Search results for: priority class

Authors: Musa Sekamatte

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Background: Zoonotic diseases continue to be a public health burden in countries around the world. Uganda is especially vulnerable due to its location, biodiversity, and population. Given these concerns, the Ugandan government in collaboration with the Global Health Security Agenda conducted a zoonotic disease prioritization workshop to identify zoonotic diseases of concern to multiple Ugandan ministries. Materials and Methods: The One Health Zoonotic Disease Prioritization tool, developed by the U.S. Centers for Disease Control and Prevention (CDC), was used for prioritization of zoonotic diseases in Uganda. Workshop participants included voting members representing human, animal, and environmental health ministries as well as key partners who observed the workshop. Over 100 articles describing characteristics of these zoonotic diseases were reviewed for the workshop. During the workshop, criteria for prioritization were selected, and questions and weights relevant to each criterion were determined. Next steps for multi-sectoral engagement for the prioritized zoonoses were then discussed. Results: 48 zoonotic diseases were considered during the workshop. Criteria selected to prioritize zoonotic diseases in order of importance were (1) severity of disease in humans in Uganda, (2) availability of effective control strategies, (3) potential to cause an epidemic or pandemic in humans or animals, (4) social and economic impacts, and (5) bioterrorism potential. Seven zoonotic diseases were identified as priorities for Uganda: anthrax, zoonotic influenza viruses, viral hemorrhagic fevers, brucellosis, African trypanosomiasis, plague, and rabies. Discussion: One Health approaches and multi-sectoral collaborations are crucial in the surveillance, prevention, and control strategies for zoonotic diseases. Uganda used such an approach to identify zoonotic diseases of national concern. Identifying these priority diseases enables the National One Health Platform and the Zoonotic Disease Coordinating Office to address the diseases in the future.

Keywords: national one health platform, zoonotic diseases, multi-sectoral, severity

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Authors: Malik Ghulam Behlol, Alison Fox, Faiza Masood, Sabiha Arshad

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This paper explores the barriers to the application of learning-supportive assessment at teaching practicum while investigating the role of university teachers (UT), cooperative teachers (CT), prospective teachers ( PT) and heads of the practicum schools (HPS) in the selected universities of Pakistan and the UK. It is a qualitative case study and data were collected through the lesson observation of UT in the pre-service teacher education setting and PT in practicum schools. Interviews with UT, HPS, and Focus Group Discussions with PT were conducted too. The study has concluded that as compared to the UK counterpart, PT in Pakistan faces significant barriers in applying learning-supportive assessment in the school practicum settings because of large class sizes, lack of institutionalised collaboration between universities and schools, poor modelling of the lesson, ineffective feedback practices, lower order thinking assignments, and limited opportunities to use technology in school settings.

Keywords: assessment, pre-service teacher education, theory-practice gap, teacher education

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Authors: V. Vsevolozhskaia

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Since 1990, energy-efficient development concepts have constituted both a turning point in civil engineering and a challenge for an environmentally friendly future. Energy and water currently play an essential role in the sustainable economic growth of the world in general and Russia in particular: the efficiency of the water supply system is the second most important parameter for energy consumption according to the British assessment method, while the water-energy nexus has been identified as a focus for accelerating sustainable growth and developing effective, innovative solutions. The activities considered in this study were aimed at organizing and executing the renovation of the property in residential buildings located in St. Petersburg, specifically buildings with local or federal historical heritage status under the control of the St. Petersburg Committee for the State Inspection and Protection of Historic and Cultural Monuments (KGIOP) and UNESCO. Even after reconstruction, these buildings still fall into energy efficiency class D. Russian Government Resolution No. 87 on the structure and required content of project documentation contains a section entitled ‘Measures to ensure compliance with energy efficiency and equipment requirements for buildings, structures, and constructions with energy metering devices’. Mention is made of the need to install collectors and meters, which only calculate energy, neglecting the main purpose: to make buildings more energy-efficient, potentially even energy efficiency class A. The least-explored aspects of energy-efficient technology in the Russian Federation remain the water balance and the possibility of implementing rain and meltwater collection systems. These modern technologies are used exclusively for new buildings due to a lack of government directive to create project documentation during the planning of major renovations and reconstruction that would include the collection and reuse of rainwater. Energy-efficient technology for rain and meltwater collection is currently applied only to new buildings, even though research has proved that using rainwater is safe and offers a huge step forward in terms of eco-efficiency analysis and water innovation. Where conservation is mandatory, making changes to protected sites is prohibited. In most cases, the protected site is the cultural heritage building itself, including the main walls and roof. However, the installation of a second water supply system and collection of rainwater would not affect the protected building itself. Water efficiency in St. Petersburg is currently considered only from the point of view of the installation that regulates the flow of the pipeline shutoff valves. The development of technical guidelines for the use of grey- and/or rainwater to meet the needs of residential buildings during reconstruction or renovation is not yet complete. The ideas for water treatment, collection and distribution systems presented in this study should be taken into consideration during the reconstruction or renovation of residential cultural heritage buildings under the protection of KGIOP and UNESCO. The methodology applied also has the potential to be extended to other cultural heritage sites in northern countries and lands with an average annual rainfall of over 600 mm to cover average toilet-flush needs.

