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Nowadays, most universities provide a learning management system (LMS) to support teaching and learning. These LMS provide an ability to publish learning content, announce news and exchange opinion etc. However, most students may not pay attention to LMS when compared with online social media which play a key role in student’s everyday life. This paper presents the development of a Facebook application called F-learning for supporting Moodle LMS by presenting activities such as quiz and assignment files. F learning will notify students through Facebook when activities have been updated. Moreover, F-learning is also able to rank quiz score by H-index concept, rewarding the top-3 in each course, displaying and sharing overall medal table in accordance with the Gamification concept. The evaluation results reveal that F-learning can motivate students to use the learning manage system.

Plagiarism is deemed a serious ethical offense. Without proper protection and accurate detection algorithms, the number of innovations would significantly dwindle, impeding the advancement of national research and education. Especially in programming courses, plagiarism is extremely common. Most students tend to do their homework in the simplest way: copying the source code of others. Such unpleasant issues must be addressed to preclude this misbehavior before it becomes students’ habit, and to promote positive attitudes in our juveniles. In this paper, we, propose an algorithm to identify original source codes, helping instructors to pinpoint whom to monitor and be able to set measures or correctly warn each wrong-doing student. This work introduces a rule, derived from a m+l evolutionary algorithm, for identifying which source codes are original. First, we run the maximum spanning tree algorithm to generate a phylogenetic tree, representing the relationships and sequences of plagiarisms.Then, we apply our proposed rule to identify the source and its copies, whose relations are represented by arrows’ directions. The experiment result shows that the proposed rule yields the accuracy of 90.24%.

This paper examines a deep convolutional neural network (Deep CNN) for plant recognition in the natural environment. The primary objective was to compare 4 CNN architectures including LeNet-5, AlexNet, GoogLeNet, and VGGNet on three plant datasets; PNE, 102 Flower, and Folio. The images in the PNE and 102 Flower dataset include a complicated background because they were taken in a natural environment. On the other hand, the images in the Folid dataset are only leaf images that were taken in a laboratory environment using a white background. The comparison of deep CNN using GoogLeNet and VGGNet Architecture show that GoogLeNet outperformed while working on the PNE and 102 Flower dataset when using a training time with iterations of 10,000 epochs. GoogLeNet also faster than the VGGNet architecture. However, the experiment showed that the VGGNet architecture outperforms the other CNN architectures on the Folio dataset and used only 1,000 epochs for training. In our experiment, we can create a model from the deep CNN using GoogleNet architecture, and this is because it showed better results with the plant images that were taken in the natural environment.

In this paper, we study the properties of open sets, closed sets, closure operator and interior operator on minimal structure space. We will provide characterization of sg -submaximal space by using various kinds of generalized closed sets and open sets.

In this paper, factors affecting mechanical properties and metallurgical structure of semi-solid aluminum alloy grades 356 and 7075 were investigated by a transient liquid-phase bonding method. ZA 27 zinc alloys were used as coagulants (solders) in a liquid state during the welding process. Semi-rigid aluminum castings with butt joints were prepared as a cylindrical shape 12 mm in diameter, 45 mm length and ZA 27 zinc alloys were 12 mm in diameter, and 0.25 mm thick. Variables in this transient liquid-phase bonding method included 60 minutes and 120 minutes welding time, welding temperatures at 450, 500 and 550 degrees Celsius, compression pressure at 4 MPa, and the flow rate of argon gas atmosphere at 4 liters/min. According to the results, the physical characteristics of all samples were well bonded. The microstructure in the bond line showed that size of the grain had grown because of the heat during transient liquid-phase bonding. However, at temperature 550ºC and compressive holding time for 60 minutes some porosities showed after welding, and the tensile strength of all samples were broken in the bonded line. However, at temperature 500ºC and compressive holding time 60 minutes, the maximum average tensile strength at 103.06 MPa was in the bonded line area where the hardness properties were higher than in other areas. In short, transient liquid-phase bonding technique could reduce welding time when compared to the diffusion bonding process.

