Search results for: healthcare building

Authors: Norhayati Mat Wajid, Abdul Murad Zainal Abidin, Faiz Fadzil, Mohd Yusof Aizad Mukhtar

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One of the areas that present an opportunity to reduce the national carbon emission is the energy management of public buildings. To our present knowledge, there is no easy-to-use and centralized mechanism that enables the government to monitor the overall energy performance, as well as the carbon footprint, of Malaysia’s public buildings. Therefore, the Public Works Department Malaysia, or PWD, has developed a web-based energy performance reporting tool called JENOSYS (JKR Energy Online System), which incorporates a database of utility account numbers acquired from the utility service provider for analysis and reporting. For test case purposes, 23 buildings under PWD were selected and monitored for their monthly energy performance (in kWh), carbon emission reduction (in tCO₂eq) and utility cost (in MYR), against the baseline. This paper demonstrates the simplicity with which buildings without energy metering can be monitored centrally and the benefits that can be accrued by the government in terms of building energy disclosure and concludes with the recommendation of expanding the system to all the public buildings in Malaysia.

Keywords: energy-efficient buildings, energy management systems, government buildings, JENOSYS

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Authors: Büşra Elibol, İsmail Sait Soyer, Hamid Farrokh Ghatte

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The continuity of the structural and non-structural elements within the envelope of the buildings is one of the fundamental factors in buildings during seismic actions. This investigation aims to make a comparison between Van and İzmir earthquakes in terms of damage assessment of the various facades. A strong earthquake (magnitude 7.2) struck the city of Van in the east of Turkey on 23 October 2011, and similarly, another strong earthquake struck the city of İzmir (magnitude 6.9) in Turkey on 30 October 2020. This paper presents the damage assessment of the current facade systems from multi-story buildings in Van and İzmir, Turkey. This investigation covers the buildings greater than three stories in height, excluding most unreinforced masonry facades. Regarding a building that can have more than one facade system, any of the facade systems are considered individually. Observation of different kinds of damages in the facade is discussed and represented in terms of its performance level throughout the seismic actions. Furthermore, presenting the standard design guidelines (i.e., Turkish seismic design code) is required not only for designers but also for installers of facade systems.

Keywords: damage, earthquake, facade, structural element, seismic action

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Authors: Venkata Narayana Chejarla, Nafisa Parvez Shaik, Gopi Vara Prasad Marabathula, Deva Kumar Bejjam

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Yoga is an advanced, well-recognized method with roots in Indian philosophy. Yoga benefits both the body and the psyche. Yoga is a regular exercise that helps people relax and sleep better while also enhancing their balance, endurance, and concentration. Yoga can be learned in a variety of settings, including at home with the aid of books and the internet as well as in yoga studios with the guidance of an instructor. Self-learning does not teach the proper yoga poses, and doing them without the right instruction could result in significant injuries. We developed "Online Yoga Asana Trainer using Deep Learning" so that people could practice yoga without a teacher. Our project is developed using Tensorflow, Movenet, and Keras models. The system makes use of data from Kaggle that includes 25 different yoga poses. The first part of the process involves applying the movement model for extracting the 17 key points of the body from the dataset, and the next part involves preprocessing, which includes building a pose classification model using neural networks. The system scores a 98.3% accuracy rate. The system is developed to work with live videos.

Keywords: yoga, deep learning, movenet, tensorflow, keras, CNN

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Authors: Mohamed Haffar, Lombe Ngome Enongene, Mohammed Hamdan, Gbolahan Gbadamosi

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Despite the considerable body of literature investigating the influence of National Culture (NC) dimensions on consumer behaviour, there is a lack of studies comparing the influence of NC in Africa with Western European countries. This study is intended to fill the vacuum in knowledge by exploring how NC affects consumer buyer behavior in Nigeria and the United Kingdom. The primary data were collected through in depth, semi-structured interviews conducted with three groups of individuals: British students, Nigerian students in the United Kingdom, and Nigerian-based students. This approach and new frontier to analyze culture and consumer behaviour could help understand residual cultural threads of people (that are ingrained in their being) irrespective of exposure to other cultures. The findings of this study show that Nigerian and British consumers differ remarkably in cultural orientations such as symbols, values and psychological standpoints. This ultimately affects the choices made at every stage of the decision building process, and proves beneficial for international retail marketing.