Keywords: cultural heritage, energy efficiency, renovation, rainwater collection, reconstruction, water management, water supply

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Authors: Heny Hartono, Cecilia Titiek Murniati

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The pandemic has given teachers and students no other choice but having full online learning. In such an emergency situation as the time of the covid-19 pandemic, the application of LMS (Learner Management System) in higher education is the most reasonable solution for students and teachers. In fact, the online learning requires all elements of a higher education systems, including the human resources, infrastructure, and supporting systems such as the application, server, and stable internet connection. The readiness of the higher education institution in preparing the online system may secure those who are involved in the online learning process. It may also result in students’ self-efficacy in online learning. This research aimed to investigate how students perceive their self-efficacy in online English learning, especially in speaking classes which is considered as a productive language skill. This research collects qualitative data with narrative inquiry involving 25 students of speaking classes as the respondents. The results of this study show that students perceive their self-efficacy in speaking online classes as not very high.

Keywords: self-efficacy, online learning, speaking class, college students, e-learning

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Authors: Hadeer M. Sayed, Hesham E. El Deeb, Shereen A. Taie

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In the big data era, we are facing a diversity of datasets from different sources in different domains that describe a single life event. These datasets consist of multiple modalities, each of which has a different representation, distribution, scale, and density. Multimodal fusion is the concept of integrating information from multiple modalities in a joint representation with the goal of predicting an outcome through a classification task or regression task. In this paper, multimodal fusion techniques are classified into two main classes: model-agnostic techniques and model-based approaches. It provides a comprehensive study of recent research in each class and outlines the benefits and limitations of each of them. Furthermore, the audiovisual speech recognition task is expressed as a case study of multimodal data fusion approaches, and the open issues through the limitations of the current studies are presented. This paper can be considered a powerful guide for interested researchers in the field of multimodal data fusion and audiovisual speech recognition particularly.

Keywords: multimodal data, data fusion, audio-visual speech recognition, neural networks

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Authors: William Kwabena Nantwi

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This quantitative study investigates Creative Arts teachers' perceptions regarding the implementation of an Inclusive Creative Arts curriculum. The research employs a descriptive approach utilizing a 5-point Likert scale questionnaire comprising 15 items to gather data from Creative Arts educators. The Census with a disproportionate stratified sampling method was utilized to select 226 teachers from five educational circuits (Circuit A, B, C, D & E) within Offinso Municipality, Ghana. The findings indicate that most Creative Arts teachers hold a positive perception towards implementing an inclusive Creative Arts curriculum. Positive perceptions and attitudes among teachers are correlated with increased student engagement and participation in class activities. This study recommends organizing workshops and in-service training sessions focused on inclusive Creative Arts education for Creative Arts teachers. Additionally, it suggests that Colleges of Education and Universities responsible for teacher training integrate foundational courses in Creative Arts and Special Education into their primary education teacher preparation programs.

Keywords: perception, attitude, inclusive education, creative art, creative arts teachers, Ghana

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Authors: Christoph Linse, Thomas Martinetz

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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

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Authors: Penn P. Wu

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Recent advances in virtual reality (VR) technologies have made it possible for students to experience a virtual on-the-scene or virtual in-person observation of an educational event. In an experimental class, the author uses VR, particularly 360° videos, to virtually engage students in an event, through a wide spectrum of educational resources, such s a virtual “bystander.” Students were able to observe the event as if they were physically on site, although they could not intervene with the scene. The author will describe the adopted equipment, specification, and cost of building them as well as the quality of VR. The author will discuss (a) feasibility, effectiveness, and efficiency of using VR as a supplemental technology to teach college students and criteria and methodologies used by the authors to evaluate them; (b) barriers and issues of technological implementation; and (c) pedagogical practices learned through this experiment. The author also attempts to explore (a) how VR could provide an interactive virtual in-person learning experience; (b) how VR can possibly change traditional college education and online education; (c) how educators and balance six critical factors: cost, time, technology, quality, result, and content.

