Search results for: functional store image

Authors: Luis Gracia, Carlos Perez-Vidal, Carlos Gracia

Abstract:

This paper presents the theoretical background and the real implementation of an automated computer system to introduce machine vision in flower, fruit and vegetable processing for recollection, cutting, packaging, classification, or fumigation tasks. The considerations and implementation issues presented in this work can be applied to a wide range of varieties of flowers, fruits and vegetables, although some of them are especially relevant due to the great amount of units that are manipulated and processed each year over the world. The computer vision algorithms developed in this work are shown in detail, and can be easily extended to other applications. A special attention is given to the electromagnetic compatibility in order to avoid noisy images. Furthermore, real experimentation has been carried out in order to validate the developed application. In particular, the tests show that the method has good robustness and high success percentage in the object characterization.

Keywords: Image processing, Vision system, Automation

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Authors: A. Nachour, L. Ouzizi, Y. Aoura

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Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: Edge detection, medical MR images, multi-agent systems, vector field convolution.

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Authors: Ferreira F. C. L., Souza D. N., Rodrigues T. M. A., Cunha C. J., Dullius M. A., Andrade J. E., Sousa A. H., Vieira J. P. C., Carvalho Júnior A. B., Santos L. P. B., Passos R. O.

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The objective this study was to characterize and develop anthropomorphic liver phantoms in tomography hepatic procedures for quality control and improvement professionals in nuclear medicine. For the conformation of the anthropomorphic phantom was used in plaster and acrylic. We constructed three phantoms representing processes with liver cirrhosis. The phantoms were filled with 99mTc diluted with water to obtain the scintigraphic images. Tomography images were analyzed anterior and posterior phantom representing a body with a greater degree cirrhotic. It was noted that the phantoms allow the acquisition of images similar to real liver with cirrhosis. Simulations of hemangiomas may contribute to continued professional education of nuclear medicine, on the question of image acquisition, allowing of the study parameters such of the matrix, energy window and count statistics.

Keywords: Nuclear medicine, liver phantom, control quality

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Authors: Mallappa A. Devani, John U. Kennedy Oubagaranadin, Basudeb Munshi

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In this preliminary work, locally available husk of Cajanus cajan (commonly known in India as Tur or Arhar), a bio-waste, has been used in its physically treated and chemically activated form for the removal of binary Cu (II) and Zn(II) ions from the real waste water obtained from an electroplating industry in Bangalore, Karnataka, India and from laboratory prepared binary solutions having almost similar composition of the metal ions, for comparison. The real wastewater after filtration and dilution for five times was used for biosorption studies at the normal pH of the solutions at room temperature. Langmuir's binary model was used to calculate the metal uptake capacities of the biosorbents. It was observed that Cu(II) is more competitive than Zn(II) in biosorption. In individual metal biosorption, Cu(II) uptake was found to be more than that of the Zn(II) and a similar trend was observed in the binary metal biosorption from real wastewater and laboratory prepared solutions. FTIR analysis was carried out to identify the functional groups in the industrial wastewater and EDAX for the elemental analysis of the biosorbents after experiments.

Keywords: Biosorption, Cajanus cajan, multi metal remediation, wastewater.

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Authors: J. L. Liu, L. Wang, B. Zhu, J. Zhou, W. D. Gao

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Fabric textures are very common in our daily life. However, the representation of fabric textures has never been explored from neuroscience view. Theoretical studies suggest that primary visual cortex (V1) uses a sparse code to efficiently represent natural images. However, how the simple cells in V1 encode the artificial textures is still a mystery. So, here we will take fabric texture as stimulus to study the response of independent component analysis that is established to model the receptive field of simple cells in V1. We choose 140 types of fabrics to get the classical fabric textures as materials. Experiment results indicate that the receptive fields of simple cells have obvious selectivity in orientation, frequency and phase when drifting gratings are used to determine their tuning properties. Additionally, the distribution of optimal orientation and frequency shows that the patch size selected from each original fabric image has a significant effect on the frequency selectivity.

