Search results for: innovative model for inclusion

Authors: Haifeng Wang, Haili Zhang

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Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: computational social science, movie preference, machine learning, SVM

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Authors: Muhammad Abu-Khaizaran, Ahmad Faza’, Tariq Othman, Yahia Yousef

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This paper presents a study to provide sufficient and reliable information about constructing a Photovoltaic energy profile of the Birzeit University campus (BZU) based on the weather forecast. The developed Photovoltaic energy profile helps to predict the energy yield of the Photovoltaic systems based on the weather forecast and hence helps planning energy production and consumption. Two models will be developed in this paper; a Clear Sky Irradiance model and a Cloud-Cover Radiation model to predict the irradiance for a clear sky day and a cloudy day, respectively. The adopted procedure for developing such models takes into consideration two levels of abstraction. First, irradiance and weather data were acquired by a sensory (measurement) system installed on the rooftop of the Information Technology College building at Birzeit University campus. Second, power readings of a fully operational 51kW commercial Photovoltaic system installed in the University at the rooftop of the adjacent College of Pharmacy-Nursing and Health Professions building are used to validate the output of a simulation model and to help refine its structure. Based on a comparison between a mathematical model, which calculates Clear Sky Irradiance for the University location and two sets of accumulated measured data, it is found that the simulation system offers an accurate resemblance to the installed PV power station on clear sky days. However, these comparisons show a divergence between the expected energy yield and actual energy yield in extreme weather conditions, including clouding and soiling effects. Therefore, a more accurate prediction model for irradiance that takes into consideration weather factors, such as relative humidity and cloudiness, which affect irradiance, was developed; Cloud-Cover Radiation Model (CRM). The equivalent mathematical formulas implement corrections to provide more accurate inputs to the simulation system. The results of the CRM show a very good match with the actual measured irradiance during a cloudy day. The developed Photovoltaic profile helps in predicting the output energy yield of the Photovoltaic system installed at the University campus based on the predicted weather conditions. The simulation and practical results for both models are in a very good match.

Keywords: clear-sky irradiance model, cloud-cover radiation model, photovoltaic, weather forecast

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Authors: Taki Eddine Seghier, Mohd Hamdan Ahmad, Yaik-Wah Lim, Samuel Opeyemi Williams

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The assessment of building sustainability to achieve a specific green benchmark and the preparation of the required documents in order to receive a green building certification, both are considered as major challenging tasks for green building design team. However, this labor and time-consuming process can take advantage of the available Building Information Modeling (BIM) features such as material take-off and scheduling. Furthermore, the workflow can be automated in order to track potentially achievable credit points and provide rating feedback for several design options by using integrated Visual Programing (VP) to handle the stored parameters within the BIM model. Hence, this study proposes a BIM-based tool that uses Green Building Index (GBI) rating system requirements as a unique input case to evaluate the building sustainability in the design stage of the building project life cycle. The tool covers two key models for data extraction, firstly, a model for data extraction, calculation and the classification of achievable credit points in a green template, secondly, a model for the generation of the required documents for green building certification. The tool was validated on a BIM model of residential building and it serves as proof of concept that building sustainability assessment of GBI certification can be automatically evaluated and documented through BIM.

Keywords: green building rating system, GBRS, building information modeling, BIM, visual programming, VP, sustainability assessment

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Authors: Vahid Nourani, Atefeh Ashrafi

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Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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Authors: Helena Macedo, Larissa Tomaz, Levi Guimarães, Luís Cerqueira-Pinto, José Dinis-Carvalho

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In the context of retail logistics, the pursuit of operational efficiency and cost optimization involves a rigorous distinction between value-added and non-value-added activities. In today's competitive market, optimizing efficiency and reducing operational costs are paramount for retail businesses. This research paper focuses on the development of a classification model adapted to the retail sector, specifically examining internal logistics processes. Based on a comprehensive analysis conducted in a retail supermarket located in the north of Portugal, which covered various aspects of internal retail logistics, this study questions the concept of value and the definition of wastes traditionally applied in a manufacturing context and proposes a new way to assess activities in the context of internal logistics. This study combines quantitative data analysis with qualitative evaluations. The proposed classification model offers a systematic approach to categorize operations within the retail logistics chain, providing actionable insights for decision-makers to streamline processes, enhance productivity, and allocate resources more effectively. This model contributes not only to academic discourse but also serves as a practical tool for retail businesses, aiding in the enhancement of their internal logistics dynamics.

