Search results for: relevance vector machines

Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: M. Al Zallouha, Y. Landkocz, J. Brunet, R. Cousin, J. M. Halket, E. Genty, P. J. Martin, A. Verdin, D. Courcot, S. Siffert, P. Shirali, S. Billet

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Toluene is one of the most used Volatile Organic Compounds (VOCs) in the industry. Amongst VOCs, Benzene, Toluene, Ethylbenzene and Xylenes (BTEX) emitted into the atmosphere have a major and direct impact on human health. It is, therefore, necessary to minimize emissions directly at source. Catalytic oxidation is an industrial technique which provides remediation efficiency in the treatment of these organic compounds. However, during operation, the catalysts can release some compounds, called byproducts, more toxic than the original VOCs. The catalytic oxidation of a gas stream containing 1000ppm of toluene on Pd/α-Al2O3 can release a few ppm of benzene, according to the operating temperature of the catalyst. The development of new catalysts must, therefore, include chemical and toxicological validation phases. In this project, A549 human lung cells were exposed in air/liquid interface (Vitrocell®) to gas mixtures derived from the oxidation of toluene with a catalyst of Pd/α-Al2O3. Both exposure concentrations (i.e. 10 and 100% of catalytic emission) resulted in increased gene expression of Xenobiotics Metabolising Enzymes (XME) (CYP2E1 CYP2S1, CYP1A1, CYP1B1, EPHX1, and NQO1). Some of these XMEs are known to be induced by polycyclic organic compounds conventionally not searched during the development of catalysts for VOCs degradation. The increase in gene expression suggests the presence of undetected compounds whose toxicity must be assessed before the adoption of new catalyst. This enhances the relevance of toxicological validation of such systems before scaling-up and marketing.

Keywords: BTEX toxicity, air/liquid interface cell exposure, Vitrocell®, catalytic oxidation

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Authors: Edgar Mauricio Ruiz Osuna, Claudia Yaneth Herrera Bolivar, Sandra Liliana Gomez Vasquez

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The increasing needs of professionals with skills in software development in industry are incremental, therefore, the relevance of an educational process in line with the strengthening of these competencies, are part of the responsibilities of universities with careers related to the area of Informatics and Systems. In this sense, it is important to consider that in the National Science, Technology and Innovation Plan for the development of the Electronics, Information Technologies and Communications (2013) sectors, it is established as a weakness in the SWOT Analysis of the Software sector and Services, Deficiencies in training and professional training. Accordingly, UNIMINUTO's Computer Technology Program has addressed the analysis of students' performance in software development, identifying various problems such as dropout in programming subjects, academic averages, as well as deficiencies in strategies and competencies developed in the area of programming. As a result of this analysis, it was determined to design a collaborative learning platform in basic programming using heat maps as a tool to support didactic feedback. The pilot phase allows to evaluate in a programming course the ALGORINFO platform as a didactic resource, through an interactive and collaborative environment where students can develop basic programming practices and in turn, are fed back through the analysis of time patterns and difficulties frequent in certain segments or program cycles, by means of heat maps. The result allows the teacher to have tools to reinforce and advise critical points generated on the map, so that students and graduates improve their skills as software developers.

Keywords: collaborative platform, learning, feedback, programming, heat maps

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Authors: Raymond Feng, Shadi Ghiasi

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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

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Authors: Jawid Ahmad Baktash, Tadashi Shiroma, Tomokazu Nagata, Yuji Taniguchi, Morikazu Nakamura

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The goal of this paper is to explore the use of formal methods for Dynamic Routing, The purpose of network communication with dynamic routing is sending a massage from one node to others by using pacific protocols. In dynamic routing connections are possible based on protocols of Distance vector (Routing Information Protocol, Border Gateway protocol), Link State (Open Shortest Path First, Intermediate system Intermediate System), Hybrid (Enhanced Interior Gateway Routing Protocol). The responsibility for proper verification becomes crucial with Dynamic Routing. Formal methods can play an essential role in the Routing, development of Networks and testing of distributed systems. Event-B is a formal technique consists of describing rigorously the problem; introduce solutions or details in the refinement steps to obtain more concrete specification, and verifying that proposed solutions are correct. The system is modeled in terms of an abstract state space using variables with set theoretic types and the events that modify state variables. Event-B is a variant of B, was designed for developing distributed systems. In Event-B, the events consist of guarded actions occurring spontaneously rather than being invoked. The invariant state properties must be satisfied by the variables and maintained by the activation of the events.

