, anxiety, social dysfunction and depression). Results: The hemodialysis patients gave the following scores: -to the physical symptoms, women showed a higher average value than men (1,16 ± 1,26 against 0,49 ± 0,93), -at the anxiety scale, it seems that women are superior to men (1,68 ± 1,20 against 0,90 ± 1,22), -at the social dysfunction scale, the elderly patients ( > 65 years old) were presented a with higher average (2,59), and -at the depression scale, patients with a higher average value were those who lived in non-urban areas. The appearance of mental disorder, in relation to patient characteristics, did not show significant statistical correlation. The sex, the age and the place of residence affect more the assessment of mental health, while education did not seem to have any significant effect on the other. Conclusions: The hemodialysis process can significantly affect the patient’s Quality of Life and it can bring adverse changes in lifestyle, affecting the physical, social and psychological state of the individual. For that reason, hemodialysis should be aimed not only at extending life but in upgrading the Quality of Life.

Keywords: hemodialysis, chronic kidney disease, depression, social dysfunction, physical condition

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Authors: Anastasios Manos, Despina Elisabeth Filippidou

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Introduction: Historical buildings are an inte-gral part of the cultural heritage of every place, and beyond the obvious need for protection against risks, they have specific requirements regarding the handling of hazards and disasters such as fire, floods, earthquakes, etc. Ensuring high levels of protection and safety for these buildings is impera-tive for two distinct but interconnected reasons: a) they themselves constitute cultural heritage, and b) they are often used as museums/cultural spaces, necessitating the protection of both human life (vis-itors and workers) and the cultural treasures they house. However, these buildings present serious constraints in implementing the necessary measures to protect them from destruction due to their unique architecture, construction methods, and/or the structural materials used in the past, which have created an existing condition that is sometimes challenging to reshape and operate within the framework of modern regulations and protection measures. One of the most devastating risks that threaten historical buildings is fire. Catastrophic fires demonstrate the need for timely evaluation of fire safety measures in historical buildings. Recog-nizing the criticality of protecting historical build-ings from the risk of fire, the Confederation of Fire Protection Associations in Europe (CFPA E) issued specific guidelines in 2013 (CFPA-E Guideline No 30:2013 F) for the fire protection of historical buildings at the European level. However, until now, few actions have been implemented towards leveraging modern technologies in the field of con-struction and maintenance of buildings, such as Building Information Modeling (BIM) and the Inter-net of Things (IoT), for the protection of historical buildings from risks like fires, floods, etc. The pro-ject BIM4Cult has bee developed in order to fill this gap. It is a tool for timely assessing and monitoring of the fire safety level of historical buildings using BIM and IoT technologies in an integrated manner. The tool serves as a decision support expert system for improving the fire safety of historical buildings by continuously monitoring, controlling and as-sessing critical risk factors for fire.

Keywords: Iot, fire, BIM, expert system

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Authors: Raymond Puijk, Rachid Rassir, Inger N. Sierevelt, Anneke Spekenbrink-Sporen, Bart G. C. W. Pijls, Rob G. H. H. Nelissen, Peter A. Nolte

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Background: Among uncemented total knee arthroplasty (TKA), a wide variety of metal surface structures (MSS) and coatings exist to enhance implants' biological properties (i.e., bone ingrowth). This study explores the variety of MSS-coating combinations and compares their mid-long-term survivorships with cemented TKAs, by using data from the Dutch Arthroplasty Register. Methods: A total of 235,500 cemented and 11,132 uncemented primary TKAs with a median follow-up of 5.1 years were included. MSS-coating combinations were (1) Porous-uncoated (n=8986), (2) Beaded-hydroxyapatite (HA)(n=1093), (3) Matte-uncoated (n=846), (4) Matte-Titanium-nitride (TiN) (n=207). Five- and 10-year revision-free survival for all-cause revisions, and aseptic loosening of the tibial component, were calculated and compared by using Kaplan-Meier, Log-rank tests, and multivariable Cox proportional hazard regression analyses. Results: Ten-year survival rates with all-cause revisions as an endpoint, were 94.2% for cement, and 94.7%, 96.3%, 92.1%, and 79.0% for porous-uncoated, beaded-HA, matte-uncoated, and Matte-TiN, respectively (p<0.01). Rates for aseptic loosening were 98.8% for cemented, and 98.7%, 99.8%, 97.2%, and 94.9% for the uncemented, respectively (p<0.01).The beaded-HA implants were half the risk for an all-cause revision compared to cemented implants (p<0.01). Matte-uncoated and matte-TiN implants were at more risk of an all-cause revision than cemented implants (p=0.01, p<0.01). Proportions of revisions for aseptic loosening were comparable among most groups. Conclusion: Based on Dutch registry data, four main MSS-coating combinations among uncemented TKAs were found. survivorships for all-cause revisions and aseptic release differed widely between groups. Beaded-HA and porous-uncoated implants had the best survival rates among the uncemented TKAs and were non-inferior to the cemented TKAs.

