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Authors: Ling-Han Liu, Qian-Qian Yu, Xiang-Lin Gu

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In this paper, the fragility analysis of earthquake-strong wind concurrent hazards considering structural uncertainties was conducted. Eleven sets of structural uncertainty parameters were considered, and random structural models were generated using Latin hypercube sampling. The uncertainties in seismic ground motion and wind load inputs were incorporated, and the conditional failure probability of the structures was calculated. A 12-story concrete building was used as an example, with the IDR (Inter-story Drift Ratio) as the performance indicator. The failure probabilities under individual and multiple hazards were compared, along with a comparison of fragility analysis results with and without considering structural uncertainties. The numerical simulations show that including structural uncertainties increases the structural failure probability by 20%. The peak stress and strain of core-restrained concrete, the structural damping ratio, and the peak stress of unrestrained concrete are found to be decisive factors in the structural response.

Keywords: structural uncertainty, incremental dynamic analysis, multi-hazard fragility, latin hypercube sampling

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Authors: Jing Jiang, Wenhuan XU, Lei Zhang, Shiyi Zhang, Tongli Wang

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Climate data quality significantly affects the reliability of ecological modeling. In the Asia Pacific (AP) region, low-quality climate data hinders ecological modeling. ClimateAP, a software developed in 2017, generates high-quality climate data for the AP region, benefiting researchers in forestry and agriculture. However, its adoption remains limited. This study aims to confirm the validity of biologically relevant variable data generated by ClimateAP during the normal climate period through comparison with the currently available gridded data. Climate data from 2,366 weather stations were used to evaluate the prediction accuracy of ClimateAP in comparison with the commonly used gridded data from WorldClim1.4. Univariate regressions were applied to 48 monthly biologically relevant variables, and the relationship between the observational data and the predictions made by ClimateAP and WorldClim was evaluated using Adjusted R-Squared and Root Mean Squared Error (RMSE). Locations were categorized into mountainous and flat landforms, considering elevation, slope, ruggedness, and Topographic Position Index. Univariate regressions were then applied to all biologically relevant variables for each landform category. Random Forest (RF) models were implemented for the climatic niche modeling of Cunninghamia lanceolata. A comparative analysis of the prediction accuracies of RF models constructed with distinct climate data sources was conducted to evaluate their relative effectiveness. Biologically relevant variables were obtained from three unpublished Chinese meteorological datasets. ClimateAPv3.0 and WorldClim predictions were obtained from weather station coordinates and WorldClim1.4 rasters, respectively, for the normal climate period of 1961-1990. Occurrence data for Cunninghamia lanceolata came from integrated biodiversity databases with 3,745 unique points. ClimateAP explains a minimum of 94.74%, 97.77%, 96.89%, and 94.40% of monthly maximum, minimum, average temperature, and precipitation variances, respectively. It outperforms WorldClim in 37 biologically relevant variables with lower RMSE values. ClimateAP achieves higher R-squared values for the 12 monthly minimum temperature variables and consistently higher Adjusted R-squared values across all landforms for precipitation. ClimateAP's temperature data yields lower Adjusted R-squared values than gridded data in high-elevation, rugged, and mountainous areas but achieves higher values in mid-slope drainages, plains, open slopes, and upper slopes. Using ClimateAP improves the prediction accuracy of tree occurrence from 77.90% to 82.77%. The biologically relevant climate data produced by ClimateAP is validated based on evaluations using observations from weather stations. The use of ClimateAP leads to an improvement in data quality, especially in non-mountainous regions. The results also suggest that using biologically relevant variables generated by ClimateAP can slightly enhance climatic niche modeling for tree species, offering a better understanding of tree species adaptation and resilience compared to using gridded data.

Keywords: climate data validation, data quality, Asia pacific climate, climatic niche modeling, random forest models, tree species

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Authors: Sittichai Charoensettasilp, Chong Wu

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This study employs sampling of 400 Thai people who live in Bangkok and have used air transportation to travel. A random convenience sampling technique is used to collect data. The results found that at 0.05 significance level the differences of means of Thai consumers’ expectations (before) and satisfaction (after) receiving services in the service marketing mix, the results of all aspects are different both in general and for each aspect of the service marketing mix. Average levels of expectations before receiving services are higher than satisfaction after receiving services in all aspects, as well. When analyzing further to the correlation between average means, the means of expectations before receiving services are higher than those of satisfaction after receiving services in general. As in all aspects of the service marketing mix, any aspect that has a big difference between expectations before receiving services and satisfaction after receiving services has low correlation.

