Search results for: content independent features

Authors: I. Bagheri, M.B. Dehpour

Abstract:

The effect of moisture content and loading rate on mechanical strength of 12 brown rice grain varieties was determined. The results showed that the rupture force of brown rice grain decreased by increasing the moisture content and loading rate. The highest rupture force values was obtained at the moisture content of 8% (w.b.) and loading rate of 10 mm/min; while the lowest rupture force corresponded to the moisture content of 14% (w.b.) and loading rate of 15 mm/min. The 12 varieties were divided into three groups, namely local short grain varieties, local long grain varieties and improved long grain varieties. It was observed that the rupture strength of the three groups were statistically different from each other (P<0.01). It was revealed that the brown rice rupture at lower levels of moisture content was in the form of sudden failure with less deformation; while at higher levels of moisture content the grain rupture was in the form of gradually crushing with more deformation.

Keywords: Brown rice, loading rate, moisture content, ruptureforce

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Authors: Awais Ahmad Khan, Emad Abouel Nasr, H. M. A. Hussein, Abdulrahman Al-Ahmari

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Sheet-metal parts have been widely applied in electronics, communication and mechanical industries in recent decades; but the advancement in sheet-metal part design and manufacturing is still behind in comparison with the increasing importance of sheet-metal parts in modern industry. This paper presents a methodology for automatic extraction of some common 2D internal sheet metal features. The features used in this study are taken from Unipunch ™ catalogue. The extraction process starts with the data extraction from STEP file using an object oriented approach and with the application of suitable algorithms and rules, all features contained in the catalogue are automatically extracted. Since the extracted features include geometry and engineering information, they will be effective for downstream application such as feature rebuilding and process planning.

Keywords: Feature Extraction, Internal Features, Punch Shapes, Sheet metal, STEP.

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Authors: M. Analoui, M. Fadavi Amiri

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The design of a pattern classifier includes an attempt to select, among a set of possible features, a minimum subset of weakly correlated features that better discriminate the pattern classes. This is usually a difficult task in practice, normally requiring the application of heuristic knowledge about the specific problem domain. The selection and quality of the features representing each pattern have a considerable bearing on the success of subsequent pattern classification. Feature extraction is the process of deriving new features from the original features in order to reduce the cost of feature measurement, increase classifier efficiency, and allow higher classification accuracy. Many current feature extraction techniques involve linear transformations of the original pattern vectors to new vectors of lower dimensionality. While this is useful for data visualization and increasing classification efficiency, it does not necessarily reduce the number of features that must be measured since each new feature may be a linear combination of all of the features in the original pattern vector. In this paper a new approach is presented to feature extraction in which feature selection, feature extraction, and classifier training are performed simultaneously using a genetic algorithm. In this approach each feature value is first normalized by a linear equation, then scaled by the associated weight prior to training, testing, and classification. A knn classifier is used to evaluate each set of feature weights. The genetic algorithm optimizes a vector of feature weights, which are used to scale the individual features in the original pattern vectors in either a linear or a nonlinear fashion. By this approach, the number of features used in classifying can be finely reduced.

Keywords: Feature reduction, genetic algorithm, pattern classification, nearest neighbor rule classifiers (k-NNR).

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Authors: C. S. Sastry, Saurabh Jain, Ashish Mishra

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Image retrieval is a topic where scientific interest is currently high. The important steps associated with image retrieval system are the extraction of discriminative features and a feasible similarity metric for retrieving the database images that are similar in content with the search image. Gabor filtering is a widely adopted technique for feature extraction from the texture images. The recently proposed sparsity promoting l1-norm minimization technique finds the sparsest solution of an under-determined system of linear equations. In the present paper, the l1-norm minimization technique as a similarity metric is used in image retrieval. It is demonstrated through simulation results that the l1-norm minimization technique provides a promising alternative to existing similarity metrics. In particular, the cases where the l1-norm minimization technique works better than the Euclidean distance metric are singled out.

Keywords: l1-norm minimization, content based retrieval, modified Gabor function.

