Search results for: Statistical package IBM SPSS 20

Authors: C. G. Sawant, C. S. Patil

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The investigation was conducted during January 2016 on Farmer’s field at Nandur Madhyameshwar, Tq. Niphad, Dist. Nashik (Maharashtra: India) on bio-efficacy of newer insecticides against Plutella xylostella L. infesting cabbage. The cabbage crop (var. Saint) was raised according to package of practices except for plant protection measures. Six newer insecticides along with two conventional insecticides and one synthetic pyrethroid were applied twice at 30 and 55 days after transplanting. Insecticidal solutions were diluted in water (375-500 L ha-1) and applied using knapsack sprayer (16L) with hollow cone nozzle. Treatments included indoxacarb @ 40 g a.i.ha-1, spinosad @ 17.5 g a.i.ha-1, flubendiamide @18.24 g a.i. ha-1, diafenthiuron @ 300 g a. i. ha-1, emamectin benzoate @ 10 g a. i. ha-1, chlorantraniliprole @ 10 g a. i. ha-1, quinalphos @ 250 g a. i. ha-1, triazophos @ 500 g a. i. ha-1, bifenthrin @ 50 g a.i. ha-1 and untreated control. The larvae were counted on head and outside the head. Observations were recorded one day before spray (Precount) and 1,3,7,14 days after spray. Results revealed that all the insecticidal treatments were significantly superior over untreated control by recording lower larval count. Among the insecticidal treatments, significantly lowest number of larvae of diamondback moth was recorded in chlorantraniliprole @ 10 g a.i.ha-1 (1.00 larvae plant-1) followed by spinosad @ 17.5 g a.i. ha-1 (1.45 larvae plant-1 and flubendiamide 18.24 g a.i. ha-1(1.53 larvae plant-1). The efficacy of insecticides reflected on yield of marketable cabbage heads by recording 242.27 qt ha-1 (1:33.38) in the treatment of chlorantraniliprole @ 10 g a.i.ha-1. It was followed by spinosad @ 17.5 g a.i. ha-1 with 236.91 qt ha-1 (1:24.92) and flubendiamide 18.24 g a.i. ha-1 with 228.49 qt ha-1 (1:30.43).

Keywords: bio-efficacy, cabbage, chlorantraniliprole, Plutella xylostella L.

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Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

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Authors: Muhammad Sulman, Tabinda Khurshid, Afsheen Masood

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The current research focused on determining the factors that determine the brand loyalty in consumers. It was hypothesized that there are certain demographical features that lead the consumers to adhere more towards certain brands. Cross-sectional research design was used. The sample for the current research comprised of participants (N=500) from age group 16 to 55 years. The data was collected through self-constructed demographic questionnaire as well as from a self-constructed Brand Loyalty Questionnaire. Brand Loyalty Questionnaire was adapted after taking permission from researchers. A pilot study was conducted to chalk out all the ambiguities of the questionnaire. The final version was administered on 250 participants. The descriptive and inferential analyses were carried on through SPSS version 24.00 to explore the factors that determine Brand Loyalty. The findings revealed that there is a relationship between brand loyalty and brand loyalty demographics and certain factors emerged as significant predictors of brand loyalty in young and middle aged consumers. The research findings carry strong implications for organizational and consumer psychologists in particular and for professionals in marketing and policy making in general.

Keywords: consumers, consumer psychologists, marketing, organizational, policy making

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Authors: Sibel Karacaoglu, Fatma Ç. Kayapinar

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The aim of the study is to investigate the effect of the core training program on physical fitness characteristics and body composition in male volleyball players. 26 male university volleyball team players aged between 19 to 24 years who had no health problems and injury participated in the study. Subjects were divided into training (TG) and control groups (CG) as randomly. Data from twenty-one players who completed all training sessions were used for statistical analysis (TG,n=11; CG,n=10). A core training program was applied to the training group three days a week for 10 weeks. On the other hand, the control group did not receive any training. Before and after the 10-week training program, pre- and post-testing comprised of body composition measurements (weight, BMI, bioelectrical impedance analysis) and physical fitness measurements including flexibility (sit and reach test), muscle strength (back, leg and grip strength by dynamometer), muscle endurance (sit-ups and push-ups tests), power (one-legged jump and vertical jump tests), speed (20m sprint, 30m sprint) and balance tests (one-legged standing test) were performed. Changes of pre- and post- test values of the groups were determined by using dependent t test. According to the statistical analysis of data, no significant difference was found in terms of body composition in the both groups for pre- and post- test values. In the training group, all physical fitness measurements improved significantly after core training program (p<0.05) except 30m speed and handgrip strength (p>0.05). On the hand, only 20m speed test values improved after post-test period (p<0.05), but the other physical fitness tests values did not differ (p>0.05) between pre- and post- test measurement in the control group. The results of the study suggest that the core training program has positive effect on physical fitness characteristics in male volleyball players.

