Search results for: quality of learning

Authors: Hyun-Woo Cho

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The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

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Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

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Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

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Authors: Huey-Yeu Yan, Ching-Ying Lee, Hung-Ru Lin

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Background: Physical assessment is a vital clinical nursing competence. The gap between conventional teaching method and the way e-generation students’ preferred could be bridged owing to the support of Internet technology, i.e. interacting with online media to manage learning works. Nursing instructors in the wake of new learning pattern of the e-generation students are challenged to actively adjust and make teaching contents and methods more versatile. Objective: The objective of this research is to explore the effects on teaching and learning with live webcast-assisted on a specific topic, Physical Assessment technique, on a designated group of young nursing majors. It’s hoped that, with a way of nursing instructing, more versatile learning resources may be provided to facilitate self-directed learning. Design: This research adopts a cross-sectional descriptive survey. The instructor demonstrated physical assessment techniques and operation procedures via live webcast broadcasted online to all students. It increased both the off-time interaction between teacher and students concerning teaching materials. Methods: A convenient sampling was used to recruit a total of 52 nursing-majors at a certain university. The nursing majors took two-hour classes of Physical Assessment per week for 18 weeks (36 hrs. in total). The instruction covered four units with live webcasting and then conducted an online anonymous survey of learning outcomes by questionnaire. The research instrument was the online questionnaire, covering three major domains—online media used, learning outcome evaluation and evaluation result. The data analysis was conducted via IBM SPSS Statistics Version 2.0. The descriptive statistics was undertaken to describe the analysis of basic data and learning outcomes. Statistical methods such as descriptive statistics, t-test, ANOVA, and Pearson’s correlation were employed in verification. Results: Results indicated the following five major findings. (1) learning motivation, about four fifth of the participants agreed the online instruction resources are very helpful in improving learning motivation and raising the learning interest. (2) learning needs, about four fifth of participants agreed it was helpful to plan self-directed practice after the instruction, and meet their needs of repetitive learning and/or practice at their leisure time. (3) learning effectiveness, about two third agreed it was helpful to reduce pre-exam anxiety, and improve their test scores. (4) course objects, about three fourth agreed that it was helpful to achieve the goal of ‘executing the complete Physical Assessment procedures with proper skills’. (5) finally, learning reflection, about all of participants agreed this experience of online instructing, learning, and practicing is beneficial to them, they recommend instructor to share with other nursing majors, and they will recommend it to fellow students too. Conclusions: Live webcasting is a low-cost, convenient, efficient and interactive resource to facilitate nursing majors’ motivation of learning, need of self-directed learning and practice, outcome of learning. When live webcasting is integrated into nursing teaching, it provides an opportunity of self-directed learning to promote learning effectiveness, as such to fulfill the teaching objective.

Keywords: innovative teaching, learning effectiveness, live webcasting, physical assessment technique

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Authors: Amer Obaid Saud

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Water quality index (WQI) is considered as an effective tool in categorization of water resources for its quality and suitability for different uses. The Canadian version of water quality index (CCME WQI) which based on the comparison of the water quality parameters to regulatory standards and give a single value to the water quality of a source was applied in this study to assess the water quality of Euphrates river in Iraq at Babylon Governorate north of Baghdad and determine its suitability for aquatic environment (GWQI), drinking water (PWSI) and irrigation(IWQI). Five stations were selected on the river in Babylon (Euphrates River/AL-Musiab, Hindia barrage, two stations at Hilla city and the fifth station at Al-Hshmeya north of Hilla. Fifteen water samples were collected every month during August 2013 to July 2014 at the study sites and analyzed for the physico-chemical parameters like (Temperature, pH, Electrical Conductivity, Total Dissolved Solids(TDS), Total Suspended Solids(TSS), Total Alkalinity, Total Hardness, Calcium and Magnesium Concentration, some of nutrient like Nitrite, Nitrate, Phosphate also the study of concentration of some heavy metals (Fe, Pb, Zn, Cu, Mn, and Cd) in water and comparison of measures to benchmarks such as guidelines and objectives to assess change in water quality. The result of Canadian version of(CCME .WQI) to assess the irrigation water quality (IWQI) of Euphrates river was (83-good) at site one during second seasonal period while the lowest was (66-Fair) in the second station during the fourth seasonal period, the values of potable water supply index (PWSI)that the highest value was (68-Fair) in the fifth site during the second period while the lowest value (42 -Poor) in the second site during the first seasonal period,the highest value for general water quality (GWQI) was (74-Fair) in site five during the second seasonal period, the lowest value (48-Marginal) in the second site during the first seasonal period. It was observed that the main cause of deterioration in water quality was due to the lack of, unprotected river sites ,high anthropogenic activities and direct discharge of industrial effluent.