Keywords: dynamic rout RIP, formal method, event-B, pro-B

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Authors: Bin Liu

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MicroRNAs (miRNAs) are small non-coding RNA molecules, functioning in transcriptional and post-transcriptional regulation of gene expression. The discrimination of the real pre-miRNAs from the false ones (such as hairpin sequences with similar stem-loops) is necessary for the understanding of miRNAs’ role in the control of cell life and death. Since both their small size and sequence specificity, it cannot be based on sequence information alone but requires structure information about the miRNA precursor to get satisfactory performance. Kmers are convenient and widely used features for modeling the properties of miRNAs and other biological sequences. However, Kmers suffer from the inherent limitation that if the parameter K is increased to incorporate long range effects, some certain Kmer will appear rarely or even not appear, as a consequence, most Kmers absent and a few present once. Thus, the statistical learning approaches using Kmers as features become susceptible to noisy data once K becomes large. In this study, we proposed a Gapped k-mer approach to overcome the disadvantages of Kmers, and applied this method to the field of miRNA prediction. Combined with the structure status composition, a classifier called imiRNA-GSSC was proposed. We show that compared to the original imiRNA-kmer and alternative approaches. Trained on human miRNA precursors, this predictor can achieve an accuracy of 82.34 for predicting 4022 pre-miRNA precursors from eleven species.

Keywords: gapped k-mer, imiRNA-GSSC, microRNA precursor, support vector machine

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Authors: Thi Phuong Lan Nguyen

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Vietnamese English Language Teacher Education (ELTE) has been changing a lot in response to the rapidly evolving socio-economic context requirements. The Vietnamese government assigns the Ministry of Education and Training (MOET) primary tasks to have policy changes to prepare for ELTE development in the globalization and socialization process. Many educational policies have been made to develop ELTE, however, they seem not to address the new global or social demands. The issue is that there are still significant disparities between the national policy and the institutional implementation. This study is to investigate the alignment between ELTE institutional curriculum, pedagogies, and MOET standards. This study used a mixed-method with the data sources from policy documents, a survey, and 33 interviews conducted with the lecturers and administrators from eleven Vietnamese ELTE institutions. The data have been analysed to understand the gap between policy and practice. The initial findings are (i) a low alignment of curriculum and language proficiency standards and (ii) a moderate alignment between curriculum and future-career skills standards. Many pedagogical challenges have been found. In order to address these gaps, it is necessary for the curriculum to be standards-based designed. It is also vital for professional development in order to improve the quality teaching. The study offers multiple perspectives on a complex issue. The study is meaningful not only to educational governance, but also to teaching practitioners, English language researchers, and English language learners. The significance lies in its relevance to English teaching careers across all parts of Vietnam, it yet remains relevant to ELTE in other countries teaching English as a foreign language.

Keywords: alignment, curriculum, educational policy, English language teaching, pedagogy, standards

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Authors: Anjali Chouksey, Riya Nimje, Jahanvi Saraf

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Online transactions have increased dramatically in this new ‘social-distancing’ era. With online transactions, Fraud in online payments has also increased significantly. Frauds are a significant problem in various industries like insurance companies, baking, etc. These frauds include leaking sensitive information related to the credit card, which can be easily misused. Due to the government also pushing online transactions, E-commerce is on a boom. But due to increasing frauds in online payments, these E-commerce industries are suffering a great loss of trust from their customers. These companies are finding credit card fraud to be a big problem. People have started using online payment options and thus are becoming easy targets of credit card fraud. In this research paper, we will be discussing machine learning algorithms. We have used a decision tree, XGBOOST, k-nearest neighbour, logistic-regression, random forest, and SVM on a dataset in which there are transactions done online mode using credit cards. We will test all these algorithms for detecting fraud cases using the confusion matrix, F1 score, and calculating the accuracy score for each model to identify which algorithm can be used in detecting frauds.

Keywords: machine learning, fraud detection, artificial intelligence, decision tree, k nearest neighbour, random forest, XGBOOST, logistic regression, support vector machine

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Authors: Steven D. P. Moore

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An electrical discharge in the air induces an electromagnetic (EM) wave capable of wireless transfer, reception, and conversion back into electrical discharge at a distant location. Following Norton’s ground wave principles, EM wave radiation (EMR) runs parallel to the Earth’s surface. Energy in an EMR wave can move through the air and be focused to create a spark at a distant location, focused by a receiver to generate a local electrical discharge. This local discharge can be amplified and stored but also has the propensity to initiate another EMR wave. In addition to typical EM waves, lightning is also associated with atmospheric events, trans-ionospheric pulse pairs, the most powerful natural EMR signal on the planet. With each lightning strike, regardless of global position, it generates naturally occurring pulse-pairs that are emitted towards space within a narrow cone. An EMR wave can self-propagate, travel at the speed of light, and, if polarized, contain vector properties. If this reflective pulse could be directed by design through structures that have increased probabilities for lighting strikes, it could theoretically travel near the surface of the Earth at light speed towards a selected receiver for local transformation into electrical energy. Through research, there are several influencing parameters that could be modified to model, test, and increase the potential for adopting this technology towards the goal of developing a global grid that utilizes natural sources of energy.