Keywords: body composition, core training, physical fitness, volleyball

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Authors: A. Ridall, J. Ingels

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Microplastics (MPs; < 5 mm) have been cited as exceptionally detrimental to marine organisms and ocean health. They can carry other pollutants and abundant microbes that can serve as food for other organisms. Their small particle size and high abundance means that non-discriminatory feeders may ingest MPs involuntarily and microbial colonization of the particles (a niche coined ‘Plastisphere’) could facilitate particle ingestion. To assess how marine nematodes, the most abundant member of the meiofauna (32-500 um), are affected by microbe-MP associations, an experiment was conducted with three MP concentrations (low, medium, and expected high values of MPs in a local bay system), and two levels of microbe-MP associations (absence or presence). MPs were introduced into sediment microcosms and treatments were removed at three distinct time points (0, 3, and 7 days) to measure mean MP consumption/individual nematode. The quantitative results from this work should inform on microbial facilitation of MP ingestion and MP effects on seafloor ecology. As most MP feeding experiments use straight-from-package or sterile MPs, this work represents an important step in realizing the effects of MPs and their plastispheres in coastal sediments where they likely accumulate microbial biofilms prior to their ingestion by marine metazoans. Furthermore, the results here convey realistic effects of MPs on faunal behaviors, as the MP concentrations used are based on field measurements rather than artificially high levels.

Keywords: ecosystem function, microbeads, plastisphere, pollution, polyethylene

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Authors: Hai L. Tran

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When covering events and issues, the news media often employ both personal accounts as well as facts and figures. However, the process of using numbers and narratives in the newsroom is mostly operated through trial and error. There is a demonstrated need for the news industry to better understand the specific effects of storytelling and data-driven reporting on the audience as well as explanatory factors driving such effects. In the academic world, anecdotal evidence and statistical evidence have been studied in a mutually exclusive manner. Existing research tends to treat pertinent effects as though the use of one form precludes the other and as if a tradeoff is required. Meanwhile, narratives and statistical facts are often combined in various communication contexts, especially in news presentations. There is value in reconceptualizing and theorizing about both relative and collective impacts of numbers and narratives as well as the mechanism underlying such effects. The current undertaking seeks to link theory to practice by providing a complete picture of how and why people are influenced by information conveyed through quantitative and qualitative accounts. Specifically, the cognitive-experiential theory is invoked to argue that humans employ two distinct systems to process information. The rational system requires the processing of logical evidence effortful analytical cognitions, which are affect-free. Meanwhile, the experiential system is intuitive, rapid, automatic, and holistic, thereby demanding minimum cognitive resources and relating to the experience of affect. In certain situations, one system might dominate the other, but rational and experiential modes of processing operations in parallel and at the same time. As such, anecdotes and quantified facts impact audience response differently and a combination of data and narratives is more effective than either form of evidence. In addition, the present study identifies several media variables and human factors driving the effects of statistics and anecdotes. An integrative model is proposed to explain how message characteristics (modality, vividness, salience, congruency, position) and individual differences (involvement, numeracy skills, cognitive resources, cultural orientation) impact selective exposure, which in turn activates pertinent modes of processing, and thereby induces corresponding responses. The present study represents a step toward bridging theoretical frameworks from various disciplines to better understand the specific effects and the conditions under which the use of anecdotal evidence and/or statistical evidence enhances or undermines information processing. In addition to theoretical contributions, this research helps inform news professionals about the benefits and pitfalls of incorporating quantitative and qualitative accounts in reporting. It proposes a typology of possible scenarios and appropriate strategies for journalists to use when presenting news with anecdotes and numbers.

Keywords: data, narrative, number, anecdote, storytelling, news

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Authors: Sutharsini Jesuthasan, N. Umakanth

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Presently the impact of electronic word of mouth on consumer’s purchasing intentions very popular one for a long time period. Even though now this E-WOM got a new evolution through social media. Before this new concept, general people were able to speak with any people on the internet. But likely social media enable people to talk with colleagues, friends and other people on the internet. Meanwhile, this new path way of E-WOM might be more powerful in terms of confusing purchase intention. And negative side of E-WOM very important in this competitive era. So, this study elaborates the negative E-WOM within the context of social media such as face book. And especially this study identifies the influence of negative E-WOM in social media on consumer’s purchase intention. Virtual snowball sampling method was used by researcher to identify the hidden population. Finally, spss 20.0 also used for data analysis purpose. And conclusion and recommendations are given based on the findings. And this research also will support to both parties such as researcher and participants.

