Search results for: Content- Based Recommendation

Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

This paper presents an interval-based multi-attribute decision making (MADM) approach in support of the decision process with imprecise information. The proposed decision methodology is based on the model of linear additive utility function but extends the problem formulation with the measure of composite utility variance. A sample study concerning with the evaluation of electric generation expansion strategies is provided showing how the imprecise data may affect the choice toward the best solution and how a set of alternatives, acceptable to the decision maker (DM), may be identified with certain confidence.

Keywords: Decision Making, Power Generation, ElectricUtilities, Resource Planning.

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Authors: Zilong He, Yuesheng Zhu

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Based on the combined shape feature and texture feature, a fast object detection method with rotation invariant features is proposed in this paper. A quick template matching scheme based online learning designed for online applications is also introduced in this paper. The experimental results have shown that the proposed approach has the features of lower computation complexity and higher detection rate, while keeping almost the same performance compared to the HOG-based method, and can be more suitable for run time applications.

Keywords: gradient feature, online learning, rotationinvariance, template feature

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Authors: Ali Ganoun

Abstract:

This paper proposes evaluation of sound parameterization methods in recognizing some spoken Arabic words, namely digits from zero to nine. Each isolated spoken word is represented by a single template based on a specific recognition feature, and the recognition is based on the Euclidean distance from those templates. The performance analysis of recognition is based on four parameterization features: the Burg Spectrum Analysis, the Walsh Spectrum Analysis, the Thomson Multitaper Spectrum Analysis and the Mel Frequency Cepstral Coefficients (MFCC) features. The main aim of this paper was to compare, analyze, and discuss the outcomes of spoken Arabic digits recognition systems based on the selected recognition features. The results acqired confirm that the use of MFCC features is a very promising method in recognizing Spoken Arabic digits.

Keywords: Speech Recognition, Spectrum Analysis, Burg Spectrum, Walsh Spectrum Analysis, Thomson Multitaper Spectrum, MFCC.

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Authors: Nathan W. Manthey, Francisco Cardona, Gaston M. Francucci, Thiru Aravinthan

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Novel acrylated epoxidized hemp oil (AEHO) based bioresins were successfully synthesised, characterized and applied to biocomposites reinforced with woven jute fibre. Characterisation of the synthesised AEHO consisted of acid number titrations and FTIR spectroscopy to assess the success of the acrylation reaction. Three different matrices were produced (vinylester (VE), 50/50 blend of AEHO/VE and 100% AEHO) and reinforced with jute fibre to form three different types of biocomposite samples. Mechanical properties in the form of flexural and interlaminar shear strength (ILSS) were investigated and compared for the different samples. Results from the mechanical tests showed that AEHO and 50/50 based neat bioresins displayed lower flexural properties compared with the VE samples. However when applied to biocomposites and compared with VE based samples, AEHO biocomposites demonstrated comparable flexural performance and improved ILSS. These results are attributed to improved fibre-matrix interfacial adhesion due to surface-chemical compatibility between the natural fibres and bioresin.

Keywords: Biocomposite, hemp oil based bioresin, green building materials, mechanical properties.

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Authors: S. Aouabdi, M. Taibi

Abstract:

This paper presents powerful techniques for the development of a new monitoring method based on multi-scale entropy (MSE) in order to characterize the behaviour of the concentrations of different gases present in the synthesis of Ammonia and soft-sensor based on Principal Component Analysis (PCA).

Keywords: Ammonia synthesis, concentrations of different gases, soft sensor, multi-scale entropy, multivariate statistics.

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Authors: Bing-Fei Wu, Yen-Lin Chen, Chung-Cheng Chiu

Abstract:

In this study, a new criterion for determining the number of classes an image should be segmented is proposed. This criterion is based on discriminant analysis for measuring the separability among the segmented classes of pixels. Based on the new discriminant criterion, two algorithms for recursively segmenting the image into determined number of classes are proposed. The proposed methods can automatically and correctly segment objects with various illuminations into separated images for further processing. Experiments on the extraction of text strings from complex document images demonstrate the effectiveness of the proposed methods.1

Keywords: image segmentation, multilevel thresholding, clustering, discriminant analysis

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Authors: Shipra Upadhyay , R. K. Nagaria, R. A. Mishra

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In this paper, we present the design and experimental evaluation of complementary energy path adiabatic logic (CEPAL) based 1 bit full adder circuit. A simulative investigation on the proposed full adder has been done using VIRTUOSO SPECTRE simulator of cadence in 0.18μm UMC technology and its performance has been compared with the conventional CMOS full adder circuit. The CEPAL based full adder circuit exhibits the energy saving of 70% to the conventional CMOS full adder circuit, at 100 MHz frequency and 1.8V operating voltage.

