Search results for: optimum data transfer
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9090

Search results for: optimum data transfer

7350 A Cuckoo Search with Differential Evolution for Clustering Microarray Gene Expression Data

Authors: M. Pandi, K. Premalatha

Abstract:

A DNA microarray technology is a collection of microscopic DNA spots attached to a solid surface. Scientists use DNA microarrays to measure the expression levels of large numbers of genes simultaneously or to genotype multiple regions of a genome. Elucidating the patterns hidden in gene expression data offers a tremendous opportunity for an enhanced understanding of functional genomics. However, the large number of genes and the complexity of biological networks greatly increase the challenges of comprehending and interpreting the resulting mass of data, which often consists of millions of measurements. It is handled by clustering which reveals the natural structures and identifying the interesting patterns in the underlying data. In this paper, gene based clustering in gene expression data is proposed using Cuckoo Search with Differential Evolution (CS-DE). The experiment results are analyzed with gene expression benchmark datasets. The results show that CS-DE outperforms CS in benchmark datasets. To find the validation of the clustering results, this work is tested with one internal and one external cluster validation indexes.

Keywords: DNA, Microarray, genomics, Cuckoo Search, Differential Evolution, Gene expression data, Clustering.

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7349 Design of Variable Fractional-Delay FIR Differentiators

Authors: Jong-Jy Shyu, Soo-Chang Pei, Min-Han Chang

Abstract:

In this paper, the least-squares design of variable fractional-delay (VFD) finite impulse response (FIR) digital differentiators is proposed. The used transfer function is formulated so that Farrow structure can be applied to realize the designed system. Also, the symmetric characteristics of filter coefficients are derived, which leads to the complexity reduction by saving almost a half of the number of coefficients. Moreover, all the elements of related vectors or matrices for the optimal process can be represented in closed forms, which make the design easier. Design example is also presented to illustrate the effectiveness of the proposed method.

Keywords: Differentiator, variable fractional-delay filter, FIR filter, least-squares method, Farrow structure.

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7348 Physiological Action of Anthraquinone-Containing Preparations

Authors: Dmitry Yu. Korulkin, Raissa A. Muzychkina, Evgenii N. Kojaev

Abstract:

In review the generalized data about biological activity of anthraquinone-containing plants and specimens on their basis is presented. Data of traditional medicine, results of bioscreening and clinical researches of specimens are analyzed.

Keywords: Anthraquinones, physiologically active substances, phytopreparation, Ramon.

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7347 Dynamical Analysis of Circadian Gene Expression

Authors: Carla Layana Luis Diambra

Abstract:

Microarrays technique allows the simultaneous measurements of the expression levels of thousands of mRNAs. By mining this data one can identify the dynamics of the gene expression time series. By recourse of principal component analysis, we uncover the circadian rhythmic patterns underlying the gene expression profiles from Cyanobacterium Synechocystis. We applied PCA to reduce the dimensionality of the data set. Examination of the components also provides insight into the underlying factors measured in the experiments. Our results suggest that all rhythmic content of data can be reduced to three main components.

Keywords: circadian rhythms, clustering, gene expression, PCA.

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7346 Modified Data Mining Approach for Defective Diagnosis in Hard Disk Drive Industry

Authors: S. Soommat, S. Patamatamkul, T. Prempridi, M. Sritulyachot, P. Ineure, S. Yimman

Abstract:

Currently, slider process of Hard Disk Drive Industry become more complex, defective diagnosis for yield improvement becomes more complicated and time-consumed. Manufacturing data analysis with data mining approach is widely used for solving that problem. The existing mining approach from combining of the KMean clustering, the machine oriented Kruskal-Wallis test and the multivariate chart were applied for defective diagnosis but it is still be a semiautomatic diagnosis system. This article aims to modify an algorithm to support an automatic decision for the existing approach. Based on the research framework, the new approach can do an automatic diagnosis and help engineer to find out the defective factors faster than the existing approach about 50%.

Keywords: Slider process, Defective diagnosis and Data mining.