Keywords: word of mouth, social media, purchase intention, electronic word of mouth

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

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This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

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Authors: Gholamreza Madad

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The role of medical equipment in modern advanced hospitals is irrefutable. Despite limited financial resources, developing countries have taken an uncontrollable manner to the purchase of complex and expensive equipment, although they have not taken good maintenance to keep these huge capitals. In our country, limited studies have indicated that the irregularities exist in the management of medical equipment maintenance. Research method: The research was done as a cross-sectional one, and in this study, a questionnaire was used to collect data in 10 hospitals. After distributing and collecting questionnaires in person, the collected data were analyzed using descriptive statistics and SPSS software. Research findings: According to the obtained results from the four dimensions of the management of medical equipment maintenance, only (maintenance planning) was in a moderate position and other components with a score of less than 50% were at a low level. There was a direct relationship between the total score of maintenance management and guidance points and coordination of medical equipment maintenance, and as well as the age of hospital managers. Discussion and conclusion: In sum, we can say that problems such as lack of skilled staff in medical engineering departments of hospitals, lack of funds and unaware of the authorities of medical engineering units to their duties have caused that the maintenance situation of medical equipment maintenance is in poor condition (near average). The low inexperience of the authorities of the unit has also contributed to this problem.

Keywords: equipment, maintenance, medical equipment, hospitals

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Authors: Jose Ramon Sanabria Navarro, Yahilina Silveira Perez, Valentin Molina Moreno, Digna Dionisia Perez Bravo

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The general objective of this research is to conceive a model of strategic direction for Latin American high-performance sports centers for the improvement of their results. The sample is 62 managers, 187 trainers, 2930 athletes and 62 expert researchers from centers in Cuba, Venezuela, Ecuador, Colombia and Argentina, for 3241. The measurement instrument includes 12 key variables in the process of management strategies which are consolidated with the factorial analysis and the ANOVA of a factor through the SPSS 24.0. The reliability of the scale obtained an alpha higher than 0.7 in each sample. In this sense, a model is obtained that taxes the deficiencies detected in the diagnosis, based on the needs of the members of these organizations, considering criteria and theories of the strategic direction in the improvement of the organizational results. The validation of the model for high performance sports centers of the countries analyzed aims to develop joint strategies to generate synergies in their operational mode, which leads to enhance the sports organization.

Keywords: sports organization, information management, decision making, control

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Authors: Mohammed Bala Banki

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This paper examines the relationship between employee satisfaction, customer satisfaction and loyalty in fast food restaurants in Nigeria and ascertains if prior job experience of employees before their present job moderate the relationship between customer satisfaction and loyalty. Data for this study were collected from matched pairs of employees and customers of fast restaurants in four Nigerian cities. A Structural Equation Modelling (SEM) was used for the analysis to test the proposed relationships and hierarchical multiple regression was performed in SPSS 22 to test moderating effect. Findings suggest that there is a direct positive and significant relationship between employee satisfaction and customer satisfaction and customer satisfaction and loyalty while the path between employee satisfaction and customer loyalty is insignificant. Results also reveal that employee’s prior job experience significantly moderate the relationship between customer satisfaction and loyalty. Further analysis indicates that employees with more years of experience provide more fulfilling services to restaurants customers. This paper provides some theoretical and managerial implications for academia and practitioners.

Keywords: employee’s satisfaction, customer’s satisfaction, loyalty, employee’s prior job experience, fast food industry

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Authors: Seungho Shin, Keunwoo Choi, Ali Akbar, Sukkee Um

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In this study, the nanoscale transport properties and catalyst utilization of vertically aligned carbon nanotube (VACNT) catalyst layers are computationally predicted by the three-dimensional lattice Boltzmann simulation based on the quasi-random nanostructural model in pursuance of fuel cell catalyst performance improvement. A series of catalyst layers are randomly generated with statistical significance at the 95% confidence level to reflect the heterogeneity of the catalyst layer nanostructures. The nanoscale gas transport phenomena inside the catalyst layers are simulated by the D3Q19 (i.e., three-dimensional, 19 velocities) lattice Boltzmann method, and the corresponding mass transport characteristics are mathematically modeled in terms of structural properties. Considering the nanoscale reactant transport phenomena, a transport-based effective catalyst utilization factor is defined and statistically analyzed to determine the structure-transport influence on catalyst utilization. The tortuosity of the reactant mass transport path of VACNT catalyst layers is directly calculated from the streaklines. Subsequently, the corresponding effective mass diffusion coefficient is statistically predicted by applying the pre-estimated tortuosity factors to the Knudsen diffusion coefficient in the VACNT catalyst layers. The statistical estimation results clearly indicate that the morphological structures of VACNT catalyst layers reduce the tortuosity of reactant mass transport path when compared to conventional catalyst layer and significantly improve consequential effective mass diffusion coefficient of VACNT catalyst layer. Furthermore, catalyst utilization of the VACNT catalyst layer is substantially improved by enhanced mass diffusion and electric current paths despite the relatively poor interconnections of the ion transport paths.

Keywords: Lattice Boltzmann method, nano transport phenomena, polymer electrolyte fuel cells, vertically aligned carbon nanotube

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Authors: K. Sekulová, M. Šimon

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The article demonstrates on a case study how it is possible to identify MSD risk. It is based on a dissertation risk identification model of occupational diseases formation in relation to the work activity that determines what risk can endanger workers who are exposed to the specific risk factors. It is evaluated based on statistical calculations. These risk factors are main cause of upper-extremities musculoskeletal disorders.

