Search results for: Hybrid deep learning

Authors: Ng Liang Shen, Hau Yuan Wen

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Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

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Authors: U.-B. Schaer, M. Wehr, R. Hodler

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Background: Most nursing students require more training time for necessary nursing skills than defined by nursing schools curriculum to acquire basic nursing skills. Given skills training lessons are too brief to enable effective student learning, meaning in-depth skills practice and repetition various learning steps. This increases stress levels and the pressure to succeed for a nursing student with slower learning capabilities. Another possible consequence is that nursing students are less prepared in the required skills for future clinical practice. Intervention: The Bern College of Higher Education of Nursing, Switzerland, started the independent peer practice learning program in 2012. A concept was developed which defines specific aims and content as well as student’s rights and obligations. Students enlist beforehand and order the required materials. They organize themselves and train in small groups in allocated training location in the area of Learning Training and Transfer (LTT). During the peer practice, skills and knowledge can be repeatedly trained and reflected in the peer groups without the presence of a tutor. All invasive skills are practiced only on teaching dummies. This allows students to use all their potential. The students may access learning materials as literature and their own student notes. This allows nursing students to practice their skills and to deepen their knowledge on corresponding with their own learning rate. Results: Peer group discussions during the independent peer practice learning support the students in gaining certainty and confidence in their knowledge and skills. This may improve patient safety in future daily care practice. Descriptive statics show that the number of students who take advantage of the independent peer practice learning increased continuously (2012-2018). It has to be mentioned that in 2012, solely students of the first semester attended the independent peer practice learning program, while in 2018 over one-third of the participating students were in their fifth semester and final study year. It is clearly visible that the demand for independent peer practice learning is increasing. This has to be considered in the development of future teaching curricula.

Keywords: learning program, nursing students, peer learning, skill training

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Authors: Mohammad Arabi

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The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

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Authors: Marlies Achenbach

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System competencies play a key role to ensure an effective and efficient improvement of production systems. Thus, there can be observed an increasing demand for developing system competencies in industry as well as in engineering education. System competencies consist of the following two main abilities: Evaluating the current state of a production system and developing a target state. The innovative course ‘multi-perspective learning in a real production plant (multi real)’ is developed to create a learning setting that supports the development of these system competencies. Therefore, the setting combines two innovative aspects: First, the Learning takes place in heterogeneous groups formed by students as well as professionals and managers from industry. Second, the learning takes place in a real production plant. This paper presents the innovative didactic concept of ‘multi real’ in detail, which will initially be implemented in October/November 2016 in the industrial engineering, logistics and mechanical master’s program at TU Dortmund University.

Keywords: experiential learning, heterogeneous groups, improving production systems, system competencies

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Authors: Joanne Rieta Miranda

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Learning anatomy and physiology among Deaf Non-Science major students is a challenge. They have this mindset that Anatomy and Physiology are difficult and very technical. In this study, nine (9) deaf students who are business majors were considered. Non-conventional teaching strategies and classroom activities were employed such as cooperative learning, virtual lab, Facebook live, big sky, blood typing, mind mapping, reflections, etc. Of all the activities; the deaf students ranked cooperative learning as the best learning activity. This is where they played doctors. They measured the pulse rate, heart rate and blood pressure of their partner classmate. In terms of mindset, 2 out of 9 students have a growth mindset with some fixed ideas while 7 have a fixed mindset with some growth ideas. All the students passed the course. Three out of nine students got a grade of 90% and above. The teacher was evaluated by the deaf students as very satisfactory with a mean score of 3.54. This means that the learner-centered practices in the classroom are manifested to a great extent.

Keywords: deaf students, learning anatomy and physiology, teaching strategies, learner-entered practices

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Authors: Reda Mankbadi

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In this paper we explore the use of a second-order unstructured-grid, finite-volume code for direct noise prediction. We consider a Mach 1.5 jet impinging on a perpendicular flat plate. Hybrid LES-RANS simulations are used to calculate directly both the flow field and the radiated sound. The ANSYS Fluent commercial code is utilized for the calculations. The acoustic field is obtained directly from the simulations and is compared with the integral approach of Ffowcs Williams-Hawkings (FWH). Results indicate the existence of a preferred radiation angle. The spectrum obtained is in good agreement with observations. This points out to the possibility of handling the effects of complicated geometries on noise radiation by using unstructured second-orders codes.

