Search results for: digital learning environment

Authors: Alena Sicakova, Adriana Estokova

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Although properly made concrete is inherently a durable material, there are many physical and chemical forces in the environment which can contribute to its deterioration. This paper deals with two aspects of concrete durability in chemical aggressive environment: degradation effect of particular aggressive exposure and role of particular mineral additives. Results of the study of leaching and acid corrosion processes in samples prepared with specific dosage of microsilica and zeolite are given in the paper. Corrosion progress after 60-day exposition is manifested by increasing rate of both Ca and Si release, what is identified by XRF method. Kind and dosage of additions used in experiment was found to be helpful for stabilization of concrete microstructure. The lowest concentration of mean elements in leachates was observed for mixture V1 (microsilica only) unlike the V2 (microsilica + zeolite). It is surprising in the terms of recommendations of zeolite application for acid exposure. Using microsilica only seems to be more effective.

Keywords: sustainability, durability, concrete, acid corrosion, leaching

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Authors: Yasmine Abu Adla, Racha Soubra, Milana Kasab, Mohamad O. Diab, Aly Chkeir

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Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals, out of which 11 were chosen based on their intraclass correlation coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, 5 features were introduced to the linear discriminant analysis classifier, and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90%, respectively.

Keywords: Doppler radar system, stand-to-sit phase, TUG test, machine learning, classification

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Authors: Natia Tabatadze

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The research aim is to study the physical - mechanical characteristics of structural materials, in particular, hydraulic concrete in the surface active environment and receiving of high strength concrete, low-deformable, resistant to aggressive environment concrete due application of nano technologies. The obtained concrete with additives will by possible to apply in hydraulic structures. We used cement (compressive strength R28=39,42 mPa), sand (0- 5 mm), gravel (5-10 mm, 10-20 mm), admixture CHRYSO® Fuge B 1,5% dosage of cement. CHRYSO® Fuge B renders mortar and concrete highly resistant to capillary action and reduces, or even eliminates infiltration of water under pressure. The fine particles that CHRYSO® Fuge B contains combine with the lime in the cement to form water repellent particles. These obstruct the capillary action within concrete. CHRYSO® Fuge B does not significantly modify the characteristics of the fresh concrete and mortar, nor the compressive strength. As result of research, the alkali-silica reaction was improved (relative elongation 0,122 % of admixture instead of 0,126 % of basic concrete after 14 days). The aggressive environment impact on the strength of heavy concrete, fabricated on the basis of the hydraulic admixture with the penetrating waterproof additives also was improved (strength on compression R28=47,5 mPa of admixture instead of R28=35,8 mPa), as well as the mass water absorption (W=3,37 % of admixture instead of W=1,41 %), volume water absorption (W=1,41 % of admixture instead of W=0,59 %), water tightness (R14=37,9 mPa instead R14=28,7 mPa) and water-resistance (B=18 instead B=12). The basic parameters of concrete with admixture was improved in comparison with basic concrete.

Keywords: structural materials, hydraulic concrete, low-deformable, water absorption for mass, water absorption for volume

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Authors: Laref Nabil

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Ecology is at the center of many debates and international regulations. It therefore becomes a necessity and a privileged axis in many countries policy. The rise of environmental problems, the particularism of the hospital as an actor Public Health must lead by example in hygiene, prevention of risks to man and his environment. In this, it seemed interesting to make a poster on hospital liquid effluents in order to know not only the regulatory aspects but also their degree of pollution and their management in health institutions. Materials and methods: Samples taken at several looks, analysis performed at STEP Reghaia Algiers. Discussion and / or findings: In general, central gaze analysis results of water we can conclude that the contents of the various physico-chemical parameters greatly exceed the standards. Although the hypothesis of assimilating hospital liquid effluents domestic waters is confirmed, the liquid effluent from the University Hospital of Beni Messous and dumped in the natural environment still represent ecotoxicological risk.

Keywords: health, hospital, liquid effluents, water

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Authors: Lok Yi Joyce Poon

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China's mobile payment market has boomed in the past few years. WeChat (Chinese name as Weixin) owned by Tencent is known as the fastest growing all-in-one social messaging platforms. The company has launched the WeChat Pay in 2013, in which users can link their credit card to their user account and make payments within the app’s built in digital wallet. WeChat Payment is a one-stop payment tool that can provide a seamless online experience for the shoppers to transfer money between WeChat users (peer-to-peer) and make payments online by scanning a QR code, a prominent facilitator for transactions in WeChat, to complete the payment with the app without directing the users to the external websites. The aims of this study are to examine the effectiveness of WeChat mobile payment in China as well as the impacts of the China teen’s online purchasing behavior since the establishment of WeChat Payment. The research method of this study is conducted by both online survey on Sojump, a popular online survey platform in China. A total of 120 respondents among 18 to 25 teens in China completed the survey. Data sources included participants’ response to an end-of-session questionnaire, encompassing with the types of multiple choice, open-ended questions. To have an in-depth analysis, a face-to-face interview with a Chinese teen who is a frequent user of the WeChat Pay. The main finding of the study shows that the majority of the teenagers frequently use the WeChat payment tool because of its convenience, user-friendliness and the scenarios offered within the WeChat Wallet. The respondents claimed that they will settle the bills in their daily lives via WeChat Pay. However, the respondents in the age group of 40 or above will not use the WeChat Pay due to the security concern and they do not see the app as a platform for commercial activities like online shopping. Throughout the study, it is recommended WeChat should put more efforts on the security issue and improve the payment technology by adopting the near-field communication terminals instead of requiring users to scan QR codes before they complete the transaction.