Keywords: Babylon governorate, Canadian version, water quality, Euphrates river

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Authors: Levan Sabauri

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Audit is an independent inspection of the financial statement of the audited person and expresses the opinion of an auditor on the reliability of this statement. The auditor’s activity (auditor’s service) is realized by auditing organizations, individual auditors in connection to conduction of an audit and rendering of audit accompanying services. The profession of auditor means a high level of responsibility for rendered service. Results of decisions made by information users depend on the quality of the auditor’s conclusion. Owners, investors, creditors, and society rely on the opinion of the auditor under the condition that inspection was conducted with good quality. Therefore, the existence of the well-functioning audit quality control system for the administering of the audit is an important issue. An efficient audit quality control system is a substantial challenge that many countries face worldwide, especially those states where these systems are being formed within the respective reform program. The presented article reflects on the best practices of the leading countries, the assumptions and recommendations for the financial accounting, reporting and audit; current reforms in Georgia are made based on this comparative analysis.

Keywords: audit quality control, audit program, financial statement, perspective analysis

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Authors: Mingming Leng

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Wal-Mart has allocated considerable human resources for its quality assurance program, in which the largest retailer serves its supply chains as a quality gatekeeper. Asda Stores Ltd., the second largest supermarket chain in Britain, is now investing £27m in significantly increasing the frequency of quality control checks in its supply chains and thus enhancing quality across its fresh food business. Moreover, Tesco, the largest British supermarket chain, already constructed a quality assessment center to carry out its gatekeeping responsibility. Motivated by the above practices, we consider a supply chain in which a retailer plays the gatekeeping role in quality assurance by identifying defects among a manufacturer's products prior to selling them to consumers. The impact of a retailer's gatekeeping activity on pricing and quality assurance in a supply chain has not been investigated in the operations management area. We draw a number of managerial insights that are expected to help practitioners judiciously consider the quality gatekeeping effort at the retail level. As in practice, when the retailer identifies a defective product, she immediately returns it to the manufacturer, who then replaces the defect with a good quality product and pays a penalty to the retailer. If the retailer does not recognize a defect but sells it to a consumer, then the consumer will identify the defect and return it to the retailer, who then passes the returned 'unidentified' defect to the manufacturer. The manufacturer also incurs a penalty cost. Accordingly, we analyze a two-stage pricing and quality decision problem, in which the manufacturer and the retailer bargain over the manufacturer's average defective rate and wholesale price at the first stage, and the retailer decides on her optimal retail price and gatekeeping intensity at the second stage. We also compare the results when the retailer performs quality gatekeeping with those when the retailer does not. Our supply chain analysis exposes some important managerial insights. For example, the retailer's quality gatekeeping can effectively reduce the channel-wide defective rate, if her penalty charge for each identified de-fect is larger than or equal to the market penalty for each unidentified defect. When the retailer imple-ments quality gatekeeping, the change in the negotiated wholesale price only depends on the manufac-turer's 'individual' benefit, and the change in the retailer's optimal retail price is only related to the channel-wide benefit. The retailer is willing to take on the quality gatekeeping responsibility, when the impact of quality relative to retail price on demand is high and/or the retailer has a strong bargaining power. We conclude that the retailer's quality gatekeeping can help reduce the defective rate for consumers, which becomes more significant when the retailer's bargaining position in her supply chain is stronger. Retailers with stronger bargaining powers can benefit more from their quality gatekeeping in supply chains.

