Search results for: Traffic Light Detection

Authors: Wiroon Sriborrirux, Sorakrai Kraipui, Nakorn Indra-Payoong

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One of the most importance of intelligence in-car and roadside systems is the cooperative vehicle-infrastructure system. In Thailand, ITS technologies are rapidly growing and real-time vehicle information is considerably needed for ITS applications; for example, vehicle fleet tracking and control and road traffic monitoring systems. This paper defines the communication protocols and software design for middleware components of B-VIS (Burapha Vehicle-Infrastructure System). The proposed B-VIS middleware architecture serves the needs of a distributed RFID sensor network and simplifies some intricate details of several communication standards.

Keywords: Middleware, RFID sensor network, Cooperativevehicle-infrastructure system, Enterprise Java Bean.

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Authors: Soukaina Motia, Nadia El Alami El Hassani, Alassane Diouf, Benachir Bouchikhi, Nezha El Bari

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Parabens are the antimicrobial molecules largely used in cosmetic products as a preservative agent. Among them, the methylparaben (MP) is the most frequently used ingredient in cosmetic preparations. Nevertheless, their potential dangers led to the development of sensible and reliable methods for their determination in environmental samples. Firstly, a sensitive and selective molecular imprinted polymer (MIP) based on screen-printed gold electrode (Au-SPE), assembled on a polymeric layer of carboxylated poly(vinyl-chloride) (PVC-COOH), was developed. After the template removal, the obtained material was able to rebind MP and discriminate it among other interfering species such as glucose, sucrose, and citric acid. The behavior of molecular imprinted sensor was characterized by Cyclic Voltammetry (CV), Differential Pulse Voltammetry (DPV) and Electrochemical Impedance Spectroscopy (EIS) techniques. Then, the biosensor was found to have a linear detection range from 0.1 pg.mL^-1 to 1 ng.mL^-1 and a low limit of detection of 0.12 fg.mL^-1 and 5.18 pg.mL^-1 by DPV and EIS, respectively. For applications, this biosensor was employed to determine MP content in four wastewaters in Meknes city and two cosmetic products (shower gel and shampoo). The operational reproducibility and stability of this biosensor were also studied. Secondly, another MIP biosensor based on tungsten trioxide (WO₃) functionalized by gold nanoparticles (Au-NPs) assembled on a polymeric layer of PVC-COOH was developed. The main goal was to increase the sensitivity of the biosensor. The developed MIP biosensor was successfully applied for the MP determination in wastewater samples and cosmetic products.

Keywords: Cosmetic products, methylparaben, molecularly imprinted polymer, wastewater.

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Authors: S. Hutasavi, D. Chen

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The built-up area is a significant proxy to measure regional economic growth and reflects the Gross Provincial Product (GPP). However, an up-to-date and reliable database of built-up areas is not always available, especially in developing countries. The cloud-based geospatial analysis platform such as Google Earth Engine (GEE) provides an opportunity with accessibility and computational power for those countries to generate the built-up data. Therefore, this study aims to extract the built-up areas in Eastern Economic Corridor (EEC), Thailand using day and nighttime satellite imagery based on GEE facilities. The normalized indices were generated from Landsat 8 surface reflectance dataset, including Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Modified Built-up Index (MBUI). These indices were applied to identify built-up areas in EEC. The result shows that MBUI performs better than BUI and NDBI, with the highest accuracy of 0.85 and Kappa of 0.82. Moreover, the overall accuracy of classification was improved from 79% to 90%, and error of total built-up area was decreased from 29% to 0.7%, after night-time light data from the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB). The results suggest that MBUI with night-time light imagery is appropriate for built-up area extraction and be utilize for further study of socioeconomic impacts of regional development policy over the EEC region.

Keywords: Built-up area extraction, Google earth engine, adaptive thresholding method, rapid mapping.

