Search results for: large language models (LLMS)

Authors: Mohsen Ziaee

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Almost all existing researches on the flowshop scheduling problems focus on the permutation schedules and there is insufficient study dedicated to the general flowshop scheduling problems in the literature, since the modeling and solving of the general flowshop scheduling problems are more difficult than the permutation ones, especially for the large-size problem instances. This paper considers the general flowshop scheduling problem with the objective function of the makespan (F//Cmax). We first find the optimal solution of the problem by solving a mixed integer linear programming model. An efficient heuristic method is then presented to solve the problem. An ant colony optimization algorithm is also proposed for the problem. In order to evaluate the performance of the methods, computational experiments are designed and performed. Numerical results show that the heuristic algorithm can result in reasonable solutions with low computational effort and even achieve optimal solutions in some cases.

Keywords: scheduling, general flow shop scheduling problem, makespan, heuristic

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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: Wilaiwan Sornpoon, Sébastien Bonnet, Savitri Garivait

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Open burning of sugarcane fields is recognized to have a negative impact on soil by degrading its properties, especially soil organic carbon (SOC) content. Better understating the effect of open burning on soil carbon dynamics is crucial for documenting the carbon sequestration capacity of agricultural soils. In this study, experiments to investigate soil carbon stocks under burned and unburned sugarcane plantation systems in Thailand were conducted. The results showed that cultivation fields without open burning during 5 consecutive years enabled to increase the SOC content at a rate of 1.37 Mg ha-1y-1. Also it was found that sugarcane fields burning led to about 15% reduction of the total carbon stock in the 0-30 cm soil layer. The overall increase in SOC under unburned practice is mainly due to the large input of organic material through the use of sugarcane residues.

Keywords: soil organic carbon, soil inorganic carbon, carbon sequestration, open burning, sugarcane

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Authors: Gui Yewei, Du Yanxia, Xiao Guangming, Liu Lei, Wei Dong, Yang Xiaofeng

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A phase change material (PCM) is a substance which absorbs a large amount of energy when undergoing a change of solid-liquid phase. The good physical and chemical properties of C or SiC foam reveal the possibility of using them as a thermal conductivity enhancer for the PCM. C or SiC foam composite PCM has a high effective conductivity and becomes one of the most interesting thermal storage techniques due to its advantage of simplicity and reliability. The paper developed a numerical method to simulate the heat transfer of SiC and C foam composite PCM, a finite volume technique was used to discretize the heat diffusion equation while the phase change process was modeled using the equivalent specific heat method. The effects of the porosity were investigated based on the numerical method, and the effects of the geometric model of the microstructure on the equivalent thermal conductivity was studies.

Keywords: SiC foam, composite, phase change material, heat transfer

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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: Selatnia Khaled Grine Ikram

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The city of Biskra, like other Algerian cities, knows of urban traffic congestion. The concentration of investments especially in the secondary and tertiary sectors in the Wilaya has attracted a large rural population. The latter, combined with the high rate of natural growing, favored the imbalance of the spatial frame of wilayal system and consequently the traffic congestion of the primate city (Biskra). This urban disease is explained by a two-tier development. The capital of Wilaya growing faster than its others centers body and takes measurements of proportion to the whole. The consequences can only be negative. The pressure on the roads, the growth of the fleet, overloading of equipment and activities have become the characteristics of the city of Biskra, which can no longer meet the needs of its inhabitants. This research attempts to show the relationship between urban congestion of the primate city and the imbalance of the spatial structure of the micro-regional urban system.

