Search results for: individual variables
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2099

Search results for: individual variables

1199 Evaluation of Degree and the Effect of Order in the Family on Violence against Children A Survey among Guidance School Students in Gilanegharb City in Iran

Authors: Javadi Alimohammad, Javadi Maryam, Feizi Fereidoon

Abstract:

A review of the literature found that Domestic violence and child maltreatment co-occur in many families, the purpose of this study attempts to emphasize the factors relating to intra-family relationships (order point of view) on violence against the children, For this purpose a survey technique on the sample size amounted 200 students of governmental guidance schools of city of Gilanegharb in country of Iran were considered. For measurement of violence against the children (VAC) the CTS scaled has been used .The results showed that children have experienced the violence more than once during the last year. degree of order in family is high. Explanation result indicated that the order variables in family including collective thinking, empathy, communal co-circumstance have significant effects on VAC.

Keywords: Violence, domestic violence, violence against children, order, guidance school, family, children.

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1198 Design of a Non-linear Observer for VSI Fed Synchronous Motor

Authors: P. Ramana , K. Alice Mary, M. Surya Kalavathi, M. Phani Kumar

Abstract:

This paper discusses two observers, which are used for the estimation of parameters of PMSM. Former one, reduced order observer, which is used to estimate the inaccessible parameters of PMSM. Later one, full order observer, which is used to estimate all the parameters of PMSM even though some of the parameters are directly available for measurement, so as to meet with the insensitivity to the parameter variation. However, the state space model contains some nonlinear terms i.e. the product of different state variables. The asymptotic state observer, which approximately reconstructs the state vector for linear systems without uncertainties, was presented by Luenberger. In this work, a modified form of such an observer is used by including a non-linear term involving the speed. So, both the observers are designed in the framework of nonlinear control; their stability and rate of convergence is discussed.

Keywords: Permanent magnet synchronous motor, Mathematicalmodelling, Rotor reference frame, parameter estimation, Luenbergerobserver, reduced order observer, full order observer

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1197 The Role of Classroom Management Efficacy in Predicting Teacher Burnout

Authors: Yalçın Ozdemir

Abstract:

The purpose of this study was to examine to what extend classroom management efficacy, marital status, gender, and teaching experience predict burnout among primary school teachers. Participants of this study were 523 (345 female, 178 male) teachers who completed inventories. The results of multiple regression analysis indicated that three dimensions of teacher burnout (Emotional Exhaustion, Depersonalization, Personal Accomplishment) were affected differently from four predictor variables. Findings indicated that for the emotional exhaustion, classroom management efficacy, marital status and teaching experience; for depersonalization dimension, classroom management efficacy and marital status and finally for the personal accomplishment dimension, classroom management efficacy, gender, and teaching experience were significant predictors.

Keywords: Classroom management efficacy, teacher burnout.

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1196 Statistical Optimization of Adsorption of a Harmful Dye from Aqueous Solution

Authors: M. Arun, A. Kannan

Abstract:

Textile industries cater to varied customer preferences and contribute substantially to the economy. However, these textile industries also produce a considerable amount of effluents. Prominent among these are the azo dyes which impart considerable color and toxicity even at low concentrations. Azo dyes are also used as coloring agents in food and pharmaceutical industry. Despite their applications, azo dyes are also notorious pollutants and carcinogens. Popular techniques like photo-degradation, biodegradation and the use of oxidizing agents are not applicable for all kinds of dyes, as most of them are stable to these techniques. Chemical coagulation produces a large amount of toxic sludge which is undesirable and is also ineffective towards a number of dyes. Most of the azo dyes are stable to UV-visible light irradiation and may even resist aerobic degradation. Adsorption has been the most preferred technique owing to its less cost, high capacity and process efficiency and the possibility of regenerating and recycling the adsorbent. Adsorption is also most preferred because it may produce high quality of the treated effluent and it is able to remove different kinds of dyes. However, the adsorption process is influenced by many variables whose inter-dependence makes it difficult to identify optimum conditions. The variables include stirring speed, temperature, initial concentration and adsorbent dosage. Further, the internal diffusional resistance inside the adsorbent particle leads to slow uptake of the solute within the adsorbent. Hence, it is necessary to identify optimum conditions that lead to high capacity and uptake rate of these pollutants. In this work, commercially available activated carbon was chosen as the adsorbent owing to its high surface area. A typical azo dye found in textile effluent waters, viz. the monoazo Acid Orange 10 dye (CAS: 1936-15-8) has been chosen as the representative pollutant. Adsorption studies were mainly focused at obtaining equilibrium and kinetic data for the batch adsorption process at different process conditions. Studies were conducted at different stirring speed, temperature, adsorbent dosage and initial dye concentration settings. The Full Factorial Design was the chosen statistical design framework for carrying out the experiments and identifying the important factors and their interactions. The optimum conditions identified from the experimental model were validated with actual experiments at the recommended settings. The equilibrium and kinetic data obtained were fitted to different models and the model parameters were estimated. This gives more details about the nature of adsorption taking place. Critical data required to design batch adsorption systems for removal of Acid Orange 10 dye and identification of factors that critically influence the separation efficiency are the key outcomes from this research.

