Search results for: image guided radiation therapy

Authors: Elizabeth B. Varghese, M. Wilscy

Abstract:

A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame. A lot of algorithms have been proposed for face recognition. Vector Quantization (VQ) based face recognition is a novel approach for face recognition. Here a new codebook generation for VQ based face recognition using Integrated Adaptive Fuzzy Clustering (IAFC) is proposed. IAFC is a fuzzy neural network which incorporates a fuzzy learning rule into a competitive neural network. The performance of proposed algorithm is demonstrated by using publicly available AT&T database, Yale database, Indian Face database and a small face database, DCSKU database created in our lab. In all the databases the proposed approach got a higher recognition rate than most of the existing methods. In terms of Equal Error Rate (ERR) also the proposed codebook is better than the existing methods.

Keywords: Face Recognition, Vector Quantization, Integrated Adaptive Fuzzy Clustering, Self Organization Map.

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Authors: B. Al-Naami, N. Gharaibeh, A. AlRazzaq Kheshman

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Alzheimer is known as the loss of mental functions such as thinking, memory, and reasoning that is severe enough to interfere with a person's daily functioning. The appearance of Alzheimer Disease symptoms (AD) are resulted based on which part of the brain has a variety of infection or damage. In this case, the MRI is the best biomedical instrumentation can be ever used to discover the AD existence. Therefore, this paper proposed a fusion method to distinguish between the normal and (AD) MRIs. In this combined method around 27 MRIs collected from Jordanian Hospitals are analyzed based on the use of Low pass -morphological filters to get the extracted statistical outputs through intensity histogram to be employed by the descriptive box plot. Also, the artificial neural network (ANN) is applied to test the performance of this approach. Finally, the obtained result of t-test with confidence accuracy (95%) has compared with classification accuracy of ANN (100 %). The robust of the developed method can be considered effectively to diagnose and determine the type of AD image.

Keywords: Alzheimer disease, Brain MRI analysis, Morphological filter, Box plot, Intensity histogram, ANN.

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Authors: Lorena Urricelqui, Armando Malanda, Arantxa Villanueva

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Purpose: To develop a method for automatic segmentation of adipose and muscular tissue in thighs from magnetic resonance images. Materials and methods: Thirty obese women were scanned on a Siemens Impact Expert 1T resonance machine. 1500 images were finally used in the tests. The developed segmentation method is a recursive and multilevel process that makes use of several concepts such as shaped histograms, adaptative thresholding and connectivity. The segmentation process was implemented in Matlab and operates without the need of any user interaction. The whole set of images were segmented with the developed method. An expert radiologist segmented the same set of images following a manual procedure with the aid of the SliceOmatic software (Tomovision). These constituted our 'goal standard'. Results: The number of coincidental pixels of the automatic and manual segmentation procedures was measured. The average results were above 90 % of success in most of the images. Conclusions: The proposed approach allows effective automatic segmentation of MRIs from thighs, comparable to expert manual performance.

Keywords: Segmentation, thigh, magnetic resonance image, fat, muscle.

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Authors: Tan Kian Lam, Abdullah Zawawi bin Haji Talib, Mohd. Azam Osman

Abstract:

This paper describes a method of modeling to model shadow play puppet using sophisticated computer graphics techniques available in OpenGL in order to allow interactive play in real-time environment as well as producing realistic animation. This paper proposes a novel real-time method is proposed for modeling of puppet and its shadow image that allows interactive play of virtual shadow play using texture mapping and blending techniques. Special effects such as lighting and blurring effects for virtual shadow play environment are also developed. Moreover, the use of geometric transformations and hierarchical modeling facilitates interaction among the different parts of the puppet during animation. Based on the experiments and the survey that were carried out, the respondents involved are very satisfied with the outcomes of these techniques.

Keywords: Animation, blending, hierarchical modeling, interactive play, real-time, shadow play, visual simulation.

