Search results for: blue color detection

Authors: Samuel B. Dulay, Sandra Julich, Herbert Tomaso, Ciara K. O'Sullivan

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An early, rapid and definite detection for the presence of biowarfare agents, pathogens, viruses and toxins is required in different situations which include civil rescue and security units, homeland security, military operations, public transportation securities such as airports, metro and railway stations due to its harmful effect on the human population. In this work, an electrochemical genosensor array that allows simultaneous detection of different biowarfare agents within an integrated microsystem that provides an easy handling of the technology which combines a microfluidics setup with a multiplexing genosensor array has been developed and optimised for the following targets: Bacillus anthracis, Brucella abortis and melitensis, Bacteriophage lambda, Francisella tularensis, Burkholderia mallei and pseudomallei, Coxiella burnetii, Yersinia pestis, and Bacillus thuringiensis. The electrode array was modified via co-immobilisation of a 1:100 (mol/mol) mixture of a thiolated probe and an oligoethyleneglycol-terminated monopodal thiol. PCR products from these relevant biowarfare agents were detected reproducibly through a sandwich assay format with the target hybridised between a surface immobilised probe into the electrode and a horseradish peroxidase-labelled secondary reporter probe, which provided an enzyme based electrochemical signal. The potential of the designed microsystem for multiplexed genosensor detection and cross-reactivity studies over potential interfering DNA sequences has demonstrated high selectivity using the developed platform producing high-throughput.

Keywords: biowarfare agents, genosensors, multipled detection, microsystem

Procedia PDF Downloads 266

Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

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Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

Procedia PDF Downloads 267

Authors: Sakchai Satienperakul, Manoch Thanomwat, Jutiporn Seedasama

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A paper based analytical devices (PADs) for the analysis of Fe (III) ion in natural water samples is developed, using reagent from guava leaf extract. The extraction is simply performed in deionized water pH 7, where tannin extract is obtained and used as an alternative natural reagent. The PADs are fabricated by ink-jet printing using alkenyl ketene dimer (AKD) wax. The quantitation of Fe (III) is carried out using reagent from guava leaf extract prepared in acetate buffer at the ratio of 1:1. A color change to gray-purple is observed by naked eye when dropping sample contained Fe (III) ion on PADs channel. The reflective absorption measurement is performed for creating a standard curve. The linear calibration range is observed over the concentration range of 2-10 mg L-1. Detection limited of Fe (III) is observed at 2 mg L-1. In its optimum form, the PADs is stable for up to 30 days under oxygen free conditions. The small dimensions, low volume requirement and alternative natural reagent make the proposed PADs attractive for on-site environmental monitoring and analysis.

Keywords: green chemical analysis, guava leaf extract, lab on a chip, paper based analytical device

Procedia PDF Downloads 232

Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

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The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

Procedia PDF Downloads 306

Authors: Ifeoma Maryjane Iloamaeke, Kelvin Obazie, Mmesoma Offornze, Chiamaka Marysilvia Ifeaghalu, Cecilia Aduaka, Ugomma Chibuzo Onyeije, Claudine Ifunanaya Ogu, Ngozi Anastesia Okonkwo

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This work investigated the effects of pH, settling time, and coagulant dosages on the removal of color, turbidity, and heavy metals from paint industrial wastewater using the seed of Artocarpus heterophyllus (AH) by the coagulation-flocculation process. The paint effluent was physicochemically characterized, while AH coagulant was instrumentally characterized by Scanning Electron Microscope (SEM), Fourier Transform Infrared (FTIR), and X-ray diffraction (XRD). A Jar test experiment was used for the coagulation-flocculation process. The result showed that paint effluent was polluted with color, turbidity (36000 NTU), mercury (1.392 mg/L), lead (0.252 mg/L), arsenic (1.236 mg/L), TSS (63.40mg/L), and COD (121.70 mg/L). The maximum color removal efficiency was 94.33% at the dosage of 0.2 g/L, pH 2 at a constant time of 50 mins, and 74.67% at constant pH 2, coagulant dosage of 0.2 g/L and 50 mins. The highest turbidity removal efficiency was 99.94% at 0.2 g/L and 50 mins at constant pH 2 and 96.66% at pH 2 and 0.2 g/L at constant time of 50 mins. The mercury removal efficiency of 99.29% was achieved at the optimal condition of 0.8 g/L coagulant dosage, pH 8, and constant time of 50 mins and 99.57% at coagulant dosage of 0.8 g/L, time of 50 mins constant pH 8. The highest lead removal efficiency was 99.76% at a coagulant dosage of 10 g/L, time of 40 mins at constant pH 10, and 96.53% at pH 10, coagulant dosage of 10 g/L and constant time of 40 mins. For arsenic, the removal efficiency is 75.24 % at 0.8 g/L coagulant dosage, time of 40 mins, and constant pH of 8. XRD imaging before treatment showed that Artocarpus heterophyllus coagulant was crystalline and changed to amorphous after treatment. The SEM and FTIR results of the AH coagulant and sludge suggested there were changes in the surface morphology and functional groups before and after treatment. The reaction kinetics were modeled best in the second order.