Keywords: traffic congestion, spatial structure, pressure on the roads, equipment and activities

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Authors: Maria Evnevich

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In modern conditions, in most markets, price competition is becoming less effective. On the one hand, there is a gradual decrease in the level of marginality in main traditional sectors of the economy, so further price reduction becomes too ‘expensive’ for the company. On the other hand, the effect of price reduction is leveled, and the reason for this phenomenon is likely to be informational. As a result, it turns out that even if the company reduces prices, making its products more accessible to the buyer, there is a high probability that this will not lead to increase in sales unless additional large-scale advertising and information campaigns are conducted. Similarly, a large-scale information and advertising campaign have a much greater effect itself than price reductions. At the same time, the cost of mass informing is growing every year, especially when using the main information channels. The article presents generalization, systematization and development of theoretical approaches and best practices in the field of customer focus approach to business management and in the field of relationship marketing in the modern digital economy. The research methodology is based on the synthesis and content-analysis of sociological and marketing research and on the study of the systems of working with consumer appeals and loyalty programs in the 50 largest client-oriented companies in Russia. Also, the analysis of internal documentation on customers’ purchases in one of the largest retail companies in Russia allowed to identify if buyers prefer to buy goods for complex purchases in one retail store with the best price image for them. The cost of attracting a new client is now quite high and continues to grow, so it becomes more important to keep him and increase the involvement through marketing tools. A huge role is played by modern digital technologies used both in advertising (e-mailing, SEO, contextual advertising, banner advertising, SMM, etc.) and in service. To implement the above-described client-oriented omnichannel service, it is necessary to identify the client and work with personal data provided when filling in the loyalty program application form. The analysis of loyalty programs of 50 companies identified the following types of cards: discount cards, bonus cards, mixed cards, coalition loyalty cards, bank loyalty programs, aviation loyalty programs, hybrid loyalty cards, situational loyalty cards. The use of loyalty cards allows not only to stimulate the customer to purchase ‘untargeted’, but also to provide individualized offers, as well as to produce more targeted information. The development of digital technologies and modern means of communication has significantly changed not only the sphere of marketing and promotion, but also the economic landscape as a whole. Factors of competitiveness are the digital opportunities of companies in the field of customer orientation: personalization of service, customization of advertising offers, optimization of marketing activity and improvement of logistics.

Keywords: customer focus, digital economy, loyalty program, relationship marketing

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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: Moon Hee Jung, Dae Seung Kim, Sang-Myung Jung, Gwang Heum Yoon, Hoo Cheol Lee, Hwa Sung Shin

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Scaffolds are an important part to support growth and differentiation of osteoblast for regeneration of injured bone in bone tissue engineering. We utilized tunicate cellulose nanowhisker (CNW) as scaffold and developed complex system that can enhance differentiation of osteoblast by applying mechanical stimulation. CNW, a crystal form of cellulose, has high stiffness with a large surface area and is useful as a biomedical material due to its biodegradability and biocompatibility. In this study, CNW was obtained from tunicate extraction and was confirmed for its adhesion, differentiation, growth of osteoblast without cytotoxicity. In addition, osteoblast was successfully differentiated under mechanical stimulation, followed by calcium dependent signaling. In conclusion, we verified suitability of CNW as scaffold and possibility of bone substitutes.

Keywords: osteoblast, cellulose nanowhisker, CNW, mechanical stimulation, bone tissue engineering, bone substitute