In the Impedance Matching (IM) condition of Wireless Power Transfer (WPT), series resonant and strong coupling structures have been widely studied which operate at an optimal parameter, a resistive load, and the high resonant frequency of greater than 1 MHz. However, i) The optimal parameter (particular value) limits the design, ii) the common loads are complex, iii) The high frequency RF sources are usually inefficient. This paper presents a modified parallel resonant structure that can operate at a low frequency of 15 kHz without an optimal parameter under the IM condition with a complex load, and the calculated efficiency is equal to 71.2 % at 5-cm transfer distance.

This paper proposes the method, called the Filter Partitioning Machine Learning Classifier (FPMLC). It can enhance an accuracy of indoor positioning based on fingerprinting by using machine learning algorithms and prominent access points (APs). FPMLC selects limited information of groups of the signal strength and combines a clustering task and a classification task. There are three processes in FPMLC, i.e. feature selection to choose prominent APs, clustering to determine approximated positions, and classification to determine fine positions. This work demonstrates the procedure of FPMLC creation. The results of FPMLC are compared with those of a primitive method by using real measured data. FPMLC is compared with well-known machine learning classifiers, i.e. Decision Tree, Naive Bayes, and Artificial Neural Networks. The performance comparison is done in terms of accuracy and error distance between classified positions and actual positions. The appropriate number of selected prominent APs and the number of clusters, are assigned in the clustering process. The result of this study shows that FPMLC can increase performance for indoor positioning of all classifiers. In addition, FPMLC is the most optimized model while having Decision Tree as its classifier.

The assessment of sustainability performance has become a topic widely discussed by business practitioners. The complexity of this issue is highlighted by the incorporation of a large number of criteria. Several methods under the context of Multiple Criteria Decision Analysis (MCDA) have been employed to facilitate the aggregation of various criteria and to provide a guideline for decision making. As most MCDA methods assume that each criterion plays a role equal to its weight, this paper investigates the weight of each criterion in evaluation of corporate sustainability by focusing on the sugar industry in order to respond to the lack of MCDA and sustainability studies in this sector. The weighting is analysed by means of the relative importance based upon interviews and the direct rating technique. Statistical analysis is also conducted. The results from this empirical research indicate priorities of sustainability criteria and demonstrate the diversity of concerns within the industry when deciding on sustainability policies and strategies. This encourages practitioners to incorporate uncertain weights of sustainability criteria into decision making. Possible reasons for variations or changes in weights have been also discussed, and this enables practitioners to perform a sensitivity analysis in a more realistic way.

This paper addresses a problem of the two-stage flexible flow shop with reentrant and blocking constraints in Hard Disk Drive Manufacturing. This problem can be formulated as a deterministic FFS|stage=2,rcrc, block|Cmax problem. In this study, adaptive Hybrid Particle Swarm Optimization with Cauchy distribution (HPSO) was developed to solve the problem. The objective of this research is to find the sequences in order to minimize the makespan. To show their performances, computational experiments were performed on a number of test problems and the results are reported. Experimental results show that the proposed algorithms give better solutions than the classical Particle Swarm Optimization (PSO) for all test problems. Additionally, the relative improvement (RI) of the makespan solutions obtained by the proposed algorithms with respect to those of the current practice is performed in order to measure the quality of the makespan solutions generated by the proposed algorithms. The RI results show that the HPSO algorithm can improve the makespan solution by averages of 14.78%.

Soil salinity causes corrosion of engineering structures worldwide. The main cause of soil salinization is capillary rise of saline groundwater. Soil salinity can be mitigated once the capillary rise of saline groundwater in soils is understood. The objective of this paper is to present experimental results of capillary rising rates of different salt concentration waters in three sandy soils. Each sample comprised of a soil column 300-mm height and 50-mm in diameter steeped in a 25-mm deep saline water pool for a time period to allow for the capillary action to develop. The salinity strength varied from fresh water, EC = 2 dS/m, to medium saline (50, 100, and 150 dS/m), and to high saline water (200 dS/m). It was found that the highest rate of capillary rise occurred in medium saline waters, while the lowest is the fresh water. The very saline water has lower rate than the medium ones but higher than fresh water.