Keywords: bargaining, game theory, pricing, quality, supply chain

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Authors: Bahia Braktia, Ana Marcela Montenegro Sanchez

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Social media, such as Facebook, Twitter, and YouTube, has been used for teaching and learning for quite some time. These platforms have been proven to be a good tool to improve various language skills, students’ performance of the English language, motivation as well as trigger the authentic language interaction. However, little is known about the potential effects of social media usage on the learning performance of Arabic language learners. The present study explores the potential role that the social media technologies play in learning Arabic as a foreign language at a university in Southeast of United States. In order to investigate this issue, an online survey was administered to examine the perceptions and attitudes of American students learning Arabic. The research questions were: How does social media, specifically Facebook and Twitter, impact the students' Arabic language skills, and what is their attitude toward it? The preliminary findings of the study showed that students had a positive attitude toward the use of social media to enhance their Arabic language skills, and that they used a range of social media features to expose themselves to the Arabic language and communicate in Arabic with native Arabic speaking friends. More detailed findings will be shared in the light data analysis with the audience during the presentation.

Keywords: foreign language learning, social media, students’ perceptions, survey

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Authors: Teja Koduru

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Untreated Lyme disease can lead to neurological, cardiac, and dermatological complications. Rapid diagnosis of the erythema migrans (EM) rash, a characteristic symptom of Lyme disease is therefore crucial to early diagnosis and treatment. In this study, we aim to utilize deep learning frameworks including Tensorflow and Keras to create deep convolutional neural networks (DCNN) to detect images of acute Lyme Disease from images of erythema migrans. This study uses a custom database of erythema migrans images of varying quality to train a DCNN capable of classifying images of EM rashes vs. non-EM rashes. Images from publicly available sources were mined to create an initial database. Machine-based removal of duplicate images was then performed, followed by a thorough examination of all images by a clinician. The resulting database was combined with images of confounding rashes and regular skin, resulting in a total of 683 images. This database was then used to create a DCNN with an accuracy of 93% when classifying images of rashes as EM vs. non EM. Finally, this model was converted into a web and mobile application to allow for rapid diagnosis of EM rashes by both patients and clinicians. This tool could be used for patient prescreening prior to treatment and lead to a lower mortality rate from Lyme disease.

Keywords: Lyme, untreated Lyme, erythema migrans rash, EM rash

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Authors: Robert John Godby

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To be responsive now and in the future, workplaces must address the demands of multicultural teams as they become more common elements of the global labor force. This is especially the case for aged care due to the aging population, industry growth and migrant recruitment. This research identifies influences on and improvements for learning in these environments. Its unique contribution is to illuminate how culturally diverse workplaces can work and learn together more effectively. A mixed-methods approach was used to gather data about this topic in two phases. Firstly, the research methods included a survey of 102 aged care workers around Australia from two multi-site aged care organisations. The questionnaire elicited both quantitative and qualitative data about worker characteristics and perspectives on working and learning in aged care. Secondly, a case study of one aged care worksite was formulated drawing on worksite information and interviews with workers. A review of the literature suggests that learning in multicultural work environments is influenced by three main factors: 1) the individual workers themselves, 2) their interaction with each other and 3) the environment in which they work. There are various accounts of these three factors, how they are manifested and how they lead to a change in workers’ disposition, knowledge, or expertise when confronted with new circumstances. The study has found that a key individual factor influencing learning is cultural background. Their unique view of the world was shown to affect their approach to both their work and co-working. Interactional factors suggest that the high requirement for collaboration in aged care positively supports learning in this context; however, it can be hindered by cultural bias and spoken accent. The study also found that environmental factors, such as disruptions caused by the pandemic, were another key influence. For example, the need to wear face masks hindered the communication needed for workplace learning. This was especially challenging due to the diverse language backgrounds and abilities within the teams. Potential improvements for learning in multicultural aged care work environments were identified. These include more frequent and structured inter-peer learning (e.g. buddying), communication training (e.g. English language usage for both native and non-native speaking workers) and support for cross-cultural habitude (e.g. recognizing and adapting to cultural differences). Workplace learning in cross-cultural aged care environments is an area that is not extensively dealt with in the literature. This study addresses this gap and holds the potential to contribute practical insights to aged care and other diverse industries.

