Locating Critical Failure Surface in Rock Slope Stability with Hybrid Model Based on Artificial Immune System and Cellular Learning Automata (CLA-AIS)

Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.

Particle Swarm Optimization Approach on Flexible Structure at Wiper Blade System

Application of flexible structures has been significantly, increased in industry and aerospace missions due to their contributions and unique advantages over the rigid counterparts. In this paper, vibration analysis of a flexible structure i.e., automobile wiper blade is investigated and controlled. The wiper generates unwanted noise and vibration during the wiping the rain and other particles on windshield which may cause annoying noise in different ranges of frequency. A two dimensional analytical modeled wiper blade whose model accuracy is verified by numerical studies in literature is considered in this study. Particle swarm optimization (PSO) is employed in alliance with input shaping (IS) technique in order to control or to attenuate the amplitude level of unwanted noise/vibration of the wiper blade.

Sustainable Water Management for Tourist Accommodations is Amphawa, Samut Songkram, Thailand

This study aims to initiate sustainable water management for tourist accommodations in Amphawa, Samut Songkram Province, Thailand. Wastewater generated by tourist accommodation was conducted in 10 homestays and resorts in Amphawa during August – October, 2011. The prominent parameters which are of pH, Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Fat Oil and Grease (FOG), Nitrate (No3-), and Phosphate (PO43-) were conducted monthly. The results revealed that some parameters were over national water quality standard (Class II). Especially, 90% of tourist accommodations have been recorded that FOG was over the standard of wastewater quality from accommodation (group I: total room of accommodation less than 200 rooms). Therefore, grease trap and natural treatment should be utilized in tourist accommodations in order to reduce the discharged of fat, oil, and grease from tourism activities. In addition, number of tourists also relate statistically with BOD and Nitrate at 0.05 level of significance.

A Quality Optimization Approach: An Application on Next Generation Networks

The next generation wireless systems, especially the cognitive radio networks aim at utilizing network resources more efficiently. They share a wide range of available spectrum in an opportunistic manner. In this paper, we propose a quality management model for short-term sub-lease of unutilized spectrum bands to different service providers. We built our model on competitive secondary market architecture. To establish the necessary conditions for convergent behavior, we utilize techniques from game theory. Our proposed model is based on potential game approach that is suitable for systems with dynamic decision making. The Nash equilibrium point tells the spectrum holders the ideal price values where profit is maximized at the highest level of customer satisfaction. Our numerical results show that the price decisions of the network providers depend on the price and QoS of their own bands as well as the prices and QoS levels of their opponents- bands.

Effect of Phosphate Solubilization Microorganisms (PSM) and Plant Growth Promoting Rhizobacteria (PGPR) on Yield and Yield Components of Corn (Zea mays L.)

In order to study the effect of phosphate solubilization microorganisms (PSM) and plant growth promoting rhizobacteria (PGPR) on yield and yield components of corn Zea mays (L. cv. SC604) an experiment was conducted at research farm of Sari Agricultural Sciences and Natural Resources University, Iran during 2007. Experiment laid out as split plot based on randomized complete block design with three replications. Three levels of manures (consisted of 20 Mg.ha-1 farmyard manure, 15 Mg.ha-1 green manure and check or without any manures) as main plots and eight levels of biofertilizers (consisted of 1-NPK or conventional fertilizer application; 2-NPK+PSM+PGPR; 3 NP50%K+PSM+PGPR; 4- N50%PK+PSM +PGPR; 5-N50%P50%K+PSM+ PGPR; 6-PK+PGPR; 7- NK+PSM and 8-PSM+PGPR) as sub plots were treatments. Results showed that farmyard manure application increased row number, ear weight, grain number per ear, grain yield, biological yield and harvest index compared to check. Furthermore, using of PSM and PGPR in addition to conventional fertilizer applications (NPK) could improve ear weight, row number and grain number per row and ultimately increased grain yield in green manure and check plots. According to results in all fertilizer treatments application of PSM and PGPR together could reduce P application by 50% without any significant reduction of grain yield. However, this treatment could not compensate 50% reduction of N application.