Keywords: CFD, Ffowcs Williams-Hawkings (FWH), imping jet, ANSYS fluent commercial code, hybrid LES-RANS simulations

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Authors: Fahad Suleiman

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The aim of this paper is to study students’ view on mathematics learning in Katsina State Senior Secondary Schools of Nigeria, such as their conceptions of mathematics, attitudes toward mathematics learning, etc. A questionnaire was administered to a random sample of 1,225 senior secondary two (SS II) students of Katsina State in Nigeria. The data collected showed a clear picture of the hurdles that affect the teaching and learning of mathematics in our schools. Problems such as logistics and operational which include shortage of mathematics teachers, non–availability of a mathematics laboratory, etc. were identified. It also depicted the substantial trends of changing views and attitudes toward mathematics across secondary schools. Students’ responses to the conception of mathematics were consistent and they demonstrated some specific characteristics of their views in learning mathematics. This survey has provided useful information regarding students’ needs and aspirations in mathematics learning for curriculum planners and frontline teachers for future curriculum reform and implementation.

Keywords: attitudes, mathematics, students, teacher

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Authors: Eleni Giouli

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Distance learning provides a flexible approach to education, enabling busy learners to complete their coursework at their own pace, on their own schedule, and from a convenient location. This flexibility combined with a series of other issues; make the benefits of lifelong distance learning numerous. The purpose of the paper is to investigate whether distance education can contribute to the improvement of adult skills in Greece, highlighting in this way the necessity of the lifelong distance learning. To investigate this goal, a questionnaire is constructed and analyzed based on responses from 3,016 attendees of lifelong distance learning programs in the e-learning of the National and Kapodistrian University of Athens in Greece. In order to do so, a series of relationships is examined including the effects of a) the gender, b) the previous educational level, c) the current employment status, and d) the method used in the distance learning program, on the development of new general, technical, administrative, social, cultural, entrepreneurial and green skills. The basic conclusions that emerge after using a binary logistic framework are that the following factors are critical in order to develop new skills: the gender, the education level and the educational method used in the lifelong distance learning program. The skills more significantly affected by those factors are the acquiring new skills in general, as well as acquiring general, language and cultural, entrepreneurial and green skills, while for technical and social skills only gender and educational method play a crucial role. Moreover, routine skills and social skills are not affected by the four factors included in the analysis.

Keywords: adult skills, distance learning, education, lifelong learning

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Authors: Ilham Ihoume, Rachid Tadili, Nora Arbaoui

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The use of solar energy in agricultural applications has gained significant at‎tention ‎‎in recent years as a sustainable and environmentally friendly alternative to ‎‎conventional energy sources. In particular, solar drying of crops has ‎been identified ‎‎as an effective method to preserve agricultural produce while ‎minimizing energy ‎‎consumption and reducing carbon emissions. In this context, the present study ‎‎aims to evaluate the thermo-economic and ecological ‎performance of a solar-electric hybrid greenhouse dryer designed for grape ‎drying. The proposed system ‎‎integrates solar collectors, an electric heater, ‎and a greenhouse structure to create a ‎‎controlled and energy-efficient environment for grape drying. The thermo-economic assessment involves the ‎analysis of the thermal performance, energy ‎‎consumption, and cost-effectiveness of the solar-electric hybrid greenhouse dryer. ‎‎On the other ‎hand, the ecological assessment focuses on the environmental impact ‎‎of the ‎system in terms of carbon emissions and sustainability. The findings of this ‎‎‎study are expected to contribute to the development of sustainable agricultural ‎‎practices and the promotion of renewable energy technologies in the ‎context of ‎‎food production. Moreover, the results may serve as a basis for the ‎design and ‎‎optimization of similar solar drying systems for other crops and ‎regions.‎

Keywords: solar energy, sustainability, agriculture, energy ‎‎analysis‎

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Authors: Amlan Kumar Das, Avinash Marwal, Vikram Pareek