Keywords: learning with VR, virtual experience of learning, virtual in-person learning, virtual reality for education

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Authors: Ange Meghane Hakizimana, Landry Ndikuriyo

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Retention of employees in the hospitality industry is a recurrent agenda in the organization involving all the combined efforts to maintain the best available laborer. The general objective of this research is to assess the impact of effective employee retention strategies on the success of the hotel industry at Galileo Hotel, Huye District in Rwanda, for the period of 2019-2021. Herzberg Two Factor Theory and Equity Theory were used. The study adopted a descriptive research design. Descriptive research design allowed us to study the elements in their natural form without making any alterations to them. Secondary data and primary data and the data collected were sorted and entered into the statistical packages for social sciences for analysis (SPSS) version 26. Frequencies, descriptive statistics and percentages were used to analyze and establish extent to which employee retention strategies impact the success of the hotel industry of Rwanda and this was analyzed using regression and correlation analysis. The results revealed that employee training and development had an influence of 24.8% on the success of the hotel industry in Rwanda. According to the results of our study, the employee reward system contributes 20.7% to the success of the hotel industry in Rwanda, the value of t is 3.475 and this is greater than the standard t value score of 1.96, p-value is 0.002. Therefore the employee reward system has a great positive impact on the success of the hotel industry in Rwanda. The results also show that 15.7% of the success of the hospitality industry in Rwanda is due to the work environment of employees. With a t-value of 4.384 and a p-value of 0.000, the above statistics show a positive impact of the employees' working environment on success of the hospitality industry in Rwanda. A priority to the retention of their employees should be given by the hotel industry and its managers because it has already been proven that it is an effective approach to offering good customer service. In addition, employee retention reduces expenses associated with employee recruitment and turnover.

Keywords: success, hotel industry, training and development, employee reward system, employee work environment

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Authors: Muhammad Tufail, Jawad Hussain, Hammad Hussain, Imran Hafeez, Naveed Ahmad

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Road safety performance index is a composite index which combines various indicators of road safety into single number. Development of a road safety performance index using appropriate safety performance indicators is essential to enhance road safety. However, a road safety performance index in developing countries has not been given as much priority as needed. The primary objective of this research is to develop a general Road Safety Performance Index (RSPI) for developing countries based on the facility as well as behavior of road user. The secondary objectives include finding the critical inputs in the RSPI and finding the better method of making the index. In this study, the RSPI is developed by selecting four main safety performance indicators i.e., protective system (seat belt, helmet etc.), road (road width, signalized intersections, number of lanes, speed limit), number of pedestrians, and number of vehicles. Data on these four safety performance indicators were collected using observation survey on a 20 km road section of the National Highway N-125 road Taxila, Pakistan. For the development of this composite index, two methods are used: a) Principal Component Analysis (PCA) and b) Equal Weighting (EW) method. PCA is used for extraction, weighting, and linear aggregation of indicators to obtain a single value. An individual index score was calculated for each road section by multiplication of weights and standardized values of each safety performance indicator. However, Simple Average technique was used for weighting and linear aggregation of indicators to develop a RSPI. The road sections are ranked according to RSPI scores using both methods. The two weighting methods are compared, and the PCA method is found to be much more reliable than the Simple Average Technique.

Keywords: indicators, aggregation, principle component analysis, weighting, index score

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Authors: Edward W. Staley, Corban G. Rivera, Ashley J. Llorens

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Advances in reinforcement learning (RL) have resulted in recent breakthroughs in the application of artificial intelligence (AI) across many different domains. An emerging landscape of development environments is making powerful RL techniques more accessible for a growing community of researchers. However, most existing frameworks do not directly address the problem of learning in complex operating environments, such as dense urban settings or defense-related scenarios, that incorporate distributed, heterogeneous teams of agents. To help enable AI research for this important class of applications, we introduce the AI Arena: a scalable framework with flexible abstractions for distributed multi-agent reinforcement learning. The AI Arena extends the OpenAI Gym interface to allow greater flexibility in learning control policies across multiple agents with heterogeneous learning strategies and localized views of the environment. To illustrate the utility of our framework, we present experimental results that demonstrate performance gains due to a distributed multi-agent learning approach over commonly-used RL techniques in several different learning environments.