Keywords: domestic low-cost airlines, Thai consumers, relationship, expectation before receiving services, satisfaction after receiving services

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Authors: Medjadj Tarek, Ghribi Hayet

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This study aims to develop a flood sensitivity assessment tool using machine learning (ML) techniques and geographic information system (GIS). The importance of this study is integrating the geographic information systems (GIS) and machine learning (ML) techniques for mapping flood risks, which help decision-makers to identify the most vulnerable areas and take the necessary precautions to face this type of natural disaster. To reach this goal, we will study the case of the city of M'sila, which is among the areas most vulnerable to floods. This study drew a map of flood-prone areas based on the methodology where we have made a comparison between 3 machine learning algorithms: the xGboost model, the Random Forest algorithm and the K Nearest Neighbour algorithm. Each of them gave an accuracy respectively of 97.92 - 95 - 93.75. In the process of mapping flood-prone areas, the first model was relied upon, which gave the greatest accuracy (xGboost).

Keywords: Geographic information systems (GIS), machine learning (ML), emergency mapping, flood disaster management

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Authors: Bry X., Trottier C., Mortier F., Cornu G., Verron T.

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We address component-based regularization of a Multivariate Generalized Linear Model (MGLM). A set of random responses Y is assumed to depend, through a GLM, on a set X of explanatory variables, as well as on a set T of additional covariates. X is partitioned into R conceptually homogeneous blocks X1, ... , XR , viewed as explanatory themes. Variables in each Xr are assumed many and redundant. Thus, Generalised Linear Regression (GLR) demands regularization with respect to each Xr. By contrast, variables in T are assumed selected so as to demand no regularization. Regularization is performed searching each Xr for an appropriate number of orthogonal components that both contribute to model Y and capture relevant structural information in Xr. We propose a very general criterion to measure structural relevance (SR) of a component in a block, and show how to take SR into account within a Fisher-scoring-type algorithm in order to estimate the model. We show how to deal with mixed-type explanatory variables. The method, named THEME-SCGLR, is tested on simulated data.

Keywords: Component-Model, Fisher Scoring Algorithm, GLM, PLS Regression, SCGLR, SEER, THEME

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Authors: Mahsa Mousavi, Hamid Reza Pourshaghaghi, Mohammad Tahghighi, Henk Corporaal

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Recently, Statistic Random-Access Memory-based (SRAM-based) Field-Programmable Gate Arrays (FPGAs) are widely used in aeronautics and space systems where high dependability is demanded and considered as a mandatory requirement. Since design’s circuit is stored in configuration memory in SRAM-based FPGAs; they are very sensitive to Single Event Upsets (SEUs). In addition, the adverse effects of SEUs on the electronics used in space are much higher than in the Earth. Thus, developing fault tolerant techniques play crucial roles for the use of SRAM-based FPGAs in space. However, fault tolerance techniques introduce additional penalties in system parameters, e.g., area, power, performance and design time. In this paper, an accurate estimation of configuration memory vulnerability to SEUs is proposed for approximate-tolerant applications. This vulnerability estimation is highly required for compromising between the overhead introduced by fault tolerance techniques and system robustness. In this paper, we study applications in which the exact final output value is not necessarily always a concern meaning that some of the SEU-induced changes in output values are negligible. We therefore define and propose Approximate-based Configuration Memory Vulnerability Factor (ACMVF) estimation to avoid overestimating configuration memory vulnerability to SEUs. In this paper, we assess the vulnerability of configuration memory by injecting SEUs in configuration memory bits and comparing the output values of a given circuit in presence of SEUs with expected correct output. In spite of conventional vulnerability factor calculation methods, which accounts any deviations from the expected value as failures, in our proposed method a threshold margin is considered depending on user-case applications. Given the proposed threshold margin in our model, a failure occurs only when the difference between the erroneous output value and the expected output value is more than this margin. The ACMVF is subsequently calculated by acquiring the ratio of failures with respect to the total number of SEU injections. In our paper, a test-bench for emulating SEUs and calculating ACMVF is implemented on Zynq-7000 FPGA platform. This system makes use of the Single Event Mitigation (SEM) IP core to inject SEUs into configuration memory bits of the target design implemented in Zynq-7000 FPGA. Experimental results for 32-bit adder show that, when 1% to 10% deviation from correct output is considered, the counted failures number is reduced 41% to 59% compared with the failures number counted by conventional vulnerability factor calculation. It means that estimation accuracy of the configuration memory vulnerability to SEUs is improved up to 58% in the case that 10% deviation is acceptable in output results. Note that less than 10% deviation in addition result is reasonably tolerable for many applications in approximate computing domain such as Convolutional Neural Network (CNN).

