Search results for: mixed data sampling

Authors: Xizhen Zhou, Yanjie Ji

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The charging behavior of drivers provides a reference for the planning and management of charging facilities. Based on the real trajectory data of electric vehicles, this study explored the influence of the surrounding environments of the parking spot on charging decisions. The built environment, the condition of vehicles, and the nearest charging station were all considered. And the mixed binary logit model was used to capture the impact of unobserved heterogeneity. The results show that the number of fast chargers in the charging station, parking price, dwell time, and shopping services all significantly impact the charging decision, while the leisure services, scenic spots, and mileage since the last charging are opposite. Besides, factors related to unobserved heterogeneity include the number of fast chargers, parking and charging prices, residential areas, etc. The interaction effects of random parameters further illustrate the complexity of charging choice behavior. The results provide insights for planning and managing charging facilities.

Keywords: charging decision, trajectory, electric vehicle, infrastructure, mixed logit

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Authors: Charity Ngoatle, Tebogo M. Mothiba, Mahlapahlapana J. Themane

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Misapprehension of medications instructions due to poor health literacy is common in diabetic patients, predominantly leading to suboptimal medication therapy caused by taking less than expected, or getting inadequate medication concentration. Globally, 50% of adults have been reported to have misunderstood medication instructions which could be the cause of not using medication as prescribed. Reading material has been found not to improve people’s knowledge to the extent where they would be informed and knowledgeable about their health. This, therefore, depicts that instructive materials alone cannot improve health literacy but further patient education is still needed to explain what the information really mean. The aim of this study was to investigate patients’ interpretation of prescribed medication instructions at Makanye Clinic in Limpopo Province, South Africa. The study used a mixed method approach. A non-probability purposive and simple random sampling strategies will be used to select ten (10) participants for the pilot study. Semi-structured interviews with a guide and self- administered structured questionnaires will be used to collect data. Tesch’s eight steps for qualitative data analysis and SPSS version 24 with descriptive statistics will be adopted. The preliminary findings from other studies show that: (a) poor health literacy negatively affect medication adherence, (b) general literacy influence health literacy, and (c) there are poor health outcomes and medication adverse effects due to poor medication comprehension.

Keywords: instructions, diabetes mellitus, patients, prescribed medication

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Authors: Areej R. Banjar, Abraham G. Campbell

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The use of Mixed Reality (MR) in teaching and training is growing popular and can improve students’ ability to perform technical procedures. This short paper outlines the creation of an interactive educational MR 3D application that aims to improve the quality of instruction for dentistry students. This application is called MRImplantology and aims to teach the fundamentals and preoperative planning of dental implant placement. MRImplantology uses cone-beam computed tomography (CBCT) images as the source for 3D dental models that dentistry students will be able to freely manipulate within a 3D MR world to aid their learning process.

Keywords: augmented reality, education, dentistry, cone-beam computed tomography CBCT, head mounted display HMD, mixed reality

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Authors: Sakshi Gupta, Seema Joshi

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Thiosemicarbazones (TSCs) have garnered significant attention in coordination chemistry due to their versatile coordination modes and pharmacological properties. Mixed ligand complexes of TSCs represent a promising area of research, offering enhanced antimicrobial activities compared to their parent compounds. This review provides an overview of the synthesis, characterization, and antimicrobial properties of mixed ligand complexes incorporating thiosemicarbazones. The synthesis of mixed ligand complexes typically involves the reaction of a metal salt with TSC ligands and additional ligands, such as nitrogen- or oxygen-based ligands. Various transition metals, including copper, nickel, and cobalt, have been employed to form mixed ligand complexes with TSCs. Characterization techniques such as spectroscopy, X-ray crystallography, and elemental analysis are commonly utilized to confirm the structures of these complexes. One of the key advantages of mixed ligand complexes is their enhanced antimicrobial activity compared to pure TSC compounds. The synergistic effect between the TSC ligands and additional ligands contributes to increased efficacy, possibly through improved metal-ligand interactions or enhanced membrane permeability. Furthermore, mixed ligand complexes offer the potential for selective targeting of microbial species while minimizing toxicity to mammalian cells. This selectivity arises from the specific interactions between the metal center, TSC ligands, and biological targets within microbial cells. Such targeted antimicrobial activity is crucial for developing effective treatments with minimal side effects. Moreover, the versatility of mixed ligand complexes allows for the design of tailored antimicrobial agents with optimized properties. By varying the metal ion, TSC ligands, and additional ligands, researchers can fine-tune the physicochemical properties and biological activities of these complexes. This tunability opens avenues for the development of novel antimicrobial agents with improved efficacy and reduced resistance. In conclusion, mixed ligand complexes of thiosemicarbazones represent a promising class of compounds with potent antimicrobial activities. Further research in this field holds great potential for the development of novel therapeutic agents to combat microbial infections effectively.

