Search results for: multiple linear regression analysis

Authors: Sungkyung Kim, Jee-Hyeon Na, Dong-Seung Kwon

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Future mobile networks following 5th generation will be characterized by one thousand times higher gains in capacity; connections for at least one hundred billion devices; user experience capable of extremely low latency and response times. To be close to the capacity requirements and higher reliability, advanced technologies have been studied, such as multiple connectivity, small cell enhancement, heterogeneous networking, and advanced interference and mobility management. This paper is focused on the multiple connectivity in heterogeneous cellular networks. We investigate the performance of coverage and user throughput in several deployment scenarios. Using the stochastic geometry approach, the SINR distributions and the coverage probabilities are derived in case of dual connection. Also, to compare the user throughput enhancement among the deployment scenarios, we calculate the spectral efficiency and discuss our results.

Keywords: heterogeneous networks, multiple connectivity, small cell enhancement, stochastic geometry

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Authors: Ali Hesari, Arezoo Esmaeeli

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Regarding to dramatic changes of fertility and higher order births during recent decades in Iran, access to knowledge about affecting factors on different birth orders has crucial importance. In this study, According to hierarchical structure of many of social sciences data and the effect of variables of different levels of social phenomena that determine different birth orders in 365 days ending to 1390 census have been explored by multilevel approach. In this paper, 2% individual row data for 1390 census is analyzed by HLM software. Three different hierarchical linear regression models are estimated for data analysis of the first and second, third, fourth and more birth order. Research results displays different outcomes for three models. Individual level variables entered in equation are; region of residence (rural/urban), age, educational level and labor participation status and province level variable is GDP per capita. Results show that individual level variables have different effects in these three models and in second level we have different random and fixed effects in these models.

Keywords: fertility, birth order, hierarchical approach, fixe effects, random effects

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Authors: Taksina Bunbut

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Personality and grooming are vital for creating professionalism and safety image for all staffs in the airline industry. Airline Business Program also has an aim to educate students through the subject Personality Development and Grooming in order to elevate the quality of students to meet standard requirements of the airline industry. However, students agree that there are many difficulties that cause unsuccessful learning experience in this subject. The research is to study problems that can afflict students from getting good results in the classroom. Furthermore, exploring possible solutions to overcome challenges are also included in this study. The research sample consists of 140 students who attended the class of Personality Development and Grooming. The employed research instrument is a questionnaire. Statistic for data analysis is t-test and Multiple Regression Analysis. The result found that although students are satisfied with teaching and learning of this subject, they considered that teaching in English and teaching topics in social etiquette in different cultures are difficult for them to understand.

Keywords: personality development, grooming, Airline Business Program, soft skill

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Authors: Nivedita Roy, Aparajita Chattopadhyay

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Gender discrimination is already one of the major factors why India is still in the list of the 3rd World Countries, but, when it comes to gender inclusion in the environmental arena, this umbrella concept is quite unheard of by our countrymen. The main objective was to assess gender equality for the environment through calculating Environment and Gender Index on a country level, India, in this case. 22 states out of 29 were considered for calculation. Also, out of the 72 countries chosen by IUCN to calculate EGI, the lower middle income group of countries was chosen to assess the position of India, also a lower middle income group country, among them. Linear Regression is executed through SPSS and simple graphs and tables are prepared through MS-EXCEL for analysis. India portrays good governance, reporting activities well to the UN but in terms of basic livelihood and gender equality, the performance is comparatively weak.

Keywords: environment, gender, livelihood, rights, participation, development, conservation

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Authors: Ali A. Abdollahi

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During the last several decades, scientists have consistently applied Multiple Criteria Decision-Making methods in making decisions about multi-faceted, complicated subjects. While making such decisions and in order to achieve more accurate evaluations, they have regularly used a variety of criteria instead of applying just one Optimum Evaluation Criterion. The method presented here utilizes both ‘quantity’ and ‘quality’ to assess the function of the Multiple-Criteria method. Applying Data envelopment analysis (DEA), weighted aggregated sum product assessment (WASPAS), Weighted Sum Approach (WSA), Analytic Network Process (ANP), and Charnes, Cooper, Rhodes (CCR) methods, we have analyzed thirteen parks in Kerman city. It further indicates that the functions of WASPAS and WSA are compatible with each other, but also that their deviation from DEA is extensive. Finally, the results for the CCR technique do not match the results of the DEA technique. Our study indicates that the ANP method, with the average rate of 1/51, ranks closest to the DEA method, which has an average rate of 1/49.

