Search results for: pre-trained language models

Authors: Milorad Pavlovic, Sebastiano Trevisani, Antonella Cecchi

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In this paper, a procedure for the evaluation of seismic behavior of slender masonry structures (towers, bell towers, chimneys, minarets, etc.) is presented. The presented procedure is based on a full three-dimensional modal analyses and frequency measurements. As well-known, masonry is a composite material formed by bricks, or stone blocks, and mortar arranged more or less regularly and adopted for many centuries as structural material. Dynamic actions may represent the major risk of collapse of brickworks, and despite the progress achieved so far in science and mechanics; the assessment of their seismic performance remains a challenging task. Then, reliable physical and numerical models are worthy of recommendation. In this paper, attention is paid to the historical bell tower of the Basilica of Santa Maria Gloriosa dei Frari - usually called Frari - one of the greatest churches in Venice, Italy.

Keywords: bell tower, FEM, masonry, modal analysis, non-destructive testing

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Authors: Quentin C.P. Bourgogne, Vanessa Bouchart, Pierre Chevrier, Emmanuel Dattoli

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This study presents an experimental and theoretical work conducted on a PolyPhenylene Sulfide reinforced with 40%wt of short glass fibers (PPS GF40) and its matrix. Thermoplastics are widely used in the automotive industry to lightweight automotive parts. The replacement of metallic parts by thermoplastics is reaching under-the-hood parts, near the engine. In this area, the parts are subjected to high temperatures and are immersed in cooling liquid. This liquid is composed of water and glycol and can affect the mechanical properties of the composite. The aim of this work was thus to quantify the evolution of mechanical properties of the thermoplastic composite, as a function of temperature and liquid aging effects, in order to develop a reliable design of parts. An experimental campaign in the tensile mode was carried out at different temperatures and for various glycol proportions in the cooling liquid, for monotonic and cyclic loadings on a neat and a reinforced PPS. The results of these tests allowed to highlight some of the main physical phenomena occurring during these solicitations under tough hydro-thermal conditions. Indeed, the performed tests showed that temperature and liquid cooling aging can affect the mechanical behavior of the material in several ways. The more the cooling liquid contains water, the more the mechanical behavior is affected. It was observed that PPS showed a higher sensitivity to absorption than to chemical aggressiveness of the cooling liquid, explaining this dominant sensitivity. Two kinds of behaviors were noted: an elasto-plastic type under the glass transition temperature and a visco-pseudo-plastic one above it. It was also shown that viscosity is the leading phenomenon above the glass transition temperature for the PPS and could also be important under this temperature, mostly under cyclic conditions and when the stress rate is low. Finally, it was observed that soliciting this composite at high temperatures is decreasing the advantages of the presence of fibers. A new phenomenological model was then built to take into account these experimental observations. This new model allowed the prediction of the evolution of mechanical properties as a function of the loading environment, with a reduced number of parameters compared to precedent studies. It was also shown that the presented approach enables the description and the prediction of the mechanical response with very good accuracy (2% of average error at worst), over a wide range of hydrothermal conditions. A temperature-humidity equivalence principle was underlined for the PPS, allowing the consideration of aging effects within the proposed model. Then, a limit of improvement of the reachable accuracy was determinate for all models using this set of data by the application of an artificial intelligence-based model allowing a comparison between artificial intelligence-based models and phenomenological based ones.

Keywords: aging, analytical modeling, mechanical testing, polymer matrix composites, sequential model, thermomechanical

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Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng

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Tires are extremely challenging to recycle due to the available chemically cross-linked polymer which constitutes their nature and therefore, they are neither fusible nor soluble and consequently, cannot be remoulded into other shapes without serious degradation. Pyrolysis of tires produces four valuable products namely; char, steel, tire pyrolytic oil (TPO) and non-condensable gases. TPO has been reported to have similar properties to commercial diesel fuel (CDF). In this study, distillation of TPO was carried out in a batch distillation column and biodiesel was produced from waste cooking oil. FTIR analysis proved that TPO can be used as a fuel due to the available compounds detected and GC analysis displayed 94% biodiesel concentration from waste cooking oil. Different blends of TPO/biodiesel, TPO/CDF and biodiesel/CDF were prepared at different ratios. Fuel properties such as viscosity, density, flash point, and calorific value were studied. Viscosity and density models were also studied to measure the quality of different blends.

