Search results for: English learning strategies

Authors: Szymon Wojciechowski, Damian Przestacki, Tadeusz Chwalczuk

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The paper is focused on the evaluation of surface integrity formed during turning of Inconel 718 with the application of various laser assistance strategies. The primary objective of the work was to determine the relations between the applied machining strategy and the obtained surface integrity, in order to select the effective cutting conditions allowing the obtainment of high surface quality. The carried out experiment included the machining of Inconel 718 in the conventional turning conditions, as well as during the continuous laser assisted machining and sequential laser assistance. The surface integrity was evaluated by the measurements of machined surface topographies, microstructures and the microhardness. Results revealed that surface integrity of Inconel 718 is strongly affected by the selected machining strategy. The significant improvement of the surface roughness formed during machining of Inconel 718, can be reached by the application of simultaneous laser heating and cutting (LAM).

Keywords: Inconel 718, laser assisted machining, surface integrity, turning

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Authors: Yun-Ju Chiu, Feng-Yi Chen

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Kinematics is the beginning to learn mechanics in physics course. The concept of acceleration plays an important role in learning kinematics. Teachers usually instruct the conception through the formulas and graphs of kinematics and the well-known law F = ma. However, over the past few decades, a lot of researchers reveal numerous students’ difficulties in learning acceleration. One of these difficulties is that students frequently confuse acceleration with velocity and force. Why is the concept of acceleration so difficult to learn? The aim of this study is to understand the conceptual evolution of acceleration through the historical textual analysis. Text analysis and one-to-one interviews with high school students and teachers are used in this study. This study finds the history of science constructed from textbooks is usually quite different from the real evolution of history. For example, most teachers and students believe that the best-known law F = ma was written down by Newton. The expression of the second law is not F = ma in Newton’s best-known book Principia in 1687. Even after more than one hundred years, a famous Cambridge textbook titled An Elementary Treatise on Mechanics by Whewell of Trinity College did not express this law as F = ma. At that time of Whewell, the early mid-nineteenth century Britain, the concept of acceleration was not only ambiguous but also confused with the concept of force. The process of learning the concept of acceleration is analogous to its conceptual development in history. The study from the perspective of historical textual analysis will promote the understanding of the concept learning difficulties, the development of professional physics teaching, and the improvement of the context of physics textbooks.

Keywords: acceleration, textbooks, mechanics, misconception, history of science

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Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

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Safe performance and efficient energy consumption are essential factors for designing a control system. This paper presents a reinforcement learning (RL) model that can be applied to control applications to improve safety and reduce energy consumption. As hardware constraints and environmental disturbances are imprecise and unpredictable, conventional control methods may not always be effective in optimizing control designs. However, RL has demonstrated its value in several artificial intelligence (AI) applications, especially in the field of control systems. The proposed model intelligently monitors a system's success by observing the rewards from the environment, with positive rewards counting as a success when the controlled reference is within the desired operating zone. Thus, the model can determine whether the system is safe to continue operating based on the designer/user specifications, which can be adjusted as needed. Additionally, the controller keeps track of energy consumption to improve energy efficiency by enabling the idle mode when the controlled reference is within the desired operating zone, thus reducing the system energy consumption during the controlling operation. Water temperature control for a hydroponic system is taken as a case study for the RL model, adjusting the variance of disturbances to show the model’s robustness and efficiency. On average, the model showed safety improvement by up to 15% and energy efficiency improvements by 35%- 40% compared to a traditional RL model.

Keywords: control system, hydroponics, machine learning, reinforcement learning

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Authors: Mohammed Ali

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In this paper, evaluation of flexible manufacturing system is made under different manufacturing strategies. The objective of this paper is to test the impact of pallets and routing flexibility on system performance operating at different sequencing rules, dispatching rules and at unbalanced load condition. A computer simulation model is developed to evaluate the effects of aforementioned manufacturing strategies on the make-span performance of flexible manufacturing system. The impact of number of pallets is shown with the different levels of routing flexibility. In this paper, the same manufacturing system is modeled under different combination of sequencing and dispatching rules. A series of simulation experiments are conducted and results analyzed. The result of the simulation shows that there is impact of pallets and routing flexibility on the performance of the system.