Keywords: multiple criteria decision making, Data envelopment analysis (DEA), Charnes Cooper Rhodes (CCR), Weighted Sum Approach (WSA)

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Authors: Bright E. Owusu, Nittaya McNeil

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Rainfall is one of the most essential quantities in meteorology and hydrology. It has important impacts on people’s daily life and excess or inadequate of it could bring tremendous losses in economy and cause fatalities. Population increase around the globe tends to have a corresponding increase in settlement and industrialization. Some countries are affected by flood and drought occasionally due to climate change, which disrupt most of the daily activities. Knowledge of trends in spatial and temporal rainfall variability and their physical explanations would be beneficial in climate change assessment and to determine erosivity. This study describes the spatial-temporal variability of daily rainfall in Australia and their corresponding long-term trend during 1950-2013. The spatial patterns were investigated by using exploratory factor analysis and the long term trend in rainfall time series were determined by linear regression, Mann-Kendall rank statistics and the Sen’s slope test. The exploratory factor analysis explained most of the variations in the data and grouped Australia into eight distinct rainfall regions with different rainfall patterns. Significant increasing trends in annual rainfall were observed in the northern regions of Australia. However, the northeastern part was the wettest of all the eight rainfall regions.

Keywords: climate change, explanatory factor analysis, Mann-Kendall and Sen’s slope test, rainfall.

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Authors: Adji Achmad Rinaldo Fernandes

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Path analysis tests the relationship between variables through cause and effect. Before conducting further tests on path analysis, the assumption of linearity must be met. If the shape of the relationship is not linear and the shape of the curve is unknown, then use a nonparametric approach, one of which is a truncated spline. The purpose of this study is to estimate the function and get the best model on the nonparametric truncated spline path of linear, quadratic, and cubic orders with 1 and 2-knot points and determine the significance of the best function estimator in modeling farmer loyalty through the jackknife resampling method. This study uses secondary data through questionnaires to farmers in Sumbawa Regency who use SP-36 subsidized fertilizer products as many as 100 respondents. Based on the results of the analysis, it is known that the best-truncated spline nonparametric path model is the quadratic order of 2 knots with a coefficient of determination of 85.50%; the significance of the best-truncated spline nonparametric path estimator shows that all exogenous variables have a significant effect on endogenous variables.

Keywords: nonparametric path analysis, farmer loyalty, jackknife resampling, truncated spline

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Authors: Mina Adel Shokry Fahim, Jūratė Sužiedelytė Visockienė

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With the growing concern over air pollution (AP), it is clear that this has gained more prominence than ever before. The level of consciousness has increased and a sense of knowledge now has to be forwarded as a duty by those enlightened enough to disseminate it to others. This realisation often comes after an understanding of how poor air quality indices (AQI) damage human health. The study focuses on assessing air pollution prediction models specifically for Lithuania, addressing a substantial need for empirical research within the region. Concentrating on Vilnius, it specifically examines particulate matter concentrations 10 micrometers or less in diameter (PM10). Utilizing Gaussian Process Regression (GPR) and Regression Tree Ensemble, and Regression Tree methodologies, predictive forecasting models are validated and tested using hourly data from January 2020 to December 2022. The study explores the classification of AP data into anthropogenic and natural sources, the impact of AP on human health, and its connection to cardiovascular diseases. The study revealed varying levels of accuracy among the models, with GPR achieving the highest accuracy, indicated by an RMSE of 4.14 in validation and 3.89 in testing.

Keywords: air pollution, anthropogenic and natural sources, machine learning, Gaussian process regression, tree ensemble, forecasting models, particulate matter