Keywords: Acid Orange 10, Activated carbon, Optimum conditions, Statistical design.

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1195 Effect of the Rise/Span Ratio of a Spherical Cap Shell on the Buckling Load

Authors: Peter N. Khakina, Mohammed I. Ali, Enchun Zhu, Huazhang Zhou, Baydaa H. Moula

Abstract:

Rise/span ratio has been mentioned as one of the reasons which contribute to the lower buckling load as compared to the Classical theory buckling load but this ratio has not been quantified in the equation. The purpose of this study was to determine a more realistic buckling load by quantifying the effect of the rise/span ratio because experiments have shown that the Classical theory overestimates the load. The buckling load equation was derived based on the theorem of work done and strain energy. Thereafter, finite element modeling and simulation using ABAQUS was done to determine the variables that determine the constant in the derived equation. The rise/span was found to be the determining factor of the constant in the buckling load equation. The derived buckling load correlates closely to the load obtained from experiments.

Keywords: Buckling, Finite element, Rise/span ratio, Sphericalcap

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1194 Applications of Artificial Neural Network to Building Statistical Models for Qualifying and Indexing Radiation Treatment Plans

Authors: Pei-Ju Chao, Tsair-Fwu Lee, Wei-Luen Huang, Long-Chang Chen, Te-Jen Su, Wen-Ping Chen

Abstract:

The main goal in this paper is to quantify the quality of different techniques for radiation treatment plans, a back-propagation artificial neural network (ANN) combined with biomedicine theory was used to model thirteen dosimetric parameters and to calculate two dosimetric indices. The correlations between dosimetric indices and quality of life were extracted as the features and used in the ANN model to make decisions in the clinic. The simulation results show that a trained multilayer back-propagation neural network model can help a doctor accept or reject a plan efficiently. In addition, the models are flexible and whenever a new treatment technique enters the market, the feature variables simply need to be imported and the model re-trained for it to be ready for use.

Keywords: neural network, dosimetric index, radiation treatment, tumor

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1193 The Keys to Innovation: Defining and Evaluating Attributes that Measure Innovation Capabilities

Authors: Mohammad Samarah, Benjamin Stark, Jennifer Kindle, Langley Payton

Abstract:

Innovation is a key driver for companies, society, and economic growth. However, assessing and measuring innovation for individuals as well as organizations remains difficult. Our i5-Score presented in this study will help to overcome this difficulty and facilitate measuring the innovation potential. The score is based on a framework we call the 5Gs of innovation which defines specific innovation attributes. Those are 1) the drive for long-term goals 2) the audacity to generate new ideas, 3) the openness to share ideas with others, 4) the ability to grow, and 5) the ability to maintain high levels of optimism. To validate the i5-Score, we conducted a study at Florida Polytechnic University. The results show that the i5-Score is a good measure reflecting the innovative mindset of an individual or a group. Thus, the score can be utilized for evaluating, refining and enhancing innovation capabilities.

Keywords: Change management, innovation attributes, organizational development, STEM and venture creation.

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1192 Appreciating, Interpreting and Understanding Posters via Levels of Visual Literacy

Authors: Mona Masood, Zakiah Zain

Abstract:

This study was conducted in Malaysia to discover how meaning and appreciation were construed among 35 Form Five students. Panofsky-s theory was employed to discover the levels of reasoning among students when various types of posters were displayed. The independent variables used were posters that carried explicit and implicit meanings; the moderating variable was students- visual literacy levels while the dependent variable was the implicit interpretation level. One-way ANOVA was applied for the data analysis. The data showed that before students were exposed to Panofsky-s theory, there were differences in thinking between boys, who did not think abstractly or implicit in comparison to girls. The study showed that students- visual literacy in posters depended on the use of visual texts and illustration. This paper discuss further on posters with text only have a tendency to be too abstract as opposed to posters with visuals plus text.