Keywords: digital wallet, mobile payment, online purchasing behavior, WeChat Pay

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Authors: Ziying Wu, Danfeng Yan

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Multi-Access Edge Computing (MEC) is one of the key technologies of the future 5G network. By deploying edge computing centers at the edge of wireless access network, the computation tasks can be offloaded to edge servers rather than the remote cloud server to meet the requirements of 5G low-latency and high-reliability application scenarios. Meanwhile, with the development of IOV (Internet of Vehicles) technology, various delay-sensitive and compute-intensive in-vehicle applications continue to appear. Compared with traditional internet business, these computation tasks have higher processing priority and lower delay requirements. In this paper, we design a 5G-based Vehicle-Aware Multi-Access Edge Computing Network (VAMECN) and propose a joint optimization problem of minimizing total system cost. In view of the problem, a deep reinforcement learning-based joint computation offloading and task migration optimization (JCOTM) algorithm is proposed, considering the influences of multiple factors such as concurrent multiple computation tasks, system computing resources distribution, and network communication bandwidth. And, the mixed integer nonlinear programming problem is described as a Markov Decision Process. Experiments show that our proposed algorithm can effectively reduce task processing delay and equipment energy consumption, optimize computing offloading and resource allocation schemes, and improve system resource utilization, compared with other computing offloading policies.

Keywords: multi-access edge computing, computation offloading, 5th generation, vehicle-aware, deep reinforcement learning, deep q-network

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Authors: Adhi Susilo

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This paper addresses the roles of distance education in the agricultural extension workers’ education. Agriculture plays an important role in both poverty reduction and economic growth. The technology of agriculture in the developing world should change continuously to keep pace with rising populations and rapidly changing social, economic, and environmental conditions. Therefore, agricultural extension workers should have several competencies in order to carry out their duties properly. One of the essential competencies that they must possess is the professional competency that is directly related to their duties in carrying out extension activities. Such competency can be acquired through studying at Universitas Terbuka (UT). With its distance learning system, agricultural extension workers can study at UT without leaving their duties. This paper presenting sociological analysis and lessons learnt from the specific context of Indonesia. Diversities in geographic, demographic, social cultural and economic conditions of the country provide specific challenges for its distance education practice and the process of social transformation to which distance education can contribute. Extension officers used distance education for personal benefits and increased professional productivity. An increase in awareness is important for the further adoption of distance learning for extension purposes. Organizations in both the public and private sector must work to increase knowledge of ICTs for the benefit of stakeholders. The use of ICTs can increase productivity for extensions officers and expand educational opportunities for learners. The use of distance education by extension to disseminate educational materials around the world is widespread. Increasing awareness and use of distance learning can lead to more productive relationships between extension officers and agricultural stakeholders.

Keywords: agricultural extension, demographic and geographic condition, distance education, ICTs

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Authors: Giuseppina Settanni, Antonio Panarese, Raffaele Vaira, Maurizio Galiano

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Nowdays, artificial intelligence is used successfully in academia and industry for its ability to learn from a large amount of data. In particular, in recent years the use of machine learning algorithms in the field of e-commerce has spread worldwide. In this research study, a prototype software platform was designed and implemented in order to suggest to users the most suitable products for their needs. The platform includes a chatbot and a recommender system based on artificial intelligence algorithms that provide suggestions and decision support to the customer. The recommendation systems perform the important function of automatically filtering and personalizing information, thus allowing to manage with the IT overload to which the user is exposed on a daily basis. Recently, international research has experimented with the use of machine learning technologies with the aim to increase the potential of traditional recommendation systems. Specifically, support vector machine algorithms have been implemented combined with natural language processing techniques that allow the user to interact with the system, express their requests and receive suggestions. The interested user can access the web platform on the internet using a computer, tablet or mobile phone, register, provide the necessary information and view the products that the system deems them most appropriate. The platform also integrates a dashboard that allows the use of the various functions, which the platform is equipped with, in an intuitive and simple way. Artificial intelligence algorithms have been implemented and trained on historical data collected from user browsing. Finally, the testing phase allowed to validate the implemented model, which will be further tested by letting customers use it.

Keywords: machine learning, recommender system, software platform, support vector machine

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Authors: Teresa M. Odipo

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Inclusive physical education and an inclusive educational approach in German schools have received much attention in recent years due to the UN Convention on the rights of persons with disabilities proposals, which came into force in Germany in 2009. The aim of inclusive PE is to include children with disabilities and able bodied children, based on the idea, that all children should attend school together. While PE mostly took place in a heterogeneous environment, introducing children with all kinds of disabilities posed more challenges to the teachers, when children with disabilities were included. Therefore it is important that the educational approach should include pre-service teachers’ (PST) self-efficacy for and their attitudes towards inclusive practices. The PSTs’ self-efficacy for inclusive practices is one of the strongest predictors of the success of the inclusion reforms introduced in 2009, in order to improve PSTs’ ability to handle these very new challenges. PE stands out because the very nature of sport involves the body which means that all children, especially those with special needs should be treated in an appropriate manner. Up till now, it has been mostly English-speaking countries that have been assessed for inclusive practices in PE. Due to the lack of research in Germany, there is a strong need to question PSTs’ prepared-ness. This paper presents results from the 2016 survey conducted on around 100 PSTs by the German University of Sports in Cologne and opens up new directions within PSTs’ education, concerning their attitudes and self-efficacy towards inclusive PE. These new aspects will be included in the construction of new learning and teaching tools to improve pre-service teachers’ education for inclusive Physical Education.