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Liposome plays an important role in medical and pharmaceutical science as e.g. nano scale drug carriers. Liposomes are vesicles of varying size consisting of a spherical lipid bilayer and an aqueous inner compartment. Magnet-driven liposome used for the targeted delivery of drugs to organs and tissues1. These liposome preparations contain encapsulated drug components and finely dispersed magnetic particles. Liposomes are vesicles of varying size consisting of a spherical lipid bilayer and an aqueous inner compartment that are generated in vitro. These are useful in terms of biocompatibility, biodegradability, and low toxicity, and can control biodistribution by changing the size, lipid composition, and physical characteristics2. Furthermore, liposomes can entrap both hydrophobic and hydrophilic drugs and are able to continuously release the entrapped substrate, thus being useful drug carriers. Magnetic liposomes (MLs) are phospholipid vesicles that encapsulate magneticor paramagnetic nanoparticles. They are applied as contrast agents for magnetic resonance imaging (MRI)3. The biological synthesis of nanoparticles using plant extracts plays an important role in the field of nanotechnology4. Green-synthesized magnetite nanoparticles-protein hybrid has been produced by treating Iron (III)/Iron(II) chloride with the leaf extract of Dhatura Inoxia. The phytochemicals present in the leaf extracts act as a reducing as well stabilizing agents preventing agglomeration, which include flavonoids, phenolic compounds, cardiac glycosides, proteins and sugars. The magnetite nanoparticles-protein hybrid has been trapped inside the aqueous core of the liposome prepared by reversed phase evaporation (REV) method using oleic and linoleic acid which has been shown to be driven under magnetic field confirming the formation magnetic liposome (ML). Chemical characterization of stealth magnetic liposome has been performed by breaking the liposome and release of magnetic nanoparticles. The presence iron has been confirmed by colour complex formation with KSCN and UV-Vis study using spectrophotometer Cary 60, Agilent. This magnet driven liposome using nanoparticles-protein hybrid can be a smart vesicles for the targeted drug delivery.

Keywords: nanoparticles-protein hybrid, magnetic liposome, medical, pharmaceutical science

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Authors: Mostert Jacques, Gulseven Osman, Williams Courtney

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The Covid-19 pandemic caused unparalleled disruption in the lives of the majority of the world. This included school closures and introduction of Online Learning. In this article we investigated the impact of distance learning on the self-efficacy and anxiety levels experienced by educators in South Africa. We surveyed 60 respondents from Independent Schools using a Likert Scale rating of 0 to 4. The results suggested that despite experiencing moderate anxiety, educators showed a sense of high self-efficacy during distance learning. This was specifically true for those with underlying health concerns. There was no significant difference between how the different genders experienced anxiety and self-efficacy. Further research into the impact on learners’ anxiety levels during distance learning will provide policymakers and educators with a better understanding of how the use of technology is influencing the effectiveness of teaching, learning, and assessment.

Keywords: COVID-19, education, self-efficacy, anxiety

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Authors: Karen Butler

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Johnson C. Smith University, one of the nation’s oldest Historically Black Colleges and Universities, has a strong history of service learning and community service. We first integrated service learning and peer education into health education courses in the spring of 2000. Students enrolled in the classes served as peer educators for the semester. Since then, the program has evolved and expanded but remains an integral part of several courses. The purpose of this session is to describe our program in terms of development, successes, and obstacles, and feedback received. A detailed description of the service learning component in HED 235: Drugs and Drug Education and HED 337: Environmental Health will be provided. These classes are required of our Community Health majors but are also popular electives for students in other disciplines. Three sources of student feedback were used to evaluate and continually modify the component: the SIR II course evaluation, service learning reflection papers, and focus group interviews. Student feedback has been largely positive. When criticism was given, it was thoughtful and constructive – given in the spirit of making it better for the next group. Students consistently agreed that the service learning program increased their awareness of pertinent health issues; that both the service providers and service recipients benefited from the project; and that the goals/issues targeted by the service learning component fit the objectives of the course. Also, evidence of curriculum and learning enhancement was found in the reflection papers and focus group sessions. Service learning sets up a win-win situation. It provides a way to respond to campus and community health needs while enhancing the curriculum, as students learn more by doing things that benefit the health and wellness of others. Service learning is suitable for any health education course and any target audience would welcome the effort.

