Search results for: machine learning techniques

Authors: Alemayehu Agizew Woldeamanuel, Mekonnen Maschal Tarekegn, Raj Mohan Balakrishina

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Composting is one of the conventional techniques adopted for organic waste management but the practice is very limited in emerging cities despite that most of the waste generated is organic. This paper aims to examine the viability of composting for organic waste management in the emerging city of Addis Ababa, Ethiopia by addressing the composting practice, quality of compost and application of compost in urban agriculture. The study collects data using compost laboratory testing and urban farm households’ survey and uses descriptive analysis on the state of compost production and application, physicochemical analysis of the compost samples, and regression analysis on the urban farmer’s willingness to pay for compost. The findings of the study indicated that there is composting practice at a small scale, most of the producers use unsorted feedstock materials, aerobic composting is dominantly used and the maturation period ranged from four to 10 weeks. The carbon content of the compost ranges from 30.8 to 277.1 due to the type of feedstock applied and this surpasses the ideal proportions for C:N ratio. The total nitrogen, pH, organic matter and moisture content are relatively optimal. The levels of heavy metals measured for Mn, Cu, Pb, Cd and Cr6+ in the compost samples are also insignificant. In the urban agriculture sector, chemical fertilizer is the dominant type of soil input in crop productions but vegetable producers use a combination of both fertilizer and other organic inputs including compost. The willingness to pay for compost depends on income, household size, gender, type of soil inputs, monitoring soil fertility, the main product of the farm, farming method and farm ownership. Finally, this study recommends the need for collaboration among stakeholders along the value chain of waste, awareness creation on the benefits of composting and addressing challenges faced by both compost producers and users.

Keywords: Composting, emerging city, organic waste management, urban agriculture.

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Authors: Ákos Wolf, Richard P. Ray

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Due to the introduction of Eurocode 8, the structural design for seismic and dynamic effects has become more significant in Hungary. This has emphasized the need for more effort to describe the behavior of structures under these conditions. Soil conditions have a significant effect on the response of structures by modifying the stiffness and damping of the soil-structural system and by modifying the seismic action as it reaches the ground surface. Shear modulus (G) and shear wave velocity (v_s), which are often measured in the field, are the fundamental dynamic soil properties for foundation vibration problems, liquefaction potential and earthquake site response analysis. There are several laboratory and in-situ measurement techniques to evaluate dynamic soil properties, but unfortunately, they are often too expensive for general design practice. However, a significant number of correlations have been proposed to determine shear wave velocity or shear modulus from Cone Penetration Tests (CPT), which are used more and more in geotechnical design practice in Hungary. This allows the designer to analyze and compare CPT and seismic test result in order to select the best correlation equations for Hungarian soils and to improve the recommendations for the Hungarian geologic conditions. Based on a literature review, as well as research experience in Hungary, the influence of various parameters on the accuracy of results will be shown. This study can serve as a basis for selecting and modifying correlation equations for Hungarian soils. Test data are taken from seven locations in Hungary with similar geologic conditions. The shear wave velocity values were measured by seismic CPT. Several factors are analyzed including soil type, behavior index, measurement depth, geologic age etc. for their effect on the accuracy of predictions. The final results show an improved prediction method for Hungarian soils

Keywords: CPT correlation, dynamic soil properties, seismic CPT, shear wave velocity.

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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The automatic extraction of shipping routes is advantageous for intelligent traffic management systems to identify events and support decision-making in maritime surveillance. At present, there is a high demand for the extraction of maritime traffic networks that resemble the real traffic of vessels accurately, which is valuable for further analytical processing tasks for vessels trajectories (e.g., naval routing and voyage planning, anomaly detection, destination prediction, time of arrival estimation). With the help of big data and processing huge amounts of vessels’ trajectory data, it is possible to learn these shipping routes from the navigation history of past behaviour of other, similar ships that were travelling in a given area. In this paper, we propose a spatial clustering model of vessels’ trajectories (SPTCLUST) to extract spatial representations of sailing routes from historical Automatic Identification System (AIS) data. The whole model consists of three main parts: data preprocessing, path finding, and route extraction, which consists of clustering and representative trajectory extraction. The proposed clustering method provides techniques to overcome the problems of: (i) optimal input parameters selection; (ii) the high complexity of processing a huge volume of multidimensional data; (iii) and the spatial representation of complete representative trajectory detection in the context of trajectory clustering algorithms. The experimental evaluation showed the effectiveness of the proposed model by using a real-world AIS dataset from the Port of Halifax. The results contribute to further understanding of shipping route patterns. This could aid surveillance authorities in stable and sustainable vessel traffic management.

Keywords: Vessel trajectory clustering, trajectory mining, Spatial Clustering, marine intelligent navigation, maritime traffic network extraction, sdailing routes extraction.

