Search results for: Plant Extract.

Authors: M. Capocelli, A. Caputo, M. De Falco, D. Mazzei, V. Piemonte

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This paper presents the experimental results and the related modeling of a thermal energy storage (TES) facility, ideated and realized by ENEA and realizing the thermocline with an innovative geometry. Firstly, the thermal energy exchange model of an equivalent shell & tube heat exchanger is described and tested to reproduce the performance of the spiral exchanger installed in the TES. Through the regression of the experimental data, a first-order thermocline model was also validated to provide an analytical function of the thermocline, useful for the performance evaluation and the comparison with other systems and implementation in simulations of integrated systems (e.g. power plants). The experimental data obtained from the plant start-up and the short-cut modeling of the system can be useful for the process analysis, for the scale-up of the thermal storage system and to investigate the feasibility of its implementation in actual case-studies.

Keywords: Thermocline, modelling, heat exchange, spiral, shell, tube.

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Authors: Chaimongkol Limpianchob

Abstract:

This work addresses the problem of production planning that arises in the production of aromatic coconuts from Samudsakhorn province in Thailand. The planning involves the forwarding of aromatic coconuts from the harvest areas to the factory, which is classified into two groups; self-owned areas and contracted areas, the decisions of aromatic coconuts flow in the plant, and addressing a question of which warehouse will be in use. The problem is formulated as a mixed-integer linear programming model within supply chain management framework. The objective function seeks to minimize the total cost including the harvesting, labor and inventory costs. Constraints on the system include the production activities in the company and demand requirements. Numerical results are presented to demonstrate the feasibility of coconuts supply chain model compared with base case.

Keywords: Aromatic coconut, supply chain management, production planning, mixed-integer linear programming.

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: Data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse.

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Authors: Bokyung Sung, Jungsoo Kim, Jinman Kwun, Junhyung Park, Jihye Ryeo, Ilju Ko

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In this paper, we propose a practical digital music matching system that is robust to variation in sound qualities. The proposed system is subdivided into two parts: client and server. The client part consists of the input, preprocessing and feature extraction modules. The preprocessing module, including the music onset module, revises the value gap occurring on the time axis between identical songs of different formats. The proposed method uses delta-grouped Mel frequency cepstral coefficients (MFCCs) to extract music features that are robust to changes in sound quality. According to the number of sound quality formats (SQFs) used, a music server is constructed with a feature database (FD) that contains different sub feature databases (SFDs). When the proposed system receives a music file, the selection module selects an appropriate SFD from a feature database; the selected SFD is subsequently used by the matching module. In this study, we used 3,000 queries for matching experiments in three cases with different FDs. In each case, we used 1,000 queries constructed by mixing 8 SQFs and 125 songs. The success rate of music matching improved from 88.6% when using single a single SFD to 93.2% when using quadruple SFDs. By this experiment, we proved that the proposed method is robust to various sound qualities.

Keywords: Digital Music, Music Matching, Variation in Sound Qualities, Robust Matching method.

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Authors: Oliver Mărunţălu, Gheorghe Lăzăroiu, Elena Elisabeta Manea, Dana Andreya Bondrea, Lăcrămioara Diana Robescu

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This paper presents the results obtained by numerical simulation using the software ANSYS CFX-CFD for the air pollutants dispersion in the atmosphere coming from the evacuation of combustion gases resulting from the fuel combustion in an electric thermal power plant. The model uses the Navier-Stokes equation to simulate the dispersion of pollutants in the atmosphere. It is considered as important factors in elaboration of simulation the atmospheric conditions (pressure, temperature, wind speed, wind direction), the exhaust velocity of the combustion gases, chimney height and the obstacles (buildings). Using the air quality monitoring stations it is measured the concentrations of main pollutants (SO2, NOx and PM). The pollutants were monitored over a period of 3 months, after that the average concentration are calculated, which is used by the software. The concentrations are: 8.915 μg/m3 (NOx), 9.587 μg/m3 (SO2) and 42 μg/m3 (PM). A comparison of test data with simulation results demonstrated that CFX was able to describe the dispersion of the pollutant as well the concentration of this pollutants in the atmosphere.

Keywords: Air pollutants, computational fluid dynamics, dispersion, simulation.

