Search results for: mobile learning technology acceptance

Authors: Collins Molua

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This paper investigated the effect of Teaching Strategies on Academic Achievement in Secondary Physics Education as a quality assurance process for the teaching and learning of the subject. Teaching strategies investigated were the interactive, independent and dependent strategies. Three null hypotheses were tested at p< 0.05 using one instrument, physics achievement test(PAT).The data were analyzed using analysis of covariance (ANCOVA).Results showed that teaching strategies have significant effect on students achievement; the joint effect of the teaching strategies was also significant on students achievement in Physics. The interactive teaching strategies was recommended for teaching the subject and the students should be exposed to practical, computer literacy to stimulate interest and curiosity to enhance quality.

Keywords: quality, assurance, secondary education, strategies, physics

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Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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Authors: Gianna Zou

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Propensity score matching (PSM), introduced by Paul R. Rosenbaum and Donald Rubin in 1983, is a popular statistical matching technique which tries to estimate the treatment effects by taking into account covariates that could impact the efficacy of study medication in clinical trials. PSM can be used to reduce the bias due to confounding variables. However, PSM assumes that the response values are normally distributed. In some cases, this assumption may not be held. In this paper, a machine learning method - Bayesian Additive Regression Tree (BART), is used as a more robust method of matching. BART can work well when models are misspecified since it can be used to model heterogeneous treatment effects. Moreover, it has the capability to handle non-linear main effects and multiway interactions. In this research, a BART Matching Method (BMM) is proposed to provide a more reliable matching method over PSM. By comparing the analysis results from PSM and BMM, BMM can perform well and has better prediction capability when the response values are not normally distributed.

Keywords: BART, Bayesian, matching, regression

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Authors: Khulood Miliany

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This study examines the media habits of young people in Saudi Arabia, in particular their use of the Internet and television in the domestic sphere, and how use of the Internet impacts upon other activities. In order to address the research questions, focus group interviews were conducted with Saudi university students. The study found that television has become a central part of social life within the household where television represents a main source for family time, particularly in Ramadan while the Internet is a solitary activity where it is used in more private spaces. Furthermore, Saudi females were also more likely to have their Internet access monitored and circumscribed by family members, with parents controlling the location and the amount of time spent using the Internet.

Keywords: domestication of technology, internet, social context, television, young people

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Authors: Almagul Assainova , Dariya Abykenova, Liudmila Goncharenko, Sergey Sybachin, Saule Rakhimova, Abay Aman

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The recognition of a handwritten Kazakh text is a relevant objective today for the digitization of materials. The study presents a model of a hybrid neural network for handwriting recognition, which includes a convolutional neural network and a multi-layer perceptron. Each network includes 1024 input neurons and 42 output neurons. The model is implemented in the program, written in the Python programming language using the EMNIST database, NumPy, Keras, and Tensorflow modules. The neural network training of such specific letters of the Kazakh alphabet as ә, ғ, қ, ң, ө, ұ, ү, h, і was conducted. The neural network model and the program created on its basis can be used in electronic document management systems to digitize the Kazakh text.

Keywords: handwriting recognition system, image recognition, Kazakh font, machine learning, neural networks

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Authors: Suleiman Babani, Jazuli Sanusi Kazaure

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In this paper, two coupled-line couplers are designed and simulated using stripline technology. The coupled-line couplers (A and B) are designed with different values of coupling coefficient 6dB and 10dB respectively. Both of circuits have a coupled output port, a through output port and an isolated output port. Moreover, both circuits are tuned to function around 2.45 GHz. The design results are presented by simulation results obtained using ADS 2012.08 (Advanced Design System) software.

Keywords: ADS, coupled-line coupler, directional coupler, stripline

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Authors: Maria E. Eggink

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Human capital is one of the essential factors in an innovation system and innovation is the driving force of economic growth and development. Schumpeter focused on the entrepreneur as innovator, but the evolutionary economists shifted the focus to all participants in the innovation system. Education and training institutions are important participants in an innovation system, but there is a gap in literature on competence building as part of the analysis of innovation systems. In this paper the education and training institutions’ competence building role in the innovation system is examined. The Mpumalanga Province of South Africa is used as a case study. It was found that the absence of a university, the level of education, the quality and performance in the education sector and the condition of the education infrastructure have not been conducive to learning.

Keywords: education institutions, human capital, innovation systems, Mpumalanga Province

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Authors: Nada Mouchfiq, Ahmed Habbani, Chaimae Benjbara

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The security aspect of the IoT occupies a place of great importance especially after the evolution that has known this field lastly because it must take into account the transformations and the new applications .Blockchain is a new technology dedicated to the data sharing. However, this does not work the same way in the different systems with different operating principles. This article will discuss network security using the Blockchain to facilitate the sending of messages and information, enabling the use of new processes and enabling autonomous coordination of devices. To do this, we will discuss proposed solutions to ensure a high level of security in these networks in the work of other researchers. Finally, our article will propose a method of security more adapted to our needs as a team working in the ad hoc networks, this method is based on the principle of the Blockchain and that we named ”MPR Blockchain”.