Keywords: black colleges, community health, health education, service learning

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Authors: S. Art-in

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This research was a survey research. The objective of this study was to study current situation and need in learning management for developing the analytical thinking of teachers in basic education of Thailand. The target group consisted of 400 teachers teaching in basic education level. They were selected by multi-stage random sampling. The instrument used in this study was the questionnaire asking current situation and need in learning management for developing the analytical thinking, 5 level rating scale. Data were analyzed by calculating the frequency, mean, standard deviation, percentage and content analysis. The research found that: 1) For current situation, the teachers provided learning management for developing analytical thinking, in overall, in “high” level. The issue with lowest level of practice: the teachers had competency in designing and establishing the learning management plan for developing the students’ analytical thinking. Considering each aspect it was found that: 1.1) the teacher aspect; the issue with lowest level of practice was: the teachers had competency in designing and establishing the learning management plan for developing the students’ analytical thinking, and 1.2) the learning management aspect for developing the students’ analytical thinking, the issue with lowest level of practice was: the learning activities provided opportunity for students to evaluate their analytical thinking process in each learning session. 2) The teachers showed their need in learning management for developing the analytical thinking, in overall, in “the highest” level. The issue with highest level of the need was: to obtain knowledge and competency in model, technique, and method for learning management or steps of learning management for developing the students’ analytical thinking. Considering each aspect it was found that: 2.1) teacher aspect; the issue with highest level of the need was: to obtain knowledge and comprehension in model, technique, and method for learning management or steps of learning management for developing the students’ analytical thinking, and 2.2) learning management aspect for developing the analytical thinking, the issue with highest level of need consisted of the determination of learning activities as problem situation, and the opportunity for students to comprehend the problem situation as well as practice their analytical thinking in order to find the answer.

Keywords: current situation and need, learning management, analytical thinking, teachers in basic education level, Thailand

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Authors: Halil Ibrahim Demir, Abdullah Hulusi Kokcam, Fuat Simsir, Özer Uygun

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Traditionally, three important manufacturing functions which are process planning, scheduling and due-date assignment are performed sequentially and separately. Although there are numerous works on the integration of process planning and scheduling and plenty of works focusing on scheduling with due date assignment, there are only a few works on integrated process planning, scheduling and due-date assignment. Although due-dates are determined without taking into account of weights of the customers in the literature, here weighted due-date assignment is employed to get better performance. Jobs are scheduled according to weighted earliest due date dispatching rule and due dates are determined according to some popular due date assignment methods by taking into account of the weights of each job. Simulated Annealing, Evolutionary Strategies, Random Search, hybrid of Random Search and Simulated Annealing, and hybrid of Random Search and Evolutionary Strategies, are applied as solution techniques. Three important manufacturing functions are integrated step-by-step and higher integration levels are found better. Search meta-heuristics are found to be very useful while improving performance measure.

Keywords: process planning, weighted scheduling, weighted due-date assignment, simulated annealing, evolutionary strategies, hybrid searches

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Authors: Victoria Appatova

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internal and external, that are largely shaped by the student’s perceptions. Since 2006, the ELE concept has been studied by an international group of scholars through the creation of an ELE survey which was administered in nine countries and translated into five languages. The survey compares students’ perceptions of their learning environments and self-efficacy across A student’s effective learning environment (ELE) is comprised of multiple factors, both cultures as well as distinguishes similarities and differences in the students’ needs related to their learning. The main objectives of this international project include the following: Determine a system of components constituting ELE from the perspective of students and other academic populations Analyze students’ expectations, and their chances to succeed in college based on their expectations Conceptualize a comprehensive approach for assessing the effectiveness of a learning environment Compare the actualization of the ELE concept in American schools versus other national educational systems Compare student perceptions of ELE with those of faculty, administrators, and professional staff Four major factors influencing student learning across cultures and various national educational systems were determined: students’ initiative in using support services; learning skills; external comfort; and curriculum. Recent changes in the students’ perceptions, resulting from technology advances and a rapid shift to online learning, are being explored. The findings call for administrative and pedagogical actions which would cultivate more equitable education systems.

Keywords: learning environment, student perception, global perspectives, self-efficacy

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Authors: M. Alpaslan Koroglu

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Fibre reinforced polymer (FRP) bridge decks have become an innovative alternative, and they have offered many advantages, and this has been increasing attention for applications in not only reinforcement of existing bridges decks but also construction of new bridges decks. The advantages of these FRP decks are; lightweight, high-strength FRP materials, corrosion resistance. However, this high strength deck is not ductile. In this study, the behaviour of hybrid FRP-steel decks are investigated. All FRP decks was analysed with the commercial package ABAQUS. In the FE model, the webs and flanges were discretised by 4 nodes shell elements. A full composite action between the steel and the FRP composite was assumed in the FE analysis because the bond-slip behaviour was unknown at that time. The performance of the proposed hybrid FRP deck panel with steel plates was evaluated by means of FE analysis.