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Authors: Mohamed El Morsy, Gabriela Achtenová

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Research on damage of gears and gear pairs using vibration signals remains very attractive, because vibration signals from a gear pair are complex in nature and not easy to interpret. Predicting gear pair defects by analyzing changes in vibration signal of gears pairs in operation is a very reliable method. Therefore, a suitable vibration signal processing technique is necessary to extract defect information generally obscured by the noise from dynamic factors of other gear pairs.This article presents the value of cepstrum analysis in vehicle gearbox fault diagnosis. Cepstrum represents the overall power content of a whole family of harmonics and sidebands when more than one family of sidebands is present at the same time. The concept for the measurement and analysis involved in using the technique are briefly outlined. Cepstrum analysis is used for detection of an artificial pitting defect in a vehicle gearbox loaded with different speeds and torques. The test stand is equipped with three dynamometers; the input dynamometer serves asthe internal combustion engine, the output dynamometers introduce the load on the flanges of the output joint shafts. The pitting defect is manufactured on the tooth side of a gear of the fifth speed on the secondary shaft. Also, a method for fault diagnosis of gear faults is presented based on order Cepstrum. The procedure is illustrated with the experimental vibration data of the vehicle gearbox. The results show the effectiveness of Cepstrum analysis in detection and diagnosis of the gear condition.

Keywords: Cepstrum analysis, fault diagnosis, gearbox.

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Authors: Feng Ge, Tiecheng Liu, Song Wang, Joachim Stahl

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This paper presents a novel template-based method to detect objects of interest from real images by shape matching. To locate a target object that has a similar shape to a given template boundary, the proposed method integrates three components: contour grouping, partial shape matching, and boundary verification. In the first component, low-level image features, including edges and corners, are grouped into a set of perceptually salient closed contours using an extended ratio-contour algorithm. In the second component, we develop a partial shape matching algorithm to identify the fractions of detected contours that partly match given template boundaries. Specifically, we represent template boundaries and detected contours using landmarks, and apply a greedy algorithm to search the matched landmark subsequences. For each matched fraction between a template and a detected contour, we estimate an affine transform that transforms the whole template into a hypothetic boundary. In the third component, we provide an efficient algorithm based on oriented edge lists to determine the target boundary from the hypothetic boundaries by checking each of them against image edges. We evaluate the proposed method on recognizing and localizing 12 template leaves in a data set of real images with clutter back-grounds, illumination variations, occlusions, and image noises. The experiments demonstrate the high performance of our proposed method1.

Keywords: Object detection, shape matching, contour grouping.

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Authors: Marco E. O. Jardim, Frederico A. M. Souza, Valeria M. Bastos, Myrian C. A. Costa, Nelson F. F. Ebecken

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Urban public transportation in Rio de Janeiro is based on bus lines, powered by diesel, and four limited metro lines that support only some neighborhoods. This work presents an infrastructure built to better understand microclimate variations related to massive urban transportation in some specific areas of the city. The use of sensor nodes with small analytics capacity provides environmental information to population or public services. The analyses of data collected from a few small sensors positioned near some heavy traffic streets show the harmful impact due to poor bus route plan.

Keywords: Big data, IoT, public transportation, public health system.

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Authors: Jonghyun Park, Soonyoung Park, Sanggyun Kim, Wanhyun Cho, Sunworl Kim

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In general, image-based 3D scenes can now be found in many popular vision systems, computer games and virtual reality tours. So, It is important to segment ROI (region of interest) from input scenes as a preprocessing step for geometric stricture detection in 3D scene. In this paper, we propose a method for segmenting ROI based on tensor voting and Dirichlet process mixture model. In particular, to estimate geometric structure information for 3D scene from a single outdoor image, we apply the tensor voting and Dirichlet process mixture model to a image segmentation. The tensor voting is used based on the fact that homogeneous region in an image are usually close together on a smooth region and therefore the tokens corresponding to centers of these regions have high saliency values. The proposed approach is a novel nonparametric Bayesian segmentation method using Gaussian Dirichlet process mixture model to automatically segment various natural scenes. Finally, our method can label regions of the input image into coarse categories: “ground", “sky", and “vertical" for 3D application. The experimental results show that our method successfully segments coarse regions in many complex natural scene images for 3D.

Keywords: Region segmentation, tensor voting, image-based 3D, geometric structure, Gaussian Dirichlet process mixture model

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: Computer-aided system, detection, image segmentation, morphology.