Keywords: flexibility, flexible manufacturing system, pallets, make-span, simulation

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Authors: Elham Azimzadeh, Hamidollah Hassanlouei, Hadi Nobari, Georgian Badicu, Jorge Pérez-Gómez, Luca Paolo Ardigò

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Children with cerebral palsy (CP) have weak physical abilities and their limitations may have an effect on performing everyday motor activities. One of the most important and common debilitating factors in CP is the malfunction in the upper extremities to perform motor skills and there is strong evidence that task-specific training may lead to improve general upper limb function among this population. However, augmented feedback enhances the acquisition and learning of a motor task. Practice conditions may alter the difficulty, e.g., the reduced frequency of PG could be more challenging for this population to learn a motor task. So, the purpose of this study was to investigate the effect of physical guidance (PG) on learning a tracking task in children with cerebral palsy (CP). Twenty-five independently ambulant children with spastic hemiplegic CP aged 7-15 years were assigned randomly to five groups. After the pre-test, experimental groups participated in an intervention for eight sessions, 12 trials during each session. The 0% PG group received no PG; the 25% PG group received PG for three trials; the 50% PG group received PG for six trials; the 75% PG group received PG for nine trials; and the 100% PG group, received PG for all 12 trials. PG consisted of placing the experimenter's hand around the children's hand, guiding them to stay on track and complete the task. Learning was inferred by acquisition and delayed retention tests. The tests involved two blocks of 12 trials of the tracking task without any PG being performed by all participants. They were asked to make the movement as accurate as possible (i.e., fewer errors) and the number of total touches (errors) in 24 trials was calculated as the scores of the tests. The results showed that the higher frequency of PG led to more accurate performance during the practice phase. However, the group that received 75% PG had significantly better performance compared to the other groups in the retention phase. It is concluded that the optimal frequency of PG played a critical role in learning a tracking task in children with CP and likely this population may benefit from an optimal level of PG to get the appropriate amount of information confirming the challenge point framework (CPF), which state that too much or too little information will retard learning a motor skill. Therefore, an optimum level of PG may help these children to identify appropriate patterns of motor skill using extrinsic information they receive through PG and improve learning by activating the intrinsic feedback mechanisms.

Keywords: cerebral palsy, challenge point framework, motor learning, physical guidance, tracking task

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Authors: Muhammad Ali

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Cyber-attacks and anomaly detection on the Internet of Things (IoT) infrastructure is emerging concern in the domain of data-driven intrusion. Rapidly increasing IoT risk is now making headlines around the world. denial of service, malicious control, data type probing, malicious operation, DDos, scan, spying, and wrong setup are attacks and anomalies that can affect an IoT system failure. Everyone talks about cyber security, connectivity, smart devices, and real-time data extraction. IoT devices expose a wide variety of new cyber security attack vectors in network traffic. For further than IoT development, and mainly for smart and IoT applications, there is a necessity for intelligent processing and analysis of data. So, our approach is too secure. We train several machine learning models that have been compared to accurately predicting attacks and anomalies on IoT systems, considering IoT applications, with ANOVA-based feature selection with fewer prediction models to evaluate network traffic to help prevent IoT devices. The machine learning (ML) algorithms that have been used here are KNN, SVM, NB, D.T., and R.F., with the most satisfactory test accuracy with fast detection. The evaluation of ML metrics includes precision, recall, F1 score, FPR, NPV, G.M., MCC, and AUC & ROC. The Random Forest algorithm achieved the best results with less prediction time, with an accuracy of 99.98%.

Keywords: machine learning, analysis of variance, Internet of Thing, network security, intrusion detection