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Authors: Mahsa Tavakoli, Seyed Mohammad Hojjati, Yahya Kooch

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In this study, the effect of coal mining activities on lead and cadmium concentrations and distribution in soil was investigated in Hyrcanian forest, North Iran. 16 plots (20×20 m²) were established by systematic-randomly (60×60 m²) in an area of 4 ha (200×200 m²-mine entrance placed at center). An area adjacent to the mine was not affected by the mining activity; considered as the controlled area. In order to investigate soil lead and cadmium concentration, one sample was taken from the 0-10 cm in each plot. To study the spatial pattern of soil properties and lead and cadmium concentrations in the mining area, an area of 80×80m² (the mine as the center) was considered and 80 soil samples were systematic-randomly taken (10 m intervals). Geostatistical analysis was performed via Kriging method and GS⁺ software (version 5.1). In order to estimate the impact of coal mining activities on soil quality, pollution index was measured. Lead and cadmium concentrations were significantly higher in mine area (Pb: 10.97±0.30, Cd: 184.47±6.26 mg.kg^-1) in comparison to control area (Pb: 9.42±0.17, Cd: 131.71±15.77 mg.kg^-1). The mean values of the PI index indicate that Pb (1.16) and Cd (1.77) presented slightly polluted. Results of the NIPI index showed that Pb (1.44) and Cd (2.52) presented slight pollution and moderate pollution respectively. Results of variography and kriging method showed that it is possible to prepare interpolation maps of lead and cadmium around the mining areas in Hyrcanian forest. According to results of pollution and risk assessments, forest soil was contaminated by heavy metals (lead and cadmium); therefore, using reclamation and remediation techniques in these areas is necessary.

Keywords: Traditional coal mining, heavy metals, pollution indicators, geostatistics, caspian forest.

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Authors: Chi-Fang Huang, Yun-Shiow Chen, Yun-Kung Chung

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In the past decade, artificial neural networks (ANNs) have been regarded as an instrument for problem-solving and decision-making; indeed, they have already done with a substantial efficiency and effectiveness improvement in industries and businesses. In this paper, the Back-Propagation neural Networks (BPNs) will be modulated to demonstrate the performance of the collaborative forecasting (CF) function of a Collaborative Planning, Forecasting and Replenishment (CPFR®) system. CPFR functions the balance between the sufficient product supply and the necessary customer demand in a Supply and Demand Chain (SDC). Several classical standard BPN will be grouped, collaborated and exploited for the easy implementation of the proposed modular ANN framework based on the topology of a SDC. Each individual BPN is applied as a modular tool to perform the task of forecasting SKUs (Stock-Keeping Units) levels that are managed and supervised at a POS (point of sale), a wholesaler, and a manufacturer in an SDC. The proposed modular BPN-based CF system will be exemplified and experimentally verified using lots of datasets of the simulated SDC. The experimental results showed that a complex CF problem can be divided into a group of simpler sub-problems based on the single independent trading partners distributed over SDC, and its SKU forecasting accuracy was satisfied when the system forecasted values compared to the original simulated SDC data. The primary task of implementing an autonomous CF involves the study of supervised ANN learning methodology which aims at making “knowledgeable" decision for the best SKU sales plan and stocks management.

Keywords: CPFR, artificial neural networks, global logistics, supply and demand chain.

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Authors: Jean-Jacques Randrianarimanana, Nassim Sebaibi, Mohamed Boutouil

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In order to solve problems associated with stormwater runoff in urban areas and their effects on natural and artificial water bodies, the integration of new technical solutions to the rainwater drainage becomes even more essential. Permeable pavement systems are one of the most widely used techniques. This paper presents a laboratory analysis of stormwater runoff hydraulic and pollutant removal performance of permeable pavement system using pervious pavements based on seashell products. The laboratory prototype is a square column of 25 cm of side and consists of the surface in pervious concrete, a bedding of 3 cm in height, a geotextile and a subbase layer of 50 cm in height. A series of constant simulated rain events using semi-synthetic runoff which varied in intensity and duration were carried out. The initial vertical saturated hydraulic conductivity of the entire pervious pavement system was 0.25 cm/s (148 L/m²/min). The hydraulic functioning was influenced by both the inlet flow rate value and the test duration. The total water losses including evaporation ranged between 9% to 20% for all hydraulic experiments. The temporal and vertical variability of the pollutant removal efficiency (PRE) of the system were studied for total suspended solids (TSS). The results showed that the PRE along the vertical profile was influenced by the size of the suspended solids, and the pervious paver has the highest capacity to trap pollutant than the other porous layers of the permeable pavement system after the geotextile. The TSS removal efficiency was about 80% for the entire system. The first-flush effect of TSS was observed, but it appeared only at the beginning (2 to 6 min) of the experiments. It has been shown that the PPS can capture first-flush. The project in which this study is integrated aims to contribute to both the valorization of shellfish waste and the sustainable management of rainwater.

Keywords: Hydraulic, pervious concrete, pollutant removal efficiency, seashell by-products, stormwater runoff.