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Authors: Asad Ullah Madni, Mahmood Ahmad, Naveed Akhtar, Muhammad Usman

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A new and cost effective RP-HPLC method was developed and validated for simultaneous analysis of non steroidal anti inflammatory dugs Diclofenac sodium (DFS), Flurbiprofen (FLP) and an opioid analgesic Tramadol (TMD) in advanced drug delivery systems (Liposome and Microcapsules), marketed brands and human plasma. Isocratic system was employed for the flow of mobile phase consisting of 10 mM sodium dihydrogen phosphate buffer and acetonitrile in molar ratio of 67: 33 with adjusted pH of 3.2. The stationary phase was hypersil ODS column (C18, 250×4.6 mm i.d., 5 μm) with controlled temperature of 30 C°. DFS in liposomes, microcapsules and marketed drug products was determined in range of 99.76-99.84%. FLP and TMD in microcapsules and brands formulation were 99.78 - 99.94 % and 99.80 - 99.82 %, respectively. Single step liquid-liquid extraction procedure using combination of acetonitrile and trichloroacetic acid (TCA) as protein precipitating agent was employed. The detection limits (at S/N ratio 3) of quality control solutions and plasma samples were 10, 20, and 20 ng/ml for DFS, FLP and TMD, respectively. The Assay was acceptable in linear dynamic range. All other validation parameters were found in limits of FDA and ICH method validation guidelines. The proposed method is sensitive, accurate and precise and could be applicable for routine analysis in pharmaceutical industry as well as in human plasma samples for bioequivalence and pharmacokinetics studies.

Keywords: Diclofenac Sodium, Flurbiprofen, Tramadol, HPLCUV detection, Validation.

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Authors: V. Praveena, N. Kiruthika

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In this paper, we explore a new scheme for filtering spoofed packets (DDOS attack) which is a combination of path fingerprint and client puzzle concepts. In this each IP packet has a unique fingerprint is embedded that represents, the route a packet has traversed. The server maintains a mapping table which contains the client IP address and its corresponding fingerprint. In ingress router, client puzzle is placed. For each request, the puzzle issuer provides a puzzle which the source has to solve. Our design has the following advantages over prior approaches, 1) Reduce the network traffic, as we place a client puzzle at the ingress router. 2) Mapping table at the server is lightweight and moderate.

Keywords: Client puzzle, DDOS attack, Egress, Ingress, IP Spoofing, Spoofed Packet.

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Authors: SP. Chokkalingam, K. Komathy

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Advances in the field of image processing envision a new era of evaluation techniques and application of procedures in various different fields. One such field being considered is the biomedical field for prognosis as well as diagnosis of diseases. This plethora of methods though provides a wide range of options to select from, it also proves confusion in selecting the apt process and also in finding which one is more suitable. Our objective is to use a series of techniques on bone scans, so as to detect the occurrence of rheumatoid arthritis (RA) as accurately as possible. Amongst other techniques existing in the field our proposed system tends to be more effective as it depends on new methodologies that have been proved to be better and more consistent than others. Computer aided diagnosis will provide more accurate and infallible rate of consistency that will help to improve the efficiency of the system. The image first undergoes histogram smoothing and specification, morphing operation, boundary detection by edge following algorithm and finally image subtraction to determine the presence of rheumatoid arthritis in a more efficient and effective way. Using preprocessing noises are removed from images and using segmentation, region of interest is found and Histogram smoothing is applied for a specific portion of the images. Gray level co-occurrence matrix (GLCM) features like Mean, Median, Energy, Correlation, Bone Mineral Density (BMD) and etc. After finding all the features it stores in the database. This dataset is trained with inflamed and noninflamed values and with the help of neural network all the new images are checked properly for their status and Rough set is implemented for further reduction.

Keywords: Computer Aided Diagnosis, Edge Detection, Histogram Smoothing, Rheumatoid Arthritis.