Keywords: fault tolerance, FPGA, single event upset, approximate computing

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Authors: Αlexios Kotsakis, Stefanos Katsavounis, Dimitra Alexiou

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Networks can be utilized to represent project planning problems, using nodes for activities and arcs to indicate precedence relationship between them. For fixed activity duration, a simple algorithm calculates the amount of time required to complete a project, followed by the activities that comprise the critical path. Program Evaluation and Review Technique (PERT) generalizes the above model by incorporating uncertainty, allowing activity durations to be random variables, producing nevertheless a relatively crude solution in planning problems. In this paper, based on the findings of the relevant literature, which strongly suggests that a Beta distribution can be employed to model earthmoving activities, we utilize Monte Carlo simulation, to estimate the project completion time distribution and measure the influence of skewness, an element inherent in activities of modern technical projects. We also extract the activity criticality index, with an ultimate goal to produce more accurate planning estimations.

Keywords: beta distribution, PERT, Monte Carlo simulation, skewness, project completion time distribution

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Authors: Hadi Manjiri, Mahdyeh Bakhshi, Ali Jafari, Maryam Salati

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This study investigates the influence of e-learning on teacher-student instructional interactions through the mediating role of computer literacy among elementary school teachers in Tehran. The research method is a survey that was conducted among elementary school students in Tehran. A sample size of 338 was determined based on Morgan's table. A stratified random sampling method was used to select 228 women and 110 men for the study. Bagherpour et al.'s computer literacy questionnaire, Elahi et al.'s e-learning questionnaire, and Lourdusamy and Khine's questionnaire on teacher-student instructional interactions were used to measure the variables. The data were analyzed using SPSS and LISREL software. It was found that e-learning affects teacher-student instructional interactions, mediated by teachers' computer literacy. In addition, the results suggest that e-learning predicts a 0.66 change in teacher-student instructional interactions, while computer literacy predicts a 0.56 change in instructional interactions between teachers and students.

Keywords: e-learning, instructional interactions, computer literacy, students

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Authors: Ahmad Badawi Saluy, Novawiguna Kemalasari

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This study aims to examine and analyze the influence of organizational culture, organizational commitment, and transformational leadership style on employee performance. This study used descriptive survey method with quantitative approach, and questionnaires as a tool used for basic data collection. The sampling technique used is proportionate stratified random sampling technique; all respondents in this study were 70 respondents. The analytical method used in this research is multiple linear regressions. The result of determination coefficient of 52.3% indicates that organizational culture, organizational commitment, and transformational leadership style simultaneously have a significant influence on the performance of employees, while the remaining 47.7% is explained by other factors outside the research variables. Partially, organization culture has strong and positive influence on employee performance, organizational commitment has a moderate and positive effect on employee performance, while the transformational leadership style has a strong and positive influence on employee performance and this is also the variable that has the most impact on employee performance.

Keywords: organizational culture, organizational commitment, transformational leadership style, employee performance

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Authors: Kholoud Adeeb. Al-Dababneh

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This study aimed at investigating teachers' perceptions of using assistive technologies in teaching children with disabilities in Jordan. The researcher developed a study instrument (questionnaire) to examine teachers' perceptions regarding the use of assistive technologies in teaching children with disabilities. The validity and reliability of the research instrument were checked. A random sample of 260 teachers who teach children with disabilities participated in the study by completing the questionnaire; fifteen teachers were later interviewed. Results revealed that the use of assistive technology by teachers in teaching children with disabilities was high. The results also revealed that there are statistically significant differences at (α= .05) according to the type of disability in favor of teachers of children with specific learning disabilities (SLD), according to educational settings in favor of local public schools (inclusion settings). The results revealed that there were no statistically significant differences attributed to the teacher's level of education and teachers' gender. In light of the study results, the researcher addressed several recommendations and future implications.