Keywords: explicit visual, implicit visual, visual interpretation, visual literacy

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1191 School-Based Intervention for Academic Achievement: Targeting Cognitive, Motivational and Affective Factors

Authors: Joan Antony

Abstract:

Outcome in any learning process should target three goals – propelling the underachiever’s engagement in the learning process, enhancing the drive to achieve, and modifying attitudes and beliefs in his/her capabilities. An intervention study with a three-pronged approach incorporating self-regulatory training targeting three categories of strategies – cognitive, metacognitive and motivational – was designed adopting the before and after control-experimental group design. The evaluation of the training process was based on pre- and post-intervention measures obtained through three indices of measurement – academic scores based on grades on school examinations and comprehension tests, affective variables scores and level of strategy use obtained through responses on scales and questionnaires, and content analysis of subjective responses to open-ended probes. The evaluation relied on three sources – student, teacher and parent. The t-test results for the experimental and control groups on the pre- and post-intervention measurements indicate a significant increase on comprehension tasks for the experimental group. Though statistically significant difference was not found on the school examination scores for the experimental group, there was considerable decline in performance for the control group. Analysis of covariance (ANCOVA) was applied on the scores obtained on affective variables, namely, self-esteem, personal achievement goals, personal ego goals, personal task goals, and locus of control. The experimental group showed increase in personal achievement goals and personal ego goals as compared to the control group. Responses given by the experimental group to the open-ended probes on causal attributions indicated a considerable shift from external to internal causes when moving from the pre- to post-intervention stage. ANCOVA results revealed significantly higher use of learning strategies inclusive of mental learning strategies, behavioral learning strategies, self-regulatory strategies, and an improvement in study orientation encompassing study habits and study attitudes among the experimental group students. Parents and teachers reported significant progressive transformation towards constructive engagement with study material and self-imposed regulation. The implications of this study are three-fold: firstly, strategies training (cognitive, metacognitive and motivational) should be embedded into daily classroom routine; secondly, scaffolding by teachers through activities based on curriculum will eventually enable students to rely more on their own judgements of effective strategy use; thirdly, enhanced confidence will radiate to the affective aspects with enduring effects on other domains of life as well. The cyclic nature of the interaction between utilizing one’s resources, managing effort and regulating emotions forms the foundation for academic achievement.

Keywords: Academic achievement, cognitive strategies, metacognitive strategies, motivational strategies.

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1190 Multi-objective Optimisation of Composite Laminates under Heat and Moisture Effects using a Hybrid Neuro-GA Algorithm

Authors: M. R. Ghasemi, A. Ehsani

Abstract:

In this paper, the optimum weight and cost of a laminated composite plate is seeked, while it undergoes the heaviest load prior to a complete failure. Various failure criteria are defined for such structures in the literature. In this work, the Tsai-Hill theory is used as the failure criterion. The theory of analysis was based on the Classical Lamination Theory (CLT). A newly type of Genetic Algorithm (GA) as an optimization technique with a direct use of real variables was employed. Yet, since the optimization via GAs is a long process, and the major time is consumed through the analysis, Radial Basis Function Neural Networks (RBFNN) was employed in predicting the output from the analysis. Thus, the process of optimization will be carried out through a hybrid neuro-GA environment, and the procedure will be carried out until a predicted optimum solution is achieved.

Keywords: Composite Laminates, GA, Multi-objectiveOptimisation, Neural Networks, RBFNN.

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1189 An Adaptive Fuzzy Clustering Approach for the Network Management

Authors: Amal Elmzabi, Mostafa Bellafkih, Mohammed Ramdani

Abstract:

The Chiu-s method which generates a Takagi-Sugeno Fuzzy Inference System (FIS) is a method of fuzzy rules extraction. The rules output is a linear function of inputs. In addition, these rules are not explicit for the expert. In this paper, we develop a method which generates Mamdani FIS, where the rules output is fuzzy. The method proceeds in two steps: first, it uses the subtractive clustering principle to estimate both the number of clusters and the initial locations of a cluster centers. Each obtained cluster corresponds to a Mamdani fuzzy rule. Then, it optimizes the fuzzy model parameters by applying a genetic algorithm. This method is illustrated on a traffic network management application. We suggest also a Mamdani fuzzy rules generation method, where the expert wants to classify the output variables in some fuzzy predefined classes.