Keywords: Fabric Texture, Receptive Filed, Simple Cell, Spare Coding.

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Authors: Muhammad Zeeshan UlHaque, Peng Du, Leo K. Cheng, Marc D. Jacobs

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Sensory nerves in the foot play an important part in the diagnosis of various neuropathydisorders, especially in diabetes mellitus.However, a detailed description of the anatomical distribution of the nerves is currently lacking. A computationalmodel of the afferent nerves inthe foot may bea useful tool for the study of diabetic neuropathy. In this study, we present the development of an anatomically-based model of various major sensory nerves of the sole and dorsal sidesof the foot. In addition, we presentan algorithm for generating synthetic somatosensory nerve networks in the big-toe region of a right foot model. The algorithm was based on a modified version of the Monte Carlo algorithm, with the capability of being able to vary the intra-epidermal nerve fiber density in differentregionsof the foot model. Preliminary results from the combinedmodel show the realistic anatomical structure of the major nerves as well as the smaller somatosensory nerves of the foot. The model may now be developed to investigate the functional outcomes of structural neuropathyindiabetic patients.

Keywords: Diabetic neuropathy, Finite element modeling, Monte Carlo Algorithm, Somatosensory nerve networks

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Authors: E. B. Jo, J. H. Lee, J. Y. Park, S. M. Kim

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In this study, we present an advanced detection technique for mass type breast cancer based on texture information of organs. The proposed method detects the cancer areas in three stages. In the first stage, the midpoints of mass area are determined based on AHE (Adaptive Histogram Equalization). In the second stage, we set the threshold coefficient of homogeneity by using MLE (Maximum Likelihood Estimation) to compute the uniformity of texture. Finally, mass type cancer tissues are extracted from the original image. As a result, it was observed that the proposed method shows an improved detection performance on dense breast tissues of Korean women compared with the existing methods. It is expected that the proposed method may provide additional diagnostic information for detection of mass-type breast cancer.

Keywords: Mass Type Breast Cancer, Mammography, Maximum Likelihood Estimation (MLE), Ranklets, SVM

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Authors: Diego Saqui, José H. Saito, José R. Campos, Lúcio A. de C. Jorge

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Hyperspectral images and remote sensing are important for many applications. A problem in the use of these images is the high volume of data to be processed, stored and transferred. Dimensionality reduction techniques can be used to reduce the volume of data. In this paper, an approach to band selection based on clustering algorithms is presented. This approach allows to reduce the volume of data. The proposed structure is based on Fuzzy C-Means (or K-Means) and NWHFC algorithms. New attributes in relation to other studies in the literature, such as kurtosis and low correlation, are also considered. A comparison of the results of the approach using the Fuzzy C-Means and K-Means with different attributes is performed. The use of both algorithms show similar good results but, particularly when used attributes variance and kurtosis in the clustering process, however applicable in hyperspectral images.

Keywords: Band selection, fuzzy C-means, K-means, hyperspectral image.

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Authors: Mina Alibeigi, Sattar Hashemi, Ali Hamzeh

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Since dealing with high dimensional data is computationally complex and sometimes even intractable, recently several feature reductions methods have been developed to reduce the dimensionality of the data in order to simplify the calculation analysis in various applications such as text categorization, signal processing, image retrieval, gene expressions and etc. Among feature reduction techniques, feature selection is one the most popular methods due to the preservation of the original features. In this paper, we propose a new unsupervised feature selection method which will remove redundant features from the original feature space by the use of probability density functions of various features. To show the effectiveness of the proposed method, popular feature selection methods have been implemented and compared. Experimental results on the several datasets derived from UCI repository database, illustrate the effectiveness of our proposed methods in comparison with the other compared methods in terms of both classification accuracy and the number of selected features.