Keywords: assistive technologies, children with disabilities, Jordan, teachers

Procedia PDF Downloads 116

Authors: M. Sadeghi, H. Pezeshk, R. Tusserkani, A. Sharifi Zarchi, A. Malekpour, M. Foroughmand, S. Goliaei, M. Totonchi, N. Ansari–Pour

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The role and relative importance of intrinsic and extrinsic factors in the development of complex diseases such as cancer still remains a controversial issue. Determining the amount of variation explained by these factors needs experimental data and statistical models. These models are nevertheless based on the occurrence and accumulation of random mutational events during stem cell division, thus rendering cancer development a stochastic outcome. We demonstrate that not only individual genome sequencing is uninformative in determining cancer risk, but also assigning a unique genome sequence to any given individual (healthy or affected) is not meaningful. Current whole-genome sequencing approaches are therefore unlikely to realize the promise of personalized medicine. In conclusion, since genome sequence differs from cell to cell and changes over time, it seems that determining the risk factor of complex diseases based on genome sequence is somewhat unrealistic, and therefore, the resulting data are likely to be inherently uninformative.

Keywords: cancer risk, extrinsic factors, genome sequencing, intrinsic factors

Procedia PDF Downloads 271

Authors: Moammar Dayoub

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The study aimed to know the reality of farmers and determine the extent of adoption of the recommendations of the fertilizer and the difficulties and problems they face. The study was conducted on a random sample of farmers consist of 95 farmers who had analysed their field soil in scientific research centres in agricultural southern region through the form specially prepared for this purpose, the results showed that the rate of adoption of the fertilizer recommendations whole amounted to an average of 36.9% in the southern region, The degree of adoption was 34.7% in the region. The results showed that 41% of farmers did not implement the recommendations because of the non-convenient analysis, and 34% due to neglect, and 15% due to the weather and an environment, while 10% of them for lack of manure in the suitable time. The study also revealed that Independent factors affecting the continuing adoption of soil analysis are: farms experience, sampling method in farmer’s schools, irrigated area, and personal knowledge of farmers in analysing the soil. Also, show that the application of fertilizer recommendations led to increased production by 15-20%, this analysis emphasizes the importance of soil analysis and adherence to the recommendations of the research centres.

Keywords: adoption, recommendations of the fertilizer, soil analysis, southern region

Procedia PDF Downloads 169

Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

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Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

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Authors: Mehravar Javid, Laura Reid Harris, Zahra Khodadadi, Rachel Walton

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The study aimed to explore commitment precedence through self-expansion among students at the Medical Science University of Shiraz, Iran. Method: The statistical population was comprised of students at Shiraz University of Medical Science during the academic years 2013 to 2014. Using random sampling, 133 married students (50 males and 83 females) were selected. The commitment condition of this studied group was assessed using Adam and Jones' (1999) Marital Commitment Dimensions Scale (DCI), and self-expansion was measured using Aron and Lewandowski's (2002) Self-Expansion Questionnaire. Simple regression analyses investigated commitment precedence via self-expansion. Results: The data revealed a positive correlation between total commitment (r=0.35, p < 0.01), the subscales of commitment to the spouse (r=0.43, p < 0.01), and commitment to marriage (r=0.31, p < 0.01). Regression analyses indicated that perceived self-expansion positively correlated with commitment to marital relationships in married students. The findings suggest that an increased possibility of self-expansion in a marital relationship corresponds with heightened commitment.

Keywords: commitment to marital relationship, married students, relationship dynamics, self-expansion

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Authors: Frank Frimpong Opuni, Michael Mba Allan, Kwame Adu-Gyamfi, Michael Sarkodie Baffoe

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This paper assesses the effect of relationship marketing on service quality and customer satisfaction from the perspective of the moderating role of emotional intelligence in the insurance industry in Ghana. A descriptive quantitative research technique was employed. A random sample of 384 each of customers and service providers in 3 insurance firms in Accra were used as the source of data. According to findings, emotional intelligence makes a strong positive effect on relationship marketing at 5% significance level, r (283) = .817, p = .000. Though relationship marketing makes a strong positive effect on service quality (r = .767, p < .05) and customer satisfaction (r = .647, p < .05), this effect becomes insignificant (p > .05) when the effect of emotional intelligence on relationship marketing is controlled for. It is therefore recommended that insurance firms give priority to equipping their relationship employees with emotional intelligence to maximise service quality and customer satisfaction.