A High Accuracy Measurement Circuit for Soil Moisture Detection

The study of soil for agriculture purposes has remained the main focus of research since the beginning of civilization as humans- food related requirements remained closely linked with the soil. The study of soil has generated an interest among the researchers for very similar other reasons including transmission, reflection and refraction of signals for deploying wireless underground sensor networks or for the monitoring of objects on (or in ) soil in the form of better understanding of soil electromagnetic characteristics properties. The moisture content has been very instrumental in such studies as it decides on the resistance of the soil, and hence the attenuation on signals traveling through soil or the attenuation the signals may suffer upon their impact on soil. This work is related testing and characterizing a measurement circuit meant for the detection of moisture level content in soil.

River Analysis System Model for Proposed Weirs at Downstream of Large Dam, Thailand

This research was conducted in the Lower Ping River Basin downstream of the Bhumibol Dam and the Lower Wang River Basin in Tak Province, Thailand. Most of the tributary streams of the Ping can be considered as ungauged catchments. There are 10- pumping station installation at both river banks of the Ping in Tak Province. Recently, most of them could not fully operate due to the water amount in the river below the level that would be pumping, even though included water from the natural river and released flow from the Bhumibol Dam. The aim of this research was to increase the performance of those pumping stations using weir projects in the Ping. Therefore, the river analysis system model (HEC-RAS) was applied to study the hydraulic behavior of water surface profiles in the Ping River with both cases of existing conditions and proposed weirs during the violent flood in 2011 and severe drought in 2013. Moreover, the hydrologic modeling system (HMS) was applied to simulate lateral streamflow hydrograph from ungauged catchments of the Ping. The results of HEC-RAS model calibration with existing conditions in 2011 showed best trial roughness coefficient for the main channel of 0.026. The simulated water surface levels fitted to observation data with R2 of 0.8175. The model was applied to 3 proposed cascade weirs with 2.35 m in height and found surcharge water level only 0.27 m higher than the existing condition in 2011. Moreover, those weirs could maintain river water levels and increase of those pumping performances during less river flow in 2013.

Integrating Artificial Neural Network and Taguchi Method on Constructing the Real Estate Appraisal Model

In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Strategies for Development of Information Society in Montenegro

Creation of information society, or in other words, a society based on knowledge, has wide consequences, both on individual and complete society, and in general – on a economy of one country. Development and implementation of ICT represents a stimulant for economic growth. On individual level, knowledge, skills and information gathered using ICT, are expanding individual possibilities of persons, enabling them to have access to timely sensitive information, such as market prices or investment conditions, possibilities to access Government-s or private development funds, etc. By doing so, productivity is increased both on individual and national level and therefore social wellbeing in general. In one word, creation of information society - a knowledge society is happening. This work will describe challenges and strategies that will follow the development as well as obstacles in creating information society – knowledge society in Montenegro.

Influence of Cultivar and Storage Conditions in Anthocyanin Content and Radical-Scavenging Activity of Strawberry Jams

The strawberry jam is rich in bioactive compounds. It is economically and commercially important and widely consumed. Different strawberries cultivars can be used for its preparation, however, a careful selection should be performed to guarantee the preservation of bioactive compounds during jam storage. Two strawberry cultivars (Camarosa and American 13) were analyzed by HPLC, three anthocyanins: cyanidin-3-glucoside, pelargonidin-3- glucoside and pelargonidin-3-rutinoside were quantified. Camarosa strawberries presented significantly higher concentration of anthocyanins (p

A Method for Iris Recognition Based on 1D Coiflet Wavelet

There have been numerous implementations of security system using biometric, especially for identification and verification cases. An example of pattern used in biometric is the iris pattern in human eye. The iris pattern is considered unique for each person. The use of iris pattern poses problems in encoding the human iris. In this research, an efficient iris recognition method is proposed. In the proposed method the iris segmentation is based on the observation that the pupil has lower intensity than the iris, and the iris has lower intensity than the sclera. By detecting the boundary between the pupil and the iris and the boundary between the iris and the sclera, the iris area can be separated from pupil and sclera. A step is taken to reduce the effect of eyelashes and specular reflection of pupil. Then the four levels Coiflet wavelet transform is applied to the extracted iris image. The modified Hamming distance is employed to measure the similarity between two irises. This research yields the identification success rate of 84.25% for the CASIA version 1.0 database. The method gives an accuracy of 77.78% for the left eyes of MMU 1 database and 86.67% for the right eyes. The time required for the encoding process, from the segmentation until the iris code is generated, is 0.7096 seconds. These results show that the accuracy and speed of the method is better than many other methods.

