Search results for: inquiry- based instruction

Authors: Khaja Moiduddin, Tamer Khalaf, Muthuramalingam Thangaraj

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Due to the variety of benefits over traditional cutting techniques, the usage of laser cutting technology has risen substantially in recent years. Hot wire machining can cut the leather in the required shape by controlling the wire by generating thermal energy. In the present study, an attempt has been made to investigate the effects of performance measures in the hot wire machining process on cutting leather specimens. Carbonization and material removal rates were considered as quality indicators. Burning leather during machining might cause carbon particles, reducing product quality. Minimizing the effect of carbon particles is crucial for assuring operator and environmental safety, health, and product quality. Hot wire machining can efficiently cut the specimens by controlling the current through it. Taguchi- DEAR-based optimization was also performed in the process, which resulted in a required Carbonization and material removal rate. Using the DEAR approach, the optimal parameters of the present study were found with 3.7% prediction error accuracy.

Keywords: cabronization, leather, MRR, current

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Authors: Anne Klimesch, Alejandra Martinez, Martin HäRter, Isabelle Scholl, Paulina Bravo

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Patient-centered care (PCC) is a key principle of high-quality healthcare. In Latin America, research on and promotion of PCC have taken place in the past. However, thorough implementation of PCC in practice is still missing. In Germany, an integrative model of patient-centeredness has been developed by synthesis of diverse concepts of PCC. The model could serve as a point of reference for further research on the implementation of PCC. However, it is predominantly based on research from Europe and North America. This scoping review, therefore, aims to accumulate research on PCC in Latin America in the past 15 years and analyse how PCC has been conceptualized. The resulting overview of PCC in Latin America will be a foundation for a subsequent study aiming at the adaptation of the integrative model of patient-centeredness to the Latin American health care context. Scientific databases (MEDLINE, EMBASE, PsycINFO, CINAHL, Scopus, Web of Science, SCIELO, Redalyc.) will be searched, and reference and citation tracking will be performed. Studies will be included if they were carried out in Latin America, investigated PCC in any clinical and community setting (public and private), and were published in English, Spanish, French, or Portuguese since 2006. Furthermore, any theoretical framework or conceptual model to guide how PCC is conceptualized in Latin America will be included. Two reviewers will be responsible for the identification of articles, screening of records, and full-text assessment. The results of the scoping review will be used in the development of a mixed-methods study with the aim to understand the needs for PCC, as well as barriers and facilitators in Latin America. Based on the outcomes, the integrative model of PCC will be translated to Spanish and adapted to the Latin American context. The integrative model will enable the dissemination of the concept of PCC in Latin America and will provide a common ground for further research on the topic. The project will thereby make an important contribution to an evidence-based implementation of PCC in Latin America.

Keywords: conceptual framework, integrative model of PCC, Latin America, patient-centered care

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Authors: Farusil Najeeb Mullaveettil, Rolanas Dauksevicius

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Cellular structures produced by additive manufacturing have earned wide research attention due to their unique specific strength and energy absorption potentiality. The literature review concludes that pattern type and density are vital parameters that affect the mechanical properties of parts formed by additive manufacturing techniques and have an influence on printing time and material consumption. Fused deposition modeling technique (FDM) is used here to produce Polyvinylidene fluoride (PVDF) parts. In this work, patterns are based on triply periodic minimal surfaces (TPMS) produced by PVDF-based filaments using the FDM technique. PVDF homopolymer filament Fluorinar-H™ and PVDF copolymer filament Fluorinar-C™ are printed with three types of TPMS patterns. The patterns printed are Gyroid, Schwartz diamond, and Schwartz primitive. Tensile, flexural, and compression tests under quasi-static loading conditions are performed in compliance with ISO standards. The investigation elucidates the deformation mechanisms and a study that establishes a relationship between the printed and nominal specimens' dimensional accuracy. In comparison to the examined TPMS pattern, Schwartz diamond showed a higher relative elastic modulus and strength than the other patterns in tensile loading, and the Gyroid pattern showed the highest mechanical characteristics in flexural loading. The concluded results could be utilized to produce informed cellular designs for biomedical and mechanical applications.