Keywords: Feature, Feature Selection, Filter, Probability Density Function

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Authors: H. Mehdi, Kh. S. Karimov, A. A. Kavokin

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Methods of clustering which were developed in the data mining theory can be successfully applied to the investigation of different kinds of dependencies between the conditions of environment and human activities. It is known, that environmental parameters such as temperature, relative humidity, atmospheric pressure and illumination have significant effects on the human mental performance. To investigate these parameters effect, data mining technique of clustering using entropy and Information Gain Ratio (IGR) K(Y/X) = (H(X)–H(Y/X))/H(Y) is used, where H(Y)=-ΣPi ln(Pi). This technique allows adjusting the boundaries of clusters. It is shown that the information gain ratio (IGR) grows monotonically and simultaneously with degree of connectivity between two variables. This approach has some preferences if compared, for example, with correlation analysis due to relatively smaller sensitivity to shape of functional dependencies. Variant of an algorithm to implement the proposed method with some analysis of above problem of environmental effects is also presented. It was shown that proposed method converges with finite number of steps.

Keywords: Clustering, Correlation analysis, EnvironmentalParameters, Information Gain Ratio, Mental Performance.

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Authors: Hossein Pazhoumand-Dar, Amir Mohsen Toliyat Abolhassani, Ehsan Saeedi

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Speed estimation is one of the important and practical tasks in machine vision, Robotic and Mechatronic. the availability of high quality and inexpensive video cameras, and the increasing need for automated video analysis has generated a great deal of interest in machine vision algorithms. Numerous approaches for speed estimation have been proposed. So classification and survey of the proposed methods can be very useful. The goal of this paper is first to review and verify these methods. Then we will propose a novel algorithm to estimate the speed of moving object by using fuzzy concept. There is a direct relation between motion blur parameters and object speed. In our new approach we will use Radon transform to find direction of blurred image, and Fuzzy sets to estimate motion blur length. The most benefit of this algorithm is its robustness and precision in noisy images. Our method was tested on many images with different range of SNR and is satisfiable.

Keywords: Blur Analysis, Fuzzy sets, Speed estimation.

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Authors: Hong Yi Huang, Wei Ti Kuo, Yi You Huang

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Non-viral gene carriers composed of biodegradable polymers or lipids have been considered as a safer alternative for gene carriers over viral vectors. We have developed multi-functional nano-micelles for both drug and gene delivery application. Polyethyleneimine (PEI) was modified by grafting stearic acid (SA) and formulated to polymeric micelles (PEI-SA) with positive surface charge for gene and drug delivery. Our results showed that PEI-SA micelles provided high siRNA binding efficiency. In addition, siRNA delivered by PEI-SA carriers also demonstrated significantly high cellular uptake even in the presence of serum proteins. The post-transcriptional gene silencing efficiency was greatly improved by the polyplex formulated by 10k PEI-SA/siRNA. The amphiphilic structure of PEI-SA micelles provided advantages for multifunctional tasks; where the hydrophilic shell modified with cationic charges can electrostatically interact with DNA or siRNA, and the hydrophobic core can serve as payloads for hydrophobic drugs, making it a promising multifunctional vehicle for both genetic and chemotherapy application.

Keywords: polyethyleneimine, gene delivery, micelles, siRNA

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Authors: A. Biran, P. Sobhe Bidari, A. Almazroe V. Lakshminarayanan, K. Raahemifar

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Diabetic Retinopathy (DR) is a severe retinal disease which is caused by diabetes mellitus. It leads to blindness when it progress to proliferative level. Early indications of DR are the appearance of microaneurysms, hemorrhages and hard exudates. In this paper, an automatic algorithm for detection of DR has been proposed. The algorithm is based on combination of several image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Also, Support Vector Machine (SVM) Classifier is used to classify retinal images to normal or abnormal cases including non-proliferative or proliferative DR. The proposed method has been tested on images selected from Structured Analysis of the Retinal (STARE) database using MATLAB code. The method is perfectly able to detect DR. The sensitivity specificity and accuracy of this approach are 90%, 87.5%, and 91.4% respectively.

Keywords: Diabetic retinopathy, fundus images, STARE, Gabor filter, SVM.

