Search results for: Shear field test method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12006

Search results for: Shear field test method

1176 Theoretical Analysis of Self-Starting Busemann Intake Family

Authors: N. Moradian, E. Timofeev, R. Tahir

Abstract:

In this work, startability of the Busemann intake family with weak/strong conical shock, as most efficient intakes, via overboard mass spillage method is theoretically analyzed. Masterix and Candifix codes are used to numerically simulate few models of this type of intake and verify the theoretical results. Portions of the intake corresponding to various flow capture angles are considered to have mass spillage in the starting process of this intake. This approach allows for overboard mass spillage via a V-shaped slot with the tip of V coinciding with the focal point of the Busemann flow. The theoretical results, achieved using two different theories, of self-started Busemann takes with weak/strong conical shock show that significant improve in intake startability using overboard spillage technique. The starting phenomena of Busemann intakes with weak conical shock and seven different capture angles are numerically simulated at freestream Mach number of 3 to find the minimum area ratios of self-started intakes. The numerical results confirm the theoretical ones achieved by authors.

Keywords: Busemann intake, conical shock, overboard spillage, startability.

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1175 Economical Analysis of Thermal Energy Storage by Partially Operation

Authors: Z. Noranai, M.Z. Md Yusof

Abstract:

Building Sector is the major electricity consumer and it is costly to building owners. Therefore the application of thermal energy storage (TES) has gained attractive to reduce energy cost. Many attractive tariff packages are being offered by the electricity provider to promote TES. The tariff packages offered higher cost of electricity during peak period and lower cost of electricity during off peak period. This paper presented the return of initial investment by implementing a centralized air-conditioning plant integrated with thermal energy storage with partially operation strategies. Building load profile will be calculated hourly according to building specification and building usage trend. TES operation conditions will be designed according to building load demand profile, storage capacity, tariff packages and peak/off peak period. The Payback Period analysis method was used to evaluate economic analysis. The investment is considered a good investment where by the initial cost is recovered less than ten than seven years.

Keywords: building load profile, energy consumption, payback period, thermal energy storage

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1174 A New Approach for Prioritization of Failure Modes in Design FMEA using ANOVA

Authors: Sellappan Narayanagounder, Karuppusami Gurusami

Abstract:

The traditional Failure Mode and Effects Analysis (FMEA) uses Risk Priority Number (RPN) to evaluate the risk level of a component or process. The RPN index is determined by calculating the product of severity, occurrence and detection indexes. The most critically debated disadvantage of this approach is that various sets of these three indexes may produce an identical value of RPN. This research paper seeks to address the drawbacks in traditional FMEA and to propose a new approach to overcome these shortcomings. The Risk Priority Code (RPC) is used to prioritize failure modes, when two or more failure modes have the same RPN. A new method is proposed to prioritize failure modes, when there is a disagreement in ranking scale for severity, occurrence and detection. An Analysis of Variance (ANOVA) is used to compare means of RPN values. SPSS (Statistical Package for the Social Sciences) statistical analysis package is used to analyze the data. The results presented are based on two case studies. It is found that the proposed new methodology/approach resolves the limitations of traditional FMEA approach.

Keywords: Failure mode and effects analysis, Risk priority code, Critical failure mode, Analysis of variance.

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1173 Deoxygenation of Beef Fat over Pd Supported Mesoporous TiO2 Catalyst Prepared by Single-Step Sol-Gel Process with Surfactant Template

Authors: Tossaporn Jindarat, Siriporn Jongpatiwut, Somchai Osuwan, Suchada Butnark

Abstract:

Deoxygenation of beef fat for the production of hydrogenated biodiesel is investigated in a high pressure continuous flow fixed bed reactor over palladium-supported mesoporous titania catalyst synthesized via a combined single-step sol-gel process with surfactant-assisted templating method (SATM). The catalyst possessed a mesoporous charactheristic with high surface area and narrow pore size distribution. The main products of all Pd/TiO2 catalysts are n-heptadecane (n-C17) and n-pentadecane (n-C15) resulting from decarbonylation reaction. Pd/TiO2 catalyst synthesized via a combined single-step sol-gel process with SATM (SSSG) gave higher activity and selectivity to the desired products when compared to IWI/SG-TiO2 and IWI/P25-TiO2, respectively. SSSG catalyst gave the average conversion up to 80-90 % and 80 % for the selectivity in diesel range hydrocarbons. This result may cause by the higher surface area and the ability in dispersion of palladium ion in mesoporous of TiO2 during sol-gel process.