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7345 Authentication and Data Hiding Using a Reversible ROI-based Watermarking Scheme for DICOM Images

Authors: Osamah M. Al-Qershi, Khoo Bee Ee

Abstract:

In recent years image watermarking has become an important research area in data security, confidentiality and image integrity. Many watermarking techniques were proposed for medical images. However, medical images, unlike most of images, require extreme care when embedding additional data within them because the additional information must not affect the image quality and readability. Also the medical records, electronic or not, are linked to the medical secrecy, for that reason, the records must be confidential. To fulfill those requirements, this paper presents a lossless watermarking scheme for DICOM images. The proposed a fragile scheme combines two reversible techniques based on difference expansion for patient's data hiding and protecting the region of interest (ROI) with tamper detection and recovery capability. Patient's data are embedded into ROI, while recovery data are embedded into region of non-interest (RONI). The experimental results show that the original image can be exactly extracted from the watermarked one in case of no tampering. In case of tampered ROI, tampered area can be localized and recovered with a high quality version of the original area.

Keywords: DICOM, reversible, ROI-based, watermarking.

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7344 Study of Photonic Crystal Band Gap and Hexagonal Microcavity Based on Elliptical Shaped Holes

Authors: A. Benmerkhi, A. Bounouioua, M. Bouchemat, T. Bouchemat

Abstract:

In this paper, we present a numerical optical properties of a triangular periodic lattice of elliptical air holes. We report the influence of the ratio (semi-major axis length of elliptical hole to the filling ratio) on the photonic band gap. Then by using the finite difference time domain (FDTD) algorithm, the resonant wavelength of the point defect microcavities in a two-dimensional photonic crystal (PC) shifts towards the low wavelengths with significantly increased filing ratio. It can be noted that the Q factor is gradually changed to higher when the filling ratio increases. It is due to an increase in reflectivity of the PC mirror. Also we theoretically investigate the H1 cavity, where the value of semi-major axis (Rx) of the six holes surrounding the cavity are fixed at 0.5a and the Rx of the two edge air holes are fixed at the optimum value of 0.52a. The highest Q factor of 4.1359 × 106 is achieved at the resonant mode located at λ = 1.4970 µm.

Keywords: Photonic crystal, microcavity, filling ratio, elliptical holes.

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7343 Continual Learning Using Data Generation for Hyperspectral Remote Sensing Scene Classification

Authors: Samiah Alammari, Nassim Ammour

Abstract:

When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on hyperspectral image (HSI) dataset on Indian Pines. The results confirm the capability of the proposed method.

Keywords: Continual learning, data reconstruction, remote sensing, hyperspectral image segmentation.

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7342 MHD Mixed Convection in a Vertical Porous Channel

Authors: B. Fersadou, H. Kahalerras

Abstract:

This work deals with the problem of MHD mixed convection in a completely porous and differentially heated vertical channel. The model of Darcy-Brinkman-Forchheimer with the Boussinesq approximation is adopted and the governing equations are solved by the finite volume method. The effects of magnetic field and buoyancy force intensities are given by the Hartmann and Richardson numbers respectively, as well as the Joule heating represented by Eckert number on the velocity and temperature fields, are examined. The main results show an augmentation of heat transfer rate with the decrease of Darcy number and the increase of Ri and Ha when Joule heating is neglected.

Keywords: Heat sources, magnetic field, mixed convection, porous channel.

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7341 Optimization of New 25A-size Metal Gasket Design Based on Contact Width Considering Forming and Contact Stress Effect

Authors: Didik Nurhadiyanto , Moch Agus Choiron , Ken Kaminishi , Shigeyuki Haruyama

Abstract:

At the previous study of new metal gasket, contact width and contact stress were important design parameter for optimizing metal gasket performance. However, the range of contact stress had not been investigated thoroughly. In this study, we conducted a gasket design optimization based on an elastic and plastic contact stress analysis considering forming effect using FEM. The gasket model was simulated by using two simulation stages which is forming and tightening simulation. The optimum design based on an elastic and plastic contact stress was founded. Final evaluation was determined by helium leak quantity to check leakage performance of both type of gaskets. The helium leak test shows that a gasket based on the plastic contact stress design better than based on elastic stress design.