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Authors: Sherin M. Youssef, Ahmed Abouelfarag, Noha M. Ghatwary

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An adaptive Fuzzy Inference Perceptual model has been proposed for watermarking of digital images. The model depends on the human visual characteristics of image sub-regions in the frequency multi-resolution wavelet domain. In the proposed model, a multi-variable fuzzy based architecture has been designed to produce a perceptual membership degree for both candidate embedding sub-regions and strength watermark embedding factor. Different sizes of benchmark images with different sizes of watermarks have been applied on the model. Several experimental attacks have been applied such as JPEG compression, noises and rotation, to ensure the robustness of the scheme. In addition, the model has been compared with different watermarking schemes. The proposed model showed its robustness to attacks and at the same time achieved a high level of imperceptibility.

Keywords: Watermarking, The human visual system (HVS), Fuzzy Inference System (FIS), Local Binary Pattern (LBP), Discrete Wavelet Transform (DWT).

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Authors: N. Chetty, K. Singh

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In this work, the relationship between the melanin content in a tissue and subsequent absorption of light through that tissue was determined using a digital camera. This technique proved to be simple, cost effective, efficient and reliable. Tissue phantom samples were created using milk and soy sauce to simulate the optical properties of melanin content in human tissue. Increasing the concentration of soy sauce in the milk correlated to an increase in melanin content of an individual. Two methods were employed to measure the light transmitted through the sample. The first was direct measurement of the transmitted intensity using a conventional lux meter. The second method involved correctly calibrating an ordinary digital camera and using image analysis software to calculate the transmitted intensity through the phantom. The results from these methods were then graphically compared to the theoretical relationship between the intensity of transmitted light and the concentration of absorbers in the sample. Conclusions were then drawn about the effectiveness and efficiency of these low cost methods.

Keywords: Tissue phantoms, scattering coefficient, albedo, low-cost method.

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Authors: M. Iommi, G. Losco

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Current building sector is focused on reduction of energy requirements, on renewable energy generation and on regeneration of existing urban areas. These targets need to be solved with a systemic approach, considering several aspects simultaneously such as climate conditions, lighting conditions, solar radiation, PV potential, etc. The solar access analysis is an already known method to analyze the solar potentials, but in current years, simulation tools have provided more effective opportunities to perform this type of analysis, in particular in the early design stage. Nowadays, the study of the solar access is related to the easiness of the use of simulation tools, in rapid and easy way, during the design process. This study presents a comparison of three simulation tools, from the point of view of the user, with the aim to highlight differences in the easy-to-use of these tools. Using a real urban context as case study, three tools; Ecotect, Townscope and Heliodon, are tested, performing models and simulations and examining the capabilities and output results of solar access analysis. The evaluation of the ease-to-use of these tools is based on some detected parameters and features, such as the types of simulation, requirements of input data, types of results, etc. As a result, a framework is provided in which features and capabilities of each tool are shown. This framework shows the differences among these tools about functions, features and capabilities. The aim of this study is to support users and to improve the integration of simulation tools for solar access with the design process.

Keywords: Solar access analysis, energy building design tools, urban planning, solar potential.

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Authors: Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park, Kwang-Mo Jung

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This paper proposes a method to recognize the tip of a finger and space touch hand gesture using an infrared camera in a smart device environment. The proposed method estimates the tip of a finger with a curvature-based ellipse fitting algorithm, and verifies that the estimated object is indeed a finger with an ellipse fitting rectangular area. The feature extracted from the verified finger tip is used to implement the movement of a mouse and clicking gesture. The proposed algorithm was implemented with an actual smart device to test the proposed method. Empirical parameters were obtained from the keypad software and an image analysis tool for the performance optimization, and a comparative analysis with conventional research showed improved performance with the proposed method.

Keywords: Infrared camera, Hand gesture, Smart device, Space touch.

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Authors: Lubis A., Setiawati L., Setyoningrum A. R., Suryawan A., Irwanto

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Asthma is a condition that causing chronic health problems in children. In addition to basic therapy against disease, we must try to reduce the impact of chronic health problems and also optimize their medical aspect of growth and development. A boy with mild asthma attack frequent episode did not showed any improvement with medical treatment and his asthma control test was 11. From radiologic examination he got hyperaerated lung and billateral sinusitis maxillaris; skin test results were house dust, food and pet allergy; an overweight body; bad school grades; psychological and environmental problem. We followed and evaluated this boy in 6 months, treated holistically. Even we could not do much on environmental but no more psychological and school problems, his on a good bodyweight and his asthma control test was 22. A case of a child with mild asthma attack frequent episode was reported. Asthma clinical course show no significant improvement when other predisposing factor is not well-controlled and a child’s growth and development may be affected. Improving condition of the patient can be created with the help of loving and caring way of nurturing from the parents and supportive peer group. Therefore, continuous and consistent monitoring is required because prognosis of asthma is generally good when regularly and properly controlled.