Keywords: national culture, consumer behaviour, international business, Nigeria

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Authors: Shahab Hasani Nasab, Aran Aeini, Navid Kermanshahi

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In order to reduce road building costs and reduce environmental damage, recycled materials can be used instead of mineral materials in the production of asphalt mixtures. Today, in most parts of the world, cold recycled asphalt with bitumen emulsion, has acceptable results. However, Cold Recycled Asphalt have some deficiency such as stripping, thermal cracking, and rutting. This requires the addition of additives to reduce this deficiency of recycled pavement with emulsified asphalt. In this research, nano-alumina and emulsified asphalt were used to modify the properties of recycled asphalt mixtures according to the technical specifications and the operation of cold recycling. Marshall test methods, dynamic creep test, and resiliency modulus test has been used to obtain the nano-alumina’s effects on asphalt mixture properties. The results show that the addition of nano-alumina would reduce the Marshall stability in samples but increases the rutting resistance. The resiliency modulus increases significantly with this additive.

Keywords: cold asphalt, cold recycling, nano-alumina, dynamic creep, bitumen emulsion

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Authors: Carlos A. Domínguez Torres, Antonio Domínguez Delgado

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In this work we study the thermodynamic behavior of some ventilated facades under summer operating conditions in Southern Spain. Under these climatic conditions, indoor comfort implies a high energetic demand due to high temperatures that usually are reached in this season in the considered geographical area. The aim of this work is to determine if during summer operating conditions in Southern Spain, ventilated façades provide some energy saving compared to the non-ventilated façades and to deduce their behavior patterns in terms of energy efficiency. The modeling of the air flow in the channel has been performed by using Navier-Stokes equations for thermodynamic flows. Numerical simulations have been carried out with a 2D Finite Element approach. This way, we analyze the behavior of ventilated façades under different weather conditions as variable wind, variable temperature and different levels of solar irradiation. CFD computations show that the combined effect of the shading of the external wall and the ventilation by the natural convection into the air gap achieve a reduction of the heat load during the summer period. This reduction has been evaluated by comparing the thermodynamic performances of two ventilated and two unventilated façades with the same geometry and thermophysical characteristics.

Keywords: passive cooling, ventilated façades, energy-efficient building, CFD, FEM

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Authors: Yun Zhang, Zhu Wang

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Renewing ancient residential areas is an integral part of the sustainable development of modern cities. Compared with a metropolis, the old areas of small and medium-sized cities is more complicated to update, as the spatial form is more fragmented. In this context, the author takes as the research object, the ancient town of Changshu City, which is a small city representative in China with a history of more than 1,200 years. Through the analysis of urban research and update projects, the spatial evolution characteristics and renewal strategies of small ancient urban settlements are studied. On this basis, it is proposed to protect the residential area from the perspective of integrity and sustainability, strengthen the core public part, control the district building, and reshape the important interface. Renewing small and medium-sized urban areas should respect the rhythm of their own urban development and gradually complete the update, not blindly copying the experience of large cities.

Keywords: ancient residential area, Changshu, city renewal strategy, small and medium-sized cities

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Authors: Fu-Pei Hsiao, Fung-Chung Tu, Chien-Kuo Chiu

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In this work, to develop a method for detailed assesses of post-earthquake seismic performance for RC buildings in Taiwan, experimental data for several column specimens with various failure modes (flexural failure, flexural-shear failure, and shear failure) are used to derive reduction factors of seismic capacity for specified damage states. According to the damage states of RC columns and their corresponding seismic reduction factors suggested by experimental data, this work applies the detailed seismic performance assessment method to identify the seismic capacity of earthquake-damaged RC buildings. Additionally, a post-earthquake emergent assessment procedure is proposed that can provide the data needed for decision about earthquake-damaged buildings in a region with high seismic hazard. Finally, three actual earthquake-damaged school buildings in Taiwan are used as a case study to demonstrate application of the proposed assessment method.