Effect of Information System Strategies on Supply Chain Strategies and Supply Chain Performance

In order to achieve competitive advantage and better performance of firm, supply chain management (SCM) strategy should support and drive forward business strategy. It means that supply chain should be aligned with business strategy, at the same time supply chain (SC) managers need to use appropriate information system (IS) solution to support their strategy, which would lead to stay competitive. There are different kinds of IS strategies which enable managers to meet the SC requirement by selecting the best IS strategy. Therefore, it is important to align IS strategies and practices with SC strategies and practices, which could help us to plan for an IS application that supports and enhances a SCMS. In this study, aligning IS with SC in strategy level is considered. The main aim of this paper is to align the various IS strategies with SCM strategies and demonstrate their impact on SC and firm performance.

The Framework for Adaptive Games for Mobile Application Using Neural Networks

The rapid development of the BlackBerry games industry and its development goals were not just for entertainment, but also used for educational of students interactively. Unfortunately the development of adaptive educational games on BlackBerry in Indonesian language that interesting and entertaining for learning process is very limited. This paper shows the research of development of novel adaptive educational games for students who can adjust the difficulty level of games based on the ability of the user, so that it can motivate students to continue to play these games. We propose a method where these games can adjust the level of difficulty, based on the assessment of the results of previous problems using neural networks with three inputs in the form of percentage correct, the speed of answer and interest mode of games (animation / lessons) and 1 output. The experimental results are presented and show the adaptive games are running well on mobile devices based on BlackBerry platform

Studying on ARINC653 Partition Run-time Scheduling and Simulation

Avionics software is safe-critical embedded software and its architecture is evolving from traditional federated architectures to Integrated Modular Avionics (IMA) to improve resource usability. ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in Safety-critical avionics Real-time operating systems. Arinc653 uses two-level scheduling strategies, but current modeling tools only apply to simple problems of Arinc653 two-level scheduling, which only contain time property. In avionics industry, we are always manually allocating tasks and calculating the timing table of a real-time system to ensure it-s running as we design. In this paper we represent an automatically generating strategy which applies to the two scheduling problems with dependent constraints in Arinc653 partition run-time environment. It provides the functionality of automatic generation from the task and partition models to scheduling policy through allocating the tasks to the partitions while following the constraints, and then we design a simulating mechanism to check whether our policy is schedulable or not

Determination of Effective Variables on Arachidonic Acid Production by Mortierella alpina CBS 754.68in Solid-State Fermentation using Plackett-Burman Screening Design

In the present study, the oleaginous fungus Mortierella alpina CBS 754.68 was screened for arachidonic acidproduction using inexpensive agricultural by-products as substrate. Four oilcakes were analysed to choose the best substrate among them. Sunflower oilcake was the most effective substrate for ARA production followed by soybean, colza and olive oilcakes. In the next step, seven variables including substrate particle size, moisture content, time, temperature, yeast extract supply, glucose supply and glutamate supply were surveyed and effective variables for ARA production were determined using a Plackett-Burman screening design. Analysis results showed that time (12 days), substrate particle size (1-1.4 mm) and temperature (20ºC) were the most effective variables for the highest level of ARA production respectively.

Simple Agents Benefit Only from Simple Brains

In order to answer the general question: “What does a simple agent with a limited life-time require for constructing a useful representation of the environment?" we propose a robot platform including the simplest probabilistic sensory and motor layers. Then we use the platform as a test-bed for evaluation of the navigational capabilities of the robot with different “brains". We claim that a protocognitive behavior is not a consequence of highly sophisticated sensory–motor organs but instead emerges through an increment of the internal complexity and reutilization of the minimal sensory information. We show that the most fundamental robot element, the short-time memory, is essential in obstacle avoidance. However, in the simplest conditions of no obstacles the straightforward memoryless robot is usually superior. We also demonstrate how a low level action planning, involving essentially nonlinear dynamics, provides a considerable gain to the robot performance dynamically changing the robot strategy. Still, however, for very short life time the brainless robot is superior. Accordingly we suggest that small organisms (or agents) with short life-time does not require complex brains and even can benefit from simple brain-like (reflex) structures. To some extend this may mean that controlling blocks of modern robots are too complicated comparative to their life-time and mechanical abilities.