Keywords: Contact stress, metal gasket, plastic, elastic

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7340 Data Projects for “Social Good”: Challenges and Opportunities

Authors: Mikel Niño, Roberto V. Zicari, Todor Ivanov, Kim Hee, Naveed Mushtaq, Marten Rosselli, Concha Sánchez-Ocaña, Karsten Tolle, José Miguel Blanco, Arantza Illarramendi, Jörg Besier, Harry Underwood

Abstract:

One of the application fields for data analysis techniques and technologies gaining momentum is the area of social good or “common good”, covering cases related to humanitarian crises, global health care, or ecology and environmental issues, among others. The promotion of data-driven projects in this field aims at increasing the efficacy and efficiency of social initiatives, improving the way these actions help humanity in general and people in need in particular. This application field, however, poses its own barriers and challenges when developing data-driven projects, lagging behind in comparison with other scenarios. These challenges derive from aspects such as the scope and scale of the social issue to solve, cultural and political barriers, the skills of main stakeholders and the technological resources available, the motivation to be engaged in such projects, or the ethical and legal issues related to sensitive data. This paper analyzes the application of data projects in the field of social good, reviewing its current state and noteworthy initiatives, and presenting a framework covering the key aspects to analyze in such projects. The goal is to provide guidelines to understand the main challenges and opportunities for this type of data project, as well as identifying the main differential issues compared to “classical” data projects in general. A case study is presented on the initial steps and stakeholder analysis of a data project for the inclusion of refugees in the city of Frankfurt, Germany, in order to empirically confront the framework with a real example.

Keywords: Data-Driven projects, humanitarian operations, personal and sensitive data, social good, stakeholders analysis.

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7339 Separation of Hazardous Brominated Plastics from Waste Plastics by Froth Flotation after Surface Modification with Mild Heat-Treatment

Authors: Nguyen Thi Thanh Truc, Chi-Hyeon Lee, Byeong-Kyu Lee, Srinivasa Reddy Mallampati

Abstract:

This study evaluated to facilitate separation of ABS plastics from other waste plastics by froth flotation after surface hydrophilization of ABS with heat treatment. The mild heat treatment at 100oC for 60s could selectively increase the hydrophilicity of the ABS plastics surface (i.e., ABS contact angle decreased from 79o to 65.8o) among other plastics mixture. The SEM and XPS results of plastic samples sufficiently supported the increase in hydrophilic functional groups and decrease contact angle on ABS surface, after heat treatment. As a result of the froth flotation (at mixing speed 150 rpm and airflow rate 0.3 L/min) after heat treatment, about 85% of ABS was selectively separated from other heavy plastics with 100% of purity. The effect of optimum treatment condition and detailed mechanism onto separation efficiency in the froth floatation was also investigated. This research is successful in giving a simple, effective, and inexpensive method for ABS separation from waste plastics.

Keywords: ABS, hydrophilic, heat treatment, froth flotation, contact angle.

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7338 A Comparison of Dilute Sulfuric and Phosphoric Acid Pretreatments in Biofuel Production from Corncobs

Authors: Jirakarn Nantapipat, Apanee Luengnaruemitchai, Sujitra Wongkasemjit

Abstract:

Biofuels, like biobutanol, have been recognized for being renewable and sustainable fuels which can be produced from lignocellulosic biomass. To convert lignocellulosic biomass to biofuel, pretreatment process is an important step to remove hemicelluloses and lignin to improve enzymatic hydrolysis. Dilute acid pretreatment has been successful developed for pretreatment of corncobs and the optimum conditions of dilute sulfuric and phosphoric acid pretreatment were obtained at 120 °C for 5 min with 15:1 liquid to solid ratio and 140 °C for 10 min with 10:1 liquid to solid ratio, respectively. The result shows that both of acid pretreatments gave the content of total sugar approximately 34–35 g/l. In case of inhibitor content (furfural), phosphoric acid pretreatment gives higher than sulfuric acid pretreatment. Characterizations of corncobs after pretreatment indicate that both of acid pretreatments can improve enzymatic accessibility and the better results present in corncobs pretreated with sulfuric acid in term of surface area, crystallinity, and composition analysis.