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Authors: M.M. Jafarpour, Ar. Foolad, M.K. Mansouri, Z. Nikbakhsh, H. Saeedizade

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Ammonia nitrogen is one of the most hazardous water pollutants, discharging into water receptors through industrial effluents. Negative environmental impacts of such chemical species in hydrosphere include accelerated eutrophication, water toxicity and harming the aquatics. Natural zeolite clinoptilolite has very high selectivity & capacity for ammonium cation sorption. It occurs in high abundances and rich mines of this zeolite exist in different parts of Iran and thus are available more cheaply and with different sizing. The aim of this study is to investigate ammonia nitrogen removal over this natural sorbent from real samples of high polluted wastewater discharging from a fertilizer producing plant. The experimental results showed that this natural sorbent without even any pre treatment system & with the same particle size available in Iranian markets has still high capability & selectivity in ammonia nitrogen removal both in batch and continuous tests.

Keywords: Ammonia nitrogen removal, Clinoptilolite, Naturalzeolite, Waste water.

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Authors: C. Chaiyaraksa, T. Khamko

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This study investigated the influence of limestone and sepiolite on heavy metals accumulation in the soil and soybean. The soil was synthesized to contaminate with zinc 150 mg/kg, copper 100 mg/kg, and cadmium 1 mg/kg. The contaminated soil was mixed with limestone and sepiolite at the ratio of 1:0, 0:1, 1:1, and 2:1. The amount of soil modifier added to soil was 0.2%, 0.4%, and 0.8%. The metals determination was performed on soil both before and after soybean planting and in the root, shoot, and seed of soybean after harvesting. The study was also on metal translocate from root to seed and on bioaccumulation factor. Using of limestone and sepiolite resulted in a reduction of metals accumulated in soybean. For soil containing a high concentration of copper, cadmium, and zinc, a mixture of limestone and sepiolite (1:1) was recommended to mix with soil with the amount of 0.2%. Zinc could translocate from root to seed more than copper, and cadmium. From studying the movement of metals from soil to accumulate in soybean, the result was that soybean could absorb the highest amount of cadmium, followed by zinc, and copper, respectively.

Keywords: Heavy metals, limestone, sepiolite, soil, soybean.

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Authors: M. M. Mon, S. S. Maw, Z. K. Oo

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Antioxidant activities of ethanolic extracts of Ardisia japonica Blume., Ageartum conyzoides Linn., and Cocculus hirsutus Linn Diels. leaves was determined qualitatively and quantitatively in this research. 1, 1-diphenyl-2-picrylhydrazyl (DPPH) free radical solution was used to investigate free radical scavenging activity of these leaves extracts. Ascorbic acid (Vitamin C) was used as the standard. In the present investigation, it is found that all of these extracts have remarkable antioxidant activities. The EC50 values of these ethanolic extracts were 12.72 μg/ml for A. japonica, 15.19 μg/ml for A. conyzoides, 10.68 μg/ml for C. hirsutus respectively. Among these Myanmar medicinal plants, C. hirsutus showed higher antioxidant activities as well as free radical scavenging activity than black tea (Camellia sinensis), the famous antioxidant, and A. japonica and A. conyzoides showed a rather lower antioxidant activity than tea extracts. According to results from bioassay with carrot discs infected with Agrobacterium tumefaciens, all extracts showed anti-tumor activity after 3 weeks of incubation. No gall was detected in carrot disks treated with C. hirsutus and A. japonica extracts in the dose of 100ppm and in carrot discs treated with A. conyzoides extract in the dose of 1000 ppm. Therefore, the research clearly indicates that these weedy plants of dry farm land are exceptionally advantageous for human health.

Keywords: Antioxidant, Anti-tumor activity, Carrot-discbioassay, DPPH

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Authors: Zehai Yu, Hui Zhu, Linglong Lin, Huawei Liang, Biao Yu, Weixin Huang

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With the development of intelligent vehicle systems, a high-precision road map is increasingly needed in many aspects. The automatic lane lines extraction and modeling are the most essential steps for the generation of a precise lane-level road map. In this paper, an automatic lane-level road map generation system is proposed. To extract the road markings on the ground, the multi-region Otsu thresholding method is applied, which calculates the intensity value of laser data that maximizes the variance between background and road markings. The extracted road marking points are then projected to the raster image and clustered using a two-stage clustering algorithm. Lane lines are subsequently recognized from these clusters by the shape features of their minimum bounding rectangle. To ensure the storage efficiency of the map, the lane lines are approximated to cubic polynomial curves using a Bayesian estimation approach. The proposed lane-level road map generation system has been tested on urban and expressway conditions in Hefei, China. The experimental results on the datasets show that our method can achieve excellent extraction and clustering effect, and the fitted lines can reach a high position accuracy with an error of less than 10 cm.

