Artificial Neural Network Development by means of Genetic Programming with Graph Codification

The development of Artificial Neural Networks (ANNs) is usually a slow process in which the human expert has to test several architectures until he finds the one that achieves best results to solve a certain problem. This work presents a new technique that uses Genetic Programming (GP) for automatically generating ANNs. To do this, the GP algorithm had to be changed in order to work with graph structures, so ANNs can be developed. This technique also allows the obtaining of simplified networks that solve the problem with a small group of neurons. In order to measure the performance of the system and to compare the results with other ANN development methods by means of Evolutionary Computation (EC) techniques, several tests were performed with problems based on some of the most used test databases. The results of those comparisons show that the system achieves good results comparable with the already existing techniques and, in most of the cases, they worked better than those techniques.

DWT Based Robust Watermarking Embed Using CRC-32 Techniques

As far as the latest technological improvements are concerned, digital systems more become popular than the past. Despite this growing demand to the digital systems, content copy and attack against the digital cinema contents becomes a serious problem. To solve the above security problem, we propose “traceable watermarking using Hash functions for digital cinema system. Digital Cinema is a great application for traceable watermarking since it uses watermarking technology during content play as well as content transmission. The watermark is embedded into the randomly selected movie frames using CRC-32 techniques. CRC-32 is a Hash function. Using it, the embedding position is distributed by Hash Function so that any party cannot break off the watermarking or will not be able to change. Finally, our experimental results show that proposed DWT watermarking method using CRC-32 is much better than the convenient watermarking techniques in terms of robustness, image quality and its simple but unbreakable algorithm.

Daily Global Solar Radiation Modeling Using Multi-Layer Perceptron (MLP) Neural Networks

Predict daily global solar radiation (GSR) based on meteorological variables, using Multi-layer perceptron (MLP) neural networks is the main objective of this study. Daily mean air temperature, relative humidity, sunshine hours, evaporation, wind speed, and soil temperature values between 2002 and 2006 for Dezful city in Iran (32° 16' N, 48° 25' E), are used in this study. The measured data between 2002 and 2005 are used to train the neural networks while the data for 214 days from 2006 are used as testing data.

N-Grams: A Tool for Repairing Word Order Errors in Ill-formed Texts

This paper presents an approach for repairing word order errors in English text by reordering words in a sentence and choosing the version that maximizes the number of trigram hits according to a language model. A possible way for reordering the words is to use all the permutations. The problem is that for a sentence with length N words the number of all permutations is N!. The novelty of this method concerns the use of an efficient confusion matrix technique for reordering the words. The confusion matrix technique has been designed in order to reduce the search space among permuted sentences. The limitation of search space is succeeded using the statistical inference of N-grams. The results of this technique are very interesting and prove that the number of permuted sentences can be reduced by 98,16%. For experimental purposes a test set of TOEFL sentences was used and the results show that more than 95% can be repaired using the proposed method.

Genetic Algorithm Based Design of Fuzzy Logic Power System Stabilizers in Multimachine Power System

This paper presents an approach for the design of fuzzy logic power system stabilizers using genetic algorithms. In the proposed fuzzy expert system, speed deviation and its derivative have been selected as fuzzy inputs. In this approach the parameters of the fuzzy logic controllers have been tuned using genetic algorithm. Incorporation of GA in the design of fuzzy logic power system stabilizer will add an intelligent dimension to the stabilizer and significantly reduces computational time in the design process. It is shown in this paper that the system dynamic performance can be improved significantly by incorporating a genetic-based searching mechanism. To demonstrate the robustness of the genetic based fuzzy logic power system stabilizer (GFLPSS), simulation studies on multimachine system subjected to small perturbation and three-phase fault have been carried out. Simulation results show the superiority and robustness of GA based power system stabilizer as compare to conventionally tuned controller to enhance system dynamic performance over a wide range of operating conditions.

Decision Support System for Flood Crisis Management using Artificial Neural Network

This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.