Keywords: Asthma, chronic health problems, growth and development.

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Authors: Peng-Hui Maffee Wan, Klarissa Ting Ting Chang, Rax Suen Chun Lung

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Icons, or pictorial and graphical objects, are commonly used in human-computer interaction (HCI) fields as the mediator in order to communicate information to users. Yet there has been little studies focusing on a majority of the world’s population – semi-literate communities – in terms of the fundamental knowhow for designing icons for such population. In this study, two sets of icons belonging in different icon taxonomy – abstract and concrete – are designed for a mobile application for semi-literate agricultural communities. In this paper, we propose a triadic relationship of an icon, namely meaning, task and mental image, which inherits the triadic relationship of a sign. User testing with the application and a post-pilot questionnaire are conducted as the experimental approach in two rural villages in India. Icons belonging to concrete taxonomy perform better than abstract icons on the premise that the design of the icon fulfills the underlying rules of the proposed triadic relationship.

Keywords: Icon, GUI, mobile app, semi-literate.

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Authors: Ching-Fen Jiang

Abstract:

Edge detection is usually the first step in medical image processing. However, the difficulty increases when a conventional kernel-based edge detector is applied to ultrasonic images with a textural pattern and speckle noise. We designed an adaptive diffusion filter to remove speckle noise while preserving the initial edges detected by using a Sobel edge detector. We also propose a genetic algorithm for edge selection to form complete boundaries of the detected entities. We designed two fitness functions to evaluate whether a criterion with a complex edge configuration can render a better result than a simple criterion such as the strength of gradient. The edges obtained by using a complex fitness function are thicker and more fragmented than those obtained by using a simple fitness function, suggesting that a complex edge selecting scheme is not necessary for good edge detection in medical ultrasonic images; instead, a proper noise-smoothing filter is the key.

Keywords: edge detection, ultrasonic images, speckle noise

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Authors: M. Hajzler, J. Klimesova, T. Streda, K. Vejrazka, V. Marecek, T. Cholastova

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The most planted cover crops in the Czech Republic are mustard (Sinapis alba) and phacelia (Phacelia tanacetifolia Benth.). A field trial was executed to evaluate root system size (RSS) in eight varieties of mustard and five varieties of phacelia on two locations, in three BBCH phases and in two years. The relationship between RSS and aboveground biomass was inquired. The root system was assessed by measuring its electric capacity. Aboveground mass and root samples to be evaluated by means of a digital image analysis were recovered in the BBCH phase 70. The yield of aboveground biomass of mustard was always statistically significantly higher than that of phacelia. Mustard showed a statistically significant negative correlation between root length density (RLD) within 10 cm and aboveground biomass weight (r = - 0.46*). Phacelia featured a statistically significant correlation between aboveground biomass production and nitrate nitrogen content in soil (r=0.782**).

Keywords: Aboveground Biomass, Cover crop, Nitrogen content, Root system size

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Authors: H. Heidari-Bafroui, B. Ribeiro, A. Charbaji, C. Anagnostopoulos, M. Faghri

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In this paper, we report the development of a portable and inexpensive infrared lightbox for improving the detection limits of paper-based phosphate devices. Commercial paper-based devices utilize the molybdenum blue protocol to detect phosphate in the environment. Although these devices are easy to use and have a long shelf life, their main deficiency is their low sensitivity based on the qualitative results obtained via a color chart. To improve the results, we constructed a compact infrared lightbox that communicates wirelessly with a smartphone. The system measures the absorbance of radiation for the molybdenum blue reaction in the infrared region of the spectrum. It consists of a lightbox illuminated by four infrared light-emitting diodes, an infrared digital camera, a Raspberry Pi microcontroller, a mini-router, and an iPhone to control the microcontroller. An iPhone application was also developed to analyze images captured by the infrared camera in order to quantify phosphate concentrations. Additionally, the app connects to an online data center to present a highly scalable worldwide system for tracking and analyzing field measurements. In this study, the detection limits for two popular commercial devices were improved by a factor of 4 for the Quantofix devices (from 1.3 ppm using visible light to 300 ppb using infrared illumination) and a factor of 6 for the Indigo units (from 9.2 ppm to 1.4 ppm) with repeatability of less than or equal to 1.2% relative standard deviation (RSD). The system also provides more granular concentration information compared to the discrete color chart used by commercial devices and it can be easily adapted for use in other applications.

