Abstract: The objective is to study the knowledge utilization from the participants of the announcer training program by National Broadcasting and Telecommunications Commission (NBTC). This study is a quantitative research based on surveys and self-answering questionnaires. The population of this study is 100 participants randomly chosen by non-probability sampling method. The results have shown that most of the participants were satisfied with the topics of general knowledge about the broadcasting and television business for 37 people representing 37%, followed by the topics of broadcasting techniques. The legal issues, consumer rights, television business ethics, and credibility of the media are, in addition to the media's role and responsibilities in society, the use of language for successful communication. Therefore, the communication language skills are the most important for all of the trainees and will also build up the image of the broadcasting center.
Abstract: Cloud computing is one of the most sharp and important movement in various computing technologies. It provides flexibility to users, cost effectiveness, location independence, easy maintenance, enables multitenancy, drastic performance improvements, and increased productivity. On the other hand, there are also major issues like security. Being a common server, security for a cloud is a major issue; it is important to provide security to protect user’s private data, and it is especially important in e-commerce and social networks. In this paper, encryption algorithms such as Advanced Encryption Standard algorithms, their vulnerabilities, risk of attacks, optimal time and complexity management and comparison with other algorithms based on software implementation is proposed. Encryption techniques to improve the performance of AES algorithms and to reduce risk management are given. Secure Hash Algorithms, their vulnerabilities, software implementations, risk of attacks and comparison with other hashing algorithms as well as the advantages and disadvantages between hashing techniques and encryption are given.
Abstract: This article is an extension of previous research presenting the relevant factors related to environmental perceptions, residential community, and the design of a healing environment, which have effects on the well-being and requirements of Thai elderly. Research methodology began with observations and interviews in three case studies in terms of the management processes and environment design of similar existing projects in Thailand. The interview results were taken to summarize with related theories and literature. A questionnaire survey was designed for data collection to confirm the factors of requirements in a residential community intended for the Thai elderly. A structural equation model (SEM) was formulated to explain the cause-effect factors for the requirements of a residential community for Thai elderly. The research revealed that the requirements of a residential community for Thai elderly were classified into three groups when utilizing a technique for exploratory factor analysis. The factors were comprised of (1) requirements for general facilities and activities, (2) requirements for facilities related to health and security, and (3) requirements for facilities related to physical exercise in the residential community. The results from the SEM showed the background of elderly people had a direct effect on their requirements for a residential community from various aspects. The results should lead to the formulation of policies for design and management of residential communities for the elderly in order to enhance quality of life as well as both the physical and mental health of the Thai elderly.
Abstract: Determination of 90Sr in environmental samples has been widely developed with several radioanlytical methods and radiation measurement techniques since 90Sr is one of the most hazardous radionuclides produced from nuclear reactors. Liquid extraction technique using di-(2-ethylhexyl) phosphoric acid (HDEHP) to separate and purify 90Y and Cherenkov counting using liquid scintillation counter to determine 90Y in secular equilibrium to 90Sr was developed and performed at our institute, the Office of Atoms for Peace. The approach is inexpensive, non-laborious, and fast to analyse 90Sr in environmental samples. To validate our analytical performance for the accurate and precise criteria, determination of 90Sr using the IAEA-TEL-2016-04 ALMERA proficiency test samples were performed for statistical evaluation. The experiment used two spiked tap water samples and one naturally contaminated spruce needles sample from Austria collected shortly after the Chernobyl accident. Results showed that all three analyses were successfully passed in terms of both accuracy and precision criteria, obtaining “Accepted” statuses. The two water samples obtained the measured results of 15.54 Bq/kg and 19.76 Bq/kg, which had relative bias 5.68% and -3.63% for the Maximum Acceptable Relative Bias (MARB) 15% and 20%, respectively. And the spruce needles sample obtained the measured results of 21.04 Bq/kg, which had relative bias 23.78% for the MARB 30%. These results confirm our analytical performance of 90Sr determination in water and spruce needles samples using the same developed method.