Keywords: Ad hocs networks, blockchain, MPR, security

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Authors: Natalia Podkhodova, Olga Sheremeteva, Mariia Soldaeva

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Creating favorable conditions for students’ comprehension of mathematical content is one of the primary problems in teaching mathematics in secondary school. Psychology research has demonstrated that positive comprehension becomes possible when new information becomes part of student’s subjective experience and when linkages between the attributes of notions and various ways of their presentations can be established. The fact of comprehension includes the ability to build a working situational model and thus becomes an important means of solving mathematical problems. The article describes the implementation of a holistic approach to teaching mathematics designed to address the primary challenges of such teaching, specifically, the challenge of students’ comprehension. This approach consists of (1) establishing links between the attributes of a notion: the sense, the meaning, and the term; (2) taking into account the components of student’s subjective experience -emotional and value, contextual, procedural, communicative- during the educational process; (3) links between different ways to present mathematical information; (4) identifying and leveraging the relationships between real, perceptual and conceptual (scientific) mathematical spaces by applying real-life situational modeling. The article describes approaches to the practical use of these foundational concepts. Identifying how proposed methods and technology influence understanding of material used in teaching mathematics was the research’s primary goal. The research included an experiment in which 256 secondary school students took part: 142 in the experimental group and 114 in the control group. All students in these groups had similar levels of achievement in math and studied math under the same curriculum. In the course of the experiment, comprehension of two topics -'Derivative' and 'Trigonometric functions'- was evaluated. Control group participants were taught using traditional methods. Students in the experimental group were taught using the holistic method: under the teacher’s guidance, they carried out problems designed to establish linkages between notion’s characteristics, to convert information from one mode of presentation to another, as well as problems that required the ability to operate with all modes of presentation. The use of the technology that forms inter-subject notions based on linkages between perceptional, real, and conceptual mathematical spaces proved to be of special interest to the students. Results of the experiment were analyzed by presenting students in each of the groups with a final test in each of the studied topics. The test included problems that required building real situational models. Statistical analysis was used to aggregate test results. Pierson criterion was used to reveal the statistical significance of results (pass-fail the modeling test). A significant difference in results was revealed (p < 0.001), which allowed the authors to conclude that students in the study group showed better comprehension of mathematical information than those in the control group. Also, it was revealed (used Student’s t-test) that the students of the experimental group performed reliably (p = 0.0001) more problems in comparison with those in the control group. The results obtained allow us to conclude that increasing comprehension and assimilation of study material took place as a result of applying implemented methods and techniques.

Keywords: comprehension of mathematical content, holistic approach to teaching mathematics in secondary school, subjective experience, technology of the formation of inter-subject notions

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Authors: Carlos Alberto Rivera-corredor, Angie Dayana Vargas-Ceballos, Edison Gilpavas, Izabela Dobrosz-Gómez, Miguel Ángel Gómez-García

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Hexavalent chromium, Cr (VI) is present in the effluents from different industries such as electroplating, mining, leather tanning, etc. This compound is of great academic and industrial concern because of its toxic and carcinogenic behavior. Its dumping to both environmental and public health for animals and humans causes serious problems in water sources. The amount of Cr (VI) in industrial wastewaters ranges from 0.5 to 270,000 mgL-1. According to the Colombian standard for water quality (NTC-813-2010), the maximum allowed concentration for the Cr (VI) in drinking water is 0.05 mg L-1. To comply with this limit, it is essential that industries treat their effluent to reduce the Cr (VI) to acceptable levels. Numerous methods have been reported for the treatment removing metal ions from aqueous solutions such as: reduction, ion exchange, electrodialysis, etc. Adsorption has become a promising method for the purification of metal ions in water, since its application corresponds with an economic and efficient technology. The absorbent selection and the kinetic and thermodynamic study of the adsorption conditions are key to the development of a suitable adsorption technology. The Ce0.25Zr0.75O2.nH2O presents higher adsorption capacity between a series of hydrated mixed oxides Ce1-xZrxO2 (x = 0, 0.25, 0.5, 0.75, 1). This work presents the kinetic and thermodynamic study of Cr (VI) adsorption on Ce0.25Zr0.75O2.nH2O. Experiments were performed under the following experimental conditions: initial Cr (VI) concentration = 25, 50 and 100 mgL-1, pH = 2, adsorbent charge = 4 gL-1, stirring time = 60 min, temperature=20, 28 and 40 °C. The Cr (VI) concentration was spectrophotometrically estimated by the method of difenilcarbazide with monitoring the absorbance at 540 nm. The Cr (VI) adsorption over hydrated Ce0.25Zr0.75O2.nH2O models was analyzed using pseudo-first and pseudo-second order kinetics. The Langmuir and Freundlich models were used to model the experimental data. The convergence between the experimental values and those predicted by the model, is expressed as a linear regression correlation coefficient (R2) and was employed as the model selection criterion. The adsorption process followed the pseudo-second order kinetic model and obeyed the Langmuir isotherm model. The thermodynamic parameters were calculated as: ΔH°=9.04 kJmol-1,ΔS°=0.03 kJmol-1 K-1, ΔG°=-0.35 kJmol-1 and indicated the endothermic and spontaneous nature of the adsorption process, governed by physisorption interactions.