Keywords: Beef fat, Deoxygenation, Hydrogenated biodiesel, Pd/TiO2

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1172 Preconcentration and Determination of Cyproheptadine in Biological Samples by Hollow Fiber Liquid Phase Microextraction Coupled with High Performance Liquid Chromatography

Authors: Najari Moghadam Sh., Qomi M., Raofie F., Khadiv J.

Abstract:

In this study, a liquid phase microextraction by hollow fiber (HF-LPME) combined with high performance liquid chromatography-UV detector was applied to preconcentrate and determine trace levels of Cyproheptadine in human urine and plasma samples. Cyproheptadine was extracted from 10 mL alkaline aqueous solution (pH: 9.81) into an organic solvent (n-octnol) which was immobilized in the wall pores of a hollow fiber. Then was back-extracted into an acidified aqueous solution (pH: 2.59) located inside the lumen of the hollow fiber. This method is simple, efficient and cost-effective. It is based on pH gradient and differences between two aqueous phases. In order to optimize the HF-LPME some affecting parameters including the pH of donor and acceptor phases, the type of organic solvent, ionic strength, stirring rate, extraction time and temperature were studied and optimized. Under optimal conditions enrichment factor, limit of detection (LOD) and relative standard deviation (RSD(%), n=3) were up to 112, 15 μg.L−1 and 2.7, respectively.

Keywords: Biological samples, Cyproheptadine, hollow fiber, liquid phase microextraction.

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1171 Advanced Neural Network Learning Applied to Pulping Modeling

Authors: Z. Zainuddin, W. D. Wan Rosli, R. Lanouette, S. Sathasivam

Abstract:

This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

Keywords: Convergence, pulping modeling, neural networks, preconditioned conjugate gradient.

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1170 Geometric and Material Nonlinear Analysis of Reinforced Concrete Structure Considering Soil-Structure Interaction

Authors: Mohamed M. El-Gendy, Ibrahim A. El-Arabi, Rafik W. Abdel-Missih, Omar A. Kandil

Abstract:

In the present research, a finite element model is presented to study the geometrical and material nonlinear behavior of reinforced concrete plane frames considering soil-structure interaction. The nonlinear behaviors of concrete and reinforcing steel are considered both in compression and tension up to failure. The model takes account also for the number, diameter, and distribution of rebar along every cross section. Soil behavior is taken into consideration using four different models; namely: linear-, nonlinear Winkler's model, and linear-, nonlinear continuum model. A computer program (NARC) is specially developed in order to perform the analysis. The results achieved by the present model show good agreement with both theoretical and experimental published literature. The nonlinear behavior of a rectangular frame resting on soft soil up to failure using the proposed model is introduced for demonstration.

Keywords: Nonlinear analysis, Geometric nonlinearity, Material nonlinearity, Reinforced concrete, Finite element method, Soilstructure interaction, Winkler's soil model, Continuum soil model

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1169 Control Chart Pattern Recognition Using Wavelet Based Neural Networks

Authors: Jun Seok Kim, Cheong-Sool Park, Jun-Geol Baek, Sung-Shick Kim

Abstract:

Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.

Keywords: Control chart pattern recognition, Multi-resolution wavelet analysis, Bi-directional Kohonen network, Back-propagation network, Feature extraction.

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1168 Hazardous Waste Generated in the Peruvian Textile Industry: Haute Couture, Alpaca Fiber and Tannery

Authors: Huiman C. Alberto

Abstract:

The research cites the various hazardous waste generated in the textile industry. The method used is descriptive and comparative, the process consisted of the search and evaluation of information, both nationally and internationally. The results indicate: (1) Waste is generated from the alpaca fiber industry in the various stages of camelid rearing, they stand out for their dangerousness: excreta, residual fiber and yarn scraps. (2) The main hazardous waste generated by the tannery industry are grease, hides, hair, plastic containers with traces of toxic substances, chips and pieces of leather with chrome. (3) Three companies' Solid Waste Management Plans were analyzed, randomly selected, and none of them detail waste treatment processes and warn of the lack of supervision by the authorities. It is concluded that the hazardous waste generated can affect human and environmental health. There is the possibility of taking advantage of certain hazardous waste such as manure and alpaca fiber, after treatment; while non-hazardous waste from the tannery such as yarn, panel weaving, cloth, scraps, and thread, can be used to produce new products, generating a production chain in favor of the entrepreneur himself.