Keywords: Fuzzy entropy, fuzzy inference systems, genetic algorithms, network management, subtractive clustering.

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1188 Research on the Protection and Reuse Model of Historical Buildings in Chinese Airports

Authors: Jie Ouyang, Chen Nie

Abstract:

China had constructed a large number of military and civilian airports before and after World War II, and then began large-scale repairs, reconstructions or relocation of airports after the baptism of wars after World War I and World War II. The airport's historical area and its historical buildings such as terminals, hangars, and towers have adopted different protection strategies and reuse application strategies. This paper is based on the judgment of the value of airport historical buildings to study different protection and reuse strategies. The protection and reuse models of historical buildings are classified in three dimensions: the airport historical area, the airport historical building complex and its individual buildings, and combined with specific examples to discuss and summarize the technical characteristics, protection strategies and successful experiences of different modes of protection and reuse of historical areas and historical buildings of airports.

Keywords: Airport, airport area, historic airport building, protection, reuse model.

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1187 Methods of Estimating the Equilibrium Real Effective Exchange Rate (REER)

Authors: Pavla Ruzickova, Petr Teply

Abstract:

There are many debates now regarding undervalued and overvalued currencies currently traded on the world financial market. This paper contributes to these debates from a theoretical point of view. We present the three most commonly used methods of estimating the equilibrium real effective exchange rate (REER): macroeconomic balance approach, external sustainability approach and equilibrium real effective exchange rate approach in the reduced form. Moreover, we discuss key concepts of the calculation of the real exchange rate (RER) based on applied explanatory variables: nominal exchange rates, terms of trade and tradable and non-tradable goods. Last but not least, we discuss the three main driving forces behind real exchange rates movements which include terms of trade, relative productivity growth and the interest rate differential.

Keywords: real exchange rate, real effective exchange rate, foreign exchange, terms of trade

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1186 Optimizing Mobile Agents Migration Based on Decision Tree Learning

Authors: Yasser k. Ali, Hesham N. Elmahdy, Sanaa El Olla Hanfy Ahmed

Abstract:

Mobile agents are a powerful approach to develop distributed systems since they migrate to hosts on which they have the resources to execute individual tasks. In a dynamic environment like a peer-to-peer network, Agents have to be generated frequently and dispatched to the network. Thus they will certainly consume a certain amount of bandwidth of each link in the network if there are too many agents migration through one or several links at the same time, they will introduce too much transferring overhead to the links eventually, these links will be busy and indirectly block the network traffic, therefore, there is a need of developing routing algorithms that consider about traffic load. In this paper we seek to create cooperation between a probabilistic manner according to the quality measure of the network traffic situation and the agent's migration decision making to the next hop based on decision tree learning algorithms.

Keywords: Agent Migration, Decision Tree learning, ID3 algorithm, Naive Bayes Classifier

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1185 Investigating the Areas of Self-Reflection in Malaysian Students’ Personal Blogs: A Case Study

Authors: Chen May Oh, Nadzrah Abu Bakar

Abstract:

This case study investigates the areas of self-reflection through the written content of four university students’ blogs. The study was undertaken to explore the categories of self-reflection in relation to the use of blogs. Data collection methods included downloading students’ blog entries and recording individual interviews to further support the data. Data was analyzed using computer assisted qualitative data analysis software, Nvivo, to categories and code the data. The categories of self-reflection revealed in the findings showed that university students used blogs to reflect on (1) life in varsity, (2) emotions and feelings, (3) various relationships, (4) personal growth, (5) spirituality, (6) health conditions, (7) busyness with daily chores, (8) gifts for people and themselves and (9) personal interests. Overall, all four of the students had positive experiences and felt satisfied using blogs for self-reflection.

Keywords: Blogging, personal growth, self-reflection, university students.