Keywords: lean retail, lean logisitcs, retail logistics, value-added and non-value-added

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Authors: Mo Zhou, Samantha Ashby, Lyn Ebert

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In China, the changes that men experience in the perinatal period are not well researched. Men are also at risk of maladaptation to parenthood. The aim of this research is to review current studies regarding changes that Chinese men experience during transitioning to parenthood. 5 databases were employed to search relevant papers. The search found 128 articles. Based on the inclusion and exclusion criteria, 35 articles were included in this integrative review. Results showed the changes that Chinese fathers experienced during the transition to parenthood can be divided into two aspects: family relationships and mental problems. During transition to parenthood, fathers usually experienced an increase in their disappointment with marital conflict resolution and decreased sexual intimacy with their partner. Mental health declined, with fathers often feeling depressed and/or anxious during this time. Some men were diagnosed with clinical depression. The predictors of these changes included three domains: personal background (age and income), family background (gender of infant, relationship status and unplanned child) and cultural background (‘doing the month’, Confucianism, policy, social support).

Keywords: China, men, fatherhood, life change, postpartum

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Authors: Zina Ghiloufi, Tahar Khir

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A transient three-dimensional computational fluid dynamics (CFD) model is developed to determine the velocity and temperature distribution in different positions cold room during pre-cooling of dates. The turbulence model used is the k-ω Shear Stress Transport (SST) with the standard wall function, the air. The numerical results obtained show that cooling rate is not uniform inside the room; the product at the medium of room has a slower cooling rate. This cooling heterogeneity has a large effect on the energy consumption during cold storage.

Keywords: CFD, cold room, cooling rate, dDates, numerical simulation, k-ω (SST)

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Authors: Man-Yu Wong, Siyu Zhou, Zhiqiang Cao

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In quality of life, health service utilization is an important determinant of medical resource expenditures on Colorectal cancer (CRC) care, a better understanding of the increased utilization of health services is essential for optimizing the allocation of healthcare resources to services and thus for enhancing the service quality, especially for high expenditure on CRC care like Hong Kong region. In assessing the association between the health-related quality of life (HRQOL) and health service utilization in patients with colorectal neoplasm, count data models can be used, which account for over dispersion or extra zero counts. In our data, the HRQOL evaluation is a self-reported measure obtained from a questionnaire completed by the patients, misreports and variations in the data are inevitable. Besides, there are more zero counts from the observed number of clinical consultations (observed frequency of zero counts = 206) than those from a Poisson distribution with mean equal to 1.33 (expected frequency of zero counts = 156). This suggests that excess of zero counts may exist. Therefore, we study tests for detecting zero-inflation in models with measurement error in covariates. Method: Under classical measurement error model, the approximate likelihood function for zero-inflation Poisson regression model can be obtained, then Approximate Maximum Likelihood Estimation(AMLE) can be derived accordingly, which is consistent and asymptotically normally distributed. By calculating score function and Fisher information based on AMLE, a score test is proposed to detect zero-inflation effect in ZIP model with measurement error. The proposed test follows asymptotically standard normal distribution under H0, and it is consistent with the test proposed for zero-inflation effect when there is no measurement error. Results: Simulation results show that empirical power of our proposed test is the highest among existing tests for zero-inflation in ZIP model with measurement error. In real data analysis, with or without considering measurement error in covariates, existing tests, and our proposed test all imply H0 should be rejected with P-value less than 0.001, i.e., zero-inflation effect is very significant, ZIP model is superior to Poisson model for analyzing this data. However, if measurement error in covariates is not considered, only one covariate is significant; if measurement error in covariates is considered, only another covariate is significant. Moreover, the direction of coefficient estimations for these two covariates is different in ZIP regression model with or without considering measurement error. Conclusion: In our study, compared to Poisson model, ZIP model should be chosen when assessing the association between condition-specific HRQOL and health service utilization in patients with colorectal neoplasm. and models taking measurement error into account will result in statistically more reliable and precise information.