Keywords: Infrared lightbox, paper-based device, phosphate detection, smartphone colorimetric analyzer.

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Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi

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In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.

Keywords: Automatic number plate recognition, character segmentation, convolutional neural network, CNN, deep learning, number plate localization.

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Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8.

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Authors: Magda S. Taipina, Maria L. Garbelotti, Mariana G.B. Cadioli

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Banana is one of the most consumed fruits in the tropics and subtropics. Brazil accounts for about 9% of the world banana production. However, the production losses are as high as 30 to 40% and even much higher in some developing countries. The green banana flour is a complex carbohydrate source, including a high total starch (73.4%), resistant starch (17.5%) with functional properties. Gamma irradiation is considered to be an alternative method for food preservation. It has been performed due to the need of extending the shelf - life of foods, whilst maintaining their safety and avoiding one of the main concerns: the nutrient loss. In this work data about on the effects of ionizing radiation on the physicochemical analysis (carbohydrate, proteins, lipids, alimentary fiber, moistures and ashes) of Brazilian functional products (biscuits and bread) of the green banana pulp are presented. The caloric value was calculated. No significant difference was observed between the samples of irradiated and non – irradiated green banana biscuits with the following determinations: carbohydrates, proteins, alimentary fiber and ashes. Only a small significant difference was found in lipids (macronutrients). The results of physical chemical analysis of the irradiated and non- irradiated green banana bread non- irradiated showed no significant difference with the following determinations: carbohydrates, lipids (macronutrients), moisture, ashes and caloric value. A small difference was found in proteins (macronutrients). Irradiation of functional products (biscuits and bread) with doses of 1 and 3kGy maintained their original macronutrients content, showing good radioresistance.

Keywords: Irradiation, Functional Food, Nutritional value.

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Authors: Farhana Mohamad Yusop, Syafrudin Masri, Dahaman Ishak, Mohamad Kamarol

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Electromagnetic forces on three-phase five-wire (3P5W) busbar system is investigated under three-phase short-circuits current. The conductor busbar placed in compact galvanized steel enclosure is in the rectangular shape. Transient analysis from Opera-2D is carried out to develop the model of three-phase short-circuits current in the system. The result of the simulation is compared with the calculation result, which is obtained by applying the theories of Biot Savart’s law and Laplace equation. Under this analytical approach, the moment of peak short-circuit current is taken into account. The effect upon geometrical arrangement of the conductor and the present of the steel enclosure are considered by the theory of image. The result depict that the electromagnetic force due to the transient short-circuit from simulation is agreed with the calculation.

Keywords: Busbar, electromagnetic force, short-circuit current, transient analysis.

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Authors: S. Sarumathi, M. Vaishnavi, S. Geetha, P. Ranjetha

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Machine learning is a new and exciting area of artificial intelligence nowadays. Machine learning is the most valuable, time, supervised, and cost-effective approach. It is not a narrow learning approach; it also includes a wide range of methods and techniques that can be applied to a wide range of complex realworld problems and time domains. Biological image classification, adaptive testing, computer vision, natural language processing, object detection, cancer detection, face recognition, handwriting recognition, speech recognition, and many other applications of machine learning are widely used in research, industry, and government. Every day, more data are generated, and conventional machine learning techniques are becoming obsolete as users move to distributed and real-time operations. By providing fundamental knowledge of machine learning tools and research opportunities in the field, the aim of this article is to serve as both a comprehensive overview and a guide. A diverse set of machine learning resources is demonstrated and contrasted with the key features in this survey.

Keywords: Artificial intelligence, machine learning, deep learning, machine learning algorithms, machine learning tools.