Keywords: attitudes, inclusive physical education, pre-service teachers, self-efficacy

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Authors: Aadityaa Singla

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The big five personality traits are as follows: openness, conscientiousness, extraversion, agreeableness, and neuroticism. In order to get an insight into their personality, many flocks to these categories, which each have different meanings/characteristics. This information is important not only to individuals but also to career professionals and psychologists who can use this information for candidate assessment or job recruitment. The links between AI and psychology have been well studied in cognitive science, but it is still a rather novel development. It is possible for various AI classification models to accurately predict a personality question via ten input questions. This would contrast with the hundred questions that normal humans have to answer to gain a complete picture of their five personality traits. In order to approach this problem, various AI classification models were used on a dataset to predict what a user may answer. From there, the model's prediction was compared to its actual response. Normally, there are five answer choices (a 20% chance of correct guess), and the models exceed that value to different degrees, proving their significance. By utilizing an MLP classifier, decision tree, linear model, and K-nearest neighbors, they were able to obtain a test accuracy of 86.643, 54.625, 47.875, and 52.125, respectively. These approaches display that there is potential in the future for more nuanced predictions to be made regarding personality.

Keywords: machine learning, personally, big five personality traits, cognitive science

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Authors: Kausik Halder, Nabendu Chaki, Ranjan Dasgupta

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We present a modelling framework that supports the engineering of early requirements specifications for design of learner centric dynamic Learning Management System. The framework is based on i* modelling tool and Means End Analysis, that adopts primitive concepts for modelling early requirements (such as actor, goal, and strategic dependency). We show how pedagogical and computational requirements for designing a learner centric Learning Management system can be adapted for the automatic early requirement engineering specifications. Finally, we presented a model on a Learner Quanta based adaptive Courseware. Our early requirement analysis shows that how means end analysis reveals gaps and inconsistencies in early requirements specifications that are by no means trivial to discover without the help of formal analysis tool.

Keywords: adaptive courseware, early requirement engineering, means end analysis, organizational modelling, requirement modelling

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Authors: Sara Aziz, Madiha Arooj, Hira Rizwani, Wasim Irshad

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Enterprise Resource Planning (ER) as component of Information Resource System has turned up as one of the most demanding software in market for the new millennium. ERP system automates the core activities of any organization such as finance, manufacturing and supply chain management, human resource etc. to generate an access to the information in real time environment. Despite this fact many of the organizations globally particularly in developing country Pakistan are unaware and avoid adopting it. The development and implementation of ERP system is a complex and challenging process. This research was aimed to explore the benefits and coping strategies (with reference to end user reaction) of organizations those have implemented ERP. The problems addressed in this study focused the challenges and key success factors regarding implementing ERP Pakistani Organizations. Secondly, it has explored the stumbling blocks and business integration of those organizations that are not implementing ERP. The public and corporate sector organizations in Pakistan were selected to collect the data. The research finding shows that the organizational culture, openness towards adoption and learning, deployment and development, top management commitment and change systems, business processes and compatibility and user acceptance and reaction are contributing factors for successful implementation and development of ERP system. This research is thus an addition to enhance knowledge and understanding of implementation of ERP system in Pakistan.

Keywords: ERP system, user acceptance and involvement, change management, organizational culture

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Authors: Sanchari Mukhopadhyay

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Today, almost the entire realm of human activities are becoming increasingly dependent on the power of information, where through ICTs it is now possible to cater distances and avail various services at a few clicks. In principle, ICTs are thus expected to blur location-specific differences and affiliations of development and bring in an inclusive society at the wake of globalization. However, eventually researchers and policy analysts realized that ICTs are also generating inequality in spite of the hope for an integrated world and widespread social well-being. Regarding this unevenness, location plays a major role as often ICT development is seen to be concentrated into pockets, leaving behind large tracks as underprivileged. Thus, understanding the spatial pattern of ICT development and distribution is significant in relation to exploring the extent to which ICTs are fulfilling the promises or reassuring the existing divisions. In addition, it is also profoundly crucial to investigate how regions are connecting and competing both locally and globally. The focus of the research paper is to evaluate the spatial structure of ICT led development in India. Thereby, it attempts to understand the state level (four selected states) pattern of ICT penetration, the pattern of diffusion across districts with respect to large urban centres and the rural-urban disparity of technology adoption. It also tries to assess the changes in access dynamisms of ICTs as one move away from a large metropolitan city towards the periphery. In brief, the analysis investigates into the tendency towards the uneven growth of development through the identification of the core areas of ICT advancement within the country and its diffusion from the core to the periphery. In order to assess the level of ICT development and rural-urban disparity across the districts of selected states, two indices named ICT Development Index and Rural-Urban Digital Divide Index have been constructed. The study mostly encompasses the latest Census (2011) of the country and TRAI (Telecom Regulatory Authority of India) in some cases.