Keywords: count data, measurement error, score test, zero inflation

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Authors: Peter Kress, Alexander Pflaum, Ulrich Loewen

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The number of Internet-of-Things (IoT) platforms is steadily increasing across various industries, especially for smart factories, smart homes and smart mobility. Also in the manufacturing industry, the number of Industrial-IoT platforms is growing. Both IT players, start-ups and increasingly also established industry players and small-and-medium-enterprises introduce offerings for the connection of industrial equipment on platforms, enabled by advanced information and communication technology. Beside the offered functionalities, the established ecosystem of partners around a platform is one of the key differentiators to generate a competitive advantage. The key question is how platform operators design the business model around their platform to attract a high number of customers and partners to co-create value for the entire ecosystem. The present research tries to answer this question by determining the key characteristics of business models of successful platforms in the manufacturing industry. To achieve that, the authors selected an explorative qualitative research approach and created an inductive comparative case study. The authors generated valuable descriptive insights of the business model elements (e.g., value proposition, pricing model or partnering model) of various established platforms. Furthermore, patterns across the various cases were identified to derive propositions for the successful design of business models of platforms in the manufacturing industry.

Keywords: industrial-internet-of-things, business models, platforms, ecosystems, case study

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Authors: Iman Farasat, Howard M. Salis

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The CRISPR/Cas9 system has revolutionized genome engineering by enabling site-directed and high-throughput genome editing, genome insertion, and gene knockdowns in several species, including bacteria, yeast, flies, worms, and human cell lines. This technology has the potential to enable human gene therapy to treat genetic diseases and cancer at the molecular level; however, the current CRISPR/Cas9 system suffers from seemingly sporadic off-target genome mutagenesis that prevents its use in gene therapy. A comprehensive mechanistic model that explains how the CRISPR/Cas9 functions would enable the rational design of the guide-RNAs responsible for target site selection while minimizing unexpected genome mutagenesis. Here, we present the first quantitative model of the CRISPR/Cas9 genome mutagenesis system that predicts how guide-RNA sequences (crRNAs) control target site selection and cleavage activity. We used statistical thermodynamics and law of mass action to develop a five-step biophysical model of cas9 cleavage, and examined it in vivo and in vitro. To predict a crRNA's binding specificities and cleavage rates, we then compiled a nearest neighbor (NN) energy model that accounts for all possible base pairings and mismatches between the crRNA and the possible genomic DNA sites. These calculations correctly predicted crRNA specificity across 5518 sites. Our analysis reveals that cas9 activity and specificity are anti-correlated, and, the trade-off between them is the determining factor in performing an RNA-mediated cleavage with minimal off-targets. To find an optimal solution, we first created a scheme of safe-design criteria for Cas9 target selection by systematic analysis of available high throughput measurements. We then used our biophysical model to determine the optimal Cas9 expression levels and timing that maximizes on-target cleavage and minimizes off-target activity. We successfully applied this approach in bacterial and mammalian cell lines to reduce off-target activity to near background mutagenesis level while maintaining high on-target cleavage rate.

Keywords: biophysical model, CRISPR, Cas9, genome editing

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Authors: Mballa Abanda Serge, Henda Gnakate Biba, Romaric Guemno Kuate, Akono Rufine Nicole, Petfiang Sidonie, Bella Sidonie

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The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original and innovative research thesis. The main hypotheses proposed around the definition of the syllable and of music, of the common origin of music and language, should lead the reader to reflect on the cross-cutting questions raised by the debate on the notion of universals in linguistics and musicology. These are objects of controversy, and there lies its interest: the debate raises questions that are at the heart of theories on language. It is an inventive, original and innovative research thesis. A contribution to the theoretical, musicological, ethno musicological and linguistic conceptualization of languages, giving rise to the practice of interlocution between the social and cognitive sciences, the activities of artistic creation and the question of modeling in the human sciences: mathematics, computer science, translation automation and artificial intelligence. When you apply this theory to any text of a folksong of a world-tone language, you do not only piece together the exact melody, rhythm, and harmonies of that song as if you knew it in advance but also the exact speaking of this language. The author believes that the issue of the disappearance of tonal languages and their preservation has been structurally resolved, as well as one of the greatest cultural equations related to the composition and creation of tonal, polytonal and random music. The experimentation confirming the theorization, It designed a semi-digital, semi-analog application which translates the tonal languages of Africa (about 2,100 languages) into blues, jazz, world music, polyphonic music, tonal and anatonal music and deterministic and random music). To test this application, I use a music reading and writing software that allows me to collect the data extracted from my mother tongue, which is already modeled in the musical staves saved in the ethnographic (semiotic) dictionary for automatic translation ( volume 2 of the book). Translation is done (from writing to writing, from writing to speech and from writing to music). Mode of operation: you type a text on your computer, a structured song (chorus-verse), and you command the machine a melody of blues, jazz and world music or variety etc. The software runs, giving you the option to choose harmonies, and then you select your melody.