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Authors: M. Heikkinen, A. Sarpola, H. Hellman, J. Rämö, Y. Hiltunen

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Independent component analysis (ICA) is a computational method for finding underlying signals or components from multivariate statistical data. The ICA method has been successfully applied in many fields, e.g. in vision research, brain imaging, geological signals and telecommunications. In this paper, we apply the ICA method to an analysis of mass spectra of oligomeric species emerged from aluminium sulphate. Mass spectra are typically complex, because they are linear combinations of spectra from different types of oligomeric species. The results show that ICA can decomposite the spectral components for useful information. This information is essential in developing coagulation phases of water treatment processes.

Keywords: Independent component analysis, massspectroscopy, water treatment, aluminium sulphate.

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Authors: M. R. Jokanović, V. M. Tomović, M. T. Jović, S. B. Škaljac, B. V. Šojić, P. M. Ikonić, T. A. Tasić

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Proximate (moisture, protein, total fat, total ash) and mineral (K, P, Na, Mg, Ca, Zn, Fe, Cu and Mn) composition of chicken giblets (heart, liver and gizzard) were investigated. Phosphorous content, as well as proximate composition, were determined according to recommended ISO methods. The content of all elements, except phosphorus, of the giblets tissues were determined using inductively coupled plasma-optical emission spectrometry (ICP-OES), after dry ashing mineralization. Regarding proximate composition heart was the highest in total fat content, and the lowest in protein content. Liver was the highest in protein and total ash content, while gizzard was the highest in moisture and the lowest in total fat content. Regarding mineral composition liver was the highest for K, P, Ca, Mg, Fe, Zn, Cu, and Mn, while heart was the highest for Na content. The contents of almost all investigated minerals in analysed giblets tissues of chickens from Vojvodina were similar to values reported in the literature, i.e. in national food composition databases of other countries.

Keywords: Chicken giblets, proximate composition, mineral composition.

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Authors: Vahid Khorramshahi, Alireza Behrad, Neeraj K. Kanhere

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In this paper we present a new method for over-height vehicle detection in low headroom streets and highways using digital video possessing. The accuracy and the lower price comparing to present detectors like laser radars and the capability of providing extra information like speed and height measurement make this method more reliable and efficient. In this algorithm the features are selected and tracked using KLT algorithm. A blob extraction algorithm is also applied using background estimation and subtraction. Then the world coordinates of features that are inside the blobs are estimated using a noble calibration method. As, the heights of the features are calculated, we apply a threshold to select overheight features and eliminate others. The over-height features are segmented using some association criteria and grouped using an undirected graph. Then they are tracked through sequential frames. The obtained groups refer to over-height vehicles in a scene.

Keywords: Feature extraction, over-height vehicle detection, traffic monitoring, vehicle tracking.

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Authors: Ernst D. Schmitter

Abstract:

Monitoring lightning electromagnetic pulses (sferics) and other terrestrial as well as extraterrestrial transient radiation signals is of considerable interest for practical and theoretical purposes in astro- and geophysics as well as meteorology. Managing a continuous flow of data, automation of the analysis and classification process is important. Features based on a combination of wavelet and statistical methods proved efficient for this task and serve as input into a radial basis function network that is trained to discriminate transient shapes from pulse like to wave like. We concentrate on signals in the Very Low Frequency (VLF, 3 -30 kHz) range in this paper, but the developed methods are independent of this specific choice.

Keywords: Transient signals, statistics, wavelets, neural networks

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Authors: Surat Srinoy, Werasak Kurutach, Witcha Chimphlee, Siriporn Chimphlee

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One main drawback of intrusion detection system is the inability of detecting new attacks which do not have known signatures. In this paper we discuss an intrusion detection method that proposes independent component analysis (ICA) based feature selection heuristics and using rough fuzzy for clustering data. ICA is to separate these independent components (ICs) from the monitored variables. Rough set has to decrease the amount of data and get rid of redundancy and Fuzzy methods allow objects to belong to several clusters simultaneously, with different degrees of membership. Our approach allows us to recognize not only known attacks but also to detect activity that may be the result of a new, unknown attack. The experimental results on Knowledge Discovery and Data Mining- (KDDCup 1999) dataset.