Keywords: metal complex, thiosemicarbazones, mixed ligand, selective targeting, antimicrobial activity

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Authors: Yasuyuki Takahashi, Hirotaka Shimada, Takao Kanzaki

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A Dual-detector SPECT system is widely by use of myocardial SPECT studies. With 180-degree (180°) acquisition, reconstructed images are distorted in the posterior wall of myocardium due to the lack of sufficient data of posterior projection. We hypothesized that quality of myocardial SPECT images can be improved by the addition of data acquisition of only a few posterior projections to ordinary 180° acquisition. The proposed acquisition method (180° plus acquisition methods) uses the dual-detector SPECT system with a pair of detector arranged in 90° perpendicular. Sampling angle was 5°, and the acquisition range was 180° from 45° right anterior oblique to 45° left posterior oblique. After the acquisition of 180°, the detector moved to additional acquisition position of reverse side once for 2 projections, twice for 4 projections, or 3 times for 6 projections. Since these acquisition methods cannot be done in the present system, actual data acquisition was done by 360° with a sampling angle of 5°, and projection data corresponding to above acquisition position were extracted for reconstruction. We underwent the phantom studies and a clinical study. SPECT images were compared by profile curve analysis and also quantitatively by contrast ratio. The distortion was improved by 180° plus method. Profile curve analysis showed increased of cardiac cavity. Analysis with contrast ratio revealed that SPECT images of the phantoms and the clinical study were improved from 180° acquisition by the present methods. The difference in the contrast was not clearly recognized between 180° plus 2 projections, 180° plus 4 projections, and 180° plus 6 projections. 180° plus 2 projections method may be feasible for myocardial SPECT because distortion of the image and the contrast were improved.

Keywords: 180° plus acquisition method, a few posterior projections, dual-detector SPECT system, myocardial SPECT

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Authors: Routsukol Sunalai

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This research purpose is to study and compare the administration of Buddhist monks at northeastern Thailand. The samples used in the study are the priest in the Northeast by simple random sampling for 190 sampling. The tools used in this study is questioner were created in the 40 question items. The statistics used for data analysis were percentage, average, and standard deviation. The research found that the human resources management for the Buddhist monks as a whole is moderate. But it was found that the highest average is the policy followed by the management information. The Buddhist monks aged less than 25 years old with the overall difference was not significant. The priests who are less than 10 years in the monk experience and the priest has long held in the position for 10 years are not different in the significant level.

Keywords: employee job-related outcomes, ethical institutionalization, quality of work life, stock exchange of Thailand

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Authors: Bundit Pungnirund

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This research aimed to study the relationship between marketing mix attitudes, motivation of buying decision and tendency of consumer decision making in buying the condominiums in Thailand. This study employed by survey and quantitative research. The questionnaire was used to collect the data from 400 sampled of customers who interested in buying condominium in Bangkok. The descriptive statistics and Pearson’s correlation coefficient analysis were used to analyze data. The research found that marketing mixed factors in terms of product and price were related to buying decision making tendency in terms of price and room size. Marketing mixed factors in terms of price, place and promotion were related to buying decision making tendency in term of word of mouth. Consumers’ buying motivation in terms of social acceptance, self-esteemed and self-actualization were related to buying decision making tendency in term of room size. In addition, motivation in self-esteemed was related to buying decision making tendency within a year.