Keywords: biodiesel, distillation, pyrolysis, tire

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Authors: Elena Antonova Unlu, Cigdem Sagin Simsek

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The research presents two studies examining the impact of formal interpreting training (FIT) on Working Memory Capacity (WMC) of student-interpreters. In Study 1, the storage and processing capacities of the working memory (WM) of last-year student-interpreters were compared with those of last-year Foreign Language Education (FLE) students. In Study 2, the impact of FIT on the WMC of student-interpreters was examined via comparing their results on WM tasks at the beginning and the end of their FIT. In both studies, Digit Span Task (DST) and Reading Span Task (RST) were utilized for testing storage and processing capacities of WM. The results of Study 1 revealed that the last-year student-interpreters outperformed the control groups on the RST but not on the DST. The findings of Study 2 were consistent with Study 1 showing that after FIT, the student-interpreters performed better on the RST but not on the DST. Our findings can be considered as evidence supporting the view that FIT has a beneficial effect not only on the interpreting skills of student-interpreters but also on the central executive and processing capacity of their WM.

Keywords: working memory capacity, formal interpreting training, student-interpreters, cross-sectional and longitudinal data

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Authors: Ruwan Gunawardane

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Second language teaching and learning is a complex process in which various factors are identified as having a negative impact on the competency in English among undergraduates of Sri Lanka. One such issue is the lack of intrinsic motivation among them to learn English despite the fact that they all know the importance of English. This study attempted to ascertain how the intrinsic motivation of undergraduates to learn English can be improved through reading out of curiosity. Humans are curious by nature, and cognitive psychology says that curiosity facilitates learning, memory, and motivation. The researcher carried out this study during the closure of universities due to the outbreak of the coronavirus through ‘Online Reading Café’, an online reading programme introduced by himself. He invited 1166 students of the Faculty of Science, University of Ruhuna, to read 50 articles taken from CNN and the BBC and posted at least two to three articles on the LMS of the faculty almost every day over a period of 23 days. The themes of the articles were based on the universe, exploration of planets, scientific experiments, evolution, etc., and the students were encouraged to collect as many words, phrases, and sentence structures as possible while reading and to form meaningful sentences using them. The data obtained through the students’ feedback was qualitatively analyzed. It was found that these undergraduates were interested in reading something out of curiosity, due to which intrinsic motivation is enhanced, and it facilitates competence in L2.

Keywords: English, competence, reading, curiosity

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Authors: C. P. Griffin

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This paper seeks to critically review special educational needs (SEN) policy in the Irish education system since the introduction of the Education Act in 1998. In particular, the author seeks to focus on the impact of SEN policy on inclusionary practices for children with significant care needs in light of the introduction on the Special Needs Assistant (SNA) scheme. Following a systematic review of the literature, the growth of the SNA scheme in Ireland will be critically reviewed. Strengths and weaknesses of the scheme will be forwarded and comparisons drawn between contrasting international models of teaching assistant support. Based on this review, avenues for future research will be forwarded, with the aim of supporting effective inclusionary practices for children with SEN based on evidence-based practice.

Keywords: care needs, inclusion, Ireland, special needs assistants

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Authors: Anupreet B. Dugal, Suruchi Mittar

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The research prospect explores fashion as a tool to effectively emancipate the Sikh identity. The study presents information on how fashion has played a critical and visible role in reflecting and helping to construct identities based on religiosity. It discusses the Sikh identity, its’ origin; its continuity and the contemporary ambivalence. Fashion has mostly, if not always been used as a means of establishing identity. This research creates a gateway to discuss the impact that fashion can have on the existing socio-cultural and religious models. The study focuses on the Sikhs, a small community of India with regard to their visual appearance. The research will be based on the case study of 1469, a store infusing Sikhism as a style quotient. Subsequently, in the research framework, a sample study would be conducted with Sikh youth (18-25 years old) hailing from New Delhi, the capital city of India. 1469 formulates a striking case study for examining the relationship between fashion and religious and personal identity.