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Authors: Joy Chadwick

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There is no doubt that classrooms of today are more complex and diverse than ever before. Preparing teacher candidates to meet these challenges is essential to ensure the retention of teachers within the profession and to ensure that graduates begin their teaching careers with the knowledge and understanding of how to effectively meet the diversity of students they will encounter. Creating inclusive classrooms requires teachers to have a repertoire of effective instructional skills and strategies. Teachers must also have the mindset to embrace diversity and value the uniqueness of individual students in their care. This qualitative study analyzed teacher candidates' experiences as they completed a fourteen-week teaching practicum while simultaneously completing a university course focused on inclusive pedagogy. The research investigated the challenges and successes teacher candidates had in navigating the translation of theory related to inclusive pedagogy into their teaching practice. Applying threshold concept theory as a framework, the research explored the troublesome concepts, liminal spaces, and transformative experiences as connected to inclusive practices. Threshold concept theory suggests that within all disciplinary fields, there exists particular threshold concepts that serve as gateways or portals into previously inaccessible ways of thinking and practicing. It is in these liminal spaces that conceptual shifts in thinking and understanding and deep learning can occur. The threshold concept framework provided a lens to examine teacher candidate struggles and successes with the inclusive education course content and the application of this content to their practicum experiences. A qualitative research approach was used, which included analyzing twenty-nine course reflective journals and six follow up one-to-one semi structured interviews. The journals and interview transcripts were coded and themed using NVivo software. Threshold concept theory was then applied to the data to uncover the liminal or stuck spaces of learning and the ways in which the teacher candidates navigated those challenging places of teaching. The research also sought to uncover potential transformative shifts in teacher candidate understanding as connected to teaching in an inclusive classroom. The findings suggested that teacher candidates experienced difficulties when they did not feel they had the knowledge, skill, or time to meet the needs of the students in the way they envisioned they should. To navigate the frustration of this thwarted vision, they relied on present and previous course content and experiences, collaborative work with other teacher candidates and their mentor teachers, and a proactive approach to planning for students. Transformational shifts were most evident in their ability to reframe their perceptions of children from a deficit or disability lens to a strength-based belief in the potential of students. It was evident that through their course work and practicum experiences, their beliefs regarding struggling students shifted as they saw the value of embracing neurodiversity, the importance of relationships, and planning for and teaching through a strength-based approach. Research findings have implications for teacher education programs and for understanding threshold concepts theory as connected to practice-based learning experiences.

Keywords: inclusion, inclusive education, liminal space, teacher education, threshold concepts, troublesome knowledge

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Authors: Michiko Miyamoto

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This paper empirically investigates whether information technology (IT) strategies, business strategies, and divisions are aligned to meet overall business goals for Korean Small and medium-sized enterprises (SMEs), based on structure based Strategic Alignment Model, and make comparison with those of Japanese SMEs. Using 2,869 valid responses of Korean Human Capital Corporate Panel survey, a result of this study suggests that Korean human resources (HR) departments have a major influence over IT strategy, which is the same as Japanese SMEs, even though their management styles are quite different. As for IT strategy, it is not related to other departments at all for Korean SMEs. The Korean management seems to possess a great power over each division, such as Sales/Service, Research and Development/Technical Experts, HR, and Production.

Keywords: IT-business alignment, structured based strategic alignment model, structural equation model, human resources department

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Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: Marie Alexandre, Jean Bernatchez

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This paper focuses on the complexity of the face-to-face-to-distance learning transition process. Our research action aims to support the process of transition from classroom to distance learning for teachers in higher education with regard to pedagogical practices that can meet the various needs of students using digital learning environments. In Quebec and elsewhere in the world, the advent of digital education is helping to transform teaching, which is significantly changing the role of teachers. While distance education implies a dissociation of teaching and learning to a variable degree in space and time, distance education (DE) is becoming more and increasingly becoming a preferred option for maintaining the delivery of certain programs and providing access to programs and to provide access to quality activities throughout Quebec. Given the impact of teaching practices on educational success, this paper reports on the results of three research objectives: 1) To document teachers' knowledge of teaching in distance education through the design, experimentation and production of a repertoire of the determinants of pedagogical practices in response to students' needs. 2) Explain, according to a gendered logic, the adequacy between the pedagogical practices implemented in distance learning and the response to the profiles and needs expressed by students using digital learning environments; 3) Produce a model of a support approach during the process of transition from classroom to distance learning at the college level. A mixed methodology, i.e., a quantitative component (questionnaire survey) and a qualitative component (explanatory interviews and living lab) was used in cycles that were part of an ongoing validation process. The intervention includes the establishment of a professional collaboration group, webinars training webinars for the participating teachers on the didactic issue of knowledge-teaching in FAD, the didactic use of technologies, and the differentiated socialization models of educational success in college education. All of the tools developed will be used by partners in the target environment as well as by all teacher educators, students in initial teacher training, practicing teachers, and the general public. The results show that access to training leading to qualifications and commitment to educational success reflects the existing links between the people in the educational community. The relational stakes of being present in distance education take on multiple configurations and different dimensions of learning testify to needs and realities that are sometimes distinct depending on the life cycle. This project will be of interest to partners in the targeted field as well as to all teacher trainers, students in initial teacher training, practicing college teachers, and to university professors. The entire educational community will benefit from digital resources in education. The scientific knowledge resulting from this action research will benefit researchers in the fields of pedagogy, didactics, teacher training and pedagogy in higher education in a digital context.