Keywords: condominium, marketing mix, motivation, tendency of consumer decision making

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Authors: Abiodun Ezekiel Adesina, Ijeoma Ginikanwa Akubugwo

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Information and Communication Technology, ICT can heighten pre-service teachers’ attitudes toward learning and metacognitive learning; however, there is a dearth of literature on the perception of the pre-service teachers on heightening their attitude toward learning and metacognitive learning. Thus, this study investigates the perception of pre-service science teachers on heightening their attitude towards learning and metacognitive learning through ICT. Two research questions and four hypotheses guided the research. A mixed methods research was adopted for the study in concurrent triangulation type of integrating qualitative and quantitative approaches to the study. The cluster random sampling technique was adopted to select 250 pre-service science teachers in Oyo township. Two self-constructed instruments: Heightening Pre-service Science Teachers’ Attitude towards Learning and Metacognitive Learning through Information and Communication Technology Scale (HPALMIS, r=.73), and an unstructured interview were used for data collection. Thematic analysis, frequency counts and percentages, t-tests, and analysis of variance were used for data analysis. The perception level of the pre-service science teachers on heightening their attitude towards learning and metacognitive learning through ICT is above average, with the majority perceiving that ICT can enhance their thinking about their learning. The perception was significant (mean=92.68, SD=10.86, df=249, t=134.91, p<.05). The perception was significantly differentiated by gender (t=2.10, df= 248, p<.05) in favour of the female pre-service teachers and based on the first time of ICTs use (F(5,244)= 9.586, p<.05). Lecturers of science and science related courses should therefore imbibe the use of ICTs in heightening pre-service teachers’ attitude towards learning and metacognitive learning. Government should organize workshops, seminars, lectures, and symposia along with professional bodies for the science education lecturers to keep abreast of the trending ICT.

Keywords: pre-service teachers’ attitude towards learning, metacognitive learning, ICT, pre-service teachers’ perspectives

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Authors: Alhadi Bustaman, Soeganda Formalidin, Titin Siswantining

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DNA microarray technology is used to analyze thousand gene expression data simultaneously and a very important task for drug development and test, function annotation, and cancer diagnosis. Various clustering methods have been used for analyzing gene expression data. However, when analyzing very large and heterogeneous collections of gene expression data, conventional clustering methods often cannot produce a satisfactory solution. Biclustering algorithm has been used as an alternative approach to identifying structures from gene expression data. In this paper, we introduce a transform technique based on singular value decomposition to identify normalized matrix of gene expression data followed by Mixed-Clustering algorithm and the Lift algorithm, inspired in the node-deletion and node-addition phases proposed by Cheng and Church based on Agglomerative Hierarchical Clustering (AHC). Experimental study on standard datasets demonstrated the effectiveness of the algorithm in gene expression data.

Keywords: agglomerative hierarchical clustering (AHC), biclustering, gene expression data, lymphoma, singular value decomposition (SVD)

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Authors: Tomas Menard

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The design of control-law for engineering systems has been investigated for many decades. While many results are concerned with continuous systems with continuous output, nowadays, many controlled systems have to transmit their output measurements through network, hence making it discrete-time. But it is well known that the sampling of a system whose control-law is based on the continuous output may render the system unstable, especially when this sampling period is long compared to the system dynamics. The control design then has to be adapted in order to cope with this issue. In this paper, we consider systems which can be modeled as double integrator with uncertainty on the input since many mechanical systems can be put under such form. We present a control scheme based on an observer using only discrete time measurement and which provides continuous time estimation of the state, combined with a continuous control law, which stabilized a system with second-order dynamics even in the presence of uncertainty. It is further shown that arbitrarily long sampling periods can be dealt with properly setting the control scheme parameters.

Keywords: dynamical system, control law design, sampled output, observer design

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Authors: Ebenezer Bayode Agboola

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The study investigated the influence of socioeconomic factors on crime perpetuation among inmates of correctional facilities in South West Nigeria. A sample size of two hundred and forty-four inmates was drawn from Ado, Akure and Ilesha correctional facilities. The sample size consisted of both male and female inmates. Individual inmate was drawn through systematic sampling with the use of inmates’ register at the correctional facilities. The study employed a mixed design, which allowed the blend of both quantitative and qualitative methods. For the quantitative method, data was collected through the use of a questionnaire and for the qualitative method; data was collected with the aid of an in-depth interview (ID. Four research questions were raised for the study and analysed descriptively using simple frequency count and percentage. Five research hypotheses were formulated for the study and tested using Analysis of Variance (ANOVA) and Multiple Regressions. Based on the data analysis, findings revealed that there was a significant relationship between family history and perpetuation of crime among inmates. Though no significant relationship was found between employment and the perpetuation of crime, however, the rate of crime perpetuation by individuals was significantly found to be related to peer pressure. Also, the study further found that there was a significant relationship between the use of substances and perpetuation of crime. Lastly, it was found that there was a significant relationship between family history, employment, and peer pressure. The study recommended that Parents should pay adequate attention to their children, especially during the adolescent stage and that the Government should enact relevant laws that will checkmate the rising involvement of young people in cybercrime or internet fraud.

