Search results for: improve

Authors: Avraham Mosseri

Abstract:

The architectural conservation process of the built heritage is a very complex process dealing with the integration of professional knowledge from many fields like history, sociology, economy, engineering, etc. One of the most important fields is the structural field, which has a great influence on the final architectural and aesthetic solution of the built heritage. In many cases, the ability to protect and save the heritage values of the historical buildings is an outcome of the structural creativity and conceptual design of the conservation engineers. This creativity is especially important when dealing with structural engineering of historic construction, where there are a lot of constraints and contradictions between different aspects like aesthetics, artistic values, culture, authenticity, structural performance, etc. But in spite of the importance of this creativity in conservation engineering, many research efforts are mainly devoted to the structural analysis of historic construction, which of course is very important and vital. But, in general, more attention can be paid to the creative process in the conceptual stage. In this situation there is a need, in parallel to analysis research, to devote more resources in order to improve the creative and conceptual theories in relation to conservation engineering. This paper focuses on the creativity aspects in the structural design process in the conservation of historic buildings as part of conservation theories.

Keywords: conservation, creativity, historic constructions, structural design

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Authors: Victor William Harris

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This research is a validation study of the Social Emotional Ability Inventory (SEAI), a multi-dimensional self-report instrument informed by positive psychology, emotional intelligence, social intelligence, and sociocultural learning theory. Designed for use in tandem with the Social Emotional Development (SEAD) theoretical model, the SEAI provides diagnostic-level guidance for professionals and individuals interested in investigating, identifying, and understanding social, emotional strengths, as well as remediating specific social competency deficiencies. The SEAI was shown to be psychometrically sound, exhibited strong internal reliability, and supported the a priori hypotheses of the SEAD. Additionally, confirmatory factor analysis provided evidence of goodness of fit, convergent and divergent validity, and supported a theoretical model that reflected SEAD expectations. The SEAI and SEAD hold potentially far-reaching and important practical implications for theoretical guidance and diagnostic-level measurement of social, emotional competency across a wide range of domains. Strategies researchers, practitioners, educators, and individuals might use to deploy SEAI in order to improve quality of life outcomes are discussed.

Keywords: emotion, emotional ability, positive psychology-social emotional ability, social emotional ability, social emotional ability instrument

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Authors: Ang Ling Weay, Mona Masood

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This paper discusses the potential benefits of an interactive multimedia information representation in enhancing students’ critical thinking aligned with history reasoning in learning history between Secondary School students in Malaysia. Two modes of multimedia information representation implemented which are chronological and thematic information representation. A qualitative study of an unstructured interview was conducted among two history teachers, one history education lecturer, two i-think expert and program trainers and five form 4 secondary school students. The interview was to elicit their opinions on the implementation of thinking maps and interactive multimedia information representation in history learning. The key elements of interactive multimedia (e.g. multiple media, user control, interactivity, and use of timelines and concept maps) were then considered to improve the learning process. Findings of the preliminary investigation reveal that the interactive multimedia information representations have the potential benefits to be implemented as instructional resource in enhancing students’ higher order thinking skills (HOTs). This paper concludes by giving suggestions for future work.

Keywords: multimedia information representation, critical thinking, history reasoning, chronological and thematic information representation

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Authors: Linda P. M. Pluymen, Mariska M. G. Leeflang, I. Stegeman, Henock G. Yebyo, Anne E. M. Brabers, Patrick M. Bossuyt, E. Dekker, Anke J. Woudstra, Mirjam P. Fransen

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Weighing the benefits and harms of colorectal cancer screening can be difficult for individuals. An existing online decision aid was expanded with a benefit-harm analysis to help people make an informed decision about participating in colorectal cancer screening. In a randomized controlled trial, we investigated whether those in the intervention group who used the decision aid with benefit-harm analysis were more certain about their decision than those in the control group who used the decision aid without benefit-harm analysis. Participants were 623 (39% of those invited) men and women aged 45 until 75 years old. Analyses were performed in those 386 participants (62%) who reported to have completed the entire decision aid. No statistically significant differences were observed between intervention and control group in decisional conflict score (mean difference 2.4, 95% CI -0.9, 5.6), clarity of values (mean difference 1.0, 95% CI -4.4, 6.6), deliberation score (mean difference 0.5, 95% CI -0.6, 1.7), anxiety score (mean difference 0.0, 95% CI -0.3, 0.3) and risk perception score (mean difference 0.1, -0.1, 0.3). Adding a benefit-harm analysis to an online decision aid did not improve informed decision making about participating in colorectal cancer screening.