Keywords: reinforcement learning, multi-agent, deep learning, artificial intelligence

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Authors: Zainab A. Alaghbri, Labiba A., Esam A.

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Tuberculosis (TB) is the fourth leading cause of death in Yemen and is considered a major priority by the Ministry of Public Health. The war in Yemen has led to the emergence of one of the worst humanitarian crises in the world. These circumstances may lead to exacerbate the situation of tuberculosis. This study aims to describe the trend and incidence of TB in north and east governorates, Yemen 2019-2021 and provide recommendations for interventions. A descriptive analysis was conducted during July to September 2022. Data of TB cases were obtained from the national tuberculosis program as soft copy. The Data included the TB case collected and diagnosed during 2019-2021. The data contains the following variables: Sex, age, governorates, smear-positive cases, extra-pulmonary cases, and treatment outcomes. 16791 TB cases were notified for an overall case notification rate 65.5/100000 for all forms (smear positive and Extra-pulmonary), There was a slightly declined in 2020 and 2021 by 1%. Both the pulmonary smear positive and Extra pulmonary rates were slightly decreased from 8.8 to 7.7 and 13.5 to 12.8 / 100, 000 populations respectively. For Tuberculosis cases by type of patient, the incidence of extra-pulmonary was the highest (12,9, 11.3 and 12,2/100000) over the three years. However, the incidence of pulmonary failure was the lowest. The majority of cases were in the age group 25-34. The overall treatment success rate for smear-positive patients was 88%. Of the 627 patients with documented unsuccessful outcomes (e.g., failure, death, and default), 165 (23%) died, 52 (8.3%) failed treatment, and 410 (65%) defaulted. Overall, the magnitude of tuberculosis decreased over the periods reviewed. The proportion of Extra-pulmonary TB was the highest. The success rate achieved after treatment was below the levels established by the WHO End Tuberculosis Strategy (90%). Failure to complete treatment may be responsible for the low success rate. Monitoring and addressing the risk factors that were associated with treatment outcomes and duration may help improve the likelihood of achieving favorable outcomes among cases of smear-positive pulmonary TB.

Keywords: tuberculosis, trend, incidence, yemen

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Authors: A. E. Dumitriu

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The LHCb experiment is situated at one of the four points around CERN’s Large Hadron Collider, being a single-arm forward spectrometer covering 10 mrad to 300 (250) mrad in the bending (non-bending) plane, designed primarily to study particles containing b and c quarks. Each one of LHCb’s sub-detectors specializes in measuring a different characteristic of the particles produced by colliding protons, its significant detection characteristics including a high precision tracking system and 2 ring-imaging Cherenkov detectors for particle identification. The major two topics that I am currently concerned in are: the RIVET project (Robust Independent Validation of Experiment and Theory) which is an efficient and portable tool kit of C++ class library useful for validation and tuning of Monte Carlo (MC) event generator models by providing a large collection of standard experimental analyses useful for High Energy Physics MC generator development, validation, tuning and regression testing and V0 analysis for 2013 LHCb NoBias type data (trigger on bunch + bunch crossing) at √s=2.76 TeV.

Keywords: LHCb physics, RIVET plug-in, RIVET, CERN

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Authors: Tushar K. Routh

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If inputs are engineered in certain manners, they can influence deep neural networks’ (DNN) performances by facilitating misclassifications, a phenomenon well-known as adversarial attacks that question networks’ vulnerability. Recent studies have unfolded the relationship between vulnerability of such networks with their complexity. In this paper, the distinctive influence of additional convolutional layers at the decision boundaries of several DNN architectures was investigated. Here, to engineer inputs from widely known image datasets like MNIST, Fashion MNIST, and Cifar 10, we have exercised One Step Spectral Attack (OSSA) and Fast Gradient Method (FGM) techniques. The aftermaths of adding layers to the robustness of the architectures have been analyzed. For reasoning, separation width from linear class partitions and local geometry (curvature) near the decision boundary have been examined. The result reveals that model complexity has significant roles in adjusting relative distances from margins, as well as the local features of decision boundaries, which impact robustness.

Keywords: DNN robustness, decision boundary, local curvature, network complexity

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Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk

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The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.

Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression

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Authors: B. Suresh Reddy

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The over dependence on chemical fertilizers for nutrient management in crop production for the last few decades has led to several problems affecting soil health, environment and farmers themselves. Based on the field work done in 2012-13 with 1080 farmers of different size-classes in semi-arid regions of Uttar Pradesh, Jharkhand and Madhya Pradesh states of India, this paper reveals that the farmers in semi-arid regions of India are actively managing soil fertility and other soil properties through a wide range of practices that are based on local resources and knowledge. It also highlights the socio-economic web woven around these soil fertility management practices. This study highlights the contribution of organic matter by traditional soil fertility management practices in maintaining the soil health. Livestock has profound influence on the soil fertility enhancement through supply of organic manure. Empirical data of this study has clearly revealed how farmers’ soil fertility management options are being undermined by government policies that give more priority to chemical fertiliser-based strategies. Based on the findings it is argued that there should be a 'level playing field' for both organic and inorganic soil fertility management methods by promoting and supporting farmers in using organic methods. There is a need to provide credit to farmers for adopting his choice of soil fertility management methods which suits his socio-economic conditions and that best suits the long term productivity of soils. The study suggests that the government policies related to soil fertility management must be enabling, creating the conditions for development based more on locally available resources and local skills and knowledge. This will not only keep Indian soils in healthy condition but also support the livelihoods of millions of people, especially the small and marginal farmers.

Keywords: livestock, organic matter, small farmers, soil fertility

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Authors: Tomas Vampola, Michael Valášek

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On the basis of simulation-generated failure states of structural elements of a turboprop engine suitable for the busy-jet class of aircraft, an algorithm for early prediction of damage or reduction in functionality of structural elements of the engine is designed and verified with real data obtained at dynamometric testing facilities of aircraft engines. Based on an expanding database of experimentally determined data from temperature and pressure sensors during the operation of turboprop engines, this strategy is constantly modified with the aim of using the minimum number of sensors to detect an inadmissible or deteriorated operating mode of specific structural elements of an aircraft engine. The assembled algorithm for the early prediction of reduced functionality of the aircraft engine significantly contributes to the safety of air traffic and to a large extent, contributes to the economy of operation with positive effects on the reduction of the energy demand of operation and the elimination of adverse effects on the environment.

Keywords: detectability of malfunction, dynamometric testing, prediction of damage, turboprop engine

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Authors: Konrad Rejdak, Agnieszka Korchut, Sebastian Szklener, Urszula Skrobas, Justyna Gerlowska, Katarzyna Grabowska-Aleksandrowicz, Dorota Szczesniak-Stanczyk

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Introduction: Neurodegenerative diseases are frequently accompanied by loss and unwanted change in functional independence, social relationships, and economic circumstances. Currently, the achievements of social robots to date is being projected to improve multidimensional quality of life among people with cognitive impairment and others. Objectives: Identification of particular human needs in context of the changes occurring in course of neurodegenerative diseases. Methods: Based on the 110 surveys performed in Medical University of Lublin from medical staff, patients, and caregivers we made prioritization of the users' needs as: high, medium, and low. The issues included in the surveys concerned four aspects: user acceptance, functional requirements, design of the robotic assistant and preferred types of human-robot interaction. Results: We received completed questionnaires: 50 from medical staff, 30 from caregivers and 30 from potential users. Above 90% of the respondents from each of the three groups, accepted robotic assistant as a potential caregiver. High priority functional capability of assistive technology was to handle emergencies in a private home like recognizing life-threatening situations and reminding about medication intake. With reference to design of the robotic assistant, the majority of the respondent would like to have an anthropomorphic appearance with positive emotionally expressive face. The most important type of human-robot interaction was voice-operated system and by touchscreen. Conclusion: The results from our study might contribute to a better understanding of the system and users’ requirements for the development of a service robot intended to support patients with dementia.

Keywords: social robot, dementia, requirements, patients needs

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Authors: David Steven Rosenstein

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The widely accepted “Input Theory” of language acquisition proposes that language is basically acquired unconsciously through extensive exposure to all kinds of natural oral and written sources, especially those where the level of the input is slightly above the learner’s competence. As such, it implies that oral error correction by teachers in a classroom is unnecessary, a waste of time, and maybe even counterproductive. And yet, oral error correction by teachers in the classroom continues to be a very common phenomenon. While input theory advocates claim that such correction doesn’t work, interrupts a student’s train of thought, harms fluency, and may cause students embarrassment and fear, many teachers would disagree. They would claim that students know they make mistakes and want to be corrected in order to know they are improving, thereby encouraging students’ desire to keep studying. Moreover, good teachers can create a positive atmosphere where students will not be embarrassed or fearful. Perhaps now is the time to revisit oral error correction in the classroom and consider the results of research carried out long ago by the present speaker. The research indicates that oral error correction may be beneficial in many cases.