Keywords: Adiabatic, CEPAL, full adder, power clock

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Authors: Tea Poklepović, Zdravka Aljinović, Mario Matković

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Modern Portfolio Theory (MPT) according to Markowitz states that investors form mean-variance efficient portfolios which maximizes their utility. Markowitz proposed the standard deviation as a simple measure for portfolio risk and the lower semi-variance as the only risk measure of interest to rational investors. This paper uses a third volatility estimator based on intraday data and compares three efficient frontiers on the Croatian Stock Market. The results show that range-based volatility estimator outperforms both mean-variance and lower semi-variance model.

Keywords: Variance, lower semi-variance, range-based volatility.

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Authors: Un Hwa Choe, Jong Hyon Choe, Yong Jun Kim

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The aim of this study was to effectively remove Fe2+ by using ozone microbubbles in bottled mineral water to prevent sediment from occurring during storage and increase shelf life. By considering the characteristics of mineral water with low solubility of ozone and high CO2 content, a suitable ozone injection step was chosen and a mineral water treatment method using microbubbles was proposed. As a result of the treatment of the bottled mineral water with ozone microbubbles, the iron ion concentration was reduced from 0.14 mg/L to 0.01 mg/L, and the shelf life increased to 360 days. During the treatment, the concentrations of K+ and Na+ were almost unchanged, and the deposition time was reduced to one-third compared to the natural oxidation.

Keywords: CO2–rich mineral water, ozone-micro bubble, shelf life, bottled mineral water, water treatment.

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Authors: Nan Li, Ying Wang

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Using entropy weight and TOPSIS method, a comprehensive evaluation is done on the development level of Chinese regional service industry in this paper. Firstly, based on existing research results, an evaluation index system is constructed from the scale of development, the industrial structure and the economic benefits. An evaluation model is then built up based on entropy weight and TOPSIS, and an empirical analysis is conducted on the development level of service industries in 31 Chinese provinces during 2006 and 2009 from the two dimensions or time series and cross section, which provides new idea for assessing regional service industry. Furthermore, the 31 provinces are classified into four categories based on the evaluation results, and deep analysis is carried out on the evaluation results.

Keywords: Chinese regional service industry, Development level, Entropy weight, TOPSIS Evaluation Method

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Authors: M. W. Yip, H. H. Ng, S. Din, N. Abu Bakar

Abstract:

This paper reviewed the relationships between the Knowledge Management (KM) activities and its perceived benefits in the knowledge based organisations. KM activities include: knowledge identification, knowledge acquisition, knowledge application, knowledge sharing, knowledge creation and knowledge preservation. And the perceived benefits of KM are fast customer responsiveness, operation excellence and high innovative intensity.  Based on the above review, a conceptual framework for KM implementation in retail business organisations has been proposed. Finally the paper forwarded some limitations of the framework and based on which, directions for future research had been suggested.

Keywords: Knowledge Management, Knowledge Management Activities, Retail Business, Knowledge Economy.

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Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras

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The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

Keywords: MOEAs, Multiobjective optimization, ZDT test functions, performance metrics.

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Authors: M. R. Aghaebrahimi, S. H. Zahiri, M. Amiri

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In this paper a data miner based on the learning automata is proposed and is called LA-miner. The LA-miner extracts classification rules from data sets automatically. The proposed algorithm is established based on the function optimization using learning automata. The experimental results on three benchmarks indicate that the performance of the proposed LA-miner is comparable with (sometimes better than) the Ant-miner (a data miner algorithm based on the Ant Colony optimization algorithm) and CNZ (a well-known data mining algorithm for classification).

Keywords: Data mining, Learning automata, Classification rules, Knowledge discovery.