Keywords: Network security, intrusion detection, rough set, ICA, anomaly detection, independent component analysis, rough fuzzy .

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Authors: Nneka N. Uchegbu, Ndidi F. Amulu

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The work studied the effect of germination on proximate, phenol and flavonoid content and antioxidant activities (AOA) of African Yam been (AYB). Germination was done in controlled dark chamber (100% RH, 28oC). The proximate, phenol and flavonoid content and antioxidant activities before and after germination were investigated. The crude protein, moisture, and crude fiber content of germinated AYB were significantly higher (P<0.05) than that of ungermianated seed, while the fat, Ash and carbohydrate content of ungerminated were higher than the germinated seed. Germination increased the phenol and flavoniod content by 19.14% and 14.53% respectively. The results of AOA assay showed that the DPPH, reducing power and FRAP of germinated AYB seed gave high values: 48.92 ±1.22 μg/ml, 0.75± 0.15μg/ml and 98.60±0.04 μmol/g while that of ungerminated seed were: 31.33μ/ml, 0.56±1.52μg/ml and 96.11±1.13μmol/g respectively. Germinated AYB has phytochemicals with potential AOA for disease prevention.

Keywords: Antioxidant, flovonoid, germination, phenol.

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Authors: Jun Wan, Zehua Chen, Yingwu Chen, Zhidong Bai

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Classification is an interesting problem in functional data analysis (FDA), because many science and application problems end up with classification problems, such as recognition, prediction, control, decision making, management, etc. As the high dimension and high correlation in functional data (FD), it is a key problem to extract features from FD whereas keeping its global characters, which relates to the classification efficiency and precision to heavens. In this paper, a novel automatic method which combined Genetic Algorithm (GA) and classification algorithm to extract classification features is proposed. In this method, the optimal features and classification model are approached via evolutional study step by step. It is proved by theory analysis and experiment test that this method has advantages in improving classification efficiency, precision and robustness whereas using less features and the dimension of extracted classification features can be controlled.

Keywords: Classification, functional data, feature extraction, genetic algorithm, wavelet.

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Authors: Aleksandrs Kovalcuks

Abstract:

Egg yolk oil is a natural source of bioactive compounds such as unsaturated fatty acids, oil soluble vitamins, pigments and others. Bioactive compound content in egg yolk oil depends from its content in eggs, from which oil was extracted. Many studies show that bioactive compound content in egg is correlated to the content of these compounds in hen feed, but there is also an opinion that hen housing systems also have influence on egg chemical content. The aim of this study was to determine which factor, laying hen housing system or hen diet, has a primary influence on bioactive compound content in egg yolk oil. The egg yolk oil was extracted from eggs obtained from 4 different hen housing systems: cage, barn and two groups of free range. All hens were fed with commercially produced compound feed except one group of free range hens which get free diet – pastured hens. Extracted egg yolk oils were analyzed for fatty acids, oil soluble vitamins and β-carotene content. α-tocopherol, ergocalcipherol and polyunsaturated fatty acid content in egg yolk oil was higher from eggs obtained from all housing systems where hens were fed with commercial compound feed. β-carotene and retinol content in egg yolk oils from free range free diet eggs was significantly (p>0.05) higher that from other eggs because hens have access to green forage. Hen physical activity in free range housing systems decreases content of some bioactive compound in egg yolk oil.

Keywords: Egg yolk oil, vitamins, caged eggs, free range.

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Authors: Yong-Gyu Lee, Gilwon Yoon

Abstract:

Automatic detection of bleeding is of practical importance since capsule endoscopy produces an extremely large number of images. Algorithm development of bleeding detection in the digestive tract is difficult due to different contrasts among the images, food dregs, secretion and others. In this study, were assigned weighting factors derived from the independent features of the contrast and brightness between bleeding and normality. Spectral analysis based on weighting factors was fast and accurate. Results were a sensitivity of 87% and a specificity of 90% when the accuracy was determined for each pixel out of 42 endoscope images.