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Authors: Gysele Lima Ricci, Jose Miguel Rodriguez Anton

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Companies in the tourism sector need to achieve competitive advantages for their survival in the market. In this way, the models based on association, cooperation, complementarity, distribution, exchange and mutual assistance arise as a possibility of organizational development, taking as reference the concept of networks. Many companies seek to partner in local networks as clusters to act together and associate. The main objective of the present research is to identify the specificities of management and the practices of cooperation in the tourist destination of São Paulo - Brazil, and to propose a new management model with possible cluster of tourism. The empirical analysis was carried out in three phases. As a first phase, a research was made by the companies, associations and tourism organizations existing in São Paulo, analyzing the characteristics of their business. In the second phase, the management specificities and cooperation practice used in the tourist destination. And in the third phase, identifying the possible strengths and weaknesses that potential or potential tourist cluster could have, proposing the development of the management model of the same adapted to the needs of the companies, associations and organizations. As a main result, it has been identified that companies, associations and organizations could be looking for synergies with each other and collaborate through a Hiperred organizational structure, in which they share their knowledge, try to make the most of the collaboration and to benefit from three concepts: flexibility, learning and collaboration. Finally, it is concluded that, the proposed tourism cluster management model is viable for the development of tourism destinations because it makes it possible to strategically address agents which are responsible for public policies, as well as public and private companies and organizations in their strategies competitiveness and cooperation.

Keywords: Cluster, management model, networks, tourism sector.

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Authors: Vijay Shankar

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Different techniques for estimating seasonal water use from soil profile water depletion frequently do not account for flux below the root zone. Shallow water table contribution to supply crop water use may be important in arid and semi-arid regions. Development of predictive root uptake models, under influence of shallow water table makes it possible for planners to incorporate interaction between water table and root zone into design of irrigation projects. A model for obtaining soil moisture depletion from root zone and water movement below it is discussed with the objective to determine impact of shallow water table on seasonal moisture depletion patterns under water table depth variation, up to the bottom of root zone. The role of different boundary conditions has also been considered. Three crops: Wheat (Triticum aestivum), Corn (Zea mays) and Potato (Solanum tuberosum), common in arid & semi-arid regions, are chosen for the study. Using experimentally obtained soil moisture depletion values for potential soil moisture conditions, moisture depletion patterns using a non linear root uptake model have been obtained for different water table depths. Comparative analysis of the moisture depletion patterns under these conditions show a wide difference in percent depletion from different layers of root zone particularly top and bottom layers with middle layers showing insignificant variation in moisture depletion values. Moisture depletion in top layer, when the water table rises to root zone increases by 19.7%, 22.9% & 28.2%, whereas decrease in bottom layer is 68.8%, 61.6% & 64.9% in case of wheat, corn & potato respectively. The paper also discusses the causes and consequences of increase in moisture depletion from top layers and exceptionally high reduction in bottom layer, and the possible remedies for the same. The numerical model developed for the study can be used to help formulating irrigation strategies for areas where shallow groundwater of questionable quality is an option for crop production.

Keywords: Moisture Depletion, crop root zone, ground water table, irrigation.

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Authors: Angelo Lerro, Manuela Battipede, Piero Gili, Alberto Brandl

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Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility.

Keywords: Neural network, aerodynamic angles, virtual sensor, unmanned aerial vehicle, air data system, flight test.

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Authors: Teresa Caswell

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Throughout the United States and within a myriad of demographic contexts, students of color experience the results of systemic inequities as an academic outcome. These disparities continue despite the increased resources provided to students and ongoing instruction-focused professional learning received by teachers. We postulated that lower levels of educator cultural competency are an underlying factor of why resource and instructional interventions are less effective than desired. Before implementing any type of intervention, however, cultural competency needed to be confirmed as a factor in schools demonstrating academic disparities between racial subgroups. A needs assessment was designed to measure levels of individual beliefs, including cultural competency, in both principals and teachers at three neighboring schools verified to have academic disparities. The resulting mixed method study utilized the Optimal Theory Applied to Identity Development (OTAID) model to measure cultural competency quantitatively, through self-identity inventory survey items, with teachers and qualitatively, through one-on-one interviews, with each school’s principal. A joint display was utilized to see combined data within and across school contexts. Each school was confirmed to have misalignments between principal and teacher levels of cultural competency beliefs while also indicating that a number of participants in the self-identity inventory survey may have intentionally skipped items referencing the term oppression. Additional use of the OTAID model and self-identity inventory in future research and across contexts is needed to determine transferability and dependability as cultural competency measures.

Keywords: Cultural competency, identity development, mixed method analysis, needs assessment.

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Authors: Mathias U. Bonet, Pericles Pilidis, Georgios Doulgeris

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A gas turbine-powered cruise Liner is scheduled to transport pilgrim passengers from Lagos-Nigeria to the Islamic port city of Jeddah in Saudi Arabia. Since the gas turbine is an air breathing machine, changes in the density and/or mass flow at the compressor inlet due to an encounter with variations in weather conditions induce negative effects on the performance of the power plant during the voyage. In practice, all deviations from the reference atmospheric conditions of 15 ^oC and 1.103 bar tend to affect the power output and other thermodynamic parameters of the gas turbine cycle. Therefore, this paper seeks to evaluate how a simple cycle marine gas turbine power plant would react under a variety of scenarios that may be encountered during a voyage as the ship sails across the Atlantic Ocean and the Mediterranean Sea before arriving at its designated port of discharge. It is also an assessment that focuses on the effect of varying aerodynamic and hydrodynamic conditions which deteriorate the efficient operation of the propulsion system due to an increase in resistance that results from some projected levels of the ship hull fouling. The investigated passenger ship is designed to run at a service speed of 22 knots and cover a distance of 5787 nautical miles. The performance evaluation consists of three separate voyages that cover a variety of weather conditions in winter, spring and summer seasons. Real-time daily temperatures and the sea states for the selected transit route were obtained and used to simulate the voyage under the aforementioned operating conditions. Changes in engine firing temperature, power output as well as the total fuel consumed per voyage including other performance variables were separately predicted under both calm and adverse weather conditions. The collated data were obtained online from the UK Meteorological Office as well as the UK Hydrographic Office websites, while adopting the Beaufort scale for determining the magnitude of sea waves resulting from rough weather situations. The simulation of the gas turbine performance and voyage analysis was effected through the use of an integrated Cranfield-University-developed computer code known as ‘Turbomatch’ and ‘Poseidon’. It is a project that is aimed at developing a method for predicting the off design behavior of the marine gas turbine when installed and operated as the main prime mover for both propulsion and powering of all other auxiliary services onboard a passenger cruise liner. Furthermore, it is a techno-economic and environmental assessment that seeks to enable the forecast of the marine gas turbine part and full load performance as it relates to the fuel requirement for a complete voyage.