Keywords: crime, socio economic factor, inmates, correctional facilities, Southwest

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Authors: Avirup Chowdhury, Angus K. McFadyen, Linsey Batchelor

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Blood cultures (BCs) are an important aspect of management of the septic patient, identifying the underlying pathogen and its antibiotic sensitivities. However, while the current literature outlines indications for initial BCs to be taken, there is little guidance for repeat sampling in the following 5-day period and little information on how antibiotic use can affect the usefulness of this investigation. A retrospective cohort study was conducted using inpatients who had undergone 2 or more BCs within 5 days between April 2016 and April 2017 at a 400-bed hospital in the west of Scotland and received antibiotic therapy between the first and second BCs. The data for BC sampling was collected from the electronic microbiology database, and cross-referenced with data from the hospital electronic prescribing system. Overall, 283 BCs were included in the study, taken from 92 patients (mean 3.08 cultures per patient, range 2-10). All 92 patients had initial BCs, of which 83 were positive (90%). 65 had a further sample within 24 hours of commencement of antibiotics, with 35 positive (54%). 23 had samples within 24-48 hours, with 4 (17%) positive; 12 patients had sampling at 48-72 hours, 12 at 72-96 hours, and 10 at 96-120 hours, with none positive. McNemar’s Exact Test was used to calculate statistical significance for patients who received blood cultures in multiple time blocks (Initial, < 24h, 24-120h, > 120h). For initial vs. < 24h-post BCs (53 patients tested), the proportion of positives fell from 46/53 to 29/53 (one-tailed P=0.002, OR 3.43, 95% CI 1.48-7.96). For initial vs 24-120h (n=42), the proportions were 38/42 and 4/42 respectively (P < 0.001, OR 35.0, 95% CI 4.79-255.48). For initial vs > 120h (n=36), these were 33/36 and 2/36 (P < 0.001,OR ∞). These were also calculated for a positive in initial or < 24h vs. 24-120h (n=42), with proportions of 41/42 and 4/42 (P < 0.001, OR 38.0, 95% CI 5.22-276.78); and for initial or < 24h vs > 120h (n=36), with proportions of 35/36 and 2/36 respectively (P < 0.001, OR ∞). This data appears to show that taking an initial BC followed by a BC within 24 hours of antibiotic commencement would maximise blood culture yield while minimising the risk of false negative results. This could potentially remove the need for as many as 46% of BC samples without adversely affecting patient care. BC yield decreases sharply after 48 hours of antibiotic use, and may not provide any clinically useful information after this time. Further multi-centre studies would validate these findings, and provide a foundation for future health policy generation.

Keywords: antibiotics, blood culture, efficacy, inpatient

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Authors: Mohammad Obeidat, Ayman Mansour

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In this paper a unique issue rising from feedback control of Atrial Fibrillation monitoring system with embedded communication channels has been investigated. One of the important factors to measure the performance of the feedback control closed loop system is disturbance and noise attenuation factor. It is important that the feedback system can attenuate such disturbances on the atrial fibrillation heart rate signals. Communication channels depend on network traffic conditions and deliver different throughput, implying that the sampling intervals may change. Since signal estimation is updated on the arrival of new data, its dynamics actually change with the sampling interval. Consequently, interaction among sampling, signal estimation, and the controller will introduce new issues in remotely controlled Atrial Fibrillation system. This paper treats a remotely controlled atrial fibrillation system with one communication channel which connects between the heart rate and rhythm measurements to the remote controller. Typical and optimal signal estimation schemes is represented by a signal averaging filter with its time constant derived from the step size of the signal estimation algorithm.