Keywords: music, entanglement, langauge, science

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Authors: Jacob Livingston Slosser, Naja Holten Moller, Thomas Troels Hildebrandt, Henrik Palmer Olsen

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In this paper, we propose a model for human-AI interaction in public administration that involves legal decision-making. Inspired by Alan Turing’s test for machine intelligence, we propose a way of institutionalizing a continuous working relationship between man and machine that aims at ensuring both good legal quality and higher efficiency in decision-making processes in public administration. We also suggest that our model enhances the legitimacy of using AI in public legal decision-making. We suggest that case loads in public administration could be divided between a manual and an automated decision track. The automated decision track will be an algorithmic recommender system trained on former cases. To avoid unwanted feedback loops and biases, part of the case load will be dealt with by both a human case worker and the automated recommender system. In those cases an experienced human case worker will have the role of an evaluator, choosing between the two decisions. This model will ensure that the algorithmic recommender system is not compromising the quality of the legal decision making in the institution. It also enhances the legitimacy of using algorithmic decision support because it provides justification for its use by being seen as superior to human decisions when the algorithmic recommendations are preferred by experienced case workers. The paper outlines in some detail the process through which such a model could be implemented. It also addresses the important issue that legal decision making is subject to legislative and judicial changes and that legal interpretation is context sensitive. Both of these issues requires continuous supervision and adjustments to algorithmic recommender systems when used for legal decision making purposes.

Keywords: administrative law, algorithmic decision-making, decision support, public law

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Authors: Gyoomi Kim, Jiyoung Bae

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The purpose of this study was to propose a framework that verifies the structural relationships among students’ use of digital English learning strategy (DELS), affective domains, and their individual variables. The study developed a hypothetical model based on previous studies on language learning strategy use as well as digital language learning. The participants were 720 Korean high school students and 430 university students. The instrument was a self-response questionnaire that contained 70 question items based on Oxford’s SILL (Strategy Inventory for Language Learning) as well as the previous studies on language learning strategies in digital learning environment in order to measure DELS and affective domains. The collected data were analyzed through structural equation modeling (SEM). This study used quantitative data analysis procedures: Explanatory factor analysis (EFA) and confirmatory factor analysis (CFA). Firstly, the EFA was conducted in order to verify the hypothetical model; the factor analysis was conducted preferentially to identify the underlying relationships between measured variables of DELS and the affective domain in the EFA process. The hypothetical model was established with six indicators of learning strategies (memory, cognitive, compensation, metacognitive, affective, and social strategies) under the latent variable of the use of DELS. In addition, the model included four indicators (self-confidence, interests, self-regulation, and attitude toward digital learning) under the latent variable of learners’ affective domain. Secondly, the CFA was used to determine the suitability of data and research models, so all data from the present study was used to assess model fits. Lastly, the model also included individual learner factors as covariates and five constructs selected were learners’ gender, the level of English proficiency, the duration of English learning, the period of using digital devices, and previous experience of digital English learning. The results verified from SEM analysis proposed a theoretical model that showed the structural relationships between Korean students’ use of DELS and their affective domains. Therefore, the results of this study help ESL/EFL teachers understand how learners use and develop appropriate learning strategies in digital learning contexts. The pedagogical implication and suggestions for the further study will be also presented.