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Authors: Yue Zhao, Chao Li

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Camera calibration is an important step in 3D reconstruction. Camera calibration may be classified into two major types: traditional calibration and self-calibration. However, a calibration method in using a checkerboard is intermediate between traditional calibration and self-calibration. A self is proposed based on a square in this paper. Only a square in the planar template, the camera self-calibration can be completed through the single view. The proposed algorithm is that the virtual circle and straight line are established by a square on planar template, and circular points, vanishing points in straight lines and the relation between them are be used, in order to obtain the image of the absolute conic (IAC) and establish the camera intrinsic parameters. To make the calibration template is simpler, as compared with the Zhang Zhengyou-s method. Through real experiments and experiments, the experimental results show that this algorithm is feasible and available, and has a certain precision and robustness.

Keywords: Absolute conic, camera calibration, circle point, vanishing point.

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Authors: Mounir Sayadi, Farhat Fnaiech

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In the framework of adaptive parametric modelling of images, we propose in this paper a new technique based on the Chandrasekhar fast adaptive filter for texture characterization. An Auto-Regressive (AR) linear model of texture is obtained by scanning the image row by row and modelling this data with an adaptive Chandrasekhar linear filter. The characterization efficiency of the obtained model is compared with the model adapted with the Least Mean Square (LMS) 2-D adaptive algorithm and with the cooccurrence method features. The comparison criteria is based on the computation of a characterization degree using the ratio of "betweenclass" variances with respect to "within-class" variances of the estimated coefficients. Extensive experiments show that the coefficients estimated by the use of Chandrasekhar adaptive filter give better results in texture discrimination than those estimated by other algorithms, even in a noisy context.

Keywords: Texture analysis, statistical features, adaptive filters, Chandrasekhar algorithm.

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Authors: Chen-Chien Hsu, Guo-Tang Dai

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This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multiple swarms are created depending on the number of the target objects under tracking. Because of the efficiency and simplicity of the PSO algorithm for global optimization, target objects can be tracked as iterations continue. Experimental results confirm that the proposed PSO algorithm can rapidly converge, allowing real-time tracking of each target object. When the objects being tracked move outside the tracking range, global search capability of the PSO resumes to re-trace the target objects.

Keywords: multiple object tracking, particle swarm optimization, gray-level histogram, image

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Authors: Emanuele Stomeo, Tatiana Kalganova, Cyrille Lambert

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The evolution of logic circuits, which falls under the heading of evolvable hardware, is carried out by evolutionary algorithms. These algorithms are able to automatically configure reconfigurable devices. One of main difficulties in developing evolvable hardware with the ability to design functional electrical circuits is to choose the most favourable EA features such as fitness function, chromosome representations, population size, genetic operators and individual selection. Until now several researchers from the evolvable hardware community have used and tuned these parameters and various rules on how to select the value of a particular parameter have been proposed. However, to date, no one has presented a study regarding the size of the chromosome representation (circuit layout) to be used as a platform for the evolution in order to increase the evolvability, reduce the number of generations and optimize the digital logic circuits through reducing the number of logic gates. In this paper this topic has been thoroughly investigated and the optimal parameters for these EA features have been proposed. The evolution of logic circuits has been carried out by an extrinsic evolvable hardware system which uses (1+λ) evolution strategy as the core of the evolution.

Keywords: Evolvable hardware, genotype size, computational intelligence, design of logic circuits.

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Authors: H. K. G. K. D. K. Hapuhinna, R. D. Gunaratne, H. M. J. C. Pitawala

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This study aimed to find out chemical and structural suitability of synthesized eppawala hydroxyapatite composite as bone cement, by comparing and contrasting it with human bone as well as commercially available bone cement, which is currently used in orthopedic surgeries. Therefore, a mixture of commercially available bone cement and its liquid monomer, commercially available methyl methacrylate (MMA) and a mixture of solid state synthesized eppawala hydroxyapatite powder with commercially available MMA were prepared as the direct substitution for bone cement. Then physical and chemical properties including composition, crystallinity, presence of functional groups, thermal stability, surface morphology, and microstructural features were examined compared to human bone. Results show that there is a close similarity between synthesized product and human bone and it has exhibited high thermal stability, good crystalline and porous properties than the commercial product. Finally, the study concluded that synthesized hydroxyapatite composite can be used directly as a substitution for commercial bone cement.