Keywords: Alpaca fiber, excreta, Haute couture, hazardous waste tannery, hazardous waste treatment, textile waste,

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1167 Facial Expressions Recognition from Complex Background using Face Context and Adaptively Weighted sub-Pattern PCA

Authors: Md. Zahangir Alom, Mei-Lan Piao, Md. Ashraful Alam, Nam Kim, Jae-Hyeung Park

Abstract:

A new approach for facial expressions recognition based on face context and adaptively weighted sub-pattern PCA (Aw-SpPCA) has been presented in this paper. The facial region and others part of the body have been segmented from the complex environment based on skin color model. An algorithm has been proposed to accurate detection of face region from the segmented image based on constant ratio of height and width of face (δ= 1.618). The paper also discusses on new concept to detect the eye and mouth position. The desired part of the face has been cropped to analysis the expression of a person. Unlike PCA based on a whole image pattern, Aw-SpPCA operates directly on its sub patterns partitioned from an original whole pattern and separately extracts features from them. Aw-SpPCA can adaptively compute the contributions of each part and a classification task in order to enhance the robustness to both expression and illumination variations. Experiments on single standard face with five types of facial expression database shows that the proposed method is competitive.

Keywords: Aw-SpPC, Expressoin Recognition, Face context, Face Detection, PCA

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1166 Synthesis of Activated Carbon Using Agricultural Wastes from Biodiesel Production

Authors: A. Buasri, N. Chaiyut, V. Loryuenyong, E. Phakdeepataraphan, S. Watpathomsub, V. Kunakemakorn

Abstract:

In this research, the optimum conditions for the synthesis of activated carbon from biodiesel wastes such as palm shells (PS) and Jatropha curcas fruit shells (JS) by chemical activation method using potassium hydroxide (KOH) as an activating agent under nitrogen atmosphere were investigated. The effects of soaking in hydrofluoric acid (HF), impregnation ratio, activation temperature and activation time on adsorption capacity of methylene blue (MB) and iodine (I2) solution were examined. The results showed that HF-treated activated carbons exhibited higher adsorption capacities by eliminating ash residues, which might fill up the pores. In addition, the adsorption capacities of methylene blue and iodine solution were also significantly influenced by the types of raw materials, the activation temperature and the activation time. The highest adsorption capacity of methylene blue 257.07mg/g and iodine 847.58mg/g were obtained from Jatropha curcas wastes.

Keywords: Activated Carbon, Palm Shells (PS), Jatropha Curcas Fruit Shells (JS), Agricultural Wastes, Biodiesel Wastes, Optimum Conditions.

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1165 Rainfall–Runoff Simulation Using WetSpa Model in Golestan Dam Basin, Iran

Authors: M. R. Dahmardeh Ghaleno, M. Nohtani, S. Khaledi

Abstract:

Flood simulation and prediction is one of the most active research areas in surface water management. WetSpa is a distributed, continuous, and physical model with daily or hourly time step that explains precipitation, runoff, and evapotranspiration processes for both simple and complex contexts. This model uses a modified rational method for runoff calculation. In this model, runoff is routed along the flow path using Diffusion-Wave equation which depends on the slope, velocity, and flow route characteristics. Golestan Dam Basin is located in Golestan province in Iran and it is passing over coordinates 55° 16´ 50" to 56° 4´ 25" E and 37° 19´ 39" to 37° 49´ 28"N. The area of the catchment is about 224 km2, and elevations in the catchment range from 414 to 2856 m at the outlet, with average slope of 29.78%. Results of the simulations show a good agreement between calculated and measured hydrographs at the outlet of the basin. Drawing upon Nash-Sutcliffe model efficiency coefficient for calibration periodic model estimated daily hydrographs and maximum flow rate with an accuracy up to 59% and 80.18%, respectively.