Keywords: adsorption, hexavalent chromium, kinetics, thermodynamics

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Authors: Margarita Zavala, Gabriel Chavira, José González, Jorge Orozco, Julio Rolón, Roberto Pichardo

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Adolescence is a neuralgic stage in the formation of every human being, generally this stage is when the middle school level is studied. In 2006, Mexico incorporated 'mentoring' space to assist students in their integration and participation in life. In public middle schools, it is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. With this, they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

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Authors: Gowtham Kalkere Jayanna, Mohamad Nazri Husin

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Graph theory, chemistry, and technology are all combined in cheminformatics. The structure and physiochemical properties of organic substances are linked using some useful graph invariants and the corresponding molecular graph. In this paper, we study specific reverse topological indices such as the reverse sum-connectivity index, the reverse Zagreb index, the reverse arithmetic-geometric, and the geometric-arithmetic, the reverse Sombor, the reverse Nirmala indices for the bistar graphs B (n: m) and the corona product Kₘ∘Kₙ', where Kₙ' Represent the complement of a complete graph Kₙ.

Keywords: reverse topological indices, bistar graph, the corona product, graph

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Authors: Hengameh Hosseini

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Design of large healthcare facilities – such as hospitals, multi-service line clinics, and nursing facilities - that can accommodate patients with wide-ranging disabilities is a challenging endeavor and one that is poorly understood among healthcare facility managers, administrators, and executives. An even less-understood extension of this problem is the implications of weakly or insufficiently accommodative design of facilities for healthcare workers in physically-intensive jobs who may also suffer from a range of disabilities and who are therefore at increased risk of workplace accident and injury. Combine this reality with the vast range of facility types, ages, and designs, and the problem of universal accommodation becomes even more daunting and complex. In this study, we focus on the implication of facility design for healthcare workers suffering with low vision who also have physically active jobs. The points of difficulty are myriad and could span health service infrastructure, the equipment used in health facilities, and transport to and from appointments and other services can all pose a barrier to health care if they are inaccessible, less accessible, or even simply less comfortable for people with various disabilities. We conduct a series of surveys and interviews with employees and administrators of 7 facilities of a range of sizes and ownership models in the Northeastern United States and combine that corpus with in-facility observations and data collection to identify five major points of failure common to all the facilities that we concluded could pose safety threats to employees with vision impairments, ranging from very minor to severe. We determine that lack of design empathy is a major commonality among facility management and ownership. We subsequently propose three methods for remedying this lack of empathy-informed design, to remedy the dangers posed to employees: the use of an existing open-sourced Augmented Reality application to simulate the low-vision experience for designers and managers; the use of a machine learning model we develop to automatically infer facility shortcomings from large datasets of recorded patient and employee reviews and feedback; and the use of a computer vision model fine tuned on images of each facility to infer and predict facility features, locations, and workflows, that could again pose meaningful dangers to visually impaired employees of each facility. After conducting a series of real-world comparative experiments with each of these approaches, we conclude that each of these are viable solutions under particular sets of conditions, and finally characterize the range of facility types, workforce composition profiles, and work conditions under which each of these methods would be most apt and successful.

Keywords: artificial intelligence, healthcare workers, facility design, disability, visually impaired, workplace safety

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Authors: Hanane Sarnou, Sabri Koç

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In this paper, the interconnection between curriculum development for basic education and the use of information and communication technologies (ICTs) in the classroom referring to the Licence, Master's and Doctorate (LMD) benefits under such link will be presented and analysed. This study seeks to achieve to what extent LMD, competency-based approach (CBA) and ICTs use are interrelated. Likewise, the data collected from the responses of our teachers and learners who are concerned with LMD impact on their learning and teaching through interviews will be discussed, analysed, and classified. This paper is divided into two sections. The first section is about the curriculum development for basic education and its relation with higher education under the LMD and its link with ICTs in the university while the second section is about the classification of learners’ and teachers’ positive/negative responses concerning their positive or negative attitudes towards the ICT integration. The focus will be on the positive aspects of students’ expectations, opinions and assumptions regarding the integration of ICTs into the classroom under LMD and CBA.