Keywords: ICT development, diffusion, core-periphery, digital divide

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Authors: Waleed Al-Nuaimy, Luke Anastassiou, Manjinder Kainth

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As the process of teaching has evolved with the advent of new technologies over the ages, so has the process of learning. Educators have perpetually found themselves on the lookout for new technology-enhanced methods of teaching in order to increase learning efficiency and decrease ever expanding workloads. Shortly after the invention of the internet, web-based learning started to pick up in the late 1990s and educators quickly found that the process of providing learning material and marking assignments could change thanks to the connectivity offered by the internet. With the creation of early web-based virtual learning environments (VLEs) such as SPIDER and Blackboard, it soon became apparent that VLEs resulted in higher reported computer self-efficacy among students, but at the cost of students being less satisfied with the learning process . It may be argued that the impersonal nature of VLEs, and their limited functionality may have been the leading factors contributing to this reported dissatisfaction. To this day, often faced with the prospects of assigning colossal engineering cohorts their homework and assessments, educators may frequently choose optimally curated assessment formats, such as multiple-choice quizzes and numerical answer input boxes, so that automated grading software embedded in the VLEs can save time and mark student submissions instantaneously. A crucial skill that is meant to be learnt during most science and engineering undergraduate degrees is gaining the confidence in using, solving and deriving mathematical equations. Equations underpin a significant portion of the topics taught in many STEM subjects, and it is in homework assignments and assessments that this understanding is tested. It is not hard to see that this can become challenging if the majority of assignment formats students are engaging with are multiple-choice questions, and educators end up with a reduced perspective of their students’ ability to manipulate equations. Artificial intelligence (AI) has in recent times been shown to be an important consideration for many technologies. In our paper, we explore the use of new AI based software designed to work in conjunction with current VLEs. Using our experience with the software, we discuss its potential to solve a selection of problems ranging from impersonality to the reduction of educator workloads by speeding up the marking process. We examine the software’s potential to increase learning efficiency through its features which claim to allow more customized and higher-quality feedback. We investigate the usability of features allowing students to input equation derivations in a range of different forms, and discuss relevant observations associated with these input methods. Furthermore, we make ethical considerations and discuss potential drawbacks to the software, including the extent to which optical character recognition (OCR) could play a part in the perpetuation of errors and create disagreements between student intent and their submitted assignment answers. It is the intention of the authors that this study will be useful as an example of the implementation of AI in a practical assessment scenario insofar as serving as a springboard for further considerations and studies that utilise AI in the setting and marking of science and engineering assignments.

Keywords: engineering education, assessment, artificial intelligence, optical character recognition (OCR)

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Authors: Fatema Tasmia, Brishti Majumder, Atiqur Rahman

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Attaining appropriate thermal comfort conditions in a place where the climate is hot and humid can be perplexing. Especially, when it resides at a congested place like old Dhaka Bangladesh, the provision of giving cross ventilation and building with proper orientation is quite difficult. This paper aims to investigate the indoor thermal environment of a room with and without transitional space or threshold in traditional row houses adjacent to a narrow alley of old Dhaka through field measurements. Transitional spaces are the part of buildings which are used for semi-outdoor household activities, social gathering and it is also proved to provide an indoor thermal effect. The field study was conducted by collecting thermal data (temperature, humidity and airflow) respectively, among the outdoor narrow alley, transitional space and adjacent indoor. This east-west elongated alley has an average width of 2.13 meter (varies from 1.5 to 2.6 meter) holding row houses on both sides. Among different aspects of thermal environment, the study of this paper is based on the analysis of temperature of corresponding cases. Other aspects and their variables were considered as constant (especially material) for accuracy and avoidance of confusion. This study focuses on the outcome that can ultimately contribute to the configuration of row houses with transitional spaces and in its relation to the adjacent outdoor space while achieving thermal comfort.

Keywords: alley, Old-Dhaka, row houses, temperature, thermal comfort, threshold, transitional space

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Authors: Marilei Amadeu Sabino

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The aim of this study is to establish differences between the terms ‘false cognates’, ‘false friends’ and ‘deceptive cognates’, usually considered to be synonyms. It will be shown they are not synonyms, since they do not designate the same linguistic process or phenomenon. Despite their differences in meaning, many pairs of formally similar words in two (or more) different languages are true cognates, although they are usually known as ‘false’ cognates – such as, for instance, the English and Italian lexical items ‘assist x assistere’; ‘attend x attendere’; ‘argument x argomento’; ‘apology x apologia’; ‘camera x camera’; ‘cucumber x cocomero’; ‘fabric x fabbrica’; ‘factory x fattoria’; ‘firm x firma’; ‘journal x giornale’; ‘library x libreria’; ‘magazine x magazzino’; ‘parent x parente’; ‘preservative x preservativo’; ‘pretend x pretendere’; ‘vacancy x vacanza’, to name but a few examples. Thus, one of the theoretical objectives of this paper is firstly to elaborate definitions establishing a distinction between the words that are definitely ‘false cognates’ (derived from different etyma) and those that are just ‘deceptive cognates’ (derived from the same etymon). Secondly, based on Set Theory and on the concepts of equal sets, subsets, intersection of sets and disjoint sets, this study is intended to elaborate some theoretical and practical questions that will be useful in identifying more precisely similarities and differences between cognate words of different languages, and according to graphic interpretation of sets it will be possible to classify them and provide discernment about the processes of semantic changes. Therefore, these issues might be helpful not only to the Learning of Second and Foreign Languages, but they could also give insights into Foreign and Second Language Teaching Methodology. Acknowledgements: FAPESP – São Paulo State Research Support Foundation – the financial support offered (proc. n° 2017/02064-7).