Keywords: relationship marketing, service quality, customer satisfaction, emotional intelligence

Procedia PDF Downloads 482

Authors: Ciaran Friel, Jerry Suls, Mark Butler, Patrick Robles, Samantha Gordon, Frank Vicari, Karina W. Davidson

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Physical activity guidelines focus on increasing moderate-intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence supports that any increase in physical activity is positively correlated with health benefits. Behavior change techniques (BCTs) have demonstrated effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a Personalized Trials (N-of-1) design to evaluate the efficacy of using four BCTs to promote an increase in low-intensity physical activity (2,000 steps of walking per day) in adults aged 45-75 years old. The 4 BCTs tested were goal setting, action planning, feedback, and self-monitoring. BCTs were tested in random order and delivered by text message prompts requiring participant engagement. The study recruited health system employees in the target age range, without mobility restrictions and demonstrating interest in increasing their daily activity by a minimum of 2,000 steps per day for a minimum of five days per week. Participants were sent a Fitbit® fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7 but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by Fitbit for two weeks. In the 8-week intervention phase of the study, participants received each of the four BCTs, in random order, for a two-week period. Text message prompts were delivered daily each morning at a consistent time. All prompts required participant engagement to acknowledge receipt of the BCT message. Engagement is dependent upon the BCT message and may have included recording that a detailed plan for walking has been made or confirmed a daily step goal (action planning, goal setting). Additionally, participants may have been directed to a study dashboard to view their step counts or compare themselves to their baseline average step count (self-monitoring, feedback). At the end of each two-week testing interval, participants were asked to complete the Self-Efficacy for Walking Scale (SEW_Dur), a validated measure that assesses the participant’s confidence in walking incremental distances, and a survey measuring their satisfaction with the individual BCT that they tested. At the end of their trial, participants received a personalized summary of their step data in response to each individual BCT. The analysis will examine the novel individual-level heterogeneity of treatment effect made possible by N-of-1 design and pool results across participants to efficiently estimate the overall efficacy of the selected behavioral change techniques in increasing low-intensity walking by 2,000 steps, five days per week. Self-efficacy will be explored as the likely mechanism of action prompting behavior change. This study will inform the providers and demonstrate the feasibility of an N-of-1 study design to effectively promote physical activity as a component of healthy aging.

Keywords: aging, exercise, habit, walking

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Authors: Ssekamanya, Mastura Badzis, Khamsiah Ismail, Dayang Shuzaidah Bt Abduludin

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With rising incidents of school violence worldwide, educators and researchers are trying to understand and find ways to enhance the safety of children at school. The purpose of this study was to investigate the extent to which the demographic variables of gender, age, length of service, position, academic qualification, and school location predicted teachers’ awareness about school safety practices in Malaysian primary schools. A stratified random sample of 380 teachers was selected in the central Malaysian states of Kuala Lumpur and Selangor. Multiple regression analysis revealed that none of the factors was a good predictor of awareness about school safety training, delivery methods of school safety information, and available school safety programs. Awareness about school safety activities was significantly predicted by school location (whether the school was located in a rural or urban area). While these results may reflect a general lack of awareness about school safety among primary school teachers in the selected locations, a national study needs to be conducted for the whole country.

Keywords: school safety awareness, predictors of school safety, multiple regression analysis, malaysian primary schools

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Authors: Dongyeob Han, Jungwon Huh, Quang Huy Tran, Choonghyun Kang

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Unmanned Aerial Vehicles (UAVs) have been used for surveillance, monitoring, inspection, and mapping. In this paper, we present a systematic approach for automatic registration of UAV images for monitoring facilities such as building, green house, and civil structures. The two-step process is applied; 1) an image matching technique based on SURF (Speeded up Robust Feature) and RANSAC (Random Sample Consensus), 2) bundle adjustment of multi-temporal images. Image matching to find corresponding points is one of the most important steps for the precise registration of multi-temporal images. We used the SURF algorithm to find a quick and effective matching points. RANSAC algorithm was used in the process of finding matching points between images and in the bundle adjustment process. Experimental results from UAV images showed that our approach has a good accuracy to be applied to the change detection of facility.