Abstract: The convective and radiative heat transfer performance and entropy generation on forced convection through a direct absorption solar collector (DASC) is investigated numerically. Four different fluids, including Cu-water nanofluid, Al2O3-waternanofluid, TiO2-waternanofluid, and pure water are used as the working fluid. Entropy production has been taken into account in addition to the collector efficiency and heat transfer enhancement. Penalty finite element method with Galerkin’s weighted residual technique is used to solve the governing non-linear partial differential equations. Numerical simulations are performed for the variation of mass flow rate. The outcomes are presented in the form of isotherms, average output temperature, the average Nusselt number, collector efficiency, average entropy generation, and Bejan number. The results present that the rate of heat transfer and collector efficiency enhance significantly for raising the values of m up to a certain range.
Abstract: The population increase in Egypt is urging for horizontal land development which became a demand to allow the benefit of different natural resources and expand from the narrow Nile valley. However, this development is facing challenges preventing land development and agriculture development. Desertification and moving sand dunes in the west sector of Egypt are considered the major obstacle that is blocking the ideal land use and development. In the proposed research, the sandy soil is treated biologically using Bacillus pasteurii bacteria as these bacteria have the ability to bond the sand partials to change its state of loose sand to cemented sand, which reduces the moving ability of the sand dunes. The procedure of implementing the Microbial Induced Carbonate Precipitation Technique (MICP) technique is examined, and the different factors affecting on this process such as the medium of bacteria sample preparation, the optical density (OD600), the reactant concentration, injection rates and intervals are highlighted. Based on the findings of the MICP treatment for sandy soil, conclusions and future recommendations are reached.
Abstract: In this work, all optical Stimulated Brillouin Scattering (SBS) generated single sideband with suppressed carrier is presented to provide better efficiency. The generation of single sideband and enhanced carrier power signal using the SBS technique is further used to strengthen the low shifted sideband and to suppress the upshifted sideband. These generated single sideband signals are able to work at high frequency ranges. Also, generated single sideband is validated over 90 km transmission using single mode fiber with acceptable bit error rate. The results for an equivalent are then compared so that the acceptable technique is chosen and also the required quality for the optimum performance of the system is reported.
Abstract: The cotton leafworm, Spodoptera littoralis (Boisduval) is a major insect pest of vegetables and cotton crops in Egypt, and exhibits different levels of tolerance to certain insecticides. Chlorantraniliprole has been registered recently in Egypt for control this insect. The susceptibilities of three S. littoralis populations collected from El Behaira governorate, north Egypt to chlorantraniliprole were determined by leaf-dipping technique on 4th instar larvae. Obvious variation of toxicity was observed among the laboratory susceptible, and three field populations with LC50 values ranged between 1.53 µg/ml and 6.22 µg/ml. However, all the three field populations were less susceptible to chlorantraniliprole than a laboratory susceptible population. The most tolerant populations were sampled from El Delengat (ED) Province where S. littoralis had been frequently challenged by insecticides. Certain enzyme activity assays were carried out to be correlated with the mechanism of the observed field population tolerance. All field populations showed significantly enhanced activities of detoxification enzymes compared with the susceptible strain. The regression analysis between chlorantraniliprole toxicities and enzyme activities revealed that the highest correlation is between α-esterase or β-esterase (α-β-EST) activity and collected field strains susceptibility, otherwise this correlation is not significant (P > 0.05). Synergism assays showed the ED and susceptible strains could be synergized by known detoxification inhibitors such as piperonyl butoxide (PBO), triphenyl phosphate (TPP) and diethyl-maleate (DEM) at different levels (1.01-8.76-fold and 1.09-2.94 fold, respectively), TPP showed the maximum synergism in both strains. The results show that there is a correlation between the enzyme activity and tolerance, and carboxylic-esterase (Car-EST) is likely the main detoxification mechanism responsible for tolerance of S. littoralis to chlorantraniliprole.
Abstract: This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.