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Authors: Marc C. Robini, Pierre-Jean Viverge, Yuemin Zhu, Jianhua Luo

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The standard approach to image reconstruction is to stabilize the problem by including an edge-preserving roughness penalty in addition to faithfulness to the data. However, this methodology produces noisy object boundaries and creates a staircase effect. The existing attempts to favor the formation of smooth contour lines take the edge field explicitly into account; they either are computationally expensive or produce disappointing results. In this paper, we propose to incorporate the smoothness of the edge field in an implicit way by means of an additional penalty term defined in the wavelet domain. We also derive an efficient half-quadratic algorithm to solve the resulting optimization problem, including the case when the data fidelity term is non-quadratic and the cost function is nonconvex. Numerical experiments show that our technique preserves edge sharpness while smoothing contour lines; it produces visually pleasing reconstructions which are quantitatively better than those obtained without wavelet-domain constraints.

Keywords:

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Authors: Sefa Aksu, Ünal Kızıl

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For this study, a town based soil database created in Gümüsçay District of Biga Town, Çanakkale, Turkey. Crop and livestock production are major activities in the district. Nutrient management is mainly based on commercial fertilizer application ignoring the livestock manure. Within the boundaries of district, 122 soil sampling points determined over the satellite image. Soil samples collected from the determined points with the help of handheld Global Positioning System. Labeled samples were sent to a commercial laboratory to determine 11 soil parameters including salinity, pH, lime, organic matter, nitrogen, phosphorus, potassium, iron, manganese, copper and zinc. Based on the test results soil maps for mentioned parameters were developed using remote sensing, GIS, and geostatistical analysis. In this study we developed a GIS database that will be used for soil nutrient management. Methods were explained and soil maps and their interpretations were summarized in the study.

Keywords: Geostatistics, GIS, Nutrient Management, Soil Mapping.

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Authors: A. Pedram, M. R. Jamali, T. Pedram, S. M. Fakhraie, C. Lucas

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Local Linear Neuro-Fuzzy Models (LLNFM) like other neuro- fuzzy systems are adaptive networks and provide robust learning capabilities and are widely utilized in various applications such as pattern recognition, system identification, image processing and prediction. Local linear model tree (LOLIMOT) is a type of Takagi-Sugeno-Kang neuro fuzzy algorithm which has proven its efficiency compared with other neuro fuzzy networks in learning the nonlinear systems and pattern recognition. In this paper, a dedicated reconfigurable and parallel processing hardware for LOLIMOT algorithm and its applications are presented. This hardware realizes on-chip learning which gives it the capability to work as a standalone device in a system. The synthesis results on FPGA platforms show its potential to improve the speed at least 250 of times faster than software implemented algorithms.

Keywords: LOLIMOT, hardware, neurofuzzy systems, reconfigurable, parallel.

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Authors: Huafeng Wang, Yunhong Wang, Yuan Cao

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During the past several years, face recognition in video has received significant attention. Not only the wide range of commercial and law enforcement applications, but also the availability of feasible technologies after several decades of research contributes to the trend. Although current face recognition systems have reached a certain level of maturity, their development is still limited by the conditions brought about by many real applications. For example, recognition images of video sequence acquired in an open environment with changes in illumination and/or pose and/or facial occlusion and/or low resolution of acquired image remains a largely unsolved problem. In other words, current algorithms are yet to be developed. This paper provides an up-to-date survey of video-based face recognition research. To present a comprehensive survey, we categorize existing video based recognition approaches and present detailed descriptions of representative methods within each category. In addition, relevant topics such as real time detection, real time tracking for video, issues such as illumination, pose, 3D and low resolution are covered.

Keywords: Face recognition, video-based, survey

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Authors: R. M. R. Hussein

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Sustainable urban waterfront development is one of the most interesting phenomena of urban renewal in the last decades. However, there are still many cities whose visual image is compromised due to the lack of a sustainable urban waterfront development, which consequently affects the place of those cities globally. This paper aims to reimagine the role of waterfront areas in city design, with a particular focus on Egypt, so that they provide attractive, sustainable urban environments while promoting the continued aesthetic development of the city overall. This aim will be achieved by determining the main principles of a sustainable urban waterfront and its applications. This paper concentrates on sustainability assessment rating systems. A number of international case-studies, wherein a city has applied the basic principles for a sustainable urban waterfront and have made use of sustainability assessment rating systems, have been selected as examples which can be applied to the urban waterfronts in Egypt. This paper establishes the importance of developing the design of urban environments in Egypt, as well as identifying the methods of sustainability application for urban waterfronts.