Keywords: additive manufacturing, FDM, PVDF, gyroid, schwartz primitive, schwartz diamond, TPMS, tensile, flexural

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Authors: S. Rezaei, Z. Mirzaei, M. Khalighi, J. Bahrami

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Bridges, as an essential part of road infrastructures, are affected by various deterioration mechanisms over time due to the changes in their performance. As changes in performance can have many negative impacts on society, it is essential to be able to evaluate and measure the performance of bridges throughout their life. This evaluation includes the development or the choice of the appropriate performance indicators, which, in turn, are measured based on the selection of appropriate models for the existing deterioration mechanism. The purpose of this article is a statistical study of indicators and deterioration mechanisms of bridges in order to discover further research capacities in bridges performance assessment. For this purpose, some of the most common indicators of bridge performance, including reliability, risk, vulnerability, robustness, and resilience, were selected. The researches performed on each index based on the desired deterioration mechanisms and hazards were comprehensively reviewed. In addition, the formulation of the indicators and their relationship with each other were studied. The research conducted on the mentioned indicators were classified from the point of view of deterministic or probabilistic method, the level of study (element level, object level, etc.), and the type of hazard and the deterioration mechanism of interest. For each of the indicators, a number of challenges and recommendations were presented according to the review of previous studies.

Keywords: bridge, deterioration mechanism, lifecycle, performance indicator

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Authors: Camila Penido Gomes

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Over the past decade, an emerging body of research has been pointing to artificial intelligence´s great potential to improve the use of open data, increase transparency and curb corruption in the public sector. Nonetheless, studies on this subject are scant and usually lack evidence to validate AI-based technologies´ effectiveness in addressing corruption, especially in developing countries. Aiming to fill this void in the literature, this paper sets out to examine how AI has been deployed by civil society to improve the use of open data and prevent congresspeople from misusing public resources in Brazil. Building on the current debates and carrying out a systematic literature review and extensive document analyses, this research reveals that AI should not be deployed as one silver bullet to fight corruption. Instead, this technology is more powerful when adopted by a multidisciplinary team as a civic tool in conjunction with other strategies. This study makes considerable contributions, bringing to the forefront discussion a more accurate understanding of the factors that play a decisive role in the successful implementation of AI-based technologies in anti-corruption efforts.

Keywords: artificial intelligence, civil society organization, corruption, open data, transparency

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Authors: Huijuan Liu, Fukun Li, Hao Yuan

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The bolted spherical node is a common type of joint in space steel structures. The bolt-sphere joint portion almost always controls the bearing capacity of the bolted spherical node. The investigation of the bearing performance and progressive failure in service often requires high-fidelity numerical models. This paper focuses on the constitutive models of bolt steel and sphere steel used in China’s space structure construction. The elastoplastic model is determined by a standard tensile test and calibrated Voce saturated hardening rule. The ductile damage is found dominant based on the fractography analysis. Then Rice-Tracey ductile fracture rule is selected and the model parameters are calibrated based on tensile tests of notched specimens. These calibrated material models can benefit research or engineering work in similar fields.

Keywords: bolt-sphere joint, steel, constitutive model, ductile damage, model calibration

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Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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Authors: Smita Mathur

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Play is an innate, player-centric, joyful, fundamental activity of early childhood development that significantly contributes to social, emotional, and academic learning. Leveraging the power of play can enhance these domains by creating engaging, interactive, and developmentally appropriate learning experiences for young children. This research aimed to systematically examine young children’s play behaviors with a focus on four primary objectives: (1) the frequency and duration of on-task behaviors, (2) social interactions and emotional expressions during play, (3) the correlation between academic skills and play, and (4) identifying best practices for integrating play-based curricula. To achieve these objectives, a mixed-method study was conducted among young preschool-aged children in low socio-economic populations in the United States. The children were identified using purposive sampling. The children were observed during structured play in classrooms and unstructured play during outdoor playtime and in their home environments. The study sampled 97 preschool-aged children. A total of 3970 minutes of observations were coded to address the research questions. Thirty-seven percent of children lived in linguistically isolated families, and 76% lived in basic budget poverty. Children lived in overcrowded housing situations (67%), and most families had mixed citizenship status (66%). The observational study was conducted using the observation protocol during the Oxford Study Project. On-task behaviors were measured by tracking the frequency and duration of activities where children maintained focus and engagement. In examining social interactions and emotional expressions, the study recorded social interactions, emotional responses, and teacher involvement during play. The study aimed to identify best practices for integrating play-based curricula into early childhood education. By analyzing the effectiveness of different play-based strategies and their impact on on-task behaviors, social-emotional development, and academic skills, the research sought to provide actionable recommendations for educators and caregivers. The findings from study 1. Highlight play behaviors that increase on-task behaviors and academic, & social skills in young children. 2. Offers insights into teacher preparation and designing play-based curriculum 3. Research critiques observation as a data collection technique.