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1184 The Job Satisfaction of the Employees with the Organization Retention of Metropolitan Waterworks Authority at Bangkhen

Authors: Siriwan Saithong, Unnop Panpuang

Abstract:

This research aimed to study correlation between work satisfaction and organization core value of officers in Waterworks Authority, Bangkean Branch. Sample group of the study was 112 officers who worked in the Waterworks Authority, Bangkean Branch. Questionnaires were employed as a research tools, while, Percentage, Mean, Standard Deviation, T-test, One-way ANOVA, and Pearson Product Moment Correlation were claimed as statistics used in this study. Researcher found that overall and individual aspects of work satisfaction namely, work characteristic, work progress, and colleagues significantly correlated with organization core value in aspect of perception in choice of work at 0.5, 0.01, and 0.01 respectively. Also, such aspects were compatible with income at .05 which indicated the low level of correlation, mid low correlation respectively at the same direction, same direction, opposite direction, and same direction, correspondingly.

Keywords: Employee of Bangkhen branch, Job Satisfaction, the organization Retention.

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1183 A Novel Pareto-Based Meta-Heuristic Algorithm to Optimize Multi-Facility Location-Allocation Problem

Authors: Vahid Hajipour, Samira V. Noshafagh, Reza Tavakkoli-Moghaddam

Abstract:

This article proposes a novel Pareto-based multiobjective meta-heuristic algorithm named non-dominated ranking genetic algorithm (NRGA) to solve multi-facility location-allocation problem. In NRGA, a fitness value representing rank is assigned to each individual of the population. Moreover, two features ranked based roulette wheel selection including select the fronts and choose solutions from the fronts, are utilized. The proposed solving methodology is validated using several examples taken from the specialized literature. The performance of our approach shows that NRGA algorithm is able to generate true and well distributed Pareto optimal solutions.

Keywords: Non-dominated ranking genetic algorithm, Pareto solutions, Multi-facility location-allocation problem.

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1182 Audio Watermarking Using Spectral Modifications

Authors: Jyotsna Singh, Parul Garg, Alok Nath De

Abstract:

In this paper, we present a non-blind technique of adding the watermark to the Fourier spectral components of audio signal in a way such that the modified amplitude does not exceed the maximum amplitude spread (MAS). This MAS is due to individual Discrete fourier transform (DFT) coefficients in that particular frame, which is derived from the Energy Spreading function given by Schroeder. Using this technique one can store double the information within a given frame length i.e. overriding the watermark on the host of equal length with least perceptual distortion. The watermark is uniformly floating on the DFT components of original signal. This helps in detecting any intentional manipulations done on the watermarked audio. Also, the scheme is found robust to various signal processing attacks like presence of multiple watermarks, Additive white gaussian noise (AWGN) and mp3 compression.

Keywords: Discrete Fourier Transform, Spreading Function, Watermark, Pseudo Noise Sequence, Spectral Masking Effect

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1181 Classification Based on Deep Neural Cellular Automata Model

Authors: Yasser F. Hassan

Abstract:

Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: Cellular automata, neural cellular automata, deep learning, classification.

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1180 Learning Monte Carlo Data for Circuit Path Length

Authors: Namal A. Senanayake, A. Beg, Withana C. Prasad

Abstract:

This paper analyzes the patterns of the Monte Carlo data for a large number of variables and minterms, in order to characterize the circuit path length behavior. We propose models that are determined by training process of shortest path length derived from a wide range of binary decision diagram (BDD) simulations. The creation of the model was done use of feed forward neural network (NN) modeling methodology. Experimental results for ISCAS benchmark circuits show an RMS error of 0.102 for the shortest path length complexity estimation predicted by the NN model (NNM). Use of such a model can help reduce the time complexity of very large scale integrated (VLSI) circuitries and related computer-aided design (CAD) tools that use BDDs.

Keywords: Monte Carlo data, Binary decision diagrams, Neural network modeling, Shortest path length estimation.

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1179 The Importance of Psychological Contracts through Leadership: The Relationship between Human Resource Strategy and Performance

Authors: Bella Llego

Abstract:

The purpose of this research is: a) to investigate how the HR practices influence psychological contracts, b) to examine the influence of psychological contracts to individual behavior and to contribute individually, c) to study the psychological contact through leadership. This research using mixed methods, qualitative and quantitative research methods were utilized to gather the data collected using a qualitative method by the HR Manager who is in charge of the trainings from the staffs and quantitative method (survey) by using questionnaire was utilized to draw upon and to elaborate on the recurring themes present during the interviews. The survey was done to 400 staffs of the company. The study found that leadership styles supporting the firm’s HR strategy is the key in making psychological contracts that benefit both the firm and its members.

Keywords: Human Resource Performance Practice, and Leadership, Psychological Contacts, Relationship of Managers and staffs.