Keywords: Hydroxyapatite, bone cement, methyl methacrylate, orthopedics.

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Authors: Cuong Nguyen Khac, Ju H. Park, Ho-Youl Jung

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This paper proposes a new approach to perform the problem of real-time face detection. The proposed method combines primitive Haar-Like feature and variance value to construct a new feature, so-called Variance based Haar-Like feature. Face in image can be represented with a small quantity of features using this new feature. We used SVM instead of AdaBoost for training and classification. We made a database containing 5,000 face samples and 10,000 non-face samples extracted from real images for learning purposed. The 5,000 face samples contain many images which have many differences of light conditions. And experiments showed that face detection system using Variance based Haar-Like feature and SVM can be much more efficient than face detection system using primitive Haar-Like feature and AdaBoost. We tested our method on two Face databases and one Non-Face database. We have obtained 96.17% of correct detection rate on YaleB face database, which is higher 4.21% than that of using primitive Haar-Like feature and AdaBoost.

Keywords: AdaBoost, Haar-Like feature, SVM, variance, Variance based Haar-Like feature.

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Authors: Ali Ihtiyar, Serdar Durdyev, Syuhaida Ismail

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Marketing is an essential issue to the survival of any real estate company in Turkey. There are some factors which are constraining the achievements of the marketing and sales strategies in the Turkey real estate industry. This study aims to identify and prioritise the most significant constraints to marketing in real estate sector and new strategies based on those constraints. This study is based on survey method, where the respondents such as credit counsellors, real estate investors, consultants, academicians and marketing representatives in Turkey were asked to rank forty seven sub-factors according to their levels of impact. The results of Multiattribute analytical technique indicated that the main subcomponents having impact on marketing in real estate sector are interest rates, real estate credit availability, accessibility, company image and consumer real income, respectively. The identified constraints are expected to guide the marketing team in a sales-effective way.

Keywords: Marketing, marketing constraints, Real estate marketing, Turkey real estate sector

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Authors: Anas M. Fares, A. Touqan

Abstract:

A common approach in resisting lateral forces is the use of reinforced concrete shear walls in buildings. These walls represent the main elements to resist the lateral forces due to their large strength and stiffness. However, such walls may contain many openings due to functional requirements, and this may largely affect the overall lateral stiffness of them. It is thus of prime importance to quantify the effect of openings on the dynamic performance of the shear walls. SAP2000 structural analysis program is used as a main source after verifying the results. This study is made by using linear elastic analysis. The results are compared to ASCE7-16 code empirical equations for estimating the fundamental period of shear wall structures. Finally, statistical regression is used to fit an equation for estimating the increase in the fundamental period of shear-walled regular structures due to windows openings in the walls.

Keywords: Concrete, earthquake-resistant design, finite element, fundamental period, lateral stiffness, linear analysis, modal analysis, rayleigh, SAP2000, shear wall, ASCE7-16.

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Authors: Sudip Ghosh, Probir Kumar Ghosh, Paramita Bhattacharjee

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Supercritical carbon dioxide extracts of Cinnamomum tamala (bay) leaves obtained at 55°C, 512 bar was found to have appreciable nutraceutical properties and was successfully employed as value-added ingredients in preparation of tofu. The bay leaf formulated tofu sample was evaluated for physicochemical properties (pH, texture analysis and lipid peroxidation), proximate analysis, phytochemical properties (total phenol content, antioxidant properties and total reducing sugar), microbial load and sensory profile analysis for a storage period of ten days, vis-à-vis an experimental control sample. These assays established the superiority of the tofu sample formulated with supercritical carbon dioxide extract of bay leaf over the control sample. Bay leaf extract formulated tofu is a new green functional food with promising nutraceutical benefits. 

Keywords: Cinnamomum tamala, Physicochemical properties Phytochemical properties, Supercritical carbon dioxide extraction, Tofu.