Keywords: play, early childhood education, social-emotional development, academic development

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Authors: Calister Wingang Makebe, Wilson Agwanande Ambindei, Zangue Steve Carly Desobgo, Abraham Billu, Emmanuel Jong Nso, P. Nisha

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Traditional liquid-state fermentation processes of Annona muricata L. juice can result in fluctuating product quality and quantity due to difficulties in control and scale up. This work describes a laboratory-scale batch fermentation process to produce a probiotic Annona muricata L. enzymatically extracted juice, which was modeled using the Doehlert design with independent extraction factors being incubation time, temperature, and enzyme concentration. It aimed at a better understanding of the traditional process as an initial step for future optimization. Annona muricata L. juice was fermented with L. acidophilus (NCDC 291) (LA), L. casei (NCDC 17) (LC), and a blend of LA and LC (LCA) for 72 h at 37 °C. Experimental data were fitted into mathematical models (Monod, Logistic and Luedeking and Piret models) using MATLAB software, to describe biomass growth, sugar utilization, and organic acid production. The optimal fermentation time was obtained based on cell viability, which was 24 h for LC and 36 h for LA and LCA. The model was particularly effective in estimating biomass growth, reducing sugar consumption, and lactic acid production. The values of the determination coefficient, R2, were 0.9946, 0.9913 and 0.9946, while the residual sum of square error, SSE, was 0.2876, 0.1738 and 0.1589 for LC, LA and LCA, respectively. The growth kinetic parameters included the maximum specific growth rate, µm, which was 0.2876 h-1, 0.1738 h-1 and 0.1589 h-1, as well as the substrate saturation, Ks, with 9.0680 g/L, 9.9337 g/L and 9.0709 g/L respectively for LC, LA and LCA. For the stoichiometric parameters, the yield of biomass based on utilized substrate (YXS) was 50.7932, 3.3940 and 61.0202, and the yield of product based on utilized substrate (YPS) was 2.4524, 0.2307 and 0.7415 for LC, LA, and LCA, respectively. In addition, the maintenance energy parameter (ms) was 0.0128, 0.0001 and 0.0004 with respect to LC, LA and LCA. With the kinetic model proposed by Luedeking and Piret for lactic acid production rate, the growth associated and non-growth associated coefficients were determined as 1.0028 and 0.0109, respectively. The model was demonstrated for batch growth of LA, LC, and LCA in Annona muricata L. juice. The present investigation validates the potential of Annona muricata L. based medium for heightened economical production of a probiotic medium.

Keywords: L. acidophilus, L. casei, fermentation, modelling, kinetics

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Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi

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Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).

Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality

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Authors: Tze-Sian Pui, Aung Than, Song-Wei Loo, Yuan-Li Hoe

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A paper-based electrode devised from an array of carboxylated multi-walled carbon nanotubes (MWNTs) and poly (diallyldimethylammonium chloride) (PDDA) has been successfully developed for the simultaneous detection of dopamine (DA) and ascorbic acid (AA) in 0.1 M phosphate buffer solution (PBS). The PDDA/MWNTs electrodes were fabricated by allowing PDDA to absorb onto the surface of carboxylated MWNTs, followed by drop-casting the resulting mixture onto a paper. Cyclic voltammetry performed using 5 mM [Fe(CN)₆]³⁻/⁴⁻ as the redox marker showed that the PDDA/MWNTs electrode has higher redox activity compared to non-functionalized carboxylated MWNT electrode. Differential pulse voltammetry was conducted with DA concentration ranging from 2 µM to 500 µM in the presence of 1 mM AA. The distinctive potential of 0.156 and -0.068 V (vs. Ag/AgCl) measured on the surface of the PDDA/MWNTs electrode revealed that both DA and AA were oxidized. The detection limit of DA was estimated to be 0.8 µM. This nanocomposite paper-based electrode has great potential for future applications in bioanalysis and biomedicine.

Keywords: dopamine, differential pulse voltammetry, paper sensor, carbon nanotube

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Authors: Muhammad Safder Shafi, Uzma Javed, Tooba Qasim

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The purpose of this paper is to find out the relationship between training and turnover intention in the presence of mediating variables promotion opportunities and job satisfaction among IT professionals in project based industry. It investigates the relationship directly between 1 independent variable training and dependent variable turnover intention. It also investigates the relationship between independent variable to the mediating variables and mediating variables to the turnover intention. Promotion opportunities and job satisfaction act as a mediator. The study sample comprised of 186 IT professionals from Pakistan, who work on different IT projects. Linear regression and Baron and Kenny approach were used to test the direct and mediated relationship between variables. The survey results demonstrated that job satisfaction fully mediate the relationship between promotion opportunities and turnover intention. Promotion opportunities fully mediate the relationship between employee training and job satisfaction. Promotion opportunities and job satisfaction mediates the relationship between training and turnover intention. The findings from the collected data may help top management to improve organizational strategies to cope up with improving different HR practices like training, pay structure and promotions in order to retain their workforce.