Keywords: seismic assessment, seismic reduction factor, residual seismic ratio, post-earthquake, reinforced concrete, building

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Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

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Authors: Faramarz Khoshnoudian, Saeed Vosoughiyan

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The main goal of this article is to clarify the soil-structure interaction (SSI) effects on the seismic performance of steel moment resisting frame buildings which are rested on soft soil and equipped with viscous fluid dampers (VFDs). For this purpose, detailed structural models of a ten-story SMRF with VFDs excluding and including the SSI are constructed first. In order to simulate the dynamic response of the foundation, in this paper, the simple cone model is applied. Then, the nonlinear time-history analysis of the models is conducted using three kinds of earthquake excitations with different intensities. The analysis results have demonstrated that the SSI effects on the seismic performance of a structure equipped with VFDs and supported by rigid foundation on soft soil need to be considered. Also VFDs designed based on rigid foundation hypothesis fail to achieve the expected seismic objective while SSI goes into effect.

Keywords: nonlinear time-history analysis, soil-structure interaction, steel moment resisting frame building, viscous fluid dampers

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Authors: Mohamed S. Selim, Nesreen A. Fatthallah, Shimaa A. Higazy, Zhifeng Hao, Xiang Chen

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After the prohibition of tin-based fouling-prevention coatings in 2003, the researchers were directed toward eco-friendly coatings. Because of their nonstick, environmental, and economic benefits, foul-release nanocoatings have received a lot of attention. They use physical anti-adhesion terminology to deter any fouling attachment.Natural bioinspired surfaces have micro/nano-roughness and low surface free energy features, which may inspire the design of dynamic antifouling coatings. Graphene-based nanocomposite surfaces were designed to combat marine-fouling adhesion with ecological as well as eco-friendly effects rather than biocidal solutions. Polymer–graphenenanofiller hybrids are a novel class of composite materials in fouling-prevention applications. The controlled preparation of nanoscale orientation, arrangement, and direction along the composite building blocks would result in superior fouling prohibition. This work representsfoul-release nanocomposite top coats for marine coating applications with superhydrophobicity, surface inertness against fouling adherence, cost-effectiveness, and increased lifetime.

Keywords: foul-release nanocoatings, graphene-based nanocomposite, polymer, nanofillers

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Authors: Fawzi Srairi, Abderrahmane Dib

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Recently, the desire for a self-powered micro and nanodevices has attracted a great interest of using sustainable energy sources. Further, the ultimate goal of nanogenerator is to harvest energy from the ambient environment in which a self-powered device based on these generators is needed. With the development of nanogenerator-based circuits design and optimization, the building of new device simulator is necessary for the study and the synthesis of electromechanical parameters of this type of models. In the present article, both numerical modeling and optimization of piezoelectric nanogenerator based on zinc oxide have been carried out. They aim to improve the electromechanical performances, robustness, and synthesis process for nanogenerator. The proposed model has been developed for a systematic study of the nanowire morphology parameters in stretching mode. In addition, heuristic optimization technique, namely, particle swarm optimization has been implemented for an analytic modeling and an optimization of nanogenerator-based process in stretching mode. Moreover, the obtained results have been tested and compared with conventional model where a good agreement has been obtained for excitation mode. The developed nanogenerator model can be generalized, extended and integrated into simulators devices to study nanogenerator-based circuits.

Keywords: electrical potential, heuristic algorithms, numerical modeling, nanogenerator

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Authors: R. Herscu-Kluska

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The rise of the flipped or inverted classroom meet the conceptual needs of our time. The evidence of increased student satisfaction and course grades improvement promoted the flipped learning approach. Due to the successful outcomes of the inverted classroom, the flipped learning became a pedagogy and educational rising strategy among all education sciences. The aim of this study is to analyze the effect of flipped classroom on higher order learning in chemistry courses since it has been suggested that in higher education courses, class time should focus on knowledge application. The results of this study indicate improving meta-cognitive thinking and learning skills. The students showed better ability to cope with higher order learning assignments during the actual class time, using inverted classroom strategy. These results suggest that flipped learning can be used as an effective pedagogy and educational strategy for developing higher order thinking skills, proved to contribute to building lifelong learning.