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Authors: Wenjun Zhang, Yunqing Du, Ming L. Wang

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Noninvasive diagnostics of diseases via breath analysis has attracted considerable scientific and clinical interest for many years and become more and more promising with the rapid advancements in nanotechnology and biotechnology. The volatile organic compounds (VOCs) in exhaled breath, which are mainly blood borne, particularly provide highly valuable information about individuals’ physiological and pathophysiological conditions. Additionally, breath analysis is noninvasive, real-time, painless, and agreeable to patients. We have developed a wireless sensor array based on single-stranded DNA (ssDNA)-functionalized single-walled carbon nanotubes (SWNT) for the detection of a number of physiological indicators in breath. Seven DNA sequences were used to functionalize SWNT sensors to detect trace amount of methanol, benzene, dimethyl sulfide, hydrogen sulfide, acetone, and ethanol, which are indicators of heavy smoking, excessive drinking, and diseases such as lung cancer, breast cancer, and diabetes. Our test results indicated that DNA functionalized SWNT sensors exhibit great selectivity, sensitivity, and repeatability; and different molecules can be distinguished through pattern recognition enabled by this sensor array. Furthermore, the experimental sensing results are consistent with the Molecular Dynamics simulated ssDNAmolecular target interaction rankings. Thus, the DNA-SWNT sensor array has great potential to be applied in chemical or biomolecular detection for the noninvasive diagnostics of diseases and personal health monitoring.

Keywords: Breath analysis, DNA-SWNT sensor array, diagnosis, noninvasive.

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Authors: Eatedal A. Alabdulkreem, Hamed S. Al-Raweshidy, Maysam F. Abbod

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Border Gateway Protocol (BGP) is the standard routing protocol between various autonomous systems (AS) in the internet. In the event of failure, a considerable delay in the BGP convergence has been shown by empirical measurements. During the convergence time the BGP will repeatedly advertise new routes to some destination and withdraw old ones until it reach a stable state. It has been found that the KEEPALIVE message timer and the HOLD time are tow parameters affecting the convergence speed. This paper aims to find the optimum value for the KEEPALIVE timer and the HOLD time that maximally reduces the convergence time without increasing the traffic. The KEEPALIVE message timer optimal value founded by this paper is 30 second instead of 60 seconds, and the optimal value for the HOLD time is 90 seconds instead of 180 seconds.

Keywords: BGP, Convergence Time, HOLD time, Keep alive.

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Authors: Ágoston Winkler, Sándor Juhász, Zoltán Benedek

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The vehicle fleet of public transportation companies is often equipped with intelligent on-board passenger information systems. A frequently used but time and labor-intensive way for keeping the on-board controllers up-to-date is the manual update using different memory cards (e.g. flash cards) or portable computers. This paper describes a compression algorithm that enables data transmission using low bandwidth wireless radio networks (e.g. GPRS) by minimizing the amount of data traffic. In typical cases it reaches a compression rate of an order of magnitude better than that of the general purpose compressors. Compressed data can be easily expanded by the low-performance controllers, too.

Keywords: Data analysis, data compression, differentialencoding, run-length encoding, vehicle control.

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Authors: G. Sandhya Devi, G. Suvarna Kumar, S. Chandini

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This research work aims to develop a system that will analyze and identify students who indulge in malpractices/suspicious activities during the course of an academic offline examination. Automated Video Surveillance provides an optimal solution which helps in monitoring the students and identifying the malpractice event immediately. This work is organized into three modules. The first module deals with performing an impersonation check using a PCA-based face recognition method which is done by cross checking his profile with the database. The presence or absence of the student is even determined in this module by implementing an image registration technique wherein a grid is formed by considering all the images registered using the frontal camera at the determined positions. Second, detecting such facial malpractices in which a student gets involved in conversation with another, trying to obtain unauthorized information etc., based on the threshold range evaluated by considering his/her mouth state whether open or closed. The third module deals with identification of unauthorized material or gadgets used in the examination hall by training the positive samples of the object through various stages. Here, a top view camera feed is analyzed to detect the suspicious activities. The system automatically alerts the administration when any suspicious activities are identified, thereby reducing the error rate caused due to manual monitoring. This work is an improvement over our previous work published in identifying suspicious activities done by examinees in an offline examination.

Keywords: Impersonation, image registration, incrimination, object detection, threshold evaluation.