Keywords: bleeding, capsule endoscopy, image analysis, weighted spectrum

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Authors: Oksana Razina, Shakeel Ahmad, Jessie Qun Ren, Olufemi Isiaq

Abstract:

The modern life of businesses is categorically reliant on their established position online, where digital (and particularly website) content plays a significant role as the first point of information. Digital content, therefore, becomes essential – from making the first impression through to the building and development of client relationships. Despite a number of valuable papers suggesting a strategic approach when dealing with digital data, other sources often do not view or accept the approach to digital content as a holistic or continuous process. Associations are frequently made with merely a one-off marketing campaign or similar. The challenge is in establishing an agreed definition for the notion of Digital Content Strategy (DCS), which currently does not exist, as it is viewed from an excessive number of angles. A strategic approach to content, nonetheless, is required, both practically and contextually. We, therefore, aimed at attempting to identify the key content components, comprising a DCS, to ensure all the aspects were covered and strategically applied – from the company’s understanding of the content value to the ability to display flexibility of content and advances in technology. This conceptual project evaluated existing literature on the topic of DCS and related aspects, using PRISMA Systematic Review Method, Document Analysis, Inclusion and Exclusion Criteria, Scoping Review, Snow-Balling Technique and Thematic Analysis. The data were collected from academic and statistical sources, government and relevant trade publications. Based on the suggestions from academics and trading sources, related to the issues discussed, we revealed the key actions for content creation and attempted to define the notion of DCS. The major finding of the study presented Key Content Components of DCS and can be considered for implementation in a business retail setting.

Keywords: Digital content strategy, digital marketing strategy, key content components, websites.

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Authors: Oksana Razina, Shakeel Ahmad, Jessie Qun Ren, Olufemi Isiaq

Abstract:

The modern life of businesses is categorically reliant on their established position online, where digital (and particularly website) content plays a significant role as the first point of information. Digital content, therefore, becomes essential – from making the first impression through to the building and development of client relationships. Despite a number of valuable papers suggesting a strategic approach when dealing with digital data, other sources often do not view or accept the approach to digital content as a holistic or continuous process. Associations are frequently made with merely a one-off marketing campaign or similar. The challenge is in establishing an agreed definition for the notion of Digital Content Strategy (DCS), which currently does not exist, as it is viewed from an excessive number of angles. A strategic approach to content, nonetheless, is required, both practically and contextually. We, therefore, aimed at attempting to identify the key content components, comprising a DCS, to ensure all the aspects were covered and strategically applied – from the company’s understanding of the content value to the ability to display flexibility of content and advances in technology. This conceptual project evaluated existing literature on the topic of DCS and related aspects, using PRISMA Systematic Review Method, Document Analysis, Inclusion and Exclusion Criteria, Scoping Review, Snow-Balling Technique and Thematic Analysis. The data were collected from academic and statistical sources, government and relevant trade publications. Based on the suggestions from academics and trading sources, related to the issues discussed, we revealed the key actions for content creation and attempted to define the notion of DCS. The major finding of the study presented Key Content Components of DCS and can be considered for implementation in a business retail setting.

Keywords: Digital content strategy, digital marketing strategy, key content components, websites.

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Authors: Liene Strauta, Sandra Muizniece-Brasava, Ina Alsina

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Phaseolus coccineus L. is the third most important cultivated Phaseolus species in the world. It is widely grown in Latvia due to its earliness, good taste and uniform and qualitative yield. Experiments were carried out in the laboratories of Department of Food Technology and Agronomical Analysis Scientific Laboratory at Latvia Universityof Agriculture. Beans (Phaseolus coccineus L.) crude protein, crude ash content as well as colour measurements were analyzed. Results show, that brown coloured beans have less crude protein content than others, and ash content have significant differences.

Keywords: Phaseoluscoccineus, protein, ash, colour.