Keywords: electricity, sparkgap, wireless, electromagnetic

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Authors: Velázquez Alejandro, Pradhan Sujan, Yoon Rokhyun, Sanada Yasushi

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The utilization of new materials as an alternative solution to decrease the environmental impact of the construction industry has been gaining more relevance in the architectural design and construction industry. One such material is cross-laminated timber (CLT), an engineered timber solution that excels for its faster construction times, workability, lightweight, and capacity for carbon storage. This material is usually used alone for the entire structure or combined with steel frames, but a hybrid with reinforced concrete (RC) is rarer. Since RC is one of the most used materials worldwide, a hybrid with CLT would allow further utilization of the latter, and in the process, it would help reduce the environmental impact of RC construction to achieve a sustainable society, but first, the structural performance of such hybrids must be understood. This paper focuses on proposing a model to predict the seismic performance of RC frames with CLT panels as infills. A series of static horizontal cyclic loading experiments were conducted on two 40% scale specimens of reinforced concrete frames with and without CLT panels at Osaka University, Japan. An analytical model was created to simulate the seismic performance of the RC frame with CLT infill based on the experimental results. The proposed model was verified by comparing the experimental and analytical results, showing that the load-deformation relationship and the failure mechanism agreed well with limited error. Hence, the proposed analytical model can be implemented for the seismic performance evaluation of the RC frames with CLT infill.

Keywords: analytical model, multi spring, performance evaluation, reinforced concrete, rocking mechanism, wooden wall

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Authors: Susan Lee

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Situated learning principles are adopted in the design of the module, professional communication, in its iteration of tasks and assignments to create a learning environment that simulates workplace reality. The success of situated learning is met when students are able to transfer and apply their skills beyond the classroom, in their personal life, and workplace. The learning process should help students recognize the relevance and opportunities for application. In the module’s learning component on negotiation, cases are created based on scenarios inspired by industry practices. The cases simulate scenarios that students on the course may encounter when they enter the workforce when they take on executive roles in the real estate sector. Engaging in the cases has enhanced students’ learning experience as they apply interpersonal communication skills in negotiation contexts of executives. Through the process of case analysis, role-playing, and peer feedback, students are placed in an experiential learning space to think and act in a deliberate manner not only as students but as professionals they will graduate to be. The immersive skills practices enable students to continuously apply a range of verbal and non-verbal communication skills purposefully as they stage their negotiations. The theme in students' feedback resonates with their awareness of the authentic and workplace experiences offered through visceral role-playing. Students also note relevant opportunities for the future transfer of the skills acquired. This indicates that students recognize the possibility of encountering similar negotiation episodes in the real world and realize they possess the negotiation tools and communication skills to deliberately apply them when these opportunities arise outside the classroom.

Keywords: deliberate practice, interpersonal communication skills, role-play, situated learning

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Authors: Imran Hashmi, Sipkaduwa Arachchige Sashika Sureni Wickramasooriya

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Gene-drive technology has emerged as a promising tool for disease control by influencing the population dynamics of disease-carrying organisms. Various gene drive mechanisms, derived from global laboratory experiments, aim to strategically manage and prevent the spread of targeted diseases. One prominent strategy involves population replacement, wherein genetically modified mosquitoes are introduced to replace the existing local wild population. To enhance our understanding and aid in the design of effective release strategies, we employ a comprehensive mathematical model. The utilized approach employs agent-based modeling, enabling the consideration of individual mosquito attributes and flexibility in parameter manipulation. Through the integration of an agent-based model and a meta-population spatial approach, the dynamics of gene drive mosquito spreading in a released site are simulated. The model's outcomes offer valuable insights into future population dynamics, providing guidance for the development of informed release strategies. This research significantly contributes to the ongoing discourse on the responsible and effective implementation of gene drive technology for disease vector control.

Keywords: gene drive, agent-based modeling, disease-carrying organisms, malaria

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Authors: Bernd Engel, Sara Salman Hassan Al-Maeeni

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A substantial amount of natural resources are nowadays consumed at a growing rate, as humans all over the world used materials obtained from the Earth. Machinery manufacturing industry is one of the major resource consumers on a global scale. Even though the incessant finding out of the new material, metals, and resources, it is urgent for the industry to develop methods to use the Earth's resources intelligently and more sustainable than before. Re-engineering of machine tools regarding design and failure analysis is an approach whereby out-of-date machines are upgraded and returned to useful life. To ensure the reliable future performance of the used machine components, it is essential to investigate the machine component failure through the material, design, and surface examinations. This paper presents an experimental approach aimed at inspecting the shaft of the rotary draw bending machine as a case to study. The testing methodology, which is based on the principle of the three-point bending test, allows assessing the shaft elastic behavior under loading. Furthermore, the shaft elastic characteristics include the maximum linear deflection, and maximum bending stress was determined by using an analytical approach and finite element (FE) analysis approach. In the end, the results were compared with the ones obtained by the experimental approach. In conclusion, it is seen that the measured bending deflection and bending stress were well close to the permissible design value. Therefore, the shaft can work in the second life cycle. However, based on previous surface tests conducted, the shaft needs surface treatments include re-carburizing and refining processes to ensure the reliable surface performance.