Keywords: Digital English Learning Strategy, DELS, individual variables, learners' affective domains, Structural Equation Modeling, SEM

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Authors: Nada Azhar

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As a developing country, The Kingdom of Saudi Arabia (KSA) needs to make the best possible use of its workforce for social and economic reasons. The workforce is diverse, calling for appropriate diversity management (DM). The thesis focuses on the banking sector in KSA. To date, there have been no studies on DM in the banking sector in this country. Many organizations have introduced specific policies and programmes to improve the recruitment, inclusion, promotion, and retention of diverse employees, in addition to the legal requirements existing in many countries. However, Western-centric models of DM may not be applicable, at least not in their entirety, in other regions. The aim of the study is to devise a framework for understanding gender, age and disability DM in the banking sector in KSA in order to enhance DM in this sector. A sample of 24 managers, 2 from each of the 12 banks, was interviewed to obtain their views on DM in the banking sector in KSA. Thematic analysis was used to analyze the data. These themes were used to develop the questionnaire, which was administered to 10 managers in each of the 12 banks. After analysis of these data, and completion of the study, the research will make a theoretical contribution to the knowledge on DM and a practical contribution to the management of diversity in Saudi banks. This paper concerns a work in progress.

Keywords: age, disability, diversity, gender, Kingdom of Saudi Arabia

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Authors: Sonia Hirt

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The Planner's Triangle, an oft-cited model that visually defined planning as the search for sustainability to balance the three basic priorities of equity, economy, and environment, has influenced planning theory and practice for a quarter of a century. In this essay, we argue that the triangle requires updating and expansion. Even if planners keep sustainability as their key core aspiration at the center of their imaginary geometry, the triangle's vertices have to be rethought. Planners should move on to a 21st-century concept. We propose a Planner's Pentangle with five basic priorities as vertices of a new conceptual polygon. These five priorities are Wellbeing, Equity, Economy, Environment, and Esthetics (WE⁴). The WE⁴ concept more accurately and fully represents planning’s history. This is especially true in the United States, where public art and public health played pivotal roles in the establishment of the profession in the late 19th and early 20th centuries. It also more accurately represents planning’s future. Both health/wellness and aesthetic concerns are becoming increasingly important in the 21st century. The pentangle can become an effective tool for understanding and visualizing planning's history and present. Planning has a long history of representing urban presents and future as conceptual models in visual form. Such models can play an important role in understanding and shaping practice. For over two decades, one such model, the Planner's Triangle, stood apart as the expression of planning's pursuit for sustainability. But if the model is outdated and insufficiently robust, it can diminish our understanding of planning practice, as well as the appreciation of the profession among non-planners. Thus, we argue for a new conceptual model of what planners do.

Keywords: sustainable development, planning for sustainable development, planner's triangle, planner's pentangle, planning and health, planning and art, planning history

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Authors: Gani Pllana

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In the conditions of the rapid development of technics and technology in recent years, the cooperation of the scientific-technical language with the standard Albanian language is continuing with a higher intensity than before. We notice a vigor of enrichment in the vocabulary of technical terminology, due to the birth and formation of new fields and subfields of technics, technology, as computing, mechatronics, telemetry, a multitude of concepts many of which, on the one hand, are marked with names of the languages they come from, mainly from English, but on the other hand, they meet their needs with the lexical mother tongue composition (by common words being raised to terms) and with the activation of other layers, such as compound word terms. Thus, for example, in the field of computing, we notice in it the inclusion of the ordinary vocabulary for reproductive reasons, like mi, dritare, flamur, adresë, skedar (Engl: mouse, window, flag, address, file), and along with them, the compound word terms, serving to differentiate relevant concepts, like, adresë e hiperlidhjes, adresë e uebit, adresë relative, adresë virtuale (Engl. address hyperlink, web address, relative address, virtual address) etc.

Keywords: common words, Albanian language, technical terminology, standardization

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Authors: Lin Wenli, Fu Linchun, Zhang Yi, Wu Ming

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To meet the demands of long-life and high-intelligence for satellites, the electrical power system should be provided with self-health condition evaluation capability. Any over-stress events in operations should be recorded. Based on Linear stresses accumulation damage theory, accumulative damage analysis was performed on thermal-mechanical-electrical united stresses for three components including the solar array, the batteries and the power conditioning unit. Then an overall health percentage evaluation model for satellite electrical power system was built. To obtain the accurate quantity for system health percentage, an automatic feedback closed-loop correction method for all coefficients in the evaluation model was present. The evaluation outputs could be referred as taking earlier fault-forecast and interventions for Ground Control Center or Satellites self.