Keywords: action research, didactics, digital learning environment, distance learning, higher education, pedagogy technological, pedagogical content knowledge

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Authors: Malavika Sundararajan

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This study introduces the use of mindfulness techniques in the classroom to make individuals aware of how the creative thinking process works, resulting in more constructive learning and application. Case observation method was utilized within a classroom setting in a graduate class in the Business School. It entailed, briefing the student participants about the use of a template called the dots and depths map, and having them complete it for themselves, compare it to their team members and reflect on the outputs. Finally, they were debriefed about the use of the template and its value to their learning and creative application process. The major finding is the increase in awareness levels of the participants following the use of the template, leading to a subsequent pursuit of diverse knowledge and acquisition of relevant information and not jumping to solutions directly, which increased their overall creative outputs for the given assignment. The significant value of this study is that it can be applied to any classroom on any subject as a powerful mindfulness tool which increases creative problem solving through constructive knowledge building.

Keywords: connecting dots, mindful awareness, constructive knowledge building, learning creatively

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Authors: Gloria Ebere Amadi, Emeka Promise Ugwunwotti

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The study was carried out to determine the strategies for managing fake news for sustainable democracy in Enugu State, Nigeria. Two research questions and two null hypotheses guided the study. A survey research design was used for the study. The population for the study consisted of 100 respondents (from Enugu state House of Assembly). Of the entire population, 24 elected law makers and 76 staff were used; hence there was no sampling since the population was manageable. A 28-item structured questionnaire developed by the researcher was used for data collection. The instrument entitled Managing Fake News Questionnaire (MFNQ) was validated by three experts, two from the Department of Computer Science and one from the Department of Maths and Statistics, all from Enugu State University of Science and Technology. Cronbach Alpha was used to determine the reliability coefficient of the two sections of the instrument, and they are 0.67 and 0.82, while the reliability coefficient of the whole instrument gave a value of 0.81. Mean with standard deviation was used to answer research questions, while the null hypotheses at 0.5 level of significance at 98 degrees of freedom were tested with a t-test. The findings of the study revealed that the respondents agreed that government and citizens-related strategies improve the management of fake news for sustainable democracy in Enugu State. Again, there was no significant difference between the mean response of the lawmakers and staff on government and citizens-related strategies for managing fake news for sustainable democracy in Enugu State. Based on the findings, it was recommended, among others, that there should be regular workshops on the management of fake news for citizens.

Keywords: fake news, sustainability, democracy, management

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Authors: Misrak Assefa

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The Amharic language is the second most widely spoken Semitic language in the world. There are several new overloaded on the web. Searching some useful documents from the web on a specific topic, which is written in the Amharic language, is a challenging task. Hence, document categorization is required for managing and filtering important information. In the classification of Amharic text news, there is still a gap in the domain of information that needs to be launch. This study attempts to design an automatic Amharic news classification using a supervised learning mechanism on four un-touch classes. To achieve this research, 4,182 news articles were used. Naive Bayes (NB) and Decision tree (j48) algorithms were used to classify the given Amharic dataset. In this paper, k-fold cross-validation is used to estimate the accuracy of the classifier. As a result, it shows those algorithms can be applicable in Amharic news categorization. The best average accuracy result is achieved by j48 decision tree and naïve Bayes is 95.2345 %, and 94.6245 % respectively using three categories. This research indicated that a typical decision tree algorithm is more applicable to Amharic news categorization.