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Authors: Amit Das

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Background and significance of the study: Generally investors and market forecasters use financial statement for investigation while it awakens contribute to investing. The main vicinity of financial accounting and reporting practices recommends a few basic financial performance indicators, namely, return on capital employed, return on assets and earnings per share, which is associated considerably with share prices. It is principally true in case of Indian pharmaceutical companies also. Share investing is intriguing a financial risk in addition to investors look for those financial evaluations which have noteworthy shock on share price. A crucial intention of financial statement analysis and reporting is to offer information which is helpful predominantly to exterior clients in creating credit as well as investment choices. Sound financial performance attracts the investors automatically and it will increase the share price of the respective companies. Keeping in view of this, this research work investigates the impact of financial performance indicators on share price of pharmaceutical companies in India which is listed in the Bombay Stock Exchange. Methodology: This research work is based on secondary data collected from moneycontrol database on September 28, 2015 of top 101 pharmaceutical companies in India. Since this study selects four financial performance indicators purposively and availability in the database, that is, earnings per share, return on capital employed, return on assets and net profits as independent variables and one dependent variable, share price of 101 pharmaceutical companies. While analysing the data, correlation statistics, multiple regression technique and appropriate test of significance have been used. Major findings: Correlation statistics show that four financial performance indicators of 101 pharmaceutical companies are associated positively and negatively with its share price and it is very much significant that more than 80 companies’ financial performances are related positively. Multiple correlation test results indicate that financial performance indicators are highly related with share prices of the selected pharmaceutical companies. Furthermore, multiple regression test results illustrate that when financial performances are good, share prices have been increased steadily in the Bombay stock exchange and all results are statistically significant. It is more important to note that sensitivity indices were changed slightly through financial performance indicators of selected pharmaceutical companies in India. Concluding statements: The share prices of pharmaceutical companies depend on the sound financial performances. It is very clear that share prices are changed with the movement of two important financial performance indicators, that is, earnings per share and return on assets. Since 101 pharmaceutical companies are listed in the Bombay stock exchange and Sensex are changed with this, it is obvious that Government of India has to take important decisions regarding production and exports of pharmaceutical products so that financial performance of all the pharmaceutical companies are improved and its share price are increased positively.

Keywords: financial performance indicators, share prices, pharmaceutical companies, India

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Authors: Abdreheman Seid Abdella

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This study examined instructors willingness, self-efficacy beliefs, attitudes and knowledge about provisions of instructional accommodations for students with disabilities in universities. Major concepts used in this study operationally defined and some models of disability were reviewed. Questionnaires were distributed to a total of 181 instructors from four universities and quantitative data was generated. Then to analyze the data, appropriate methods of data analysis were employed. The result indicated that on average instructors had positive willingness, strong self-efficacy beliefs and positive attitudes towards providing instructional accommodations. In addition, the result showed that the majority of participants had moderate level of knowledge about provision of instructional accommodations. Concerning the relationship between instructors background variables and dependent variables, the result revealed that location of university and awareness raising training about Inclusive Education showed statistically significant relationship with all dependent variables (willingness, self-efficacy beliefs, attitudes and knowledge). On the other hand, gender and college/faculty did not show a statistically significant relationship. In addition, it was found that among the inter-correlation of dependent variables, the correlation between attitudes and willingness to provide accommodations was the strongest. Furthermore, using multiple linear regression analysis, this study also indicated that predictor variables like self-efficacy beliefs, attitudes, knowledge and teaching methodology training made statistically significant contribution to predicting the criterion willingness. Predictor variables like willingness and attitudes made statistically significant contribution to predicting self-efficacy beliefs. Predictor variables like willingness, Special Needs Education course and self-efficacy beliefs made statistically significant contribution to predict attitudes. Predictor variables like Special Needs Education courses, the location of university and willingness made statistically significant contribution to predicting knowledge. Finally, using exploratory factor analysis, this study showed that there were four components or factors each that represent the underlying constructs of willingness and self-efficacy beliefs to provide instructional accommodations items, five components for attitudes towards providing accommodations items and three components represent the underlying constructs for knowledge about provisions of instructional accommodations items. Based on the findings, recommendations were made for improving the situation of instructional accommodations in Ethiopian universities.

Keywords: willingness, self-efficacy belief, attitude, knowledge

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Authors: M. Najafi, S. Bab, F. Rahimi Dehgolan

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The motion of an axially moving beam with rotating prismatic joint with a tip mass on the end is analyzed to investigate the nonlinear vibration and dynamic stability of the beam. The beam is moving with a harmonic axially and rotating velocity about a constant mean velocity. A time-dependent partial differential equation and boundary conditions with the aid of the Hamilton principle are derived to describe the beam lateral deflection. After the partial differential equation is discretized by the Galerkin method, the method of multiple scales is applied to obtain analytical solutions. Frequency response curves are plotted for the super harmonic resonances of the first and the second modes. The effects of non-linear term and mean velocity are investigated on the steady state response of the axially moving beam. The results are validated with numerical simulations.