Keywords: cross-cultural learning, learning in aged care, migrant learning, workplace learning

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Authors: Julie Wittmannová, Petr Šeda

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Quality of life measurements (QLF) help to evaluate interventions programs in different groups of persons with special needs. Our presentation deals with QLF of persons with addiction in relation to the physical activity (PA), type of addiction, age, gender and other variables. The aim of presentation is to summarize the basic findings and offer thoughts for questions arose. Methods: SQUALA (Subjective Quality of Life Analysis); SEIQoL (Schedule for the Evaluation of Individual Quality of Life); questionnaire of own construction. The results are evaluated by Mann­Whitney U test and Kruskall­Wallis ANOVA test (p ≤ 0,05). Sample of 64 participants – clients of aftercare center, aged 18 plus. Findings: Application of the methods SQUALA and SEIQoL in the chosen population seems appropriate, the obtaining information regarding the QLF correlate to intervention program topics, the need of an activelifestyle and health related topics in persons with addiction is visible. Conclusions or Implications: The subjective evaluation of quality of life of Aftercare clients is an important part of evaluation process, especially used to evaluate satisfaction with offered services and programs. Techniques SQUALA and SEIQoL gave us the desired outcomes.

Keywords: adapted physical activity, addiction, quality of life, physical activity, aftercare

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Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli

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Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.

Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning

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Authors: C.W. Kan

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Softening applied on textile products based on several reasons. First, the synthetic detergent removes natural oils and waxes, thus lose the softness. Second, compensate the harsh handle of resin finishing. Also, imitate natural fibres and improve the comfort of fabric are the reasons to apply softening. There are different types of softeners for softening finishing of textiles, nonionic softener, anionic softener, cationic softener and silicone softener. The aim of this study is to illustrate the proper application of different softeners and their final softening effect in textiles. The results could also provide guidance note to the students in learning this topic. Acknowledgment: Authors would like to thank the financial support from the Hong Kong Polytechnic University for this work.

Keywords: learning materials, softening, textiles, effect

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Authors: Imen Elleuch, Wael Ouarda, Gargouri Bilel

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We proposes in this paper a Deep Learning based approach to classify text in order to enrich an Arabic ontology based on the objects classes of Gaston Gross. Those object classes are defined by taking into account the syntactic and semantic features of the treated language. Thus, our proposed approach is a hybrid one. In fact, it is based on the one hand on the object classes that represents a knowledge based-approach on classification of text and in the other hand it uses the deep learning approach that use the word embedding-based-approach to classify text. We have applied our proposed approach on a corpus constructed from an Arabic dictionary. The obtained semantic classification of text will enrich the Arabic objects classes ontology. In fact, new classes can be added to the ontology or an expansion of the features that characterizes each object class can be updated. The obtained results are compared to a similar work that treats the same object with a classical linguistic approach for the semantic classification of text. This comparison highlight our hybrid proposed approach that can be ameliorated by broaden the dataset used in the deep learning process.

Keywords: deep-learning approach, object-classes, semantic classification, Arabic

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Authors: Maiya Smith, Tyler Thorne

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Background: The Pacific faces multiple healthcare crises, including high rates of noncommunicable diseases, infectious disease outbreaks, and susceptibility to natural disasters. These issues are expected to worsen in the coming decades, increasing the burden on an already understaffed healthcare system. Telehealth is not new to the Pacific, but improvements in technology and accessibility have increased its utility and have already proven to reduce costs and increase access to care in remote areas. Telehealth includes distance learning; a form of education that can help alleviate many healthcare issues by providing continuing education to healthcare professionals and upskilling staff, while decreasing costs. This study examined distance learning programs at the Ministry of Health in the Pacific nation of Palau and identified key elements to their successful distance learning programs. Methods: Staff at the Belau National Hospital in Koror, Palau as well as private practitioners were interviewed to assess distance learning programs utilized. This included physicians, IT personnel, public health members, and department managers of allied health. In total, 36 people were interviewed. Standardized questions and surveys were conducted in person throughout the month of July 2019. Results: Two examples of successful distance learning programs were identified. Looking at the factors that made these programs successful, as well as consulting with staff who undertook other distance learning programs, four factors for success were determined: having a cohort, having a facilitator, dedicated study time off from work, and motivation. Discussion: In countries as geographically isolated as the Pacific, with poor access to specialists and resources, telehealth has the potential to radically change how healthcare is delivered. Palau shares similar resources and issues as other countries in the Pacific and the lessons learned from their successful programs can be adapted to help other Pacific nations develop their own distance learning programs.