Keywords: benefit-harm analysis, decision aid, informed decision making, personalized decision making

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Authors: Sarah Beaver, Renee Bryce

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Audiograms detect hearing impairment, but missing values pose problems. This work explores imputations in an attempt to improve accuracy. This work implements Linear Regression, Lasso, Linear Support Vector Regression, Bayesian Ridge, K Nearest Neighbors (KNN), and Random Forest machine learning techniques to impute audiogram frequencies ranging from 125Hz to 8000Hz. The data contains patients who had or were candidates for cochlear implants. Accuracy is compared across two different Nested Cross-Validation k values. Over 4000 audiograms were used from 800 unique patients. Additionally, training on data combines and compares left and right ear audiograms versus single ear side audiograms. The accuracy achieved using Root Mean Square Error (RMSE) values for the best models for Random Forest ranges from 4.74 to 6.37. The R\textsuperscript{2} values for the best models for Random Forest ranges from .91 to .96. The accuracy achieved using RMSE values for the best models for KNN ranges from 5.00 to 7.72. The R\textsuperscript{2} values for the best models for KNN ranges from .89 to .95. The best imputation models received R\textsuperscript{2} between .89 to .96 and RMSE values less than 8dB. We also show that the accuracy of classification predictive models performed better with our best imputation models versus constant imputations by a two percent increase.

Keywords: machine learning, audiograms, data imputations, single imputations

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Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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Authors: F. Laatar, S. Ktifa, H. Ezzaouia

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Plasma Enhanced Chemical Vapor Deposition (PECVD) method is used to deposit hydrogenated nanocrystalline silicon films (nc-Si: H) on Porous Anodic Alumina Films (PAF) on glass substrate at different deposition duration. Influence of the deposition time on the physical properties of nc-Si: H grown on PAF was investigated through an extensive correlation between micro-structural and optical properties of these films. In this paper, we present an extensive study of the morphological, structural and optical properties of these films by Atomic Force Microscopy (AFM), X-Ray Diffraction (XRD) techniques and a UV-Vis-NIR spectrometer. It was found that the changes in DT can modify the films thickness, the surface roughness and eventually improve the optical properties of the composite. Optical properties (optical thicknesses, refractive indexes (n), absorption coefficients (α), extinction coefficients (k), and the values of the optical transitions EG) of this kind of samples were obtained using the data of the transmittance T and reflectance R spectra’s recorded by the UV–Vis–NIR spectrometer. We used Cauchy and Wemple–DiDomenico models for the analysis of the dispersion of the refractive index and the determination of the optical properties of these films.

Keywords: hydragenated nanocrystalline silicon, plasma processing chemical vapor deposition, X-ray diffraction, optical properties

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Authors: Marcus C. Garcia, Giselle C. Guimarães, Luciana H. Yamane, Renato R. Siman

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The environmental indicators and the classification of beach waste are essential tools to diagnose the current situation and to indicate ways to improve the quality of this environment. The purpose of this paper was to perform a quali-quantitative analysis of the beach waste on the Curva da Jurema Beach (Espírito Santo - Brazil). Three transects were used with equidistant positioning over the total length of the beach for the solid waste collection. Solid wastes were later classified according to their use and primary raw material from the low and high summer season. During the low season, average values of 7.10 items.m^-1, 18.22 g.m^-1 and 0.91 g.m^-2 were found for the whole beach, and transect 3 contributed the most waste, with the total sum of items equal to 999 (49%), a total mass of 5.62 kg and a total volume of 21.31 L. During the high summer season, average values of 8.22 items.m^-1, 54.40 g.m^-1 and 2.72 g.m^-2 were found, with transect 2 contributing the most to the total sum with 1,212 items (53%), a total mass of 10.76 kg and a total volume of 51.99 L. Of the total collected, plastic materials represented 51.4% of the total number of items, 35.9% of the total mass and 68% of the total volume. The implementation of reactive and proactive measures is necessary so that the management of the solid wastes on Curva da Jurema Beach is in accordance with principles of sustainability.