Keywords: satellite electrical power system, health percentage, linear stresses accumulation damage, evaluation model

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Authors: Suzana Leitão Russo, Mayara Laysa de Oliveira Silva, José Augusto Andrade Filho, Vitor Hugo Simon

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Currently, seismic methods and prospecting methods are commonly applied in the oil industry and, according to the information reported every day; oil is a source of non-renewable energy. It is easier to understand why the ownership of areas of oil extraction is coveted by many nations. It is necessary to think about ways that will enable the maximization of oil production. The technique of spectral analysis can be used to analyze the behavior of the variables already defined in oil well the profile. The main objective is to verify the series dependence of variables, and to model the variables using the frequency domain to observe the model residuals.

Keywords: oil, well, spectral analysis, oil extraction

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Authors: H. Kiani, S. Moradi, B. Soltani Soulgani, S. Mousavian

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Desalting/dehydration plants (DDP) are often installed in crude oil production units in order to remove water-soluble salts from an oil stream. In order to optimize this process, desalting unit should be modeled. In this research, artificial neural network is used to model efficiency of desalting unit as a function of input parameter. The result of this research shows that the mentioned model has good agreement with experimental data.

Keywords: desalting unit, crude oil, neural networks, simulation, recovery, separation

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Authors: Kefaifi Aissa, Sahraoui Tahar, Kheloufi Abdelkrim, Anas Sabiha, Hannane Farouk

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The aim of this study is to show how the Design of Experiments Method (DOE) can be put into use as a practical approach for silica sand etching behavior modeling during its primary step of leaching. In the present work, we have studied etching effect on particle size during a primary step of leaching process on Algerian silica sand with florid acid (HF) at 20% and 30 % during 4 and 8 hours. Therefore, a new purity of the sand is noted depending on the time of leaching. This study was expanded by a numerical approach using a method of experiment design, which shows the influence of each parameter and the interaction between them in the process and approved the obtained experimental results. This model is a predictive approach using hide software. Based on the measured parameters experimentally in the interior of the model, the use of DOE method can make it possible to predict the outside parameters of the model in question and can give us the optimize response without making the experimental measurement.

Keywords: acid leaching, design of experiments method(DOE), purity silica, silica etching

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Authors: Eunice Oluwakemi Chukwuma-Nwuba

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Nigeria is a developing country with an increasing rate of graduate unemployment. This has triggered successive government administrations to promote the variety of programmes to address the situation. However, none of these efforts yielded the desired outcome. Accordingly, in 2006 the government included entrepreneurship module in the curriculum of universities as a compulsory general programme for all undergraduate courses. This is in the hope that the programme will help to promote entrepreneurial mind-set and new venture creation among graduates and as a result reduce the rate of graduate unemployment. The study explores the effectiveness of entrepreneurship education in promoting entrepreneurship. This study is significant in view of the endemic graduate unemployment in Nigeria and the social consequences such as youth restiveness and militancy. It is guided by the theory of planned behaviour. It employed the two-stage structural equation modelling (AMOS) to model entrepreneurial intentions as a function of innovative teaching methods, traditional teaching methods and culture Personal attitude and subjective norm are proposed to mediate the relationships between the exogenous and the endogenous variables. The first stage was tested using multi-group confirmatory factor analysis (MGCFA) framework to confirm that the two groups assign the same meaning to the scale items and to obtain goodness-of-fit indices. The multi-group confirmatory factor analysis included the tests of configural, metric and scalar invariance. With the attainment of full configural invariance and partial metric and scalar invariance, the second stage – the structural model was applied hypothesising that, the entrepreneurial intentions of graduates (respondents who have participated in the compulsory entrepreneurship programme) will be higher than those of undergraduates (respondents who are yet to participate in the programme). The study uses the quasi-experimental design. The samples comprised 409 graduates (experimental group) and 402 undergraduates (control group) from six federal universities in Nigeria. Our findings suggest that personal attitude is positively related with entrepreneurial intentions, largely confirming prior literature. However, unlike previous studies, our results indicate that subjective norm has significant direct and indirect impact on entrepreneurial intentions indicating that reference people of the participants have important roles to play in their decision to be entrepreneurial. Furthermore, unlike the assertions in prior studies, the result suggests that traditional teaching methods have indirect effect on entrepreneurial intentions supporting that since personal characteristics can change in an educational situation, an education purposively directed at entrepreneurship might achieve similar results if not better. This study has implication for practice and theory. The research extends to the theoretical understanding of the formation of entrepreneurial intentions and explains the role of the reference others in relation to how graduates perceive entrepreneurship. Further, the study adds to the body of knowledge on entrepreneurship education in Nigeria universities and provides a developing country perspective. It proposes further research in the exploration of entrepreneurship education and entrepreneurial intentions of graduates from across the country’s universities as necessary and imperative.