Keywords: LMD system, CBA approach, curriculum development, ICT

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Authors: Bagnoud-Velásquez Mariluz, Damergi Eya, Grandjean Dominique, Frédéric Vogel, Ludwig Christian

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The sustainability of algae to biofuel processes is seriously affected by the energy intensive production of fertilizers. Large amounts of nitrogen and phosphorus are required for a large-scale production resulting in many cases in a negative impact of the limited mineral resources. In order to meet the algal bioenergy opportunity it appears crucial the promotion of processes applying a nutrient recovery and/or making use of renewable sources including waste. Hydrothermal (HT) conversion is a promising and suitable technology for microalgae to generate biofuels. Besides the fact that water is used as a “green” reactant and solvent and that no biomass drying is required, the technology offers a great potential for nutrient recycling. This study evaluated the possibility to treat the water HT effluent by the growth of microalgae while producing renewable algal biomass. As already demonstrated in previous works by the authors, the HT aqueous product besides having N, P and other important nutrients, presents a small fraction of organic compounds rarely studied. Therefore, extracted heteroaromatic compounds in the HT effluent were the target of the present research; they were profiled using GC-MS and LC-MS-MS. The results indicate the presence of cyclic amides, piperazinediones, amines and their derivatives. The most prominent nitrogenous organic compounds (NOC’s) in the extracts were carefully examined by their effect on microalgae, namely 2-pyrrolidinone and β-phenylethylamine (β-PEA). These two substances were prepared at three different concentrations (10, 50 and 150 ppm). This toxicity bioassay used three different microalgae strains: Phaeodactylum tricornutum, Chlorella sorokiniana and Scenedesmus vacuolatus. The confirmed IC50 was for all cases ca. 75ppm. Experimental conditions were set up for the growth of microalgae in the aqueous phase by adjusting the nitrogen concentration (the key nutrient for algae) to fit that one established for a known commercial medium. The values of specific NOC’s were lowered at concentrations of 8.5 mg/L 2-pyrrolidinone; 1mg/L δ-valerolactam and 0.5 mg/L β-PEA. The growth with the diluted HT solution was kept constant with no inhibition evidence. An additional ongoing test is addressing the possibility to apply an integrated water cleanup step making use of the existent hydrothermal catalytic facility.

Keywords: hydrothermal process, microalgae, nitrogenous organic compounds, nutrient recovery, renewable biomass

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Authors: Ali Nouri

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Neuroeducation is one of the most exciting research fields which is continually evolving. However, there is a need to develop its theoretical bases in connection to practice. The present paper is a starting attempt in this regard to provide a space from which to think about neuroeducational theory and invoke more investigation in this area. Accordingly, a comprehensive theory of neuroeducation could be defined as grouping or clustering of concepts and propositions that describe and explain the nature of human learning to provide valid interpretations and implications useful for educational practice in relation to philosophical aspects or values. Whereas it should be originated from the philosophical foundations of the field and explain its normative significance, it needs to be testable in terms of rigorous evidence to fundamentally advance contemporary educational policy and practice. There is thus pragmatically a need to include a course on neuroeducational theory into the curriculum of the field. In addition, there is a need to articulate and disseminate considerable discussion over the subject within professional journals and academic societies.

Keywords: neuroeducation studies, neuroeducational theory, theory building, neuroeducation research

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Authors: Omaima A. Sharaf, Wafaa M. Abd El-Rahim, Hassan Moawad, Michael J. Sadowsky