Keywords: FRP, deck, bridge, finite element

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Authors: Abdulaziz Fageeh

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This study investigates the integration of artificial intelligence (AI) within the landscape of language learning and teaching, exploring its potential benefits and challenges. Employing a mixed-methods approach, the research draws upon a comprehensive literature review, case studies, user reviews, and in-depth interviews with educators and students. Findings demonstrate that AI tools, including language learning apps and writing assistants, can enhance personalization, improve writing skills, and increase accessibility to language learning resources. However, the study also highlights concerns regarding over-reliance on AI, potential accuracy and reliability issues, and ethical implications such as data privacy and potential bias. User and educator perspectives emphasize the importance of balancing AI with traditional teaching methods, fostering critical thinking skills, and addressing potential misuse. The study concludes by underscoring the need for ongoing research and development to ensure responsible AI integration in language learning, focusing on pedagogical strategies, ethical frameworks, and the long-term impact of AI on learning outcomes.

Keywords: artificial intelligence, language learning, education, technology, ethical considerations, user perceptions

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Authors: Luma Al-Tamimi, Hassan Farhat, Wessam Hasan

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A three-dimensional (3D) hybrid quasi-steady thermal lattice Boltzmann model is developed to couple the effects of surfactant, temperature, interfacial tension, and contact angle. This 3D model is an extended scheme of a previously introduced two-dimensional (2D) hybrid lattice Boltzmann model. The 3D model is used to study the combined multi-physics effects on emulsion systems flowing in rectangular microchannels with and without confinements, where the suspended phase is made of droplets, plugs, or a mixture of both. The simulation results show that emulsion systems with plugs as the suspended phase are more efficient than with droplets, whereas mixed systems that form large plugs through coalescence have even greater efficiency. The 3D contact angle model generates matching results to those of the 2D model, which were validated with experiments. Furthermore, the effects of various confinements on adhering single drop systems are investigated for delineating their influence on the power required for transporting the suspended phase through the channel. It is shown that the deeper the constriction is, the lower the system efficiency. Increasing the surfactant concentration or fluid temperature in a channel with confinement carries a substantial positive effect on oil droplet transportation.

Keywords: lattice Boltzmann method, thermal, contact angle, surfactants, high viscosity ratio, porous media

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Authors: Anjalika Fernando, Banuka Athuraliya

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This paper presents a comprehensive approach for converting Sinhala Sign Language (SSL) into grammatically correct sentences using Natural Language Processing (NLP) techniques in real-time. While previous studies have explored various aspects of SSL translation, the research gap lies in the absence of grammar checking for SSL. This work aims to bridge this gap by proposing a two-stage methodology that leverages deep learning models to detect signs and translate them into coherent sentences, ensuring grammatical accuracy. The first stage of the approach involves the utilization of a Long Short-Term Memory (LSTM) deep learning model to recognize and interpret SSL signs. By training the LSTM model on a dataset of SSL gestures, it learns to accurately classify and translate these signs into textual representations. The LSTM model achieves a commendable accuracy rate of 94%, demonstrating its effectiveness in accurately recognizing and translating SSL gestures. Building upon the successful recognition and translation of SSL signs, the second stage of the methodology focuses on improving the grammatical correctness of the translated sentences. The project employs a Neural Machine Translation (NMT) architecture, consisting of an encoder and decoder with LSTM components, to enhance the syntactical structure of the generated sentences. By training the NMT model on a parallel corpus of Sinhala wrong sentences and their corresponding grammatically correct translations, it learns to generate coherent and grammatically accurate sentences. The NMT model achieves an impressive accuracy rate of 98%, affirming its capability to produce linguistically sound translations. The proposed approach offers significant contributions to the field of SSL translation and grammar correction. Addressing the critical issue of grammar checking, it enhances the usability and reliability of SSL translation systems, facilitating effective communication between hearing-impaired and non-sign language users. Furthermore, the integration of deep learning techniques, such as LSTM and NMT, ensures the accuracy and robustness of the translation process. This research holds great potential for practical applications, including educational platforms, accessibility tools, and communication aids for the hearing-impaired. Furthermore, it lays the foundation for future advancements in SSL translation systems, fostering inclusive and equal opportunities for the deaf community. Future work includes expanding the existing datasets to further improve the accuracy and generalization of the SSL translation system. Additionally, the development of a dedicated mobile application would enhance the accessibility and convenience of SSL translation on handheld devices. Furthermore, efforts will be made to enhance the current application for educational purposes, enabling individuals to learn and practice SSL more effectively. Another area of future exploration involves enabling two-way communication, allowing seamless interaction between sign-language users and non-sign-language users.In conclusion, this paper presents a novel approach for converting Sinhala Sign Language gestures into grammatically correct sentences using NLP techniques in real time. The two-stage methodology, comprising an LSTM model for sign detection and translation and an NMT model for grammar correction, achieves high accuracy rates of 94% and 98%, respectively. By addressing the lack of grammar checking in existing SSL translation research, this work contributes significantly to the development of more accurate and reliable SSL translation systems, thereby fostering effective communication and inclusivity for the hearing-impaired community