Keywords: Corncobs, Pretreatment, Sulfuric acid, Phosphoric acid.

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7337 A Multi-Feature Deep Learning Algorithm for Urban Traffic Classification with Limited Labeled Data

Authors: Rohan Putatunda, Aryya Gangopadhyay

Abstract:

Acoustic sensors, if embedded in smart street lights, can help in capturing the activities (car honking, sirens, events, traffic, etc.) in cities. Needless to say, the acoustic data from such scenarios are complex due to multiple audio streams originating from different events, and when decomposed to independent signals, the amount of retrieved data volume is small in quantity which is inadequate to train deep neural networks. So, in this paper, we address the two challenges: a) separating the mixed signals, and b) developing an efficient acoustic classifier under data paucity. So, to address these challenges, we propose an architecture with supervised deep learning, where the initial captured mixed acoustics data are analyzed with Fast Fourier Transformation (FFT), followed by filtering the noise from the signal, and then decomposed to independent signals by fast independent component analysis (Fast ICA). To address the challenge of data paucity, we propose a multi feature-based deep neural network with high performance that is reflected in our experiments when compared to the conventional convolutional neural network (CNN) and multi-layer perceptron (MLP).

Keywords: FFT, ICA, vehicle classification, multi-feature DNN, CNN, MLP.

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7336 An Educational Data Mining System for Advising Higher Education Students

Authors: Heba Mohammed Nagy, Walid Mohamed Aly, Osama Fathy Hegazy

Abstract:

Educational  data mining  is  a  specific  data   mining field applied to data originating from educational environments, it relies on different  approaches to discover hidden knowledge  from  the  available   data. Among these approaches are   machine   learning techniques which are used to build a system that acquires learning from previous data. Machine learning can be applied to solve different regression, classification, clustering and optimization problems.

In  our  research, we propose  a “Student  Advisory  Framework” that  utilizes  classification  and  clustering  to  build  an  intelligent system. This system can be used to provide pieces of consultations to a first year  university  student to  pursue a  certain   education   track   where  he/she  will  likely  succeed  in, aiming  to  decrease   the  high  rate   of  academic  failure   among these  students.  A real case study  in Cairo  Higher  Institute  for Engineering, Computer  Science  and  Management  is  presented using  real  dataset   collected  from  2000−2012.The dataset has two main components: pre-higher education dataset and first year courses results dataset. Results have proved the efficiency of the suggested framework.

Keywords: Classification, Clustering, Educational Data Mining (EDM), Machine Learning.

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7335 Auto Classification for Search Intelligence

Authors: Lilac A. E. Al-Safadi

Abstract:

This paper proposes an auto-classification algorithm of Web pages using Data mining techniques. We consider the problem of discovering association rules between terms in a set of Web pages belonging to a category in a search engine database, and present an auto-classification algorithm for solving this problem that are fundamentally based on Apriori algorithm. The proposed technique has two phases. The first phase is a training phase where human experts determines the categories of different Web pages, and the supervised Data mining algorithm will combine these categories with appropriate weighted index terms according to the highest supported rules among the most frequent words. The second phase is the categorization phase where a web crawler will crawl through the World Wide Web to build a database categorized according to the result of the data mining approach. This database contains URLs and their categories.

Keywords: Information Processing on the Web, Data Mining, Document Classification.

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7334 Risk Allocation in Public-Private Partnership (PPP) Projects for Wastewater Treatment Plants

Authors: Samuel Capintero, Ole H. Petersen

Abstract:

This paper examines the utilization of public-private partnerships for the building and operation of wastewater treatment plants. Our research focuses on risk allocation in this kind of projects. Our analysis builds on more than hundred wastewater treatment plants built and operated through PPP projects in Aragon (Spain). The paper illustrates the consequences of an inadequate management of construction risk and an unsuitable transfer of demand risk in wastewater treatment plants. It also shows that the involvement of many public bodies at local, regional and national level further increases the complexity of this kind of projects and make time delays more likely.

Keywords: Wastewater, treatment plants, PPP, construction.