Keywords: HCT, SET, career growth opportunities, job satisfaction, training, turnover intention

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Authors: Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif

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Falls are one of the major causes of injury and death among elderly people aged 65 and above. A support system to identify such kind of abnormal activities have become extremely important with the increase in ageing population. Pose estimation is a challenging task and to add more to this, it is even more challenging when pose estimations are performed on challenging poses that may occur during fall. Location of the body provides a clue where the person is at the time of fall. This paper presents a vision-based tracking strategy where available joints are grouped into three different feature points depending upon the section they are located in the body. The three feature points derived from different joints combinations represents the upper region or head region, mid-region or torso and lower region or leg region. Tracking is always challenging when a motion is involved. Hence the idea is to locate the regions in the body in every frame and consider it as the tracking strategy. Grouping these joints can be beneficial to achieve a stable region for tracking. The location of the body parts provides a crucial information to distinguish normal activities from falls.

Keywords: fall detection, machine learning, deep learning, pose estimation, tracking

Procedia PDF Downloads 189

Authors: Wilailak Siripornadulsil, Siriyanapat Tasaku, Jutamas Buahorm, Surasak Siripornadulsil

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The objectives of this study were to isolate LAB from various sources, dietary supplement, Thai traditional fermented food, and freshwater fish and to characterize their potential as probiotic cultures. Out of 1,558 isolates, 730 were identified as LAB based on isolation on MRS agar supplemented with a bromocresol purple indicator and CaCO3 and gram-positive, catalase and oxidase negative characteristics. Eight isolates showed the potential probiotic properties including tolerance to acid, bile salt and heat, proteolytic, amylolytic and lipolytic activities and oxalate-degrading capability. They all showed the antimicrobial activity against some Gram-negative and Gram-positive pathogenic bacteria. Based on 16S rDNA sequence analysis, they were identified as Enterococcus faecalis BT2 and MG30, Leconostoc mesenteroides SW64 and Pediococcus pentosaceous BD33, CF32, NP6, PS34 and SW5. The health beneficial effects and food safety will be further investigated and developed as a probiotic or protective culture used in Nile tilapia belly flap meat fermentation.

Keywords: probiotic, lactic acid bacteria, pathogen, protective culture

Procedia PDF Downloads 382

Authors: Aghbalou Nihad, Charki Abderafi, Saida Rahali, Reklaoui Kamal

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Maximize the benefit from the wind energy potential is the most interest of the wind power stakeholders. As a result, the wind tower size is radically increasing. Nevertheless, choosing an appropriate wind turbine for a selected site require an accurate estimate of vertical wind profile. It is also imperative from cost and maintenance strategy point of view. Then, installing tall towers or even more expensive devices such as LIDAR or SODAR raises the costs of a wind power project. Various models were developed coming within this framework. However, they suffer from complexity, generalization and lacks accuracy. In this work, we aim to investigate the ability of neural network trained using the Bayesian Regularization technique to estimate wind speed profile up to height of 100 m based on knowledge of wind speed lower heights. Results show that the proposed approach can achieve satisfactory predictions and proof the suitability of the proposed method for generating wind speed profile and probability distributions based on knowledge of wind speed at lower heights.

Keywords: bayesian regularization, neural network, wind shear, accuracy

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Authors: A. C. Dey, H. M. Ahsan