Keywords: super harmonic resonances, non-linear vibration, axially moving beam, Galerkin method

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Authors: Reeta Devi, Hitender Kumar Tyagi, Dinesh Kumar

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In present scenario, cardiovascular problems are growing challenge for researchers and physiologists. As heart disease have no geographic, gender or socioeconomic specific reasons; detecting cardiac irregularities at early stage followed by quick and correct treatment is very important. Electrocardiogram is the finest tool for continuous monitoring of heart activity. Heart rate variability (HRV) is used to measure naturally occurring oscillations between consecutive cardiac cycles. Analysis of this variability is carried out using time domain, frequency domain and non-linear parameters. This paper presents HRV analysis of the online dataset for normal sinus rhythm (taken as healthy subject) and sudden cardiac death (SCD subject) using all three methods computing values for parameters like standard deviation of node to node intervals (SDNN), square root of mean of the sequences of difference between adjacent RR intervals (RMSSD), mean of R to R intervals (mean RR) in time domain, very low-frequency (VLF), low-frequency (LF), high frequency (HF) and ratio of low to high frequency (LF/HF ratio) in frequency domain and Poincare plot for non linear analysis. To differentiate HRV of healthy subject from subject died with SCD, k –nearest neighbor (k-NN) classifier has been used because of its high accuracy. Results show highly reduced values for all stated parameters for SCD subjects as compared to healthy ones. As the dataset used for SCD patients is recording of their ECG signal one hour prior to their death, it is therefore, verified with an accuracy of 95% that proposed algorithm can identify mortality risk of a patient one hour before its death. The identification of a patient’s mortality risk at such an early stage may prevent him/her meeting sudden death if in-time and right treatment is given by the doctor.

Keywords: early stage prediction, heart rate variability, linear and non-linear analysis, sudden cardiac death

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Authors: İsmail İnce

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The aim of this study is to determine index and mechanical properties of pyroclastic rock in a practical way by means of electrical resistivity method. For this purpose, electrical resistivity, uniaxial compressive strength, point load strength, P-wave velocity, density and porosity values of 10 different pyroclastic rocks were measured in the laboratory. A simple regression analysis was made among the index-mechanical properties of the samples compatible with electrical resistivity values. A strong exponentially relation was found between index-mechanical properties and electrical resistivity values. The electrical resistivity method can be used to assess the engineering properties of the rock from which it is difficult to obtain regular shaped samples as a non-destructive method.

Keywords: electrical resistivity, index-mechanical properties, pyroclastic rocks, regression analysis

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Authors: Y. de Smet, J. Hubinont

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PROMETHEE and GAIA are well-known Multiple Criteria Decision Aid methods. Given an evaluation table and preference parameters they allow to rank the alternatives, to visualize the problem, to perform sensitivity and robustness analysis, etc. Unfortunately, it is often hard for the Decision Maker (DM) to estimate the precise values of these parameters. Therefore an alternative option is to give ranges of potential values in order to apply Stochastic Multicriteria Acceptability Analysis. This has been recently studied in the context of the SMAA-PROMETHEE method. The aim of this contribution is to propose an SMAA extension of GAIA. We show how this tool can be useful and provide complementary information to SMAA-PROMETHEE. This is illustrated on a pedagogical example.

Keywords: multiple criteria decision making, PROMETHEE, GAIA, SMAA

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Authors: Kumar Shashvat, Amol P. Bhondekar

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In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.

Keywords: odor classification, generative models, naive bayes, linear discriminant analysis

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Authors: Débora V. Busman, Venerando E. Amaro, Mattheus da C. Prudêncio

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Prognostic studies of the shoreline are of utmost importance for Ponta Negra Beach, located in Natal, Northeastern Brazil, where the infrastructure recently built along the shoreline is severely affected by flooding and erosion. This study compares shoreline predictions using three linear regression methods (LMS, LRR and WLR) and tries to discern the best method for different shoreline position scenarios. The methods have shown erosion on the beach in each of the scenarios tested, even in less intense dynamic conditions. The WLA_A with confidence interval of 95% was the well-adjusted model and calculated a retreat of -1.25 m/yr to -2.0 m/yr in hot spot areas. The change of the shoreline on Ponta Negra Beach can be measured as a negative exponential curve. Analysis of these methods has shown a correlation with the morphodynamic stage of the beach.