Keywords: beach solid waste, environmental indicators, quali-quantitative analysis, waste management

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Authors: Phanawan Whangdee, Tomoaki Watanabe, Viritpon Srimaneepong, Dujreutai Pongkao Kashima

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The anodized films formed at high current density or high voltage have been widely prepared for dental implant because it can improve the hydrophilicity to the film. Our attempt is exploring whether low current density and low voltage could enhance the good hydrophilicity to the anodized films or not. Furthermore, UV irradiation would be one of the key factor to enhance their hydrophilicity. The anodized films were performed at low current density of 2 mA/cm2 in 1M H3PO4, 1 mA/cm2 in 1M MCPM and low voltage of 6 V in either 1M H3PO4 or 1M MCPM. All samples were treated with UV for various times up to 24 h. After UV irradiation, the contact angle decreased, the chemical species changed. The Ti 2p and O 1s peaks increased, while the C 1s peak decreased which might be due to removal of hydrocarbon. The functional groups of the films shown as the change of OH groups appeared at wave number 3700 cm-1 and 2900-3000 cm-1, however, the peak of H2O at 1630 cm-1disappeared. It is indicated that UV irradiation might change the stretching modes of OH groups coordinated to surface Ti4+ cation but UV did not affect to the changes in surface morphologies. The surface energies increased after UV irradiation resulting in improving of the hydrophilicity. The anodized films formed at low current density or low voltage after UV irradiation showed a low contact angle as well as the film formed at high current density or high voltage.

Keywords: hydrophilicity, low current density, low voltage, UV irradiation

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Authors: N. Borjalilu, P. Rabiei, A. Enjoo

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Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety

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Authors: Samereh Abdoli, Amit Vora, Anusha Vora

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Background: Diabetes burnout is one of the most common contributors to decreased quality of life, poor psychosocial well-being, and increased morbidity, mortality and diabetes cost. While the term diabetes burnout is widely accepted particularly in type 1 diabetes (T1D), the state of the science on diabetes burnout is lacking a systematic approach to overcome diabetes burnout. Objective: The study aimed to explore the strategies to overcome burnout by integrating the voices of individuals with T1D. Methods: In this study, we applied a descriptive qualitative design using YouTube videos produced by individuals with T1D. Seven YouTube videos (Austria= 1, U.S=6) with the highest rate of views which met the inclusion criteria were analyzed using a qualitative content analysis approach. Results: Participants verbalized overcoming diabetes burnout as a 'difficult hole to climb out of' which make them empowered. Themes that describes their strategies to overcome burnout in T1D, in general, include; 'make plan and take action', 'start with small steps', 'ask for help', 'get engage in diabetes community' and 'do not be perfect'. Future Work: These findings can begin the examination of different strategies to overcome diabetes burnout, which may change the course of action for diabetes care and management to improve quality of diabetes care and quality of life.

Keywords: diabetes burnout, type 1 diabetes, qualitative research, YouTube videos

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Authors: Veselin Konstantinov Hristov

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In recent years, the lease contract has become more and more applicable and occupies a key place in commercial relations and business. In Bulgaria, the legal regulation of the leasing contract is relatively new and imperfectly developed. There are many legal loopholes and it is they that determine the need for a comparative legal analysis. The purpose of the study is to analyze the various European legislations regarding the leasing contract and to find effective solutions for the legal system of Bulgaria. First of all, are examined the concept of the leasing contract, which originated in the United States of America around the 1950s and spread in Europe, and the etymology of the term "leasing". After that, the main types of lease contracts – financial and operational – are examined and analyzed in detail. Their features and characteristics were studied, as well as a comparative analysis was made between them. Next, in the research, a comparative-legal analysis of the leasing contract in different European countries was made in terms of its development and distribution, as well as its legal characteristics. The mechanism of action and functioning of the leasing contract in several European countries is analyzed. Conclusions are made regarding the legal framework under which the lease contract is most effective. Types of leasing contracts specific only to certain European countries and their advantages are examined. In conclusion, recommendations are made to improve the legal framework of the leasing contract in Bulgaria.