Keywords: total knee arthroplasty, cement, uncemented, cementless;, metal surface structure, coating

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Authors: Rahaf Mandura

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Background: Idiopathic intracranial hypertension (IIH) is a disorder with elevated intracranial pressure (ICP) more than 250 mm H₂O, without evidence of meningeal inflammation, space-occupying lesion, or venous thrombosis. The aim of this research is to study the clinical profile, evaluation, management, and visual outcome in a hospital-based population of IIH cases in Jeddah. Methodology: This is a retrospective observational study that included the medical records of all patients referred to neuro-ophthalmology service for evaluation of papilledema. The medical records have been reviewed from October 2018 to February 2020 at Jeddah Eye Hospital (JEH), Saudi Arabia. A total of fifty-one patients presented with papilledema in the studied period. Forty-seven patients met our inclusion criteria and were included in the study. Results: Most of the patients were females (43, 91.5%) with a mean age of presentation of 30.83±11.40 years. The most common presenting symptom was headache (40 patients, 85.1%), followed by transient visual obscuration (20 patients, 42.6%), and reduced visual acuity (15 patients, 31.9%). All 47 patients were started on medical treatment with oral acetazolamide with four patients (8.5%) shifted to topiramate because of the lack of response or intolerance to acetazolamide while four patients (8.5%) underwent lumbar-peritoneal shunt because of inadequate control of the disease despite the treatment with medical therapy. For both eyes, the change in visual acuity across all assessment points was statistically significant. Nevertheless, there were no significant changes in the visual field findings among all of the compared assessment points. Conclusion: The present study has shown that IIH-related papilledema is common in young female patients with headaches, transient visual obscurations and reduced visual acuity. Those are the commonest symptoms in our IIH population. Medical treatment of IIH is significantly efficacious and should be considered in order to enhance the prognosis of IIH-related complications. Therefore, the visual status should be frequently monitored for these patients.

Keywords: idiopathic intracranial hypertension, intracranial hypertension, papilledema, headache

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Authors: Alena Skalon, Jennifer L. Beaudry

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Eyewitness misidentifications can sometimes lead to wrongful convictions of innocent people. This occurs in part because jurors tend to believe confident eyewitnesses even when the identification took place under suggestive conditions. Empirical research demonstrated that jurors are often unaware of the factors that can influence the reliability of eyewitness identification. Most common legal safeguards that are designed to educate jurors about eyewitness evidence are judicial instructions and expert testimony. To date, very few studies assessed the effectiveness of judicial instructions and most of them found that judicial instructions make jurors more skeptical of eyewitness evidence or do not have any effect on jurors’ judgments. Similar results were obtained for expert testimony. However, none of the previous studies focused on the ability of legal safeguards to improve jurors’ assessment of evidence obtained from suggestive identification procedures—this is one of the gaps addressed by this paper. Furthermore, only three studies investigated whether legal safeguards improve the ultimate accuracy of jurors’ judgments—that is, whether after listening to judicial instructions or expert testimony jurors can differentiate between accurate and inaccurate eyewitnesses. This presentation includes two studies. Both studies used genuine eyewitnesses (i.e., eyewitnesses who watched the crime) and manipulated the suggestiveness of identification procedures. The first study manipulated the presence of judicial instructions; the second study manipulated the presence of one of two types of expert testimony: a traditional, verbal expert testimony or expert testimony accompanied by visual aids. All participant watched a video-recording of an identification procedure and of an eyewitness testimony. The results indicated that neither judicial instructions nor expert testimony affected jurors’ judgments. However, consistent with the previous findings, when the identification procedure was non-suggestive, jurors believed accurate eyewitnesses more often than inaccurate eyewitnesses. When the procedure was suggestive, jurors believed accurate and inaccurate eyewitnesses at the same rate. The paper will discuss the implications of these studies and directions for future research.