Keywords: case study, upper-extremity musculoskeletal disorders, ergonomics, risk identification

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Authors: Olga Sukhoveeva

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Carbon dioxide (CO2) is the main component of carbon biogeochemical cycle and one of the most important greenhouse gases (GHG). Agriculture, particularly arable soils, are one the largest sources of GHG emission for the atmosphere including CO2.Models may be used for estimation of GHG emission from agriculture if they can be adapted for different countries conditions. The only model used in officially at national level in United Kingdom and China for this purpose is DNDC (DeNitrification-DeComposition). In our research, the model DNDC is offered for estimation of GHG emission from arable soils in Russia. The aim of our research was to create the method of DNDC using for evaluation of CO2 emission in Russia based on official statistical information. The target territory was European part of Russia where many field experiments are located. At the first step of research the database on climate, soil and cropping characteristics for the target region from governmental, statistical, and literature sources were created. All-Russia Research Institute of Hydrometeorological Information – World Data Centre provides open daily data about average meteorological and climatic conditions. It must be calculated spatial average values of maximum and minimum air temperature and precipitation over the region. Spatial average values of soil characteristics (soil texture, bulk density, pH, soil organic carbon content) can be determined on the base of Union state register of soil recourses of Russia. Cropping technologies are published by agricultural research institutes and departments. We offer to define cropping system parameters (annual information about crop yields, amount and types of fertilizers and manure) on the base of the Federal State Statistics Service data. Content of carbon in plant biomass may be calculated via formulas developed and published by Ministry of Natural Resources and Environment of the Russian Federation. At the second step CO2 emission from soil in this region were calculated by DNDC. Modelling data were compared with empirical and literature data and good results were obtained, modelled values were equivalent to the measured ones. It was revealed that the DNDC model may be used to evaluate and forecast the CO2 emission from arable soils in Russia based on the official statistical information. Also, it can be used for creation of the program for decreasing GHG emission from arable soils to the atmosphere. Financial Support: fundamental scientific researching theme 0148-2014-0005 No 01201352499 ‘Solution of fundamental problems of analysis and forecast of Earth climatic system condition’ for 2014-2020; fundamental research program of Presidium of RAS No 51 ‘Climate change: causes, risks, consequences, problems of adaptation and regulation’ for 2018-2020.

Keywords: arable soils, carbon dioxide emission, DNDC model, European Russia

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Authors: Musa D. Aliyu, Ouahid Harireche, Colin D. Hills

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The incapability of supercritical C02 to transport and dissolve mineral species from the geothermal reservoir to the fracture apertures and other important parameters in heat mining makes it an attractive substance for Heat extraction from hot dry rock. In other words, the thermodynamic efficiency of hot dry rock (HDR) reservoirs also increases if supercritical C02 is circulated at excess temperatures of 3740C without the drawbacks connected with silica dissolution. Studies have shown that circulation of supercritical C02 in homogenous geothermal reservoirs is quite encouraging; in comparison to that of the water. This paper aims at investigating the aforementioned processes in the case of the heterogeneous geothermal reservoir located at the Soultz site (France). The MultiPhysics finite element package COMSOL with an interface of coupling different processes encountered in the geothermal reservoir stimulation is used. A fully coupled numerical model is developed to study the thermal and hydraulic processes in order to predict the long-term operation of the basic reservoir parameters that give optimum energy production. The results reveal that the temperature of the SCC02 at the production outlet is higher than that of water in long-term stimulation; as the temperature is an essential ingredient in rating the energy production. It is also observed that the mass flow rate of the SCC02 is far more favourable compared to that of water.

Keywords: FEM, HDR, heterogeneous reservoir, stimulation, supercritical C02

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Authors: Ana Paula Soares, Alexandrina Lages, Helena Oliveira, Francisco-Javier Gutiérrez-Domínguez, Marisa Lousada