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Heterogeneous traffic composed of both motorized and non-motorized vehicles that are a common feature of urban Bangladeshi roads. Popular non-motorized vehicles include rickshaws, rickshaw-van, and bicycle. These modes performed an important role in moving people and goods in the absence of a dependable mass transport system. However, rickshaws play a major role in meeting the demand for door-to-door public transport services to the city dwellers. But there is no separate lane for non-motorized vehicles in this city. Non-motorized vehicles generally occupy the outermost or curb-side lanes, however, at intersections non-motorized vehicles get mixed with the motorized vehicles. That’s why the conventional models fail to analyze the situation completely. Microscopic traffic simulation software VISSIM 5.3, itself a lane base software but default behavioral parameters [such as driving behavior, lateral distances, overtaking tendency, CCO=0.4m, CC1=1.5s] are modified for calibrating a model to analyze the effects of non-motorized traffic at an intersection (Mirpur-10) in a non-lane based mixed traffic condition. It is seen from field data that NMV occupies an average 20% of the total number of vehicles almost all the link roads. Due to the large share of non-motorized vehicles, capacity significantly drop. After analyzing simulation raw data, significant variation is noticed. Such as the average vehicular speed is reduced by 25% and the number of vehicles decreased by 30% only for the presence of NMV. Also the variation of lateral occupancy and queue delay time increase by 2.37% and 33.75% respectively. Thus results clearly show the negative effects of non-motorized vehicles on capacity at an intersection. So special management technics or restriction of NMV at major intersections may be an effective solution to improve this existing critical condition.

Keywords: lateral occupancy, non lane based intersection, nmv, queue delay time, VISSIM 5.3

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Authors: Khanyisile Mnguni, Muthukrishnavellaisamy Kumarasamy, Jeff C. Smithers

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Umgeni Water is a water board that supplies most parts of KwaZulu Natal with bulk portable water. Currently, Umgeni Water is running its distribution system based on required reservoir levels and demands and does not consider the energy cost at different times of the day, number of pump switches, and background leakages. Including these constraints can reduce operational cost, energy usage, leakages, and increase performance. Optimising pump schedules can reduce energy usage and costs while adhering to hydraulic and operational constraints. Umgeni Water has installed an online hydraulic software, WaterNet Advisor, that allows running different operational scenarios prior to implementation in order to optimise the distribution system. This study will investigate operation scenarios using optimisation techniques and WaterNet Advisor for a local water distribution system. Based on studies reported in the literature, introducing pump scheduling optimisation can reduce energy usage by approximately 30% without any change in infrastructure. Including tariff structures in an optimisation problem can reduce pumping costs by 15%, while including leakages decreases cost by 10%, and pressure drop in the system can be up to 12 m. Genetical optimisation algorithms are widely used due to their ability to solve nonlinear, non-convex, and mixed-integer problems. Other methods such as branch and bound linear programming have also been successfully used. A suitable optimisation method will be chosen based on its efficiency. The objective of the study is to reduce energy usage, operational cost, and leakages, and the feasibility of optimal solution will be checked using the Waternet Advisor. This study will provide an overview of the optimisation of hydraulic networks and progress made to date in multi-objective optimisation for a selected sub-system operated by Umgeni Water.

Keywords: energy usage, pump scheduling, WaterNet Advisor, leakages

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Authors: M. Nakisa, A. Maimun, Yasser M. Ahmed, F. Behrouzi, A. Tarmizi

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The practical application of the Computational Fluid Dynamics (CFD), for predicting the flow pattern around Multipurpose Amphibious Vehicle (MAV) hull has made much progress over the last decade. Today, several of the CFD tools play an important role in the land and water going vehicle hull form design. CFD has been used for analysis of MAV hull resistance, sea-keeping, maneuvering and investigating its variation when changing the hull form due to varying its parameters, which represents a very important task in the principal and final design stages. Resistance analysis based on CFD (Computational Fluid Dynamics) simulation has become a decisive factor in the development of new, economically efficient and environmentally friendly hull forms. Three-dimensional finite volume method (FVM) based on Reynolds Averaged Navier-Stokes equations (RANS) has been used to simulate incompressible flow around three types of MAV hull bow models in steady-state condition. Finally, the flow structure and streamlines, friction and pressure resistance and velocity contours of each type of hull bow will be compared and discussed.

Keywords: RANS simulation, multipurpose amphibious vehicle, viscous flow structure, mechatronic

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Authors: Ana Vieira, Fernando Lau, João Pedro Mortágua, Luís Cruz, Rui Santos

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The air transport impact on environment is more than ever a limitative obstacle to the aeronautical industry continuous growth. Over the last decades, considerable effort has been carried out in order to obtain quieter aircraft solutions, whether by changing the original design or investigating more silent maneuvers. The noise propagated by rotating surfaces is one of the most important sources of annoyance, being present in most aerial vehicles. Bearing this is mind, CEIIA developed a new computational chain for noise prediction with in-house software tools to obtain solutions in relatively short time without using excessive computer resources. This work is based on the new acoustic tool, which aims to predict the rotor noise generated during steady and maneuvering flight, making use of the flexibility of the C language and the advantages of GPU programming in terms of velocity. The acoustic tool is based in the Formulation 1A of Farassat, capable of predicting two important types of noise: the loading and thickness noise. The present work describes the most important features of the acoustic tool, presenting its most relevant results and framework analyses for helicopters and UAV quadrotors.