Keywords: text categorization, supervised machine learning, naive Bayes, decision tree

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

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Authors: Lufungula Osembe

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The field of education has witnessed advances in technology and digital transformation. The methods of teaching have undergone significant changes in recent years, resulting in effects on various areas such as pedagogies, curriculum design, personalized teaching, gamification, data analytics, cloud-based learning applications, artificial intelligence tools, advanced plug-ins in LMS, and the emergence of multimedia creation and design. The field of education has not been immune to the changes brought about by digital innovation in recent years, similar to other fields such as engineering, health, science, and technology. There is a need to look at the variables/elements that digital innovation brings to education and develop a framework for higher institutions of learning to assess their readiness to create a viable environment for digital innovation to be successfully adopted. Given the potential benefits of digital innovation in education, it is essential to develop a framework that can assist academics and policymakers in higher institutions of learning to evaluate the effectiveness of adopting and adapting to the evolving landscape of digital innovation in education. The primary research question addressed in this study is to establish the preparedness of higher institutions of learning to adopt and adapt to the evolving landscape of digital innovation. This study follows a Design Science Research (DSR) paradigm to develop a framework for academics and policymakers in higher institutions of learning to evaluate the readiness of their institutions to adopt digital innovation in education. The Design Science Research paradigm is proposed to aid in developing a readiness framework for digital innovation in education. This study intends to follow the Design Science Research (DSR) methodology, which includes problem awareness, suggestion, development, evaluation, and conclusion. One of the major contributions of this study will be the development of the framework for digital innovation in education. Given the various opportunities offered by digital innovation in recent years, the need to create a readiness framework for digital innovation will play a crucial role in guiding academics and policymakers in their quest to align with emerging technologies facilitated by digital innovation in education.

Keywords: digital innovation, DSR, education, opportunities, research

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Authors: Miron Wolnicki

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In the past 75 years the world was either influenced by, competing with or learning from U.S. corporations. This is no longer true. As the economic power shifts from the West to the East, U.S. corporations are lagging behind Asian competitors. Moreover, U.S. statecraft fails to address this decline. In a world dominated by interventionist and neo-mercantilist states, having an ineffective non-activist government becomes a costly neoclassic delusion which weakens the world’s largest economy. American conservative economists continue talking about the superiority of the free market system in generating new technologies. The reality is different. The U.S. is sliding further into an overregulated, over-taxed, anti-business state. This paper argues that in order to maintain its economic strength and technological leadership, the U.S. must reform federal institutions to increase support for artificial intelligence and other cutting-edge technologies. The author outlines a number of institutional reforms, under one umbrella, which he calls the American Entrepreneurial State (AES). The AES will improve productivity and bring about coherent business strategies for the next 10-15 years. The design and inspiration for the AES come from the experience of successful statecraft examples in Asia and also other parts the global economy.

Keywords: post-neoliberal system, entrepreneurial state, government and economy, American entrepreneurial state

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Authors: Xu Qian

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This abstract explores the importance of building resilience within families and offers evidence-based strategies for promoting positive parenting and enhancing emotional well-being. It emphasizes the role of effective communication, conflict resolution, and fostering a supportive environment to strengthen family bonds and promote healthy child development. Introduction: The well-being and resilience of families play a crucial role in fostering healthy child development and promoting overall emotional well-being. This abstract highlights the significance of nurturing resilient families and provides evidence-based strategies for positive parenting. By focusing on effective communication, conflict resolution, and creating a supportive environment, families can strengthen their bonds and enhance emotional well-being for both parents and children. Methods: This abstract draws upon a comprehensive review of existing research and literature on resilient families, positive parenting, and emotional well-being. The selected studies employ various methodologies, including surveys, interviews, and longitudinal observations, to investigate the factors contributing to family resilience and the strategies that promote positive parenting practices. The findings from these studies serve as the foundation for the strategies discussed in this abstract. Results: The results of the reviewed studies demonstrate that effective communication within families is a key factor in building resilience and promoting emotional well-being. Open and honest communication allows family members to express their thoughts, feelings, and concerns, fostering trust and understanding. Conflict resolution skills, such as active listening, compromise, and problem-solving, are vital in managing conflicts constructively and preventing negative consequences on family dynamics and children's well-being. Creating a supportive environment that nurtures emotional well-being is another critical aspect of promoting resilient families. This includes providing emotional support, setting clear boundaries, and promoting positive discipline strategies. Research indicates that consistent and responsive parenting approaches contribute to improved self-regulation skills, emotional intelligence, and overall mental health in children. Discussion: The discussion centers on the implications of these findings for promoting positive parenting and emotional well-being. It emphasizes the need for parents to prioritize self-care and seek support when facing challenges. Parental well-being directly influences the quality of parenting and the overall family environment. By attending to their own emotional needs, parents can better meet the needs of their children and create a nurturing atmosphere. Furthermore, the importance of fostering resilience in children is highlighted. Resilient children are better equipped to cope with adversity, adapt to change, and thrive in challenging circumstances. By cultivating resilience through supportive relationships, encouragement of independence, and providing opportunities for growth, parents can foster their children's ability to bounce back from setbacks and develop essential life skills. Conclusion: In conclusion, nurturing resilient families is crucial for positive parenting and enhancing emotional well-being. This abstract presents evidence-based strategies that emphasize effective communication, conflict resolution, and creating a supportive environment. By implementing these strategies, parents can strengthen family bonds, promote healthy child development, and enhance overall family resilience. Investing in resilient families not only benefits individual family members but also contributes to the well-being of the broader community.