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Authors: Peter Rothenpieler, Daniela Kruger, Dennis Pfisterer, Stefan Fischer, Denise Dudek, Christian Haas, Martina Zitterbart

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In the project FleGSens, a wireless sensor network (WSN) for the surveillance of critical areas and properties is currently developed which incorporates mechanisms to ensure information security. The intended prototype consists of 200 sensor nodes for monitoring a 500m long land strip. The system is focused on ensuring integrity and authenticity of generated alarms and availability in the presence of an attacker who may even compromise a limited number of sensor nodes. In this paper, two of the main protocols developed in the project are presented, a tracking protocol to provide secure detection of trespasses within the monitored area and a protocol for secure detection of node failures. Simulation results of networks containing 200 and 2000 nodes as well as the results of the first prototype comprising a network of 16 nodes are presented. The focus of the simulations and prototype are functional testing of the protocols and particularly demonstrating the impact and cost of several attacks.

Keywords: Wireless Sensor Network, Security, Trespass Detection, Testbed.

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Authors: Anastasia Rita Widiarti

Abstract:

This paper compares Hilditch, Rosenfeld, Zhang- Suen, dan Nagendraprasad Wang Gupta (NWG) thinning algorithms for Javanese character image recognition. Thinning is an effective process when the focus in not on the size of the pattern, but rather on the relative position of the strokes in the pattern. The research analyzes the thinning of 60 Javanese characters. Time-wise, Zhang-Suen algorithm gives the best results with the average process time being 0.00455188 seconds. But if we look at the percentage of pixels that meet one-pixel thickness, Rosenfelt algorithm gives the best results, with a 99.98% success rate. From the number of pixels that are erased, NWG algorithm gives the best results with the average number of pixels erased being 84.12%. It can be concluded that the Hilditch algorithm performs least successfully compared to the other three algorithms.

Keywords: Hilditch algorithm, Nagendraprasad-Wang-Guptaalgorithm, Rosenfeld algorithm, Thinning, Zhang-suen algorithm

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Authors: Nikolaos Vassilas, Theocharis Tsenoglou, Djamchid Ghazanfarpour

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In this work, we explore the capability of the mean shift algorithm as a powerful preprocessing tool for improving the quality of spatial data, acquired from airborne scanners, from densely built urban areas. On one hand, high resolution image data corrupted by noise caused by lossy compression techniques are appropriately smoothed while at the same time preserving the optical edges and, on the other, low resolution LiDAR data in the form of normalized Digital Surface Map (nDSM) is upsampled through the joint mean shift algorithm. Experiments on both the edge-preserving smoothing and upsampling capabilities using synthetic RGB-z data show that the mean shift algorithm is superior to bilateral filtering as well as to other classical smoothing and upsampling algorithms. Application of the proposed methodology for 3D reconstruction of buildings of a pilot region of Athens, Greece results in a significant visual improvement of the 3D building block model.

Keywords: 3D buildings reconstruction, data fusion, data upsampling, mean shift.

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Authors: Giovanni Luca Masala

Abstract:

A typical definition of the Computer Aided Diagnosis (CAD), found in literature, can be: A diagnosis made by a radiologist using the output of a computerized scheme for automated image analysis as a diagnostic aid. Often it is possible to find the expression Computer Aided Detection (CAD or CADe): this definition emphasizes the intent of CAD to support rather than substitute the human observer in the analysis of radiographic images. In this article we will illustrate the application of CAD systems and the aim of these definitions. Commercially available CAD systems use computerized algorithms for identifying suspicious regions of interest. In this paper are described the general CAD systems as an expert system constituted of the following components: segmentation / detection, feature extraction, and classification / decision making. As example, in this work is shown the realization of a Computer- Aided Detection system that is able to assist the radiologist in identifying types of mammary tumor lesions. Furthermore this prototype of station uses a GRID configuration to work on a large distributed database of digitized mammographic images.

Keywords: Computer Aided Detection, Computer Aided Diagnosis, mammography, GRID.