Keywords: Sustainable Urban Waterfront, Green Infrastructure, Energy Efficient, Cairo.

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Authors: Chintanu K. Sarmah, Sandhya Samarasinghe, Don Kulasiri, Daniel Catchpoole

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Gene expression profiling is rapidly evolving into a powerful technique for investigating tumor malignancies. The researchers are overwhelmed with the microarray-based platforms and methods that confer them the freedom to conduct large-scale gene expression profiling measurements. Simultaneously, investigations into cross-platform integration methods have started gaining momentum due to their underlying potential to help comprehend a myriad of broad biological issues in tumor diagnosis, prognosis, and therapy. However, comparing results from different platforms remains to be a challenging task as various inherent technical differences exist between the microarray platforms. In this paper, we explain a simple ratio-transformation method, which can provide some common ground for cDNA and Affymetrix platform towards cross-platform integration. The method is based on the characteristic data attributes of Affymetrix- and cDNA- platform. In the work, we considered seven childhood leukemia patients and their gene expression levels in either platform. With a dataset of 822 differentially expressed genes from both these platforms, we carried out a specific ratio-treatment to Affymetrix data, which subsequently showed an improvement in the relationship with the cDNA data.

Keywords: Gene expression profiling, microarray, cDNA, Affymetrix, childhood leukaemia.

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Authors: Miika Toivanen, Jouko Lampinen

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This paper presents an online method that learns the corresponding points of an object from un-annotated grayscale images containing instances of the object. In the first image being processed, an ensemble of node points is automatically selected which is matched in the subsequent images. A Bayesian posterior distribution for the locations of the nodes in the images is formed. The likelihood is formed from Gabor responses and the prior assumes the mean shape of the node ensemble to be similar in a translation and scale free space. An association model is applied for separating the object nodes and background nodes. The posterior distribution is sampled with Sequential Monte Carlo method. The matched object nodes are inferred to be the corresponding points of the object instances. The results show that our system matches the object nodes as accurately as other methods that train the model with annotated training images.

Keywords: Bayesian modeling, Gabor filters, Online learning, Sequential Monte Carlo.

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Authors: E. Tarantino, G. Disciglio, G. Gatta, L. Frabboni, A. Libutti, A. Tarantino

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Worldwide, about two-thirds of industrial and domestic wastewater effluent is discharged without treatment, which can cause contamination and eutrophication of the water. In particular, for Mediterranean countries, irrigation with treated wastewater would mitigate the water stress and support the agricultural sector. Changing global weather patterns will make the situation worse, due to increased susceptibility to drought, which can cause major environmental, social, and economic problems. The study was carried out in open field in an intensive agricultural area of the Apulian region in Southern Italy where freshwater resources are often scarce. As well as providing a water resource, irrigation with treated wastewater represents a significant source of nutrients for soil–plant systems. However, the use of wastewater might have further effects on soil. This study thus investigated the long-term impact of irrigation with reclaimed agro-industrial wastewater on the chemical characteristics of the soil. Two crops (processing tomato and broccoli) were cultivated in succession in Stornarella (Foggia) over four years from 2012 to 2016 using two types of irrigation water: groundwater and tertiary treated agro-industrial wastewater that had undergone an activated sludge process, sedimentation filtration, and UV radiation. Chemical analyses were performed on the irrigation waters and soil samples. The treated wastewater was characterised by high levels of several chemical parameters including TSS, EC, COD, BOD₅, Na⁺, Ca²⁺, Mg²⁺, NH₄-N, PO₄-P, K⁺, SAR and CaCO₃, as compared with the groundwater. However, despite these higher levels, the mean content of several chemical parameters in the soil did not show relevant differences between the irrigation treatments, in terms of the chemical features of the soil.

Keywords: Agro-industrial wastewater, broccoli, long-term re-use, tomato.