In manufacturing process where efficiency is crucial in order to remain competitive, flowshop is a common configuration in which machines are arranged in series and products are produced through the stages one by one. In certain production processes, the machines are frequently configured in the way that each production stage may contain multiple processing units in parallel or hybrid. Moreover, along with precedent conditions, the sequence dependent setup times may exist. Finally, in case there is no buffer, a machine is said to be blocked if the next stage to handle its output is being occupied. Such NP-Hard problem, referred as Blocking Hybrid Flowshop Scheduling Problem with Sequence Dependent Setup/Changeover Times, is usually not possible to find the best exact solution to satisfy optimization objectives such as minimization of the overall production time. Thus, it is usually solved by approximate algorithms such as metaheuristics. In this paper, we investigate comparatively the effectiveness of the two approaches: a Genetic Algorithm (GA) and an Artificial Bee Colony (ABC) algorithm. GA is inspired by the process of natural selection. ABC, in the same manner, resembles the way types of bees perform specific functions and work collectively to find their foods by means of division of labor. Additionally, we apply an algorithm to improve the GA and ABC algorithms so that they can take advantage of parallel processing resources of modern multiple core processors while eliminate the need for screening the optimal parameters of both algorithms in advance.

In this paper, we survey the role of mathematics in electrical network connections. We discuss the behavior of current flows, voltages and impedances mainly for series-parallel networks. In both one-port and multiport electrical networks, the currents through these networks are governed by Maxwell’s power principle. The joint impedances of the networks, given in terms of series sum and parallel sum, satisfy the series-parallel inequality. An abstract idea can be formulated in functional analysis aspect in which any network connection is viewed to be a binary operation for positive operators satisfying certain algebraic, order and topological properties.

In this paper, the influence of fly ash fineness on water requirement and shrinkage of blended cement mortar was studied. The results indicate that the water requirement and shrinkage characteristic of the blended cement mortar are dependent on fly ash fineness and replacement level. The use of coarse fly ash slightly reduces the water requirement but greatly reduced the drying and the autogenous shrinkage of the blended cement mortars and the reduction is more with an increase in the fly ash replacement level. The finer fly ashes further reduce the water requirement, but increase the drying and the autogenous shrinkages as compared with coarser fly ash. The incorporation of superplasticizer drastically reduces the water requirement, but the effect on the drying and autogenous shrinkages of the normal Portland cement mortar is small. However, for the fly ash mortar, the use of superplasticizer results in a decrease in drying shrinkage and in a substantial increase in the autogenous shrinkage particularly for the fine fly ash at a high replacement level.

Because of nonlinear strain distributions caused either by abrupt changes in geometry or in loading in deep beam, the approach for conventional beams is not applicable. Consequently, strut-and-tie model (STM) has been applied as the most rational and simple method for strength prediction and design of reinforced concrete deep beams. A deep beam is idealized by the STM as a truss-like structure consisting of diagonal concrete struts and tension ties. There have been numerous works proposing the STMs for deep beams. However, uncertainty and complexity in shear strength computations of deep beams can be found in some STMs. Therefore, improvement of methods for predicting the shear strengths of deep beams are still needed. By means of a large experimental database of 406 deep beam test results covering a wide range of influencing parameters, several shapes and geometry of STM and six state-of-the-art formulation of the efficiency factors found in the design codes and literature, the new STMs for predicting the shear strength of simply supported reinforced concrete deep beams using multiple linear regression analysis is proposed in this paper. Furthermore, the regression diagnostics and the validation process are included in this study. Finally, two numerical examples are also provided for illustration.