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Authors: I GD Yudha Partama, A. Kanno, Y. Akamatsu, R. Inui, M. Goto, M. Sekine

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The aerial photogrammetry of shallow water bottoms has the potential to be an efficient high-resolution survey technique for shallow water topography, thanks to the advent of convenient UAV and automatic image processing techniques Structure-from-Motion (SfM) and Multi-View Stereo (MVS)). However, it suffers from the systematic overestimation of the bottom elevation, due to the light refraction at the air-water interface. In this study, we present an empirical method to correct for the effect of refraction after the usual SfM-MVS processing, using common software. The presented method utilizes the empirical relation between the measured true depth and the estimated apparent depth to generate an empirical correction factor. Furthermore, this correction factor was utilized to convert the apparent water depth into a refraction-corrected (real-scale) water depth. To examine its effectiveness, we applied the method to two river sites, and compared the RMS errors in the corrected bottom elevations with those obtained by three existing methods. The result shows that the presented method is more effective than the two existing methods: The method without applying correction factor and the method utilizes the refractive index of water (1.34) as correction factor. In comparison with the remaining existing method, which used the additive terms (offset) after calculating correction factor, the presented method performs well in Site 2 and worse in Site 1. However, we found this linear regression method to be unstable when the training data used for calibration are limited. It also suffers from a large negative bias in the correction factor when the apparent water depth estimated is affected by noise, according to our numerical experiment. Overall, the good accuracy of refraction correction method depends on various factors such as the locations, image acquisition, and GPS measurement conditions. The most effective method can be selected by using statistical selection (e.g. leave-one-out cross validation).

Keywords: Bottom elevation, multi-view stereo, river, structure-from-motion.

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Authors: Prakash Singh

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Many schools throughout the world are facing constant pressure to cope with the violence and drug abuse of learners who show little or no respect for acceptable and desirable social norms. These delinquent learners tend to harbour feelings of being beyond reproach because they strongly believe that it is well within their rights to engage in violent and destructive behaviour. Knives, guns, and other weapons appear to be more readily used by them on the school premises than before. It is known that learners smoke, drink alcohol, and use drugs during school hours, hence, their ability to concentrate, work, and learn, is affected. They become violent and display disruptive behaviour in their classrooms as well as on the school premises, and this atrocious behaviour makes it possible for drug dealers and gangsters to gain access onto the school premises. The primary purpose of this exploratory quantitative study was therefore to establish how tobephobia (TBP), caused by school violence and drug abuse, affects teaching and learning in schools. The findings of this study affirmed that poor discipline resulted in producing poor quality education. Most of the teachers in this study agreed that educating learners who consumed alcohol and other drugs on the school premises resulted in them suffering from TBP. These learners are frequently abusive and disrespectful, and resort to violence to seek attention. As a result, teachers feel extremely demotivated and suffer from high levels of anxiety and stress. The word TBP will surely be regarded as a blessing by many teachers throughout the world because finally, there is a word that will make people sit up and listen to their problems that cause real fear and anxiety in schools.

Keywords: Aims and objectives of quality education, Debilitating effects of tobephobia, Fear of failure associated with education, learners’ violent behaviour and drug abuse.

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Authors: Gianpaolo Ghiani, Emanuela Guerriero, Emanuele Manni, Alessandro Romano

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In this article, we deal with a variant of the classical course timetabling problem that has a practical application in many areas of education. In particular, in this paper we are interested in high schools remedial courses. The purpose of such courses is to provide under-prepared students with the skills necessary to succeed in their studies. In particular, a student might be under prepared in an entire course, or only in a part of it. The limited availability of funds, as well as the limited amount of time and teachers at disposal, often requires schools to choose which courses and/or which teaching units to activate. Thus, schools need to model the training offer and the related timetabling, with the goal of ensuring the highest possible teaching quality, by meeting the above-mentioned financial, time and resources constraints. Moreover, there are some prerequisites between the teaching units that must be satisfied. We first present a Mixed-Integer Programming (MIP) model to solve this problem to optimality. However, the presence of many peculiar constraints contributes inevitably in increasing the complexity of the mathematical model. Thus, solving it through a general-purpose solver may be performed for small instances only, while solving real-life-sized instances of such model requires specific techniques or heuristic approaches. For this purpose, we also propose a heuristic approach, in which we make use of a fast constructive procedure to obtain a feasible solution. To assess our exact and heuristic approaches we perform extensive computational results on both real-life instances (obtained from a high school in Lecce, Italy) and randomly generated instances. Our tests show that the MIP model is never solved to optimality, with an average optimality gap of 57%. On the other hand, the heuristic algorithm is much faster (in about the 50% of the considered instances it converges in approximately half of the time limit) and in many cases allows achieving an improvement on the objective function value obtained by the MIP model. Such an improvement ranges between 18% and 66%.