Keywords: deflection, FE analysis, shaft, stress, three-point bending

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Authors: Lakmali Anthony, Madeline Gillies

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Purpose: Decreasing mortality has led to increased focus on patient-reported outcomes such as quality of life (QoL) in breast cancer. Breast cancer patients often have decreased QoL even after treatment is complete. This systematic review of the literature aims to identify psychosocial factors associated with decreased QoL in post-treatment breast cancer patients. Methodology: This systematic review was performed in accordance with the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses recommendations. The search was conducted in MEDLINE, EMBASE, and PsychINFO using MeSH headings. The two authors screened studies for relevance and extracted data. Results: Seventeen studies were identified, including 3,150 total participants (mean = 197) with a mean age of 51.9 years. There was substantial heterogeneity in measures of QoL. The most common was the European Organisation for Research and Treatment of Cancer QLQ-C30 (n=7, 41.1%). Most studies (n=12, 70.5%) found that emotional distress correlated with poor QoL, while 3 found no significant association. The most common measure of emotional distress was the Hospital Anxiety and Depression Scale (n=12, 70.5%). Other psychosocial factors associated with QoL were unmet needs, problematic social support, and negative affect. Clinicopathologic determinants included mastectomy without reconstruction, stage IV disease, and adjuvant chemotherapy. Conclusion: This systematic review provides a summary of the psychosocial determinants of poor QoL in post-treatment breast cancer patients, as well as the most commonly reported measures of these. An understanding of these potentially modifiable determinants of poor outcome is pivotal to the provision of quality, patient-centred care in surgical oncology.

Keywords: breast cancer, quality of life, psychosocial determinants, cancer surgery

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Authors: José Eduardo García-Mendiola

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In this work, a phenomenological approach to computational modeling of analogy processing is carried out. The paper goes through the consideration of the structure of the analogy, based on the possibility of sustaining the genesis of its elements regarding Husserl's genetic theory of association. Among particular processes which take place in order to get analogical inferences, there is one which arises crucial for enabling efficient base cases retrieval through long-term memory, namely analogical transference grounded on familiarity. In general, it has been argued that analogical reasoning is a way by which a conscious agent tries to determine or define a certain scope of objects and relationships between them using previous knowledge of other familiar domain of objects and relations. However, looking for a complete description of analogy process, a deeper consideration of phenomenological nature is required in so far, its simulation by computational programs is aimed. Also, one would get an idea of how complex it would be to have a fully computational account of the analogy elements. In fact, familiarity is not a result of a mere chain of repetitions of objects or events but generated insofar as the object/attribute or event in question is integrable inside a certain context that is taking shape as functionalities and functional approaches or perspectives of the object are being defined. Its familiarity is generated not by the identification of its parts or objective determinations as if they were isolated from those functionalities and approaches. Rather, at the core of such a familiarity between entities of different kinds lays the way they are functionally encoded. So, and hoping to make deeper inroads towards these topics, this essay allows us to consider that cognitive-computational perspectives can visualize, from the phenomenological projection of the analogy process reviewing achievements already obtained as well as exploration of new theoretical-experimental configurations towards implementation of analogy models in specific as well as in general purpose machines.

Keywords: analogy, association, encoding, retrieval

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Authors: Abbas Al-Refaie, Ruba Najdawi, Nour Bata, Mohammad D. AL-Tahat

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The pharmaceutical industry is an important component of health care systems throughout the world. Measurement of a production unit-performance is crucial in determining whether it has achieved its objectives or not. This paper applies data envelopment (DEA) window analysis to assess the efficiencies of two packaging lines; Allfill (new) and DP6, in the Penicillin plant in a Jordanian Medical Company in 2010. The CCR and BCC models are used to estimate the technical efficiency, pure technical efficiency, and scale efficiency. Further, the Malmquist productivity index is computed to measure then employed to assess productivity growth relative to a reference technology. Two primary issues are addressed in computation of Malmquist indices of productivity growth. The first issue is the measurement of productivity change over the period, while the second is to decompose changes in productivity into what are generally referred to as a ‘catching-up’ effect (efficiency change) and a ‘frontier shift’ effect (technological change). Results showed that DP6 line outperforms the Allfill in technical and pure technical efficiency. However, the Allfill line outperforms DP6 line in scale efficiency. The obtained efficiency values can guide production managers in taking effective decisions related to operation, management, and plant size. Moreover, both machines exhibit a clear fluctuations in technological change, which is the main reason for the positive total factor productivity change. That is, installing a new Allfill production line can be of great benefit to increasing productivity. In conclusions, the DEA window analysis combined with the Malmquist index are supportive measures in assessing efficiency and productivity in pharmaceutical industry.