Keywords: fashion, identity, sikh identity, textiles

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Authors: Sadeq Al Yaari, Ayman Al Yaari, Adham Al Yaari, Montaha Al Yaari, Aayah Al Yaari, Sajedah Al Yaari

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Aims: To summarize and critically review involved articles for the purpose of investigating the research ethics in them. It also tests the hypothesis, identifying causal relationship, association between variables and differences between/ among groups of participants Design: This is quasi experimental study wherein scientific models were included. It starts from the ideas before the researchers draw the questions, formulate the hypothesis and seek for the solutions. Hypothesis was brief and to the point. A data collection form was constructed. The researchers made use of speculative, presumptive, stipulated and conclusive propositions. Data are statistically analyzed and visualized and are treated objectively in light of the characteristics of a good research. Outcomes: Results and discussion are relevant to the statement of the problem and research objectives. Principles of ethical research were met where the researchers ensured high ethical standards. Variables’ types are scientifically analyzed.

Keywords: research, method, analysis, speech, text

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Authors: Fakhrosadat Sajjadian

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In the USA, about 5% of women diagnosed with breast cancer annually are affected by Inflammatory Breast Cancer (IBC), which is a highly aggressive type of Locally Advanced Breast Cancer (LABC). It is a type of LABC that is clinically and pathologically different, known for its rapid growth, invasiveness, and ability to promote the growth of blood vessels. Almost all women are found to have lymph nodes affected upon diagnosis, while around 36% show obvious distant metastases. Even with the latest improvements in multimodality therapies, the outlook for patients with IBC remains bleak, as the average disease-free survival time is less than 2.5 years. Recent research on the genetic factors responsible for the IBC phenotype has resulted in the discovery of genes that play a role in the advancement of this illness. The development of primary human cell lines and animal models has assisted in this research. These advancements offer new possibilities for future actions in identifying and treating IBC.

Keywords: breast cancer, inflammation, diagnosis, IBC, LABC

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Authors: O. Bilbao, I. Loizaga, F. A. Girot, A. Torregaray

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The current energetical situation and the high competitiveness in industrial sectors as the automotive one have become the development of new manufacturing processes with less energy and raw material consumption a real necessity. As consequence, new forming processes related with high temperature hot forging in closed dies have emerged in the last years as new solutions to expand the possibilities of hot forging and iron casting in the automotive industry. These technologies are mid-way between hot forging and semi-solid metal processes, working at temperatures higher than the hot forging but below the solidus temperature or the semi solid range, where no liquid phase is expected. This represents an advantage comparing with semi-solid forming processes as thixoforging, by the reason that no so high temperatures need to be reached in the case of high melting point alloys as steels, reducing the manufacturing costs and the difficulties associated to semi-solid processing of them. Comparing with hot forging, this kind of technologies allow the production of parts with as forged properties and more complex and near-net shapes (thinner sidewalls), enhancing the possibility of designing lightweight components. From the process viewpoint, the forging forces are significantly decreased, and a significant reduction of the raw material, energy consumption, and the forging steps have been demonstrated. Despite the mentioned advantages, from the material behavior point of view, the expansion of these technologies has shown the necessity of developing new material flow behavior models in the process working temperature range to make the simulation or the prediction of these new forming processes feasible. Moreover, the knowledge of the material flow behavior at the working temperature range also allows the design of the new closed dies concept required. In this work, the flow behavior characterization in the mentioned temperature range of the widely used in automotive commercial components 42CrMo4 steel has been studied. For that, hot compression tests have been carried out in a thermomechanical tester in a temperature range that covers the material behavior from the hot forging until the NDT (Nil Ductility Temperature) temperature (1250 ºC, 1275 ºC, 1300 ºC, 1325 ºC, 1350ºC, and 1375 ºC). As for the strain rates, three different orders of magnitudes have been considered (0,1 s-1, 1s-1, and 10s-1). Then, results obtained from the hot compression tests have been treated in order to adapt or re-write the Spittel model, widely used in automotive commercial softwares as FORGE® that restrict the current existing models up to 1250ºC. Finally, the obtained new flow behavior model has been validated by the process simulation in a commercial automotive component and the comparison of the results of the simulation with the already made experimental tests in a laboratory cellule of the new technology. So as a conclusion of the study, a new flow behavior model for the 42CrMo4 steel in the new working temperature range and the new process simulation in its application in automotive commercial components has been achieved and will be shown.