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Textile industry is one of the important industries in the worldwide. It is known that the eco-friendly industrial and agricultural activities are significant for socio-economic stability of all countries. The absence of appropriate industrial waste water treatments is essential barrier for sustainable development in food and agricultural sectors especially in developing country like Egypt. Thus, the development of enzymatic bioremediation technology for textile dye removal will enhance the collaboration between scientists who develop the technology and industry where this technology will be implemented towards the safe disposal of the textile dye wastes. Highly efficient microorganisms are of most importance in developing and using highly effective biological treatment processes. Bacterial degradation of azo dyes is generally initiated by an enzymatic step that involves cleavage of azo linkages, usually with the aid of an azoreductase as electron donor. Thus, expanding the spectrum of microorganisms with high enzymatic activities as azoreductases and discovering novel azo-dye degrading enzymes, with enhanced stability and superior catalytic properties, are necessary for many environmental and industrial applications. Consequently, the use of molecular tools has become increasingly integrated into the understanding of enzyme properties and characterization. Researchers have utilized a gene cloning and expression methods as a tool to produce recombinant protein for decolorizing dyes more efficiently. Thus, presumptive evidence for the presence of genes encoding azoreductases in the genomes of selected local, and most potent azo-degrading strains were obtained by using specific oligonucleotides primers. These potent strains have been isolated from textile industrial wastewater in Egypt and identified using 16S rRNA sequence analysis as 'Lysinibacillus macrolidesB8, Brevibacillus parabrevisB11, Bacillus coagulansB7, and B. cereusB5'. PCR products of two full length genes designated as (AZO1;621bp and AZO2;534bp) were detected. BLASTx results indicated that AZO1 gene was corresponding to predicted azoreductase from of Bacillus sp. ABP14, complete genome, multispecies azoreductase [Bacillus], It was submitted to the gene bank by an accession no., BankIt2085371 AZO1 MG923210 (621bp; 207 amino acids). AZO1 was generated from the DNA of our identified strains Lysinibacillus macrolidesB8. On the other hand, AZO2 gene was corresponding to a predicted azoreductase from Bacillus cereus strain S2-8. Gene bank accession no. was BankIt2085839 AZO2 MG932081 (534bp;178 amino acids) and it was amplified from our Bacillus coagulansB7. Both genes were successfully cloned into pCR2.1TOPO (Invitrogen) and in pET28b+ vectors, then they transformed into E. coli DH5α and BL21(DE3) cells for heterologous expression studies. Our recombinant azoreductases (AZO1&AZO2) exhibited potential enzyme activity and efficiently decolorized an azo dye (Direct violet). They exhibited pH stability between 6 and 8 with optimum temperature up to 60°C and 37 °C after induction by 1mM and 1.5mM IPTG, for both AZO1 &AZO2, respectively. These results suggested that further optimization and purification of these recombinant proteins by using different heterologous expression systems will give great potential for the sustainable utilization of these recombinant enzymes in several industrial applications especially in wastewater treatments.

Keywords: azoreductases, decolorization, enzyme activity, gene cloning and expression

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Authors: S. Sumanth, Babu Rao Ponangi, K. N. Seetharamu

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As the technology is emerging day by day, there is a need for some better methodology which will enhance the performance of radiator. Nanofluid is the one area which has promised the enhancement of the radiator performance. Currently, nanofluid has got a well effective solution for enhancing the performance of the automobile radiators. Suspending the nano sized particle in the base fluid, which has got better thermal conductivity value when compared to a base fluid, is preferably considered for nanofluid. In the current work, at first mathematical formulation has been carried out, which will govern the performance of the radiator. Current work is justified by plotting the graph for different parameters. Current work justifies the enhancement of radiator performance using nanofluid.

Keywords: nanofluid, radiator performance, graphene, gamma aluminium oxide (γ-Al2O3), titanium dioxide (TiO2)

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Authors: Aravind Ravichandran, Marc Ramuz, Sylvain Blayac

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With the rapid development of wearable electronics and sensor networks, batteries cannot meet the sustainable energy requirement due to their limited lifetime, size and degradation. Ambient energies such as wind have been considered as an attractive energy source due to its copious, ubiquity, and feasibility in nature. With miniaturization leading to high-power and robustness, triboelectric nanogenerator (TENG) have been conceived as a promising technology by harvesting mechanical energy for powering small electronics. TENG integration in large-scale applications is still unexplored considering its attractive properties. In this work, a state of the art design TENG based on wind venturi system is demonstrated for use in any complex environment. When wind introduces into the air gap of the homemade TENG venturi system, a thin flexible polymer repeatedly contacts with and separates from electrodes. This device structure makes the TENG suitable for large scale harvesting without massive volume. Multiple stacking not only amplifies the output power but also enables multi-directional wind utilization. The system converts ambient mechanical energy to electricity with 400V peak voltage by charging of a 1000mF super capacitor super rapidly. Its future implementation in an array of applications aids in environment friendly clean energy production in large scale medium and the proposed design performs with an exhaustive material testing. The relation between the interfacial micro-and nano structures and the electrical performance enhancement is comparatively studied. Nanostructures are more beneficial for the effective contact area, but they are not suitable for the anti-adhesion property due to the smaller restoring force. Considering these issues, the nano-patterning is proposed for further enhancement of the effective contact area. By considering these merits of simple fabrication, outstanding performance, robust characteristic and low-cost technology, we believe that TENG can open up great opportunities not only for powering small electronics, but can contribute to large-scale energy harvesting through engineering design being complementary to solar energy in remote areas.

Keywords: triboelectric nanogenerator, wind energy, vortex design, large scale energy

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Authors: Jaeyoung Lee

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Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Athanase Gahungu, Karen Freeman

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Different groups of stakeholders expect the evaluation of an international, grant-funded program to inform them of the worth of the program - the funder, the agency operating the program and its community, and the citizens of the country where the program is implemented. This paper summarizes the challenges that intercultural teams of researchers faced as they crisscrossed a host country while evaluating a teaching and learning materials program, and offers useful tips for effective collaboration. Firstly, was recommended that the teams be representative of the cultures involved, and have the required research and program evaluation skills. Secondly, cultures involved must consistently establish and maintain a shared performance system. Thirdly, successful team members must be self-aware, inter-culturally knowledgeable, not just in communication, but in conceptualizing the political and social context of international grant-funded projects.