Keywords: Heuristic, MIP model, Remedial course, School, Timetabling.

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Authors: Muhammad Aqil, Ichiro Kita, Moses Macalinao

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Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.

Keywords: Neural Network, Fuzzy, River, Forecasting

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Authors: Aniela Pop, Ianina Birsan, Corina Orha, Rodica Pode, Florica Manea

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Carbon nanofiber-epoxy composite electrode has been investigated through voltammetric and amperometric techniques in order to detect parabens from aqueous solutions. The occurrence into environment as emerging pollutants of these preservative compounds has been extensively studied in the last decades, and consequently, a rapid and reliable method for their quantitative quantification is required. In this study, methylparaben (MP) and propylparaben (PP) were chosen as representatives for paraben class. The individual electrochemical detection of each paraben has been successfully performed. Their electrochemical oxidation occurred at the same potential value. Their simultaneous quantification should be assessed electrochemically only as general index of paraben class as a cumulative signal corresponding to both MP and PP from solution. The influence of pH on the electrochemical signal was studied. pH ranged between 1.3 and 9.0 allowed shifting the detection potential value to smaller value, which is very desired for the electroanalysis. Also, the signal is better-defined and higher sensitivity is achieved. Differential-pulsed voltammetry and square-wave voltammetry were exploited under the optimum pH conditions to improve the electroanalytical performance for the paraben detection. Also, the operation conditions were selected, i.e., the step potential, modulation amplitude and the frequency. Chronomaprometry application as the easiest electrochemical detection method led to worse sensitivity, probably due to a possible fouling effect of the electrode surface. The best electroanalytical performance was achieved by pulsed voltammetric technique but the selection of the electrochemical technique is related to the concrete practical application. A good reproducibility of the voltammetric-based method using carbon nanofiber-epoxy composite electrode was determined and no interference effect was found for the cation and anion species that are common in the water matrix. Besides these characteristics, the long life-time of the electrode give to carbon nanofiber-epoxy composite electrode a great potential for practical applications.

Keywords: Carbon nanofiber-epoxy composite electrode, electroanalysis, methylparaben, propylparaben.

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Authors: M. G. Murtaza, E. E. Tzirtzilakis, M. Ferdows

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Biomagnetic fluid dynamics is an interdisciplinary field comprising engineering, medicine, and biology. Bio fluid dynamics is directed towards finding and developing the solutions to some of the human body related diseases and disorders. This article describes the flow and heat transfer of two dimensional, steady, laminar, viscous and incompressible biomagnetic fluid over a non-linear stretching sheet in the presence of magnetic dipole. Our model is consistent with blood fluid namely biomagnetic fluid dynamics (BFD). This model based on the principles of ferrohydrodynamic (FHD). The temperature at the stretching surface is assumed to follow a power law variation, and stretching velocity is assumed to have a nonlinear form with signum function or sign function. The governing boundary layer equations with boundary conditions are simplified to couple higher order equations using usual transformations. Numerical solutions for the governing momentum and energy equations are obtained by efficient numerical techniques based on the common finite difference method with central differencing, on a tridiagonal matrix manipulation and on an iterative procedure. Computations are performed for a wide range of the governing parameters such as magnetic field parameter, power law exponent temperature parameter, and other involved parameters and the effect of these parameters on the velocity and temperature field is presented. It is observed that for different values of the magnetic parameter, the velocity distribution decreases while temperature distribution increases. Besides, the finite difference solutions results for skin-friction coefficient and rate of heat transfer are discussed. This study will have an important bearing on a high targeting efficiency, a high magnetic field is required in the targeted body compartment.

Keywords: Biomagnetic fluid, FHD, nonlinear stretching sheet, slip parameter.

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Authors: R. Estrada, A. Henriquez, R. Becerra, C. Laguna

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Spatial Augmented Reality is a variation of Augmented Reality where the Head-Mounted Display is not required. This variation of Augmented Reality is useful in cases where the need for a Head-Mounted Display itself is a limitation. To achieve this, Spatial Augmented Reality techniques substitute the technological elements of Augmented Reality; the virtual world is projected onto a physical surface. To create an interactive spatial augmented experience, the application must be aware of the spatial relations that exist between its core elements. In this case, the core elements are referred to as a projection system and an input system, and the process to achieve this spatial awareness is called system calibration. The Spatial Augmented Reality system is considered calibrated if the projected virtual world scale is similar to the real-world scale, meaning that a virtual object will maintain its perceived dimensions when projected to the real world. Also, the input system is calibrated if the application knows the relative position of a point in the projection plane and the RGB-depth sensor origin point. Any kind of projection technology can be used, light-based projectors, close-range projectors, and screens, as long as it complies with the defined constraints; the method was tested on different configurations. The proposed procedure does not rely on a physical marker, minimizing the human intervention on the process. The tests are made using a Kinect V2 as an input sensor and several projection devices. In order to test the method, the constraints defined were applied to a variety of physical configurations; once the method was executed, some variables were obtained to measure the method performance. It was demonstrated that the method obtained can solve different arrangements, giving the user a wide range of setup possibilities.