Abstract: Due to the acquisition of huge amounts of brain tumor magnetic resonance images (MRI) in clinics, it is very difficult for radiologists to manually interpret and segment these images within a reasonable span of time. Computer-aided diagnosis (CAD) systems can enhance the diagnostic capabilities of radiologists and reduce the time required for accurate diagnosis. An intelligent computer-aided technique for automatic detection of a brain tumor through MRI is presented in this paper. The technique uses the following computational methods; the Level Set for segmentation of a brain tumor from other brain parts, extraction of features from this segmented tumor portion using gray level co-occurrence Matrix (GLCM), and the Artificial Neural Network (ANN) to classify brain tumor images according to their respective types. The entire work is carried out on 50 images having five types of brain tumor. The overall classification accuracy using this method is found to be 98% which is significantly good.
Abstract: Because of the easy applying and not costing too much, ultrasonic pulse velocity (UPV) is one of the most used non-destructive techniques to determine concrete characteristics along with impact-echo, Schmidt rebound hammer (SRH) and pulse-echo. This article investigates the relationship between UPV and compressive strength of hybrid fiber reinforced concretes. Water/cement ratio (w/c) was kept at 0.4 for all concrete mixes. Compressive strength of concrete was targeted at 35 MPa. UPV testing and compressive strength tests were carried out at the curing age of 28 days. The UPV of concrete containing steel fibers has been found to be higher than plain concrete for all the testing groups. It is decided that there is not a certain relationship between fiber addition and strength.
Abstract: Large exhibition halls require a lot of energy to maintain comfortable atmosphere for the visitors viewing inside. One way of reducing the energy cost is to have thermal energy storage systems installed so that the thermal energy can be stored in the middle of night when the energy price is low and then used later when the price is high. To minimize the overall energy cost, however, we should be able to decide how much energy to save during which time period exactly. If we can foresee future energy load and the corresponding cost, we will be able to make such decisions reasonably. In this paper, we use machine learning technique to obtain models for predicting weather conditions and the number of visitors on hourly basis for the next day. Based on the energy load thus predicted, we build a cost-optimal daily operation plan for the thermal energy storage systems and cooling and heating facilities through simulation-based optimization.
Abstract: A compositional reservoir simulation model (CMG-GEM) was used for cyclic CO2 injection process in unconventional tight reservoir. Cyclic CO2 injection is an enhanced oil recovery process consisting of injection, shut-in, and production. The study of cyclic CO2 injection and hydrocarbon recovery in ultra-low permeability reservoirs is mainly a function of rock, fluid, and operational parameters. CMG-GEM was used to study several design parameters of cyclic CO2 injection process to distinguish the parameters with maximum effect on the oil recovery and to comprehend the behavior of cyclic CO2 injection in tight reservoir. On the other hand, permeability reduction induced by asphaltene precipitation is one of the major issues in the oil industry due to its plugging onto the porous media which reduces the oil productivity. In addition to asphaltene deposition, solubility of CO2 in the aquifer is one of the safest and permanent trapping techniques when considering CO2 storage mechanisms in geological formations. However, the effects of the above uncertain parameters on the process of CO2 enhanced oil recovery have not been understood systematically. Hence, it is absolutely necessary to study the most significant parameters which dominate the process. The main objective of this study is to improve techniques for designing cyclic CO2 injection process while considering the effects of asphaltene deposition and solubility of CO2 in the brine in order to prevent asphaltene precipitation, minimize CO2 emission, optimize cyclic CO2 injection, and maximize oil production.
Abstract: In recent years, the combined economic and emission power dispatch is one of the main problems of electrical power system. It aims to schedule the power generation of generators in order to minimize cost production and emission of harmful gases caused by fossil-fueled thermal units such as CO, CO2, NOx, and SO2. To solve this complicated multi-objective problem, an improved version of the particle swarm optimization technique that includes non-dominated sorting concept has been proposed. Valve point loading effects and system losses have been considered. The three-unit and ten-unit benchmark systems have been used to show the effectiveness of the suggested optimization technique for solving this kind of nonconvex problem. The simulation results have been compared with those obtained using genetic algorithm based method. Comparison results show that the proposed approach can provide a higher quality solution with better performance.