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From an early age, exposure to a spoken language allows us to implicitly capture the structure underlying the succession of the speech sounds in that language and to segment it into meaningful units (words). Statistical learning (SL), i.e., the ability to pick up patterns in the sensory environment even without intention or consciousness of doing it, is thus assumed to play a central role in the acquisition of the rule-governed aspects of language and possibly to lie behind the language difficulties exhibited by children with development language disorder (DLD). The research conducted so far has, however, led to inconsistent results, which might stem from the behavioral tasks used to test SL. In a classic SL experiment, participants are first exposed to a continuous stream (e.g., syllables) in which, unbeknownst to the participants, stimuli are grouped into triplets that always appear together in the stream (e.g., ‘tokibu’, ‘tipolu’), with no pauses between each other (e.g., ‘tokibutipolugopilatokibu’) and without any information regarding the task or the stimuli. Following exposure, SL is assessed by asking participants to discriminate between triplets previously presented (‘tokibu’) from new sequences never presented together during exposure (‘kipopi’), i.e., to perform a two-alternative-forced-choice (2-AFC) task. Despite the widespread use of the 2-AFC to test SL, it has come under increasing criticism as it is an offline post-learning task that only assesses the result of the learning that had occurred during the previous exposure phase and that might be affected by other factors beyond the computation of regularities embedded in the input, typically the likelihood two syllables occurring together, a statistic known as transitional probability (TP). One solution to overcome these limitations is to assess SL as exposure to the stream unfolds using online techniques such as event-related potentials (ERP) that is highly sensitive to the time-course of the learning in the brain. Here we collected ERPs to examine the neurofunctional correlates of SL in preschool children with DLD, and chronological-age typical language development (TLD) controls who were exposed to an auditory stream in which eight three-syllable nonsense words, four of which presenting high-TPs and the other four low-TPs, to further analyze whether the ability of DLD and TLD children to extract-word-like units from the steam was modulated by words’ predictability. Moreover, to ascertain if the previous knowledge of the to-be-learned-regularities affected the neural responses to high- and low-TP words, children performed the auditory SL task, firstly, under implicit, and, subsequently, under explicit conditions. Although behavioral evidence of SL was not obtained in either group, the neural responses elicited during the exposure phases of the SL tasks differentiated children with DLD from children with TLD. Specifically, the results indicated that only children from the TDL group showed neural evidence of SL, particularly in the SL task performed under explicit conditions, firstly, for the low-TP, and, subsequently, for the high-TP ‘words’. Taken together, these findings support the view that children with DLD showed deficits in the extraction of the regularities embedded in the auditory input which might underlie the language difficulties.

Keywords: development language disorder, statistical learning, transitional probabilities, word segmentation

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Authors: Tolga Gok, Kursad Sayin

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The aim of this study is to investigate the relationship between expectation, satisfaction and loyalty of South Korean tourists visiting Turkey. In the research, a questionnaire was used as a data collecting tool. The questionnaires are filled by South Korean tourists coming to Turkey through package tours and individual. The survey was conducted in 2014 in Nevsehir (Cappadocia Region) and Istanbul. Tourist guides and agency staff have helped the implementation of surveys. The survey questions are composed of 4 parts, which are “demographic characteristics of tourists”, “travel behavior characteristics”, “perception of expectations on destination attributes” and “perception of destination loyalty”. 5-point Likert type scale including 28 destination attributes was used to measure the expectations of South Korean tourists coming to Turkey. Questions were directed to the tourists to measure the destination loyalty. The questions relating to destination loyalty are “Talking about Turkey to others”, “Recommendation Turkey to others” and “Tourists’ intentions to revisit Turkey”. The basic hypothesis of the research is that there is a statistically significant relationship among expectations, satisfactions and destination loyalty of South Korean tourists coming to Turkey. The results indicated that the expectation had a significant effect on overall satisfaction. In addition, it was seen that between overall satisfaction of tourists and destination loyalty had a significant relationship. Based on findings, some suggestions for tour operators and travel agencies were made.

Keywords: tourist expectation, tourist satisfaction, destination loyalty, destination attributes

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Authors: Songul Cinaroglu

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Background: Random Forest is an efficient, multi-class machine learning method using for classification, regression and other tasks. This method is operating by constructing each tree using different bootstrap sample of the data. Determining the number of trees in random forests is an open question in the literature for studies about improving classification performance of random forests. Aim: The aim of this study is to analyze whether there is an optimal number of trees in Random Forests and how performance of Random Forests differ according to increase in number of trees using sample health data sets in R programme. Method: In this study we analyzed the performance of Random Forests as the number of trees grows and doubling the number of trees at every iteration using “random forest” package in R programme. For determining minimum and optimal number of trees we performed Mc Nemar test and Area Under ROC Curve respectively. Results: At the end of the analysis it was found that as the number of trees grows, it does not always means that the performance of the forest is better than forests which have fever trees. In other words larger number of trees only increases computational costs but not increases performance results. Conclusion: Despite general practice in using random forests is to generate large number of trees for having high performance results, this study shows that increasing number of trees doesn’t always improves performance. Future studies can compare different kinds of data sets and different performance measures to test whether Random Forest performance results change as number of trees increase or not.

Keywords: classification methods, decision trees, number of trees, random forest

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Authors: May M. Youssef

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This article introduces a design, for additive manufacturing technology, face shield as Personal Protective Equipment from the respiratory viruses such as coronavirus 2. The face shields help to reduce ocular exposure and play a vital role in diverting away from the respiratory COVID-19 air droplets around the users' face. The proposed face shield comprises three assembled polymer parts. The frame with a transparency overhead projector sheet visor is suitable for frontline health care workers and ordinary citizens. The frame design allows tightening the shield around the user’s head and permits rubber elastic straps to be used if required. That ergonomically designed with a unique face mask support used in case of wearing extra protective mask was created using computer aided design (CAD) software package. The finite element analysis (FEA) structural verification of the proposed design is performed by an advanced simulation technique. Subsequently, the prototype model was fabricated by a 3D printing using Fused Deposition Modeling (FDM) as a globally developed face shield product. This study provides a different face shield designs for global production, which showed to be suitable and effective toward supply chain shortages and frequent needs of personal protective goods during coronavirus disease and similar viruses.