Keywords: distance learning, Pacific, Palau, telehealth

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Authors: Wade Ghribi, Abdelmoty M. Ahmed, Ahmed Said Badawy, Belgacem Bouallegue

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In higher education institutions, the most pressing priority is to improve student performance and retention. Large volumes of student data are used in Educational Data Mining techniques to find new hidden information from students' learning behavior, particularly to uncover the early symptom of at-risk pupils. On the other hand, data with noise, outliers, and irrelevant information may provide incorrect conclusions. By identifying features of students' data that have the potential to improve performance prediction results, comparing and identifying the most appropriate ensemble learning technique after preprocessing the data, and optimizing the hyperparameters, this paper aims to develop a reliable students' performance prediction model for Higher Education Institutions. Data was gathered from two different systems: a student information system and an e-learning system for undergraduate students in the College of Computer Science of a Saudi Arabian State University. The cases of 4413 students were used in this article. The process includes data collection, data integration, data preprocessing (such as cleaning, normalization, and transformation), feature selection, pattern extraction, and, finally, model optimization and assessment. Random Forest, Bagging, Stacking, Majority Vote, and two types of Boosting techniques, AdaBoost and XGBoost, are ensemble learning approaches, whereas Decision Tree, Support Vector Machine, and Artificial Neural Network are supervised learning techniques. Hyperparameters for ensemble learning systems will be fine-tuned to provide enhanced performance and optimal output. The findings imply that combining features of students' behavior from e-learning and students' information systems using Majority Vote produced better outcomes than the other ensemble techniques.

Keywords: educational data mining, student performance prediction, e-learning, classification, ensemble learning, higher education

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Authors: Slava Kalyuga

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There are two opposing major points of view on the optimal degree of initial instructional guidance that is usually discussed in the literature by the advocates of the corresponding learning approaches. Using unguided or minimally guided problem-solving tasks prior to explicit instruction has been suggested by productive failure and several other instructional theories, whereas an alternative approach - using fully guided worked examples followed by problem solving - has been demonstrated as the most effective strategy within the framework of cognitive load theory. An integrated approach discussed in this paper could combine the above frameworks within a broader theoretical perspective which would allow bringing together their best features and advantages in the design of learning tasks for STEM education. This paper represents a systematic review of the available empirical studies comparing the above alternative sequences of instructional methods to explore effects of several possible moderating factors. The paper concludes that different approaches and instructional sequences should coexist within complex learning environments. Selecting optimal sequences depends on such factors as specific goals of learner activities, types of knowledge to learn, levels of element interactivity (task complexity), and levels of learner prior knowledge. This paper offers an outline of a theoretical framework for the design of complex learning tasks in STEM education that would integrate explicit instruction and inquiry (exploratory, discovery) learning approaches in ways that depend on a set of defined specific factors.

Keywords: cognitive load, explicit instruction, exploratory learning, worked examples

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Authors: Jonathan Frank, Michelle Salmona

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We conducted quantitative and qualitative analyses of nurses’ perceived ease of use of electronic medical records and telemedicine in the Cook Islands. We examined antecedents of perceived ease of use through the lens of social construction of learning, and cultural diffusion. Our findings confirmed expected linkages between PEOU, attitudes and intentions. Interviews with nurses suggested infrastructural barriers to engaged learning. We discussed managerial implications of our findings, and areas of interest for future research.