Abstract: Test data compression is an efficient method for reducing the test application cost. The problem of reducing test data has been addressed by researchers in three different aspects: Test Data Compression, Built-in-Self-Test (BIST) and Test set compaction. The latter two methods are capable of enhancing fault coverage with cost of hardware overhead. The drawback of the conventional methods is that they are capable of reducing the test storage and test power but when test data have redundant length of runs, no additional compression method is followed. This paper presents a modified Run Length Coding (RLC) technique with Multilevel Selective Huffman Coding (MLSHC) technique to reduce test data volume, test pattern delivery time and power dissipation in scan test applications where redundant length of runs is encountered then the preceding run symbol is replaced with tiny codeword. Experimental results show that the presented method not only improves the test data compression but also reduces the overall test data volume compared to recent schemes. Experiments for the six largest ISCAS-98 benchmarks show that our method outperforms most known techniques.
Abstract: Clustering is a well known data mining technique used in pattern recognition and information retrieval. The initial dataset to be clustered can either contain categorical or numeric data. Each type of data has its own specific clustering algorithm. In this context, two algorithms are proposed: the k-means for clustering numeric datasets and the k-modes for categorical datasets. The main encountered problem in data mining applications is clustering categorical dataset so relevant in the datasets. One main issue to achieve the clustering process on categorical values is to transform the categorical attributes into numeric measures and directly apply the k-means algorithm instead the k-modes. In this paper, it is proposed to experiment an approach based on the previous issue by transforming the categorical values into numeric ones using the relative frequency of each modality in the attributes. The proposed approach is compared with a previously method based on transforming the categorical datasets into binary values. The scalability and accuracy of the two methods are experimented. The obtained results show that our proposed method outperforms the binary method in all cases.
Abstract: Economic Load Dispatch (ELD) proves to be a vital optimization process in electric power system for allocating generation amongst various units to compute the cost of generation, the cost of emission involving global warming gases like sulphur dioxide, nitrous oxide and carbon monoxide etc. In this dissertation, we emphasize ramp rate constriction factor based particle swarm optimization (RRCPSO) for analyzing various performance objectives, namely cost of generation, cost of emission, and a dual objective function involving both these objectives through the experimental simulated results. A 6-unit 30 bus IEEE test case system has been utilized for simulating the results involving improved weight factor advanced ramp rate limit constraints for optimizing total cost of generation and emission. This method increases the tendency of particles to venture into the solution space to ameliorate their convergence rates. Earlier works through dispersed PSO (DPSO) and constriction factor based PSO (CPSO) give rise to comparatively higher computational time and less good optimal solution at par with current dissertation. This paper deals with ramp rate and constriction factor based well defined ramp rate PSO to compute various objectives namely cost, emission and total objective etc. and compares the result with DPSO and weight improved PSO (WIPSO) techniques illustrating lesser computational time and better optimal solution.
Abstract: The majority of wireless power transfer (WPT) systems transfer power in a directional manner. This paper describes a discrete exciting voltage control technique for WPT via magnetic resonant coupling with two orthogonal transmitter coils (2D omni-directional WPT system) which can maximize the power transfer efficiency in response to the change of coupling status. The theory allows the equations of the efficiency of the system to be determined at all the rate of the mutual inductance. The calculated results are included to confirm the advantage to one directional WPT system and the validity of the theory and the equations.
Abstract: The motivation of our work is to detect different
terrain types traversed by a robot based on acoustic data from the
robot-terrain interaction. Different acoustic features and classifiers
were investigated, such as Mel-frequency cepstral coefficient and
Gamma-tone frequency cepstral coefficient for the feature extraction,
and Gaussian mixture model and Feed forward neural network for the
classification. We analyze the system’s performance by comparing
our proposed techniques with some other features surveyed from
distinct related works. We achieve precision and recall values between
87% and 100% per class, and an average accuracy at 95.2%. We also
study the effect of varying audio chunk size in the application phase
of the models and find only a mild impact on performance.
Abstract: Machine vision system provides automatic inspection to reduce manufacturing costs considerably. However, only a few principles have been found to optimize machine vision system and help it function more accurately in industrial practice. Mostly, there were complicated and impractical design techniques to improve the accuracy of machine vision system. This paper discusses implementing the Six Sigma Define, Measure, Analyze, Improve, and Control (DMAIC) approach to optimize the setup parameters of machine vision system when it is used as a direct measurement technique. This research follows a case study showing how Six Sigma DMAIC methodology has been put into use.