Keywords: Curve fitting, lane-level road map, line recognition, multi-thresholding, two-stage clustering.

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Authors: Nuzlinda Abdul Rahman, Syerrina Zakaria

Abstract:

Deprivation indices are widely used in public health study. These indices are also referred as the index of inequalities or disadvantage. Even though, there are many indices that have been built before, it is believed to be less appropriate to use the existing indices to be applied in other countries or areas which had different socio-economic conditions and different geographical characteristics. The objective of this study is to construct the index based on the geographical and socio-economic factors in Peninsular Malaysia which is defined as the weighted household-based deprivation index. This study has employed the variables based on household items, household facilities, school attendance and education level obtained from Malaysia 2000 census report. The factor analysis is used to extract the latent variables from indicators, or reducing the observable variable into smaller amount of components or factor. Based on the factor analysis, two extracted factors were selected, known as Basic Household Amenities and Middle-Class Household Item factor. It is observed that the district with a lower index values are located in the less developed states like Kelantan, Terengganu and Kedah. Meanwhile, the areas with high index values are located in developed states such as Pulau Pinang, W.P. Kuala Lumpur and Selangor.

Keywords: Factor Analysis, Basic Household Amenities, Middle-Class Household Item, Socio-economic Index

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Authors: Josip Vasilj, Petar Sarajcev, Damir Jakus

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One of the major difficulties introduced with wind power penetration is the inherent uncertainty in production originating from uncertain wind conditions. This uncertainty impacts many different aspects of power system operation, especially the balancing power requirements. For this reason, in power system development planing, it is necessary to evaluate the potential uncertainty in future wind power generation. For this purpose, simulation models are required, reproducing the performance of wind power forecasts. This paper presents a wind power forecast error simulation models which are based on the stochastic process simulation. Proposed models capture the most important statistical parameters recognized in wind power forecast error time series. Furthermore, two distinct models are presented based on data availability. First model uses wind speed measurements on potential or existing wind power plant locations, while the seconds model uses statistical distribution of wind speeds.

Keywords: Wind power, Uncertainty, Stochastic process, Monte Carlo simulation.

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Authors: Yong Zhao, Jian He, Cheng Zhang

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Cardiovascular disease resulting from hypertension poses a significant threat to human health, and early detection of hypertension can potentially save numerous lives. Traditional methods for detecting hypertension require specialized equipment and are often incapable of capturing continuous blood pressure fluctuations. To address this issue, this study starts by analyzing the principle of heart rate variability (HRV) and introduces the utilization of sliding window and power spectral density (PSD) techniques to analyze both temporal and frequency domain features of HRV. Subsequently, a hypertension prediction network that relies on HRV is proposed, combining Resnet, attention mechanisms, and a multi-layer perceptron. The network leverages a modified ResNet18 to extract frequency domain features, while employing an attention mechanism to integrate temporal domain features, thus enabling auxiliary hypertension prediction through the multi-layer perceptron. The proposed network is trained and tested using the publicly available SHAREE dataset from PhysioNet. The results demonstrate that the network achieves a high prediction accuracy of 92.06% for hypertension, surpassing traditional models such as K Near Neighbor (KNN), Bayes, Logistic regression, and traditional Convolutional Neural Network (CNN).

Keywords: Feature extraction, heart rate variability, hypertension, residual networks.

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Authors: J. Fernandez de Canete, S. Gonzalez-Perez, P. del Saz-Orozco, I. Garcia-Moral

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Robust stability and performance are the two most basic features of feedback control systems. The harmonic balance analysis technique enables to analyze the stability of limit cycles arising from a neural network control based system operating over nonlinear plants. In this work a robust stability analysis based on the harmonic balance is presented and applied to a neural based control of a non-linear binary distillation column with unstructured uncertainty. We develop ways to describe uncertainty in the form of neglected nonlinear dynamics and high harmonics for the plant and controller respectively. Finally, conclusions about the performance of the neural control system are discussed using the Nyquist stability margin together with the structured singular values of the uncertainty as a robustness measure.

Keywords: Robust stability, neural network control, unstructured uncertainty, singular values, distillation column.