Keywords: deceptive cognates, false cognates, foreign language learning, teaching methodology

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Authors: Ronit Chakraborty, Sugata Banerji

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There has been a marked increase in the reported prevalence of Autism Spectrum Disorder (ASD) among children in the US over the past two decades. This research has analyzed the growth in state-level ASD prevalence against 45 different potentially explanatory factors, including socio-economic, demographic, healthcare, public policy, and political factors. The goal was to understand if these factors have adequate predictive power in modeling the differential growth in ASD prevalence across various states and if they do, which factors are the most influential. The key findings of this study include (1) the confirmation that the chosen feature set has considerable power in predicting the growth in ASD prevalence, (2) the identification of the most influential predictive factors, (3) given the nature of the most influential predictive variables, an indication that a considerable portion of the reported ASD prevalence differentials across states could be attributable to over and under diagnosis, and (4) identification of Florida as a key outlier state pointing to a potential under-diagnosis of ASD there.

Keywords: autism spectrum disorder, clustering, machine learning, predictive modeling

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Authors: Kamal KC, Zhendong Yin, Dasen Li, Zhilu Wu

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Intra-plant disease classification based on leaf images is a challenging computer vision task due to similarities in texture, color, and shape of leaves with a slight variation of leaf spot; and external environmental changes such as lighting and background noises. Deep convolutional neural network (DCNN) has proven to be an effective tool for binary classification. In this paper, two methods for binary classification of diseased plant leaves using DCNN are presented; model created from scratch and transfer learning. Our main contribution is a thorough evaluation of 4 networks created from scratch and transfer learning of 5 pre-trained models. Training and testing of these models were performed on a plant leaf images dataset belonging to 16 distinct classes, containing a total of 22,265 images from 8 different plants, consisting of a pair of healthy and diseased leaves. We introduce a deep CNN model, Optimized MobileNet. This model with depthwise separable CNN as a building block attained an average test accuracy of 99.77%. We also present a fine-tuning method by introducing the concept of a convolutional block, which is a collection of different deep neural layers. Fine-tuned models proved to be efficient in terms of accuracy and computational cost. Fine-tuned MobileNet achieved an average test accuracy of 99.89% on 8 pairs of [healthy, diseased] leaf ImageSet.

Keywords: deep convolution neural network, depthwise separable convolution, fine-grained classification, MobileNet, plant disease, transfer learning

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Authors: Asmaa Shehata

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Prior research indicates that second language (L2) learners encounter difficulty in the distinguishing novel L2 contrasting sounds that are not contrastive in their native languages. L2 orthographic information, however, is found to play a positive role in the acquisition of non-native phoneme contrasts. While most studies have mainly involved a familiar written script (i.e., the Roman script), the influence of a foreign, unfamiliar script is still unknown. Therefore, the present study asks: Does unfamiliar L2 script play a role in creating distinct phonological representations of novel contrasting phonemes? It is predicted that subjects’ performance in the unfamiliar orthography group will outperform their counterparts’ performance in the control group. Thus, training that entails orthographic inputs can yield a significant improvement in L2 adult learners’ identification and lexical encoding of novel L2 consonant contrasts. Results are discussed in terms of their implications for the type of input introduced to L2 learners to improve their language learning.

Keywords: Arabic, consonant contrasts, foreign script, lexical encoding, orthography, word learning

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Authors: Mostafa Gabr, Rania Abdul Galil, Nihal Salim

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Various interventions are applied in cities with the aim to improve living and acoustic environmental conditions. Noise is one of the most influential and critical factors in the environment that has an effect on the QOL (quality of life) and urban environment. It ranks second among environmental pollution issues according to EEAA. Traffic noise is a major source of noise. Noise barriers are one of the physical techniques in landscape design used to reduce the impact of noise pollution in urban areas. Roadways noise pollution can be best controlled by a noise barrier. The aim of this paper is to consider all facets of sustainability when designing a comfortable acoustic environment in roadways, through different strategies related to planning and the design process. The study focuses on the relation between the design of noise barriers as a landscape noise mitigation installation and their materiality in so far as it influences the sustainability of the open space and the acceptability of users. According to previous studies, design of noise barrier mainly depends on cost as a decisive factor. This study asserts that environmental and socioeconomic costs associated are equally important. Hence, the paper presents a strategy for sustainable soundscape design. It builds a framework focusing on materiality considering the environmental and socioeconomic impact of noise barriers shaping urban open space around the road ways, and the different academic and market positions on noise barrier types and materials. Finally, it concludes with a matrix of the relation between the noise barrier design consideration and the three pillars of sustainability (social, economic and environmental).