Keywords: atrial fibrillation, communication channels, closed loop, estimation

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Authors: Hector Valverde Martínez

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In this text, the application possibilities of developments in MR are explored as an element within the museographic space that affects the visitor-museum relationship to satisfy the needs of knowledge and recreation that visitors have to improve the experience. The emphasis points out the way in which it is thinking from the digital to understand the possibilities in the design of museum experiences, and are analyzed the strategies used inside and outside the museum space are exemplified from the use of MR and their impact on the visitors' experience to reach different levels of depth of knowledge in an exhibition; the exploration of limits in the creation of atmospheres that allow visitors to feel immersed in a completely different reality from the one they live to better understand the topics addressed in the exhibition, and strategies that are used to encourage museum audiences to actively participate and extend the experience of the museum beyond its walls.

Keywords: mixed realities, experience, visitor, museums

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Authors: Ahmed Alkarimi, Kevin Welham

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Organic mixed mode monolithic columns were fabricated from; glycidyl methacrylate-co-ethylene dimethacrylate-co-stearyl methacrylate, using glycidyl methacrylate and stearyl methacrylate as co monomers representing 30% and 70% respectively of the liquid volume with ethylene dimethacrylate crosslinker and 2,2-dimethoxy-2-phenylacetophenone as the free radical initiator. The monomers were mixed with a binary porogenic solvent, comprising propan-1-ol, and methanol (0.825 mL each). The monolith was formed by photo polymerization (365 nm) inside a borosilicate glass tube (1.5 mm ID and 3 mm OD x 50 mm length). The monolith was observed to have formed correctly by optical examination and generated reasonable backpressure, approximately 650 psi at a flow rate of 0.2 mL min⁻¹ 50:50 acetonitrile: water. The morphological properties of the monolithic columns were investigated using scanning electron microscopy images, and Brunauer-Emmett-Teller analysis, the results showed that the monolith was formed properly with 19.98 ± 0.01 mm² surface area, 0.0205 ± 0.01 cm³ g⁻¹ pore volume and 6.93 ± 0.01 nm average pore size. The polymer monolith formed was further investigated using proton nuclear magnetic resonance, and Fourier transform infrared spectroscopy. The monolithic columns were investigated using high-performance liquid chromatography to test their ability to separate different samples with a range of properties. The columns displayed both hydrophobic/hydrophilic and hydrophobic/ion exchange interactions with the compounds tested indicating that true mixed mode separations. The mixed mode monolithic columns exhibited significant separation of proteins.

Keywords: LC separation, proteins separation, monolithic column, mixed mode

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Authors: M. Babul Hasan

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Management sciences (MS), big group of companies and industries or government policies (GP) is affiliated with a huge number of decision ingredients and complicated restrictions. Every factor in MS, every product in Industries or decision in GP is not always bankable in practice. After formulating these models there arises large-scale mixed integer programming (MIP) problem. In this paper, we developed decomposition-based pricing procedure to filter the unnecessary decision ingredients from MIP where the variables in huge number will be abated and the complicacy of restrictions will be elementary. A real life numerical example has been illustrated to demonstrate the methods. We develop the computer techniques for these methods by using a mathematical programming language (AMPL).

Keywords: Lagrangian relaxation, decomposition, sub-problem, master-problem, pricing, mixed IP, AMPL

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Authors: M. Gulam Kibria, Shourav Ahmed, Kais Zaman