Keywords: expert testimony, eyewitness evidence, judicial instructions, jurors’ decision making, legal safeguards

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Authors: Hoda Ghavamipoor, S. Alireza Hashemi Golpayegani

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An approach to model the customer interaction with e-commerce websites is presented. Considering the service quality level as a predictive feature, we offer an improved method based on the Customer Behavior Model Graph (CBMG), a state-transition graph model. To derive the Quality of Service sensitive-CBMG (QoS-CBMG) model, process-mining techniques is applied to pre-processed website server logs which are categorized as ‘buy’ or ‘visit’. Experimental results on an e-commerce website data confirmed that the proposed method outperforms CBMG based method.

Keywords: customer behavior model, electronic commerce, quality of service, customer behavior model graph, process mining

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Authors: Golnoosh Torabian, P. Valtchev, F. Dehghani

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The need for efficient nutraceutical products has been dramatically changing the approach of the industrial processes. The development of novel mild processes is highly demanded for the production of such products; especially when both quality and safety need to be guaranteed during their long shelf life. Within this research, for the first time, we investigated the effect of supercritical carbon dioxide treatment for the inactivation of microbes and enzymes in a berry juice possessing therapeutic effect. We demonstrated that a complete inactivation of microbes can be achieved at optimized conditions of treatment. However, the bottle neck of the process was represented by the unpromising inactivation of the degradative enzyme by supercritical carbon dioxide treatment. However, complete enzyme inactivation was achieved by applying two strategies: the first was optimizing juicing method by adding a mechanical step and the second strategy was addition of natural inhibitors to the juice. Overall these results demonstrate that our hybrid process has a significant effect on the inactivation of microorganism and enzymes in the fresh juice. The developed process opens the possibility for the evolution of new products with optimal nutritional and sensorial characteristics, as well as offering a competitive cost and an environmentally friendly alternative for pasteurization and extension of shelf life in a wide range of natural therapeutic products.

Keywords: hybrid method, berry juice, pasteurization, enzymes inactivation

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Authors: Tolulope Aremu

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This paper is based on the idea of using deep learning methodology for optimizing production yield by tuning a few key process parameters in a manufacturing environment. The study was explicitly on how to maximize production yield and minimize operational costs by utilizing advanced neural network models, specifically Long Short-Term Memory and Convolutional Neural Networks. These models were implemented using Python-based frameworks—TensorFlow and Keras. The targets of the research are the precision molding processes in which temperature ranges between 150°C and 220°C, the pressure ranges between 5 and 15 bar, and the material flow rate ranges between 10 and 50 kg/h, which are critical parameters that have a great effect on yield. A dataset of 1 million production cycles has been considered for five continuous years, where detailed logs are present showing the exact setting of parameters and yield output. The LSTM model would model time-dependent trends in production data, while CNN analyzed the spatial correlations between parameters. Models are designed in a supervised learning manner. For the model's loss, an MSE loss function is used, optimized through the Adam optimizer. After running a total of 100 training epochs, 95% accuracy was achieved by the models recommending optimal parameter configurations. Results indicated that with the use of RSM and DOE traditional methods, there was an increase in production yield of 12%. Besides, the error margin was reduced by 8%, hence consistent quality products from the deep learning models. The monetary value was annually around $2.5 million, the cost saved from material waste, energy consumption, and equipment wear resulting from the implementation of optimized process parameters. This system was deployed in an industrial production environment with the help of a hybrid cloud system: Microsoft Azure, for data storage, and the training and deployment of their models were performed on Google Cloud AI. The functionality of real-time monitoring of the process and automatic tuning of parameters depends on cloud infrastructure. To put it into perspective, deep learning models, especially those employing LSTM and CNN, optimize the production yield by fine-tuning process parameters. Future research will consider reinforcement learning with a view to achieving further enhancement of system autonomy and scalability across various manufacturing sectors.