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Authors: Luay A. Fraiwan, Natheer Y. Khaswaneh, Khaldon Y. Lweesy

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Sleep stage scoring is the process of classifying the stage of the sleep in which the subject is in. Sleep is classified into two states based on the constellation of physiological parameters. The two states are the non-rapid eye movement (NREM) and the rapid eye movement (REM). The NREM sleep is also classified into four stages (1-4). These states and the state wakefulness are distinguished from each other based on the brain activity. In this work, a classification method for automated sleep stage scoring based on a single EEG recording using wavelet packet decomposition was implemented. Thirty two ploysomnographic recording from the MIT-BIH database were used for training and validation of the proposed method. A single EEG recording was extracted and smoothed using Savitzky-Golay filter. Wavelet packets decomposition up to the fourth level based on 20th order Daubechies filter was used to extract features from the EEG signal. A features vector of 54 features was formed. It was reduced to a size of 25 using the gain ratio method and fed into a classifier of regression trees. The regression trees were trained using 67% of the records available. The records for training were selected based on cross validation of the records. The remaining of the records was used for testing the classifier. The overall correct rate of the proposed method was found to be around 75%, which is acceptable compared to the techniques in the literature.

Keywords: Features selection, regression trees, sleep stagescoring, wavelet packets.

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Authors: Togzhan D. Mukasheva, Anel A. Omirbekova, Raikhan S. Sydykbekova, Ramza Zh. Berzhanova, Lyudmila V. Ignatova

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Following plants-barley (Hordeum sativum), alfalfa (Medicago sativa), grass mixture (red fescue-75%, long-term ryegrass - 20% Kentucky bluegrass - 10%), oilseed rape (Brassica napus biennis), resistant to growth in the contaminated soil with oil content of 15.8 g / kg 25.9 g / kg soil were used. Analysis of the population showed that the oil pollution reduces the number of bacteria in the rhizosphere and rhizoplane of plants and enhances the amount of spore-forming bacteria and saprotrophic micromycetes. It was shown that regardless of the plant, dominance of Pseudomonas and Bacillus genera bacteria was typical for the rhizosphere and rhizoplane of plants. The frequency of bacteria of these genera was more than 60%. Oil pollution changes the ratio of occurrence of various types of bacteria in the rhizosphere and rhizoplane of plants. Besides the Pseudomonas and Bacillus genera, in the presence of hydrocarbons in the root zone of plants dominant and most typical were the representatives of the Mycobacterium and Rhodococcus genera. Together the number was between 62% to 72%.

Keywords: Identification, micromycetes, pollution, root system.

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Authors: Jameela Ali Alkrimi, Loay E. George, Azizah Suliman, Abdul Rahim Ahmad, Karim Al-Jashamy

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. Anemia is a lack of RBCs is characterized by its level compared to the normal hemoglobin level. In this study, a system based image processing methodology was developed to localize and extract RBCs from microscopic images. Also, the machine learning approach is adopted to classify the localized anemic RBCs images. Several textural and geometrical features are calculated for each extracted RBCs. The training set of features was analyzed using principal component analysis (PCA). With the proposed method, RBCs were isolated in 4.3secondsfrom an image containing 18 to 27 cells. The reasons behind using PCA are its low computation complexity and suitability to find the most discriminating features which can lead to accurate classification decisions. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network RBFNN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained within short time period, and the results became better when PCA was used.

Keywords: Red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC.

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Authors: A. Tellaeche, X. P. Burgos-Artizzu, G. Pajares, A. Ribeiro

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One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.

Keywords: Fuzzy k-Means, Precision agriculture, SupportVectors Machines, Weed detection.

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Authors: H. C. Chang, J. R. Wang, A. L. Ho, S. W. Chen, J. H. Yang, C. Shih, L. C. Wang

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To confirm the reactor and containment integrity of the Advanced Boiling Water Reactor (ABWR), we perform the analysis of main steamline break (MSLB) transient by using the TRACE, PARCS, and SNAP codes. The process of the research has four steps. First, the ABWR nuclear power plant (NPP) model is developed by using the above codes. Second, the steady state analysis is performed by using this model. Third, the ABWR model is used to run the analysis of MSLB transient. Fourth, the predictions of TRACE and PARCS are compared with the data of FSAR. The results of TRACE/PARCS and FSAR are similar. According to the TRACE/PARCS results, the reactor and containment integrity of ABWR can be maintained in a safe condition for MSLB.