Genetically Optimized TCSC Controller for Transient Stability Improvement

This paper presents a procedure for modeling and tuning the parameters of Thyristor Controlled Series Compensation (TCSC) controller in a multi-machine power system to improve transient stability. First a simple transfer function model of TCSC controller for stability improvement is developed and the parameters of the proposed controller are optimally tuned. Genetic algorithm (GA) is employed for the optimization of the parameter-constrained nonlinear optimization problem implemented in a simulation environment. By minimizing an objective function in which the oscillatory rotor angle deviations of the generators are involved, transient stability performance of the system is improved. The proposed TCSC controller is tested on a multi-machine system and the simulation results are presented. The nonlinear simulation results validate the effectiveness of proposed approach for transient stability improvement in a multimachine power system installed with a TCSC. The simulation results also show that the proposed TCSC controller is also effective in damping low frequency oscillations.

Comparison of Nutritional and Chemical Parameters of Soymilk and Cow milk

Cow milk, is a product of the mammary gland and soymilk is a beverage made from soybeans; it is the liquid that remains after soybeans are soaked. In this research effort, we compared nutritional parameters of this two kind milk such as total fat, fiber, protein, minerals (Ca, Fe and P), fatty acids, carbohydrate, lactose, water, total solids, ash, pH, acidity and calories content in one cup (245 g). Results showed soymilk contains 4.67 grams of fat, 0.52 of fatty acids, 3.18 of fiber, 6.73 of protein, 4.43 of carbohydrate, 0.00 of lactose, 228.51 of water, 10.40 of total solids and 0.66 of ash, also 9.80 milligrams of Ca, 1.42 of Fe, and 120.05 of P, 79 Kcal of calories, pH=6.74 and acidity was 0.24%. Cow milk contains 8.15 grams of fat, 5.07 of fatty acids, 0.00 of fiber, 8.02 of protein, 11.37 of carbohydrate, ´Çá4.27 of lactose, 214.69 of water, 12.90 of total solids, 1.75 of ash, 290.36 milligrams of Ca, 0.12 of Fe, and 226.92 of P, 150 Kcal of calories, pH=6.90 and acidity was 0.21% . Soy milk is one of plant-based complete proteins and cow milk is a rich source of nutrients as well. Cow milk is containing near twice as much fat as and ten times more fatty acids do soymilk. Cow milk contains greater amounts of mineral (except Fe) it contain more than three hundred times the amount of Ca and nearly twice the amount of P as does soymilk but soymilk contains more Fe (ten time more) than does cow milk. Cow milk and soy milk contain nearly identical amounts of protein and water and fiber is a big plus, dairy has none. Although what we choose to drink is really a mater of personal preference and our health objectives but looking at the comparison, soy looks like healthier choices.

Effective Strategies for Teaching Cultural Competency to MSW Students in a Global Society

An ethical mandate of the social work profession in the United States is that BSW and MSW graduates are sufficiently prepared to both understand diverse cultural values and beliefs and offer services that are culturally sensitive and relevant to clients. This skill set is particularly important for social workers in the 21st Century, given the increasing globalization of the U.S. and world. The purpose of this paper is to outline a pedagogical model for teaching cultural competency that resulted in a significant increase in cultural competency for MSW graduates at Western Kentucky University (WKU). More specifically, this model is predicated on five specific culturally sensitive principles and activities that were found to be highly effective in conveying culturally relevant knowledge and skills to MSW students at WKU. Future studies can assess the effectiveness of these principles in other MSW programs across the U.S. and abroad.

Upgrading Performance of DSR Routing Protocol in Mobile Ad Hoc Networks

Routing in mobile ad hoc networks is a challenging task because nodes are free to move randomly. In DSR like all On- Demand routing algorithms, route discovery mechanism is associated with great delay. More Clearly in DSR routing protocol to send route reply packet, when current route breaks, destination seeks a new route. In this paper we try to change route selection mechanism proactively. We also define a link stability parameter in which a stability value is assigned to each link. Given this feature, destination node can estimate stability of routes and can select the best and more stable route. Therefore we can reduce the delay and jitter of sending data packets.

Application of Tacit Knowledge from Professional Packaging Designer for Teaching Packaging Design

In the package design industry, there are a lot of tacit knowledge resided within each designer. The objectives are to capture them and compile it to be used as a teaching resource and to create a video clip of package design process as well as to evaluate its quality and learning effectiveness. Interview were used as a technique for capturing knowledge in brand design concept, differentiation, recognition, rank of recognition factor, consumer survey, knowledge about marketing, research, graphic design, the effect of color, and law and regulation. Video clip about package design were created. The clip consisted of both the speech and clip of actual process. The quality of the video in term of media was ranked as good while the content was ranked as excellent. The students- score on post-test was significantly greater than that of pretest (p>0.001).