Keywords: chemistry education, flipped classroom, flipped learning, inverted classroom, science education

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Authors: Qian Zaijian

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E-government is one of the hot issues in the current academic research of public policy and management. As the organic integration of information and communication technology (ICT) and public administration, e-government is one of the most important areas in contemporary information society. Policy information system is a basic subsystem of public policy system, its operation affects the overall effect of the policy process or even exerts a direct impact on the operation of a public policy and its success or failure. The basic principle of its operation is information collection, processing, analysis and release for a specific purpose. The function of E-government for public policy information system lies in the promotion of public access to the policy information resources, information transmission through e-participation, e-consultation in the process of policy analysis and processing of information and electronic services in policy information stored, to promote the optimization of policy information systems. However, due to many factors, the function of e-government to promote policy information system optimization has its practical limits. In the building of E-government in our country, we should take such path as adhering to the principle of freedom of information, eliminating the information divide (gap), expanding e-consultation, breaking down information silos and other major path, so as to promote the optimization of public policy information systems.

Keywords: China, e-consultation, e-democracy, e-government, e-participation, ICTs, public policy information systems

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Authors: Kehabtimer Shiferaw Kotiso, Getachew Hailemariam, Abiy Seifu Estifanos

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Introduction: Despite the highest share of low birth weight (LBW) for neonatal mortality and morbidity, predicting births with LBW for better intervention preparation is challenging. This study aims to predict LBW using a dataset encompassing 53,637 birth cohorts collected from 36 primary hospitals across seven regions in Ethiopia from February 2022 to June 2024. Methods: We identified ten explanatory variables related to maternal and neonatal characteristics, including maternal education, age, residence, history of miscarriage or abortion, history of preterm birth, type of pregnancy, number of livebirths, number of stillbirths, antenatal care frequency, and sex of the fetus to predict LBW. Using WEKA 3.8.2, we developed and compared seven machine learning algorithms. Data preprocessing included handling missing values, outlier detection, and ensuring data integrity in birth weight records. Model performance was evaluated through metrics such as accuracy, precision, recall, F1-score, and area under the Receiver Operating Characteristic curve (ROC AUC) using 10-fold cross-validation. Results: The results demonstrated that the decision tree, J48, logistic regression, and gradient boosted trees model achieved the highest accuracy (94.5% to 94.6%) with a precision of 93.1% to 93.3%, F1-score of 92.7% to 93.1%, and ROC AUC of 71.8% to 76.6%. Conclusion: This study demonstrates the effectiveness of machine learning models in predicting LBW. The high accuracy and recall rates achieved indicate that these models can serve as valuable tools for healthcare policymakers and providers in identifying at-risk newborns and implementing timely interventions to achieve the sustainable developmental goal (SDG) related to neonatal mortality.

Keywords: low birth weight, machine learning, classification, neonatal mortality, Ethiopia

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Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

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Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

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Authors: Ali Etemadi, Polat H. Gulkan

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The drift spectrum derived through the continuous shear-beam and wave propagation theory is known to be useful appliance to measure of the demand of pulse like near field ground motions on building structures. As regards, many of old frame buildings with poor or non-ductile column elements, pass the elastic limits and blurt the post yielding hysteresis degradation responses when subjected to such impulsive ground motions. The drift spectrum which, is based on a linear system cannot be predicted the overestimate drift demands arising from inelasticity in an elastic plastic systems. A simple procedure to estimate the drift demands in shear-type frames which, respond over the elastic limits is described and effect of hysteresis degradation behavior on seismic demands is clarified. Whereupon the modification factors are proposed to incorporate the hysteresis degradation effects parametrically. These factors are defined with respected to the linear systems. The method can be applicable for rapid assessment of existing poor detailed, non-ductile buildings.

Keywords: drift spectrum, shear-type frame, stiffness and strength degradation, pinching, smooth hysteretic model, quasi static analysis

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Authors: Lam Hong Lan, Gabor Sarlos