Keywords: ABWR, TRACE, PARCS, SNAP.

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Authors: Aumnad Phdungsilp, Teeradej Wuttipornpun

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Decision support based upon risk analysis into comparison of the electricity generation from different renewable energy technologies can provide information about their effects on the environment and society. The aim of this paper is to develop the assessment framework regarding risks to health and environment, and the society-s benefits of the electric power plant generation from different renewable sources. The multicriteria framework to multiattribute risk analysis technique and the decision analysis interview technique are applied in order to support the decisionmaking process for the implementing renewable energy projects to the Bangkok case study. Having analyses the local conditions and appropriate technologies, five renewable power plants are postulated as options. As this work demonstrates, the analysis can provide a tool to aid decision-makers for achieving targets related to promote sustainable energy system.

Keywords: Analytic Hierarchy Process, Bangkok, MultiattributeRisk Analysis, Renewable Energy Technology.

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Authors: Elena Fauquet-Alekhine-Pavlovskaya, Irina M. Nesterova

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On the territory of France fenugreek is spread since long on a line from the Gironde to the Italian border. In Belarus experimental cultivation has begun since 2004. Experiments with fenugreek variety Ovari 4 were conducted about time of sowing in order to study their growth, development, and evaluation of productivity in the North-east part of Belarus and Central part of France. Reaching full ripeness of seeds the plants of fenugreek in the Central part of France requires about 94-97 days. Average seeds yield of 2011-2012 is 1259 kg/ha. Plant height is about 36,8 cm. Plants were affected by aphid and in the high moist agro-climatic conditions by powdery mildew. In North-east part of Belarus plants need 86-93 days to full ripeness. Plants of fenugreek have steam about 59 cm. The average seeds yield of 2007-2009 was about 723 kg/ha. Plants were resistant to aphid and diseases.

Keywords: Fenugreek, time of sowing, variety, yield.

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Authors: Wei-Pin Tseng, Jie-Chung Lou, Ming-Ching Wu, Huang-Ming Fang

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For stricter drinking water regulations in the future, reducing the humic acid and disinfection byproducts in raw water, namely, trihalomethanes (THMs) and haloacetic acids (HAAs) is worthy for research. To investigate the removal of waterborne organic material using a lab-scale of bio-activated carbon filter under different EBCT, the concentrations of humic acid prepared were 0.01, 0.03, 0.06, 0.12, 0.17, 0.23, and 0.29 mg/L. Then we conducted experiments using a pilot plant with in-field of the serially connected bio-activated carbon filters and hollow fiber membrane processes employed in traditional water purification plants. Results showed under low TOC conditions of humic acid in influent (0.69 to 1.03 mg TOC/L) with an EBCT of 30 min, 40 min, and 50 min, TOC removal rates increases with greater EBCT, attaining about 39 % removal rate. The removal rate of THMs and HAAs by BACF was 54.8 % and 89.0 %, respectively.

Keywords: Bio-activated carbon filter, hollow fiber membrane, humic acid, THMs, HAAs, Water Treatment

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Authors: İres İskender, Ahmet Karaarslan

Abstract:

In this study, the performance of a high-frequency arc welding machine including a two-switch inverter is analyzed. The control of the system is achieved using two different control techniques i- fuzzy logic control (FLC) ii- state space averaging based sliding control. Fuzzy logic control does not need accurate mathematical model of a plant and can be used in nonlinear applications. The second method needs the mathematical model of the system. In this method the state space equations of the system are derived for two different “on" and “off" states of the switches. The derived state equations are combined with the sliding control rule considering the duty-cycle of the converter. The performance of the system is analyzed by simulating the system using SIMULINK tool box of MATLAB. The simulation results show that fuzzy logic controller is more robust and less sensitive to parameter variations.

Keywords: Fuzzy logic, arc welding, sliding state space control, PWM, current control.