Lightning striking on a transmission tower induces high ground potential rise and high voltage at tower arms in which potential is normally at ground level, and subsequently causes overvoltage across an insulator string. If this overvoltage is higher than the withstanding voltage of the insulator string according to the v-t (voltage-time) curve, back flashover phenomena will occur and this event may cause outage. The main objective of this paper is to study the factors influencing the back flashover phenomena. The computer program PSCAD/EMTDC (Power System Computer Aided Design/Electromagnetic Transients including DC) is used to simulate lightning striking on a transmission tower 115kV. Lightning current, transmission towers, ground resistance, insulator strings and back flashover phenomena are modeled. Main simulations are lightning striking on different towers, different soil resistivity, different lightning current magnitudes and wave shapes, different locations, and different phase angles of source voltage. Simulation results show that the higher tower encounters higher induced voltage. A back flashover occurs at the top tower arm easier than at the middle and lower arms. The higher soil resistivity induces higher voltage. The larger lightning current magnitude impacts on higher induced voltage. The longer rise time of lightning current generates lower induced voltage. Lightning strikes directly on tower generate higher voltage than that of striking on overhead ground wires.

This paper presents the concept of a speed estimation of sensorless control for asymmetrical parameter type two-phase induction motor drive, by using the adaptive observer system. The motor speed is estimated on the rotor-flux reference frame to simplicity for application. The design guideline of the gain of speed estimate system for a motor has speed change. The experimental results for all test conditions show that the responses of current, torque and speed are stable for the entire operating region.

Ancient statues are cultural heritages that should be preserved and maintained. Nevertheless, such invaluable statues may be targeted by vandalism or burglary. In order to guard these statues by using image processing, this research aims to develop a technique for detecting images of ancient statues with missing parts using digital image processing. This paper proposed the effective feature extraction method for detecting images of damaged statues or statues with missing parts based on the Histogram Oriented Gradient (HOG) technique, a popular method for object detection. Unlike the original HOG technique, the proposed method has improved the area scanning strategy that effectively extracts important features of statues. Results obtained from the proposed method were compared with those of the HOG method. The tested image dataset composed of 500 images of perfect statues and 500 images of statues with missing parts. The experimental results show that the proposed method yields 99.88% accuracy while the original HOG method gives the accuracy of only 84.86%.

This study was aimed to increase the impact resistance of circular tubes reinforced by fiber reinforced plastic (FRP).The tube made of aluminum 6063-T5 with the D/t ratio of 25.40, 29.63, and 42.33. Outside surface of aluminum tube was reinforced by wrapping fiberglass/polyester. The fiber orientation angle were [0]3 , [45]3 , [90]3 , [0/902 ], [45/-452 ], and [90/02 ]. Then, they were tested under impact with cross head of 45 kg and speed of 6.26 m/s in axial direction. The result revealed that the impact resistance of the hybrid tube and aluminum tube trend to increase as the D/t ratio increases and The hybrid tube with wrapped angle of [0/902 ] was maximum mean load and higher than aluminum tube by 50.02, 45.14, and 52.03 % at D/t = 25.40, 29.63, and 42.33 receptively. Failure mode and crush behavior of hybrid tube were also presented and disused in this paper.

Social media sites have experienced an explosion in both the number of users and the amount of user-contributed content in recent years. There is the need for the solution for information overload in social media. In this paper, we focus on solving the problem of finding relevant Twitter users to follow and selecting only popular tweets to post, we have collected information about Twitter users, particularly the number of influential users who are followers, the number of general followers, and the number of tweets that are frequently retweeted. Then we used such statistics information to compute the user rankings. In addition, we also created a Twitter account to automatically post only tweets that have been retweeted many times. Based on the survey result and using the Spearman’s rank correlation coefficient, the recommended Twitter users suggested by the system have proven to be popular and pertinent, and the rank order by the proposed system has a statistical significant degree of similarity with the user survey result.