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Authors: D. Mondal, A. Chakrabarti, A. Sengupta

Abstract:

This paper aims to select the optimal location and setting parameters of TCSC (Thyristor Controlled Series Compensator) controller using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to mitigate small signal oscillations in a multimachine power system. Though Power System Stabilizers (PSSs) are prime choice in this issue, installation of FACTS device has been suggested here in order to achieve appreciable damping of system oscillations. However, performance of any FACTS devices highly depends upon its parameters and suitable location in the power network. In this paper PSO as well as GA based techniques are used separately and compared their performances to investigate this problem. The results of small signal stability analysis have been represented employing eigenvalue as well as time domain response in face of two common power system disturbances e.g., varying load and transmission line outage. It has been revealed that the PSO based TCSC controller is more effective than GA based controller even during critical loading condition.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Small Signal Stability, Thyristor Controlled Series Compensator.

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Authors: J. Ivorra-Martinez, L. Quiles-Carrillo, J. Gomez-Caturla, T. Boronat, R. Balart

Abstract:

The utilization of almond crop by-products to obtain Poly(3-hydroxybutyrat-co-3-hydroxyhexanoat) (PHBH)-based composites was carried out by using an extrusion process followed by an injection to obtain test samples. To improve the properties of the resulting composite, the incorporation of Oligomer Lactic Acid (OLA 8) as a coupling agent and plasticizer was additionally considered. A characterization process was carried out by the measurement of mechanical properties, thermal properties, surface morphology, and water absorption ability. The use of the almond residue allows obtaining composites based on PHBH with a higher environmental interest and lower cost.

Keywords: Almond shell, PHBH, composite, polymer.

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Authors: Velid Demir, Mesut Akgün

Abstract:

The lanthanum and zinc oxide were synthesized and then loaded with 6 wt% over γ-Al2O3 using the wet impregnation method. The samples were calcined at 900 °C to ensure a coherent structure with high catalytic performance. Characterization of the catalysts was verified by X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR). The effect of catalysts on biodiesel content from jatropha oil was studied under supercritical conditions. The results showed that ZnO/γ-Al2O3 was the superior catalyst for jatropha oil with 98.05% biodiesel under reaction conditions of 7 min reaction time, 1:40 oil to methanol molar ratio, 6 wt% of catalyst loading, 90 bar of reaction pressure, and 300 °C of reaction temperature, compared to 95.50% with La2O3/γ-Al2O3 at the same parameters. For this study, ZnO/γ-Al2O3 was the most suitable catalyst due to performance and cost considerations.

Keywords: Biodiesel, heterogeneous catalyst, Jatropha oil, supercritical methanol, transesterification.

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Authors: M.S. Dhanya, N. Gupta, H.C. Joshi, Lata

Abstract:

The present investigation was undertaken to explore the biogas potentiality of Jatropha (Jatropha curcas, Euphorbiaceae) Fruit Coat (JFC) alone and in combination with cattle dung (CD) in various proportions at 15 per cent total solids by batch phase anaerobic digestion for a period of ten weeks HRT (Hydraulic Retention Time) under a temperature of 35°C+1°C. The maximum biogas production was noticed in Cattle dung and Jatropha Fruit Coat in 2:1 ratio with 403.84 L/kg dry matter followed by 3:1,1:2, 1:1 and 1:3 having 329.66, 219.77, 217.79, 203.64 L /kg dm respectively as compared to 178.49 L/kg dm in CD alone. The JFC alone found to produce 91 per cent of total biogas that obtained from Cattle dung. The per cent methane content of the biogas in all the treatments was found on par with Cattle dung.

Keywords: Jatropha Fruit Coat, Cattle dung, Hydraulic Retention Time, Dry matter

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Authors: Manisha Dubey, Aalok Dubey

Abstract:

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

Keywords: Dynamic stability, Fuzzy logic power systemstabilizer, Genetic Algorithms, Genetic based power systemstabilizer

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Authors: K. Broniszewski, J. Woźniak, K. Czechowski, P. Orłowski, A. Olszyna

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Alumina matrix composites with addition of hexagonal boron nitride (hBN), acting as solid lubricant, were produced. Main purpose of solid lubricants is to dispose the necessity of using cooling lubricants in machining process. Hot pressing was used as a consolidating process for Al2O3-x%wt.hBN (x=1/ 2,5/ 5 /7,5 /10) composites. Properties of sinters such as relative density, hardness, Young-s modulus and fracture toughness were examined. Obtained samples characterize by high relative density. Hardness and fracture toughness values allow the use of alumina – hBN composites for machining steels even in hardened condition. However it was observed that high weight content of hBN can negatively influence the mechanical properties of composites.