Keywords: health information technology, ICT4D, TAM, developing countries

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Authors: Fiseha M. Guangul, Annissa Muhammed, Aja O. Chikere

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Group task is one method to create the conducive environment for the active teaching-learning process. Performing group task with active involvement of students will benefit the students in many ways. However, in most cases all students do not participate actively in the group task, and hence the intended benefits are not acquired. This paper presents the improvements of students’ participation in the group task and learning from the group task by introducing different techniques to enhance students’ participation. For the purpose of this research Carpentry and Joinery II (WT-392) course from Wood Technology Department at Adama Science and Technology University was selected, and five groups were formed. Ten group tasks were prepared and the first five group tasks were distributed to the five groups in the first day without introducing the techniques that are used to enhance participation of students in the group task. On another day, the other five group tasks were distributed to the same groups and various techniques were introduced to enhance students’ participation in the group task. The improvements of students’ learning from the group task after the implementation of the techniques. After implementing the techniques the evaluation showed that significant improvements were obtained in the students’ participation and learning from the group task.

Keywords: group task, students participation, active learning, the evaluation method

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Authors: Beulah Rani Inbanathan

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In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: Paul Koffitse Agobia

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In 2020 the Ministry of Education in Ghana and the National Council for Curriculum and Assessment (NaCCA) rolled out a new curriculum, Common Core Programme (CCP) for Basic 7 to 10, that lays emphasis on character building and values which are important to the Ghanaian society by providing education that will produce character–minded learners, with problem solving skills, who can play active roles in dealing with the increasing challenges facing Ghana and the global society. Therefore, learning and teaching approaches that prioritise the use of digital learning resources and active learning are recommended. The new challenge facing Ghanaian teachers is the ability to use new technologies together with the appropriate content pedagogical knowledge to help learners develop, aside the communication skills in French, the essential 21st century skills as recommended in the new curriculum. This article focusses on the pedagogical approaches that are recommended by NaCCA. The study seeks to examine French language teachers’ understanding of the recommended pedagogical approaches and how they use digital learning resources in class to foster the development of these essential skills and values. 54 respondents, comprised 30 teachers and 24 head teachers, were selected in 6 Junior High schools in rural districts (both private and public) and 6 from Junior High schools in an urban setting. The schools were selected in three regions: Volta, Central and Western regions. A class observation checklist and an interview guide were used to collect data for the study. The study reveals that some teachers adopt teaching techniques that do not promote active learning. They demonstrate little understanding of the core competences and values, therefore, fail to integrate them in their lessons. However, some other teachers, despite their lack of understanding of learning and teaching philosophies, adopted techniques that can help learners develop some of the core competences and values. In most schools, digital learning resources are not utilized, though teachers have smartphones or laptops.

Keywords: active learning, core competences, digital learning resources, pedagogical approach, values.

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Om Viroje

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Quantum machine learning represents a frontier in computational technology, promising significant advancements in data processing capabilities. This study explores the significance of data encoding techniques, specifically amplitude and phase encoding, in this emerging field. By employing a comparative analysis methodology, the research evaluates how these encoding techniques affect the accuracy, efficiency, and noise resilience of quantum algorithms. Our findings reveal that amplitude encoding enhances algorithmic accuracy and noise tolerance, whereas phase encoding significantly boosts computational efficiency. These insights are crucial for developing robust quantum frameworks that can be effectively applied in real-world scenarios. In conclusion, optimizing encoding strategies is essential for advancing quantum machine learning, potentially transforming various industries through improved data processing and analysis.

Keywords: quantum machine learning, data encoding, amplitude encoding, phase encoding, noise resilience

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Authors: Lailial Muhtifah, Sirtul Marhamah