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7333 Performance Evaluation of Karanja Oil Based Biodiesel Engine Using Modified Genetic Algorithm

Authors: G. Bhushan, S. Dhingra, K. K. Dubey

Abstract:

This paper presents the evaluation of performance (BSFC and BTE), combustion (Pmax) and emission (CO, NOx, HC and smoke opacity) parameters of karanja biodiesel in a single cylinder, four stroke, direct injection diesel engine by considering significant engine input parameters (blending ratio, compression ratio and load torque). Multi-objective optimization of performance, combustion and emission parameters is also carried out in a karanja biodiesel engine using hybrid RSM-NSGA-II technique. The pareto optimum solutions are predicted by running the hybrid RSM-NSGA-II technique. Each pareto optimal solution is having its own importance. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results.

Keywords: Karanja biodiesel, single cylinder direct injection diesel engine, response surface methodology, central composite rotatable design, genetic algorithm.

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7332 Retrieval of Relevant Visual Data in Selected Machine Vision Tasks: Examples of Hardware-based and Software-based Solutions

Authors: Andrzej Śluzek

Abstract:

To illustrate diversity of methods used to extract relevant (where the concept of relevance can be differently defined for different applications) visual data, the paper discusses three groups of such methods. They have been selected from a range of alternatives to highlight how hardware and software tools can be complementarily used in order to achieve various functionalities in case of different specifications of “relevant data". First, principles of gated imaging are presented (where relevance is determined by the range). The second methodology is intended for intelligent intrusion detection, while the last one is used for content-based image matching and retrieval. All methods have been developed within projects supervised by the author.

Keywords: Relevant visual data, gated imaging, intrusion detection, image matching.

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7331 SOA-Based Mobile Application for Crime Control in Thailand

Authors: Jintana Khemprasit, Vatcharaporn Esichaikul

Abstract:

Crime is a major societal problem for most of the world's nations. Consequently, the police need to develop new methods to improve their efficiency in dealing with these ever increasing crime rates. Two of the common difficulties that the police face in crime control are crime investigation and the provision of crime information to the general public to help them protect themselves. Crime control in police operations involves the use of spatial data, crime data and the related crime data from different organizations (depending on the nature of the analysis to be made). These types of data are collected from several heterogeneous sources in different formats and from different platforms, resulting in a lack of standardization. Moreover, there is no standard framework for crime data collection, integration and dissemination through mobile devices. An investigation into the current situation in crime control was carried out to identify the needs to resolve these issues. This paper proposes and investigates the use of service oriented architecture (SOA) and the mobile spatial information service in crime control. SOA plays an important role in crime control as an appropriate way to support data exchange and model sharing from heterogeneous sources. Crime control also needs to facilitate mobile spatial information services in order to exchange, receive, share and release information based on location to mobile users anytime and anywhere.

Keywords: Crime Control, Geographic Information System (GIS), Mobile GIS, Service Oriented Architecture (SOA).

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7330 Effect of Oxygen on Biochar Yield and Properties

Authors: Ramlan Zailani, Halim Ghafar, Mohamad Sofian So'aib

Abstract:

Air infiltration in mass scale industrial applications of bio char production is inevitable. The presence of oxygen during the carbonization process is detrimental to the production of biochar yield and properties. The experiment was carried out on several wood species in a fixed-bed pyrolyser under various fractions of oxygen ranging from 0% to 11% by varying nitrogen and oxygen composition in the pyrolysing gas mixtures at desired compositions. The bed temperature and holding time were also varied. Process optimization was carried out by Response Surface Methodology (RSM) by employing Central Composite Design (CCD) using Design Expert 6.0 Software. The effect of oxygen ratio and holding time on biochar yield within the range studied were statistically significant. From the analysis result, optimum condition of 15.2% biochar yield of mangrove wood was predicted at pyrolysis temperature of 403 oC, oxygen percentage of 2.3% and holding time of two hours. This prediction agreed well with the experiment finding of 15.1% biochar yield.

Keywords: Mangrove wood, slow pyrolysis, oxygen infiltration.

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7329 Multidimensional and Data Mining Analysis for Property Investment Risk Analysis

Authors: Nur Atiqah Rochin Demong, Jie Lu, Farookh Khadeer Hussain

Abstract:

Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expert-s opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of experts- experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper.