Keywords: building, image matching, temperature, unmanned aerial vehicle

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Authors: Athar Hussain Memon

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Objectives: We tried to determine the frequency of raised C-reactive protein (CRP) in patients with type 2 diabetes mellitus. Patients and Methods: This cross-sectional descriptive study of six months study was conducted at Liaquat University Hospital Hyderabad from March 2013 to August 2013. All diabetic patients of ≥35 years age of either gender for >01 year duration visited at OPD were evaluated for C-reactive protein and their glycemic status by hemoglobin A1c. The data was analyzed in SPSS and the frequency and percentage were calculated. Results: During six month study period, total 100 diabetic patients were evaluated for C-reactive protein. The majority of patients were from urban areas 75/100 (75%). The mean ±SD for age of patients with diabetes mellitus was 51.63±7.82. The mean age ±SD of patient with raised CRP was 53±7.21. The mean ±SD for HbA1c in patients with raised CRP is 9.55±1.73. The mean random blood sugar level in patients with raised CRP was 247.42 ± 6.62. The majority of subjects were of 50-69 years of age group with female predominance (p=0.01) while the CRP was raised in 70 (70%) patients in relation to age (p=0.02) and gender (p=0.01), respectively. Both HbA1c and CRP were raised in 64.9% (p=0.04) in patients with type 2 diabetes mellitus. The mean ±SD of CRP was 5.8±1.21 while for male and female individuals with raised CRP was 3.52±1.22 and 5.7±1.63, respectively. Conclusions: The raised CRP was observed in patients with type 2 diabetes mellitus.

Keywords: diabetes mellitus, C-reactive protein, hemoglobin A1c, diabetes and metabolism

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Authors: Muhammed Auwal Umar, M. Saleh

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The main purpose of this research is to examine the relationship between entrepreneurial orientation (innovativeness, risk-taking propensity, and proactiveness) and SME's growth in Bauchi metropolis. The study is quantitative in nature using a cross-sectional survey. The population of the study was 364 SMEs. Using simple random sampling, 183 questionnaires were personally distributed, out of which 165 (90%) were found valid for the analysis. Kregcie and Morgan (1970) table was used to determine the sample size. Pearson correlation was used to test the hypotheses. The analysis was conducted with the aid of IBM Statistical Package for Social Sciences (SPSS) version 20. The results established that innovativeness, risk-taking propensity, and proactiveness have significant positive relationship with SME's growth. It is therefore recommended that SMEs’ owners/managers should change their attitude by changing their product and mode of operation in line with customer demand, being proactive ahead of other competitors in trying a better way of doing things, and taking calculated risks in anticipation of high return in order for their businesses to survive and grow.

Keywords: SMEs growth, innovativeness, risk-taking propensity, proactiveness

Procedia PDF Downloads 118

Authors: A. A. Adekunle, A. M. Omoare, W. O. Oyediran

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This study was carried out to assess rural women’s skill acquisition in the processing of locust bean in Ipokia Local Government Area of Ogun State, Nigeria. Simple random sampling technique was used to select 90 women locust bean processors for this study. Data were analyzed with descriptive statistics and Pearson Product Moment Correlation. The result showed that the mean age of respondents was 40.72 years. Most (70.00%) of the respondents were married. The mean processing experience was 8.63 years. 93.30% of the respondents relied on information from fellow locust beans processors and friends. All (100%) the respondents did not acquire improved processing skill through trainings and workshops. It can be concluded that the rural women’s skill acquisition on modernized processing techniques was generally low. It is hereby recommend that the rural women processors should be trained by extension service providers through series of workshops and seminars on improved processing techniques.

Keywords: locust bean, processing, skill acquisition, rural women

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Authors: Jung-Hsuan Hsu

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Due to intense competition within the industry, companies have increasingly recognized partnerships with other companies. In addition, with outsourcing and globalization of the supply chain, it leads to companies' increasing reliance on external resources. Consequently, supply chain network becomes complex, so that it reduces the visibility of the manufacturing process. Therefore, this study is going to focus on the impact of supply chain relationship quality (SCRQ) on cooperative strategy and visibility. Questionnaire survey is going to be conducted as research method, using the organic food industry as the research subject, and the sampling method is random sampling. Finally, the data analysis will use SPSS statistical software and AMOS software to analyze and verify the hypothesis. The expected results in this study is to evaluate the supply chain relationship quality between Taiwan's food manufacturing and their suppliers regarding whether it has a positive impact for the persistence, frequency and diversity of cooperative strategy, as well as the dimensions of supply chain relationship quality on visibility regarding whether it has a positive effect.