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It is hard to search for best practices in promotion for local fashion brands in Vietnam as the industry is still very young. Local fashion start-ups have grown quickly in the last five years, thanks in part to the internet and social media. However, local designer/owners can face a huge challenge when competing with international brands in the Vietnamese market – and few local case studies are available for guidance. In response, this paper studied how local small- to medium-sized enterprises (SMEs) promote to their target customers in order to compete with international brands. Knowledge of both successful and unsuccessful approaches generated by this study is intended to both contribute to the academic literature on local fashion in Vietnam as well as to help local designers to learn from and improve their brand-building strategy. The primary study featured qualitative data collection via semi-structured depth interviews. Transcription and data analysis were conducted manually in order to identify success factors that local brands should consider as part of their promotion strategy. Purposive sampling of SMEs identified five designers in Ho Chi Minh City (the biggest city in Vietnam) and three designers in Hanoi (the second biggest) as interviewees. Participant attributes included: born in the 1980s or 1990s; familiar with internet and social media; designer/owner of a successful local fashion brand in the key middle market and/or mass market segments (which are crucial to the growth of local brands). A secondary study was conducted using social listening software to gather further qualitative data on what were considered to be successful or unsuccessful approaches to local fashion brand promotion on social media. Both the primary and secondary studies indicated that local designers had maximized their promotion budget by using owned media and earned media instead of paid media. Findings from the qualitative interviews indicate that internet and social media have been used as effective promotion platforms by local fashion start-ups. Facebook and Instagram were the most popular social networks used by the SMEs interviewed, and these social platforms were believed to offer a more affordable promotional strategy than traditional media such as TV and/or print advertising. Online stores were considered an important factor in helping the SMEs to reach customers beyond the physical store. Furthermore, a successful online store allowed some SMEs to reduce their business rental costs by maintaining their physical store in a cheaper, less central city area as opposed to a more traditional city center store location. In addition, the small comparative size of the SMEs allowed them to be more attentive to their customers, leading to higher customer satisfaction and rate of return. In conclusion, this study found that these kinds of cost savings helped the SMEs interviewed to focus their scarce resources on producing unique, high-quality collections in order to differentiate themselves from international brands. Facebook and Instagram were the main platforms used for promotion and brand-building. The main challenge to this promotion strategy identified by the SMEs interviewed was to continue to find innovative ways to maximize the impact of a limited marketing budget.

Keywords: Vietnam, SMEs, fashion brands, promotion, marketing, social listening

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Authors: Tamas Hartvanyi, Zoltan Andras Nagy, Miklos Szabo

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The dynamic and static capacity are two opposing aspect of warehouse design. Static capacity optimization aims to maximize the space-usage for goods storing, while dynamic capacity needs more free place to handling them. They are opposing by the building structure and the area utilization. According to Pareto principle: the 80% of the goods are the 20% of the variety. From the origin of this statement, it worth to store the big amount of same products by fulfill the space with minimal corridors, meanwhile the rest 20% of goods have the 80% variety of the whole range, so there is more important to be fast-reachable instead of the space utilizing, what makes the space fulfillment numbers worse. The warehouse design decisions made in present practice by intuitive and empiric impressions, the planning method is formed to one selected technology, making this way the structure of the warehouse homogeny. Of course the result can’t be optimal for the inhomogeneous demands. A new innovative model based on our research will be introduced in this paper to describe the technic capacities, what makes possible to define optimal cluster of technology. It is able to optimize the space fulfillment and the dynamic operation together with this cluster application.

Keywords: warehouse, warehouse capacity, warehouse design method, warehouse optimization

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Authors: M. Bilal Ishfaq, Adnan N. Qureshi

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COVID-19 is the most infectious disease these days, it was first reported in Wuhan, the capital city of Hubei in China then it spread rapidly throughout the whole world. Later on 11 March 2020, the World Health Organisation (WHO) declared it a pandemic. Since COVID-19 is highly contagious, it has affected approximately 219M people worldwide and caused 4.55M deaths. It has brought the importance of accurate diagnosis of respiratory diseases such as pneumonia and COVID-19 to the forefront. In this paper, we propose a hybrid approach for the automated detection of COVID-19 using medical imaging. We have presented the hybridization of manually extracted and convolutional features. Our approach combines Haralick texture features and convolutional features extracted from chest X-rays and CT scans. We also employ a minimum redundancy maximum relevance (MRMR) feature selection algorithm to reduce computational complexity and enhance classification performance. The proposed model is evaluated on four publicly available datasets, including Chest X-ray Pneumonia, COVID-19 Pneumonia, COVID-19 CTMaster, and VinBig data. The results demonstrate high accuracy and effectiveness, with 0.9925 on the Chest X-ray pneumonia dataset, 0.9895 on the COVID-19, Pneumonia and Normal Chest X-ray dataset, 0.9806 on the Covid CTMaster dataset, and 0.9398 on the VinBig dataset. We further evaluate the effectiveness of the proposed model using ROC curves, where the AUC for the best-performing model reaches 0.96. Our proposed model provides a promising tool for the early detection and accurate diagnosis of COVID-19, which can assist healthcare professionals in making informed treatment decisions and improving patient outcomes. The results of the proposed model are quite plausible and the system can be deployed in a clinical or research setting to assist in the diagnosis of COVID-19.