Keywords: additive manufacturing, Coronavirus-19, face shield, personal protective equipment, 3D printing

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Authors: Sarah Elmammeri

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This paper will represent the postcolonial every day in the journey of asylum seekers through the asylum process in the UK. It represents everyday borders, which are defined as everyday barriers, and obstacles facing asylum seekers and refugees in the host country. These everyday barriers can be legal, financial, social and educational under the umbrella of the racialized administrative border creating a package. The arguments build on a set of 21 semi-structured interviews in English and Arabic. The interviews were conducted in the UK, online via zoom lasting between 25 minutes and 2 hours with asylum seekers, refugees, Non-governmental organisations workers and volunteers. The interviews focus on the meaning of borders both physical and metaphorical and ways to challenge the ongoing postcolonial everyday border practices. The findings conclude that these barriers are there deliberately and intentionally to target asylum seekers and limit their legal right to claim asylum in a form of policy and regulations. People in the asylum process, NGO workers, and refugees relate to this aspect of the everyday borders. Second, these barriers come intertwined together creating a structure that interferes with the daily life of an asylum seeker and later affects people with refugee status creating racialised barriers starting with the structural and official form of it: the asylum process. These structural barriers will be linked forming a multi-level barrier enhancing the racialisation of people who are categorised and selected.

Keywords: everyday borders, asylum policies, inclusion and exclusion, refugees and asylum seekers

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Authors: Ali M. Al-Shaery

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The purpose of this paper is to address the functions of sustainability dimensions in city information modelling and to present the required sustainability criteria that support establishing a sustainable planning framework for enhancing existing cities and developing future smart cities. The paper is divided into two sections. The first section is based on the examination of a wide and extensive array of cross-disciplinary literature in the last decade and a half to conceptualize the terms ‘sustainable’ and ‘smart city,' and map their associated criteria to city information modelling. The second section is based on analyzing two approaches relating to city information modelling, namely statistical and dynamic approaches, and their suitability in the development of cities’ action plans. The paper argues that the use of statistical approaches to embedding sustainability dimensions in city information modelling have limited value. Despite the popularity of such approaches in addressing other dimensions like utility and service management in development and action plans of the world cities, these approaches are unable to address the dynamics across various city sectors with regards to economic, environmental and social criteria. The paper suggests an integrative dynamic and cross-disciplinary planning approach to embedding sustainability dimensions in city information modelling frameworks. Such an approach will pave the way towards optimal planning and implementation of priority actions of projects and investments. The approach can be used to achieve three main goals: (1) better development and action plans for world cities (2) serve the development of an integrative dynamic and cross-disciplinary framework that incorporates economic, environmental and social sustainability criteria and (3) address areas that require further attention in the development of future sustainable and smart cities. The paper presents an innovative approach for city information modelling and a well-argued, balanced hierarchy of sustainability criteria that can contribute to an area of research which is still in its infancy in terms of development and management.

Keywords: information modelling, smart city, sustainable city, sustainability dimensions, sustainability criteria, city development planning

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Authors: Haruna Daddau

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This study investigates the effect of sustainable supply chain management (SSCM) on the performance of agricultural firms in Nigeria. Green packaging, product design, waste reduction and supply chain design were examined. The ecological modernization theory, which suggests the economic benefit of the environment, was used to underpin the study. The research is quantitative in nature, and a survey research method was adopted where information was obtained using questionnaires distributed directly to the top managers of 6 agricultural firms in Nigeria. STATA and SPSS were used for the data analysis, and regression analysis was used to examine the effects. Findings showed that SSCM positively improves the performance of the firms. Also, detailed information about the study’s selected variables' effect on performance was provided. Additionally, the significant role of SSCM in accelerating the firms’ performance was highlighted. It is recommended that SSCM should be given serious attention by integrating it into the overall firm's business strategy.

Keywords: sustainable supply chain management, green packaging, product design, waste reduction, supply chain design and performance

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Authors: Leo Carlo B. Rondina

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Self-image is an important factor to improve the self-esteem of the personnel. The purpose of the study is to determine the self-image of the police. The respondents were the 503 policemen assigned in different Police Station in Davao City, and they were chosen with the used of random sampling. With the used of Exploratory Factor Analysis (EFA), latent construct variables of police image were identified as follows; professionalism, obedience, morality and justice and fairness. Further, ordinal regression indicates statistical characteristics on ages 21-40 which means the age of the respondent statistically improves self-image.