Keywords: rotor noise, acoustic tool, GPU Programming, UAV noise

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Authors: V. S. Klimash, Ye Min Thu

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Thyristor rectifiers, inverters grid-tied, and AC voltage regulators are widely used in industry, and on electrified transport, they have a lot in common both in the power circuit and in the control system. They have a common mathematical structure and switching processes. At the same time, the rectifier, but the inverter units and thyristor regulators of alternating voltage are considered separately both theoretically and practically. They are written about in different books as completely different devices. The aim of this work is to combine them into one class based on the unity of the equations describing electromagnetic processes, and then, to show this unity on the mathematical model and experimental setup. Based on research from mathematics to the product, a conclusion is made about the methodology for the rapid conduct of research and experimental design work, preparation for production and serial production of converters with a unified bundle. In recent years, there has been a transition from thyristor circuits and transistor in modular design. Showing the example of thyristor rectifiers and AC voltage regulators, we can conclude that there is a unity of mathematical structures and grid-tied thyristor converters.

Keywords: direct current, alternating current, rectifier, AC voltage regulator, generalized mathematical model

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Authors: Muhammad Babar Suleman

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Transgressing the boundaries of the real and the virtual, the temporal and the spatial and the personal and the political, Four Broken Hearts is a hybrid storyworld encompassing film, live performance, location-based experiences and social media. The project is scheduled for launch early next year and is currently a work-in-progress undergoing initial user testing. The story of Four Broken Hearts is being told by taking each of the classic elements of fiction- character, setting, exposition, climax and denouement - and bringing them ‘to life’ in the medium that conveys them to the highest degree of mimesis: Characters are built and explored through social media, Setting is experienced through location-based storytelling, the Backstory is fleshed out using film and the Climax is performed as an immersive drama. By taking advantage of what each medium does best while complementing the other mediums, Four Broken Hearts is presented in the form of a rich transmedia experience that allows audiences to explore the story world across many different platforms while still tying it all together within a cohesive narrative. This article presents an investigation of the project’s narrative outputs produced so far.

Keywords: narratology, storyworld, transmedia, narrative, storytelling

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Authors: Sayyed Benyamin Alavi, Giovanni Cerri, Leila Chennaoui, Ambra Giovannelli, Stefano Mazzoni

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Primary energy consumption and emissions of pollutants (including CO2) sustainability call to search methodologies to lower power absorption for unit of a given product. Cool production plants based on vapour compression are widely used for many applications: air conditioning, food conservation, domestic refrigerators and freezers, special industrial processes, etc. In the field of cool production, the amount of Yearly Consumed Primary Energy is enormous, thus, saving some percentage of it, leads to big worldwide impact in the energy consumption and related energy sustainability. Among various techniques to reduce power required by a Vapour Compression Cool Production Plant (VCCPP), the technique based on Power Regeneration by means of Internal Direct Cycle (IDC) will be considered in this paper. Power produced by IDC reduces power need for unit of produced Cool Power by the VCCPP. The paper contains basic concepts that lead to develop IDCs and the proposed options to use the IDC Power. Among various selections for using turbo machines, Best Economically Available Technologies (BEATs) have been explored. Based on vehicle engine turbochargers, they have been taken into consideration for this application. According to BEAT Database and similarity rules, the best turbo machine selection leads to the minimum nominal power required by VCCPP Main Compressor. Results obtained installing the prototype in “ad hoc” designed test bench will be discussed and compared with the expected performance. Forecasts for the upgrading VCCPP, various applications will be given and discussed. 4-6% saving is expected for air conditioning cooling plants and 15-22% is expected for cryogenic plants.

Keywords: Refrigeration Plant, Vapour Pressure Amplifier, Compressor, Expander, Turbine, Turbomachinery Selection, Power Saving

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Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice

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In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.