Keywords: COVID-19, feature engineering, artificial neural networks, radiology images

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Authors: Fatemeh Sadat Sharifi, A. A. Bidokhti, M. Ezam, F. Ahmadi Givi

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This study focuses on the tidal oscillation and its speed to create a general pattern in seas. The purpose of the analysis is to find out the amplitude and phase for several important tidal components. Therefore, Regional Ocean Models (ROMS) was rendered to consider the correlation and accuracy of this pattern. Finding tidal harmonic components allows us to predict tide at this region. Better prediction of these tides, making standard platform, making suitable wave breakers, helping coastal building, navigation, fisheries, port management and tsunami research. Result shows a fair accuracy in the SSH. It reveals tidal currents are highest in Hormuz Strait and the narrow and shallow region between Kish Island. To investigate flow patterns of the region, the results of limited size model of FVCOM were utilized. Many features of the present day view of ocean circulation have some precedent in tidal and long- wave studies. Tidal waves are categorized to be among the long waves. So that tidal currents studies have indeed effects in subsequent studies of sea and ocean circulations.

Keywords: barotropic tide, FVCOM, numerical model, OTPS, ROMS

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Authors: Mohammadmehdi Torfehnejad, Serhan Sensoy

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Many structures sustain damage during a mainshock earthquake but undergo severe damage under aftershocks following the mainshock. Past researches have studied aftershock effects through different methodologies, but few structural systems have been evaluated for these effects. Collapse capacity and energy absorption mechanism of the Special Steel Moment Frame (SSMF) system is evaluated in this study, under aftershock earthquakes when prior damage is caused by the mainshock. A twenty-story building is considered in assessing the residual collapse capacity and energy absorption mechanism under aftershock excitation. In addition, various levels of mainshock damage are considered and reflected through two different response parameters. Aftershock collapse capacity is estimated using incremental dynamic analysis (IDA) applied following the mainshock. The study results reveal that the collapse capacity of high-rise structures undergoes a remarkable reduction for high level of mainshock damage. The energy absorption in the columns is decreased by increasing the level of mainshock damage.

Keywords: seismic collapse, mainshock-aftershock effect, incremental dynamic analysis, energy absorption

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasy

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Energy consumption schedule (ECS) technique shifts usage of loads from on peak hours and redistributes them throughout the day according to residents’ operating time preferences. This technique is used as form of indirect control from utility to improve the load curve and hence its load factor and reduce customer’s total electric bill as well. Similarly, load shifting technique achieves ECS purposes but as direct control form applied from utility. In this paper, ECS is simulated twice as optimal constrained mathematical formula, solved by using CVX program in MATLAB^® R2013b. First, it is utilized for single residential building with ten apartments to determine max allowable energy consumption per hour for each residential apartment. Then, it is used for single apartment with number of shiftable domestic devices, where operating schedule is deduced using previous simulation output results as constraints. The paper ends by giving differences between ECS technique and load shifting technique via literature and simulation. Based on results assessment, it will be shown whether using ECS or load shifting is more beneficial to both customer and utility.

Keywords: energy consumption schedule, load shifting, comparison, demand side mangement

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Authors: Lori Timmis

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The COVID-19 pandemic precipitated significant organizational change in employee turnover, retirements, and burnout exacerbated by enrollment declines in higher education, especially community colleges. To counter this downturn, community college leaders must thoughtfully examine meaningful work opportunities to retain an engaged and productive workforce. Higher education led fully remote teams during the pandemic, which highlighted the benefits and weaknesses of building and leading remote teams. Hybrid remote teams offer possibility to reimagine community college structures, though leading remote teams requires specific e-leadership competencies. This paper examines the literature of studies on e-leadership conducted during the pandemic and from several higher education studies, pre-pandemic, against an e-leadership competency framework. The e-leadership studies conducted pre-pandemic and from the pandemic complement the e-leadership competency framework, comprising six e-leadership competencies performed via information technology communications, which provides community college (and higher education) leaders to consider hybrid remote team structures and the necessary leadership skills to lead hybrid remote teams.