Keywords: alternative financing, leasing contract, financing instruments, innovation

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Authors: Xiaoming Jiang, Jinqiao Shi, Qingfeng Tan, Wentao Zhang, Xuebin Wang, Muqian Chen

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Nowadays, big companies such as Google, Microsoft, which have adequate proxy servers, have perfectly implemented their web crawlers for a certain website in parallel. But due to lack of expensive proxy servers, it is still a puzzle for researchers to crawl large amounts of information from a single website in parallel. In this case, it is a good choice for researchers to use free public proxy servers which are crawled from the Internet. In order to improve efficiency of web crawler, the following two issues should be considered primarily: (1) Tasks may fail owing to the instability of free proxy servers; (2) A proxy server will be blocked if it visits a single website frequently. In this paper, we propose Proxisch, an optimization approach of large-scale unstable proxy servers scheduling, which allow anyone with extremely low cost to run a web crawler efficiently. Proxisch is designed to work efficiently by making maximum use of reliable proxy servers. To solve second problem, it establishes a frequency control mechanism which can ensure the visiting frequency of any chosen proxy server below the website’s limit. The results show that our approach performs better than the other scheduling algorithms.

Keywords: proxy server, priority queue, optimization algorithm, distributed web crawling

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Authors: Roshani Gusain, Deep Sinha, Karan Nayal, Anmol Kumar Mishra, Manav Singh

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In this research paper, we introduce "Mind Care Assistant - Companion App", which is a Flutter and Firebase-based mental health monitor. The app wants to improve and monitor the mental health of its users, it uses noninvasive ways to check for a change in their emotional state. By responding to questions, the app will provide individualized suggestions ᅳ tasks and mindfulness exercises ᅳ for users who are depressed or anxious. The app features a chat-bot that incorporates cognitive behavioural therapy (CBT) principles and combines natural language processing with machine learning to develop personalised responses. The feature of the app that makes it easy for us to choose between iOS and Android is cross-platform, which allows users from both mobile systems to experience almost no changes in their interfaces. With Firebase integration synchronized and real-time data storage, security is easily possible. The paper covers the architecture of the app, how it was developed and some important features. The primary research result presents the promise of a "Mind Care Assistant" in mental health care using new wait-for-health technology, proposing a full stack application to be able to manage depression/anxiety and overall Mental well-being very effectively.

Keywords: mental health, mobile application, flutter, firebase, Depression, Anxiety

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Authors: Yuling Cui, Danhao Deng, Chaowei Wang, Weidong Wang

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In recent years, unmanned aerial vehicles (UAVs) have been widely used in wireless communication, attracting more and more attention from researchers. UAVs can not only serve as a relay for auxiliary communication but also serve as an aerial base station for ground users (GUs). However, limited energy means that they cannot work all the time and cover a limited range of services. In this paper, we investigate 2D UAV trajectory design and power allocation in order to maximize the UAV's service time and downlink throughput. Based on deep reinforcement learning, we propose a depth deterministic strategy gradient algorithm for trajectory design and power distribution (TDPA-DDPG) to solve the energy-efficient and communication service quality problem. The simulation results show that TDPA-DDPG can extend the service time of UAV as much as possible, improve the communication service quality, and realize the maximization of downlink throughput, which is significantly improved compared with existing methods.