Keywords: churn prediction, data mining, decision-theoretic rough set, feature selection

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Authors: Rajlakshmi Guha, Sajjad Ansari, Shazia Nasreen, Hirak Banerjee, Jiaul Paik

Abstract:

Dyslexia is a neurocognitive disorder, affecting around fifteen percent of the Indian population. The symptoms include difficulty in reading alphabet, words, and sentences. This can be difficult at the phonemic or recognition level and may further affect lexical structures. Therapeutic intervention of dyslexic children post assessment is generally done by special educators and psychologists through one on one interaction. Considering the large number of children affected and the scarcity of experts, access to care is limited in India. Moreover, unavailability of resources and timely communication with caregivers add on to the problem of proper intervention. With the development of Educational Technology and its use in India, access to information and care has been improved in such a large and diverse country. In this context, this paper proposes an ICT enabled home-based intervention program for dyslexic children which would support the child, and provide an interactive interface between expert, parents, and students. The paper discusses the details of the database design and system layout of the program. Along with, it also highlights the development of different technical aids required to build out personalized android applications for the Indian dyslexic population. These technical aids include speech database creation for children, automatic speech recognition system, serious game development, and color coded fonts. The paper also emphasizes the games developed to assist the dyslexic child on cognitive training primarily for attention, working memory, and spatial reasoning. In addition, it talks about the specific elements of the interactive intervention tool that makes it effective for home based intervention of dyslexia.

Keywords: Android applications, cognitive training, dyslexia, intervention

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Authors: Zolzaya Badmaavanchig, Shoko Miyamoto

Abstract:

In recent years, universal design for learning (hereinafter referred to as "UDL"), which aims to establish an inclusive education system and to make all children, regardless of their disabilities, experts in learning, has been attracting attention, and there have been some attempts to incorporate it into regular classrooms where children with developmental disabilities and those who show such tendencies are enrolled. The purpose of this study was to examine the effectiveness and challenges of implementing UDL in Japanese elementary schools based on the previous literature. As a method, we first searched for articles on UDL for learning and UDL in the classroom from 2010 to 2022. In addition, we selected practice studies that targeted children with special educational support needs and the classroom as a whole. In response to the extracted literature, this bridge examined the following five perspectives: (1) subjects and grades in which UDL was practiced, (2) methods to grasp the actual conditions of the children, (3) consideration for children with special needs during class, (4) form of class, and (5) effects of the practice. Based on the results, we would like to present issues related to future UDL efforts in Japanese elementary schools.

Keywords: universal design for learning, regular elementary school class, children with special education needs, special educational support

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Authors: Temitayo Abayomi Ewemoje, Isaac Olugbemiga Afolayan, Badmus Alao Tayo

Abstract:

Researchers in developing countries have worked on improving cassava resistance to diseases and pests, high yielding and early maturity However, water management has received little or no attention as cassava cultivation in Sub-Saharan Africa depended on available precipitation (rain-fed condition). Therefore the need for water management in Agricultural crop production cannot be overemphasized. As other sectors compete with agricultural sector for fresh water (which is not readily available), there is need to increase water productivity in agricultural production. Experimentation was conducted to examine water use, growth and yield of improved cassava varieties under rain fed condition using Latin- square design with four replications. Four improved disease free stem cassava varieties TMS (30572, 980505, 920326 and 090581) were planted and growth parameters of the varieties were monitored for 90 and 120 days after planting (DAP). Effective rainfall useful for the plant growth was calculated using CROPWAT8 for Windows. Results indicated TMS090581 was having the highest tuber yield and plant height while TMS30572 had highest number of nodes. Tuber stem and leaf water productivities at 90 and 120 DAP of TMS (30572, 980505, 920326 and 090581) are (1.27 and 3.58, 1.44 and 2.35, 0.89 and 1.86, 1.64 and 3.77) kg/m3 (1.56 and 2.59, 1.95 and 2.02, 1.98 and 2.05, 1.95 and 2.18) kg/m3, and (1.34 and 2.32, 1.94 and 2.16, 1.57 and 1.40, 1.27 and 1.80) kg/m3 respectively. Based on tuber water productivity TMS090581 are recommended while TMS30572 are recommended based on leaf and stem productivity in water scarce regions.Experimentation was conducted to examine water use, growth and yield of improved cassava varieties under rain fed condition using Latin- square design with four replications. Four improved disease free stem cassava varieties TMS (30572, 980505, 920326 and 090581) were planted and growth parameters of the varieties were monitored for 90 and 120 days after planting (DAP). Effective rainfall useful for the plant growth was calculated using CROPWAT8 for Windows. Results indicated TMS090581 was having the highest tuber yield and plant height while TMS30572 had the highest number of nodes. Tuber, stem and leaf water productivities at 90 and 120 DAP of TMS (30572, 980505, 920326 and 090581) are (1.27 and 3.58, 1.44 and 2.35, 0.89 and 1.86, 1.64 and 3.77) kg/m3 (1.56 and 2.59, 1.95 and 2.02, 1.98 and 2.05, 1.95 and 2.18) kg/m3, and (1.34 and 2.32, 1.94 and 2.16, 1.57 and 1.40, 1.27 and 1.80) kg/m3 respectively. Based on tuber water productivity TMS090581 are recommended while TMS30572 are recommended based on leaf and stem productivity in water scarce regions