Keywords: Uncertainty factors, data mining, multidimensional data model, risk analysis.

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7328 Computational Aspects of Regression Analysis of Interval Data

Authors: Michal Cerny

Abstract:

We consider linear regression models where both input data (the values of independent variables) and output data (the observations of the dependent variable) are interval-censored. We introduce a possibilistic generalization of the least squares estimator, so called OLS-set for the interval model. This set captures the impact of the loss of information on the OLS estimator caused by interval censoring and provides a tool for quantification of this effect. We study complexity-theoretic properties of the OLS-set. We also deal with restricted versions of the general interval linear regression model, in particular the crisp input – interval output model. We give an argument that natural descriptions of the OLS-set in the crisp input – interval output cannot be computed in polynomial time. Then we derive easily computable approximations for the OLS-set which can be used instead of the exact description. We illustrate the approach by an example.

Keywords: Linear regression, interval-censored data, computational complexity.

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7327 Zinc Borate Synthesis Using Hydrozincite and Boric Acid with Ultrasonic Method

Authors: D. S. Vardar, A. S. Kipcak, F. T. Senberber, E. M. Derun, N. Tugrul, S. Piskin

Abstract:

Zinc borate is an important inorganic hydrate borate material, which can be used as a flame retardant agent and corrosion resistance material. This compound can loss its structural water content at higher than 290°C. Due to thermal stability; Zinc Borate can be used as flame retardant at high temperature process of plastic and gum. In this study, the ultrasonic reaction of zinc borates were studied using hydrozincite (Zn5(CO3)2·(OH)6) and boric acid (H3BO3) raw materials. Before the synthesis raw materials were characterized by X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR). Ultrasonic method is a new application on the zinc borate synthesis. The synthesis parameters were set to 90°C reaction temperature and 55 minutes of reaction time, with 1:1, 1:2, 1:3, 1:4 and 1:5 molar ratio of starting materials (Zn5(CO3)2·(OH)6 : H3BO3). After the zinc borate synthesis, the products were analyzed by XRD and FT-IR. As a result, optimum molar ratio of 1:5 is determined for the synthesis of zinc borates with ultrasonic method.

Keywords: Borate, ultrasonic method, zinc borate, zinc borate synthesis.

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7326 Effect of Chemical Modifier on the Properties of Polypropylene (PP) / Coconut Fiber (CF) in Automotive Application

Authors: K. Shahril, A. Nizam, M. Sabri, A. Siti Rohana, H. Salmah

Abstract:

Chemical modifier (Acrylic Acid) is used as filler treatment to improve mechanical properties and swelling behavior of polypropylene/coconut fiber (PP/CF) composites by creating more adherent bonding between CF filler and PP Matrix. Treated (with chemical modifier) and untreated (without chemical modifier) composites were prepared in the formulation of 10 wt%, 20 wt%, 30 wt%, and 40 wt%. The mechanical testing indicates that composite with 10 wt% of untreated composite has the optimum value of tensile strength, and the composite with chemical modifier shows the tensile strength was increased. By increasing of filler loading, elastic modulus was increased while the elongation at brake was decreased. Meanwhile, the swelling test discerned that the increase of filler loading increased the water absorption of composites and the presence of chemical modifier reduced the equilibrium water absorption percentage.

Keywords: Coconut fiber, polypropylene, acid acrylic, ethanol, chemical modifier, composites.

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7325 Time-Derivative Estimation of Noisy Movie Data using Adaptive Control Theory

Authors: Soon-Hyun Park, Takami Matsuo

Abstract:

This paper presents an adaptive differentiator of sequential data based on the adaptive control theory. The algorithm is applied to detect moving objects by estimating a temporal gradient of sequential data at a specified pixel. We adopt two nonlinear intensity functions to reduce the influence of noises. The derivatives of the nonlinear intensity functions are estimated by an adaptive observer with σ-modification update law.

Keywords: Adaptive estimation, parameter adjustmentlaw, motion detection, temporal gradient, differential filter.