Keywords: 42CrMo4 high temperature flow behavior, high temperature hot forging in closed dies, simulation of automotive commercial components, spittel flow behavior model

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Authors: Sarah Odofin, Zhiwei Gao

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Operations and maintenance of wind turbine have received much attention by researcher due to rapid expansion of wind farms. This paper explores a novel fault diagnosis that is designed and optimized to be very sensitive to faults and robust to disturbances. The faults considered are the sensor faults of which the augmented observer is considered to enlarge faults and to be robust to disturbance. A qualitative model based analysis is proposed for early fault diagnosis to minimize downtime mostly caused by components breakdown and exploit productivity. Simulation results are computed validating the models provided which demonstrates system performance using practical application of fault type examples. The results demonstrate the effectiveness of the developed techniques investigated in a Matlab/Simulink environment.

Keywords: wind turbine, condition monitoring, genetic algorithm, fault diagnosis, augmented observer, disturbance robustness, fault estimation, sensor monitoring

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Authors: Afroza Akhter Tina

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This paper reports on an investigation into the use of specific types of oral communication strategies, namely ‘topic avoidance’, ‘message abandonment’, ‘code-switching’, ‘paraphrasing’, ‘restructuring’, and ‘stalling’ by Bangladeshi EFL learners at the graduate level. It chiefly considers the frequency of using these strategies as well as the students and teachers attitudes toward such uses. The participants of this study are 66 EFL students and 12 EFL teachers of Jahangirnagar University. Data was collected through questionnaire, oral interview, and classroom observation form. The findings reveal that the EFL students tried to employ all the strategies to various extents due to the language difficulties they encountered in their oral English performance. Among them, the mostly used strategy was ‘stalling’ or the use of fillers, followed by ‘code-switching’. The least used strategies were ‘topic avoidance’, ‘restructuring’, and ‘paraphrasing’. The findings indicate that the use of such strategies was related to the contexts of situation and data-elicitation tasks. It also reveals that the students were not formally trained to use the strategies though the majority of the teachers and students acknowledge them as helpful in communication. Finally the study suggests that an awareness of the nature and functions of these strategies can contribute to the overall improvement of the learners’ communicative competence in spoken English.

Keywords: communicative strategies, competency, attitude, frequency

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Authors: Avinash Malladhi

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Forensic accounting is a specialized field that involves the application of accounting principles, investigative skills, and legal knowledge to detect and prevent fraud. With the rise of big data and technological advancements, artificial intelligence (AI) and machine learning (ML) algorithms have emerged as powerful tools for forensic accountants to enhance their fraud detection capabilities. In this paper, we review and analyze various AI/ML algorithms that are commonly used in forensic accounting, including supervised and unsupervised learning, deep learning, natural language processing Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Support Vector Machines (SVMs), Decision Trees, and Random Forests. We discuss their underlying principles, strengths, and limitations and provide empirical evidence from existing research studies demonstrating their effectiveness in detecting financial fraud. We also highlight potential ethical considerations and challenges associated with using AI/ML in forensic accounting. Furthermore, we highlight the benefits of these technologies in improving fraud detection and prevention in forensic accounting.

Keywords: AI, machine learning, forensic accounting & fraud detection, anti money laundering, Benford's law, fraud triangle theory

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Authors: Abdulaziz Fageeh

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In the bustling digital landscape of Saudi Arabia, a chilling wave of cybercrime has swept across the nation. Among the most nefarious acts are financial blackmail schemes, perpetrated by anonymous actors lurking within the shadows of social media platforms. This chilling reality necessitates the utilization of forensic linguistic techniques to unravel the identities of these virtual villains. This research delves into the complex world of authorship profiling, investigating the effectiveness of various linguistic features in identifying the perpetrators of malicious messages within the Saudi social media environment. By meticulously analyzing patterns of language, vocabulary choice, and stylistic nuances, the study endeavors to uncover the hidden characteristics of the individuals responsible for these heinous acts. Through this linguistic detective work, the research aims to provide valuable insights to investigators and policymakers in the ongoing battle against cybercrime and to shed light on the evolution of malicious online behavior within the Saudi context.