Keywords: window analysis, malmquist index, efficiency, productivity

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Authors: Chuks Odiegwu-Enwerem

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The classical notion of opinion leadership presupposes that the media is at the center of an effective and successful opinion leadership. Under this idea, an opinion leader is an active media user who consumes, understands, digests and interprets the messages for the understanding and acceptance/adoption by lower-end media users – whose access and understanding of media content are supposedly low. Because of their unique access to and presumed understanding of media functions and their content, opinion leaders are typically esteemed by those who look forward to and accept their opinions. Lazarsfeld and Katz’s two-step flow of communication theory is the basis of opinion leadership – propelled by limited access to the media. With the emergence and spread of social media and its unlimited access by all and sundry, however, the study interrogates the relevance and application of opinion leaders and, by implication, the two-step flow communication theory in Nigeria’s Northcentral region. It seeks to determine whether opinion leaders still exist in the picture and if they still exert considerable influence, especially in matters of political conversations and decision-making among the citizens of this area. It further explores whether the diffusion of social media is a reality and how the ‘low-end’ media users react to the new-found freedom of access to media, and how they are using it to inform their decisions on important matters as well as examines if they are still glued to their opinion leaders. This study explores the empirical dimensions of the two-step flow hypothesis in relation to the activities of social media to determine if a change has occurred and in what direction, using mixed methos of Survey and in-depth interviews. Our understanding and belief in some theoretical assumptions may be enhanced or challenged by the study outcome.

Keywords: Opinion Leadership, Active Media User, Two-Step-Flow, Social media, Northcentral Nigeria

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Authors: Tai Yuan Yu, Pei-Jen Wang

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Oil-free turbomachinery is considered one of the critical technologies for future green power generation systems as rotor machinery systems. Oil-free technology allows clean, compact, and maintenance-free working, and gas foil bearings, abbreviated as GFBs, are important for the technology. Since the first applications in the auxiliary power units and air cycle machines in the 1970s, obvious improvement has been created to the computational models for dynamic rotor behavior. However, many technical issues are still poorly understood or remain unsolved, and some of those are thermal management and the pattern of how pressure will be distributed in bearing clearance. This paper presents a three-dimensional, abbreviated as 3D, fluid-structure interaction model of single pad foil bearings and three pad foil bearings to predict bearing working behavior that researchers could compare characteristics of those. The coupling analysis model involves dynamic working characteristics applied to all the gas film and mechanical structures. Therefore, the elastic deformation of foil structure and the hydrodynamic pressure of gas film can both be calculated by a finite element method program. As a result, the temperature distribution pattern could also be iteratively solved by coupling analysis. In conclusion, the working fluid state in a gas film of various pad forms of bearings working characteristic at constant rotational speed for both can be solved for comparisons with the experimental results.

Keywords: fluid-structure interaction, multi-physics simulations, gas foil bearing, oil-free, transient thermo-hydrodynamic

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Authors: Felipe Bedoya Maya, Agustina Calatayud, Vileydy Gonzalez Mejia

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Encompassing inventory, warehousing, and transportation management, logistics is a crucial predictor of firm performance. This has been extensively proven by extant literature in business and operations management. Logistics is also a fundamental determinant of a country's ability to access international markets. Available studies in international and transport economics have shown that limited transport infrastructure and underperforming transport services can severely affect international competitiveness. However, the evidence lacks the overall impact of logistics performance-encompassing all inventory, warehousing, and transport components- on global trade. In order to fill this knowledge gap, the paper uses a gravitational trade model with 155 countries from all geographical regions between 2007 and 2018. Data on logistics performance is obtained from the World Bank's Logistics Performance Index (LPI). First, the relationship between logistics performance and a country’s total trade is estimated, followed by a breakdown by the economic sector. Then, the analysis is disaggregated according to the level of technological intensity of traded goods. Finally, after evaluating the intensive margin of trade, the relevance of logistics infrastructure and services for the extensive trade margin is assessed. Results suggest that: (i) improvements in both logistics infrastructure and services are associated with export growth; (ii) manufactured goods can significantly benefit from these improvements, especially when both exporting and importing countries increase their logistics performance; (iii) the quality of logistics infrastructure and services becomes more important as traded goods are technology-intensive; and (iv) improving the exporting country's logistics performance is essential in the intensive margin of trade while enhancing the importing country's logistics performance is more relevant in the extensive margin.

Keywords: gravity models, infrastructure, international trade, logistics

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Authors: Dalia. G. Aseel

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Begomoviruses are economically important plant viruses that infect dicotyledonous plants and exclusively transmitted by the whitefly Bemisia tabaci. Here, replicative form was isolated from Okra, Cotton, Tomato plants and whitefly infected with Begomoviruses. Using coat protein specific primers (AV1), the viral infection was verified with amplicon at 450 bp. The sequence of OLCuV-AV1 gene was recorded and received an accession number (FJ441605) from Genebank. The phylogenetic tree of OLCuV was closely related to Okra leaf curl virus previously isolated from Cameroon and USA with nucleotide sequence identity of 92%. The protein purification was carried out using His-Tag methodology by using Affinity Chromatography. The purified protein was separated on SDS-PAGE analysis and an enriched expected size of band at 30 kDa was observed. Furthermore, RAPD and SDS-PAGE were used to detect genetic variability between different hosts of okra leaf curl virus (OLCuV), cotton leaf curl virus (CLCuV), tomato yellow leaf curl virus (TYLCuV) and the whitefly vector. Finally, the present study would help to understand the relationship between the whitefly and different economical crops in Egypt.