Keywords: Color depth sensor, human computer interface, interactive surface, spatial augmented reality.

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Authors: Muhibul Haque Bhuyan

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Inclusion of any design project in an undergraduate electrical and electronic engineering curriculum and producing creative ideas in the final year capstone design projects have received numerous comments at the Board of Accreditation for Engineering and Technical Education (BAETE) several times by the mentors and visiting program evaluator team members at different public and private universities in Bangladesh. To eradicate this deficiency which is needed for getting the program accreditation, a thorough change was required in the Department of Electrical and Electronic Engineering (EEE) for its BSc in EEE program at Southeast University, Dhaka, Bangladesh. We suggested making changes in the course curriculum titles and contents, emphasizing to include capstone design projects, question setting, examining students through other standard methods, selecting and retaining Outcome-Based Education (OBE)-oriented engineering faculty members, improving laboratories through purchasing new equipment and software as well as developing new experiments for each laboratory courses, and engaging the students to practical designs in various courses and final year projects. This paper reports on capstone design project course objectives, course outcomes, mapping with the program outcomes, cognitive domain of learning, assessment schemes, guidelines, suggestions and recommendations for supervision processes, assessment strategy, and rubric setting, etc. It is expected that this will substantially improve the capstone design projects offering, supervision, and assessment in the undergraduate EEE program to fulfill the arduous requirements of BAETE accreditation based on OBE.

Keywords: Course outcome, capstone design project, assessment and evaluation, electrical and electronic engineering.

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Authors: Melis Inalpulat, Levent Genc, Unal Kizil, Tugce Civelek

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Livestock production is one of the most important components of rural economy. Due to the urban expansion, rural areas close to expanding cities transform into urban districts during the time. However, the legislations have some restrictions related to livestock farming in such administrative units since they tend to create environmental concerns like odor problems resulted from excessive manure production. Therefore, the existing animal operations should be moved from the settlement areas. This paper was focused on determination of suitable lands for livestock production in Canakkale province of Turkey using remote sensing (RS) data and GIS techniques. To achieve the goal, Formosat 2 and Landsat 8 imageries, Aster DEM, and 1:25000 scaled soil maps, village boundaries, and village livestock inventory records were used. The study was conducted using suitability analysis which evaluates the land in terms of limitations and potentials, and suitability range was categorized as Suitable (S) and Non-Suitable (NS). Limitations included the distances from main and crossroads, water resources and settlements, while potentials were appropriate values for slope, land use capability and land use land cover status. Village-based S land distribution results were presented, and compared with livestock inventories. Results showed that approximately 44230 ha area is inappropriate because of the distance limitations for roads and etc. (NS). Moreover, according to LULC map, 71052 ha area consists of forests, olive and other orchards, and thus, may not be suitable for building such structures (NS). In comparison, it was found that there are a total of 1228 ha S lands within study area. The village-based findings indicated that, in some villages livestock production continues on NS areas. Finally, it was suggested that organized livestock zones may be constructed to serve in more than one village after the detailed analysis complemented considering also political decisions, opinion of the local people, etc.

Keywords: GIS, livestock, LULC, remote sensing, suitable lands.

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Authors: Ç. Gökçek-Saraç, Ş. Özen, N. Derin

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The N-methyl-D-aspartate (NMDA)-dependent pathway is the major intracellular signaling pathway implemented in both short- and long-term memory formation in the hippocampus which is the most studied brain structure because of its well documented role in learning and memory. However, little is known about the effects of RF-EMR exposure on NMDA receptor signaling pathway including activation of protein kinases, notably Ca²⁺/calmodulin-dependent protein kinase II alpha (CaMKIIα). The aim of the present study was to investigate the effects of acute and chronic 900 MHz RF-EMR exposure on both passive avoidance behaviour and hippocampal levels of CaMKIIα and its phosphorylated form (pCaMKIIα). Rats were divided into the following groups: Sham rats, and rats exposed to 900 MHz RF-EMR for 2 h/day for 1 week (acute group) or 10 weeks (chronic group), respectively. Passive avoidance task was used as a behavioural method. The hippocampal levels of selected kinases were measured using Western Blotting technique. The results of passive avoidance task showed that both acute and chronic exposure to 900 MHz RF-EMR can impair passive avoidance behaviour with minor effects on chronic group of rats. The analysis of western blot data of selected protein kinases demonstrated that hippocampal levels of CaMKIIα and pCaMKIIα were significantly higher in chronic group of rats as compared to acute groups. Taken together, these findings demonstrated that different duration times (1 week vs 10 weeks) of 900 MHz RF-EMR exposure have different effects on both passive avoidance behaviour of rats and hippocampal levels of selected protein kinases.

Keywords: Hippocampus, protein kinase, rat, RF-EMR.