Keywords: Watershed simulation, WetSpa, stream flow, flood prediction.

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1164 Knowledge Representation and Retrieval in Design Project Memory

Authors: Smain M. Bekhti, Nada T. Matta

Abstract:

Knowledge sharing in general and the contextual access to knowledge in particular, still represent a key challenge in the knowledge management framework. Researchers on semantic web and human machine interface study techniques to enhance this access. For instance, in semantic web, the information retrieval is based on domain ontology. In human machine interface, keeping track of user's activity provides some elements of the context that can guide the access to information. We suggest an approach based on these two key guidelines, whilst avoiding some of their weaknesses. The approach permits a representation of both the context and the design rationale of a project for an efficient access to knowledge. In fact, the method consists of an information retrieval environment that, in the one hand, can infer knowledge, modeled as a semantic network, and on the other hand, is based on the context and the objectives of a specific activity (the design). The environment we defined can also be used to gather similar project elements in order to build classifications of tasks, problems, arguments, etc. produced in a company. These classifications can show the evolution of design strategies in the company.

Keywords: Project Memory, Knowledge re-use, Design rationale, Knowledge representation.

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1163 Effectiveness of the Flavonoids Isolated from Thymus inodorus by Different Solvents against Some Pathogenis Microorganisms

Authors: N. Behidj, K. Benyounes, T. Dahmane, A. Allem

Abstract:

The aim of this study was to investigate the antimicrobial activity of flavonoids isolated from the aerial part of a medicinal plant which is Thymus inodorusby the middle agar diffusion method on following microorganisms. We have Staphylococcus aureus, Escherichia coli, Pseudomonas fluorescens, AspergillusNiger, Aspergillus fumigatus and Candida albicans. During this study, flavonoids extracted by stripping with steam are performed. The yields of flavonoids is 7.242% for the aqueous extract and 28.86% for butanol extract, 29.875% for the extract of ethyl acetate and 22.9% for the extract of di - ethyl. The evaluation of the antibacterial effect shows that the diameter of the zone of inhibition varies from one microorganism to another. The operation values obtained show that the bacterial strain P fluoresces, and 3 yeasts and molds; A. Niger, A. fumigatus and C. albicansare the most resistant. But it is noted that, S. aureus is shown more sensitive to crude extracts, the stock solution and the various dilutions. Finally for the minimum inhibitory concentration is estimated only with the crude extract of Thymus inodorus flavonoid.Indeed, these extracts inhibit the growth of Gram + bacteria at a concentration varying between 0.5% and 1%. While for bacteria to Gram -, it is limited to a concentration of 0.5%.

Keywords: Antimicrobial activity, flavonoids, strains, Thymus inodorus.

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1162 Local Spectrum Feature Extraction for Face Recognition

Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd Zaizu Ilyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

Abstract:

This paper presents two techniques, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapped on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non- Gaussian in the feature space and by using combination of several Gaussian functions that has different statistical properties, the best feature representation can be modelled using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculated GMM components. The method is tested using FERET datasets and is able to achieved 92% recognition rates.

Keywords: Local features modelling, face recognition system, Gaussian mixture models.

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1161 Investigation of SSR Characteristics of SSSC With GA Based Voltage Controller

Authors: R. Thirumalaivasan, M.Janaki, Nagesh Prabhu

Abstract:

In this paper, investigation of subsynchronous resonance (SSR) characteristics of a hybrid series compensated system and the design of voltage controller for three level 24-pulse Voltage Source Converter based Static Synchronous Series Compensator (SSSC) is presented. Hybrid compensation consists of series fixed capacitor and SSSC which is a active series FACTS controller. The design of voltage controller for SSSC is based on damping torque analysis, and Genetic Algorithm (GA) is adopted for tuning the controller parameters. The SSR Characteristics of SSSC with constant reactive voltage control modes has been investigated. The results show that the constant reactive voltage control of SSSC has the effect of reducing the electrical resonance frequency, which detunes the SSR.The analysis of SSR with SSSC is carried out based on frequency domain method, eigenvalue analysis and transient simulation. While the eigenvalue and damping torque analysis are based on D-Q model of SSSC, the transient simulation considers both D-Q and detailed three phase nonlinear system model using switching functions.