Keywords: authorship profiling, arabic linguistics, saudi social media, cybercrime, financial blackmail, linguistic features, forensic linguistics, online threats

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Authors: Yongxu Fu, Shaolong Wan

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We study the band degeneracy, defectiveness, as well as exceptional points of non-Hermitian systems and materials analytically. We elaborate on the energy bands, the band degeneracy, and the defectiveness of eigenstates under open boundary conditions based on developing a general theory of one-dimensional (1D) non-Hermitian systems. We research the presence of the exceptional points in a generalized non-Hermitian Su-Schrieffer-Heeger model under open boundary conditions. Beyond our general theory, there exist infernal points in 1D non-Hermitian systems, where the energy spectra under open boundary conditions converge on some discrete energy values. We study two 1D non-Hermitian models with the existence of infernal points. We generalize the infernal points to the infernal knots in four-dimensional non-Hermitian systems.

Keywords: non-hermitian, degeneracy, defectiveness, exceptional points, infernal points

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Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

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Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

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Authors: Tajuddin Mohamad Rasdi, Chung Ming Zhe, Nurul Anida Mohamad

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This research paper aims to examine the lack of the idea of democracy and its concept among Malaysia’s citizens. In fact, all civil servants, whether federal or state departments, are the machinery of citizens. The objective of this research is to evaluate the administrative buildings in Selangor from the perspective of democratic architecture. The methodology used in this research is by reviewing and evaluating the selected administrative building, Majlis Bandaraya Petaling Jaya, as a case study, and the interview was conducted. The data collection was recorded based on a few criteria of the following architectural characteristic and management principles (public square, town hall, meeting rooms, convenient parking space, humanitarian spaces, public spaces) and architectural design elements (scale and massing, ornament, elevational language, accessibility, and spatial hierarchy). The analysis result shows that the administrative building elements which show the idea of democracy are not reflected well in some of the criteria that restrict the public, but those setbacks could be improved.

Keywords: democratic architecture, case study, design elements, administrative buildings

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Authors: Mohammad ASadian, Samira RajiAsadabadi

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Osteoporosis is very common, particularly in post-menopausal women and is characterized by a decrease in bone mass and strength. Osteoporosis also affects the jawbone and it is considered a potential contraindication to the placement of dental implants. The present paper reviews the literature regarding the effect of osteoporosis on the osseointegration of implants. Experimental models have shown that osteoporosis affects the process of osseointegration, which can be reversed by treatment. However, studies in subjects with osteoporosis have shown no differences in the survival of the implants compared to healthy individuals. Therefore, osteoporosis cannot be considered a contraindication for implant placement. Oral bisphosphonates are the most commonly used pharmacological agents in the treatment of osteoporosis. Although there have been cases of osteonecrosis of the jaw in patients treated with bisphosphonates, they are very rare and it is more usually associated with intravenous bisphosphonates in patients with neoplasms or other serious diseases. Nevertheless, patients treated with bisphosphonates must be informed in writing about the possibility of this complication and must give informed consent. Ceasing to use of bisphosphonates before implant placement does not seem to be necessary.

Keywords: Osteoporosis, dental implant, bisphosphonates, survival

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Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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Authors: Rujijan Vichivanives, Kittiya Poonsilp, Canasanan Wanavijit

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This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.

Keywords: rice disease, data analysis system, mobile application, iOS operating system

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Authors: Nancy Daly

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Migrant youth who have experienced traumatic events in their home countries or in their passage to the United States may require interventions or formal services to support varying levels and types of needs. The manner in which such youth are engaged and evaluated, as well as the framework of evaluation, can impact their educational services and placement. Evidenced-based trauma-informed practices that engage and support migrant youth serve as an important bridge to stabilization; however, ensuring long-term growth may require a range of integrated services, including special education and mental health services. Special education evaluations which consider the eligibility of Emotional Disturbance for migrant youth must carefully weigh issues of mental health needs against the exclusionary criteria of lack of access to education, limited language skills, as well as other environmental factors. Case studies of recently arrived migrant youth reveal both commonalities and differences in types and levels of need which underscores the importance of adept evaluation and case management to ensure the provision of services that support growth and resiliency.