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Authors: Md Rabiul Islam, Ben Wadham

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This paper describes how indigenous students face challenges with various school activities due to inadequate equity and diversity principles in mainstream primary schools in Bangladesh. This study focuses on indigenous students’ interactions with mainstream class teachers and students through teaching-learning activities at public primary schools. Ethnographic research methods guided data collection under a case study methodology in Chittagong Hill Tracts (CHTs) region where maximum indigenous peoples’ inhabitants. The participants (class teachers) shared information through in-depth interviews about their experiences in the four selecting schools. The authors also observed the effects of school activities by use of equity and diversity lens for indigenous students’ situations in those schools. The authors argue that the socio-economic situations of indigenous families are not supportive of the educational development of their children. Similarly, the Bangladesh government does not have enough initiative programs based on equity and diversity principles for fundamental education of indigenous children at rural schools level. Besides this, the conventional teaching system cannot improve the diversification among the students in classrooms. The principles of equity and diversity are not well embedded in professional development of teachers, and using teaching materials in classrooms. The findings suggest that implementing equitable education; there are needed to arrange teachers’ education with equitable knowledge and introducing diversified teaching materials, and implementing teaching through students centered activities that promote the diversification among the multicultural students.

Keywords: Case study research, equity and diversity, Indigenous children.

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Authors: Iacopo Testi, Diego Pajarito, Nicoletta Roberto, Carmen Greco

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Today, a consistent segment of the world’s population lives in urban areas, and this proportion will vastly increase in the next decades. Therefore, understanding the key trends in urbanization, likely to unfold over the coming years, is crucial to the implementation of sustainable urban strategies. In parallel, the daily amount of digital data produced will be expanding at an exponential rate during the following years. The analysis of various types of data sets and its derived applications have incredible potential across different crucial sectors such as healthcare, housing, transportation, energy, and education. Nevertheless, in city development, architects and urban planners appear to rely mostly on traditional and analogical techniques of data collection. This paper investigates the prospective of the data science field, appearing to be a formidable resource to assist city managers in identifying strategies to enhance the social, economic, and environmental sustainability of our urban areas. The collection of different new layers of information would definitely enhance planners' capabilities to comprehend more in-depth urban phenomena such as gentrification, land use definition, mobility, or critical infrastructural issues. Specifically, the research results correlate economic, commercial, demographic, and housing data with the purpose of defining the youth economic discomfort index. The statistical composite index provides insights regarding the economic disadvantage of citizens aged between 18 years and 29 years, and results clearly display that central urban zones and more disadvantaged than peripheral ones. The experimental set up selected the city of Rome as the testing ground of the whole investigation. The methodology aims at applying statistical and spatial analysis to construct a composite index supporting informed data-driven decisions for urban planning.

Keywords: Data science, spatial analysis, composite index, Rome, urban planning, youth economic discomfort index.

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Authors: T. Jayanthi, K. Velusamy, H. Seetha, S. A. V. Satya Murty

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Verification and Validation of Simulated Process Model is the most important phase of the simulator life cycle. Evaluation of simulated process models based on Verification and Validation techniques checks the closeness of each component model (in a simulated network) with the real system/process with respect to dynamic behaviour under steady state and transient conditions. The process of Verification and Validation helps in qualifying the process simulator for the intended purpose whether it is for providing comprehensive training or design verification. In general, model verification is carried out by comparison of simulated component characteristics with the original requirement to ensure that each step in the model development process completely incorporates all the design requirements. Validation testing is performed by comparing the simulated process parameters to the actual plant process parameters either in standalone mode or integrated mode. A Full Scope Replica Operator Training Simulator for PFBR - Prototype Fast Breeder Reactor has been developed at IGCAR, Kalpakkam, INDIA named KALBR-SIM (Kalpakkam Breeder Reactor Simulator) where in the main participants are engineers/experts belonging to Modeling Team, Process Design and Instrumentation & Control design team. This paper discusses about the Verification and Validation process in general, the evaluation procedure adopted for PFBR operator training Simulator, the methodology followed for verifying the models, the reference documents and standards used etc. It details out the importance of internal validation by design experts, subsequent validation by external agency consisting of experts from various fields, model improvement by tuning based on expert’s comments, final qualification of the simulator for the intended purpose and the difficulties faced while co-coordinating various activities.

Keywords: Verification and Validation (V&V), Prototype Fast Breeder Reactor (PFBR), Kalpakkam Breeder Reactor Simulator (KALBR-SIM), Steady State, Transient State.

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Authors: Matheus Müller, Delma Vidal

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The present paper aims to expose two techniques of dewatering for sludge, analyzing its operations and dewatering processes, aiming at improving the conditions of disposal of residues with high liquid content. It describes the field tests performed on two geotextile systems, a closed geotextile tube and an open geotextile drying bed, both of which are submitted to two filling cycles. The sludge used in the filling cycles for the field trials is from the water treatment plant of the Technological Center of Aeronautics – CTA, in São José dos Campos, Brazil. Data about volume and height abatement due to the dewatering and consolidation were collected per time, until it was observed constancy. With the laboratory analysis of the sludge allied to the data collected in the field, it was possible to perform a critical comparative study between the observed and the scientific literature, in this way, this paper expresses the data obtained and compares them with the bibliography. The tests were carried out on three fronts: field tests, including the filling cycles of the systems with the sludge from CTA, taking measurements of filling time per cycle and maximum filling height per cycle, heights against the abatement by dewatering of the systems over time; tests carried out in the laboratory, including the characterization of the sludge and removal of material samples from the systems to ascertain the solids content within the systems per time and; comparing the data obtained in the field and laboratory tests with the scientific literature. Through the study, it was possible to perceive that the process of densification of the material inside a closed system, such as the geotextile tube, occurs faster than the observed in the drying bed system. This process of accelerated densification can be brought about by the pumping pressure of the sludge in its filling and by the confinement of the residue through the permeable geotextile membrane (allowing water to pass through), accelerating the process of densification and dewatering by its own weight after the filling with sludge.