Keywords: police image, exploratory factor analysis, ordinal regression, Galatea effect

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Authors: Saira Soroya, Khalid Mahmood

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Library catalogs open the door to the library collection. OPAC (Online Public Access Catalog) are one of the services offered by automated libraries. The present study aims to explore user’s awareness, the level of use and their searching behavior of OPAC with a purpose to give suggestions and ways to improve user-friendly features of library OPAC. The population consisted of OPAC users of Lahore University of Management Sciences (LUMS). Convenient sampling technique was carried out. Total sample size was 100 OPAC users. Quantitative research design, based on survey method used to carry out the study. The data collection instrument was adopted. Data was analyzed using SPSS. Results revealed that a considerable number of users were not aware of OPAC i.e. (30%); however, those who were aware were using basic features of the OPAC. It was found that lack of knowledge was considered the frequent reason for not using all features of OPAC. In this regard, it is strongly recommended that compulsory information literacy programme should be established.

Keywords: catalog, OPAC, library automation, usability study, university library

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Authors: Pebri Nurhayati, Rozanah Ahlam Fadiyah

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In the development of the city often use rural areas that can not be separated from the change in land use that lead to the degradation of urban green space in the city fringe. In the long run, the degradation of green open space this can impact on the decline of ecological, psychological and public health. Therefore, this research aims to (1) determine the relationship between the parameters of the degradation rate of urban development with green space, (2) develop a spatial model of the impact of urban development on the degradation of green open space with remote sensing techniques and Geographical Information Systems in an integrated manner. This research is a descriptive research with data collection techniques of observation and secondary data . In the data analysis, to interpret the direction of urban development and degradation of green open space is required in 2005-2010 ASTER image with NDVI. Of interpretation will generate two maps, namely maps and map development built land degradation green open space. Secondary data related to the rate of population growth, the level of accessibility, and the main activities of each city map is processed into a population growth rate, the level of accessibility maps, and map the main activities of the town. Each map is used as a parameter to map the degradation of green space and analyzed by non-parametric statistical analysis using Crosstab thus obtained value of C (coefficient contingency). C values were then compared with the Cmaximum to determine the relationship. From this research will be obtained in the form of modeling spatial map of the City Development Impact Degradation Green Space in Urban Fringe eastern city of Yogyakarta 2005-2010. In addition, this research also generate statistical analysis of the test results of each parameter to the degradation of green open space in the Urban Fringe eastern city of Yogyakarta 2005-2010.

Keywords: spatial analysis, urban development, degradation of green space, urban fringe

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Authors: Pankhuri Dagaonkar, Charumani Singh, Poornima Krothapalli, Krishna Karthik

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The backbone of any retail e-commerce success story is a unique design of supply chain network, providing the business an unparalleled speed and scalability. Primary goal of the supply chain strategy is to meet customer expectation by offering fastest deliveries while keeping the cost minimal. Meeting this objective at the large market that India provides is the problem statement that we have targeted here. There are many models and optimization techniques focused on network design to identify the ideal facility location and size, optimizing cost and speed. In this paper we are presenting a tactical approach to optimize cost of an existing network for a predefined speed. We have considered both forward and reverse logistics of a retail e-commerce supply chain consisting of multiple fulfillment (warehouse) and delivery centers, which are connected via sortation nodes. The mathematical model presented here determines if the shipment from a node should get sorted directly for the last mile delivery center or it should travel as consolidated package to another node for further sortation (resort). The objective function minimizes the total cost by varying the resort percentages between nodes and provides the optimal resource allocation and number of sorts at each node.

Keywords: distribution strategy, mathematical model, network design, supply chain management

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Authors: Gulnaz Erkomaishvili

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Introduction. One of the most important issues of state economic policy in the 21st century is the problem of environmental protection. The Georgian government considers the green economy as one of the most important means of sustainable economic development and takes the initiative to implement voluntary measures to promote sustainable development. In this context, it is important to promote the development of ecosystem services, clean production, environmental education and green jobs.The development of the green economy significantly reduces the inefficient use of natural resources, waste generation, emissions into the atmosphere and the discharge of untreated water into bodies of water.It is, therefore, an important instrument in the environmental orientation of sustainable development. Objectives.The aim of the paper is to analyze the current status of the green economy in Georgia and identify effective ways to improve the environmental, economic policy of sustainable development. Methodologies: This paper uses general and specific methods, in particular, analysis, synthesis, induction, deduction, scientific abstraction, comparative and statistical methods, as well as experts’ evaluation. bibliographic research of scientific works and reports of organizations was conducted; Publications of the National Statistics Office of Georgia are used to determine the regularity between analytical and statistical estimations. Also, theoretical and applied research of international organizations and scientist-economists are used. Contributions: The country should implement such an economic policy that ensures the transition to a green economy, in particular, revising water, air and waste laws, strengthening existing environmental management tools and introcing new tools (including economic tools). Perfecting the regulatory legal framework of the environmental impact assessment system, which includes the harmonization of Georgian legislation with the requirements of the European Union. To ensure the protection and rational use of Georgia's forests, emphasis should be placed on sustainable forestry, protection and restoration of forests.