Keywords: input theory, language acquisition, teachers' corrections, recurrent errors

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Authors: Fatemeh Abbasi, Sahand Daneshvar

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Productivity is one of the essential goals of companies to improve performance, which as a strategy-oriented method, determines the basis of the company's economic growth. The history of productivity goes back centuries, but most researchers defined productivity as the relationship between a product and the factors used in production in the early twentieth century. Productivity as the optimal use of available resources means that "more output using less input" can increase companies' economic growth and prosperity capacity. Also, having a quality life based on economic progress depends on productivity growth in that society. Therefore, productivity is a national priority for any developed country. There are several methods for calculating productivity growth measurements that can be divided into parametric and non-parametric methods. Parametric methods rely on the existence of a function in their hypotheses, while non-parametric methods do not require a function based on empirical evidence. One of the most popular non-parametric methods is Data Envelopment Analysis (DEA), which measures changes in productivity over time. The DEA evaluates the productivity of decision-making units (DMUs) based on mathematical models. This method uses multiple inputs and outputs to compare the productivity of similar DMUs such as banks, government agencies, companies, airports, Etc. Non-parametric methods are themselves divided into the frontier and non frontier approaches. The Malmquist productivity index (MPI) proposed by Caves, Christensen, and Diewert (1982), the Hicks–Moorsteen productivity index (HMPI) proposed by Bjurek (1996), or the Luenberger productivity indicator (LPI) proposed by Chambers (2002) are powerful tools for measuring productivity changes over time. This study will compare the Malmquist, Hicks–Moorsteen, and Luenberger indices theoretically and empirically based on DEA models and review their strengths and weaknesses.

Keywords: data envelopment analysis, Hicks–Moorsteen productivity index, Leuenberger productivity indicator, malmquist productivity index

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Authors: A. Lambert-Mogiliansky

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In this paper, we investigate the properties of simple rules for reappointment aimed at holding a public official accountable and monitor his activity. The public official allocates budget resources to various activities which results in the delivery of public services to citizens. He has discretion over the use of resource so he can divert some of them for private ends. Because of a liability constraint, zero diversion can never be secured in all states. The optimal reappointment mechanism under complete information is shown to exhibit some leniency thus departing from the zero tolerance principle. Under asymmetric information (about the state), a rule with random verification in a pre-announced subset is shown to be optimal in a class of common rules. Surprisingly, those common rules make little use of hard information about service delivery when available. Similarly, PO's claim about his record is of no value to improve the performance of the examined rules. In contrast requesting that the PO defends his records publicly can be very useful if the service users are given the chance to refute false claims with cheap talk complaints: the first best complete information outcome can be approached in the absence of any observation by the manager of the accountability mechanism.

Keywords: accountability, corruption, persuasion, debate

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Authors: K. Tejasri, K. Suvarna Vani, S. Prathyusha, S. Ramya

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Proteins are chained sequences of amino acids which are brought together by the peptide bonds. Many varying formations of the chains are possible due to multiple combinations of amino acids and rotation in numerous positions along the chain. Protein structure prediction is one of the crucial goals worked towards by the members of bioinformatics and theoretical chemistry backgrounds. Among the four different structure levels in proteins, we emphasize mainly the secondary level structure. Generally, the secondary protein basically comprises alpha-helix and beta-sheets. Multi-class classification problem of data with disparity is truly a challenge to overcome and has to be addressed for the beta strands. Imbalanced data distribution constitutes a couple of the classes of data having very limited training samples collated with other classes. The secondary structure data is extracted from the protein primary sequence, and the beta-strands are predicted using suitable machine learning algorithms.