Keywords: community college, e-leadership, great resignation, hybrid remote teams

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Authors: Fatima Taqi, Abrar Alanzi

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Objectives: The objective of this study is to determine and assess the level of knowledge and attitudes of dental patients attending Kuwait University Dental Clinics (KUDC) regarding the infection control protocols practiced in the clinic. The results would highlight the importance of conducting awareness campaigns in the community to promote good oral healthcare in Kuwait. Materials and Methods: A cross-sectional descriptive survey was carried out among dental patients attending KUDC. A structured questionnaire, in both Arabic and English languages, was used for data collection about the socio-demographic characteristics, knowledge about the dental cross-infection, and attitudes and self-reported practices regarding infection transmission and control in dentistry. Results: A response rate of 80% (202/250) was reported. 47% of respondents had poor knowledge about dental infection transmission, and only 19.8% had satisfactory knowledge. Female participants obtained a higher satisfactory score (14.3%) compared to males (5.5%). Patients with a university degree or higher education had a better level of knowledge compared to patients with a lower educational level (p < 0.05). The majority of participants agreed that the dentist should wear gloves (95.5%), masks (89.6%), safety glasses (70.3%), and gowns (84.7%). Many patients believed that the protection measures are mainly to stop the infection transmission from patient to patient via the dentist. Half of the participants would ask if the instruments are sterilized and might accept treatment from non-vaccinated dentists. Conclusions: Many dental patients attending KUDC have obtained poor knowledge scores regarding infection transmission in the dental clinic. The educational level was significantly associated with their level of knowledge. An overall positive attitude was reported regarding the infection control protocols practiced in the dental clinic. Raising awareness among dental patients about dental infection transmission and protective measures is of utmost importance.

Keywords: dental infection, knowledge, dental patients, infection control

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Authors: Yuko Tomoto

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The purpose of this research is to examine the assumption that female bilingual speakers more often change the way they talk or think depending on the language they use compared with male bilingual speakers. The author collected data through questionnaires on 241 bilingual speakers. Also, in-depth interview surveys were conducted with 13 Japanese/English bilingual speakers whose native language is Japanese and 16 English/Japanese bilingual speakers whose native language is English. The results indicate that both male and female bilingual speakers are more or less influenced consciously and unconsciously by the language they use, as well as by the background cultural values of each language. At the same time, it was found that female speakers are much more highly affected by the language they use, its background culture and also by the interlocutors they were talking to. This was probably due to the larger cultural expectations on women. Through conversations, speakers are not only conveying a message but also attempting to express who they are, and what they want to be like. In other words, they are constantly building up and updating their own identities by choosing the most appropriate language and descriptions to express themselves in the dialogues. It has been claimed that the images of ideal L2 self could strongly motivate learners. The author hopes to make the best use of the fact that bilingual speakers change their presence depending on the language they use, in order to motivate Japanese learners of English, especially female learners from the viewpoint of finding their new selves in English.

Keywords: cultural influence, gender expectation, language learning, L2 self

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Authors: Elizabeth Mahenge

Abstract:

Unemployment is a problem that face many graduates all over the world. Every year universities in many parts of the world produce graduates who are looking for an employment. Swahili, a Bantu language originated in East African coast, can be used as an avenue for youth’s employment in South Africa. This paper helps youth to know about job opportunities available through teaching Swahili language. The objective of this paper is capacity building to youths to be teachers of Swahili and be ready to compete in the marketplace. The methodology was through two weeks online training on how to teach Swahili as a foreign language. The communicative approach and task-based approach were used.  Participants to this training were collected through a WhatsApp group advertisement about “short training for Swahili teachers for foreigners”. A total number of 30 participants registered but only 11 attended the training. Training was online via zoom. The contribution of this paper is that by being fluent in Swahili one would benefit with teaching job opportunities anywhere in the world. Hence the problem of unemployment among the youths would be reduced as they can employ themselves or being employed in academic institutions anywhere in the world. The paper calls for youths in South Africa to opt for Swahili language courses to be trained and become experts in the teaching Swahili as a foreign language.