Effects of Retaining Skillful Employees on the Career Management: A Field Study

Enterprises need a strategic plan to retain their skillful employees and provide their career management, sustain their existence, to have growth and leadership qualities, to reach the objectives to increase the value of the enterprise and to not to be affected from changing demographic structure. In the cases when the long term career expectations of skillful employees are in integrity with the enterprise’s interests, skill management process is directly related to the career management. With a long term plan, the enterprises should cover the labor force need that may arise in the future by using systematic career development programs and be prepared against developments for all times. Skill management is considered as a practice with which career mobility is planned for the skillful employee to be prepared for high level positions. Career planning is the planning of an employee’s progress or promotion within an organization for which he works by developing his knowledge, skills, abilities and motives. Career planning is considered as an individual’s planning his future and the position which he wants to have, the area which he want to work in, the objectives which he want to reach. With the aim of contributing the abovementioned discussion process, career management concept and its perception manner are examined in this study in a comparative manner.

A Supplier-Manufacturer Relationship Model for Teak Forest Carbon Sequestration and Teak Log Demand Fulfillment with Sustainability Consideration

Availability of raw materials is important for Indonesia as a furniture exporting country. Teak log as raw materials is supplied to the furniture industry by Perum Perhutani (PP). PP needs to involve carbon trading for nature conservation. PP also has an obligation in the Corporate Social Responsibility program. PP and furniture industry also must prosecute the regulations related to ecological issues and labor rights. This study has the objective to create the relationship model between supplier and manufacturer to fulfill teak log demand that involving teak forest carbon sequestration. A model is formulated as Goal Programming to get the favorable solution for teak log procurement and support carbon sequestration that considering economical, ecological, and social aspects of both supplier and manufacturer. The results show that the proposed model can be used to determine the teak log quantity involving carbon trading to achieve the seven goals to be satisfied the sustainability considerations.

Reducing Greenhouse Gas Emissions by Recyclable Material Bank Project of Universities in Central Region of Thailand

This research studied recycled waste by the Recyclable Material Bank Project of 4 universities in the central region of Thailand for the evaluation of reducing greenhouse gas emissions compared with landfilling activity during July 2012 to June 2013. The results showed that the projects collected total amount of recyclable wastes of about 911,984.80 kilograms. Office paper had the largest amount among these recycled wastes (50.68% of total recycled waste). Groups of recycled waste can be prioritized from high to low according to their amount as paper, plastic, glass, mixed recyclables, and metal, respectively. The project reduced greenhouse gas emissions equivalent to about 2814.969 metric tons of carbon dioxide. The most significant recycled waste that affects the reduction of greenhouse gas emissions is office paper which is 70.16% of total reduced greenhouse gasses emission. According to amount of reduced greenhouse gasses emission, groups of recycled waste can be prioritized from high to low significances as paper, plastic, metals, mixed recyclables, and glass, respectively.

A Qualitative Evaluation of an Instrument for Measuring the Influence of Factors Affecting Use of Business-to-Employee (B2E) Portals

B2E portals represent a new class of web-based information technologies which many organisations are introducing in recent years to stay in touch with their distributed workforces and enable them to perform value added activities for organisations. However, actual usage of these emerging systems (measured using suitable instruments) has not been reported in the contemporary scholarly literature. We argue that many of the instruments to measure usage of various types of IT-enabled information systems are not directly applicable for B2E portals because they were developed for the context of traditional mainframe and PC-based information systems. It is therefore important to develop a new instrument for web-based portal technologies aimed at employees. In this article, we report on the development and initial qualitative evaluation of an instrument that seeks to operationaise a set of independent factors affecting the usage of portals by employees. The proposed instrument is useful to IT/e-commerce researchers and practitioners alike as it enhances their confidence in predicting employee usage of portals in organisations.