Keywords: UAV trajectory design, power allocation, energy efficient, downlink throughput, deep reinforcement learning, DDPG

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Authors: Frederick N. F. Chou, Nguyen Thi Thuy Linh

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The impact of water shortages has been increasingly severe as a consequence of population growth, urbanization, economic development, and climate change. The need for improvements in reliable water supply systems is urgent with the increasing living standards of regions. In this study, a suitable shortage index capable of multi-aspect description - frequency, magnitude, and duration - is adopted to more accurately describe the characteristics of a shortage situation. The values of the index were determined to cope with the increasing need for reliability. There are four reservoirs in series located on the Be River of the Dong Nai River Basin in Southern Vietnam. The primary purpose of the three upstream reservoirs is hydropower generation while the primary purpose of the fourth is water supply. A compromise between hydropower generation and water supply can be negotiated for these four reservoirs to reduce the severity of water shortages. A generalized water allocation model was applied to simulate the water supply, and hydropower generation of various management alternatives and the system’s reliability was evaluated using the adopted multiple shortage indices. Modifying management policies of water resources using data-based indexes can improve the reliability of water supply.

Keywords: cascade reservoirs, hydropower, shortage index, water supply

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Authors: Hari Prasad Nepal

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Research on lecture method issues confirm that this teaching method has been practiced from the very beginnings of schooling. Many teachers, lecturers and professors are convinced that lecture still represents main tool of contemporary instructional process. The central purpose of this study is to uncover the extent of using lecture method in the higher education. The study was carried out in Nepalese context with employing mixed method research design. To obtain the primary data this study employed a questionnaire involving items with close and open answers. 120 teachers, lecturers and professors participated in this study. The findings indicated that 75 percent of the respondents use the lecture method in their classroom teaching. The study reveals that there are advantages of using lecture method such as easy to practice, less time to prepare, high pass rate, high students’ satisfaction, little comments on instructors, appropriate to large classes and high level students. In addition, the study divulged the instructors’ reflections and measures to improve the lecture method. This research concludes that the practice of lecture method is still significantly applicable in colleges and universities in Nepalese contexts. So, there are no significant changes in the application of lecture method in the higher education classroom despite the emergence of new learning approaches and strategies.

Keywords: instructors, learning approaches, learning strategies, lecture method

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Authors: Mohammed T. Hayajneh, Adel Mahmood Hassan, Moath AL-Qudah

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Burnishing is increasingly used as a finishing operation to improve surface roughness and surface hardness. This can be achieved by applying a hard ball or roller onto metallic surfaces under pressure, in order to achieve many advantages in the metallic surface. In the present work, the feed rate, speed and force have been considered as the basic burnishing parameters to study the surface roughness and surface hardness of metallic matrix composites. The considered metal matrix composites were made from Aluminum-Magnesium-Graphite with five different weight percentage of graphite. Both effects of burnishing parameters mentioned above and the graphite percentage on the surface hardness and surface roughness of the metallic matrix composites were studied. The results of this investigation showed that the surface hardness of the metallic composites increases with the increase of the burnishing force and decreases with the increase in the burnishing feed rate and burnishing speed. The surface roughness of the metallic composites decreases with the increasing of the burnishing force, feed rate, and speed to certain values, then it starts to increase. On the other hand, the increase in the weight percentage of the graphite in the considered composites causes a decrease in the surface hardness and an increase in the surface roughness.

Keywords: burnishing process, Al-Mg-Graphite composites, surface hardness, surface roughness

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Authors: H. L. M. Fawzan

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Undoubtedly, learning English as a second language (ESL) is considered a challenging task. It is more difficult for students in far-away districts when compared with the students in the capital cities, where learning resources are easily available and where the environment is conducive to learning. Thus, this study is an analysis of the challenges faced by learners in learning English as the second language within kurunegala district in Sri Lanka. Even though various efforts have been taken by the Sri Lankan Educationalists for improving the situation of English language teaching for the past few decades, a disappointing situation still exist in the achievements of English learning among Sri Lankan students. So, it is necessary to explore real reasons behind the poor achievements of the students in the English Language. It is also an attempt to highlight what can be done to improve the situation significantly. Kurunegala is far away from the capital city of Sri Lanka and is a densely populated district. In the year 2020, state university admission was 45.87% from the Kurunegala district (Department of Examinations). The researcher strived to examine some of the likely challenges faced when teaching English in secondary schools in Kurunegala. The data was collected using a questionnaire from 35 students from schools within the Kurunegala education division. The result of the study reveals that students were highly motivated to learn English for their prospects and expectations such as local and international communication, academic advancement, and employment prospects.