Keywords: coastal erosion, prognostic model, DSAS, environmental safety

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Authors: Tugce Caliskan

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The gentrification literature in Turkey provided important insights regarding the analysis of the socio-spatial change in İstanbul mostly through the existing gentrification theories which were produced in Anglo-American literature. Yet early researches focused on the classical gentrification while failing to notice other place-specific forms of the phenomena. It was only after the mid-2000s that scholarly attention shifted to the recent discussions in the mainstream such as the neoliberal urban policies, government involvement, and resistance. Although these studies have considerable potential to contribute to the geography of gentrification, it seems that copying the linear timeline of Anglo-American conceptualization limited the space to introduce contextually nuanced way of process in Turkey. More specifically, the gentrification literature in Turkey acknowledged the linear timeline of the process drawing on the mainstream studies, and, made the spontaneous classical gentrification as the starting point in İstanbul at the expense of contextually specific forms of the phenomenon that took place in the same years. This paper is an attempt to understand place-specific forms of gentrification through the abandonment of the linear understanding of time. In this vein, this paper approaches the process as moving both linear and cyclical rather than the waves succeeded each other. Maintaining a dialectical relationship between the cyclical and the linear time, this paper investigates how the components of gentrification have been taken place in the cyclical timeline while becoming bolder in the linear timeline. This paper argues that taking the (re)investment in the secondary circuit of capital and class transformation as the core characteristics of gentrification, and accordingly, searching for these components beyond the linear timeline provide strategic value to decenter the perspectives, not merely for Turkish studies. In this vein, this strategy revealed that Western experience of gentrification did not travel, adopted or copied in Turkey but gentrification -as an abstract and general concept- has emerged as a product of different contextual, historical and temporal forces which must be considered within the framework of state-led urbanization as early as 1980 differing from the Global North trajectories.

Keywords: comparative urbanism, geography of gentrification, linear and cyclical timeline, state-led gentrification

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Authors: Y. Rathiranee, D. M. Semasinghe

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This study attempts to identify the factors influencing on women empowerment of rural area in Sri Lanka through micro finance services. Data were collected from one hundred (100) rural women involving self employment activities through a questionnaire using direct personal interviews. Judgment and Convenience Random sampling technique was used to select the sample size from three Divisional Secretariat divisions of Kandawalai, Poonakari and Karachchi in Kilinochchi District. The factor analysis was performed on fourteen (14) variables for screening and reducing the variables to identify the influencing factors on empowerment. Multiple regression analysis was used to identify the relationship between the three empowerment factors and the impact of micro-finance on overall empowerment of rural women. The result of this study summarized the variables into three factors namely decision making, freedom to mobility and family support and which are positively associated with empowerment. In addition to this the value of adjusted R2 is 0.248 indicates that all the variables extracted can be explained 24.8% of the variation in the women empowerment through microfinance. Independent variables of these three factors have a positive correlation with women empowerment as well as significant values at 5 percent level.

Keywords: influencing factors, micro finance, rural women, women empowerment

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Authors: Tunjo Perić, Franjo Bratić

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In this paper the goal programming methodology for solving multiple objective problem of the technological variants and production plan optimization has been applied. The optimization criteria are determined and the multiple objective linear programming model for solving a problem of the technological variants and production plan optimization is formed and solved. Then the obtained results are analysed. The obtained results point out to the possibility of efficient application of the goal programming methodology in solving the problem of the technological variants and production plan optimization. The paper points out on the advantages of the application of the goal programming methodolohy compare to the Surrogat Worth Trade-off method in solving this problem.

Keywords: goal programming, multi objective programming, production plan, SWT method, technological variants

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Authors: Leng Jian-Wei, Wang Lai-Jun, Li Ye