Simulation and Statistical Analysis of Motion Behavior of a Single Rockfall

The impact force of a rockfall is mainly determined by its moving behavior and velocity, which are contingent on the rock shape, slope gradient, height, and surface roughness of the moving path. It is essential to precisely calculate the moving path of the rockfall in order to effectively minimize and prevent damages caused by the rockfall. By applying the Colorado Rockfall Simulation Program (CRSP) program as the analysis tool, this research studies the influence of three shapes of rock (spherical, cylindrical and discoidal) and surface roughness on the moving path of a single rockfall. As revealed in the analysis, in addition to the slope gradient, the geometry of the falling rock and joint roughness coefficient ( JRC ) of the slope are the main factors affecting the moving behavior of a rockfall. On a single flat slope, both the rock-s bounce height and moving velocity increase as the surface gradient increases, with a critical gradient value of 1:m = 1 . Bouncing behavior and faster moving velocity occur more easily when the rock geometry is more oval. A flat piece tends to cause sliding behavior and is easily influenced by the change of surface undulation. When JRC

Food Habits and Nutritional Status of Fiji Rugby Players

The 15-a-side Fiji rugby team trains well in preparations for any rugby competition but rarely performs to expectations. In order to help the Fiji local based rugby players to identify some key basic areas in improving their performance, a series of workshops were conducted to assess their nutritional status and dietary habits in relation to energy demand during rugby matches. The nutrition workshop included the administration of questionnaires to 19 local based rugby players, requesting the following information: usual food intakes, training camp food intakes, carbohydrate loading, pre-game meals and post-game meals. The study revealed that poor eating habits of the players resulted in the low carbohydrate intake, which may have contributed to increase levels of fatigue leading to loss of stamina even before the second half of the game. It appears that the diet of most 15-a-side players does not provide enough energy to enable them to last the full eightyminutes of the game.

Investigation on Feature Extraction and Classification of Medical Images

In this paper we present the deep study about the Bio- Medical Images and tag it with some basic extracting features (e.g. color, pixel value etc). The classification is done by using a nearest neighbor classifier with various distance measures as well as the automatic combination of classifier results. This process selects a subset of relevant features from a group of features of the image. It also helps to acquire better understanding about the image by describing which the important features are. The accuracy can be improved by increasing the number of features selected. Various types of classifications were evolved for the medical images like Support Vector Machine (SVM) which is used for classifying the Bacterial types. Ant Colony Optimization method is used for optimal results. It has high approximation capability and much faster convergence, Texture feature extraction method based on Gabor wavelets etc..

Crystalline Graphene Nanoribbons with Atomically Smooth Edges via a Novel Physico- Chemical Route

A novel physico-chemical route to produce few layer graphene nanoribbons with atomically smooth edges is reported, via acid treatment (H2SO4:HNO3) followed by characteristic thermal shock processes involving extremely cold substances. Samples were studied by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy and X-ray photoelectron spectroscopy. This method demonstrates the importance of having the nanotubes open ended for an efficient uniform unzipping along the nanotube axis. The average dimensions of these nanoribbons are approximately ca. 210 nm wide and consist of few layers, as observed by transmission electron microscopy. The produced nanoribbons exhibit different chiralities, as observed by high resolution transmission electron microscopy. This method is able to provide graphene nanoribbons with atomically smooth edges which could be used in various applications including sensors, gas adsorption materials, composite fillers, among others.

Automated Detection of Alzheimer Disease Using Region Growing technique and Artificial Neural Network

Alzheimer is known as the loss of mental functions such as thinking, memory, and reasoning that is severe enough to interfere with a person's daily functioning. The appearance of Alzheimer Disease symptoms (AD) are resulted based on which part of the brain has a variety of infection or damage. In this case, the MRI is the best biomedical instrumentation can be ever used to discover the AD existence. Therefore, this paper proposed a fusion method to distinguish between the normal and (AD) MRIs. In this combined method around 27 MRIs collected from Jordanian Hospitals are analyzed based on the use of Low pass -morphological filters to get the extracted statistical outputs through intensity histogram to be employed by the descriptive box plot. Also, the artificial neural network (ANN) is applied to test the performance of this approach. Finally, the obtained result of t-test with confidence accuracy (95%) has compared with classification accuracy of ANN (100 %). The robust of the developed method can be considered effectively to diagnose and determine the type of AD image.