Keywords: proteins, secondary structure elements, beta-sheets, beta-strands, alpha-helices, machine learning algorithms

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Authors: Y. P. Wang, J. K. Chen, C. H. Lee, G. H. Huang, M. C. Wang, S. W. Chen, Y. T. Kuan, H. C. Lin, C. Y. Huang, W. H. Liang, W. C. Lin, H. C. Yu

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The hi-tech industries in the Science Park at southern Taiwan were heavily damaged by a strong earthquake early 2016. The financial loss in this event was attributed primarily to the automated stocker system handling fully processed products, and recovery of the automated stocker system from the aftermath proved to contribute major lead time. Therefore, development of effective means for protection of stockers against earthquakes has become the highest priority for risk minimization and business continuity. This study proposes to mitigate the seismic response of the stockers by introducing viscous fluid dampers in between the ceiling and the top of the stockers. The stocker is expected to vibrate less violently with a passive control force on top. Linear damper is considered in this application with an optimal damping coefficient determined from a preliminary parametric study. The damper is small in size in comparison with those adopted for building or bridge applications. Component test of the dampers has been carried out to make sure they meet the design requirement. Shake table tests have been further conducted to verify the proposed scheme under realistic earthquake conditions. Encouraging results have been achieved by effectively reducing the seismic responses of up to 60% and preventing the FOUPs from falling off the shelves that would otherwise be the case if left unprotected. Effectiveness of adopting a viscous fluid damper for seismic control of the stocker on top against the ceiling has been confirmed. This technique has been adopted by Macronix International Co., LTD for seismic retrofit of existing stockers. Demonstrative projects on the application of the proposed technique are planned underway for other companies in the display industry as well.

Keywords: hi-tech industries, seismic protection, automated stocker system, viscous fluid damper

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Authors: Saumyaranjan Sahoo, Sudhir Yadav

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Indian manufacturing firms operating in rapidly changing and highly competitive market, over the last few decades, have embraced organization-wide transformation to achieve cultural and operational excellence. In recent years, numerous approaches have been proposed to improve business and manufacturing performance. Lean practices in particular, Total Productive Management (TPM) and Total Quality Management (TQM) have received considerable attention, as they being adopted and adapted for raising the performance standard of Indian manufacturing firms to world class levels. The complementary nature of TPM and TQM is being practiced in many companies to achieve synergy. Specifically, this research investigates whether joint TPM-TQM implementation contribute to higher business performance when compared to individual implementation. Data from 160 manufacturing firms were analyzed that demonstrate synergetic implementation of both TPM-TQM practices over a reasonable period of time, contributed in delivering better business performance as compared to individual implementation strategy.

Keywords: total productive management, total quality management, Indian manufacturing firms, business performance

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Authors: Daniel O'Shea, Mario M. Attard, David C. Kellermann

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In this paper, we propose a hyperelastic strain energy function that maps isotopic hyperelastic constitutive laws for the use of orthotropic materials without the use of structural tensors or any kind of fiber vector, or the use of standard invariants. In particular, we focus on neo-Hookean class of models and represent them using an invariant-free formulation. To achieve this, we revise the invariant-free formulation of isotropic hyperelasticity. The formulation uses quadruple contractions between fourth-order tensors, rather than scalar products of scalar invariants. We also propose a new decomposition of the orthotropic Hookean stiffness tensor into two fourth-order Lamé tensors that collapse down to the classic Lamé parameters for isotropic continua. The resulting orthotropic hyperelastic model naturally maintains all of the advanced properties of the isotropic counterparts, and similarly collapse back down to their isotropic form by nothing more than equality of parameters in all directions (isotropy). Comparisons are made with large strain experimental results for transversely isotropic rubber type materials under tension.

Keywords: finite strain, hyperelastic, invariants, orthotropic

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Authors: Khaled Klib, Yousri Azzam, Ibrahim Maarouf

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Tourism is one of the most important and fastest growing economic activities in the world, which has a prominent role in the growth and development of countries and has become increasingly important as business and trade after the World War II. The tourism development is one of the most important aspects of urban development, which aims to plan and develop tourist attractions and improve the urban environment within cities. Tourism development has become a priority for the urban development policy of cities, particularly those which have many tourist potentials. Complementary services, such as infrastructure, roads’ networks, transportation, and communications are needed for these potentials to function properly. In order to achieve these functionalities, also a new planning for the new areas as an expansion is required, or developing and renovating the existing urban areas according to pre-prepared plans to avoid random expansion of the urban structure of the city. This paper aims to determine the tourist attractions of Al-Khomse city, by reviewing the most important tourist attractions such as the Roman city (Leptis Magna), the geographical location on the Mediterranean coast, the temperate climate and diversity of the natural environment. The paper also examines the reality of the infrastructure and tourist services in the city and its suitability to serve the tourism sector. The paper also includes a proposed for tourism development in the city as one of the city's urban expansion trends, which can guide the development strategy in the future. The paper concludes with a vision for the tourism development areas as one of the trends for urban expansion in the future. The paper also concludes tourism development will have an effective role in the growth and development of urban, economic and social, in addition to preserving the natural environment. The paper recommended the need to emphasize the role of tourism development as one of the pillars and trends for the development policy and expansion of Al-Khomse city, preservation of tourist attractions and natural resources and developing infrastructure and tourist services such as accommodation, entertainment, mobility, and accessibility.