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Authors: Po-Chuang Chen, Hsiu-Mei Chiu, Yau-Pin Chyou, Chiou-Shia Yu

Abstract:

This study presents a simulation model for converting coal to methanol, based on gasification technology with the commercial chemical process simulator, Pro/II® V8.1.1. The methanol plant consists of air separation unit (ASU), gasification unit, gas clean-up unit, and methanol synthetic unit. The clean syngas is produced with the first three operating units, and the model has been verified with the reference data from United States Environment Protection Agency. The liquid phase methanol (LPMEOHTM) process is adopted in the methanol synthetic unit. Clean syngas goes through gas handing section to reach the reaction requirement, reactor loop/catalyst to generate methanol, and methanol distillation to get desired purity over 99.9 wt%. The ratio of the total energy combined with methanol and dimethyl ether to that of feed coal is 78.5% (gross efficiency). The net efficiency is 64.2% with the internal power consumption taken into account, based on the assumption that the efficiency of electricity generation is 40%.

Keywords: Gasification, Methanol, LPMEOH, System-levelsimulation.

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Authors: D. Pujimulyani, S. Raharjo, Y. Marsono, U. Santoso

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Background and objectives: Most of the agricultural products are processed by blanching. Blanching can increase antioxidant activity in white saffron products. The objective of this research were to determine antioxidant activity, to identify, and to measure changes in phenolic substances of fresh and blanched white saffron rhizomes (Curcuma mangga Val.). Methods: White saffron rhizomes were peeled, washed and blanched in boiling water containing 0% or 0.05% citric acid solution for 5 and 10 minutes. Samples were extracted using methanol, rotaevaporated, and freezedried. Dried extract was determined antioxidant activity by DPPH method, identified and quantified for the phenolic substances by High Performance Liquid Chromatography (HPLC) equipped with coloumn C₁₈ and Photodiode-array detector (PAD). Result: This research showed that the quantity of the 6 phenolic substances identified in blanched white saffron in citric acid solution increased significantly compared to that of the non-blanched. Blanching white saffron in 0.05% citric acid media for 5 minutes increased its antioxidant activity, and total phenolic content. Conclusions: The identified phenolic substances of white saffron were Gallic Acid (GA), Catechin (C), Epicatechin (EC), Epigallocatechin (EGC), Epigallocatechingallat (EGCG) and Gallocatechingallat (GCG). The blanched white saffron contained C and EGCG significantly higher than that of fresh rhizomes.

Keywords: White saffron, antioxidant activity, blanching, phenolic.

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Authors: Sulata Maharana, B Biswas, Adity Ganguly, Ashok Kumar

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In this paper, the requirement for Coke quality prediction, its role in Blast furnaces, and the model output is explained. By applying method of Artificial Neural Networking (ANN) using back propagation (BP) algorithm, prediction model has been developed to predict CSR. Important blast furnace functions such as permeability, heat exchanging, melting, and reducing capacity are mostly connected to coke quality. Coke quality is further dependent upon coal characterization and coke making process parameters. The ANN model developed is a useful tool for process experts to adjust the control parameters in case of coke quality deviations. The model also makes it possible to predict CSR for new coal blends which are yet to be used in Coke Plant. Input data to the model was structured into 3 modules, for tenure of past 2 years and the incremental models thus developed assists in identifying the group causing the deviation of CSR.

Keywords: Artificial Neural Networks, backpropagation, CokeStrength after Reaction, Multilayer Perceptron.

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Authors: J. R. Wang, Y. Chiang, W. Y. Li, H. T. Lin, H. C. Chen, C. Shih, S. W. Chen

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The dry-storage systems of nuclear power plants (NPPs) in Taiwan have become one of the major safety concerns. There are two steps considered in this study. The first step is the verification of the TRACE by using VSC-17 experimental data. The results of TRACE were similar to the VSC-17 data. It indicates that TRACE has the respectable accuracy in the simulation and analysis of the dry-storage systems. The next step is the application of TRACE in the dry-storage system of Kuosheng NPP (BWR/6). Kuosheng NPP is the second BWR NPP of Taiwan Power Company. In order to solve the storage of the spent fuels, Taiwan Power Company developed the new dry-storage system for Kuosheng NPP. In this step, the dry-storage system model of Kuosheng NPP was established by TRACE. Then, the steady state simulation of this model was performed and the results of TRACE were compared with the Kuosheng NPP data. Finally, this model was used to perform the safety analysis of Kuosheng NPP dry-storage system. Besides, FRAPTRAN was used tocalculate the transient performance of fuel rods.

Keywords: BWR, TRACE, FRAPTRAN, Dry-Storage.