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This article forwards the conceptual framework of continuous academic lecturer model in Islamic higher education (IHE). It is intended to make a contribution to the broader issue of how the concept of excellence can promote adherence to standards in higher education and drive quality enhancement. This model reveals a process and steps to increase performance and achievement of excellence regular lecturer gradually. Studies in this model are very significant to realize excellence academic culture in IHE. Several steps were identified from previous studies through literature study and empirical findings. A qualitative study was conducted at institute. Administrators and lecturers were interviewed, and lecturers learning communities observed to explore institute culture policies, and procedures. The original in this study presents and called Continuous Academic Lecturer Model (CALM) with its components, namely Standard, Quality, and Excellent as the basis for this framework (SQE). Innovation Excellence Framework requires Leaders to Support (LS) lecturers to achieve a excellence culture. So, the model named CALM-SQE+LS. Several components of performance and achievement of CALM-SQE+LS Model should be disseminated and cultivated to all lecturers in university excellence in terms of innovation. The purpose of this article is to define the concept of “CALM-SQE+LS”. Originally, there were three components in the Continuous Academic Lecturer Model i.e. standard, quality, and excellence plus leader support. This study is important to the community as specific cases that may inform educational leaders on mechanisms that may be leveraged to ensure successful implementation of policies and procedures outline of CALM with its components (SQE+LS) in institutional culture and professional leader literature. The findings of this study learn how continuous academic lecturer is part of a group's culture, how it benefits in university. This article blends the available criteria into several sub-component to give new insights towards empowering lecturer the innovation excellence at the IHE. The proposed conceptual framework is also presented.

Keywords: continuous academic lecturer model, excellence, quality, standard

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Authors: Yi-Cheng Tian, Miin-Shen Yang

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The mixture likelihood approach to clustering is a popular clustering method where the expectation and maximization (EM) algorithm is the most used mixture likelihood method. In the literature, the EM algorithm had been used for mixture regression models. However, these EM mixture regression algorithms are sensitive to initial values with a priori number of clusters. In this paper, to resolve these drawbacks, we construct a learning-based schema for the EM mixture regression algorithm such that it is free of initializations and can automatically obtain an approximately optimal number of clusters. Some numerical examples and comparisons demonstrate the superiority and usefulness of the proposed learning-based EM mixture regression algorithm.

Keywords: clustering, EM algorithm, Gaussian mixture model, mixture regression model

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Authors: Samar Alharbi, Yota Dimitriadi

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The literature on educational technology in Saudi Arabia reveals female learners’ unwillingness to study fully online courses in higher education despite the fact that Saudi universities have offered a variety of online degree programmes to undergraduate students in many regions of the country. The root causes keeping female students from successfully learning in online environments are limited social interaction, lack of motivation and difficulty with the use of e-learning platforms. E-immediacy remains an important method of online teaching to enhance students’ interaction and support their online learning. This study explored Saudi female students’ perceptions, as well as the experiences of lecturers’ immediacy behaviours in online environments, who participate in fully online courses using Blackboard at a Saudi university. Data were collected through interviews with focus groups. The three focus groups included five to seven students each. The female participants were asked about lecturers’ e-immediacy behaviours and which e-immediacy behaviours were important for an effective learning environment. A thematic analysis of the data revealed three main themes: the encouragement of student interaction, the incorporation of social media and addressing the needs of students. These findings provide lecturers with insights into instructional designs and strategies that can be adopted in using e-immediacy in effective ways, thus improving female learners’ interactions as well as their online learning experiences.

Keywords: e-learning, female students, higher education, immediacy

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Authors: Aida Nurul Safitri, Rosita Sari

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Physics is science, which in its learning there are some product such as theory, fact, concept, law and formula. So that to understand physics lesson students not only need a theory or concept but also mathematical calculation to solve physics problem through formula or equation. This is can be taken from mathematics lesson which obtained by students. This research is to know the influence of mathematics learning outcomes towards physics ability in Senior High School through authentic assessment system. Based on the researches have been discussed, is obtained that mathematic lesson have an important role in physics learning but it according to one aspect only, namely cognitive aspect. In Indonesia, curriculum of 2013 reinforces displacement in the assessment, from assessment through test (measuring the competence of knowledge based on the result) toward authentic assessment (measuring the competence of attitudes, skills, and knowledge based on the process and results). In other researches are mentioned that authentic assessment system give positive responses for students to improve their motivation and increase the physics learning in the school.

Keywords: authentic assessment, curriculum of 2013, mathematic, physics

Procedia PDF Downloads 249

Authors: Vinay P., Srinivas K. S.