Keywords: Sinhala sign language, sign Language, NLP, LSTM, NMT

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Authors: Gunawan Muhammad, Takashi Atsumi, Akira Komaru

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Pinctada fucata has been the most important pearl culture species in Japan and known as Japanese Akoya Pearl Oyster. However, during summer 1994, mass mortality devastated pearl culture in most parts of Japan. Therefore, pearl farmers started to import Chinese Pearl Oysters from Hainan Island that came from the same species because they are believed to be more resistant towards high water temperature, despite their lack of ability in producing high-quality pearls. The local farmers were then hybridized Japanese and Chinese pearl oysters and currently known as Hybrid pearl oysters, as an attempt to produce a new oyster's strain which is more resistant towards high temperature but also able to produce higher quality pearls. However, despite both strains were implanted by mantle tissues from the same group of donors, the thickness of pearl nacre produced by both strains was different, even though tablet thickness shows a rather similar pattern. Hence, this leads to a question of whether mother oysters play a major role in both nacre deposition rate and tablet thickness of pearls or not. This study first describes the nacre deposition rate of the shells of Japanese and Hybrid mother oysters towards the water temperature condition in Ago Bay, Mie Prefecture, Japan. Later, a comparative study was conducted among 4 shell positions that had been chosen according to the mantle tissue location and shell growth directions. A correlative study was then taken between shells and pearls nacre deposition rate to know whether mother oyster ability in depositing nacre on their shells is related to that of pearls. All the four shell positions were significantly different in shell nacre growth rate (Kruskal-Wallis, p-value < 0.05), and the third position have faster nacre growth among the other three both in Japanese and Hybrid strains, especially in warm temperature. The ability to deposit nacre between Japanese and Hybrid during warm water conditions (August and September) is also significantly different in almost all positions (Mann Whitney U, p-value < 0.01), Japanese oyster growth faster than Hybrid in all four positions. This leads to a different total growth among the two strains and a higher possibility of thicker nacre thickness in Japanese shell nacre. Tablet thickness is significantly different among all positions of shells (Kruskal-Wallis, p-value < 0.01), the 2nd position deposited rather thinner tablet thickness than the other three, including on the 6th month of culture which is more desirable in producing pearls with good luster. This result gives us new information that pearl growth rate is highly affected by the mother oysters; however, nacre tablet thickness might be the result of the shell matrix expressed by different mantle position from donor oysters.

Keywords: nacre, deposition, biomineralization, pearl aquaculture, pearl oyster, Akoya pearl, pearl

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Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma, K. Jagannath, Achutha Kini U.

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In the present study, response surface methodology has been used to optimize turn-assisted deep cold rolling process of AISI 4140 steel. A regression model is developed to predict surface hardness and surface roughness using response surface methodology and central composite design. In the development of predictive model, deep cold rolling force, ball diameter, initial roughness of the workpiece, and number of tool passes are considered as model variables. The rolling force and the ball diameter are the significant factors on the surface hardness and ball diameter and numbers of tool passes are found to be significant for surface roughness. The predicted surface hardness and surface roughness values and the subsequent verification experiments under the optimal operating conditions confirmed the validity of the predicted model. The absolute average error between the experimental and predicted values at the optimal combination of parameter settings for surface hardness and surface roughness is calculated as 0.16% and 1.58% respectively. Using the optimal processing parameters, the hardness is improved from 225 to 306 HV, which resulted in an increase in the near surface hardness by about 36% and the surface roughness is improved from 4.84µm to 0.252 µm, which resulted in decrease in the surface roughness by about 95%. The depth of compression is found to be more than 300µm from the microstructure analysis and this is in correlation with the results obtained from the microhardness measurements. Taylor Hobson Talysurf tester, micro Vickers hardness tester, optical microscopy and X-ray diffractometer are used to characterize the modified surface layer.