Keywords: FACTS, SSR, SSSC, damping torque, GA.

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1160 Adaptive PID Controller based on Reinforcement Learning for Wind Turbine Control

Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

A self tuning PID control strategy using reinforcement learning is proposed in this paper to deal with the control of wind energy conversion systems (WECS). Actor-Critic learning is used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency, a single RBF neural network is used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for WECS and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

Keywords: Wind energy conversion systems, reinforcementlearning; Actor-Critic learning; adaptive PID control; RBF network.

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1159 Effects of Varying Air Temperature in the Polishing Component of Single-Pass Mill on the Quality of Rice

Authors: M. A. U. Baradi, F. B. Bulao, N. D. Ganotisi, M. Jose C. Regalado, F. P. Bongat, S. B. Manglinong, M. L. O. Quigao, N. G. T. Martinez, R. G. Ancheta, M. P. Ortal

Abstract:

The effects of varying air temperature (full, ¾ full, ½ full aircon adjustment, no aircon) in polishing component of Single-Pass Mill on the quality of Philippine inbred rice variety, was investigated. Parameters measured were milling recovery (MR), headrice recovery (HR), and percentage with bran streaks. Cooling method (with aircon) increased MR, HR, and percentage with bran streaks of milled rice. Highest MR and HR (67.62%; 47.33%) were obtained from ¾ full adjustment whereas no aircon were lowest (66.27%; 39.76%). Temperature in polishing component at ¾ full adjustment was 33oC whereas no aircon was 45oC. There was increase of 1.35% in MR and 7.57% in HR. Additional cost of milling per kg due to aircon cooling was P0.04 at 300 tons/yr volume, with 0.15 yr payback period. Net income was estimated at ₱98,100.00. Percentage of kernels with bran streaks increased from 5%–14%, indicating more nutrients of milled rice.

Keywords: Aircon, air temperature, polishing component, quality, Single-Pass Mill.

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1158 Review and Classification of the Indicators and Trends Used in Bridge Performance Modeling

Authors: S. Rezaei, Z. Mirzaei, M. Khalighi, J. Bahrami

Abstract:

Bridges, as an essential part of road infrastructures, are affected by various deterioration mechanisms over time due to the changes in their performance. As changes in performance can have many negative impacts on society, it is essential to be able to evaluate and measure the performance of bridges throughout their life. This evaluation includes the development or the choice of the appropriate performance indicators, which, in turn, are measured based on the selection of appropriate models for the existing deterioration mechanism. The purpose of this article is a statistical study of indicators and deterioration mechanisms of bridges in order to discover further research capacities in bridges performance assessment. For this purpose, some of the most common indicators of bridge performance, including reliability, risk, vulnerability, robustness, and resilience, were selected. The researches performed on each index based on the desired deterioration mechanisms and hazards were comprehensively reviewed. In addition, the formulation of the indicators and their relationship with each other were studied. The research conducted on the mentioned indicators were classified from the point of view of deterministic or probabilistic method, the level of study (element level, object level, etc.), and the type of hazard and the deterioration mechanism of interest. For each of the indicators, a number of challenges and recommendations were presented according to the review of previous studies.

Keywords: Bridge, deterioration mechanism, lifecycle, performance indicator.

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1157 Phenotypical and Genotypical Assessment Techniques for Identification of Some Contagious Mastitis Pathogens

Authors: A. El Behiry, R. N. Zahran, R. Tarabees, E. Marzouk, M. Al-Dubaib

Abstract:

Mastitis is one of the most economic disease affecting dairy cows worldwide. Its classic diagnosis using bacterial culture and biochemical findings is a difficult and prolonged method. In this research, using of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) permitted identification of different microorganisms with high accuracy and rapidity (only 24 hours for microbial growth and analysis). During the application of MALDI-TOF MS, one hundred twenty strains of Staphylococcus and Streptococcus species isolated from milk of cows affected by clinical and subclinical mastitis were identified, and the results were compared with those obtained by traditional methods as API and VITEK 2 Systems. 37 of totality 39 strains (~95%) of Staphylococcus aureus (S. aureus) were exactly detected by MALDI TOF MS and then confirmed by a nuc-based PCR technique, whereas accurate identification was observed in 100% (50 isolates) of the coagulase negative staphylococci (CNS) and Streptococcus agalactiae (31 isolates). In brief, our results demonstrated that MALDI-TOF MS is a fast and truthful technique which has the capability to replace conventional identification of several bacterial strains usually isolated in clinical laboratories of microbiology.