Keywords: okra leaf curl virus, AV1 gene, sequencing, phylogenetic, cloning, purified protein, genetic diversity and viral proteins

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Authors: Kaisar Akhir, Azhar Slamet

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This study aims to provide recommendations for addressing marine plastic litter at the ocean tourism destinations in Indonesia sustainably through technological interventions in the framework of the National Action Plan for Marine Litter Management 2018-2025. In Indonesia, marine tourism is a rapidly growing economic sector. However, marine tourism destinations are facing a global challenge called marine plastic litter. Marine plastic litter is a threat to those destinations since it has potential impacts on the reduction of marine environmental sustainability, the health of tourists and local communities as well as tourism business income. Since 2018, the Indonesian government has passed and promulgated the National Plan of Action on Marine Litter Management 2018-2025. This national action plan consists of three important key aspects of interventions (i.e., societal effort, technological application, and institutional coordination) and five strategies for addressing marine litter in Indonesia, in particular, to address 70% of marine plastic litter by 2025. The strategies include 1) National movement for raising awareness of stakeholders, 2) Land-based litter management, 3) Litter management at the sea and coasts, 4) Funding mechanism, institutional strengthening, monitoring, and law enforcement, and 5) Research and development. In this study, technological interventions around the world and in Indonesia are reviewed and analyzed on their relevance to the national action plan based on five criteria. As a result, there are twelve kinds of technological interventions recommended to be implemented for addressing marine plastic litter in the marine tourism destinations in Indonesia.

Keywords: marine litter management, marine plastic litter, national action plan, ocean sustainability, ocean tourism destination, technological interventions

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Authors: Priscilla Adoley Moffat

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This study explored perceptions rooted in and acquired from the cultures of many developing countries and how they impact applicants’ preferences and choices of STEM programs. The context of developing countries was chosen for this study because gender role socialization continues to maintain an important place in most of these cultures. This study’s relevance rests in the fact that, as the world takes steps to encourage and promote the choice and study of STEM programs, especially among females, there is a need for efforts towards understanding various cultural perceptions towards some programs of study, particularly STEM programs, which have diverse gender attributions in many developing cultures. Also, as the world strives to achieve gender equity in education, such a study comes in handy, as it provides a useful understanding of the underlying cultural factors that affect study program preferences of applicants, particularly in developing countries like Ghana as well as others in Africa. The study analyzed the admission application data of five public universities in Ghana. 1600 randomly-sampled final-year students of 32 randomly-selected senior high schools from the 16 regions of Ghana were interviewed. Since parents and teachers often guide and influence the study program choices of applicants, the study examined the perceptions of 180 teachers and 360 parents. The study found, among other things, that STEM programs are commonly perceived to pose much more difficulty to females than they do to males. As a result, many female applicants are discouraged from choosing these programs. While nursing programs are perceived more as programs for females, with the justification that females are better caregivers, males are perceived to be better medical doctors, engineers, and computer technicians. Thus, many females are less encouraged to choose Technology and Engineering programs.

Keywords: culture, perceptions, STEM, choice, preference

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Authors: Rui Liu, Pengyu Cui, Nan Jiang

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At present, there is much research on the application of centralized management and cross-integration application of basic geographic information. However, the idea of information integration and sharing between land, sea, and air navigation targets is not deeply applied into the research of navigation information service, especially in the information expression. Targeting at this problem, the paper carries out works about the expression pattern of navigation electronic map for ground vehicles under air and land united navigation mechanism. At first, with the support from multi-source information fusion of GIS vector data, RS data, GPS data, etc., an air and land united information expression pattern is designed aiming at specific navigation task of emergency rescue in the earthquake. And then, the characteristics and specifications of the united expression of air and land navigation information under the constraints of map load are summarized and transferred into expression rules in the rule bank. At last, the related navigation experiment is implemented to evaluate the effect of the expression pattern. The experiment selects evaluation factors of the navigation task accomplishment time and the navigation error rate as the main index, and make comparisons with the traditional single information expression pattern. To sum up, the research improved the theory of navigation electronic map and laid a certain foundation for the design and realization of united navigation system in the aspect of real-time navigation information delivery.