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In order to measure and analyze the transportation situation within the counties of Shaanxi province over a certain period of time and to promote the province's future transportation planning and development, this paper proposes a reasonable layout plan and compares model rationality. The study uses entropy weight method to measure the transportation advantages of 107 counties in Shaanxi province from three dimensions: road network density, trunk line influence and location advantage in 2013 and 2021, and applies spatial autocorrelation analysis method to analyze the spatial layout and development trend of county-level transportation, and conducts ordinary least square (OLS)regression on transportation impact factors and other influencing factors. The paper also compares the regression fitting degree of the Geographically weighted regression(GWR) model and the OLS model. The results show that spatially, the transportation advantages of Shaanxi province generally show a decreasing trend from the Weihe Plain to the surrounding areas and mainly exhibit high-high clustering phenomenon. Temporally, transportation advantages show an overall upward trend, and the phenomenon of spatial imbalance gradually decreases. People's travel demands have changed to some extent, and the demand for rapid transportation has increased overall. The GWR model regression fitting degree of transportation advantages is 0.74, which is higher than the OLS regression model's fitting degree of 0.64. Based on the evolution of transportation advantages, it is predicted that this trend will continue for a period of time in the future. To improve the transportation advantages of Shaanxi province increasing the layout of rapid transportation can effectively enhance the transportation advantages of Shaanxi province. When analyzing spatial heterogeneity, geographic factors should be considered to establish a more reliable model

Keywords: traffic dominance, GWR model, spatial autocorrelation analysis, temporal and spatial evolution

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Authors: Wanida Suwunniponth

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The purpose of this research was to investigate the relationship between the factors of using online social network for tourism destination in case of Bangkok area in Thailand, by extending the use of technology acceptance model (TAM). This study employed by quantitative research and the target population were entrepreneurs and local people in Bangkok who use social network-Facebook concerning tourist destinations in Bangkok. Questionnaire was used to collect data from 300 purposive samples. The multiple regression analysis and path analysis were used to analyze data. The results revealed that most people who used Facebook for promoting tourism destinations in Bangkok perceived ease of use, perceived usefulness, perceived trust in using Facebook and influenced by social normative as well as having positive attitude towards using this application. Addition, the hypothesis results indicate that acceptance of online social network-Facebook was related to the positive attitude towards using of Facebook and related to their intention to use this application for tourism.

Keywords: Facebook, online social network, technology acceptance model, tourism destination

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Authors: Chigozirim Onwusiribe, Jude Mbanasor

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Egusi Melon (Citrullus Lanatus Thunb. Mansf ) is a very important oil seed that serves a major ingredient in the diet of most of the households in Nigeria. Egusi Melon is very nutritious and very important in meeting the food security needs of Nigerians. Egusi Melon is cultivated in most farm enterprise in South East Nigeria but the profitability of its value chain needs to be investigated. This study analyzed the profitability of the Egusi Melon value chain. Specifically this study developed a value chain map for Egusi Melon, analysed the profitability of each stage of the Egusi Melon Value chain and analysed the determinants of the profitability of the Egusi Melon at each stage of the value chain. Multi stage sampling technique was used to select 125 farm enterprises with similar capacity and characteristics. Questionnaire and interview were used to elicit the required data while descriptive statistics, Food and Agriculture Organization Value Chain Analysis Tool, profitability ratios and multiple regression analysis were used for the data analysis. One of the findings showed that the stages of the Egusi Melon value chain are very profitable. Based on the findings, we recommend the provision of grants by government and donor agencies to the farm enterprises through their cooperative societies, this will provide the necessary funds for the local fabrication of value addition and processing equipment to suit their unique value addition needs not met by the imported equipment.

Keywords: value, chain, melon, farm, enterprises

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Authors: Rhea Mathews

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The purpose of the study is to investigate the effects of perceived social support and cultural self-efficacy on the acculturative stress of international postgraduate students in the United Kingdom. The study adopted Berry, Kim, Minde & Mok’s (1987) acculturative framework on acculturative stress and examined the relationship between the variables. The study hypothesized that perceived social support and cultural self-efficacy would predict lower levels of acculturative stress among students. Postgraduate students in the United Kingdom (N = 76) completed three surveys measuring the variables; Acculturative Stress Scale for International Students, Multidimensional Scale of Perceived Social Support, and Cultural Self-efficacy for Adolescents. To evaluate the role of the perceived social support and cultural self-efficacy in determining the acculturative stress level of international students, multiple linear regression was employed. Both independent variables exhibited a significant, negative relationship with acculturative stress (p < 0.001; p < 0.01). Results described that cultural self-efficacy and perceived social support significantly predicted acculturative stress (p < 0.01). Together, the variables accounted for 22% of the variance in acculturative stress scores (adjusted R² = 0.22), with cultural self-efficacy playing a larger role in predicting the dependent variable. Limitations and implications of the study are noted. The findings of the study are discussed in relation to enhancing international students’ acculturative experience when relocating to a new environment.