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Authors: Almas Tayebi, Tayeb Saki Nejad, Alireza Shoukofar

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The trial in the city, located 170 kilometers from the Iranian city of Ahvaz was Omidiyeh. The main factor in this project includes 4 levels in control (without hormones), use of hormones in the seed, vegetative and flowering stage respectively. And sub-plots included 3 varieties of vetch in three levels, with local names, was the jewel in the study of light and Auxin in the vegetative and reproductive different times in different varieties of vetch was investigated. This test has been taken in the plots in a randomized complete block with four replications. In order to study the effects of the hormone Auxin in the growth stages (seed, vegetative and flowering) to control (no hormone Auxin) on three local varieties of vetch, the essence of light and plant height, number of pods per plant, seed number The pods, seeds per plant, grain weight, grain yield, plant dry weight and protein content were measured. Among the vetch varieties for plant height, number of pods per plant, a seed per plant, grain weight, grain yield, and plant dry weight and protein levels of 1 percent of plant and seed number per pod per plant at 5% level of There was no significant difference. Interactions for grain yield per plant, grain yield and protein levels of 1 percent and the number of seeds per pod and seed weight are significant differences in levels 5 and plant height and plant dry weight of the interaction were INFLUENCE There was no significant difference in them.

Keywords: Auxin hormones, various periods of growth, production components, vetch

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Authors: Sarabjeet Kaur Kochhar

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With a surge of stream processing applications novel techniques are required for generation and analysis of association rules in streams. The traditional rule mining solutions cannot handle streams because they generally require multiple passes over the data and do not guarantee the results in a predictable, small time. Though researchers have been proposing algorithms for generation of rules from streams, there has not been much focus on their analysis. We propose Association rule profiling, a user centric process for analyzing association rules and attaching suitable profiles to them depending on their changing frequency behavior over a previous snapshot of time in a data stream. Association rule profiles provide insights into the changing nature of associations and can be used to characterize the associations. We discuss importance of characteristics such as predictability of linkages present in the data and propose metric to quantify it. We also show how association rule profiles can aid in generation of user specific, more understandable and actionable rules. The framework is implemented as SUPAR: System for Usercentric Profiling of Association Rules in streaming data. The proposed system offers following capabilities: i) Continuous monitoring of frequency of streaming item-sets and detection of significant changes therein for association rule profiling. ii) Computation of metrics for quantifying predictability of associations present in the data. iii) User-centric control of the characterization process: user can control the framework through a) constraint specification and b) non-interesting rule elimination.

Keywords: Data Streams, User subjectivity, Change detection, Association rule profiles, Predictability.

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Authors: Toni Raurich, Joan Llonch-Andreu

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This research focused on the relationship between Search Engine Marketing (SEM) and traditional advertising. The dominant assumption is that SEM does not help brand awareness and only does it in session as if it were the cost of manufacturing the product being sold. The study is methodologically developed using an experiment where the effects were determined to analyze the billboard effect. The research allowed the cross-linking of theoretical and empirical knowledge on digital marketing. This paper has validated that, this marketing generates retention as traditional advertising would by measuring brand awareness and its improvements. This changes the way performance and brand campaigns are distributed within marketing departments, effectively rebalancing budgets moving forward.

Keywords: Search engine marketing, click-through ratios, pay-per-click, marketing attribution.

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Authors: P. Ashok, G. M. Kadhar Nawaz

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Rough set theory is used to handle uncertainty and incomplete information by applying two accurate sets, Lower approximation and Upper approximation. In this paper, the rough clustering algorithms are improved by adopting the Similarity, Dissimilarity–Similarity and Entropy based initial centroids selection method on three different clustering algorithms namely Entropy based Rough K-Means (ERKM), Similarity based Rough K-Means (SRKM) and Dissimilarity-Similarity based Rough K-Means (DSRKM) were developed and executed by yeast dataset. The rough clustering algorithms are validated by cluster validity indexes namely Rand and Adjusted Rand indexes. An experimental result shows that the ERKM clustering algorithm perform effectively and delivers better results than other clustering methods. Outlier detection is an important task in data mining and very much different from the rest of the objects in the clusters. Entropy based Rough Outlier Factor (EROF) method is seemly to detect outlier effectively for yeast dataset. In rough K-Means method, by tuning the epsilon (ᶓ) value from 0.8 to 1.08 can detect outliers on boundary region and the RKM algorithm delivers better results, when choosing the value of epsilon (ᶓ) in the specified range. An experimental result shows that the EROF method on clustering algorithm performed very well and suitable for detecting outlier effectively for all datasets. Further, experimental readings show that the ERKM clustering method outperformed the other methods.

Keywords: Clustering, Entropy, Outlier, Rough K-Means, validity index.