Keywords: english, teaching, Kurunegala, Sri Lanka, challenges

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Authors: Hussain Ali Bekhet, Tuan Ab. Rashid Bin Tuan Abdullah, Tahira Yasmin

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The strong relationship between energy consumption and economic growth is widely recognised. Most countries’ energy demand declined during the economic depression known as the Global Financial Crisis (GFC) of 2008–2009. The objective of the current study is to investigate the energy consumption and performance of Malaysia’s manufacturing sectors during the GFC. We applied the output multiplier approach, which is based on the input-output model. Two input-output tables of Malaysia covering 2005 and 2010 were used. The results indicate significant changes in the output multipliers of the manufacturing sectors between 2005 and 2010. Moreover, the energy-to-manufacturing sectors’ output multipliers also decreased during the GFC due to a decline in export-oriented industries during the crisis. The increasing importance of the manufacturing sector to the development of Malaysian trade resulted in a noticeable decrease in the consumption of each energy sector’s output, especially the electricity and gas sector. Based on the research findings, the Malaysian government released several policy implementations in the form of stimulus packages to enhance these sectors’ performance and generally improve the Malaysian economy.

Keywords: global financial crisis, input-output model, manufacturing, output multipliers, energy, Malaysia

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Authors: Paffrath Meinhard, Zhou Yayun, Guo Yiqing, Ertl Harald

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Winding geometry design is an important part of power transformer electrical design. Conventionally, the winding geometry is designed manually, which is a time-consuming job because it involves many iteration steps in order to meet all cost, manufacturing and electrical requirements. Here a method is presented which automatically generates the winding geometry for given user parameters and allows the user to interactively set and change parameters. To achieve this goal, the winding problem is transferred to a mixed integer nonlinear optimization problem. The relevant geometrical design parameters are defined as optimization variables. The cost and other requirements are modeled as constraints. For the solution, a stochastic ant colony optimization algorithm is applied. It is well-known, that an optimizer can get stuck in a local minimum. For the winding problem, we present efficient strategies to come out of local minima, furthermore a reduced variable search range helps to accelerate the solution process. Numerical examples show that the optimization result is delivered within seconds such that the user can interactively change the variable search area and constraints to improve the design.

Keywords: ant colony optimization, mixed integer nonlinear programming, power transformer, winding design

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Authors: Bih-O Lee, Hsiu-Wan Hsieh, Hsiu-Chen Liu, Mer Yu Pan

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Background: Illness perceptions are developed when people face health-threatening situations. Previous research suggests that understanding discrepancies between illness perceptions of patients and caregivers may need to improve quality of health care. Objective: This study examined the differences between illness perceptions of injured patients and those of their caregivers. Methods: Comparative study design was used. The study setting was the surgical wards of a teaching hospital in Taiwan. Participants were 127 pairs of injured patients and their caregivers. The participants completed socio-demographic data and completed the Chinese Illness Perception Questionnaire Revised-Trauma, which comprises eight subscales. Clinical data of the injured patients was obtained from medical records. Results: This study found that injured patients were more pessimistic than their caregivers about the injury. There were significant differences between patients and caregivers insofar as patients perceived more physical symptoms, scored higher in terms of reasons for their injury, had more negative emotions and experienced more consequences than caregivers. Elderly caregivers and caregivers for patients who were over 65, severely injured and admitted to an ICU perceived more negative perceptions about the injury. Conclusions: This study indicated that patients and caregivers had negative illness representations several months after injury although the intensity of their perceptions was different. The interventions should highlight the need to assist patients and caregivers after injury.