Keywords: traffic noise level, acoustic sustainability, noise barrier, noise reduction, noise control, acoustical level

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Authors: Frazer G. Thompson

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Israel is a nation of cultural and historical diversity, yet the success factors for a modern Bedouin-Arab high-tech entrepreneur seem to be different from those of other Jewish-Israeli citizens. The purpose of this descriptive narrative case study is to explore how an Arab-Israeli all Negev-Bedouin technology company has succeeded in the Israeli high-tech industry by utilizing technology and engineering career opportunities available to Bedouin youth for ‘Sadel Tech,’ at Be’er-Sheva, the Negev, Israel. Methods: The strategy of inquiry seeks to explore real-life contextual understandings, multi-level perspectives, and the cultural influences of personal, community, educational, and entrepreneurial factors. The research methodology includes in-depth one-on-one interviews, focus group sessions, and overt observation to explore the meaning and understanding of the constructs toward determining the effect all or a few of the elements may have on the overall success factors of the company. Results: Study results indicate that the state-run educational system in Israel fails to adequately integrate important aspects of Bedouin culture into the learning environment. However, Bedouin entrepreneurs are finding ways to compensate for these inadequacies by utilizing non-traditional methods of teaching, learning, and doing business. Government incentives for Bedouin start-ups are also recognized as contributors. Employees of Sadel live and work in the Negev, the Gaza Strip, and the West Bank, further informing the study that the traditions of tribal etiquette continue to contribute to modern Bedouin-Arab business culture. Conclusion: Bedouin's business success in Israel is a multi-dimensional concept. While cultural acumen plays a prominent and unique role for both Arab-Israelis and Jewish-Israelis in economic and entrepreneurial pursuits, the marginalization of the Bedouin continues to contribute to the lack of educational and professional opportunities for Bedouin in Israel. Although recognized as important at the government level, programs necessary to implement the infrastructure required to support Bedouin entrepreneurship in Israel remain infantile. The Israeli Government is providing opportunities through grants and other incentives for Bedouin entrepreneurial start-ups, indicating that Israel has recognized the impact of this growing demographic. However, although many Bedouin graduates from University each year with advanced degrees, opportunities for Bedouin within the Israeli high-tech sector remain scarce.

Keywords: Bedouin education, Bedouin entrepreneur, economic anthropology, ethnic business opportunities, Israeli tech, Silicon Wadi

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Authors: Tran Thi Thuy Oanh, Nguyen Ngoc Bao Tran

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In the view of Cognitive Linguistics (CL), knowledge and experience of things and events are used by human beings in expressing concepts, especially in their daily life. The human conceptual system is considered to be fundamentally metaphorical in nature. It is also said that the way we think, what we experience, and what we do everyday is very much a matter of language. In fact, language is an integral factor of cognition in that CL is a family of broadly compatible theoretical approaches sharing the fundamental assumption. The relationship between language and thought, of course, has been addressed by many scholars. CL, however, strongly emphasizes specific features of this relation. By experiencing, we receive knowledge of lives. The partial things are ideal domains, we make use of all aspects of this domain in metaphorically understanding abstract targets. The paper refered to applying this theory on pragmatics lessons for major English students at University of Foreign Language Studies - The University of Da Nang, Viet Nam. We conducted the study with two third – year students groups studying English pragmatics lessons. To clarify this study, the data from these two classes were collected for analyzing linguistic perspectives in the view of CL and traditional concepts. Descriptive, analytic, synthetic, comparative, and contrastive methods were employed to analyze data from 50 students undergoing English pragmatics lessons. The two groups were taught how to transfer the meanings of expressions in daily life with the view of CL and one group used the traditional view for that. The research indicated that both ways had a significant influence on students' English translating and interpreting abilities. However, the traditional way had little effect on students' understanding, but the CL view had a considerable impact. The study compared CL and traditional teaching approaches to identify benefits and challenges associated with incorporating CL into the curriculum. It seeks to extend CL concepts by analyzing metaphorical expressions in daily conversations, offering insights into how CL can enhance language learning. The findings shed light on the effectiveness of applying CL in teaching and learning English pragmatics. They highlight the advantages of using metaphorical expressions from daily life to facilitate understanding and explore how CL can enhance cognitive processes in language learning in general and teaching English pragmatics to third-year students at the UFLS - UDN, Vietnam in personal. The study contributes to the theoretical understanding of the relationship between language, cognition, and learning. By emphasizing the metaphorical nature of human conceptual systems, it offers insights into how CL can enrich language teaching practices and enhance students' comprehension of abstract concepts.

Keywords: cognitive linguisitcs, lakoff and johnson, pragmatics, UFLS

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Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: Lisa Chandler, Alistair Ward

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A significant component of design pedagogy is the need to foster design thinking in various contexts and to support students in understanding links between educational exercises and their potential application in professional design practice. It is also important that educators provide opportunities for students to engage with new technologies and encourage them to imagine applying their design skills for a range of outcomes. Problem solving is central to design so it is also essential that students understand that there can be multiple solutions to a design brief, and are supported in undertaking creative experimentation to generate imaginative outcomes. This paper presents a case study examining some innovative approaches to addressing these elements of design pedagogy. It investigates the effectiveness of the Immerse Lab, a three wall projection room at the University of the Sunshine Coast, Australia, as a learning context for design practice, for generating ideas and for supporting learning involving the comparative display of design outcomes. The project required first year design students to create a simple graphic design derived from an ordinary object and to incorporate specific design criteria. Utilizing custom-designed software, the students’ solutions were projected together onto the Immerse walls to create a large-scale, immersive grid of images, which was used to compare and contrast various responses to the same problem. The software also enabled individual student designs to be transformed, multiplied and enlarged in multiple ways and prompted discussions around the applicability of the designs in real world contexts. Teams of students interacted with their projected designs, brainstorming imaginative applications for their outcomes. Analysis of 77 anonymous student surveys revealed that the majority of students found: learning in the Immerse Lab to be beneficial; comparative review more effective than in standard tutorial rooms; that the activity generated new ideas; it encouraged students to think differently about their designs; it inspired students to develop their existing designs or create new ones. The project demonstrates that curricula involving immersive spaces can be effective in supporting engaging and relevant design pedagogy and might be utilized in other disciplinary areas.