Keywords: program evaluation, international collaboration, intercultural, shared performance

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Authors: Ran Goldblatt, Nicholas Jones, Jennifer Mannix, Brad Bottoms

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Accurate, complete, and up-to-date geospatial information is the foundation of successful disaster management. When the 2010 Haiti Earthquake struck, accurate and timely information on the distribution of critical infrastructure was essential for the disaster response community for effective search and rescue operations. Existing geospatial datasets such as Google Maps did not have comprehensive coverage of these features. In the days following the earthquake, many organizations released high-resolution satellite imagery, catalyzing a worldwide effort to map Haiti and support the recovery operations. Of these organizations, OpenStreetMap (OSM), a collaborative project to create a free editable map of the world, used the imagery to support volunteers to digitize roads, buildings, and other features, creating the most detailed map of Haiti in existence in just a few weeks. However, large portions of the island are still not fully covered by OSM. There is an increasing need for a tool to automatically identify which areas in Haiti, as well as in other countries vulnerable to disasters, that are not fully mapped. The objective of this project is to leverage different types of remote sensing measurements, together with machine learning approaches, in order to identify geographical areas where OSM coverage of building footprints is incomplete. Several remote sensing measures and derived products were assessed as potential predictors of OSM building footprints coverage, including: intensity of light emitted at night (based on VIIRS measurements), spectral indices derived from Sentinel-2 satellite (normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), soil-adjusted vegetation index (SAVI), urban index (UI)), surface texture (based on Sentinel-1 SAR measurements)), elevation and slope. Additional remote sensing derived products, such as Hansen Global Forest Change, DLR`s Global Urban Footprint (GUF), and World Settlement Footprint (WSF), were also evaluated as predictors, as well as OSM street and road network (including junctions). Using a supervised classification with a random forest classifier resulted in the prediction of 89% of the variation of OSM building footprint area in a given cell. These predictions allowed for the identification of cells that are predicted to be covered but are actually not mapped yet. With these results, this methodology could be adapted to any location to assist with preparing for future disastrous events and assure that essential geospatial information is available to support the response and recovery efforts during and following major disasters.

Keywords: disaster management, Haiti, machine learning, OpenStreetMap, remote sensing

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Authors: Colin David La Grange, Lisa Frost Ramsay

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Hydrogen sulphide (H2S) is a minor component of landfill gas, but significant in its distinct odorous quality and its association with landfill-related community complaints. The World Health Organisation (WHO) provides two guidelines for H2S: a health guideline at 150 µg/m3 on a 24-hour average, and a nuisance guideline at 7 µg/m3 on a 30-minute average. Albeit a practical distinction for impact assessment, this paper highlights the danger of the apparent dualism between nuisance and health impact, particularly when it is used to dismiss community concerns of perceived health impacts at low concentrations of H2S, as in the case of a community battle against the impacts of a landfill in Shongweni, KwaZulu-Natal, South Africa. Here community members reported, using a community developed mobile phone application, a range of health symptoms that coincided with, or occurred subsequent to, odour events and localised H2S peaks. Local doctors also documented increased visits for symptoms of respiratory distress, eye and skin irritation, and stress after such odour events. Objectively measured H2S and other pollutant concentrations during these events, however, remained below WHO health guidelines. This case study highlights the importance of the physiological link between the experience of environmental nuisance and overall health and wellbeing, showing these to be less distinct than the WHO guidelines would suggest. The potential mechanisms of impact of an odorous plume, with key constituents at concentrations below traditional health thresholds, on psychologically and/or physiologically sensitised individuals are described. In the case of psychological sensitisation, previously documented mechanisms such as aversive conditioning and odour-triggered panic are relevant. Physiological sensitisation to environmental pollutants, evident as a seemingly disproportionate physical (allergy-type) response to either low concentrations or a short duration exposure of a toxin or toxins, remains extensively examined but still not well understood. The links between a heightened sensitivity to toxic compounds, accumulation of some compounds in the body, and a pre-existing or associated immunological stress disorder are presented as a possible explanation.

Keywords: immunological stress disorder, landfill odour, odour nuisance, odour sensitisation, toxin accumulation

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Authors: Ashley Venerable, Rosario Tatlonghari

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This study identified how college deaf students of Bartimaeus Center for Alternative Learning in Tiaong, Quezon, Philippines view development using visual communication techniques and generating themes from responses. Complete enumeration was employed. Guided by Constructivist Theory of Perception, past experiences and stored information influenced perception. These themes of development emerged: social development; pleasant environment; interpersonal relationships; availability of resources; employment; infrastructure development; values; and peace and security. Using the National Economic and Development Authority development indicators, findings showed the deaf students’ views on development were similar from the mainstream views. Responses also became more meaningful through visual communication techniques.