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Authors: Benjapol Auprasert, Yachai Limpiyakorn

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Measuring the complexity of software has been an insoluble problem in software engineering. Complexity measures can be used to predict critical information about testability, reliability, and maintainability of software systems from automatic analysis of the source code. During the past few years, many complexity measures have been invented based on the emerging Cognitive Informatics discipline. These software complexity measures, including cognitive functional size, lend themselves to the approach of the total cognitive weights of basic control structures such as loops and branches. This paper shows that the current existing calculation method can generate different results that are algebraically equivalence. However, analysis of the combinatorial meanings of this calculation method shows significant flaw of the measure, which also explains why it does not satisfy Weyuker's properties. Based on the findings, improvement directions, such as measures fusion, and cumulative variable counting scheme are suggested to enhance the effectiveness of cognitive complexity measures.

Keywords: Cognitive Complexity Measure, Cognitive Weight of Basic Control Structure, Counting Rules, Cumulative Variable Counting Scheme.

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Authors: S. Ashrafpour, T. Tohidi Moghadam, B. Ranjbar

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Identifying the nature of protein-nanoparticle interactions and favored binding sites is an important issue in functional characterization of biomolecules and their physiological responses. Herein, interaction of silver nanoparticles with lysozyme as a model protein has been monitored via fluorescence spectroscopy. Formation of complex between the biomolecule and silver nanoparticles (AgNPs) induced a steady state reduction in the fluorescence intensity of protein at different concentrations of nanoparticles. Tryptophan fluorescence quenching spectra suggested that silver nanoparticles act as a foreign quencher, approaching the protein via this residue. Analysis of the Stern-Volmer plot showed quenching constant of 3.73 μM−1. Moreover, a single binding site in lysozyme is suggested to play role during interaction with AgNPs, having low affinity of binding compared to gold nanoparticles. Unfolding studies of lysozyme showed that complex of lysozyme- AgNPs has not undergone structural perturbations compared to the bare protein. Results of this effort will pave the way for utilization of sensitive spectroscopic techniques for rational design of nanobiomaterials in biomedical applications.

Keywords: Nanocarrier, Nanoparticles, Surface Plasmon Resonance, Quenching Fluorescence.

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Authors: Leena N. Fukey, Surya S. Issac

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This review paper aims at understanding the importance of implementing sustainable green practices in the current hotel industry and the perception of the same from the point of view of the customers as well as the industry experts. Many hotels have benefited from green management such as enhanced reputation of the firm and more worth customers. For the business standing, it reduces business’s cost for posting advertisements and the clear hotel’s orientation shows hotels’ positive image which might increase employees’ recognition toward the business. Sustainability in business is the growth in lively processes which enable people to understand the potential to protect the Earth’s existent support systems. Well, looking to the future today’s green concerns will definitely become facet of more synchronized business environment, perhaps the concerns discussed in this study, may exchange a few words which hotels may consider in near future to widen awareness and improve business model.

Keywords: Environmental Protection, Green Hotel Concept, Hotel Industry, Sustainability.

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Authors: Jieh-Haur Chen, Pei-Fen Huang

Abstract:

This paper presents an integrated model that automatically measures the change of rivers, damage area of bridge surroundings, and change of vegetation. The proposed model is on the basis of a neurofuzzy mechanism enhanced by SOM optimization algorithm, and also includes three functions to deal with river imagery. High resolution imagery from FORMOSAT-2 satellite taken before and after the invasion period is adopted. By randomly selecting a bridge out of 129 destroyed bridges, the recognition results show that the average width has increased 66%. The ruined segment of the bridge is located exactly at the most scour region. The vegetation coverage has also reduced to nearly 90% of the original. The results yielded from the proposed model demonstrate a pinpoint accuracy rate at 99.94%. This study brings up a successful tool not only for large-scale damage assessment but for precise measurement to disasters.

Keywords: remote sensing image, damage assessment, typhoon disaster, bridge, ANN, fuzzy, SOM, optimization.

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