Currently the amount of web data has increased excessively. Its metadata is widely used in order to fully exploit web information resources. This causes the need for Semantic Web technology to quickly analyze such big data. Resource Description Framework (RDF) is a standard for describing web resources. In this paper, we propose a method to exploit a NoSQL database, specifically MongoDB, to store and query RDF data. We choose MongoDB to represent a NoSQL database because it is one of the most popular high-performance NoSQL databases. We evaluate the proposed design and implementation by using the Berlin SPARQL Benchmark, which is one of the most widely accepted benchmarks for comparing the performance of RDF storage systems. We compare three database systems, which are Apache Jena TDB (native RDF store), MySQL (relational database), and our proposed system with MongoDB (NoSQL database). Based on the experimental results analysis, our proposed system outperforms other database systems for most queries when the data set size is small. However, for a larger data set, MongoDB performs well for queries with simple operators while MySQL offers an efficient solution for complex queries. The result of this work can provide some guideline for choosing an appropriate RDF database system and applying a NoSQL database in storing and querying RDF data.

This paper proposed a nonlinear finite element model to investigate mechanism and behavior of the concrete columns confined with metal sheet. Three dimensional modeling was chosen. Concrete was modeled using the Drucker-Prager yield criterion and a softening function, whereas the Von-Mises yield criterion was chosen for metal sheet. Between both materials, a set of interface elements was inserted to represent layers of the bonding material. The results showed that the finite element model could model the behaviors that were observed from the laboratory experiments, and could capture the mechanisms that were not noticed in the laboratory experiment as well.

The main objective of this paper is to discuss alternative approaches to convert a propositional logic problem into a 0-1 integer program. The substitution method proposed by Williams and CNF method is used for modeling and representation of logical inference problem. The similarity between the two fields viz. optimization problems or mathematical programming and deductive logic are shown.

This research is purposed to study crashworthiness behavior of fiberglass tube subjected axial compression. The specimens are made of fiberglass and hand lay-up in different ply angles which are; specimen A ply angle is [(0/90)/(0/90)/(0/90)] specimen B ply angle is [(45/-45)/(45/-45)/(45/-45)] and specimen C ply angle is [(45/-45)/(0/90)/(45/-45)]. The tube has 50 mm outside diameter, 2 mm wall thickness and 100 mm length. Quasi-static test is done by ESH Universal Testing Machine with 10 mm/min of crushing speed. Impact test is done by Vertical Impact Testing Machine with the impact speed of 7 m/s. The result showed that specimen A gives highest specific energy absorption due to the vertical fiber orientation. In addition, the collapse mode and response of specimens to impact are also discussed in the paper.

This paper presents the double input converters for different voltage input sources with isolated charger coils. This research aims to increase the performance of the battery charger circuit. In the circuit, there are the different voltage levels of input source. The operating modes of the switch in the circuit use the microcontroller to control the battery charge and to control discharge mode automatically when the input voltage sources are lost from the system. The experimental result of this research shows better performance for charging at any time period of the switch, while the voltage input sources work together. Therefore, this research can use and develop to battery charger for present or future.

To proposed a new adaptive intelligent system for a robot work cell that can visually track and intercept an invariant stationary HGA feature undergoing arbitrary orientation anywhere along its predicted trajectory within the robot’s workspace is presented in this paper. A combination of the seven invariant moment technique, image feature technique and the MADALINE network are used for identifying the stationary HGA at any rotation angle without overlapping and generating the predicted robot trajectory respectively. An invariant moment that has system for a scale, translation and orientation are calculated for each significant region in the input images. Inertial ellipse is determining for angle rotation that compare against to the accepted orientation that required. The result shown that, the relationship between the visual feedback image data and the control command for changing the axis motion shows deviation of robot placing less than 2% by the MADALINE network for intercepting stationary HGA at any rotation angle. The location and image features of these HGAs need not be preprogrammed, marked and known before, and any change in a task is possible without changing the robot program. Finally, this novel method can improve the hard disk drive (HDD) assembly process productivity.

For environmental reason, new binders that can be used as Portland cement replacement materials are being needed. Recently, alkali-activated binders (AAB) and geopolymer have found increasing interest. As several research reports have showed that the two new binders are likely to have high potential to be developed and become an alternative to OPC. However, confusion in the classification of both binders is still there. This paper reviews knowledge about AAB and geopolymer including historical background, reaction mechanisms and reaction products. The similarities and differences of both binders are discussed. The application to environmental engineering on hazardous waste management using stabilization/solidification is also described.