Keywords: navigation electronic map, united navigation, multi-element expression pattern, multi-source information fusion

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Authors: Jeter Canete, Noreen Joyce Estrella, Yedda Sachi Patrice Madelo

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Zooplankton plays a crucial role in aquatic ecosystems and a number of water parameters involved in it. Despite their relevance, there is inadequate information about zooplankton communities in Sarangani Bay, Sarangani Province: one of the most essential waterbodies in Mindanao. The aim of the present study was to determine the composition, abundance, and diversity of zooplankton as well as to provide more recent data about the physico-chemical characteristics of Sarangani Bay. Zooplankton samples were collected by vertical hauls using a zooplankton net (mouth diameter: 0.5m; mesh size opening: round, 350μm) in three stations in the coastal waters of Alabel, Malapatan, and Maasim during November 2018. A total of 74 species of zooplankton belonging mainly to Kingdom Protozoa, Phylum Arthropoda, Chaetognatha, and Chordata were identified. Results showed a total zooplankton abundance of 1,984,166 ind/m³ with the highest count recorded at Malapatan (717,169 ind/m³) and the lowest at Maasim (624,411 ind/m³). Among 22 zooplankton groups identified, subclass Copepoda was found to be the most dominant (73.10%), followed by Appendicularia (12.18%) and Vertebrata (3.54%). Diversity analysis revealed an even distribution of species and a diverse ecosystem in all stations sampled. Correlation analysis indicated a strong relationship between zooplankton abundance and physico-chemical parameters. Overall, the physico-chemical profile of Sarangani Bay did not differ from the standards set by DENR, and analysis of the zooplankton communities revealed that Sarangani Bay favorably supports marine organisms to flourish. The findings of this study provide useful knowledge on zooplankton communities and can be used to create management strategies to protect the aquatic biodiversity in Sarangani Bay.

Keywords: aquatic biomonitoring, biodiversity, physicochemical analysis, population survey, Sarangani Bay, Sarangani Province, zooplankton

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Authors: Emmanuel Larbi Offei, Felix Agyei-Sasu, Maura Naa Densua Ashong

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Ghana has 26 universal banks and several banking and non-banking financial institutions operating in the country. The growing number of banks has heightened competition among banks to attract and retain customers more customers to ensure sustainability. Hence the need to identify and understand factors that influences customers’ choice of banks cannot be overemphasised. This study investigates the determinants of bank selection criteria by banking customers in Ghana. Four banks were purposively sampled for this study namely Barclays, Standard Chartered, Sahel Sahara and Unibank. Convenience sampling was then used to select 114 bank customers in Accra and interviewed. Questionnaires were used to collect data that were analysed in tables and charts with the use of STATA software. The findings of the study revealed that quick/prompt services and complaint handling, safety of funds, networked branches, easy access to functional Automated Teller Machines (ATMs) and low/moderate service charges were the major determinants of customers’ choice of banks. The results further show that 89.5 percent of all deposits are held in either current or savings accounts. About 22.1 percent of the respondents indicated that they have plans of changing their banks in the near future because they are not satisfied with their banks. A gender analysis of the choice criteria showed differences between the choice criteria of the male as compared to the female. The study recommends that banks in Ghana should focus on products and policies that will not compromise on the safety of funds of their customers. Again, banks must address customer complaints and dissatisfactions as promptly as possible by taking pragmatic steps to address administrative bureaucracies and infrastructural challenges that prolong the duration of banking transactions.

Keywords: Ghana, banks, determinants, customers’ choice, competition

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Authors: Rima Hleiss, Elie Bitar, Mahmoud Hassan, Mohamad Khalil

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A comprehensive study of object recognition in the human brain requires combining both spatial and temporal analysis of brain activity. Here, we are mainly interested in three issues: the time perception of visual objects, the ability of discrimination between two particular categories (objects vs. animals), and the possibility to identify a particular spatial representation of visual objects. Our experiment consisted of acquiring dense electroencephalographic (EEG) signals during a picture-naming task comprising a set of objects and animals’ images. These EEG responses were recorded from nine participants. In order to determine the time perception of the presented visual stimulus, we analyzed the Event Related Potentials (ERPs) derived from the recorded EEG signals. The analysis of these signals showed that the brain perceives animals and objects with different time instants. Concerning the discrimination of the two categories, the support vector machine (SVM) was applied on the instantaneous EEG (excellent temporal resolution: on the order of millisecond) to categorize the visual stimuli into two different classes. The spatial differences between the evoked responses of the two categories were also investigated. The results showed a variation of the neural activity with the properties of the visual input. Results showed also the existence of a spatial pattern of electrodes over particular regions of the scalp in correspondence to their responses to the visual inputs.

Keywords: brain activity, categorization, dense EEG, evoked responses, spatio-temporal analysis, SVM, time perception

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Authors: Michael Smalenberger

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Intelligent tutoring systems (ITS) are computer-based platforms which can incorporate artificial intelligence to provide step-by-step guidance as students practice problem-solving skills. ITS can replicate and even exceed some benefits of one-on-one tutoring, foster transactivity in collaborative environments, and lead to substantial learning gains when used to supplement the instruction of a teacher or when used as the sole method of instruction. A common facet of many ITS is their use of Bayesian Knowledge Tracing (BKT) to estimate parameters necessary for the implementation of the artificial intelligence component, and for the probability of mastery of a knowledge component relevant to the ITS. While various techniques exist to estimate these parameters and probability of mastery, none directly and reliably ask the user to self-assess these. In this study, 111 undergraduate students used an ITS in a college-level introductory statistics course for which detailed transaction-level observations were recorded, and users were also routinely asked direct questions that would lead to such a self-assessment. Comparisons were made between these self-assessed values and those obtained using commonly used estimation techniques. Our findings show that such self-assessments are particularly relevant at the early stages of ITS usage while transaction level data are scant. Once a user’s transaction level data become available after sufficient ITS usage, these can replace the self-assessments in order to eliminate the identifiability problem in BKT. We discuss how these findings are relevant to the number of exercises necessary to lead to mastery of a knowledge component, the associated implications on learning curves, and its relevance to instruction time.