Keywords: green economy, environmental protection, environmental protection economic policy, environmental protection policy challanges

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Authors: Mona Hajirasouli

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Abstract: introduction: Antimicrobial compounds are important in the first line of the host defense system of many animal species. Material and methods: In the present study antibacterial activity of crude and proteins precipitate of hemolymph and crude hepatopancreas extracts from Portunus segnis and Grapsus albolineatus against a range of 6 different bacterial strains evaluated. Amoxicillin as a positive control were also used. Results: Maximum activity (15.9 mm) was recorded in male haemolymph of p.segnis against Entrobacter and minimum activity (7 mm) was recorded against Serratia marcescens, Enterobacter sp. and Proteus mirabilis from different extracts of Grapsus albolineatus. Data were analyzed using independent-t in SPSS version 16, and results indicate that there were not any significant differences between hemolymph and hepatopancreas extracts of 2 species. Discussion: Antimicrobial activity has been reported earlier in the hemolymph of some brachyuran crabs such as: blue crab Callinectes sapidus, mud crab Scylla serrata, Ocypode macrocera and Carcinus maenas. This study shows that hemolymph and hepatopancreas of Portunus segnis and Grapsus albolineatus may potential antibiotics.

Keywords: brachyuran, Portunus segnis, Grapsus albolineatus, hemolymph, hepatopancreas, antibacterial

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Authors: Apoorva Bamal, Agnieszka Indiana Olbert

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Floods are known to be one of the most devastating hydro-climatic events, impacting a wide range of stakeholders in terms of environmental, social and economic losses. With difference in inundation durations and level of impact, flood hazards are of different degrees and strength. Amongst various set of domains being impacted by floods, environmental degradation in terms of water quality deterioration is one of the majorly effected but less highlighted domains across the world. The degraded water quality is caused by numerous natural and anthropogenic factors that are both point and non-point sources of pollution. Therefore, it is essential to understand the nature and source of the water pollution due to flooding. The major impact of floods is not only on the physico-chemical water quality parameters, but also on the biological elements leading to a vivid influence on the aquatic ecosystem. This deteriorated water quality is impacting many water categories viz. agriculture, drinking water, aquatic habitat, and miscellaneous services requiring an appropriate water quality to survive. This study identifies, reviews, evaluates and assesses multiple researches done across the world to determine the impact of floods on water quality. With a detailed statistical analysis of top relevant researches, this study is a synopsis of the methods used in assessment of impact of floods on water quality in different geographies, and identifying the gaps for further abridgement. As per majority of the studies, different flood magnitudes have varied impact on the water quality parameters leading to either increased or decreased values as compared to the recommended values for various categories. There is also an evident shift of the biological elements in the impacted waters leading to a change in its phenology and inhabitants of the specified water body. This physical, chemical and biological water quality degradation by floods is dependent upon its duration, extent, magnitude and flow direction. Therefore, this research provides an overview into the multiple impacts of floods on water quality, along with a roadmap of way forward to an efficient and uniform linkage of floods and impacted water quality dynamics.

Keywords: floods, statistical analysis, water pollution, water quality

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Authors: Xiaoqin Wang, Li Yin

Abstract:

Background and purpose: In many practices, one estimates causal effects arising from a complex stochastic process, where a sequence of treatments are assigned to influence a certain outcome of interest, and there exist time-dependent covariates between treatments. When covariates are plentiful and/or continuous, statistical modeling is needed to reduce the huge dimensionality of the problem and allow for the estimation of causal effects. Recently, Wang and Yin (Annals of statistics, 2020) derived a new general formula, which expresses these causal effects in terms of the point effects of treatments in single-point causal inference. As a result, it is possible to conduct the modeling via point effects. The purpose of the work is to study the modeling of these causal effects via point effects. Challenges and solutions: The time-dependent covariates often have influences from earlier treatments as well as on subsequent treatments. Consequently, the standard parameters – i.e., the mean of the outcome given all treatments and covariates-- are essentially all different (null paradox). Furthermore, the dimension of the parameters is huge (curse of dimensionality). Therefore, it can be difficult to conduct the modeling in terms of standard parameters. Instead of standard parameters, we have use point effects of treatments to develop likelihood-based parametric approach to the modeling of these causal effects and are able to model the causal effects of a sequence of treatments by modeling a small number of point effects of individual treatment Achievements: We are able to conduct the modeling of the causal effects from a sequence of treatments in the familiar framework of single-point causal inference. The simulation shows that our method achieves not only an unbiased estimate for the causal effect but also the nominal level of type I error and a low level of type II error for the hypothesis testing. We have applied this method to a longitudinal study of COVID-19 mortality among Scandinavian countries and found that the Swedish approach performed far worse than the other countries' approach for COVID-19 mortality and the poor performance was largely due to its early measure during the initial period of the pandemic.

Keywords: causal effect, point effect, statistical modelling, sequential causal inference

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