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7324 Oil Palm Shell Ash - Cement Mortar Mixture and Modification of Mechanical Properties

Authors: Abdoullah Namdar, Fadzil Mat Yahaya

Abstract:

The waste agriculture materials cause environment pollution, recycle of these materials help sustainable development. This study focused on the impact of used oil palm shell ash on the compressive and flexural strengths of cement mortar. Two different cement mortar mixes have been designed to investigate the impact of oil palm shell ash on strengths of cement mortar. Quantity of 4% oil palm shell ash has been replaced in cement mortar. The main objective of this paper is, to modify mechanical properties of cement mortar by replacement of oil palm ash in it at early age of 7 days. The results have been revealed optimum quantity of oil palm ash for replacement in cement mortar. The deflection, load to failure, time to failure of compressive strength and flexural strength of all specimens have significantly been improved. The stress-strain behavior has been indicated ability of modified cement mortar in control stress path and strain. The micro property of cement paste has not been investigated.

Keywords: Minerals, additive, flexural strength, compressive strength, modulus of elasticity.

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7323 Transformation of the Business Model in an Occupational Health Care Company Embedded in an Emerging Personal Data Ecosystem: A Case Study in Finland

Authors: Tero Huhtala, Minna Pikkarainen, Saila Saraniemi

Abstract:

Information technology has long been used as an enabler of exchange for goods and services. Services are evolving from generic to personalized, and the reverse use of customer data has been discussed in both academia and industry for the past few years. This article presents the results of an empirical case study in the area of preventive health care services. The primary data were gathered in workshops, in which future personal data-based services were conceptualized by analyzing future scenarios from a business perspective. The aim of this study is to understand business model transformation in emerging personal data ecosystems. The work was done as a case study in the context of occupational healthcare. The results have implications to theory and practice, indicating that adopting personal data management principles requires transformation of the business model, which, if successfully managed, may provide access to more resources, potential to offer better value, and additional customer channels. These advantages correlate with the broadening of the business ecosystem. Expanding the scope of this study to include more actors would improve the validity of the research. The results draw from existing literature and are based on findings from a case study and the economic properties of the healthcare industry in Finland.

Keywords: Ecosystem, business model, personal data, preventive healthcare.

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7322 Thermo-Exergy Optimization of Gas Turbine Cycle with Two Different Regenerator Designs

Authors: Saria Abed, Tahar Khir, Ammar Ben Brahim

Abstract:

A thermo-exergy optimization of a gas turbine cycle with two different regenerator designs is established. A comparison was made between the performance of the two regenerators and their roles in improving the cycle efficiencies. The effect of operational parameters (the pressure ratio of the compressor, the ambient temperature, excess of air, geometric parameters of the regenerators, etc.) on thermal efficiencies, the exergy efficiencies, and irreversibilities were studied using thermal balances and quantitative exegetic equilibrium for each component and for the whole system. The results are given graphically by using the EES software, and an appropriate discussion and conclusion was made.

Keywords: Exergy efficiency, gas turbine, heat transfer, irreversibility, optimization, regenerator, thermal efficiency.

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7321 Beam and Diffuse Solar Energy in Zarqa City

Authors: Ali M. Jawarneh

Abstract:

Beam and diffuse radiation data are extracted analytically from previous measured data on a horizontal surface in Zarqa city. Moreover, radiation data on a tilted surfaces with different slopes have been derived and analyzed. These data are consisting of of beam contribution, diffuse contribution, and ground reflected contribution radiation. Hourly radiation data for horizontal surface possess the highest radiation values on June, and then the values decay as the slope increases and the sharp decreasing happened for vertical surface. The beam radiation on a horizontal surface owns the highest values comparing to diffuse radiation for all days of June. The total daily radiation on the tilted surface decreases with slopes. The beam radiation data also decays with slopes especially for vertical surface. Diffuse radiation slightly decreases with slopes with sharp decreases for vertical surface. The groundreflected radiation grows with slopes especially for vertical surface. It-s clear that in June the highest harvesting of solar energy occurred for horizontal surface, then the harvesting decreases as the slope increases.

Keywords: Beam and Diffuse Radiation, Zarqa City

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