Keywords: illness representations, injury, caregivers, comparative study

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Authors: Xudong He, Jian Wang, Jiqiang Liu, Lei Han, Yang Yu, Shaohua Lv

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Nowadays, the threats of the internet are enormous and increasing; however, the classification of huge alert messages generated in this environment is relatively monotonous. It affects the accuracy of the network situation assessment, and also brings inconvenience to the security managers to deal with the emergency. In order to deal with potential network threats effectively and provide more effective data to improve the network situation awareness. It is essential to build a hierarchical filtering method to prevent the threats. In this paper, it establishes a model for data monitoring, which can filter systematically from the original data to get the grade of threats and be stored for using again. Firstly, it filters the vulnerable resources, open ports of host devices and services. Then use the entropy theory to calculate the performance changes of the host devices at the time of the threat occurring and filter again. At last, sort the changes of the performance value at the time of threat occurring. Use the alerts and performance data collected in the real network environment to evaluate and analyze. The comparative experimental analysis shows that the threat filtering method can effectively filter the threat alerts effectively.

Keywords: correlation analysis, hierarchical filtering, multisource data, network security

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Authors: Kamalendu Pal

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This paper describes the main features of a knowledge-based system evaluation method. System evaluation is placed in the context of a hybrid legal decision-support system, Advisory Support for Home Settlement in Divorce (ASHSD). Legal knowledge for ASHSD is represented in two forms, as rules and previously decided cases. Besides distinguishing the two different forms of knowledge representation, the paper outlines the actual use of these forms in a computational framework that is designed to generate a plausible solution for a given case, by using rule-based reasoning (RBR) and case-based reasoning (CBR) in an integrated environment. The nature of suitability assessment of a solution has been considered as a multiple criteria decision making process in ASHAD evaluation. The evaluation was performed by a combination of discussions and questionnaires with different user groups. The answers to questionnaires used in this evaluations method have been measured as a combination of linguistic variables, fuzzy numbers, and by using defuzzification process. The results show that the designed evaluation method creates suitable mechanism in order to improve the performance of the knowledge-based system.

Keywords: case-based reasoning, fuzzy number, legal decision-support system, linguistic variable, rule-based reasoning, system evaluation

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Authors: Cam Minh Tri Tien, Richard Fenrich, Tristan Shelley, Nam Mai-Duy, Allan Malano, Xuesen Zeng

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Since additive manufacturing is a layer-by-layer deposition approach, good bonding quality between adjacent layers is critically important to achieve optimal mechanical performance, including applications in pressure vessels. The need to enhance the strength of printed products, especially in the build direction where layup gaps and voids exist between the printed layers, has garnered significant attention. The proposed research will focus on improving the current Fused Deposition Modelling (FDM) process to produce polymers reinforced with chopped fibers, utilizing a controlled heat zone to enhance the adhesion between printed layers. Energy will be applied to both printed and printing layers to improve the bonding strength between adjacent layers. Through the enhanced FDM process, the mechanical performance of composite parts will experience a substantial improvement, particularly in the build direction, as compared to current FDM methods. A combination of experimental, numerical, and analytical methods will be employed to demonstrate the enhanced performance of heat-controlled 3D printed parts.

Keywords: 3D Printing, pressure vessels, interlayer bonding, controlled heat

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Authors: Chayanon Boonyuid

Abstract:

This paper experiments the effects of low-density polyethylene (LDPE) on the structural strength and permeability of hot-mix-asphalt (HMA) pavements. Different proportions of bitumen (4%, 4.5%, 5%, 5.5% and 6% of total aggregates) and plastic (5%, 10% and 15% of bitumen) contents in HMA mixtures were investigated to estimate the optimum mixture of bitumen and plastic in HMA pavement with long-term performance. Marshall Tests and Falling Head Tests were performed to experiment the structure strength and permeability of HMA mixtures with different percentages of plastic materials and bitumen. The laboratory results show that the optimum binder content was 5.5% by weight of aggregates with higher contents of plastic materials, increase structural stability, reduce permanent deformation, increase ductility, and improve fatigue life of HMA pavements. The use of recycled plastic shopping bags can reduce the use of bitumen content by 0.5% - 1% in HMA mixtures resulting in cheaper material costs with better long-term performance. The plastic materials increase the impermeability of HMA pavements. This study has two-fold contributions: optimum contents of both bitumen and plastic materials in HMA mixtures and the impacts of plastic materials on the permeability of HMA pavements.