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Authors: M. İskefiyeli, İ. Özçelik

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PROFIBUS (PROcess FIeld BUS) which is defined with international standarts (IEC61158, EN50170) is the most popular fieldbus, and provides a communication between industrial applications which are located in different control environment and location in manufacturing, process and building automation. Its communication speed is from 9.6 Kbps to 12 Mbps over distances from 100 to 1200 meters, and so it is to be often necessary to interconnect them in order to break these limits. Unfortunately this interconnection raises several issues and the solutions found so far are not very satisfactory. In this paper, we propose a new solution to interconnect PROFIBUS segments, which uses a wireless MAN based on the IEEE 802.16 standard as a backbone system. Also, the solution which is described a model for internetworking unit integrates the traffic generated by PROFIBUS segments into IEEE 802.16 wireless MAN using encapsulation technique.

Keywords: Internetworking Unit, PROFIBUS, WiMAX, WMAN, 802.16.

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Authors: Peifei Zhu, Zisheng Li, Yasuki Kakishita, Mayumi Suzuki, Tomoaki Chono

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Segmentation of left ventricle (LV) from cardiac ultrasound images provides a quantitative functional analysis of the heart to diagnose disease. Active Shape Model (ASM) is widely used for LV segmentation, but it suffers from the drawback that initialization of the shape model is not sufficiently close to the target, especially when dealing with abnormal shapes in disease. In this work, a two-step framework is improved to achieve a fast and efficient LV segmentation. First, a robust and efficient detection based on Hough forest localizes cardiac feature points. Such feature points are used to predict the initial fitting of the LV shape model. Second, ASM is applied to further fit the LV shape model to the cardiac ultrasound image. With the robust initialization, ASM is able to achieve more accurate segmentation. The performance of the proposed method is evaluated on a dataset of 810 cardiac ultrasound images that are mostly abnormal shapes. This proposed method is compared with several combinations of ASM and existing initialization methods. Our experiment results demonstrate that accuracy of the proposed method for feature point detection for initialization was 40% higher than the existing methods. Moreover, the proposed method significantly reduces the number of necessary ASM fitting loops and thus speeds up the whole segmentation process. Therefore, the proposed method is able to achieve more accurate and efficient segmentation results and is applicable to unusual shapes of heart with cardiac diseases, such as left atrial enlargement.

Keywords: Hough forest, active shape model, segmentation, cardiac left ventricle.

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Authors: J. Schmidt, O. Kornadt

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The major part of light weight timber constructions consists of insulation. Mineral wool is the most commonly used insulation due to its cost efficiency and easy handling. The fiber orientation and porosity of this insulation material enables flowthrough. The air flow resistance is low. If leakage occurs in the insulated bay section, the convective flow may cause energy losses and infiltration of the exterior wall with moisture and particles. In particular the infiltrated moisture may lead to thermal bridges and growth of health endangering mould and mildew. In order to prevent this problem, different numerical calculation models have been developed. All models developed so far have a potential for completion. The implementation of the flow-through properties of mineral wool insulation may help to improve the existing models. Assuming that the real pressure difference between interior and exterior surface is larger than the prescribed pressure difference in the standard test procedure for mineral wool ISO 9053 / EN 29053, measurements were performed using the measurement setup for research on convective moisture transfer “MSRCMT". These measurements show, that structural inhomogeneities of mineral wool effect the permeability only at higher pressure differences, as applied in MSRCMT. Additional microscopic investigations show, that the location of a leak within the construction has a crucial influence on the air flow-through and the infiltration rate. The results clearly indicate that the empirical values for the acoustic resistance of mineral wool should not be used for the calculation of convective transfer mechanisms.