Keywords: deaf, development, perception, development indicators, visual communication

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Authors: K. O'Malley

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Background: The emergence and rapid evolution of large language models (LLMs) (i.e., models of generative artificial intelligence, or AI) has been unprecedented. ChatGPT is one of the most widely used LLM platforms. Using natural language processing technology, it generates customized responses to user prompts, enabling it to mimic human conversation. Responses are generated using predictive modeling of vast internet text and data swathes and are further refined and reinforced through user feedback. The popularity of LLMs is increasing, with a growing number of students utilizing these platforms for study and revision purposes. Notwithstanding its many novel applications, LLM technology is inherently susceptible to bias and error. This poses a significant challenge in the educational setting, where academic integrity may be undermined. This study aims to evaluate the performance of the latest iteration of ChatGPT (ChatGPT4.0) in standardized state medical licensing examinations. Methods: A considered search strategy was used to interrogate the PubMed electronic database. The keywords ‘ChatGPT’ AND ‘medical education’ OR ‘medical school’ OR ‘medical licensing exam’ were used to identify relevant literature. The search included all peer-reviewed literature published in the past five years. The search was limited to publications in the English language only. Eligibility was ascertained based on the study title and abstract and confirmed by consulting the full-text document. Data was extracted into a Microsoft Excel document for analysis. Results: The search yielded 345 publications that were screened. 225 original articles were identified, of which 11 met the pre-determined criteria for inclusion in a narrative synthesis. These studies included performance assessments in national medical licensing examinations from the United States, United Kingdom, Saudi Arabia, Poland, Taiwan, Japan and Germany. ChatGPT 4.0 achieved scores ranging from 67.1 to 88.6 percent. The mean score across all studies was 82.49 percent (SD= 5.95). In all studies, ChatGPT exceeded the threshold for a passing grade in the corresponding exam. Conclusion: The capabilities of ChatGPT in standardized academic assessment in medicine are robust. While this technology can potentially revolutionize higher education, it also presents several challenges with which educators have not had to contend before. The overall strong performance of ChatGPT, as outlined above, may lend itself to unfair use (such as the plagiarism of deliverable coursework) and pose unforeseen ethical challenges (arising from algorithmic bias). Conversely, it highlights potential pitfalls if users assume LLM-generated content to be entirely accurate. In the aforementioned studies, ChatGPT exhibits a margin of error between 11.4 and 32.9 percent, which resonates strongly with concerns regarding the quality and veracity of LLM-generated content. It is imperative to highlight these limitations, particularly to students in the early stages of their education who are less likely to possess the requisite insight or knowledge to recognize errors, inaccuracies or false information. Educators must inform themselves of these emerging challenges to effectively address them and mitigate potential disruption in academic fora.

Keywords: artificial intelligence, ChatGPT, generative ai, large language models, licensing exam, medical education, medicine, university

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Authors: Xinqi Guo, Karen R. Dobkins

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Background and Objectives: Humans are probably the only animals whose minds are constantly filled with thoughts, feelings and emotions. Previous studies have investigated human minds from different dimensions, including its proportion of time for not being present, its representative format, its personal relevance, its temporal locus, and affect valence. The current study aims at characterizing human mind by employing Experience Sampling Methods (ESM), a self-report research procedure for studying daily experience. This study emphasis on answering the following questions: 1) How does the contents of the inner experience vary across demographics, 2) Are certain types of inner experiences correlated with level of mindfulness and mental well-being (e.g., are people who spend more time being present happier, and are more mindful people more at-present?), 3) Will being prompted to report one’s inner experience increase mindfulness and mental well-being? Methods: Participants were recruited from the subject pool of UC San Diego or from the social media. They began by filling out two questionnaires: 1) Five Facet Mindfulness Questionnaire-Short Form, and 2) Warwick-Edinburgh Mental Well-being Scale, and demographic information. Then they participated in the ESM part by responding to the prompts which contained questions about their real-time inner experience: if they were 'at-present', 'mind-wandering', or 'zoned-out'. The temporal locus, the clarity, and the affect valence, and the personal importance of the thought they had the moment before the prompt were also assessed. A mobile app 'RealLife Exp' randomly delivered these prompts 3 times/day for 6 days during wake-time. After the 6 days, participants completed questionnaire (1) and (2) again. Their changes of score were compared to a control group who did not participate in the ESM procedure (yet completed (1) and (2) one week apart). Results: Results are currently preliminary as we continue to collect data. So far, there is a trend that participants are present, mind-wandering and zoned-out, about 53%, 23% and 24% during wake-time, respectively. The thoughts of participants are ranked to be clearer and more neutral if they are present vs. mind-wandering. Mind-wandering thoughts are 66% about the past, consisting 80% of inner speech. Discussion and Conclusion: This study investigated the subjective account of human mind by a tool with high ecological validity. And it broadens the understanding of the relationship between contents of mind and well-being.