Keywords: hardness, response surface methodology, microstructure, central composite design, deep cold rolling, surface roughness

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Authors: Yinghui Shang, Ziqing Zhou, Rong Han, Hang Wang, Xiaodi Liu, Yong Yang

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The design of advanced amorphous solids, such as metallic glasses, with targeted properties through artificial intelligence signifies a paradigmatic shift in physical metallurgy and materials technology. Here, we developed a machine-learning architecture that facilitates the generation of metallic glasses with targeted multifunctional properties. Our architecture integrates the state-of-the-art unsupervised generative adversarial network model with supervised models, allowing the incorporation of general prior knowledge derived from thousands of data points across a vast range of alloy compositions, into the creation of data points for a specific type of composition, which overcame the common issue of data scarcity typically encountered in the design of a given type of metallic glasses. Using our generative model, we have successfully designed copper-based metallic glasses, which display exceptionally high hardness or a remarkably low modulus. Notably, our architecture can not only explore uncharted regions in the targeted compositional space but also permits self-improvement after experimentally validated data points are added to the initial dataset for subsequent cycles of data generation, hence paving the way for the customized design of amorphous solids without human intervention.

Keywords: metallic glass, artificial intelligence, mechanical property, automated generation

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Authors: Jude Harrison

Abstract:

Child protection is a complex and sensitive practice. The core responsibility is the care and protection of children and young people who have been subject to or who are at risk from abuse and neglect. The work involves investigating allegations of harm, preparing for and making representations to the legal system, and case planning and management across a continuum of complicated care interventions. Professionals’ learning for child protection practice is evident in a range of literature investigating multiple learning processes such as university preparation, student placements, professional supervision, training, and other post-qualifying professional development experiences at work. There is, however, very limited research into how caseworkers learn in and through their daily practice. Little is known, therefore, about how learning at work unfolds for caseworkers, the dimensions in which it can be understood or the ways in which it can be best facilitated and supported. Compounding this, much of the current child protection learning literature reflects an orthodox conception of learning as mentalistic and individualised, in which knowledge is typically understood as abstract theory or as technical skill or competency. This presentation outlines key findings from a PhD research study that explored learning at work for statutory child protection caseworkers from an alternative interpretation of learning using a practice theory approach. Practice theory offers an interpretation of learning as performative and grounded in situated experience. The findings of the study show that casework practice is both a mode and site of learning. The study was ethnographic in design based and followed 17 child protection caseworkers via in-depth interviews, observations and participant reflective journaling. Inductive and abductive analysis was used to organise and interpret the data and expand analysis, leading to themes. Key findings show learning to be a sociomaterial property of doing; the social ontological character of learning; and teleoaffectivity as a feature of learning. The findings contribute to theoretical and practical understandings of learning and practice in child protection, child welfare and the professional learning literature more broadly. The findings have potential to contribute to policy directions at state, territory and national levels to enhance child protection practice and systems.

Keywords: adiult learning, workplace learning, child welfare, sociomaterial, practice theory

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Authors: H. Aoudia, Y. Touati, E. H. Teguig, A. Ali Cherif

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Conceiving and developing routing protocols for wireless sensor networks requires considerations on constraints such as network lifetime and energy consumption. In this paper, we propose a hybrid hierarchical routing protocol named HHRP combining both clustering mechanism and multipath optimization taking into account residual energy and RSSI measures. HHRP consists of classifying dynamically nodes into clusters where coordinators nodes with extra privileges are able to manipulate messages, aggregate data and ensure transmission between nodes according to TDMA and CDMA schedules. The reconfiguration of the network is carried out dynamically based on a threshold value which is associated with the number of nodes belonging to the smallest cluster. To show the effectiveness of the proposed approach HHRP, a comparative study with LEACH protocol is illustrated in simulations.

Keywords: routing protocol, optimization, clustering, WSN

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Authors: Akshit Singhal, Xuan Wang, Zhijun Wang, Hao Che, Hong Jiang

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Multiple Path Transmission Control Protocols (MPTCPs) allow flows to explore path diversity to improve the throughput, reliability and network resource utilization. However, the existing solutions may discourage users to adopt the solutions in the face of multipath scenario where different paths are charged based on different pricing structures, e.g., WiFi vs cellular connections, widely available for mobile phones. In this paper, we propose a Hybrid MPTCP (H-MPTCP) with a built-in mechanism to incentivize users to use multiple paths with different pricing structures. In the meantime, H-MPTCP preserves the nice properties enjoyed by the state-of-the-art MPTCP solutions. Extensive real Linux implementation results verify that H-MPTCP can indeed achieve the design objectives.