Research paper is the spray and engine performance investigation from preheated diesel and biodiesel oils at fuel temperature from 60 to 90 o C by comparing with non-preheated oil. In the experiment, there are fuel injection modeling and diesel engine testing, which is direct injection, 4 stroke and 4 cylinders. Results of fuel spray show that preheated diesel oil increase 4.7degree of spray angle and decrease 4.30 % of fuel injection pressure, as preheated bio-diesel oil increase 7.6degree of spray angle and decrease 13.90 % of fuel injection pressure to compare with non-preheated oil. As engine preformance testing results, preheated diesel oil increase 26.20% of thermal efficiency and decrease 4.30 % of BSFC, as preheated bio-diesel oil increase 30% of thermal efficiency and decrease 29.90 % of BSFC to compare with non-preheated oil.

This paper is aimed to investigate the properties of joint between AISI 4140 and AISI 1040 welded by friction welding. The specimens were prepared in round shape of 13 mm diameter and 100 mm long. They were welded by friction welding method under the following conditions; friction pressure of 183 MPa, friction time of 12 sec, upset pressure of 428 MPa, upset time of 7 sec. and rotational speed of 1400 rpm. The strength and hardness were tested on the welded area. The result showed finer grains. in the welded area. This is the result of friction pressure and upset pressure in the welding process. In addition, the observation result indicated some changes of Ferrite and Pearlite in welded zone. This phase change resulted in the increment of hardness in AISI 4140 at the contact area and adjacent. In part of AISI 1040, the portion of Pearlite and Ferrite are not significantly changed, therefore the value of hardness is almost constant.

This paper presents an investigation of airflow over a rugged mountain to find suitable locations for wind turbines. The investigation considers turbulent intensity and inflow angle in addition to wind speed. The area of interest is the mountain around the upper reservoir of Lamtakong Jolabha Vadhana Hydro Power Plant, Nakhon Ratchasima, Thailand. The Lamtakong Wind Turbine Power System is located near the reservoir. Due to the ruggedness of the site, according to the angle of slopes, the existing turbines may be experiencing airflow with high turbulent intensity and non-zero inflow angle. This study uses Computational Fluid Dynamics (CFD) and Wind Atlas Analysis and Application Program (WAsP) to simulate airflow. CFD is used in the final analysis to quantify turbulent intensity and inflow angle. The turbulence model is used, while the roughness height and roughness constant are tuned according to the ground cover. Detailed examinations of cases show that the highest wind speeds do not always occur at the mountain’s peaks. High turbulent intensity leads to the exclusion of locations on the lee side of the mountain, where it reaches 18%. The inflow angles are high on the upwind side of the mountain and can go up to 20 degrees. It is found that the slopes affect the inflow angles but they do not dictate the inflow angles. Finally, the results of the highest peak suggest that most suitable turbine spot is approximately 60 m downwind from the point of highest wind speed. The power density reduces from 515.3 W/m2 to 502.6 W/m2 at 60 m hub-height. Thus, to achieve a zero inflow angle, turbines may have a power output reduction but they will experience lower turbulence and uneven loading.

The objective of this paper is to design raw materials forecasting methods for material management process improvement of an outsourced ready-to-wear suit factory. In this research, we study demands of five types of frequently used raw materials and identify the most appropriate forecasting method providing the lowest Mean Absolute Percentage Error (MAPE). We found that Simple Exponential Smoothing method gives the most accurate result with smoothing parameters (α ) of 0.9439,0.6906,0.8656,0.9844and 0.8694 for SKU number EX102, RX101, HX101, IX103 and KX101, respectively. From the results, we found considering weekly demand yields more accurate forecasting results as compared to monthly demand. From our on-site experiment from October to December 2012 to identify the suitable time to adjust smoothing constant (α ), we found that the smoothing constant should be reviewed and adjusted every 4 weeks for SKU number RX101, HX101 and KX101, giving the MAPE results of 21.125, 13.170 and 18.952, respectively. For EX102 andIX103, the parameter should be reviewed every 8 weeks, giving the MAPE results of 7.538 and 8.897, respectively. Overall, the proposed model can reduce forecasting errors up to 45 percent as compared to the naïve method previously used in this factory.