Keywords: supply chain relationship quality (SCRQ), cooperative strategy, visibility, competition

Procedia PDF Downloads 452

Authors: Azzi Mohammed Amin

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The study aimed to measure the impact of the product for its size marketing innovation (the development of existing products, innovation of new products) in achieving customer loyalty from the perspective of a sample of consumers brand (Omar Ben Omar) food in the state of Biskra, and also measure the degree of customer loyalty to the brand. To achieve the objectives of the study, designed a form and distributed to a random sample of 280 consumers of the brand, has been relying on SPSS to analyze the results, the study revealed several findings; There is a strong customer loyalty to Omar bin Omar products. The presence of the impact of product innovation (development of existing products, the innovation of new products) on customer loyalty, with a Pearson correlation coefficient of 0.74 is a strong relationship. The presence of a statistically significant effect for the development of existing products in customer loyalty. The presence of a statistically significant effect for the innovation of new products to customer loyalty.

Keywords: marketing innovation, product innovation, customer loyalty, products

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Authors: Amos Olusola Akinola

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The aim of this study is to evaluate the internal control system on fraud prevention in Nigerian business organizations. A survey research was undertaken in five organizations from the banking and manufacturing sectors in Nigeria using the simple random sampling technique and primary data was obtained with the aid structured questionnaire drawn on five likert’s scale. Four Hypotheses were formulated and tested using the T-test Statistics, Correlation and Regression Analysis at 95% confidence interval. It was discovered that internal control has a significant positive relationship with fraud prevention and that a weak internal control system permits fraudulent activities among staff. Based on the findings, it was recommended that organizations should continually and methodically review and evaluate the components of its internal control system whether activities are working as planned or not and that every organization should have pre-determined guidelines for conducting its operations and ensures compliance with these set guidelines while proactive steps should be taken to establish the independence of the internal audit by making the audit reportable to the governing council of an organization and not the chief executive officer.

Keywords: internal control, internal system, internal audit, fraud prevention, fraud detection

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Authors: Babak Kamrani, Nozar Kishi

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Stochastic catalog represents the events module of the earthquake loss estimation models. It includes series of events with different magnitudes and corresponding frequencies/probabilities. For the development of the stochastic catalog, random or uniform sampling methods are used to sample the events from the seismicity model. For covering all the Magnitude Frequency Distribution (MFD), a huge number of events should be generated for the above-mentioned methods. Characteristic Event (CE) method chooses the events based on the interest of the insurance industry. We divide the MFD of each source into bins. We have chosen the bins based on the probability of the interest by the insurance industry. First, we have collected the information for the available seismic sources. Sources are divided into Fault sources, subduction, and events without specific fault source. We have developed the MFD for each of the individual and areal source based on the seismicity of the sources. Afterward, we have calculated the CE magnitudes based on the desired probability. To develop the stochastic catalog, we have introduced uncertainty to the location of the events too.

Keywords: stochastic catalogue, earthquake loss, uncertainty, characteristic event

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Authors: Huma Balouch

Abstract:

Menochilus sexmaculatus commonly known as six spotted zig zag ladybird, is an aphidophagus and the most misidentified Coccinellids due to the occurrence of numerous color variants. The correct identification of Menochilus sexmaculatus and its strains is necessary to implement the use of biological control. In the present study phenotypic and genotypic polymorphism was investigated in Menochilus sexmaculatus collected from Punjab, NWFP and Sindh provinces of Pakistan. Six different morphs of the species were distinguished by analyzing its Elytral color and spot pattern and then Polymerase Chain Reaction was used to generate random amplification of polymorphic DNA (RAPD) from six different types of Menochilus sexmaculatus. Forty primers (OPA & OPC Kit) were used to perform RAPD PCR on six different types of Menochilus sexmaculatus of which, seven primers revealed different patterns related to the Menochilus sexmaculatus types. These seven primers (OPA-04, OPA-09, OPA-18, OPC-04, OPC-12, OPC-15 and OPC-18) produced 111 clear polymorphic bands and 6 scorable strain specific markers. The cluster analysis applied to RAPD data showed high polymorphism among six types and it can be concluded that these six types are six polymorphic strains of the same species.