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Low Light Image Enhancement is of utmost impor- tance in computer vision based tasks. Applications include vision systems for autonomous driving, night vision devices for defence systems, low light object detection tasks. Many of the existing deep learning methods are resource intensive during the inference step and take considerable time for processing. The algorithm should take considerably less than 41 milliseconds in order to process a real-time video feed with 24 frames per second and should be even less for a video with 30 or 60 frames per second. The paper presents a fast and efficient solution which has two main advantages, it has the potential to be used for a real-time video feed, and it can be used in low compute environments because of the lightweight nature. The proposed solution is a pipeline of three steps, the first one is the use of a simple function to map input RGB values to output RGB values, the second is to balance the colors and the final step is to adjust the contrast of the image. Hence a custom dataset is carefully prepared using images taken in low and bright lighting conditions. The preparation of the dataset, the proposed model, the processing time are discussed in detail and the quality of the enhanced images using different methods is shown.

Keywords: low light image enhancement, real-time video, computer vision, machine learning

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Authors: Matthias Nnadi

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Using samples of 250 large listed firms by market capitalization in China and Hong Kong, we conducted empirical test to determine the impact of regulatory environment on reporting quality following IFRS convergence using three financial reporting measures; earning management, timely loss recognition and value relevance. Our results indicate that accounting data are more value relevant for Hong Kong listed firms than the Chinese A-share firms. The empirical results for timely loss recognition further reveal that there is a larger coefficient estimate on bad news earnings, which suggests that Chines A-share firms are more likely to report losses in a timely manner. The results support the evidence that substantial convergence of IFRS can improve financial reporting quality in a regulated environment such as China. This further supports the expectation that IFRS are relevant to China and has positive effect on its accounting practice and quality.

Keywords: reporting, quality, earning, loss, relevance, financial, China, Hong Kong

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Authors: Komang Rahayu Indrawati, Ni Wayan Sinthia Widiastuti, Ratna Dewi Santosa

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Today the career of Balinese working women has been highly developed where able to work with loyalty and high professionalism. Career for a woman is one conscious choice and a call of conscience, which provides financial support for her family. Career for women can develop their own potencies, intellectually, and socially, so women feel that their role is meaningful and beneficial for herself and others. Emotional support becomes important to understand certainly for women who have multirole like Balinese working women to meet the demands of their role and also enhancing their work motivation and the quality of work life. This research used quantitative research method with questionnaires dissemination to 120 respondents and analyzed using Multiple Regression Analysis. The purpose of this study was to see the role of emotional support for work motivation and quality of work life in working Balinese women. The results of this study showed that emotional support and work motivation give a significant role in the quality of work life on Balinese working women.

Keywords: Balinese working women, emotional support, quality of work life, work motivation

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Authors: Y. T. Gee, I. N. Umar

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Students’ achievement and motivation in learning English in Malaysia is a worrying trend as it is lagging behind several other countries in Asia. Thus, necessary actions have to be taken by the parties concerned to overcome this problem. The purpose of this research was to study the effects of drill and practice courseware on students’ achievement and motivation in learning English language. A multimedia courseware was developed for this purpose. The independent variable was the drill and practice courseware while the dependent variables were the students’ achievement and motivation. Their achievement was measured using pre-test and post-test scores, while motivation was measured using a questionnaire adapted from Keller’s (1979) Instructional Materials Motivation Scale. A total of 60 students from three vernacular primary schools in a northern state in Malaysia were randomly selected in this study. The findings indicate: (1) a significant difference between the students’ pre-test and post-test scores after using the courseware, (2) no significant difference in the achievement score between male and female students after using the courseware, (3) a significant difference in motivation score between the female and the male students, and (4) while the female students scored significantly higher than the male students in the aspects of relevance, confidence and satisfaction, no significant difference in terms of attention was observed between them. Overall, the findings clearly indicate that although the female students are significantly more motivated than their male students, they are equally good in terms of achievement after learning from the courseware. Through this study, the drill and practice courseware is proven to influence the students’ learning and motivation.

Keywords: courseware, drill and practice, English learning, motivation

Procedia PDF Downloads 308