Keywords: childrearing families, family education, children's mental health, positive parenting, emotional health

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Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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Authors: Venkat Garigapati

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To date, more than a dozen oligonucleotide products are approved as injectable products for clinical use. However, there is no single oligo nucleotide product approved for clinical use. Oral delivery of oligo nucleotides is patient friendly administration however, many challenges involved in the development of oral formulation. Over the course of last twenty plus years, the research in this space aimed to address these challenges. This paper describes the issues involved in solubility, stability, enzymatic (nuclease) induced degradation, and permeation of nucleotides in the Gastrointestinal (GI) and how to overcome these challenges. Also, the translation of in vitro data to in vivo models hinders the formulation development. This paper describes the challenges involved in the development of Oligo Nucleotide products for oral administration. It also discusses the chemistry and formulation strategies for oral administration of oligonucleotides.

Keywords: oral adminstration, oligo nucleotides, stability, permeation, gastrointestinal tract

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: Olaf Visker, Arnout De Vries, Lambert Schomaker

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Predictive policing refers to the usage of analytical techniques to identify potential criminal activity. It has been widely implemented by various police departments. Being a relatively new area of research, there are, to the author’s knowledge, no absolute tried, and true methods and they still exhibit a variety of potential problems. One of those problems is closely related to the lack of understanding of how acting on these prediction influence crime itself. The goal of law enforcement is ultimately crime reduction. As such, a policy needs to be established that best facilitates this goal. This research aims to find such a policy by using adversarial agent-based modeling in combination with modern reinforcement learning techniques. It is presented here that a baseline model for both law enforcement and criminal agents and compare their performance to their respective reinforcement models. The experiments show that our smart law enforcement model is capable of reducing crime by making more deliberate choices regarding the locations of potential criminal activity. Furthermore, it is shown that the smart criminal model presents behavior consistent with popular crime theories and outperforms the baseline model in terms of crimes committed and time to capture. It does, however, still suffer from the difficulties of capturing long term rewards and learning how to handle multiple opposing goals.

Keywords: adversarial, agent based modelling, predictive policing, reinforcement learning

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Authors: Kanu Priya Mohan

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Innovation in education is one of the essential pathways to achieve both educational, and development goals in today’s dynamically changing world. Over the last decade, coaching and mentoring have been applied in the field of education as positive intervention techniques for fostering teaching and learning reforms in the developed countries. The context of this research was Thailand’s educational reform process, wherein a project on coaching and mentoring (C&M) was launched in 2014. The C&M project endeavored to support the professional development of the school teachers in the various provinces of Thailand, and to also enable them to apply C&M for teaching innovative instructional techniques. This research aimed to empirically investigate the learning outcomes for the master trainers, who trained for coaching and mentoring as the first step in the process to train the school teachers. A mixed method study was used for evaluating the learning outcomes of training in terms of cognitive- behavioral-affective dimensions. In the first part of the research a quantitative research design was incorporated to evaluate the effects of learner characteristics and instructional techniques, on the learning outcomes. In the second phase, a qualitative method of in-depth interviews was used to find details about the training outcomes, as well as the perceived barriers and enablers of the training process. Sample size constraints were there, yet these exploratory results, integrated from both methods indicated the significance of evaluating training outcomes from the three dimensions, and the perceived role of other factors in the training. Findings are discussed in terms of their implications for the training of C&M, and also their impact in fostering positive education through innovative educational techniques in the developing countries.