Keywords: Menochilus sexmaculatus, aphidophagus, coccinellids, phenotypic and genotypic polymorphism, RAPD-PCR, strain specific markers

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Authors: Muhammad Shoaib

Abstract:

The aim of the study is to examine the effects of family values on honest attitudes by the mediation of tolerance attitudes and justice attitudes among family members. As many other developing settings, Pakistani society is undergoing a rapid and multifaceted social changes, in which traditional thinking coexists and often clashes with modern thinking. Family values have great effects on the honest attitudes among family members as well as all the members of Pakistani society. Tolerance attitudes, justice attitudes, personal experiences and modernity factors are contributing to the development of honest attitudes among family members. Family values attitudes enhance the concept of honesty feelings, fairness, and less thinking towards theft. For the present study 520 respondents were sampled from two urban areas of Punjab province; Lahore and Faisalabad, through proportionate random sampling technique. A survey method was used as a technique of data collection and an interview schedule was administered to collect information from the respondents. The results shows similar positive effects of tolerance and justice attitudes on honest attitude by the mediation of family values attitudes.

Keywords: family values, tolerance, justice, honesty, attitudes, Pakistan

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Authors: Maha Almumaiz, Harry Evdorides

Abstract:

Change in land value typically occurs when a new interurban road construction causes an increase in accessibility; this change in the adjacent lands values differs according to land characteristics such as geographic location, land use type, land area and sale time (appraisal time). A multiple regression model is obtained to predict the percent change in land value (CLV) based on four independent variables namely land distance from the constructed road, area of land, nature of land use and time from the works completion of the road. The random values of percent change in land value were generated using Microsoft Excel with a range of up to 35%. The trend of change in land value with the four independent variables was determined from the literature references. The statistical analysis and model building process has been made by using the IBM SPSS V23 software. The Regression model suggests, for lands that are located within 3 miles as the straight distance from the road, the percent CLV is between (0-35%) which is depending on many factors including distance from the constructed road, land use, land area and time from works completion of the new road.

Keywords: interurban road, land use types, new road construction, percent CLV, regression model

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Authors: Hong-Ming Chen

Abstract:

This work considers the resolution of the Hull and White interest rate model with the jump process. A deterministic process is adopted to model the random behavior of interest rate variation as deterministic perturbations, which is depending on the time t. The Brownian motion and jumps uncertainty are denoted as the integral functions piecewise constant function w(t) and point function θ(t). It shows that the interest rate function and the yield function of the Hull and White interest rate model with jump process can be obtained by solving a nonlinear semi-infinite programming problem. A relaxed cutting plane algorithm is then proposed for solving the resulting optimization problem. The method is calibrated for the U.S. treasury securities at 3-month data and is used to analyze several effects on interest rate prices, including interest rate variability, and the negative correlation between stock returns and interest rates. The numerical results illustrate that our approach essentially generates the yield functions with minimal fitting errors and small oscillation.

Keywords: optimization, interest rate model, jump process, deterministic

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Authors: Maricris I. Abuan

Abstract:

This assessment of macrobenthic fauna found in the intertidal zone of Brgy. Poblacion, Carmen Agusan del Norte was conducted during the lowest tides of the month of June 2008. Transect-quadrat method was employed during the sampling. Twenty-transect lines were established in the area with lengths depending on the topography of the intertidal zone and were laid perpendicular to the shore, at intervals of fifty meters. Twenty-six (26) macrobenthic species with a total of seventy (70) individuals were identified in the study area. These species belong to the four Phyla -Arthropoda, Mollusca, Echinodermata and Annelida. The three most abundant macrobenthos were hermit crabs (Phylum Arthropoda) , Archaster typicus (Phylum Echinodermata), and Nassarius pullus (Phylum Mollusca). The diversity index value was 2.36. Most species exhibited random distribution And only few species had regular and clumped distribution. The pH, salinity, and sea water temperature readings were within the normal range. Results showed a very scarce macrobenthic species present in the study area.

Keywords: diversity index, macrobenthic fauna, macrobenthos, phyla

Procedia PDF Downloads 326