Keywords: improved TMS varieties, leaf productivity, rain-fed cassava production, stem productivity, tuber productivity

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Authors: Syamimi Shamsuddin, Hanafiah Yussof, Fazah Akhtar Hanapiah, Salina Mohamed, Nur Farah Farhan Jamil, Farhana Wan Yunus

Abstract:

Robot-based intervention for children with autism is an evolving research niche in human-robot interaction (HRI). Recent studies in this area mostly covered the role of robots in the clinical and experimental setting. Our previous work had shown that interaction with a robot pose no adverse effects on the children. Also, the presence of the robot, together with specific modules of interaction was associated with less autistic behavior. Extending this impact on school-going children, interactions that are in-tune with special education lessons are needed. This methodological paper focuses on how a robot can be incorporated in a current learning environment for autistic children. Six interaction scenarios had been designed based on the existing syllabus to teach communication skills, using the Applied Behavior Analysis (ABA) technique as the framework. Development of the robotic experience in class also covers the required set-up involving participation from teachers. The actual research conduct involving autistic children, teachers and robot shall take place in the next phase.

Keywords: autism spectrum disorder, ASD, humanoid robot, communication skills, robot-assisted learning

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Authors: Mohammad Zahidul Islam Bhuiyan, Shanyong Wang, Scott William Sloan, Daichao Sheng

Abstract:

Nowadays soil pressure transducers are widely used to measure the soil stress states in laboratory and field experiments. The soil pressure transducers, investigated here, are traditional diaphragm-type earth pressure cells (DEPC) based on strain gauge principle. It is found that the output of these sensors varies with the soil conditions as well as the position of a sensor. Therefore, it is highly recommended to calibrate the pressure sensors based on the similar conditions of their intended applications. The factory calibration coefficients of the EPCs are not reliable to use since they are normally calibrated by applying fluid (a special type of oil) pressure only over load sensing zone, which does not represent the actual field conditions. Thus, the calibration of these sensors is utmost important, and they play a pivotal role for assessing earth pressures precisely. In the present study, TML soil pressure sensor is used to compare its sensitivity under different calibration systems, for example, fluid calibration, and static load calibration with or without soil. The results report that the sensor provides higher sensitivity (more accurate results) under soil calibration system.

Keywords: calibration, soil pressure, earth pressure cell, sensitivity

Procedia PDF Downloads 240

Authors: Valentina Zhang

Abstract:

While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: Elif Tugce Aksun Tumerkan

Abstract:

Although seafood is an important part of human diet and categorized highly traded food industry internationally, it is remain overlooked generally in the global food security aspect. Food product authentication is the main interest in the aim of both avoids commercial fraud and to consider the risks that might be harmful to human health safety. In recent years, with increasing consumer demand for regarding food content and it's transparency, there are some instrumental analyses emerging for determining food fraud depend on some analytical methodologies such as proteomic and metabolomics. While, fish and seafood consumed as fresh previously, within advanced technology, processed or packaged seafood consumption have increased. After processing or packaging seafood, morphological identification is impossible when some of the external features have been removed. The main fish and seafood quality-related issues are the authentications of seafood contents such as mislabelling products which may be contaminated and replacement partly or completely, by lower quality or cheaper ones. For all mentioned reasons, truthful consistent and easily applicable analytical methods are needed for assurance the correct labelling and verifying of seafood products. DNA-barcoding methods become popular robust that used in taxonomic research for endangered or cryptic species in recent years; they are used for determining food traceability also. In this review, when comparing the other proteomic and metabolic analysis, DNA-based methods are allowing a chance to identification all type of food even as raw, spiced and processed products. This privilege caused by DNA is a comparatively stable molecule than protein and other molecules. Furthermore showing variations in sequence based on different species and founding in all organisms, make DNA-based analysis more preferable. This review was performed to clarify the main advantages of using DNA-barcoding for determining seafood fraud among other techniques.

Keywords: DNA-barcoding, genetic analysis, food fraud, mislabelling, packaged seafood

Procedia PDF Downloads 168