Keywords: experience sampling method, meta-memory, mindfulness, mind-wandering

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Authors: Nan Hu, Chao Wang, Xi Li, Xuehai Zhou

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The field-programmable gate array (FPGA) has been widely adopted in the high-performance computing domain. In recent years, the embedded system-on-a-chip (SoC) contains coarse granularity multi-core CPU (central processing unit) and mobile GPU (graphics processing unit) that can be used as general-purpose accelerators. The motivation is that algorithms of various parallel characteristics can be efficiently mapped to the heterogeneous architecture coupled with these three processors. The CPU and GPU offload partial computationally intensive tasks from the FPGA to reduce the resource consumption and lower the overall cost of the system. However, in present common scenarios, the applications always utilize only one type of accelerator because the development approach supporting the collaboration of the heterogeneous processors faces challenges. Therefore, a systematic approach takes advantage of write-once-run-anywhere portability, high execution performance of the modules mapped to various architectures and facilitates the exploration of design space. In this paper, A servant-execution-flow model is proposed for the abstraction of the cooperation of the heterogeneous processors, which supports task partition, communication and synchronization. At its first run, the intermediate language represented by the data flow diagram can generate the executable code of the target processor or can be converted into high-level programming languages. The instantiation parameters efficiently control the relationship between the modules and computational units, including two hierarchical processing units mapping and adjustment of data-level parallelism. An embedded system of a three-dimensional waveform oscilloscope is selected as a case study. The performance of algorithms such as contrast stretching, etc., are analyzed with implementations on various combinations of these processors. The experimental results show that the heterogeneous computing system with less than 35% resources achieves similar performance to the pure FPGA and approximate energy efficiency.

Keywords: FPGA-CPU-GPU collaboration, design space exploration, heterogeneous computing, intermediate language, parameterized instantiation

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Authors: Jabulani Sibanda, Clemence Chikiwa

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This paper traces diverse language practices representative of equally diverse conceptions of language. To be dynamic with languaging practices, one needs to appreciate nuanced languaging practices, their challenges, prospects, and opportunities. The paper presents what we envision as three major conceptions of language that give impetus to diverse language practices. It examines theoretical models of the bilingual mental lexicon and how they inform language practices. The paper explores classroom languaging practices that have been promulgated and experimented with. The paper advocates the deployment of multisensory semiotic systems to complement linguistic classroom communication and the acknowledgement of learners’ linguistic and semiotic resources as valid in the learning enterprise. It recommends the enactment of specific clauses on language in education policies and curriculum documents that empower classroom interactants to exercise discretion in languaging practices.

Keywords: languaging, monolingual, multilingual, semiotic and linguistic repertoire

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Authors: Sumitra Sharma, Christina Parker, Kathleen Finlayson, Clint Douglas, Niall Higgins

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Background: Telehealth services have potential to increase accessibility, utilization, and effectiveness of healthcare services. As the telehealth services are yet to integrate within regular hospital services in Nepal, the use of the telehealth services among adults with diabetes is scarce. Prior to implementation of telehealth services for adults with diabetes, it is necessary to examine influencing factors of telehealth services. Objective: This study aimed to investigate factors influencing telehealth services for diabetes care in Nepal. Methods: This study used a mixed-method study design which included a cross-sectional survey among adults with diabetes and semi-structured interviews among key healthcare professionals of Nepal. The study was conducted in a medical out-patient department of a tertiary hospital of Nepal. The survey adapted a previously validated questionnaire, while semi-structured questions for interviews were developed from literature review and experts consultation. All interviews were audio-recorded, and inductive content analysis was used to code transcripts and develop themes. For a survey, a descriptive analysis, chi-square test, and Mann Whitney U test were used to analyze the data. Results: One hundred adults with diabetes were participated in a survey, and seven healthcare professionals were recruited for interviews. In a survey, just over half of the participants (53%) were male, and others were female. Almost all participants (98%) owned a mobile phone, and 67% of them had a computer with internet access at home. Majority of participants had experience in using Facebook messenger (95%), followed by Viber (60%) and Zoom (26%). Almost all of the participants (96%) were willing to use telehealth services. There were significant associations between female sex and participants living 10 km away from the hospital with their willingness to use telehealth services. There was a significant association between participants' self-perception of good health status with their willingness to use video-conference calls and phone calls to use telehealth services. Seven themes were developed from interview data which are related to predisposing, reinforcing, and enabling factors influencing telehealth services for diabetes care in Nepal. Conclusion: In summary, several factors were found to influence the use of telehealth services for diabetes care in Nepal. For effective implementation of a sustainable telehealth services for adults with diabetes in Nepal, these factors need to be considered.

Keywords: contributing factors, diabetes mellitus, developing countries, telemedicine, telecare

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