Keywords: tourism, tourist attractions, tourism development, urban expansion

Procedia PDF Downloads 245

Authors: Kumaran Narayanan, Andrew N. Osahor

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E. coli has been engineered by our group and by others as a vector to deliver DNA into cultured human and animal cells. However, so far conditions to improve gene delivery using this vector have not been investigated, resulting in a major gap in our understanding of the requirements for this vector to function optimally. Our group recently published novel data showing that simple addition of the DNA transfection reagent Lipofectamine increased the efficiency of the E. coli vector by almost 3-fold, providing the first strong evidence that further optimization of bactofection is possible. This presentation will discuss advances that demonstrate the effects of several intracellular strategies that improve the efficiency of this vector. Conditions that promote endosomal escape of internalized bacteria to evade lysosomal destruction after entry in the cell, a known obstacle limiting this vector, are elucidated. Further, treatments that increase bacterial lysis so that the vector can release its transgene into the mammalian environment for expression will be discussed. These experiments will provide valuable new insight to advance this E. coli system as an important class of vector technology for genetic correction of human disease models in cells and whole animals.

Keywords: DNA, E. coli, gene expression, vector

Procedia PDF Downloads 358

Authors: Haohao Wang

Abstract:

Technology, multimedia in Open Educational Resources, can contribute positively to student performance in an online instructional environment. Student performance data of past four years were obtained from an online course entitled Applied Calculus (MA139). This paper examined the data to determine whether multimedia (independent variable) had any impact on student performance (dependent variable) in online math learning, and how students felt about the value of the technology. Two groups of student data were analyzed, group 1 (control) from the online applied calculus course that did not use multimedia instructional materials, and group 2 (treatment) of the same online applied calculus course that used multimedia instructional materials. For the MA139 class, results indicate a statistically significant difference (p = .001) between the two groups, where group 1 had a final score mean of 56.36 (out of 100), group 2 of 70.68. Additionally, student testimonials were discussed in which students shared their experience in learning applied calculus online with multimedia instructional materials.

Keywords: online learning, open educational resources, multimedia, technology

Procedia PDF Downloads 376

Authors: Tanit Pruktara

Abstract:

The research aimed to study the students’ learning achievement and awareness level on electrical energy consumption and conservation and also to investigate the students’ attitude on the developed multimedia supplemented instructional unit for learning household electrical energy consumption and conservation in grade 10 Thailand student. This study used a quantitative method using MCQ for pre and post-achievement tests and Likert scales for awareness and attitude survey questionnaires. The results from this were employed to improve the multimedia to be appropriate for the classroom and with real life situations in the second phase, the main study. The experimental results showed that the developed learning unit significantly improved the students’ learning achievement as well as their awareness of electric energy conservation. Additional we found the student will enjoy participating in class activities when the lessons are taught using multimedia and helps them to develop the relevance between the course and real world situations.

Keywords: lesson plan, media and animations, training course, vocational school in Thailand

Procedia PDF Downloads 177

Authors: Fuad M. Alkoot

Abstract:

Different experimental technologies such as microarray sequencing have been proposed to generate high-resolution genetic data, in order to understand the complex dynamic interactions between complex diseases and the biological system components of genes and gene products. However, the generated samples have a very large dimension reaching thousands. Therefore, hindering all attempts to design a classifier system that can identify diseases based on such data. Additionally, the high overlap in the class distributions makes the task more difficult. The data we experiment with is generated for the identification of autism. It includes 142 samples, which is small compared to the large dimension of the data. The classifier systems trained on this data yield very low classification rates that are almost equivalent to a guess. We aim at reducing the data dimension and improve it for classification. Here, we experiment with applying a multistage PCA on the genetic data to reduce its dimensionality. Results show a significant improvement in the classification rates which increases the possibility of building an automated system for autism detection.

Keywords: PCA, gene expression, dimensionality reduction, classification, autism

Procedia PDF Downloads 560