Keywords: Alumina. Composites, Hexagonal boron nitride, Machining

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Authors: Ye. Shapovalov, V. Shapovalov, O. Stryzhak, A. Salyuk

Abstract:

Over the past decades, amount of scientific information has been growing exponentially. It became more complicated to process and systemize this amount of data. The approach to systematization of scientific information on the production of biogas based on the ontological IT platform “T.O.D.O.S.” has been developed. It has been proposed to select semantic characteristics of each work for their further introduction into the IT platform “T.O.D.O.S.”. An ontological graph with a ranking function for previous scientific research and for a system of selection of microorganisms has been worked out. These systems provide high performance of information management of scientific information.

Keywords: Ontology-based analysis, analysis of scientific data, methanogenesys, microorganism hierarchy, T.O.D.O.S.

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Authors: Gerard E. Sleefe

Abstract:

There is significant interest in achieving technology innovation through new product development activities. It is recognized, however, that traditional project management practices focused only on performance, cost, and schedule attributes, can often lead to risk mitigation strategies that limit new technology innovation. In this paper, a new approach is proposed for formally managing and quantifying technology innovation. This approach uses a risk-based framework that simultaneously optimizes innovation attributes along with traditional project management and system engineering attributes. To demonstrate the efficacy of the new riskbased approach, a comprehensive product development experiment was conducted. This experiment simultaneously managed the innovation risks and the product delivery risks through the proposed risk-based framework. Quantitative metrics for technology innovation were tracked and the experimental results indicate that the risk-based approach can simultaneously achieve both project deliverable and innovation objectives.

Keywords: innovation, risk assessment, product development, technology management.

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Authors: R. N. Begum, Ambalika Sharma, G. K. Singh

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Identity theft has serious ramifications beyond data and personal information loss. This necessitates the implementation of robust and efficient user identification systems. Therefore, automatic biometric recognition systems are the need of the hour, and electrocardiogram (ECG)-based systems are unquestionably the best choice due to their appealing inherent characteristics. The Convolutional Neural Networks (CNNs) are the recent state-of-the-art techniques for ECG-based user identification systems. However, the results obtained are significantly below standards, and the situation worsens as the number of users and types of heartbeats in the dataset grows. As a result, this study proposes a highly accurate and resilient ECG-based person identification system using CNN's dense learning framework. The proposed research explores explicitly the caliber of dense CNNs in the field of ECG-based human recognition. The study tests four different configurations of dense CNN which are trained on a dataset of recordings collected from eight popular ECG databases. With the highest False Acceptance Rate (FAR)  of 0.04% and the highest False Rejection Rate (FRR)  of 5%, the best performing network achieved an identification accuracy of 99.94%. The best network is also tested with various train/test split ratios. The findings show that DenseNets are not only extremely reliable, but also highly efficient. Thus, they might also be implemented in real-time ECG-based human recognition systems.

Keywords: Biometrics, dense networks, identification rate, train/test split ratio.

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Authors: A. Kowcika, E. Umamaheswari, T.V. Geetha

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In this paper we focus on event extraction from Tamil news article. This system utilizes a scoring scheme for extracting and grouping event-specific sentences. Using this scoring scheme eventspecific clustering is performed for multiple documents. Events are extracted from each document using a scoring scheme based on feature score and condition score. Similarly event specific sentences are clustered from multiple documents using this scoring scheme. The proposed system builds the Event Template based on user specified query. The templates are filled with event specific details like person, location and timeline extracted from the formed clusters. The proposed system applies these methodologies for Tamil news articles that have been enconverted into UNL graphs using a Tamil to UNL-enconverter. The main intention of this work is to generate an event based template.

Keywords: Event Extraction, Score based Clustering, Segmentation, Template Generation.

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Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

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We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: Daily activity recognition, healthcare, IoT sensors, transfer learning.