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Authors: P. Ondee, S. Pannarunothai

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In Thailand, both the 1997 and the current 2007 Thai Constitutions have mentioned the establishment of independent organizations as a new mechanism to play a key role in proposing policy recommendations to national decision-makers in the interest of collective consumers. Over the last ten years, no independent organizations have yet been set up. Evidently, nobody could point out who should be key players in establishing provincial independent consumer bodies. The purpose of this study was to find definitive stakeholders in establishing and developing independent consumer bodies in a Thai context. This was a cross-sectional study between August and September 2007, using a postal questionnaire with telephone follow-up. The questionnaire was designed and used to obtain multiple stakeholder assessment of three key attributes (power, interest and influence). Study population was 153 stakeholders associated with policy decision-making, formulation and implementation processes of civil-based consumer protection in pilot provinces. The population covered key representatives from five sectors (academics, government officers, business traders, mass media and consumer networks) who participated in the deliberative forums at 10 provinces. A 49.7% response rate was achieved. Data were analyzed, comparing means of three stakeholder attributes and classification of stakeholder typology. The results showed that the provincial health officers were the definitive stakeholders as they had legal power, influence and interest in establishing and sustaining the independent consumer bodies. However, only a few key representatives of the provincial health officers expressed their own paradigm on the civil-based consumer protection. Most provincial health officers put their own standpoint of building civic participation at only a plan-implementation level. For effective policy implementation by the independent consumer bodies, the Thai government should provide budgetary support for the operation of the provincial health officers with their paradigm shift as well as their own clarified standpoint on corporate governance.

Keywords: Civic participation, civil society, consumerprotection, independent organization, policy decision-making, stakeholder analysis.

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Authors: Sara Sharifi Rad, Hassan Haghighi

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Due to important issues, such as deadlock, starvation, communication, non-deterministic behavior and synchronization, concurrent systems are very complex, sensitive, and error-prone. Thus ensuring reliability and accuracy of these systems is very essential. Therefore, there has been a big interest in the formal specification of concurrent programs in recent years. Nevertheless, some features of concurrent systems, such as dynamic process creation, scheduling and starvation have not been specified formally yet. Also, some other features have been specified partially and/or have been described using a combination of several different formalisms and methods whose integration needs too much effort. In other words, a comprehensive and integrated specification that could cover all aspects of concurrent systems has not been provided yet. Thus, this paper makes two major contributions: firstly, it provides a comprehensive formal framework to specify all well-known features of concurrent systems. Secondly, it provides an integrated specification of these features by using just a single formal notation, i.e., the Z language.

Keywords: Concurrent systems, Formal methods, Formal specification, Z language

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Authors: Heeseung Choi, Raechoong Kang, Kyungtaek Choi, Jaihie Kim

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Fake finger submission attack is a major problem in fingerprint recognition systems. In this paper, we introduce an aliveness detection method based on multiple static features, which derived from a single fingerprint image. The static features are comprised of individual pore spacing, residual noise and several first order statistics. Specifically, correlation filter is adopted to address individual pore spacing. The multiple static features are useful to reflect the physiological and statistical characteristics of live and fake fingerprint. The classification can be made by calculating the liveness scores from each feature and fusing the scores through a classifier. In our dataset, we compare nine classifiers and the best classification rate at 85% is attained by using a Reduced Multivariate Polynomial classifier. Our approach is faster and more convenient for aliveness check for field applications.

Keywords: Aliveness detection, Fingerprint recognition, individual pore spacing, multiple static features, residual noise.

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Authors: Takaaki Ishibashi

Abstract:

Independent component analysis can estimate unknown source signals from their mixtures under the assumption that the source signals are statistically independent. However, in a real environment, the separation performance is often deteriorated because the number of the source signals is different from that of the sensors. In this paper, we propose an estimation method for the number of the sources based on the joint distribution of the observed signals under two-sensor configuration. From several simulation results, it is found that the number of the sources is coincident to that of peaks in the histogram of the distribution. The proposed method can estimate the number of the sources even if it is larger than that of the observed signals. The proposed methods have been verified by several experiments.

Keywords: blind source separation, independent component analysys, estimation for the number of the blind sources, voice activity detection, target extraction.