Keywords: Identification, mastitis pathogens, mass spectral, phenotypical.

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1156 Cellulolytic Microbial Activator Influence on Decomposition of Rubber Factory Waste Composting

Authors: Thaniya Kaosol, Sirinthrar Wandee

Abstract:

In this research, an aerobic composting method is studied to reuse organic waste from rubber factory waste as soil fertilizer and to study the effect of cellulolytic microbial activator (CMA) as the activator in the rubber factory waste composting. The performance of the composting process was monitored as a function of carbon and organic matter decomposition rate, temperature and moisture content. The results indicate that the rubber factory waste is best composted with water hyacinth and sludge than composted alone. In addition, the CMA is more affective when mixed with the rubber factory waste, water hyacinth and sludge since a good fertilizer is achieved. When adding CMA into the rubber factory waste composted alone, the finished product does not achieve a standard of fertilizer, especially the C/N ratio. Finally, the finished products of composting rubber factory waste and water hyacinth and sludge (both CMA and without CMA), can be an environmental friendly alternative to solve the disposal problems of rubber factory waste. Since the C/N ratio, pH, moisture content, temperature, and nutrients of the finished products are acceptable for agriculture use.

Keywords: composting, rubber waste, C/N ratio, sludge, cellulolytic microbial activator

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1155 A Novel Approach to Handle Uncertainty in Health System Variables for Hospital Admissions

Authors: Manisha Rathi, Thierry Chaussalet

Abstract:

Hospital staff and managers are under pressure and concerned for effective use and management of scarce resources. The hospital admissions require many decisions that have complex and uncertain consequences for hospital resource utilization and patient flow. It is challenging to predict risk of admissions and length of stay of a patient due to their vague nature. There is no method to capture the vague definition of admission of a patient. Also, current methods and tools used to predict patients at risk of admission fail to deal with uncertainty in unplanned admission, LOS, patients- characteristics. The main objective of this paper is to deal with uncertainty in health system variables, and handles uncertain relationship among variables. An introduction of machine learning techniques along with statistical methods like Regression methods can be a proposed solution approach to handle uncertainty in health system variables. A model that adapts fuzzy methods to handle uncertain data and uncertain relationships can be an efficient solution to capture the vague definition of admission of a patient.

Keywords: Admission, Fuzzy, Regression, Uncertainty

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1154 The Effectiveness of University’s Strategic Plan for Sustainability through Collaborative Platform’s Deliberation Matrix

Authors: Ashiquer Rahman

Abstract:

The paper focuses on the significance of the university's sustainability strategic plan and emphasizes the usefulness of the collaborative platform-based deliberation matrix. It will equip the university's leadership to handle impending tactics and challenges with the sustainability of the university’s strategic plan. The study addresses the significance of a set of reference points that will precede operational activities for multi-stakeholder multi-criteria evaluation on the optimal standards of Sustainable University, as well as potential action for the strategic blueprint of Sustainable University. It makes reference to the university’s sustainability strategy plan’s effectiveness through a collaborative platform and deliberation matrix. The paper outlines the conceptual framing of a sustainable university by implementing a strategic plan over the collaborative platform and deliberation matrix. Optimistically, these will be a milestone in higher education; a pathway to prepare for the University’s upcoming implementation of its sustainability strategy. In fact, the collaborative platform and deliberation matrix both are enhancement needles for institutional cooperation to the completive world.

Keywords: Sustainable strategies, institutional cooperation, multi-stakeholder multi-criteria assessment, collaborative platform, innovative method and tools.