Keywords: design pedagogy, immersive education, technology-enhanced learning, visualization

Procedia PDF Downloads 247

Authors: Brindha Senthil Kumar, Payel Chakraborty, Senthil Kumar Nachimuthu, Arindam Maitra, Prem Nath

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Gastric cancer is predominantly caused by demographic and diet factors as compared to other cancer types. The aim of the study is to predict Early Gastric Cancer (ECG) from diet and lifestyle factors using supervised machine learning algorithms. For this study, 160 healthy individual and 80 cases were selected who had been followed for 3 years (2016-2019), at Civil Hospital, Aizawl, Mizoram. A dataset containing 11 features that are core risk factors for the gastric cancer were extracted. Supervised machine algorithms: Logistic Regression, Naive Bayes, Support Vector Machine (SVM), Multilayer perceptron, and Random Forest were used to analyze the dataset using Python Jupyter Notebook Version 3. The obtained classified results had been evaluated using metrics parameters: minimum_false_positives, brier_score, accuracy, precision, recall, F1_score, and Receiver Operating Characteristics (ROC) curve. Data analysis results showed Naive Bayes - 88, 0.11; Random Forest - 83, 0.16; SVM - 77, 0.22; Logistic Regression - 75, 0.25 and Multilayer perceptron - 72, 0.27 with respect to accuracy and brier_score in percent. Naive Bayes algorithm out performs with very low false positive rates as well as brier_score and good accuracy. Naive Bayes algorithm classification results in predicting ECG showed very satisfactory results using only diet cum lifestyle factors which will be very helpful for the physicians to educate the patients and public, thereby mortality of gastric cancer can be reduced/avoided with this knowledge mining work.

Keywords: Early Gastric cancer, Machine Learning, Diet, Lifestyle Characteristics

Procedia PDF Downloads 151

Authors: S. Visetpotjanakit, C. Khrautongkieo

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Radiation monitoring in the environment and foodstuffs is one of the main responsibilities of Office of Atoms for Peace (OAP) as the nuclear regulatory body of Thailand. The main goal of the OAP is to assure the safety of the Thai people and environment from any radiological incidents. Various radioanalytical methods have been developed to monitor radiation and radionuclides in the environmental and foodstuff samples. To validate our analytical performance, several proficiency test exercises from the International Atomic Energy Agency (IAEA) have been performed. Here, the results of a proficiency test exercise referred to as the Proficiency Test for Tritium, Cobalt, Strontium and Caesium Isotopes in Seawater 2017 (IAEA-RML-2017-01) are presented. All radionuclides excepting ³H were analysed using various radioanalytical methods, i.e. direct gamma-ray counting for determining ⁶⁰Co, ¹³⁴Cs and ¹³⁷Cs and developed radiochemical techniques for analysing ¹³⁴Cs, ¹³⁷Cs using AMP pre-concentration technique and 90Sr using di-(2-ethylhexyl) phosphoric acid (HDEHP) liquid extraction technique. The analysis results were submitted to IAEA. All results passed IAEA criteria, i.e. accuracy, precision and trueness and obtained ‘Accepted’ statuses. These confirm the data quality from the OAP environmental radiation laboratory to monitor radiation in the environment.

Keywords: international atomic energy agency, proficiency test, radiation monitoring, seawater

Procedia PDF Downloads 164

Authors: Maria Fatima Almeida, Rodrigo Calili, George Soares, João Krause, Myrthes Marcele Dos Santos, Anna Carolina Suzano E. Silva, Marcos Alexandre Da