Keywords: entrepreneurship education, entrepreneurial intention, structural equation modeling, theory of planned behaviour

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Authors: H. C. Chang, J. R. Wang, A. L. Ho, S. W. Chen, J. H. Yang, C. Shih, L. C. Wang

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To confirm the reactor and containment integrity of the Advanced Boiling Water Reactor (ABWR), we perform the analysis of main steamline break (MSLB) transient by using the TRACE, PARCS, and SNAP codes. The process of the research has four steps. First, the ABWR nuclear power plant (NPP) model is developed by using the above codes. Second, the steady state analysis is performed by using this model. Third, the ABWR model is used to run the analysis of MSLB transient. Fourth, the predictions of TRACE and PARCS are compared with the data of FSAR. The results of TRACE/PARCS and FSAR are similar. According to the TRACE/PARCS results, the reactor and containment integrity of ABWR can be maintained in a safe condition for MSLB.

Keywords: advanced boiling water reactor, TRACE, PARCS, SNAP

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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: Bo-Bin Xiaoa, Chia-Yi Liua

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In the task of searching for anomalous radiation sources, personnel holding radiation detectors to search for radiation sources may be exposed to unnecessary radiation risk, and automated search using machines becomes a required project. The research uses various sophisticated algorithms, which are double Q learning, dueling network, and NoisyNet, of deep reinforcement learning to search for radiation sources. The simulation environment, which is a 10*10 grid and one shielding wall setting in it, improves the development of the AI model by training 1 million episodes. In each episode of training, the radiation source position, the radiation source intensity, agent position, shielding wall position, and shielding wall length are all set randomly. The three algorithms are applied to run AI model training in four environments where the training shielding wall is a full-shielding wall, a lead wall, a concrete wall, and a lead wall or a concrete wall appearing randomly. The 12 best performance AI models are selected by observing the reward value during the training period and are evaluated by comparing these AI models with the gradient search algorithm. The results show that the performance of the AI model, no matter which one algorithm, is far better than the gradient search algorithm. In addition, the simulation environment becomes more complex, the AI model which applied Double DQN combined Dueling and NosiyNet algorithm performs better.

Keywords: double Q learning, dueling network, NoisyNet, source searching

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Authors: Argyro Maria Skourmalla

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The present paper draws on the example of the University of Luxembourg as a multilingual and international setting. The University of Luxembourg, which is located between France, Germany, and Belgium, has adopted a new multilingualism policy in 2020, establishing English, French, German, and Luxembourgish as the official languages of the Institution. With around 7.000 students, more than half of which are international students, the University is a meeting point for languages and cultures. This paper includes data from an online survey that with undergraduate students from different disciplines at the University of Luxembourg. Students shared their personal experience and opinions regarding language use in this higher education context, as well as practices they use in learning in this multilingual context. Findings show the role of technology in assisting students in different aspects of learning this multilingual context. At the same time, more needs to be done to avoid an exclusively monolingual paradigm in higher education. Findings also show that some languages remain ‘unseen’ in this context. Overall, even though linguistic diversity in this University is seen as an asset, a lot needs to be done towards the recognition of staff and students’ linguistic repertoires for inclusion and education equity.

Keywords: higher education, learning, linguistic diversity, multilingual practices

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Authors: Lily Beaumont-Griffin, Philip Reynolds, Helen Pote, Pinder Kaur

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Siblings are a key part of the family unit, which Multisystemic Therapy (MST) intervenes, with the aim of reducing antisocial behavior and keeping families together. However, despite operating in multiple countries, including the United States of America, Europe, parts of South America, and the Western Hemisphere, there are only few previous studies on siblings within MST. According to best of authors knowledge neither of these seeks to understand the siblings' experience of the intervention nor their perception of the outcomes. This study utilized semi-structured interviews to understand the experience of seven siblings of children and adolescents who were closed to MST within the last year (2023-2024). Using reflexive thematic analysis, three themes were identified: sibling inclusion by the therapist, sharing responsibility for change, and fostering a safe and supportive environment at home. These themes express that siblings need to have a basic understanding of an intervention to be able to perceive benefits, siblings need help understanding responsibility across the whole family, and that safety is both physical and emotional. Clinical implications, including encouragement of therapists to integrate the siblings in the intervention more, and future research directions around integrating these findings into the development of iterations of MST standard are discussed.