Keywords: foreign language, linguistic market, Swahili, employment

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Authors: Joshna Rani S., Ahmadi Banu

Abstract:

Artificial Intelligence (AI) has a significant task to carry out in the medical care contributions of things to come. As AI, it is the essential capacity behind the advancement of accuracy medication, generally consented to be a painfully required development in care. Albeit early endeavors at giving analysis and treatment proposals have demonstrated testing, we anticipate that AI will at last dominate that area too. Given the quick propels in AI for imaging examination, it appears to be likely that most radiology, what's more, pathology pictures will be inspected eventually by a machine. Discourse and text acknowledgment are now utilized for assignments like patient correspondence and catch of clinical notes, and their utilization will increment. The best test to AI in these medical services areas isn't regardless of whether the innovations will be sufficiently skilled to be valuable, but instead guaranteeing their appropriation in day by day clinical practice. For far reaching selection to happen, AI frameworks should be affirmed by controllers, coordinated with EHR frameworks, normalized to an adequate degree that comparative items work likewise, instructed to clinicians, paid for by open or private payer associations, and refreshed over the long haul in the field. These difficulties will, at last, be survived, yet they will take any longer to do as such than it will take for the actual innovations to develop. Therefore, we hope to see restricted utilization of AI in clinical practice inside 5 years and more broad use inside 10 years. It likewise appears to be progressively evident that AI frameworks won't supplant human clinicians for a huge scope, yet rather will increase their endeavors to really focus on patients. Over the long haul, human clinicians may advance toward errands and work plans that draw on remarkably human abilities like sympathy, influence, and higher perspective mix. Maybe the lone medical services suppliers who will chance their professions over the long run might be the individuals who will not work close by AI

Keywords: artificial intellogence, health care, breast cancer, AI applications

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Authors: Arun Moorthy

Abstract:

Quantum computing promises to provide algorithmic speedups for a number of tasks; however, similar to classical computing, effective error-correcting codes are needed. Current quantum computers require costly equipment to control each particle, so having fewer particles to control is ideal. Although traditional quantum computers are built using qubits (2-level systems), qudits (more than 2-levels) are appealing since they can have an equivalent computational space using fewer particles, meaning fewer particles need to be controlled. Currently, qudit quantum error-correction codes are available for different level qudit systems; however, these codes have sometimes overly specific constraints. When building a qudit system, it is important for researchers to have access to many codes to satisfy their requirements. This project addresses two methods to increase the number of quantum error correcting codes available to researchers. The first method is generating new codes for a given set of parameters. The second method is generating new error-correction codes by using existing codes as a starting point to generate codes for another level (i.e., a 5-level system code on a 2-level system). So, this project builds a website that researchers can use to generate new error-correction codes or codes based on existing codes.

Keywords: qudit, error correction, quantum, qubit

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Authors: Tzu-Jung Tseng, Pei-Hsuen Han, Tsung-Hsueh Lu

Abstract:

Background: Ensuring patients with ST-elevation myocardial infarction (STEMI) access to hospitals that could perform percutaneous coronary intervention (PCI) in time is an important concern of healthcare managers. One commonly used the method to assess the coverage of population access to PCI hospital is the use GIS-estimated linear distance (crow's fly distance) between the district centroid and the nearest PCI hospital. If the distance is within a given distance (such as 20 km), the entire population of that district is considered to have appropriate access to PCI. The premise of using district centroid to estimate the coverage of population resident in that district is that the people live in the district are evenly distributed. In reality, the population density is not evenly distributed within the administrative district, especially in rural districts. Fortunately, the Taiwan government released basic statistical area (on average 450 population within the area) recently, which provide us an opportunity to estimate the coverage of population access to PCI services more accurate. Objectives: We aimed in this study to compare the population covered by a give PCI hospital according to traditional administrative district versus basic statistical area. We further examined if the differences between two geographic units used would be larger in a rural area than in urban area. Method: We selected two hospitals in Tainan City for this analysis. Hospital A is in urban area, hospital B is in rural area. The population in each traditional administrative district and basic statistical area are obtained from Taiwan National Geographic Information System, Ministry of Internal Affairs. Results: Estimated population live within 20 km of hospital A and B was 1,515,846 and 323,472 according to traditional administrative district and was 1,506,325 and 428,556 according to basic statistical area. Conclusion: In urban area, the estimated access population to PCI services was similar between two geographic units. However, in rural areas, the access population would be overestimated.

Keywords: accessibility, basic statistical area, modifiable areal unit problem (MAUP), percutaneous coronary intervention (PCI)

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