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Authors: D. Khodadadi Dehkordi

Abstract:

This research was planned in order to study the effect of drought stress and different levels of Superabsorbent and their effect on grain yield, biologic yield and harvest index. In this study, 3 different depths of irrigation were considered as the main treatment I1, I2, I3 as 100, 75 and 50 percent of water requirement of plants respectively and different levels of Superabsorbent were used as secondary treatment (S0, S1, S2 and S3, equal to 0 (control), 15, 30 and 45 gr/m2 respectively). According to the results, independent effects of irrigation and Superabsorbent treatments at 1% level on biologic and grain yield of corn were significant. In addition, independent effect of irrigation treatments at 5% level on harvest index was significant. But independent effect of Superabsorbent treatments on harvest index was not significant.

Keywords: Corn, Deficit irrigation, Superabsorbent, Yield.

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Authors: Antonino Greco, Nadia Mammone, Francesco Carlo Morabito, Mario Versaci

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Artifact rejection plays a key role in many signal processing applications. The artifacts are disturbance that can occur during the signal acquisition and that can alter the analysis of the signals themselves. Our aim is to automatically remove the artifacts, in particular from the Electroencephalographic (EEG) recordings. A technique for the automatic artifact rejection, based on the Independent Component Analysis (ICA) for the artifact extraction and on some high order statistics such as kurtosis and Shannon-s entropy, was proposed some years ago in literature. In this paper we try to enhance this technique proposing a new method based on the Renyi-s entropy. The performance of our method was tested and compared to the performance of the method in literature and the former proved to outperform the latter.

Keywords: Artifact, EEG, Renyi's entropy, kurtosis, independent component analysis.

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Authors: N.Ibrahim, Peter A. Jensen, K. Dam-Johansen, Roshafima.R. Ali, Rafiziana.M. Kasmani

Abstract:

The aim of this study was to investigate the influence of reaction temperature and wheat straw moisture content on the pyrolysis product yields, in the temperature range of 475-575 °C. Samples of straw with moisture contents from 1.5 wt % to 15.0 wt % were fed to a bench scale Pyrolysis Centrifuge Reactor (PCR). The experimental results show that the changes in straw moisture content have no significant effect on the distribution of pyrolysis product yields. The maximum bio-oil yields approximately 60 (wt %, on dry ash free feedstock basis) was observed around 525 °C - 550 °C for all straw moisture levels. The water content in the wet straw bio-oil was the highest. The heating value of bio-oil and solid char were measured and the percentages of its energy distribution were calculated. The energy distributions of bio-oil, char and gas were 56- 69 % 24-33 %, and 2-19 %, respectively.

Keywords: Flash pyrolysis, moisture content, wheat straw, biooil.

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Authors: Somkait Udomhunsakul

Abstract:

In this paper, a novel road extraction method using Stationary Wavelet Transform is proposed. To detect road features from color aerial satellite imagery, Mexican hat Wavelet filters are used by applying the Stationary Wavelet Transform in a multiresolution, multi-scale, sense and forming the products of Wavelet coefficients at a different scales to locate and identify road features at a few scales. In addition, the shifting of road features locations is considered through multiple scales for robust road extraction in the asymmetry road feature profiles. From the experimental results, the proposed method leads to a useful technique to form the basis of road feature extraction. Also, the method is general and can be applied to other features in imagery.

Keywords: Road extraction, Multiresolution, Stationary Wavelet Transform, Multi-scale analysis

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Authors: N. W. U. D. Chathurani, Shlomo Geva, Vinod Chandran, Proboda Rajapaksha

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Selecting an appropriate image representation is the most important factor in implementing an effective Content-Based Image Retrieval (CBIR) system. This paper presents a multi-feature fusion approach for efficient CBIR, based on the distance distribution of features and relative feature weights at the time of query processing. It is a simple yet effective approach, which is free from the effect of features' dimensions, ranges, internal feature normalization and the distance measure. This approach can easily be adopted in any feature combination to improve retrieval quality. The proposed approach is empirically evaluated using two benchmark datasets for image classification (a subset of the Corel dataset and Oliva and Torralba) and compared with existing approaches. The performance of the proposed approach is confirmed with the significantly improved performance in comparison with the independently evaluated baseline of the previously proposed feature fusion approaches.