Keywords: plastic bags, bitumen, structural strength, permeability

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Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

Abstract:

The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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Authors: Ben Chater, Jingbang Pan, Mark Evernden, Jie Wang

Abstract:

Traditional structural steel manufacturing routes normally produce prismatic members with flat plate elements. In these members, plate instability in the lowest buckling mode often dominates failure. It is proposed in the current study to use a new technology of metal 3D printing to print steel-plated elements with predefined imperfection patterns that can lead to higher modes of failure with increased buckling resistances. To this end, a numerical modeling program is carried out to explore various combinations of predefined buckling waves with different amplitudes in stainless steel square hollow section stub columns. Their stiffness, strength, and material consumption against the traditional structural steel members with the same nominal dimensions are assessed. It is found that depending on the slenderness of the plate elements; it is possible for an ‘imperfect’ steel member to achieve up to a 30% increase in strength with just a 3% increase in the material consumption. The obtained results shed some light on the significant potential of the new metal 3D printing technology in achieving unprecedented material efficiency and economical design in the future steel construction industry.

Keywords: 3D printing, additive manufacturing, buckling resistance, steel plate buckling, structural optimisation

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Authors: Wesam Darawsheh

Abstract:

Background: there are scarcity of studies done to investigate the level of knowledge and the level of awareness and perception of Jordanians about occupational therapy (OT). Aim: to investigate the level of awareness of lay people, clients receiving services and healthcare professionals of OT, identify the common misconceptions about OT, and to explore ways whereby the knowledge and awareness about OT can be increased. Methodology: a cross sectional design was employed in this study where a survey was distributed in the Northern, Southern, Western, Eastern provinces and the Middle (capital city: Amman) province of Jordan. The survey consisted of eight section and 61 questions that aims to investigate the demographics of participants, self evaluation concerning knowledge and awareness about OT, sources of knowledge about OT, the perception of the aims, fields of practice, OT settings, misconceptions about OT, and suggestion to improve knowledge and awareness about OT. Results: A total of 829 participants were enrolled in this study: 459 lay people, 155 clients who are currently receiving OT services, 215 healthcare professionals. About 57% of the participants did not hear about OT, and 48% of those who reported to hear about OT did not have sufficient knowledge about it. There are several misconceptions associated with OT. The statistical analysis was executed using IBM SPSS software, Version 22.0 (SPSS, Chicago, USA). Conclusion: it is the responsibility of OTRs to increase the knowledge and awareness about OT in Jordan. This is required for the profession to proliferate and to be given its status.

Keywords: knowledge, occupational therapy misconceptions, healthcare professionals, lay people, Jordan

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Authors: Chayanika Hazarika Bordoloi

Abstract:

This paper is an attempt to work on a highly inflectional language called Assamese. This is also one of the national languages of India and very little has been achieved in terms of computational research. Building a language processing tool for a natural language is not very smooth as the standard and language representation change at various levels. This paper presents inflectional suffixes of Assamese verbs and how the statistical tools, along with linguistic features, can improve the tagging accuracy. Conditional random fields (CRF tool) was used to automatically tag and train the text data; however, accuracy was improved after linguistic featured were fed into the training data. Assamese is a highly inflectional language; hence, it is challenging to standardizing its morphology. Inflectional suffixes are used as a feature of the text data. In order to analyze the inflections of Assamese word forms, a list of suffixes is prepared. This list comprises suffixes, comprising of all possible suffixes that various categories can take is prepared. Assamese words can be classified into inflected classes (noun, pronoun, adjective and verb) and un-inflected classes (adverb and particle). The corpus used for this morphological analysis has huge tokens. The corpus is a mixed corpus and it has given satisfactory accuracy. The accuracy rate of the tagger has gradually improved with the modified training data.

Keywords: CRF, morphology, tagging, tagset

Procedia PDF Downloads 194