Plagiarism is the act of taking another person's writing or idea without referring to the source of information. This is one of major problems in educational institutes. There is a number of plagiarism detection software available on the Internet. However, a few numbers of them works. Typically, they use a simple method for plagiarism detection e.g. string matching. The main weakness of this method is it cannot detect the plagiarism when the author replaces some words using synonyms. As such, this paper presents a new technique for a semantic-based plagiarism detection using Semantic Role Labeling (SRL) and term weighting. SRL is deployed in order to calculate the semantic-based similarity. The main different from the existing framework is terms in a sentence are weighted dynamically depending on their roles in the sentence e.g. subject, verb or object. This technique enhances the plagiarism detection mechanism more efficiently than existing system although positions of terms in a sentence are reordered. The experimental results show that the proposed method can detect the plagiarism document more effective than the existing methods, Anti-kobpae, Turnit-in and Traditional Semantic Role Labeling.

This paper aims to study appropriate ripeness of cultivated banana and time period for vacuum fry. Sliced bananas of thickness 1-2 mm were fried at temperature 130 ๐ C under vacuum condition. The samplings were done at 3 level of ripeness; 1) raw banana, 2) the first day of ripeness, 3) the second day of ripeness. In addition 5 levels of fried period were set; 6, 8, 10, 12, 14 min. The raw banana fried for 12 min shown the best result. The products have a crisp texture, appropriate hardness and toughness, standard moisture and color with the most acceptance by consumers.

This paper presents the COP prediction of an ejector refrigeration cycle combined with a vapour compression cycle for automotive air conditioning. Using computational fluid dynamics (CFD) technique, the performance of an ejector was analyzed in term of the entrainment ratio (Rm) and critical back pressure (CBP). The results from this study were compared with a previous study of combined ejector refrigeration system for automotive air conditioning application [1] which the entrainment ratio (Rm) were predicted from one-dimensional (1-D) equation. The performance of an ejector (Rm and CBP) from CFD and onedimensional method were analyzed and used as database for a mathematical modeling. In order to predict the COP of the combined system, a set of mathematical equations was developed using EES. The operating conditions are chosen accordingly as, intercooler temperature between 15 ๐ C and 25 ๐ C, condenser temperature equal to 35 ๐ C and evaporator temperature equal to 5 ๐ C. However, when generator temperatures are 80 ๐ C, 85 ๐ C and 90 ๐ C, the results showed average relative errors of the COP of an ejector refrigeration cycle (COPej), between CFD and 1-D are 44.64%, 50.47% and 59.68% respectively, and between CFD and 1-D NEW are 1.54%, 0.08% and 6.49% respectively.

"The paper, based on population projections for Thailand...examines the growth and the structure of the Thai population between 1990 and 2115. The projections are prepared on the basis of the sex and age distribution of the 1990 population.... The study concludes that in order to maintain...economic and social prosperity, security and [prevent] the eradication of the Thai race, the government will have to raise fertility of the population at least up to the replacement level." (SUMMARY IN ENG), (excerpt)

Based on the census data of 1970 and 1980 for each province of Thailand, the present study has revealed that between 1960-1980, a rapid fertility decline took place in 17 northern provinces and 26 central provinces of Thailand. A similar rapid fertility decline also took place starting in 1975 in the 16 northeast provinces and in the 14 southern provinces. Levels and trends of fertility found in this study suggest that most of the districts in the northern and the central regions reached the replacement level or below by 1985, and that similar levels will be attained by 1990 for almost every district in Thailand. This paper also stresses the impact of the rapid fertility decline on development in Thailand during the past 20 years, and its consequences. Lastly, the present study suggests that, for the future, the most important step is to understand well the consequences of this astonishing rapid fertility decline. This knowledge will be vital for the country and its people.