Keywords: acculturative stress, coping, cultural adjustment, cultural self-efficacy, international education, international students, migration, perceived social support

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Authors: Ren-Jieh Kuo, Chun-Shou Huang

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The research of juice flavor forecasting has become more important in China. Due to the fast economic growth in China, many different kinds of juices have been introduced to the market. If a beverage company can understand their customers’ preference well, the juice can be served more attractively. Thus, this study intends to introduce the basic theory and computing process of grapes juice flavor forecasting based on support vector regression (SVR). Applying SVR, BPN and LR to forecast the flavor of grapes juice in real data, the result shows that SVR is more suitable and effective at predicting performance.

Keywords: flavor forecasting, artificial neural networks, Support Vector Regression, China

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Authors: Lim Sanny, Felix Christian

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The use of heavy equipment in Indonesia is always increasing. Cost reduction in procurement of spare parts is the aim of the company. The spare parts in this research are focused in the kind of filters. On the early step, the choosing of priority filter will be studied further by using the ABC analysis. To find out future demand of the filter, this research is using demand forecast by utilizing the QM software for windows. And to find out the best method of inventory control for each kind of filter is by comparing the total cost of Economic Order Quantity and Quick response inventory method. For the three kind of filters which are Cartridge, Engine oil – pn : 600-211-123, Element, Transmission – pn : 424-16-11140, and Element, Hydraulic – pn : 07063-01054, the best forecasting method is Linear regression. The best method for inventory control of Cartridge, Engine oil – pn : 600-211-123 and Element, Transmission – pn : 424-16-11140, is Quick Response Inventory, while the best method for Element, Hydraulic – pn : 07063-01054 is Economic Order Quantity.

Keywords: strategy, inventory, ABC analysis, forecasting, economic order quantity, quick response inventory

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Authors: Mukisa Simon Peter Turker, Etomaru Irene

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This study examined factors determining the success of University-Industry Collaboration (UIC) in the science academic units (SAUs) at Makerere University. This was prompted by concerns about weak linkages between industry and the academic units at Makerere University. The study examined institutional, relational, output, and framework factors determining the success of UIC in the science academic units at Makerere University. The study adopted a predictive cross-sectional survey design. Data was collected using a questionnaire survey from 172 academic staff from the six SAUs at Makerere University. Stratified, proportionate, and simple random sampling techniques were used to select the samples. The study used descriptive statistics and linear multiple regression analysis to analyze data. The study findings reveal a coefficient of determination (R-square) of 0.403 at a significance level of 0.000, suggesting that UIC success was 40.3% at a standardized error of estimate of 0.60188. The strength of association between Institutional factors, Relational factors, Output factors, and Framework factors, taking into consideration all interactions among the study variables, was at 64% (R= 0.635). Institutional, Relational, Output and Framework factors accounted for 34% of the variance in the level of UIC success (adjusted R2 = 0.338). The remaining variance of 66% is explained by factors other than Institutional, Relational, Output, and Framework factors. The standardized coefficient statistics revealed that Relational factors (β = 0.454, t = 5.247, p = 0.000) and Framework factors (β = 0.311, t = 3.770, p = 0.000) are the only statistically significant determinants of the success of UIC in the SAU in Makerere University. Output factors (β = 0.082, t =1.096, p = 0.275) and Institutional factors β = 0.023, t = 0.292, p = 0.771) turned out to be statistically insignificant determinants of the success of UIC in the science academic units at Makerere University. The study concludes that Relational Factors and Framework Factors positively and significantly determine the success of UIC, but output factors and institutional factors are not statistically significant determinants of UIC in the SAUs at Makerere University. The study recommends strategies to consolidate Relational and Framework Factors to enhance UIC at Makerere University and further research on the effects of Institutional and Output factors on the success of UIC in universities.