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Authors: A. Sharma, R. Tewari, S. K. Soni

Abstract:

Biofuels production has come forth as a future technology to combat the problem of depleting fossil fuels. Bio-based ethanol production from enzymatic lignocellulosic biomass degradation serves an efficient method and catching the eye of scientific community. High cost of the enzyme is the major obstacle in preventing the commercialization of this process. Thus main objective of the present study was to optimize composition of medium components for enhancing cellulase production by newly isolated strain of Bacillus tequilensis. Nineteen factors were taken into account using statistical Plackett-Burman Design. The significant variables influencing the cellulose production were further employed in statistical Response Surface Methodology using Central Composite Design for maximizing cellulase production. The optimum medium composition for cellulase production was: peptone (4.94 g/L), ammonium chloride (4.99 g/L), yeast extract (2.00 g/L), Tween-20 (0.53 g/L), calcium chloride (0.20 g/L) and cobalt chloride (0.60 g/L) with pH 7, agitation speed 150 rpm and 72 h incubation at 37oC. Analysis of variance (ANOVA) revealed high coefficient of determination (R2) of 0.99. Maximum cellulase productivity of 11.5 IU/ml was observed against the model predicted value of 13 IU/ml. This was found to be optimally active at 60oC and pH 5.5.

Keywords: Bacillus tequilensis, CMCase, Submerged Fermentation, Optimization, Plackett-Burman Design, Response Surface Methodology.

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Authors: Monika Chuchro

Abstract:

This paper presents a preliminary attempt to apply classification of time series using meta-clusters in order to improve the quality of regression models. In this case, clustering was performed as a method to obtain subgroups of time series data with normal distribution from the inflow into wastewater treatment plant data, composed of several groups differing by mean value. Two simple algorithms, K-mean and EM, were chosen as a clustering method. The Rand index was used to measure the similarity. After simple meta-clustering, a regression model was performed for each subgroups. The final model was a sum of the subgroups models. The quality of the obtained model was compared with the regression model made using the same explanatory variables, but with no clustering of data. Results were compared using determination coefficient (R2), measure of prediction accuracy- mean absolute percentage error (MAPE) and comparison on a linear chart. Preliminary results allow us to foresee the potential of the presented technique.

Keywords: Clustering, Data analysis, Data mining, Predictive models.

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Authors: Teti Estiasih, Harijono, Weny Bekti Sunarharum, Atina Rahmawati

Abstract:

This research studied the hypoglycemic effect of water soluble polysaccharide (WSP) extracted from yam (Dioscorea hispida) tuber by three different methods: aqueous extraction, papain assisted extraction, and tempeh inoculums assisted extraction. The two later extraction methods were aimed to remove WSP binding protein to have more pure WSP. The hypoglycemic activities were evaluated by means in vivo test on alloxan induced hyperglycemic rats, glucose response test (GRT), in situ glucose absorption test using everted sac, and short chain fatty acids (SCFAs) analysis. All yam WSP extracts exhibited ability to decrease blood glucose level in hyperglycemia condition as well as inhibited glucose absorption and SCFA formation. The order of hypoglycemic activity was tempeh inoculums assisted- >papain assisted- >aqueous WSP extracts. GRT and in situ glucose absorption test showed that order of inhibition was papain assisted- >tempeh inoculums assisted- >aqueous WSP extracts. Digesta of caecum of yam WSP extracts oral fed rats had more SCFA than control. Tempeh inoculums assisted WSP extract exhibited the most significant hypoglycemic activity.

Keywords: hypoglycemic activity, papain, tempeh inoculums, water soluble polysaccharides, yam (Discorea hispida)

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Authors: S. A. Gawish, F. A. Khalifa, R. M. Mostafa

Abstract:

This paper presents Simulation and experimental study aimed at investigating the effectiveness of an adaptive artificial neural network stabilizer on enhancing the damping torque of a synchronous generator. For this purpose, a power system comprising a synchronous generator feeding a large power system through a short tie line is considered. The proposed adaptive neuro-control system consists of two multi-layered feed forward neural networks, which work as a plant model identifier and a controller. It generates supplementary control signals to be utilized by conventional controllers. The details of the interfacing circuits, sensors and transducers, which have been designed and built for use in tests, are presented. The synchronous generator is tested to investigate the effect of tuning a Power System Stabilizer (PSS) on its dynamic stability. The obtained simulation and experimental results verify the basic theoretical concepts.

Keywords: Adaptive artificial neural network, power system stabilizer, synchronous generator.

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