Keywords: cognitive-behavioral-affective learning outcomes, mixed method research, teachers in Thailand, training evaluation

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Authors: Onesmus Nyaude

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The aim of the study was to investigate participants’ views on how corruption can be combated to enhance learner academic achievement. The study was undertaken on three select public secondary institutions in Zimbabwe. This study also focuses on exploring the various views of educators; parents and the learners on the role played by corruption in perpetuating the seemingly existing learner academic achievement disparities in various educational institutions. The study further interrogates and examines the nexus between the prevalence of corruption in schools and the subsequent influence on the academic achievement of learners. Corruption is considered a form of social injustice; hence in Zimbabwe, the general consensus is that it is perceived rife to the extent that it is overtaking the traditional factors that contributed to the poor academic achievement of learners. Coupled to this, have been the issue of gross abuse of power and some malpractices emanating from concealment of essential and official transactions in the conduct of business. Through proposing robust anti-corruption mechanisms, teaching and learning resources poured in schools would be put into good use. This would prevent the unlawful diversion and misappropriation of the resources in question which has always been the culture. This study is of paramount significance to curriculum planners, teachers, parents, and learners. The study was informed by the interpretive paradigm; thus qualitative research approaches were used. Both probability and non-probability sampling techniques were adopted in ‘site and participants’ selection. A representative sample of (150) participants was used. The study found that the majority of the participants perceived corruption as a social problem and a human right threat affecting the quality of teaching and learning processes in the education sector. It was established that corruption prevalence within institutions is as a result of the perpetual weakening of ethical values and other variables linked to upholding of ‘Ubuntu’ among general citizenry. It was further established that greediness and weak systems are major causes of rampant corruption within institutions of higher learning and are manifesting through abuse of power, bribery, misappropriation and embezzlement of material and financial resources. Therefore, there is great need to collectively address the problem of corruption in educational institutions and society at large. The study additionally concludes that successful combating of corruption will promote successful moral development of students as well as safeguarding their human rights entitlements. The study recommends the adoption of principles of good corporate governance within educational institutions in order to successfully curb corruption. The study further recommends the intensification of interventionist strategies and strengthening of systems in educational institutions as well as regular audits to overcome the problem associated with rampant corruption cases.

Keywords: academic achievement, combating, corruption, good corporate governance, qualitative study

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Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

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Authors: Nik Siti Hanifah Nik Ahmad

Abstract:

This research discuss about teaching cupping therapy or hijama by using an online 3D Virtual Learning Environment. The experimental platform was using of flash and Second Life as 2D and 3D comparison. 81 samples have been used in three experiments with 21 in the first and 30 in each second and third. The design of the presentation was tested in five categories such as effectiveness, ease of use, efficacy, aesthetic and users’ satisfaction. The results from three experiments had shown promising outcome for usage of the technique to be implement in teaching Cupping Therapy as well as other alternative or conventional medicine knowledge especially for training.

Keywords: medical and health, cupping therapy or hijama, second life, online 3D VLE, virtual worlds

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Authors: Abdi Omar Shuriye

Abstract:

A social business is a business designed to address socio-economic problems to enhance the welfare of the communities involved. Lately, social business, with its focus on innovative ideas, is capturing the interest of educational institutions, governments, and non-governmental organizations. Social business uses a business model to achieve a social goal, and in the last few decades, the idea of imbuing social business into the education system of higher learning institutions has spurred much excitement. This is due to the belief that it will lead to job creation and increased social resilience. One of the higher learning institutions which have invested immensely in the idea is Albukhari International University; it is a private education institution, on a state-of-the-art campus, providing an advantageous learning ecosystem. The niche area of this institution is social business, and it graduates job creators, not job seekers; this Malaysian institution is unique and one of its kind. The objective of this paper is to develop a work plan, direction, and milestone as well as the focus area for the infusion of social business into higher learning institutions with special reference to Al-Bukhari International University. The purpose is to develop a prototype and model full-scale to enable higher learning education institutions to construct the desired curriculum fermented with social business. With this model, major predicaments faced by these institutions could be overcome. The paper sets forth an educational plan and will spell out the basic tenets of social business, focusing on the nature and implementational aspects of the curriculum. It will also evaluate the mechanisms applied by these educational institutions. Currently, since research in this area remains scarce, institutions adopt the process of experimenting with various methods to find the best way to reach the desired result on the matter. The author is of the opinion that social business in education is the main tool to educate holistic future leaders; hence educational institutions should inspire students in the classroom to start up their own businesses by adopting creative and proactive teaching methods. This proposed model is a contribution in that direction.