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Authors: Shiyang Zhu, G. Q. Lo, D. L. Kwong

Abstract:

Silicon photonics is merging as a unified platform for driving photonic based telecommunications and for local photonic based interconnect but it suffers from large footprint as compared with the nanoelectronics. Plasmonics is an attractive alternative for nanophotonics. In this work, two CMOS compatible plasmonic waveguide platforms are compared. One is the horizontal metal-insulator-Si-insulator-metal nanoplasmonic waveguide and the other is metal-insulator-Si hybrid plasmonic waveguide. Various passive and active photonic devices have been experimentally demonstrated based on these two plasmonic waveguide platforms.

Keywords: Plasmonics, on-chip integration, Silicon photonics.

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Authors: Ramin Halavati, Saeed B. Shouraki, Mahdieh Noroozian, Saman H. Zadeh

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Packing problems arise in a wide variety of application areas. The basic problem is that of determining an efficient arrangement of different objects in a region without any overlap and with minimal wasted gap between shapes. This paper presents a novel population based approach for optimizing arrangement of irregular shapes. In this approach, each shape is coded as an agent and the agents' reproductions and grouping policies results in arrangements of the objects in positions with least wasted area between them. The approach is implemented in an application for cutting sheets and test results on several problems from literature are presented.

Keywords: Optimization, Bin Packing, Agent Based Systems.

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Authors: Ebtehag Tolba

Abstract:

The study presents a proposed program for nursery school children in Egypt. The program consists of a collection of artistic activities and aims to develop the language, mathematical, and artistic skills of preschool children. Furthermore, the researcher has presented a questionnaire to experts about the link between the target group and the content. Finally, the proposed program was applied to group of 30 children. In addition, the researcher has prepared another questionnaire for measuring the effect of the program. This questionnaire was used as a pre-test and post-test, and at the end of the study, a significant difference was determined in favour of the post-test results.

Keywords: Developing, concepts, nursery, children, artistic activities.

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Authors: N. Hachemi, A. Nouani, A. Benchabane

Abstract:

The influence of cultivation factors such as content of ammonium sulfate, glucose and water in the culture medium and particle size of dry orange waste, on their bioconversion for pectinase production was studied using complete factorial design. A polygalacturonase (PG) was isolated using ion exchange chromatography under gradient elution 0-0,5 m/l NaCl (column equilibrate with acetate buffer pH 4,5), subsequently by sephadex G75 column chromatography was applied and the molecular weight was obtained about 51,28 KDa. Purified PG enzyme exhibits a pH and temperature optima of activity at 5 and 35°C respectively. Treatment of apple juice by purified enzyme extract yielded a clear juice, which was competitive with juice yielded by pure Sigma Aldrich Aspergillus niger enzyme.

Keywords: Bioconversion, orange wastes, optimization, pectinase.

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Authors: Rajkishore Prasad, Hiroshi Saruwatari, Kiyohiro Shikano

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This paper describes Independent Component Analysis (ICA) based fixed-point algorithm for the blind separation of the convolutive mixture of speech, picked-up by a linear microphone array. The proposed algorithm extracts independent sources by non- Gaussianizing the Time-Frequency Series of Speech (TFSS) in a deflationary way. The degree of non-Gaussianization is measured by negentropy. The relative performances of algorithm under random initialization and Null beamformer (NBF) based initialization are studied. It has been found that an NBF based initial value gives speedy convergence as well as better separation performance

Keywords: Blind signal separation, independent component analysis, negentropy, convolutive mixture.

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

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Neural networks offer an alternative approach both for identification and control of nonlinear processes in process engineering. The lack of software tools for the design of controllers based on neural network models is particularly pronounced in this field. SIMULINK is properly a widely used graphical code development environment which allows system-level developers to perform rapid prototyping and testing. Such graphical based programming environment involves block-based code development and offers a more intuitive approach to modeling and control task in a great variety of engineering disciplines. In this paper a SIMULINK based Neural Tool has been developed for analysis and design of multivariable neural based control systems. This tool has been applied to the control of a high purity distillation column including non linear hydrodynamic effects. The proposed control scheme offers an optimal response for both theoretical and practical challenges posed in process control task, in particular when both, the quality improvement of distillation products and the operation efficiency in economical terms are considered.

Keywords: Distillation, neural networks, software tools, identification, control.

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