Keywords: Bayesian Knowledge Tracing, Intelligent Tutoring System, in vivo study, parameter estimation

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Authors: A. Sewell

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The paper reports a research project which investigated the social interactions of nine to ten-year-olds in a mainstream primary school. The project implemented an adaption of a whole class, behavioural intervention known as 'The Good Behaviour Game (TGBG)'. TGBG is an evidence-based intervention traditionally used to reduce low-level disruptive behaviours in a classroom setting. TGBG was adapted to encourage pupil’s engagement in pro-social behaviour during lessons. A mixed methods research design was employed to evaluate intervention effects and pupil’s perceptions of their social interactions and relationships with others. Single-case research design was used to evaluate behaviour change, and Personal Construct Psychology (PCP) repertory grids were used to explore pupil’s perceptions. The findings demonstrated that TGBG could be successfully adapted to positively influence pupil’s engagement in pro-social behaviours. The findings from the PCP repertory grid interviews revealed the complexities of how children construct their social interactions and relationships with others, and how an understanding of these could be used to design better social skills interventions. It is concluded that TGBG is a cost-effective, simple to implement intervention for promoting positive social interactions and relationships at the whole class level. The paper presents the aims, design, findings, and conclusions of the study in further detail and relates limitations and potential future extensions of the research. The outcomes have direct application and relevance for practitioners interested in children’s social development and how to promote positive outcomes in this critical aspect of childhood.

Keywords: social skills, social development, social competency, the good behaviour game

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Authors: Prachi Bhatt

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Motivated workforce is an important asset of an organisation. Intrinsic motivation is one of the key aspects of people operations and performance. Researches have emphasized the significance of internal factors in individuals’ motivation. In the changing business scenario, it is a challenge for the organizations’ leaders to inspire and motivate their workforce. The present study deals with the intrinsic motivation potential of an individual which govern the innate capability of an individual driving him or her to behave or perform in the changing work environment, tasks, teams. Differences at individual level significantly influence differences in levels of motivation. In the above context, the present research attempts to explore behavioral trait dimensions which influence motivational potential of an individual. The present research emphasizes the significance of intrinsic motivational potential and the significance of exploring the differences in the intrinsic motivational potential levels of individuals at work places. Thus, this paper empirically tests the framework of behavioral traits which affects motivational potential of an individual. With the help of two studies i.e., Study 1 and Study 2, exploratory factor analysis and confirmatory factor analysis, respectively, indicated a reliable measure assessing intrinsic motivational potential of an individual. Given the variety of challenges of motivating contemporary workforce, and with increasing importance of intrinsic motivation, the paper discusses the relevance of the findings and of the measure assessing intrinsic motivational potential. Assessment of such behavioral traits would assist in the effective realization of intrinsic motivational potential of individuals. Additionally, the paper discusses the practical implications and furnishes scope for future research.

Keywords: behavioral traits, individual differences, intrinsic motivational potential, intrinsic motivation, motivation, workplace motivation

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Authors: Elisabeth Eder

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Memorizing music plays an important role for instrumentalists and has been researched very little so far. Almost every musician is confronted with memorizing music in the course of their musical career. For numerous competitions, examinations (e.g., at universities, music schools), solo performances, and the like, memorization is a requirement. Learners are often required to learn a piece by heart but are rarely given guidance on how to proceed. This was also confirmed by Eder's preliminary study to examine the topicality and relevance of the topic, in which 111 instrumentalists took part. The preliminary study revealed a great desire for more knowledge or information about learning strategies as well as a greater sense of security when performing by heart on stage through the use of learning strategies by those musicians who use learning strategies. Eder’s research focuses on learning strategies for memorizing music. As part of a large-scale empirical study – an online questionnaire translated into 10 languages was used to conduct the study – 1091 musicians from 64 different countries described how they memorize. The participants in the study also evaluated their learning strategies and justified their choice in terms of their degree of effectiveness. Based on the study and pedagogical literature, 100 learning strategies were identified and categorized; the strategies were examined with regard to their effectiveness, and instrument-specific, age-specific, country-specific, gender-specific, and education-related differences and similarities concerning the choice of learning strategies were investigated. Her research also deals with forms and models of memory and how music-related information can be stored and retrieved and also forgotten again. A further part is devoted to the possibilities that teachers and learners have to support the process of memorization independently of learning strategies. The findings resulting from Elisabeth Eder's research should enable musicians and instrumental students to memorize faster and more confidently.

Keywords: memorizing music, learning strategies, empirical study, effectiveness of strategies

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