Keywords: social business, curriculum, skills, university

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Authors: Zan Chen, D. Kwok

Abstract:

The SkillsFuture Singapore’s mission to develop a responsive and forward-looking Training and Adult Education (TAE) and workforce development system is undergirded by how successful TAE providers are in their business performance and strategies that strengthen their operational efficiency and processes. Therefore, understanding the factors that drive the business performance of TAE providers is critical to the success of SkillsFuture Singapore’s initiatives. This study aims to investigate how business strategy, work autonomy, work intensity and professional development support impact the business performance of private TAE providers. Specifically, the three research questions are: (1) Are there significant relationships between the above-mentioned four factors and TAE providers’ business performance?; (2) Are there significant differences on the four factors between low and high TAE providers’ business performance groups?; and (3) To what extent and in what manner do the four factors predict TAE providers’ business performance? This was part of the first national study on organizations and professionals working in the Training and Adult Education (TAE) sector. Data from 265 private TAE providers where respondents were Chief Executive Officers representatives from the Senior Management were analyzed. The results showed that business strategy (the extent that the organization leads the way in terms of developing new products and services; uses up-to-date learning technologies; customizes its products and services to the client’s needs), work autonomy (the extent that the staff personally have an influence on how hard they work; deciding what tasks they are to do; deciding how they are to do the tasks, and deciding the quality standards to which they work) and professional development support (both monetary and non-monetary support and incentives) had positive and significant relationships with business performance. However, no significant relationship is found between work intensity and business performance. A business strategy, work autonomy and professional development support were significantly higher in the high business performance group compared to the low-performance group among the TAE providers. Results of hierarchical regression analyses controlling for the size of the TAE providers showed significant impacts of business strategy, work autonomy and professional development support on TAE providers’ business performance. Overall, the model accounted for 27% of the variance in TAE providers’ business performance. This study provides policymakers with insights into improving existing policies, designing new initiatives and implementing targeting interventions to support TAE providers. The findings also have implications on how the TAE providers could better formulate their organizational strategies and business models. Finally, limitations of study, along with directions for future research will be discussed in the paper.

Keywords: adult education, business performance, business strategy, training, work autonomy

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Authors: Davoud Masoumi, Maryam Bourbour

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By characterizing children’s actions in the scaffolding process, which is often undermined and ignored in the studies reviewed, this study aimed to examine children’s different (re)actions in relation to the teachers’ actions in a context where digital technologies are used. Over five months, 22 children aged 4-6 with five preschool teachers were video observed. The study brought in rich details of the children’s actions in relation to the teacher’s actions in the scaffolding process. The findings of the study reveal thirteen (re)actions, including Giving short response; Explaining; Participating in the activities; Examining; Smiling and laughing; Pointing and showing; Working together; Challenging each other; Problem-solving skills; Developing vocabulary; Choosing the activity; Expressing of the emotions; and Identifying the similarities and differences. Our findings expanded and deepened the understanding of the scaffolding process, which can contribute to the notion of scaffolding and help us to gain further understanding about scaffolding of children’s learning. Characterizing the children’s (re)action in relation to teacher’s scaffolding actions further can contribute to ongoing discussions about how teachers can scaffold children’s learning using digital technologies in the learning process.

Keywords: children’ (re)actions, scaffolding process, technologies, preschools

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Authors: Aravind J.

Abstract:

Passive design can be referred to a way of designing buildings that takes advantage of the prevailing climate and natural energy resources. Which will be a key to reduce the increasing energy usage in commercial buildings. Most of the small scale commercial buildings made are merely a thermal mass inbuilt with active systems to bring lively conditions. By bringing the passive design strategies for energy efficiency in commercial buildings will reduce the usage of active systems. Thus the energy usage can be controlled through analysis of daylighting and improved living conditions in the indoor spaces by using passive techniques. And comparative study on different passive design systems and conventional methods will be approached for commercial buildings in hot and humid region. Possible effects of existing risks implied with solution for those problems is also a part of the paper. The result will be carried on with the design programme to prove the workability of the strategies.

Keywords: passive design, energy efficiency, commercial buildings, hot and humid climate

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

Abstract:

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

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

Procedia PDF Downloads 149