Keywords: convection, convective transfer, infiltration, mineralwool, permeability, resistance, leakage

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Authors: Andres Piña, Amy Meléndez, Pablo Cano, Tomas Cahuich

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The purpose of this project is to propose a quick and environmentally friendly alternative to measure the quality of oils used in food industry. There is evidence that repeated and indiscriminate use of oils in food processing cause physicochemical changes with formation of potentially toxic compounds that can affect the health of consumers and cause organoleptic changes. In order to assess the quality of oils, non-destructive optical techniques such as Interferometry offer a rapid alternative to the use of reagents, using only the interaction of light on the oil. Through this project, we used interferograms of samples of oil placed under different heating conditions to establish the changes in their quality. These interferograms were obtained by means of a Mach-Zehnder Interferometer using a beam of light from a HeNe laser of 10mW at 632.8nm. Each interferogram was captured, analyzed and measured full width at half-maximum (FWHM) using the software from Amcap and ImageJ. The total of FWHMs was organized in three groups. It was observed that the average obtained from each of the FWHMs of group A shows a behavior that is almost linear, therefore it is probable that the exposure time is not relevant when the oil is kept under constant temperature. Group B exhibits a slight exponential model when temperature raises between 373 K and 393 K. Results of the t-Student show a probability of 95% (0.05) of the existence of variation in the molecular composition of both samples. Furthermore, we found a correlation between the Iodine Indexes (Physicochemical Analysis) and the Interferograms (Optical Analysis) of group C. Based on these results, this project highlights the importance of the quality of the oils used in food industry and shows how Interferometry can be a useful tool for this purpose.

Keywords: Food industry, interferometric, oils, quality control.

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Authors: A. Badoud, M. Khemliche, S. Latreche

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The main objective developed in this paper is to find a graphic technique for modeling, simulation and diagnosis of the industrial systems. This importance is much apparent when it is about a complex system such as the nuclear reactor with pressurized water of several form with various several non-linearity and time scales. In this case the analytical approach is heavy and does not give a fast idea on the evolution of the system. The tool Bond Graph enabled us to transform the analytical model into graphic model and the software of simulation SYMBOLS 2000 specific to the Bond Graphs made it possible to validate and have the results given by the technical specifications. We introduce the analysis of the problem involved in the faults localization and identification in the complex industrial processes. We propose a method of fault detection applied to the diagnosis and to determine the gravity of a detected fault. We show the possibilities of application of the new diagnosis approaches to the complex system control. The industrial systems became increasingly complex with the faults diagnosis procedures in the physical systems prove to become very complex as soon as the systems considered are not elementary any more. Indeed, in front of this complexity, we chose to make recourse to Fault Detection and Isolation method (FDI) by the analysis of the problem of its control and to conceive a reliable system of diagnosis making it possible to apprehend the complex dynamic systems spatially distributed applied to the standard pressurized water nuclear reactor.

Keywords: Bond Graph, Modeling, Simulation, Monitoring, Analytical Redundancy Relations, Pressurized Water Reactor, Directed Graph.

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Authors: Bharadwaj Kadiyala, Sunitha V

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Most routing protocols (DSR, AODV etc.) that have been designed for wireless adhoc networks incorporate the broadcasting operation in their route discovery scheme. Probabilistic broadcasting techniques have been developed to optimize the broadcast operation which is otherwise very expensive in terms of the redundancy and the traffic it generates. In this paper we have explored percolation theory to gain a different perspective on probabilistic broadcasting schemes which have been actively researched in the recent years. This theory has helped us estimate the value of broadcast probability in a wireless adhoc network as a function of the size of the network. We also show that, operating at those optimal values of broadcast probability there is at least 25-30% reduction in packet regeneration during successful broadcasting.

Keywords: Crossover length, Percolation, Probabilistic broadcast, Wireless adhoc networks

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Authors: R. S. Fyath, Mustafa A. B. Al-Qadi

Abstract:

The inphase/quadrature (I/Q) amplitude and phase imbalance effects are studied in coherent optical orthogonal frequency division multiplexing (CO-OFDM) systems. An analytical model for the I/Q imbalance is developed and supported by simulation results. The results indicate that the I/Q imbalance degrades the BER performance considerably.

Keywords: Coherent detection, I/Q imbalance, OFDM, optical communications

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Authors: Rafsan Al Mamun, Md. Motaharul Islam, Rabana Tajrin, Nabiha Noor, Shafinaz Qader

Abstract:

In an attempt to enrich the lives of billions of people by providing proper information, security and a way of communicating with others, the need for efficient and improved satellites is constantly growing. Thus, there is an increasing demand for better error detection and correction (EDAC) schemes, which are capable of protecting the data onboard the satellites. The paper is aimed towards detecting and correcting such errors using a special algorithm called the Hamming Code, which uses the concept of parity and parity bits to prevent single-bit errors onboard a satellite in Low Earth Orbit. This paper focuses on the study of Low Earth Orbit satellites and the process of generating the Hamming Code matrix to be used for EDAC using computer programs. The most effective version of Hamming Code generated was the Hamming (16, 11, 4) version using MATLAB, and the paper compares this particular scheme with other EDAC mechanisms, including other versions of Hamming Codes and Cyclic Redundancy Check (CRC), and the limitations of this scheme. This particular version of the Hamming Code guarantees single-bit error corrections as well as double-bit error detections. Furthermore, this version of Hamming Code has proved to be fast with a checking time of 5.669 nanoseconds, that has a relatively higher code rate and lower bit overhead compared to the other versions and can detect a greater percentage of errors per length of code than other EDAC schemes with similar capabilities. In conclusion, with the proper implementation of the system, it is quite possible to ensure a relatively uncorrupted satellite storage system.

Keywords: Bit-flips, Hamming code, low earth orbit, parity bits, satellite, single error upset.

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Authors: Anamika Jain, A. S. Thoke, R. N. Patel

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This paper addresses the problems encountered by conventional distance relays when protecting double-circuit transmission lines. The problems arise principally as a result of the mutual coupling between the two circuits under different fault conditions; this mutual coupling is highly nonlinear in nature. An adaptive protection scheme is proposed for such lines based on application of artificial neural network (ANN). ANN has the ability to classify the nonlinear relationship between measured signals by identifying different patterns of the associated signals. One of the key points of the present work is that only current signals measured at local end have been used to detect and classify the faults in the double circuit transmission line with double end infeed. The adaptive protection scheme is tested under a specific fault type, but varying fault location, fault resistance, fault inception angle and with remote end infeed. An improved performance is experienced once the neural network is trained adequately, which performs precisely when faced with different system parameters and conditions. The entire test results clearly show that the fault is detected and classified within a quarter cycle; thus the proposed adaptive protection technique is well suited for double circuit transmission line fault detection & classification. Results of performance studies show that the proposed neural network-based module can improve the performance of conventional fault selection algorithms.

Keywords: Double circuit transmission line, Fault detection and classification, High impedance fault and Artificial Neural Network.

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Authors: Csaba I. Hencz, István Á. Harmati

Abstract:

Nowadays the significance of road transport is gradually increasing. All transport companies are working in the same external environment where the speed of transport is defined by traffic rules. The main objective is to accelerate the speed of service and it is only dependent on the individual abilities of the managing members. These operational control units make decisions quickly (in a typically experiential and/or intuitive way). For this reason, support for these decisions is an important task. Our goal is to create a decision support model based on fuzzy signatures that can assist the work of operational management automatically. If the model sets parameters properly, the management of transport could be more economical and efficient.

Keywords: Freight transport, decision support, information handling, fuzzy methods.

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Authors: Zonglin Yang, Tatsuya Akiyama, Kerry S. Williamson, Michael J. Franklin, Thiruvarangan Ramaraj

Abstract:

Pseudomonas aeruginosa is an opportunistic pathogen that forms surface-associated microbial communities (biofilms) on artificial implant devices and on human tissue. Biofilm infections are difficult to treat with antibiotics, in part, because the bacteria in biofilms are physiologically heterogeneous. One measure of biological heterogeneity in a population of cells is to quantify the cellular concentrations of ribosomes, which can be probed with fluorescently labeled nucleic acids. The fluorescent signal intensity following fluorescence in situ hybridization (FISH) analysis correlates to the cellular level of ribosomes. The goals here are to provide computationally and statistically robust approaches to automatically quantify cellular heterogeneity in biofilms from a large library of epifluorescent microscopy FISH images. In this work, the initial steps were developed toward these goals by developing an automated biofilm detection approach for use with FISH images. The approach allows rapid identification of biofilm regions from FISH images that are counterstained with fluorescent dyes. This methodology provides advances over other computational methods, allowing subtraction of spurious signals and non-biological fluorescent substrata. This method will be a robust and user-friendly approach which will enable users to semi-automatically detect biofilm boundaries and extract intensity values from fluorescent images for quantitative analysis of biofilm heterogeneity.

Keywords: Image informatics, Pseudomonas aeruginosa, biofilm, FISH, computer vision, data visualization.

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