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Authors: U K Chakrabarti, Jigisha Parikh

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Hazardous Material transportation by road is coupled with inherent risk of accidents causing loss of lives, grievous injuries, property losses and environmental damages. The most common type of hazmat road accident happens to be the releases (78%) of hazardous substances, followed by fires (28%), explosions (14%) and vapour/ gas clouds (6 %.). The paper is discussing initially the probable 'Impact Zones' likely to be caused by one flammable (LPG) and one toxic (ethylene oxide) chemicals being transported through a sizable segment of a State Highway connecting three notified Industrial zones in Surat district in Western India housing 26 MAH industrial units. Three 'hotspots' were identified along the highway segment depending on the particular chemical traffic and the population distribution within 500 meters on either sides. The thermal radiation and explosion overpressure have been calculated for LPG / Ethylene Oxide BLEVE scenarios along with toxic release scenario for ethylene oxide. Besides, the dispersion calculations for ethylene oxide toxic release have been made for each 'hotspot' location and the impact zones have been mapped for the LOC concentrations. Subsequently, the maximum Initial Isolation and the protective zones were calculated based on ERPG-3 and ERPG-2 values of ethylene oxide respectively which are estimated taking the worst case scenario under worst weather conditions. The data analysis will be helpful to the local administration in capacity building with respect to rescue / evacuation and medical preparedness and quantitative inputs to augment the District Offsite Emergency Plan document.

Keywords: Hotspot, Ethylene Oxide, LPG, MAH (MajorAccident Hazard).

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Authors: SunWoo Lee, TaeBum Lee, YoonHwa Park, YooJeong Kim

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Solar lentigines appear predominantly on chronically sun-exposed areas of skin, such as the face and the back of the hands. Among the several ways to lentigines treatment, quality-switched lasers are well-known effective treatment for removing solar lentigines. The present pilot study was therefore designed to assess the efficacy of quality-switched ruby laser treatment of such lentigines compare between pretreatment and posttreatment of skin brightness. Twenty-two adults with chronic sun-damaged skin (mean age 52.8 years, range 37–74 years) were treated at the Korean site. A 694 nm Q-switched ruby laser was used, with the energy density set from 1.4 to 12.5 J/cm2, to treat solar lentigines. Average brightness of skin color before ruby laser treatment was 137.3 and its skin color was brightened after ruby laser treatment by 150.5. Also, standard deviation of skin color was decreased from 17.8 to 16.4. Regarding the multivariate model, age and energy were identified as significant factors for skin color brightness change in lentigo depigmentation by ruby laser treatment. Their respective odds ratios were 1.082 (95% CI, 1.007–1.163), and 1.431 (95% CI, 1.051–1.946). Lentigo depigmentation treatment using ruby lasers resulted in a high performance in skin color brightness. Among the relative factors involve with ruby laser treatment, age and energy were the most effective factors which skin color change to brighter than pretreatment.

Keywords: Depigmentation, lentigo, quality switched ruby laser, skin color.

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Authors: Salim Ouchtati, Bedda Mouldi, Abderrazak Lachouri

Abstract:

In this paper we present an off line system for the recognition of the handwritten numeric chains. Our work is divided in two big parts. The first part is the realization of a recognition system of the isolated handwritten digits. In this case the study is based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. The used parameters to form the input vector of the neural network are extracted on the binary images of the digits by several methods: the distribution sequence, the Barr features and the centred moments of the different projections and profiles. The second part is the extension of our system for the reading of the handwritten numeric chains constituted of a variable number of digits. The vertical projection is used to segment the numeric chain at isolated digits and every digit (or segment) will be presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits). The result of the recognition of the numeric chain will be displayed at the exit of the global system.

Keywords: Optical Characters Recognition, Neural networks, Barr features, Image processing, Pattern Recognition, Featuresextraction.

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Authors: H. Kheirollahi, Y. Luo

Abstract:

Studying stress and strain trends in the femur and recognizing femur failure mechanism is very important for preventing hip fracture in the elderly. The aim of this study was to identify high stress and strain regions in the femur during normal walking and falling to find the mechanical behavior and failure mechanism of the femur. We developed a finite element model of the femur from the subject’s quantitative computed tomography (QCT) image and used it to identify potentially high stress and strain regions during the single-leg stance and the sideways fall. It was found that fracture may initiate from the superior region of femoral neck and propagate to the inferior region during a high impact force such as sideways fall. The results of this study showed that the femur bone is more sensitive to strain than stress which indicates the effect of strain, in addition to effect of stress, should be considered for failure analysis.

Keywords: Finite element analysis, hip fracture, strain, stress.

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