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In Brazil, the building sector accounts for 1/6 of energy consumption and 50% of electricity consumption. A complex sector with several driving actors plays an essential role in the country's economy. Currently, the digitalization readiness in this sector is still low, mainly due to the high investment costs and the difficulty of estimating the benefits of digital technologies in buildings. Nevertheless, the potential contribution of digitalization for increasing energy efficiency in the building sector in Brazil has been pointed out as relevant in the political and sectoral contexts, both in the medium and long-term horizons. To contribute to the debate on the possible evolving trajectories of digitalization in the building sector in Brazil and to subsidize the formulation or revision of current public policies and managerial decisions, three future scenarios were created to anticipate the potential energy efficiency in the building sector in Brazil due to digitalization by 2050. This work aims to present these scenarios as a basis to foresight the potential energy efficiency in this sector, according to different digitalization paces - slow, moderate, or fast in the 2050 horizon. A methodological approach was proposed to create alternative prospective scenarios, combining the Global Business Network (GBN) and the Laboratory for Investigation in Prospective Strategy and Organisation (LIPSOR) methods. This approach consists of seven steps: (i) definition of the question to be foresighted and time horizon to be considered (2050); (ii) definition and classification of a set of key variables, using the prospective structural analysis; (iii) identification of the main actors with an active role in the digital and energy spheres; (iv) characterization of the current situation (2021) and identification of main uncertainties that were considered critical in the development of alternative future scenarios; (v) scanning possible futures using morphological analysis; (vi) selection and description of the most likely scenarios; (vii) foresighting the potential energy efficiency in each of the three scenarios, namely slow digitalization; moderate digitalization, and fast digitalization. Each scenario begins with a core logic and then encompasses potentially related elements, including potential energy efficiency. Then, the first scenario refers to digitalization at a slow pace, with induction by the government limited to public buildings. In the second scenario, digitalization is implemented at a moderate pace, induced by the government in public, commercial, and service buildings, through regulation integrating digitalization and energy efficiency mechanisms. Finally, in the third scenario, digitalization in the building sector is implemented at a fast pace in the country and is strongly induced by the government, but with broad participation of private investments and accelerated adoption of digital technologies. As a result of the slow pace of digitalization in the sector, the potential for energy efficiency stands at levels below 10% of the total of 161TWh by 2050. In the moderate digitalization scenario, the potential reaches 20 to 30% of the total 161TWh by 2050. Furthermore, in the rapid digitalization scenario, it will reach 30 to 40% of the total 161TWh by 2050.

Keywords: building digitalization, energy efficiency, scenario building, prospective structural analysis, morphological analysis

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Authors: Mehmet Akif Bütüner, İlhan Koşalay

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Hydroelectric power plants (HEPPs) are renewable energy power plants with the highest installed power in the world. While the control systems operating in these power plants ensure that the system operates at the desired operating point, it is also responsible for stopping the relevant unit safely in case of any malfunction. While these control systems are expected not to miss signals that require stopping, on the other hand, it is desired not to cause unnecessary stops. In traditional control systems including modern systems with SCADA infrastructure, alarm conditions to create warnings or trip conditions to put relevant unit out of service automatically are usually generated with predefined limits regardless of different operating conditions. This approach results in alarm/trip conditions to be less likely to detect minimal changes which may result in serious malfunction scenarios in near future. With the methods proposed in this research, routine behavior of the oil circulation of hydraulic governor of a HEPP will be modeled with machine learning methods using historical data obtained from SCADA system. Using the created model and recently gathered data from control system, oil pressure of hydraulic accumulators will be estimated. Comparison of this estimation with the measurements made and recorded instantly by the SCADA system will help to foresee failure before becoming worse and determine remaining useful life. By using model outputs, maintenance works will be made more planned, so that undesired stops are prevented, and in case of any malfunction, the system will be stopped or several alarms are triggered before the problem grows.

Keywords: hydroelectric, governor, anomaly detection, machine learning, regression

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Authors: Dipti Parida, Atasi Mohanty

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The focus of this research is to examine the interaction effect of flipped teaching and traditional teaching mode across two different medium (English and Odia) of instructional groups. Both Science and History subjects were taken to be taught in the Class- VIII in two different instructional mode/s. In total, 180 students of Class-VIII of both Odia and English medium schools were taken as the samples of this study; 90 participants (each group) were from both English and Odia medium schools ; 45 participants of each of these two groups were again assigned either to flip or traditional teaching method. We have two independent variables and each independent variable with two levels. Medium and mode of instruction are the two independent variables. Medium of instruction has two levels of Odia medium and English medium groups. The mode of instruction has also two levels of flip and traditional teaching method. Here we get 4 different groups, such as Odia medium students with traditional mode of teaching (O.M.T), Odia medium students with flipped mode of teaching (O.M.F), English medium students with traditional mode of teaching (E.M.T) and English medium students with flipped mode of teaching (E.M.F). Before the instructional administration, these four groups were given a test on the concerned topic to be taught. Based on this result, a one-way ANOVA was computed and the obtained result showed that these four groups don’t differ significantly from each other at the beginning. Then they were taught the concerned topic either in traditional or flip mode of teaching method. After that a 2×2×2 repeated measures ANOVA was done to analyze the group differences as well as the learning outcome before and after the teaching. The result table also shows that in post-test the learning outcome is highest in case of English medium students with flip mode of instruction. From the statistical analysis it is clear that the flipped mode of teaching is as effective for Odia medium students as it is for English medium students.

Keywords: medium of instruction, mode of instruction, test mode, vernacular medium

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Authors: Jaffar Hussain, Farman Ali Shah

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As we know that Pakistan is the developing country so it adopts new technologies for progress. In last three decays, some new technologies were introduced in the world in which Effective Microorganism was one of them. Microorganisms are one of the most power full living forces on earth. Originally, EM was developed as an odor control, farm, and animal health, human health many industrial treatments. Effective Microorganism is an organic fertilizer that contains a mixture of co-existing valuable microorganism composed from the environment. There are vast application of the EM in the world in which the researchers are explained in literature .In Pakistan work on EM technologies are under process, researcher are doing work to make them most valuable. At that time the application of EM are in agriculture, water treatment, to increase Cement strength, improving saline soil etc. Effective microorganisms are environmentally friendly , not-naturally organized, not chemically synthesized, not dangerous and not pathogenic.

Keywords: developing country, technologies, effective microorganism, researchers, Pakistan, agriculture

Procedia PDF Downloads 470