Keywords: university-industry collaboration, output factors, relational factors, framework factors, institutional factors

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Authors: Margareth E. Bolla, Ludfi Djakfar, Achmad Wicaksono

Abstract:

The increase in the number of motorcycle users in Indonesia is in line with the increase in accidents involving motorcycles. Several previous studies have shown that humans are the biggest factor causing accidents, and the driver's personality factor will affect his behavior on the road. This study was conducted to see how a person's personality traits will affect the probability of having an accident while driving. The Big Five Inventory (BFI) questionnaire and the Honda Riding Trainer (HRT) simulator were used as measuring tools, while the analysis carried out was logistic regression analysis. The results of the descriptive analysis of the respondent's personality based on the BFI show that the majority of drivers have the dominant character of neuroticism (34%), while the smallest group is the driver with the dominant type of openness character (6%). The percentage of motorists who were not involved in an accident was 54%. The results of the logistic regression analysis form a mathematical model as follows Y = -3.852 - 0.288 X1 + 0.596 X2 + 0.429 X3 - 0.386 X4 - 0.094 X5 + 0.436 X6 + 0.162 X7, where the results of hypothesis testing indicate that the variables openness, conscientiousness, extraversion, agreeableness, neuroticism, history of traffic accidents and age at starting driving did not have a significant effect on the probability of a motorcyclist being involved in an accident.

Keywords: accidents, BFI, probability, simulator

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Authors: Barbara Gawda

Abstract:

Attachment model formed in childhood has an important impact on emotional development, personality, and social relationships. Attachment is also thought to have an impact on construction of affective-cognitive schemas and cognitive functioning. The aim of the current study was to verify whether there is an association between attachment and cognitive rigidity defined as dogmatism and intolerance of ambiguity. The analysis of 180 participants (persons of a similar age and education level, number of men and women was equal) was conducted. To test the attachment styles, the Revised Experiences in Close Relationships Inventory (ECR-R) was used. To examine cognitive rigidity, the Rokeach and Budner questionnaires were used. A multiple regression model was employed to examine whether attachment styles are predictors for dogmatism. The results confirmed that fearful-ambivalent attachment is the main predictor for dogmatism but not for intolerance of ambiguity.

Keywords: attachment styles, cognitive rigidity, dogmatism, intolerance of ambiguity

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Authors: Farhad Ghasemi

Abstract:

Along with transforming the international system into a complex and chaotic system, the fundamental question arises: how can deterrence be reconstructed conceptually and theoretically in this system model? The deterrence system is much more complex today than it was seven decades ago. This article suggests that the perception of deterrence as a linear system is a fundamental mistake because it does not consider the new dynamics of the international system, including network power dynamics. The author aims to improve this point by focusing on complexity and chaos theories, especially their nonlinearity and cascading failure principles. This article proposes that the perception of deterrence as a linear system is a fundamental mistake, as the new dynamics of the surrounding international system do not take into account. The author recognizes deterrence as a nonlinear system and introduces it as a concept in strategic studies.

Keywords: complexity, international system, deterrence, linear deterrence, nonlinear deterrence

Procedia PDF Downloads 142

Authors: Aschalew Cherie Workneh, K. S. Hari Prasad, Chandra Shekhar Prasad Ojha

Abstract:

Due to the increase in water scarcity, the crop water stress index (CWSI) is receiving significant attention these days, especially in arid and semiarid regions, for quantifying water stress and effective irrigation scheduling. Nowadays, machine learning techniques such as neural networks are being widely used to determine CWSI. In the present study, the performance of two artificial neural networks, namely, Self-Organizing Maps (SOM) and Feed Forward-Back Propagation Artificial Neural Networks (FF-BP-ANN), are compared while determining the CWSI of rice crop. Irrigation field experiments with varying degrees of irrigation were conducted at the irrigation field laboratory of the Indian Institute of Technology, Roorkee, during the growing season of the rice crop. The CWSI of rice was computed empirically by measuring key meteorological variables (relative humidity, air temperature, wind speed, and canopy temperature) and crop parameters (crop height and root depth). The empirically computed CWSI was compared with SOM and FF-BP-ANN predicted CWSI. The upper and lower CWSI baselines are computed using multiple regression analysis. The regression analysis showed that the lower CWSI baseline for rice is a function of crop height (h), air vapor pressure deficit (AVPD), and wind speed (u), whereas the upper CWSI baseline is a function of crop height (h) and wind speed (u). The performance of SOM and FF-BP-ANN were compared by computing Nash-Sutcliffe efficiency (NSE), index of agreement (d), root mean squared error (RMSE), and coefficient of correlation (R²). It is found that FF-BP-ANN performs better than SOM while predicting the CWSI of rice crops.

Keywords: artificial neural networks; crop water stress index; canopy temperature, prediction capability

Procedia PDF Downloads 117