Keywords: migrant youth, trauma-informed care, mental health services, special education

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Authors: Timothy Akinwande, Eddie Hui, Karien Dekker

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Housing the urban poor remains a persistent challenge, despite evident research attention over many years. It is, therefore, pertinent to investigate affordable housing provision challenges with novel approaches. For innovative solutions to affordable housing constraints, it is apposite to thoroughly examine housing solutions vis a vis the key elements of the housing supply value chain (HSVC), which are housing finance, housing construction and land acquisition. A pragmatic analysis will examine affordable housing solutions from demand and supply perspectives to arrive at consolidated solutions from bilateral viewpoints. This study thoroughly examined informal housing finance strategies of the urban poor and diligently investigated expert opinion on affordable housing finance solutions. The research questions were: (1) What mutual grounds exist between informal housing finance solutions of the urban poor and housing expert solutions to affordable housing finance constraints in developing economies? (2) What are effective approaches to affordable housing finance in developing economies from an integrated demand - supply perspective? Semi-structured interviews were conducted in the 5 largest slums of Lagos, Nigeria, with 40 informal settlers for demand-oriented solutions, while focus group discussion and in-depth interviews were conducted with 12 housing experts in Nigeria for supply-oriented solutions. Following a rigorous thematic, content and descriptive analyses of data using NVivo and Excel, findings ascertained mutual solutions from both demand and supply standpoints that can be consolidated into more effective affordable housing finance solutions in Nigeria. Deliberate finance models that recognise and include the finance realities of the urban poor was found to be the most significant supply-side housing finance solution, representing 25.4% of total expert responses. Findings also show that 100% of sampled urban poor engage in vocations where they earn little irregular income or zero income, limiting their housing finance capacities and creditworthiness. Survey revealed that the urban poor are involved in community savings and employ microfinance institutions within the informal settlements to tackle their housing finance predicaments. These are informal finance models of the urban poor, revealing common grounds between demand and supply solutions for affordable housing financing. Effective, affordable housing approach will be to modify, institutionalise and incorporate the informal finance strategies of the urban poor into deliberate government policies. This consolidation of solutions from demand and supply perspectives can eliminate the persistent misalliance between affordable housing demand and affordable housing supply. This study provides insights into mutual housing solutions from demand and supply perspectives, and findings are informative for effective, affordable housing provision approaches in developing countries. This study is novel in consolidating affordable housing solutions from demand and supply viewpoints, especially in relation to housing finance as a key component of HSVC. The framework for effective, affordable housing finance in developing economies from a consolidated viewpoint generated in this study is significant for the achievement of sustainable development goals, especially goal 11 for sustainable, resilient and inclusive cities. Findings are vital for future housing studies.

Keywords: affordable housing, affordable housing finance, developing economies, effective affordable housing, housing policy, urban poor, sustainable development goal, sustainable affordable housing

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: Lizhi Ma, Chengcheng Hu, Fuxian Wong

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Partial reduce (P-Reduce) has set a state-of-the-art performance on distributed machine learning in the heterogeneous environment over the All-Reduce architecture. The dynamic P-Reduce based on the exponential moving average (EMA) approach predicts all the intermediate model parameters, which raises unreliability. It is noticed that the approximation trick leads the wrong way to obtaining model parameters in all the nodes. In this paper, SAP-Reduce is proposed, which is a variant of the All-Reduce distributed training model with staleness-aware dynamic P-Reduce. SAP-Reduce directly utilizes the EMA-like algorithm to generate the normalized weights. To demonstrate the effectiveness of the algorithm, the experiments are set based on a number of deep learning models, comparing the single-step training acceleration ratio and convergence time. It is found that SAP-Reduce simplifying dynamic P-Reduce outperforms the intermediate approximation one. The empirical results show SAP-Reduce is 1.3× −2.1× faster than existing baselines.

Keywords: collective communication, decentralized distributed training, machine learning, P-Reduce

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Authors: Rania Ajmi, Faiza Allouche Khebour, Aude Nuscia Taibi, Sirine Essasi

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Urban green spaces (UGS) as an important contributor can be a significant part of sustainable development. A spatial method was employed to assess and map the spatial distribution of UGS in five districts in Sousse, Tunisia. Ecological management of UGS is an essential factor for the sustainable development of the city; hence the municipality of Sousse has decided to support the districts according to different green spaces characters. And to implement this policy, (1) a new GIS web application was developed, (2) then the implementation of the various green spaces was carried out, (3) a spatial mapping of UGS using Quantum GIS was realized, and (4) finally a data processing and statistical analysis with RStudio programming language was executed. The intersection of the results of the spatial and statistical analyzes highlighted the presence of an imbalance in terms of the spatial UGS distribution in the study area. The discontinuity between the coast and the city's green spaces was not designed in a spirit of network and connection, hence the lack of a greenway that connects these spaces to the city. Finally, this GIS support will be used to assess and monitor green spaces in the city of Sousse by decision-makers and will contribute to improve the well-being of the local population.