Keywords: production yield optimization, deep learning, tuning of process parameters, LSTM, CNN, precision manufacturing, TensorFlow, Keras, cloud infrastructure, cost saving

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Authors: Narendra Akhadkar, Silvestre Cano, Christophe Gourru

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Injection-molded parts are widely used in power system protection products. One of the biggest challenges in an injection molding process is shrinkage and warpage of the molded parts. All these geometrical variations may have an adverse effect on the quality of the product, functionality, cost, and time-to-market. The situation becomes more challenging in the case of intricate shapes and in mass production using multi-cavity tools. To control the effects of shrinkage and warpage, it is very important to correctly find out the input parameters that could affect the product performance. With the advances in the computer-aided engineering (CAE), different tools are available to simulate the injection molding process. For our case study, we used the MoldFlow insight tool. Our aim is to predict the spread of the functional dimensions and geometrical variations on the part due to variations in the input parameters such as material viscosity, packing pressure, mold temperature, melt temperature, and injection speed. The input parameters may vary during batch production or due to variations in the machine process settings. To perform the accurate product assembly variation simulation, the first step is to perform an individual part variation simulation to render realistic tolerance ranges. In this article, we present a method to simulate part variations coming from the input parameters variation during batch production. The method is based on computer simulations and experimental validation using the full factorial design of experiments (DoE). The robustness of the simulation model is verified through input parameter wise sensitivity analysis study performed using simulations and experiments; all the results show a very good correlation in the material flow direction. There exists a non-linear interaction between material and the input process variables. It is observed that the parameters such as packing pressure, material, and mold temperature play an important role in spread on functional dimensions and geometrical variations. This method will allow us in the future to develop accurate/realistic virtual prototypes based on trusted simulated process variation and, therefore, increase the product quality and potentially decrease the time to market.

Keywords: correlation, molding process, tolerance, sensitivity analysis, variation simulation

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Authors: Arosha Rashmi De Silva, Ananda Chandrasekara

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This study seeks to comprehensively examine the influence of fast-food consumption and physical activity levels on the body weight of young employees within the private sector of Sri Lanka. The escalating popularity of fast food has raised concerns about its nutritional content and associated health ramifications. To investigate this phenomenon, a cohort of 100 individuals aged between 25 and 45, employed in Sri Lanka's private sector, participated in this research. These participants provided socio-demographic data through a standardized questionnaire, enabling the characterization of their backgrounds. Additionally, participants disclosed their frequency of fast-food consumption and engagement in physical activities, utilizing validated assessment tools. The collected data was meticulously compiled into an Excel spreadsheet and subjected to rigorous statistical analysis. Descriptive statistics, such as percentages and proportions, were employed to delineate the body weight status of the participants. Employing chi-square tests, our study identified significant associations between fast-food consumption, levels of physical activity, and body weight categories. Furthermore, through binary logistic regression analysis, potential risk factors contributing to overweight and obesity within the young employee cohort were elucidated. Our findings revealed a disconcerting trend, with 6% of participants classified as underweight, 32% within the normal weight range, and a substantial 62% categorized as overweight or obese. These outcomes underscore the alarming prevalence of overweight and obesity among young private-sector employees, particularly within the bustling urban landscape of Colombo, Sri Lanka. The data strongly imply a robust correlation between fast-food consumption, sedentary behaviors, and higher body weight categories, reflective of the evolving lifestyle patterns associated with the nation's economic growth. This study emphasizes the urgent need for effective interventions to counter the detrimental effects of fast-food consumption. The implementation of awareness campaigns elucidating the adverse health consequences of fast food, coupled with comprehensive nutritional education, can empower individuals to make informed dietary choices. Workplace interventions, including the provision of healthier meal alternatives and the facilitation of physical activity opportunities, are essential in fostering a healthier workforce and mitigating the escalating burden of overweight and obesity in Sri Lanka

Keywords: fast food consumption, obese, overweight, physical activity level

Procedia PDF Downloads 57