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Authors: Mattias Bergstrom

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Significance of the Study: This research will provide new insights into the risks with digital embedded infrastructure. Through this research, we will analyze each risk and its potential negation strategies, especially for AI and autonomous automation. Moreover, the analysis that is presented in this paper will convey valuable information for future research that can create more stable, secure, and efficient autonomous systems. To learn and understand the risks, a large IoT system was envisioned, and risks with hardware, tampering, and cyberattacks were collected, researched, and evaluated to create a comprehensive understanding of the potential risks. Potential solutions have then been evaluated on an open source IoT hardware setup. This list shows the identified passive and active risks evaluated in the research. Passive Risks: (1) Hardware failures- Critical Systems relying on high rate data and data quality are growing; SCADA systems for infrastructure are good examples of such systems. (2) Hardware delivers erroneous data- Sensors break, and when they do so, they don’t always go silent; they can keep going, just that the data they deliver is garbage, and if that data is not filtered out, it becomes disruptive noise in the system. (3) Bad Hardware injection- Erroneous generated sensor data can be pumped into a system by malicious actors with the intent to create disruptive noise in critical systems. (4) Data gravity- The weight of the data collected will affect Data-Mobility. (5) Cost inhibitors- Running services that need huge centralized computing is cost inhibiting. Large complex AI can be extremely expensive to run. Active Risks: Denial of Service- It is one of the most simple attacks, where an attacker just overloads the system with bogus requests so that valid requests disappear in the noise. Malware- Malware can be anything from simple viruses to complex botnets created with specific goals, where the creator is stealing computer power and bandwidth from you to attack someone else. Ransomware- It is a kind of malware, but it is so different in its implementation that it is worth its own mention. The goal with these pieces of software is to encrypt your system so that it can only be unlocked with a key that is held for ransom. DNS spoofing- By spoofing DNS calls, valid requests and data dumps can be sent to bad destinations, where the data can be extracted for extortion or to corrupt and re-inject into a running system creating a data echo noise loop. After testing multiple potential solutions. We found that the most prominent solution to these risks was to use a Peer 2 Peer consensus algorithm over a blockchain to validate the data and behavior of the devices (sensors, storage, and computing) in the system. By the devices autonomously policing themselves for deviant behavior, all risks listed above can be negated. In conclusion, an Internet middleware that provides these features would be an easy and secure solution to any future autonomous IoT deployments. As it provides separation from the open Internet, at the same time, it is accessible over the blockchain keys.

Keywords: IoT, security, infrastructure, SCADA, blockchain, AI

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Authors: K. Ilicic, D. Smoljan

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The purpose of the paper is to present and verify a methodology of decreasing water losses by introducing and managing District Metered Areas (DMA) and Pressure Management Areas (PMA) by analyzing the results of the application of the methodology to the water supply system of the city of Zagreb. Since it is a relatively large system that has been expanding rapidly, approach to addressing water losses was possible only by splitting the system to smaller flow and pressure zones. Besides, the geographical and technical limitations had imposed the necessity of high pressure in the system that needed to be reduced to the technically optimal level. Results of activities were monitored on a general and local level by establishing, monitoring, and controlling indicators that had been established by the International Water Association (IWA), among which the most recognizable were non-revenue water, water losses and real losses as presented in the paper.

Keywords: district metered area, pressure metered area, active leakage control, water losses

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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: M. H. Alhajeri, Hamad M. Alhajeri, A. H. Alenezi

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Computational fluid dynamics (CFD) investigation of heat transfer in U-duct with turbulators is presented in this paper. The duct passages used to cool internally the blades in gas turbine. The study is focused in the flow behavior and the Nusselt number (Nu) distributions. The model of the u-duct contains two square legs that are connected by 180* turn. Four turbulators are located in each surface of the leg and distributed in a staggered arrangement. The turbulator height and width are equal to 0.1 of the duct width, and the turbulator height is 0.1 of the distance between the turbulators. The Reynolds number (Re) used in this study is 95000 and the inlet velocity is 10 m/s. It was noticed that, after the flow resettles from the interruptions generated by the first turbulator or the turn, the flow construct two eddies, one large and the other is small after and before the turbulator, respectively. The maximum values of the Nu are found at a distance of approximately one turbulator width w before of the flow reattachment point.

Keywords: computational fluid dynamics, CFD, rib, heat transfer, blade

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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: Tiee-Jian Wu, Chih-Yuan Hsu

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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.

Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method

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Authors: Rudraksh Kesharwani, Ritika Agarkar

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Sexually transmitted diseases are a major public health concern affecting both the mortality and the morbidity of a population. It is among the most serious causes of the diseases affecting the quality of life of a individual leading to a significant decrease in their health. In India, STIs have been a significant public health concern due to various reasons, including a large population, limited access to healthcare in certain areas, stigma around discussing sexual health, and insufficient sex education. Some common STIs in India include HIV/AIDS, syphilis, gonorrhea, chlamydia, and herpes. This research report aims to determine the percentage of people infected with sexually transmitted infections (STI) worrying about it’s impact on their day to day activity, specifically focusing on it’s impact on the mentaland sexual health of the patient infected along with his/her partner.

Keywords: sexual health, mental health, sexually transmitted disease, sexual taboos

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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

Procedia PDF Downloads 121

Authors: A. Askerov, Y. Teterin, P. Yartcev, S. Novikov

Abstract:

Introduction: Acute pancreatitis (AP) is a socially significant problem for public health and continues to be one of the most common causes of hospitalization of patients with pathology of the gastrointestinal tract. It is characterized by high mortality rates, which reaches 62-65% in infected pancreatic necrosis. Aims & Methods: The study group included 63 patients who underwent transluminal drainage (TLD) fluid collection (FC). All patients were performed transabdominal ultrasound, computer tomography of the abdominal cavity and retroperitoneal organs and endoscopic ultrasound (EUS) of the pancreatobiliary zone. The EUS was used as a final diagnostic method to determine the characteristics of FC. The indications for TLD were: the distance between the wall of the hollow organ and the FC was not more than 1 cm, the absence of large vessels on the puncture trajectory (more than 3 mm), and the size of the formation was more than 5 cm. When a homogeneous cavity with clear, even contours was detected, a plastic stent with rounded ends (“double pig tail”) was installed. The indication for the installation of a fully covered self-expanding stent was the detection of nonhomogeneous anechoic FC with hyperechoic inclusions and cloudy purulent contents. In patients with necrotic forms after drainage of the purulent cavity, a cystonasal drainage with a diameter of 7Fr was installed in its lumen under X-ray control to sanitize the cavity with a 0.05% aqueous solution of chlorhexidine. Endoscopic necrectomy was performed every 24-48 hours. The plastic stent was removed in 6 month, the fully covered self-expanding stent - in 1 month after the patient was discharged from the hospital. Results: Endoscopic TLD was performed in 63 patients. The FC corresponding to interstitial edematous pancreatitis was detected in 39 (62%) patients who underwent TLD with the installation of a plastic stent with rounded ends. In 24 (38%) patients with necrotic forms of FC, a fully covered self-expanding stent was placed. Communication with the ductal system of the pancreas was found in 5 (7.9%) patients. They underwent pancreaticoduodenal stenting. A complicated postoperative period was noted in 4 (6.3%) cases and was manifested by bleeding from the zone of pancreatogenic destruction. In 2 (3.1%) cases, this required angiography and endovascular embolization a. gastroduodenalis, in 1 (1.6%) case, endoscopic hemostasis was performed by filling the cavity with 4 ml of Hemoblock hemostatic solution. The combination of both methods was used in 1 (1.6%) patient. There was no evidence of recurrent bleeding in these patients. Lethal outcome occurred in 4 patients (6.3%). In 3 (4.7%) patients, the cause of death was multiple organ failure, in 1 (1.6%) - severe nosocomial pneumonia that developed on the 32nd day after drainage. Conclusions: 1. EUS is not only the most important method for diagnosing FC in AP, but also allows you to determine further tactics for their intraluminal drainage.2. Endoscopic intraluminal drainage of fluid zones in 45.8% of cases is the final minimally invasive method of surgical treatment of large-focal pancreatic necrosis. Disclosure: Nothing to disclose.

Keywords: acute pancreatitis, fluid collection, endoscopy surgery, necrectomy, transluminal drainage

Procedia PDF Downloads 109

Authors: Rujijan Vichivanives, Kittiya Poonsilp, Canasanan Wanavijit

Abstract:

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

Procedia PDF Downloads 287