Keywords: Consolidation, dewatering, geotextile drying bed, geotextile tube.

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, unmanned aerial vehicle, UAV, random, Kriging.

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Authors: S. Figueiredo, M. Alves Martins, C. Silva, C. Simões

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This study integrates a larger research empirical project that examines second language (SL) learners’ profiles and valid procedures to perform complete and diagnostic assessment in schools. 102 learners of Portuguese as a SL aged 7 and 17 years speakers of distinct home languages were assessed in several linguistic tasks. In this article, we focused on writing performance in the specific task of narrative essay composition. The written outputs were measured using the score in six components adapted from an English SL assessment context (Alberta Education): linguistic vocabulary, grammar, syntax, strategy, socio-linguistic, and discourse. The writing processes and strategies in Portuguese language used by different immigrant students were analysed to determine features and diversity of deficits on authentic texts performed by SL writers. Differentiated performance was based on the diversity of the following variables: grades, previous schooling, home language, instruction in first language, and exposure to Portuguese as Second Language. Indo-Aryan languages speakers showed low writing scores compared to their peers and the type of language and respective cognitive mapping (such as Mandarin and Arabic) was the predictor, not linguistic distance. Home language instruction should also be prominently considered in further research to understand specificities of cognitive academic profile in a Romance languages learning context. Additionally, this study also examined the teachers’ representations that will be here addressed to understand educational implications of second language teaching in psychological distress of different minorities in schools of specific host countries.

Keywords: Second language, writing assessment, home language, immigrant students, Portuguese language.

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: Recurrent Neural Network, players lineup, basketball data, decision making model.

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Authors: Anatoly Krivinsh

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The results of dissertation research "Preventing and  combating corruption in public procurement" are presented in this  publication. The study was conducted 2011 till 2013 in a Member  State of the European Union– in the Republic of Latvia.  Goal of the thesis is to explore corruption prevention and  combating issues in public procurement sphere, to identify the  prevalence rates, determinants and contributing factors and  prevention opportunities in Latvia.  In the first chapter the author analyzes theoretical aspects of  understanding corruption in public procurement, with particular  emphasis on corruption definition problem, its nature, causes and  consequences. A separate section is dedicated to the public  procurement concept, mechanism and legal framework. In the first  part of this work the author presents cognitive methodology of  corruption in public procurement field, based on which the author has  carried out an analysis of corruption situation in public procurement  in Republic of Latvia.  In the second chapter of the thesis, the author analyzes the  problem of corruption in public procurement, including its historical  aspects, typology and classification of corruption subjects involved,  corruption risk elements in public procurement and their  identification. During the development of the second chapter author's  practical experience in public procurements was widely used.  The third and fourth chapter deals with issues related to the  prevention and combating corruption in public procurement, namely  the operation of the concept, principles, methods and techniques,  subjects in Republic of Latvia, as well as an analysis of foreign  experience in preventing and combating corruption. The fifth chapter  is devoted to the corruption prevention and combating perspectives  and their assessment. In this chapter the author has made the  evaluation of corruption prevention and combating measures  efficiency in Republic of Latvia, assessment of anti-corruption  legislation development stage in public procurement field in Latvia. 

Keywords: Prevention of corruption, public purchases.

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Authors: Siripen Yiamjanya, Kevin Wongleedee

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This research paper aims to identify travel motivation by push and pull factors that affected decision making of international tourists in selecting Thailand as their destination choice. A total of 200 international tourists who traveled to Thailand during January and February, 2014 were used as the sample in this study. A questionnaire was employed as a tool in collecting the data, conducted in Bangkok. The list consisted of 30 attributes representing both psychological factors as “push- based factors” and destination factors as “pull-based factors”. Mean and standard deviation were used in order to find the top ten travel motives that were important determinants in the respondents’ decision making process to select Thailand as their destination choice. The finding revealed the top ten travel motivations influencing international tourists to select Thailand as their destination choice included [i] getting experience in foreign land; [ii] Thai food; [iii] learning new culture; [iv] relaxing in foreign land; [v] wanting to learn new things; [vi] being interested in Thai culture, and traditional markets; [vii] escaping from same daily life; [viii] enjoying activities; [ix] adventure; and [x] good weather. Classification of push- based and pull- based motives suggested that getting experience in foreign land was the most important push motive for international tourists to travel, while Thai food portrayed its highest significance as pull motive. Discussion and suggestions were also made for tourism industry of Thailand.

Keywords: Decision Making, Destination Choice, International Tourist, Pull Factor, Push Factor, Thailand, Travel Motivation.

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