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In system analysis, the information on the uncertain input variables cause uncertainty in the system responses. Different probabilistic approaches for uncertainty representation and propagation in such cases exist in the literature. Different uncertainty representation approaches result in different outputs. Some of the approaches might result in a better estimation of system response than the other approaches. The NASA Langley Multidisciplinary Uncertainty Quantification Challenge (MUQC) has posed challenges about uncertainty quantification. Subproblem A, the uncertainty characterization subproblem, of the challenge posed is addressed in this study. In this subproblem, the challenge is to gather knowledge about unknown model inputs which have inherent aleatory and epistemic uncertainties in them with responses (output) of the given computational model. We use two different methodologies to approach the problem. In the first methodology we use sampling-based uncertainty propagation with first order error analysis. In the other approach we place emphasis on the use of Percentile-Based Optimization (PBO). The NASA Langley MUQC’s subproblem A is developed in such a way that both aleatory and epistemic uncertainties need to be managed. The challenge problem classifies each uncertain parameter as belonging to one the following three types: (i) An aleatory uncertainty modeled as a random variable. It has a fixed functional form and known coefficients. This uncertainty cannot be reduced. (ii) An epistemic uncertainty modeled as a fixed but poorly known physical quantity that lies within a given interval. This uncertainty is reducible. (iii) A parameter might be aleatory but sufficient data might not be available to adequately model it as a single random variable. For example, the parameters of a normal variable, e.g., the mean and standard deviation, might not be precisely known but could be assumed to lie within some intervals. It results in a distributional p-box having the physical parameter with an aleatory uncertainty, but the parameters prescribing its mathematical model are subjected to epistemic uncertainties. Each of the parameters of the random variable is an unknown element of a known interval. This uncertainty is reducible. From the study, it is observed that due to practical limitations or computational expense, the sampling is not exhaustive in sampling-based methodology. That is why the sampling-based methodology has high probability of underestimating the output bounds. Therefore, an optimization-based strategy to convert uncertainty described by interval data into a probabilistic framework is necessary. This is achieved in this study by using PBO.

Keywords: aleatory uncertainty, epistemic uncertainty, first order error analysis, uncertainty quantification, percentile-based optimization

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Authors: Mohd Said Nurumal, Sarah Sheikh Abdul Karim

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Information regarding out of hospital cardiac arrest incidence include outcome in Malaysia is limited and fragmented. This study aims to identify incidence and adherence to protocol of out of hospital cardiac arrest and also to explore the issues faced by the pre-hospital personnel in regards managing cardiac arrest victim in Kuala Lumpur, Malaysia. A mixed method approach combining the qualitative and quantitative study design was used. The 285 pre-hospital care data sheet of out of hospital cardiac arrest during the year of 2011 were examined by using checklists for identify the incidence and adherence to protocol. Nine semi-structured interviews and two focus group discussions were performed. For the incidence based on the overall out of hospital cardiac arrest cases that occurred in 2011 (n=285), the survival rates were 16.8%. For adherence to protocol, only 89 (41.8%) of the cases adhered to the given protocol and 124 did not adhere to such protocol. The qualitative information provided insight about the issues related to out of hospital cardiac arrest in every aspect. All the relevant qualitative data were merged into few categories relating issues that could affect the management of out of hospital cardiac arrest performed by pre-hospital care team. One of the essential elements in the out of hospital cardiac arrest handling by pre-hospital care is to ensure increase of survival rates and excellent outcomes by adhering to given protocols based on international standard benchmarks. Measures are needed to strengthen the quick activation of the pre-hospital care service, prompt bystander cardiopulmonary resuscitation, early defibrillation and timely advanced cardiac life support and also to tackle all the issues highlighted in qualitative results.

Keywords: pre-hospital care, out of hospital cardiac arrest, incidence, protocol, mixed method research

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Salam Khalifa, Naveed Ahmed

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We present a new method to reconstruct a temporally coherent 3D animation from single or multi-view RGB-D video data using unbiased feature point sampling. Given RGB-D video data, in form of a 3D point cloud sequence, our method first extracts feature points using both color and depth information. In the subsequent steps, these feature points are used to match two 3D point clouds in consecutive frames independent of their resolution. Our new motion vectors based dynamic alignment method then fully reconstruct a spatio-temporally coherent 3D animation. We perform extensive quantitative validation using novel error functions to analyze the results. We show that despite the limiting factors of temporal and spatial noise associated to RGB-D data, it is possible to extract temporal coherence to faithfully reconstruct a temporally coherent 3D animation from RGB-D video data.