Keywords: Feature fusion, image retrieval, membership function, normalization.

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Authors: E. Khaleghi, K. Arzani, N. Moallemi, M. Barzegar

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This study was conducted to determine effect of water stress on chlorophyll content and chlorophyll fluorescence parameter in young `Dezful- olive trees. Three irrigation regimes (40% ETcrop, 65% ETcrop and 100% ETcrop) were used. After irrigation treatments were applied, some of biochemical parameters including chlorophyll a, b, total chlorophyll, chlorophyll fluorescence and also chlorophyll content index (C.C.I) were measured. Results of Analysis of variance showed that irrigation treatments had significant effect on chlorophylla, total chlorophyll (chl a+b), C.C.I and Fv/Fm ratio. The amount of decreased chlorophyll a and total chlorophyll in plants were received 40% ETcrop were 51.55% and 46.86%, respectively, compared with 100% ETcrop.

Keywords: Evatarnspiration (ETcrop), Chlorophyll Content, Chlorophyll Fluorescence, Water stress, Olive

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Authors: SuGil Choi, SeungWan Han, Chi-Yoon Jeong, TaekYong Nam

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This paper proposes a specialized Web robot to automatically collect objectionable Web contents for use in an objectionable Web content classification system, which creates the URL database of objectionable Web contents. It aims at shortening the update period of the DB, increasing the number of URLs in the DB, and enhancing the accuracy of the information in the DB.

Keywords: Web robot, objectionable Web content classification, URL database, URL rating

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Authors: Somnath Dey, Debasis Samanta

Abstract:

Iris-based biometric authentication is gaining importance in recent times. Iris biometric processing however, is a complex process and computationally very expensive. In the overall processing of iris biometric in an iris-based biometric authentication system, feature processing is an important task. In feature processing, we extract iris features, which are ultimately used in matching. Since there is a large number of iris features and computational time increases as the number of features increases, it is therefore a challenge to develop an iris processing system with as few as possible number of features and at the same time without compromising the correctness. In this paper, we address this issue and present an approach to feature extraction and feature matching process. We apply Daubechies D4 wavelet with 4 levels to extract features from iris images. These features are encoded with 2 bits by quantizing into 4 quantization levels. With our proposed approach it is possible to represent an iris template with only 304 bits, whereas existing approaches require as many as 1024 bits. In addition, we assign different weights to different iris region to compare two iris templates which significantly increases the accuracy. Further, we match the iris template based on a weighted similarity measure. Experimental results on several iris databases substantiate the efficacy of our approach.

Keywords: Iris recognition, biometric, feature processing, patternrecognition, pattern matching.

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Authors: Zhaoan Wang

Abstract:

Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: Automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation.

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Authors: Adel Sabry Eesa, Adnan Mohsin Abdulazeez Brifcani, Zeynep Orman

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Feature selection has been used in many fields such as classification, data mining and object recognition and proven to be effective for removing irrelevant and redundant features from the original dataset. In this paper, a new design of distributed intrusion detection system using a combination feature selection model based on bees and decision tree. Bees algorithm is used as the search strategy to find the optimal subset of features, whereas decision tree is used as a judgment for the selected features. Both the produced features and the generated rules are used by Decision Making Mobile Agent to decide whether there is an attack or not in the networks. Decision Making Mobile Agent will migrate through the networks, moving from node to another, if it found that there is an attack on one of the nodes, it then alerts the user through User Interface Agent or takes some action through Action Mobile Agent. The KDD Cup 99 dataset is used to test the effectiveness of the proposed system. The results show that even if only four features are used, the proposed system gives a better performance when it is compared with the obtained results using all 41 features.

Keywords: Distributed intrusion detection system, mobile agent, feature selection, Bees Algorithm, decision tree.

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