Keywords: network, TCP, WiFi, cellular, congestion control

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Authors: Jin Uk Han, Hye Won Han, Hyo Lim Kang, Tae An Kim, Seung Ho Han

Abstract:

Direct-drive generators for large-scale wind turbine, which are divided into AFPM(Axial Flux Permanent Magnet) and RFPM(Radial Flux Permanent Magnet) type machine, have attracted interest because of a higher energy density in comparison with gear train type generators. Each type of the machines provides distinguishable geometrical features such as narrow width with a large diameter for the AFPM-type machine and wide width with a certain diameter for the RFPM-type machine. When the AFPM-type machine is applied, an increase of electric power production through a multi-stage arrangement in axial direction is easily achieved. On the other hand, the RFPM-type machine can be applied by using its geometric feature of wide width. In this study, a hybrid two-stage direct-drive generator for 6.2MW class wind turbine was proposed, in which the two-stage AFPM-type machine for 5 MW was composed of two models arranged in axial direction with a hollow shape topology of the rotor with annular disc, the stator and the main shaft mounted on coupled slew bearings. In addition, the RFPM-type machine for 1.2MW was installed at the empty space of the rotor. Analytic results obtained from an electro-magnetic and structural interaction analysis showed that the structural weight of the proposed hybrid two-stage direct-drive generator can be achieved as 155tonf in a condition satisfying the requirements of structural behaviors such as allowable air-gap clearance and strength. Therefore, it was sure that the 6.2MW hybrid two-stage direct-drive generator is competitive than conventional generators. (NRF grant funded by the Korea government MEST, No. 2017R1A2B4005405).

Keywords: AFPM-type machine, direct-drive generator, electro-magnetic analysis, large-scale wind turbine, RFPM-type machine

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Authors: Vincent Liu

Abstract:

Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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Authors: Nanyonjo Juliet

Abstract:

Across Sub-Saharan Africa, it’s increasingly becoming an absolute necessity for either parents or governments to encourage learners, most particularly those attending high schools, to study a second or foreign language other than the “official language” or the language of instruction in schools. The major second or foreign languages under consideration include but are not necessarily limited to English, French, German, Arabic, Swahili/Kiswahili, Spanish and Chinese. The benefits of learning a second (foreign) language in the globalized world cannot be underestimated. Amongst others, it has been expounded to especially involve such opportunities related to traveling, studying abroad and widening one’s career prospects. Research has also revealed that beyond these non-cognitive rewards, learning a second language enables learners to become more thoughtful, considerate and confident, make better decisions, keep their brain healthier and generally – speaking, broaden their world views. The methodology of delivering a successful 2nd language – learning process by a professionally qualified teacher is located in motivation. We strongly believe that the psychology involved in teaching a foreign language is of paramount importance to a learner’s successful learning experience. The aim of this paper, therefore, is to explore and show the importance of motivation in the teaching and learning of a given 2nd (foreign) language in the local Ugandan high schools.

Keywords: second language, foreign language, language learning, language teaching, official language, language of instruction, globalized world, cognitive rewards, non-cognitive rewards, learning process, motivation

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Authors: Mahalingam Palaniandi

Abstract:

Higher education plays vital role in the nation building process for a country and the rest of world. The higher education sector develops the change-agents for the various fields which will help the human-kind wheel to run further. Conventional and traditional class-room based learning and teaching was followed in many decades which is one-to-one and one-to-many. In a way, these are simplest form of learners to be assembled in a class room wherein the teacher used the blackboard to demonstrate the theory and laboratories used for practical. As the technology evolved tremendously for the last 40 years, the teaching and learning environment changed slowly, wherein, the learning community will be anywhere in the world and teacher deliver the content through internet based tools such as video conferencing, web based conferencing tools or E-learning platforms such as Blackboard or noodle. Present day, the mobile technologies plays an important tool to deliver the teaching content on-the-go. Both PC based and mobile based learning technology brought the learning and teaching community together in various aspects. However, as the learning technology also brought various hurdles for learning processes such as plagiarism and not using the reference books entirely as most of the students wants the information instantaneously using internet without actually going to the library to take the notes from the millions of the books which are not available online as e-books which result lack of fundamental knowledge of the concepts complex theories. However, technology is inseparable in human life, now-a-days and every part of it contains piece of information technology right from computers to home appliances. To make use of the IT based learning and teaching at most efficiency, we should have a proper framework and recommendations laid to the learning community in order to derive the maximum efficiency from the IT based teaching and leaning. This paper discusses various IT based tools available for the learning community, efficiency from its usage and recommendations for the suitable framework that needs to be implemented at higher education institutions which makes the learners stronger in both theory as well as real-time knowledge of their studies that is going to be used in their future for the better world.

Keywords: higher education, e-learning, teaching learning, eLearning tools

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