Keywords: siblings, multisystemic therapy, family therapy, experience

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Authors: Ci Lin, Tet Yeap, Iluju Kiringa

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This paper introduces the subspace rotation algorithm (SRA) to train the Restricted Hopfield Network (RHN) as an auto-associative memory. Subspace rotation algorithm is a gradient-free subspace tracking approach based on the singular value decomposition (SVD). In comparison with Backpropagation Through Time (BPTT) on training RHN, it is observed that SRA could always converge to the optimal solution and BPTT could not achieve the same performance when the model becomes complex, and the number of patterns is large. The AUTS case study showed that the RHN model trained by SRA could achieve a better structure of attraction basin with larger radius(in general) than the Hopfield Network(HNN) model trained by Hebbian learning rule. Through learning 10000 patterns from MNIST dataset with RHN models with different number of hidden nodes, it is observed that an several components could be adjusted to achieve a balance between recovery accuracy and noise resistance.

Keywords: hopfield neural network, restricted hopfield network, subspace rotation algorithm, hebbian learning rule

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Norhafilah Bara

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Developing a software application using an interface with computers and peripheral devices using gestures of human body such as hand movements keeps growing in interest. A review on this hand gesture detection and recognition based on computer vision technique remains a very challenging task. This is to provide more natural, innovative and sophisticated way of non-verbal communication, such as sign language, in human computer interaction. Nevertheless, this paper explores hand detection and hand gesture recognition applying a vision based approach. The hand detection and recognition used skin color spaces such as HSV and YCrCb are applied. However, there are limitations that are needed to be considered. Almost all of skin color space models are sensitive to quickly changing or mixed lighting circumstances. There are certain restrictions in order for the hand recognition to give better results such as the distance of user’s hand to the webcam and the posture and size of the hand.

Keywords: hand detection, hand gesture, hand recognition, sign language

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Authors: Gurukiran Veerapur, Nytik Birudavolu, Seetharam U. N., Chandravva Hebbi, R. Praneeth Reddy

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This work presents a robust approach for the recognition of characters in Telugu and Kannada, two South Indian scripts with structural similarities in characters. To recognize the characters exhaustive datasets are required, but there are only a few publicly available datasets. As a result, we decided to create a dataset for one language (source language),train the model with it, and then test it with the target language.Telugu is the target language in this work, whereas Kannada is the source language. The suggested method makes use of Canny edge features to increase character identification accuracy on pictures with noise and different lighting. A dataset of 45,150 images containing printed Kannada characters was created. The Nudi software was used to automatically generate printed Kannada characters with different writing styles and variations. Manual labelling was employed to ensure the accuracy of the character labels. The deep learning models like CNN (Convolutional Neural Network) and Visual Attention neural network (VAN) are used to experiment with the dataset. A Visual Attention neural network (VAN) architecture was adopted, incorporating additional channels for Canny edge features as the results obtained were good with this approach. The model's accuracy on the combined Telugu and Kannada test dataset was an outstanding 97.3%. Performance was better with Canny edge characteristics applied than with a model that solely used the original grayscale images. The accuracy of the model was found to be 80.11% for Telugu characters and 98.01% for Kannada words when it was tested with these languages. This model, which makes use of cutting-edge machine learning techniques, shows excellent accuracy when identifying and categorizing characters from these scripts.

Keywords: base characters, modifiers, guninthalu, aksharas, vattakshara, VAN

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Authors: Belabed Lazhar

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The dimensioning of the anchored retaining screens passes always by the analysis of their stability. The calculation of anchoring lengths is practically carried out according to the mechanical model suggested by Kranz which is often criticized. The safety is evaluated through the comparison of interior force and external force. The force of anchoring over the length cut behind the failure solid is neglected. The failure surface cuts anchoring in the medium length of sealing. In this article, one proposes a new mechanical model which overcomes these disadvantages (simplifications) and gives interesting results.

Keywords: retaining walls, anchoring, stability, mechanical modeling, safety

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