Keywords: 3D video, 3D animation, RGB-D video, temporally coherent 3D animation

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Authors: Stephens Oluyemi Adetunji, Nel Norma Margaret, Krogs Sozein

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There has been a shift in the role of sports from being a form of entertainment and relaxation to becoming a huge business concern and high money spinning venture. This shift has placed a greater demand on sport coaches as regards expectations for high performance from investors as well as other stake holders. The responsibility of sports coaches in ensuring high performance of sports men and women has become increasingly more demanding from both spectators and sports organisers. Coaches are leaders who should possess soft skills such as emotional intelligence aside from employing skills and drills to ensure high performance of athletes. This study is, therefore, designed to determine the emotional intelligence of sports coaches in South Africa. An assessment of the emotional intelligence of sports coaches would enable the researchers to identify those who have low emotional intelligence and to design an intervention program that could improve their emotional intelligence. This study will adopt the pragmatic world view of research using the mixed methods research design of the quantitative and qualitative approach. The non-probability sampling technique will be used to select fifty sports coaches for the quantitative study while fifteen sports coaches will be purposively selected for the qualitative study. One research question which seeks to ascertain the level of emotional intelligence of sports coaches will be raised to guide this study. In addition, two research hypotheses stating that there will be no significant difference in the level of emotional intelligence of sports coaches on the basis of gender and type of sports will be formulated and statistically analysed at 0.05 level of significance. For the quantitative study, an emotional intelligence test will be used to measure the emotional intelligence of sport coaches. Focus group interviews and open ended questions will be used to obtain the qualitative data. Quantitative data obtained will be statistically analysed using the SPSS version 22.0 while the qualitative data will be analysed using atlas ti. Based on the findings of this study, recommendations will be made.

Keywords: emotional intelligence, high performance, sports coaches, South Africa

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Mohamed Moustafa Mahmoud Sedky

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In line start permanent magnet synchronous motor, eccentricity is a common fault that can make it necessary to remove the motor from the production line. However, because the motor may be inaccessible, diagnosing the fault is not easy. This paper presents an FEM that identifies different models, static eccentricity, dynamic eccentricity, and mixed eccentricity, at no load and full load. The method overcomes the difficulty of applying FEMs to transient behavior. It simulates motor speed, torque and flux density distribution along the air gap for SE, DE, and ME. This paper represents the various effects of different eccentricities types on the transient performance.

Keywords: line start permanent magnet, synchronous machine, static eccentricity, dynamic eccentricity, mixed eccentricity

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Authors: Srinivasa Rao Gadde

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In this article, we considered a group acceptance sampling plans for exponentiated half logistic distribution when the life-test is truncated at a pre-specified time. It is assumed that the index parameter of the exponentiated half logistic distribution is known. The design parameters such as the number of groups and the acceptance number are obtained by satisfying the producer’s and consumer’s risks at the specified quality levels in terms of medians and 10th percentiles under the assumption that the termination time and the number of items in each group are pre-fixed. Finally, an example is given to illustration the methodology.

Keywords: group acceptance sampling plan, operating characteristic, consumer and producer’s risks, truncated life-test

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Authors: Hurgesa Hundera, Samuel Shibeshibikeko, Tarike Daba, Tesfaye Ganamo

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The study aimed at examining the ongoing adaptation strategies used by smallholder farmers in response to climate variability in Boset district. It also assessed the socioeconomic factors that influence the choice of adaptation strategies of smallholder farmers to climate variability risk. For attaining the objectives of the study, both primary and secondary sources of data were employed. The primary data were obtained through a household questionnaire, key informant interviews, focus group discussions, and observations, while secondary data were acquired through desk review. Questionnaires were distributed and filled by 328 respondents, and they were identified through systematic random sampling technique. Descriptive statistics and binary logistic regression model were applied in this study as the main analytical methods. The findings of the study reveal that the sample households have utilized multiple adaptation strategies in response to climate variability, such as cropping early mature crops, planting drought resistant crops, growing mixed crops on the same farm lands, and others. The results of the binary logistic model revealed that education, sex, age, family size, off farm income, farm experience, access to climate information, access to farm input, and farm size were significant and key factors determining farmers’ choice of adaptation strategies to climate variability in the study area. To enable effective adaptation measures, Ministry of Agriculture and Natural Resource, with its regional bureaus and offices and concerned non–governmental organizations, should consider climate variability in their planning and budgeting in all levels of decision making.