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1178 Characterization of Fabricated A 384.1-MgO Based Metal Matrix Composite and Optimization of Tensile Strength using Taguchi Techniques

Authors: Nripjit, Anand K Tyagi, Nirmal Singh

Abstract:

The present work consecutively on synthesis and characterization of composites, Al/Al alloy A 384.1 as matrix in which the main ingredient as Al/Al-5% MgO alloy based metal matrix composite. As practical implications the low cost processing route for the fabrication of Al alloy A 384.1 and operational difficulties of presently available manufacturing processes based in liquid manipulation methods. As all new developments, complete understanding of the influence of processing variables upon the final quality of the product. And the composite is applied comprehensively to the acquaintance for achieving superiority of information concerning the specific heat measurement of a material through the aid of thermographs. Products are evaluated concerning relative particle size and mechanical behavior under tensile strength. Furthermore, Taguchi technique was employed to examine the experimental optimum results are achieved, owing to effectiveness of this approach.

Keywords: MMC, Thermographs, Tensile strength, Taguchi technique, Optimal parameters

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1177 Binary Mixture of Copper-Cobalt Ions Uptake by Zeolite using Neural Network

Authors: John Kabuba, Antoine Mulaba-Bafubiandi, Kim Battle

Abstract:

In this study a neural network (NN) was proposed to predict the sorption of binary mixture of copper-cobalt ions into clinoptilolite as ion-exchanger. The configuration of the backpropagation neural network giving the smallest mean square error was three-layer NN with tangent sigmoid transfer function at hidden layer with 10 neurons, linear transfer function at output layer and Levenberg-Marquardt backpropagation training algorithm. Experiments have been carried out in the batch reactor to obtain equilibrium data of the individual sorption and the mixture of coppercobalt ions. The obtained modeling results have shown that the used of neural network has better adjusted the equilibrium data of the binary system when compared with the conventional sorption isotherm models.

Keywords: Adsorption isotherm, binary system, neural network; sorption

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1176 Chips of Ti-6Al-2Sn-4Zr-6Mo Alloy – A Detailed Geometry Study

Authors: Dmytro Ostroushko, Karel Saksl, Carsten Siemers, Zuzana Rihova

Abstract:

Titanium alloys like Ti-6Al-2Sn-4Zr-6Mo (Ti- 6246) are widely used in aerospace applications. Component manufacturing, however, is difficult and expensive as their machinability is extremely poor. A thorough understanding of the chip formation process is needed to improve related metal cutting operations.In the current study, orthogonal cutting experiments have been performed and theresulting chips were analyzed by optical microscopy and scanning electron microscopy.Chips from aTi- 6246ingot were produced at different cutting speeds and cutting depths. During the experiments, depending of the cutting conditions, continuous or segmented chips were formed. Narrow, highly deformed and grain oriented zones, the so-called shear zone, separated individual segments. Different material properties have been measured in the shear zones and the segments.

Keywords: Titanium alloy, Ti-6246, chip formation, machining, shear zone, microstructure

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1175 Outlier Pulse Detection and Feature Extraction for Wrist Pulse Analysis

Authors: Bhaskar Thakker, Anoop Lal Vyas

Abstract:

Wrist pulse analysis for identification of health status is found in Ancient Indian as well as Chinese literature. The preprocessing of wrist pulse is necessary to remove outlier pulses and fluctuations prior to the analysis of pulse pressure signal. This paper discusses the identification of irregular pulses present in the pulse series and intricacies associated with the extraction of time domain pulse features. An approach of Dynamic Time Warping (DTW) has been utilized for the identification of outlier pulses in the wrist pulse series. The ambiguity present in the identification of pulse features is resolved with the help of first derivative of Ensemble Average of wrist pulse series. An algorithm for detecting tidal and dicrotic notch in individual wrist pulse segment is proposed.

Keywords: Wrist Pulse Segment, Ensemble Average, Dynamic Time Warping (DTW), Pulse Similarity Vector.