Keywords: distributions, GIS, green space, imbalance, spatial analysis

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

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A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: forecasting model, steel demand uncertainty, hierarchical Bayesian framework, exponential smoothing method

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Authors: Kushal Kumar Chode, Remus Miahi Cirstea

Abstract:

In recent times, the drive towards more efficient vehicles and the increase in the number of vehicle on the roads has driven the aerodynamic researchers from studying the vehicle in isolation towards understanding the benefits of vehicle platooning. Vehicle platooning is defined as a series of vehicles traveling in close proximity. Due to the limitations in size and load measurement capabilities for the wind tunnels facilities, it is very difficult to perform this investigation experimentally. In this paper, the use of chimera or overset meshing technique is used within the STARCCM+ software to model the flow surrounding two identical vehicle models travelling in close proximity and also during an overtaking maneuver. The results are compared with data obtained from a polyhedral mesh and identical physics conditions. The benefits in terms of computational time and resources and the accuracy of the overset mesh approach are investigated.

Keywords: chimera mesh, computational accuracy, overset mesh, platooning vehicles

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Authors: Pouya Kaafi, Gholamreza Ghodrati Amiri

Abstract:

Abnormal loads due to natural events, implementation errors and some other issues can lead to occurrence of progressive collapse in structures. Most of the past researches consist of 2- Dimensional (2D) models of steel frames without consideration of the floor system effects, which reduces the accuracy of the modeling. While employing a 3-Dimensional (3D) model and modeling the concrete slab system for the floors have a crucial role in the progressive collapse evaluation. In this research, a 3D finite element model of a 5-story steel building is modeled by the ABAQUS software once with modeling the slabs, and the next time without considering them. Then, the progressive collapse potential is evaluated. The results of the analyses indicate that the lack of the consideration of the slabs during the analyses, can lead to inaccuracy in assessing the progressive failure potential of the structure.

Keywords: abnormal loads, composite floor system, intermediate steel moment resisting frame system, progressive collapse

Procedia PDF Downloads 456

Authors: Helmi Baazaoui, Mounir Zrigui

Abstract:

This study addresses the challenge of hate speech detection in Tunisian Arabic text, a critical issue for online safety and moderation. Leveraging the strengths of the AraBERT model, we fine-tuned and evaluated its performance against the Bi-LSTM model across four distinct datasets: T-HSAB, TNHS, TUNIZI-Dataset, and a newly compiled dataset with diverse labels such as Offensive Language, Racism, and Religious Intolerance. Our experimental results demonstrate that AraBERT significantly outperforms Bi-LSTM in terms of Recall, Precision, F1-Score, and Accuracy across all datasets. The findings underline the robustness of AraBERT in capturing the nuanced features of Tunisian Arabic and its superior capability in classification tasks. This research not only advances the technology for hate speech detection but also provides practical implications for social media moderation and policy-making in Tunisia. Future work will focus on expanding the datasets and exploring more sophisticated architectures to further enhance detection accuracy, thus promoting safer online interactions.

Keywords: hate speech detection, Tunisian Arabic, AraBERT, Bi-LSTM, Gemini annotation tool, social media moderation

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Authors: Afef Dridi, Salah Mezlini

Abstract:

Since experimental devices cannot calculate stress and deformation of complex structures. The Finite Element Method FEM has been widely used in several fields of research. One of these fields is orthodontics. The advantage of using such a method is the use of an accurate and non invasive method that allows us to have a sufficient data about the physiological reactions can happening in soft tissues. Most of researches done in this field were interested in the study of stresses and deformations induced by orthodontic apparatus in soft tissues (alveolar tissues). Only few studies were interested in the distribution of stress and strain in the orthodontic brackets. These studies, although they tried to be as close as possible to real conditions, their models did not reproduce the clinical cases. For this reason, the model generated by our research is the closest one to reality. In this study, a numerical model was developed to explore the stress and strain distribution under the application of real conditions. A comparison between different material properties was also done.

Keywords: visco-hyperelasticity, FEM, orthodontic treatment, inverse method

Procedia PDF Downloads 259