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1153 Examination of Pre-Tender Budgeting Techniques for Mechanical and Electrical Services in Malaysia

Authors: Ganiyu Amuda Yusuf, Sarajul Fikri Mohamed

Abstract:

The procurement and cost management approach adopted for mechanical and electrical (M&E) services in Malaysian construction industry have been criticized for its inefficiency. The study examined early cost estimating practices adopted for mechanical and electrical services (M&E) in Malaysia so as to understand the level of compliance of the current techniques with best practices. The methodology adopted for the study is a review of bidding documents used on both completed and on – going building projects awarded between 2008 – 2010 under 9th Malaysian Plan. The analysis revealed that, M&E services cost cannot be reliably estimated at pre-contract stage; the bidding techniques adopted for M&E services failed to provide uniform basis for contractors to submit tender; detailed measurement of items were not made which could complicate post contract cost control and financial management. The paper concluded that, there is need to follow a structured approach in determining the pre-contract cost estimate for M&E services which will serve as a virile tool for post contract cost control.

Keywords: Cost Management, Mechanical and Electrical Services, Procurement, Standard Method of Measurement

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1152 The Impact of Modeling Method of Moisture Emission from the Swimming Pool on the Accuracy of Numerical Calculations of Air Parameters in Ventilated Natatorium

Authors: Piotr Ciuman, Barbara Lipska

Abstract:

The aim of presented research was to improve numerical predictions of air parameters distribution in the actual natatorium by the selection of calculation formula of mass flux of moisture emitted from the pool. Selected correlation should ensure the best compliance of numerical results with the measurements' results of these parameters in the facility. The numerical model of the natatorium was developed, for which boundary conditions were prepared on the basis of measurements' results carried out in the actual facility. Numerical calculations were carried out with the use of ANSYS CFX software, with six formulas being implemented, which in various ways made the moisture emission dependent on water surface temperature and air parameters in the natatorium. The results of calculations with the use of these formulas were compared for air parameters' distributions: Specific humidity, velocity and temperature in the facility. For the selection of the best formula, numerical results of these parameters in occupied zone were validated by comparison with the measurements' results carried out at selected points of this zone.

Keywords: Experimental validation, indoor swimming pool, moisture emission, natatorium, numerical calculations, CFD, thermal and humidity conditions, ventilation.

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1151 Reliability Based Investigation on the Choice of Characteristic Soil Properties

Authors: Jann-Eike Saathoff, Kirill Alexander Schmoor, Martin Achmus, Mauricio Terceros

Abstract:

By using partial factors of safety, uncertainties due to the inherent variability of the soil properties and loads are taken into account in the geotechnical design process. According to the reliability index concept in Eurocode-0 in conjunction with Eurocode-7 a minimum safety level of β = 3.8 for reliability class RC2 shall be established. The reliability of the system depends heavily on the choice of the prespecified safety factor and the choice of the characteristic soil properties. The safety factors stated in the standards are mainly based on experience. However, no general accepted method for the calculation of a characteristic value within the current design practice exists. In this study, a laterally loaded monopile is investigated and the influence of the chosen quantile values of the deterministic system, calculated with p-y springs, will be presented. Monopiles are the most common foundation concepts for offshore wind energy converters. Based on the calculations for non-cohesive soils, a recommendation for an appropriate quantile value for the necessary safety level according to the standards for a deterministic design is given.

Keywords: Asymptotic sampling, characteristic value, monopile foundation, probabilistic design, quantile values.

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1150 Rainfall and Flood Forecast Models for Better Flood Relief Plan of the Mae Sot Municipality

Authors: S. Chuenchooklin, S. Taweepong, U. Pangnakorn

Abstract:

This research was conducted in the Mae Sot Watershed where located in the Moei River Basin at the Upper Salween River Basin in Tak Province, Thailand. The Mae Sot Municipality is the largest urban area in Tak Province and situated in the midstream of the Mae Sot Watershed. It usually faces flash flood problem after heavy rain due to poor flood management has been reported since economic rapidly bloom up in recent years. Its catchment can be classified as ungauged basin with lack of rainfall data and no any stream gaging station was reported. It was attached by most severely flood events in 2013 as the worst studied case for all those communities in this municipality. Moreover, other problems are also faced in this watershed, such shortage water supply for domestic consumption and agriculture utilizations including a deterioration of water quality and landslide as well. The research aimed to increase capability building and strengthening the participation of those local community leaders and related agencies to conduct better water management in urban area was started by mean of the data collection and illustration of the appropriated application of some short period rainfall forecasting model as they aim for better flood relief plan and management through the hydrologic model system and river analysis system programs. The authors intended to apply the global rainfall data via the integrated data viewer (IDV) program from the Unidata with the aim for rainfall forecasting in a short period of 7-10 days in advance during rainy season instead of real time record. The IDV product can be present in an advance period of rainfall with time step of 3-6 hours was introduced to the communities. The result can be used as input data to the hydrologic modeling system model (HEC-HMS) for synthesizing flood hydrographs and use for flood forecasting as well. The authors applied the river analysis system model (HEC-RAS) to present flood flow behaviors in the reach of the Mae Sot stream via the downtown of the Mae Sot City as flood extents as the water surface level at every cross-sectional profiles of the stream. Both models of HMS and RAS were tested in 2013 with observed rainfall and inflow-outflow data from the Mae Sot Dam. The result of HMS showed fit to the observed data at the dam and applied at upstream boundary discharge to RAS in order to simulate flood extents and tested in the field, and the result found satisfying. The product of rainfall from IDV was fair while compared with observed data. However, it is an appropriate tool to use in the ungauged catchment to use with flood hydrograph and river analysis models for future efficient flood relief plan and management.

Keywords: Global rainfall, flood forecasting, hydrologic modeling system, river analysis system.

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1149 Framework and System for Supplier Scouting Enabling Web-based Collaboration

Authors: Sangil Lee, Kwangyeol Ryu, Kezia Amanda Kurniadi, Yongju Park

Abstract:

Nowadays, many manufacturing companies try to reinforce their competitiveness or find a breakthrough by considering collaboration. In Korea, more than 900 manufacturing companies are using web-based collaboration systems developed by the government-led project, referred to as i-Manufacturing. The system supports some similar functions of Product Data Management (PDM) as well as Project Management System (PMS). A web-based collaboration system provides many useful functions for collaborative works. This system, however, does not support new linking services between buyers and suppliers. Therefore, in order to find new collaborative partners, this paper proposes a framework which creates new connections between buyers and suppliers facilitating their collaboration, referred to as Excellent Manufacturer Scouting System (EMSS). EMSS plays a role as a bridge between overseas buyers and suppliers. As a part of study on EMSS, we also propose an evaluation method of manufacturability of potential partners with six main factors. Based on the results of evaluation, buyers may get a good guideline to choose their new partners before getting into negotiation processes with them.

Keywords: Supplier Scouting, Supplier Discovery, Collaboration, Web-based Collaboration System, Excellent Manufacturer Scouting System (EMSS)

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1148 Development of Perez-Du Mortier Calibration Algorithm for Ground-Based Aerosol Optical Depth Measurement with Validation using SMARTS Model

Authors: Jedol Dayou, Jackson Hian Wui Chang, Rubena Yusoff, Ag. Sufiyan Abd. Hamid, Fauziah Sulaiman, Justin Sentian

Abstract:

Aerosols are small particles suspended in air that have wide varying spatial and temporal distributions. The concentration of aerosol in total columnar atmosphere is normally measured using aerosol optical depth (AOD). In long-term monitoring stations, accurate AOD retrieval is often difficult due to the lack of frequent calibration. To overcome this problem, a near-sea-level Langley calibration algorithm is developed using the combination of clear-sky detection model and statistical filter. It attempts to produce a dataset that consists of only homogenous and stable atmospheric condition for the Langley calibration purposes. In this paper, a radiance-based validation method is performed to further investigate the feasibility and consistency of the proposed algorithm at different location, day, and time. The algorithm is validated using SMARTS model based n DNI value. The overall results confirmed that the proposed calibration algorithm feasible and consistent for measurements taken at different sites and weather conditions.

Keywords: Aerosol optical depth, direct normal irradiance, Langley calibration, radiance-based validation, SMARTS.

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1147 Missing Link Data Estimation with Recurrent Neural Network: An Application Using Speed Data of Daegu Metropolitan Area

Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

Abstract:

In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: Data Estimation, link data, machine learning, road network.

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