Effects of Adding Different Levels of Anaerobic Fungi on Cellulase Activity of Ostrich Digestive Tract-s Microorganisms under in Vitro Condition

the objective of this study is to measure the levels of cellulas activity of ostrich GI microorganisms, and comparing it with the levels of cellulas activity of rumen-s microorganisms, and also to estimate the probability of increasing enzyme activity with injecting different dosages (30%, 50% and 70%) of pure anaerobic goat rumen fungi. The experiment was conducted in laboratory and under a complete anaerobic condition (in vitro condition). 40 ml of “CaldWell" medium and 1.4g wheat straw were placed in incubator for an hour. The cellulase activity of ostrich microorganisms was compared with other treatments, and then different dosages (30%, 50% and 70%) of pure anaerobic goat rumen fungi were injected to ostrich microorganism-s media. Due to the results, cattle and goat with 2.13 and 2.08 I.U (international units) respectively showed the highest activity and ostrich with 0.91 (I.U) had the lowest cellulose activity (p < 0.05). Injecting 30% and 50% of anaerobic fungi had no significant incensement in enzyme activity, but with injecting 70% of rumen fungi to ostrich microorganisms culture a significant increase was observed 1.48 I.U. (p < 0.05).

How Learning Efficiency Affects Job Performance Effectiveness

The purpose of this research was to study the influence of learning efficiency on local accountants’ job performance effectiveness. This paper drew upon the survey data collected from 335 local accountants survey conducted at Nakhon Ratchasima province, Thailand. The statistics utilized in this paper included percentage, mean, standard deviation, and regression analysis. The findings revealed that the majority of samples were between 31-40 years old, married, held an undergraduate degree, and had an average income between 10,000-15,000 baht. The majority of respondents had less than five years of accounting experience and worked for local administrations. The overall learning efficiency score was in the highest level while the local accountants’ job performance effectiveness score was also in the high level. The hypothesis testing’s result disclosed that learning efficiency factors which were knowledge, Skill, and Attitude had an influence on local accountants’ job the performance effectiveness.

Multilevel Activation Functions For True Color Image Segmentation Using a Self Supervised Parallel Self Organizing Neural Network (PSONN) Architecture: A Comparative Study

The paper describes a self supervised parallel self organizing neural network (PSONN) architecture for true color image segmentation. The proposed architecture is a parallel extension of the standard single self organizing neural network architecture (SONN) and comprises an input (source) layer of image information, three single self organizing neural network architectures for segmentation of the different primary color components in a color image scene and one final output (sink) layer for fusion of the segmented color component images. Responses to the different shades of color components are induced in each of the three single network architectures (meant for component level processing) by applying a multilevel version of the characteristic activation function, which maps the input color information into different shades of color components, thereby yielding a processed component color image segmented on the basis of the different shades of component colors. The number of target classes in the segmented image corresponds to the number of levels in the multilevel activation function. Since the multilevel version of the activation function exhibits several subnormal responses to the input color image scene information, the system errors of the three component network architectures are computed from some subnormal linear index of fuzziness of the component color image scenes at the individual level. Several multilevel activation functions are employed for segmentation of the input color image scene using the proposed network architecture. Results of the application of the multilevel activation functions to the PSONN architecture are reported on three real life true color images. The results are substantiated empirically with the correlation coefficients between the segmented images and the original images.

An Application of a Cost Minimization Model in Determining Safety Stock Level and Location

In recent decades, the lean methodology, and the development of its principles and concepts have widely been applied in supply chain management. One of the most important strategies of being lean is having efficient inventory within the chain. On the other hand, managing inventory efficiently requires appropriate management of safety stock in order to protect against increasing stretch in the breaking points of the supply chain, which in turn can result in possible reduction of inventory. This paper applies a safety stock cost minimization model in a manufacturing company. The model results in optimum levels and locations of safety stock within the company-s supply chain in order to minimize total logistics costs.