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1174 Resource Efficiency within Current Production

Authors: Sarah Majid Ansari, Serjosha Wulf, Matthias Görke

Abstract:

In times of global warming and the increasing shortage of resources, sustainable production is becoming more and more inevitable. Companies cannot only heighten their competitiveness but also contribute positively to environmental protection through efficient energy and resource consumption. Regarding this, technical solutions are often preferred during production, although organizational and process-related approaches also offer great potential. This project focuses on reducing resource usage, with a special emphasis on the human factor. It is the aspiration to develop a methodology that systematically implements and embeds suitable and individual measures and methods regarding resource efficiency throughout the entire production. The measures and methods established help employees handle resources and energy more sensitively. With this in mind, this paper also deals with the difficulties that can occur during the sensitization of employees and the implementation of these measures and methods. In addition, recommendations are given on how to avoid such difficulties.

Keywords: Implementation, human factor, production plant, resource efficiency.

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1173 Influence of Ambient Condition on Performance of Wet Compression Process

Authors: Kyoung Hoon Kim

Abstract:

Gas turbine systems with wet compression have a potential for future power generation, since they can offer a high efficiency and a high specific power with a relatively low cost. In this study influence of ambient condition on the performance of the wet compression process is investigated with a non-equilibrium analytical modeling based on droplet evaporation. Transient behaviors of droplet diameter and temperature of mixed air are investigated for various ambient temperatures. Special attention is paid for the effects of ambient temperature, pressure ratio, and water injection ratios on the important wet compression variables including compressor outlet temperature and compression work. Parametric studies show that downing of the ambient temperature leads to lower compressor outlet temperature and consequently lower consumption of compression work even in wet compression processes.

Keywords: water injection, droplet evaporation, wet compression, gas turbine, ambient condition

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1172 Experimental Study on the Vibration Isolation Performance of Metal-Net Rubber Vibration Absorber

Authors: Su Yi Ming, Hou Ying, Zou Guang Ping

Abstract:

Metal-net rubber is a new dry friction damping material, compared with the traditional metal rubber, which has high mechanization degree, and the mechanical performance of metal-net rubber is more stable. Through the sine sweep experiment and random vibration experiment of metal-net rubber vibration isolator, the influence of several important factors such as the lines slope, relative density and wire diameter on the transfer rate, natural frequency and root-mean-square response acceleration of metal-net rubber vibration isolation system, were studied through the method of control variables. Also, several relevant change curves under different vibration levels were derived, and the effects of vibration level on the natural frequency and root-mean-square response acceleration were analyzed through the curves.

Keywords: Metal-net rubber vibration isolator, relative density, vibration level, wire diameter.

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1171 Applying Gibbs Sampler for Multivariate Hierarchical Linear Model

Authors: Satoshi Usami

Abstract:

Among various HLM techniques, the Multivariate Hierarchical Linear Model (MHLM) is desirable to use, particularly when multivariate criterion variables are collected and the covariance structure has information valuable for data analysis. In order to reflect prior information or to obtain stable results when the sample size and the number of groups are not sufficiently large, the Bayes method has often been employed in hierarchical data analysis. In these cases, although the Markov Chain Monte Carlo (MCMC) method is a rather powerful tool for parameter estimation, Procedures regarding MCMC have not been formulated for MHLM. For this reason, this research presents concrete procedures for parameter estimation through the use of the Gibbs samplers. Lastly, several future topics for the use of MCMC approach for HLM is discussed.

Keywords: Gibbs sampler, Hierarchical Linear Model, Markov Chain Monte Carlo, Multivariate Hierarchical Linear Model

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1170 Artificial Neural Network Models of the Ruminal pH in Holstein Steers

Authors: Alireza Vakili, Mohsen Danesh Mesgaran, Majid Abdollazade

Abstract:

In this study four Holstein steers with rumen fistula fed 7 kg of dry matter (DM) of diets differing in concentrate to alfalfa hay ratios as 60:40, 70:30, 80:20, and 90:10 in a 4 × 4 latin square design. The pH of the ruminal fluid was measured before the morning feeding (0.0 h) to 8 h post feeding. In this study, a two-layered feed-forward neural network trained by the Levenberg-Marquardt algorithm was used for modelling of ruminal pH. The input variables of the network were time, concentrate to alfalfa hay ratios (C/F), non fiber carbohydrate (NFC) and neutral detergent fiber (NDF). The output variable was the ruminal pH. The modeling results showed that there was excellent agreement between the experimental data and predicted values, with a high determination coefficient (R2 >0.96). Therefore, we suggest using these model-derived biological values to summarize continuously recorded pH data.

Keywords: Ruminal pH, Artificial Neural Network (ANN), Non Fiber Carbohydrate, Neutral Detergent Fiber.

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