Keywords: adaptation strategies, boset district, climate variability, smallholder farmers

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Authors: Tadesse Abera

Abstract:

This study aimed to investigate the contribution of self-advocacy and engagement in the inclusion of SWDs in HEIs. A convergent parallel mixed methods design was employed. This article reports the quantitative strand. A total of 246 SWDs were selected through stratified proportionate random sampling technique from five public HEIs in Ethiopia. Data were collected through Self-advocacy questionnaire, student engagement scale, and college student experience questionnaire and analyzed through frequency, percentage, mean, standard deviation, correlation, one sample t-test and multiple regression. Both self-advocacy and engagement were found to have a predictive power on inclusion of respondents in the HEIs, where engagement was found to be more predictor. From the components of self-advocacy, knowledge of self and leadership and from engagement dimensions sense of belonging, cognitive, and valuing in their respective orders were found to have a stronger predictive power on the inclusion of respondents in the institutions. Based on the findings it was concluded that, if students with disabilities work hard to be self-determined, strive for realizing social justice, exert quality effort and seek active involvement, their inclusion in the institutions would be ensured.

Keywords: self-advocacy, engagement, inclusion, students with disabilities, higher education institution

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Authors: Mohammad Farid

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In this paper, we introduce and study an explicit iterative method based on hybrid extragradient method to approximate a common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup in Hilbert space. Further, we prove that the sequence generated by the proposed iterative scheme converge strongly to the common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup. This common solution is the unique solution of a variational inequality problem and is the optimality condition for a minimization problem. The results presented in this paper are the supplement, extension and generalization of the previously known results in this area.

Keywords: generalized mixed equilibrium problem, fixed-point problem, nonexpansive semigroup, variational inequality problem, iterative algorithms, hybrid extragradient method

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Authors: Komol Phaisarn, Natcha Wattanaprapa

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This research is a survey research with an objective to study the safety of data storage devices of graduate students of academic year 2013, Suan Sunandha Rajabhat University. Data were collected by questionnaire on the safety of data storage devices according to CIA principle. A sample size of 81 was drawn from population by purposive sampling method. The results show that most of the graduate students of academic year 2013 at Suan Sunandha Rajabhat University use handy drive to store their data and the safety level of the devices is at good level.

Keywords: security, safety, storage devices, graduate students

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Authors: Bayu Dwi Cahyo, Ekohariadi, Theodorus Wiyanto Wibowo, I. G. P. Asto Budithahjanto, Eppy Yundra

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The objective of this study is to examine the effects of self-confidence, adversity quotient, and self-efficacy variables on critical thinking. This research's participants are 137 cadets of Aviation Polytechnics of Surabaya with the sampling technique that was purposive sampling. In this study, the data collection method used a questionnaire with Linkert-scale and distributed or given to respondents by the specified number of samples. The SPSS AMOS v23 was used to test a number of a priori multivariate growth curve models and examining relationships between the variables via path analysis. The result of path analysis was (χ² = 88.463, df= 71, χ² /df= 1.246, GFI= .914, CFI= .988, P= .079, AGFI= .873, TLI= .985, RMSEA= .043). According to the analysis, there is a positive and significant relationship between self-confidence, adversity quotient, and self-efficacy variables on critical thinking.

Keywords: self-confidence, adversity quotient, self-efficacy variables, critical thinking

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Authors: Esmaeil Sarikhani

Abstract:

Objectives: Considering the importance of introducing new methods of improving self-compassion and compassion to the others in nursing students, this study intends to evaluate the effect of self-compassion training on nursing students. Methods: This is a field trial study in which 52 nursing interns from Isfahan University of Medical Sciences were selected using convenience sampling method and divided in two experimental and control groups. The sampling was done during two phases: before and after the intervention. The intervention consisted of eight sessions over eight weeks of self-compassion training. The data were collected using the self-compassion standard questionnaire with 26 questions before and after the intervention. Data were then analyzed by the SPSS18 software and independent and paired T-tests, and also Chi-square and Mann-Whitney tests. Results: The results obtained from the independent t-test showed that the mean score of self-compassion and its components in the experimental group was significantly increased compared to the control group (p < 0.001). Comparing the groups, the mean overall score difference of self-compassion and its components had also a statistically significant change after the intervention (p < 0.001). Conclusion: Self-compassion training program, leads to improving nursing students' self-compassion. As it seems, this method can be used as an important training course in order to improve compassion of nursing students to themselves and the others.

Keywords: self-compassion, student, nursing students, field trial

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