Keywords: Artocarpus heterophyllus, coagulation-flocculation, coagulant dosages, setting time, paint effluent

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Authors: H. M. Wang, C. J. Chang

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As the threat of global climate change is more seriously, "net zero emissions by 2050" has become a common global goal. In order to reduce the consumption of petrochemical raw materials and reduce carbon emissions, low-carbon fiber materials have become key materials in the future global textile supply chain. This project uses polyolefin raw materials to modify through synthesis and amination to develop low-temperature dyeable polypropylene fibers, endow them with low-temperature dyeability and high color fastness that can be combined with acid dyes, and improve the problem of low coloring strength. The color fastness to washing can reach the requirement of commerce with 3.5 level or more. Therefore, we realize the entry of polypropylene fiber into the clothing textile supply chain, replace existing fiber raw materials, solve the problem of domestic chemical fiber, textile, and clothing industry's plight of no low-carbon alternative new material sources, and provide the textile industry with a solution to achieve the goal of net zero emissions in 2050.

Keywords: acid dyes, dyeing, low-temperature, polypropylene fiber

Procedia PDF Downloads 79

Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

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Authors: Muna F. Al-Sammaraie

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The aim of this research is to present a multi spectral image enhancement methods used to achieve highly real digital image populates only a small portion of the available range of digital values. Also, a quantitative measure of image enhancement is presented. This measure is related with concepts of the Webers Low of the human visual system. For decades, several image enhancement techniques have been proposed. Although most techniques require profuse amount of advance and critical steps, the result for the perceive image are not as satisfied. This study involves changing the original values so that more of the available range is used; then increases the contrast between features and their backgrounds. It consists of reading the binary image on the basis of pixels taking them byte-wise and displaying it, calculating the statistics of an image, automatically enhancing the color of the image based on statistics calculation using algorithms and working with RGB color bands. Finally, the enhanced image is displayed along with image histogram. A number of experimental results illustrated the performance of these algorithms. Particularly the quantitative measure has helped to select optimal processing parameters: the best parameters and transform.

Keywords: image enhancement, multi-spectral, RGB, histogram

Procedia PDF Downloads 322

Authors: Arwa Alzughaibi

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Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

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Authors: Pibool Waijittragum

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This paper has its objectives to reveal contents and personality suitable to women’s newspapers. The research methodology employed in this study is the questionnaire which is derived from a literature review related to newspapers, graphic elements method for print media design and 12 sample sizes of different daily newspapers. In order to acquire an in-depth understanding and comprehensible view of desirable for a women’s newspaper design, graphic elements that related to that personality as well as other preferable elements for a women’s newspaper, including seven editorial Many Thai newspapers were offer a women’s documentary and column space. With its feminine looks, most of them appeared with warm tones and friendly mood through their headlines, contents, illustrations and graphics. The study found that most desirable personalities for a women’s newspaper design in Thailand are: Modern, Chic and Natural. Each personality has significant graphic elements as follows: 1. Modern: significant elements of modern personality comprises of the composition with graduation pattern which creates attractiveness by using an anomalous alignment layout grid and outstanding structure to create focal points and dynamic movement. Dark to black color that has narrowed, limited hue coupled with bright color tones. The round shape of the Thai font style was suitable for this concept. Such Thai fonts have harmonious proportion and consistent stroke with the urban-polite look. 2. Chic: significant elements of chic personality comprises of the proper composition with distinctive scale, using rhythmic repetition and a contrast of scale to draw in reader attention. Vivid and bright color tones with extensive hues coupled with similar color tones and round shape of the Thai font style with a light stroke and consistent line. 3. Natural: significant elements of natural personality comprises of the proper composition using rhythmic repetition that creates a focal point through striking images and harmonious perspective. Warm color tones with restricted hues that appear to look natural. Duo tone color was suitable through the gradually increasing gradient. The Thai style with hand writing font was suitable through the inconsistent stroke. There are 10 types of daily content that were revealed to be the most desirable for Thai women readers, these are: Daily News, Economics News, Education News, Entertainment News, International news, Political News, Public Health News, Scientific News, Social News and Sports News. As well, there are 16 topics identified as very desirable for Thai women readers, such as: Art and Culture, Automobile, Classified, Special Scoop, Editorial, Advertisement, Entertainment, Health and Quality of Life, History, Horoscope, Lifestyle and Fashion, Literature, Nature - Environment and Tourism, Night Life, Stars and Jet Set Gossip, Women’s Issue.

Keywords: women behaviors, feminine looks, newspaper design, news content

Procedia PDF Downloads 157

Authors: Rabia Almas

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Today’s world is demanding natural and biological colorants on priority bases as an alternative to toxic and unsustainable synthetic dyes. Sustainable natural colors from plants and/or living organisms such as bacteria's and fungi attracted the world research scholars and textile industries recently due to the excitement and opportunities they covered. So, in the present study, natural colors from food waste, such as orange peels and peanuts, were extracted and applied to cotton fabric. The dyeing recipes were optimized in terms of dye concentration, processing temperature and time for higher color strength. The characterization of the dyes and fabric, such as Fourier transform infrared spectroscopy, Scanning Electron Microscopy, and fastness properties were measured for the identification of the chemical groups involved for a better understanding of the dyeing behavior. The results revealed that proper mordanting and concentration of dye on cotton fabric could give high color strength and good fastness to wash and light and these natural dyes can be used as an alternative to synthetic toxic colorants.

Keywords: textile, textile dyes, natural dyes, bio colors

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Authors: S. Korkut, M. S. Kilic, E. Erhan

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In order to detect and quantify the phenolic contents of a wastewater with biosensors, two working electrodes based on modified Poly (Pyrrole) films were fabricated. Enzyme horseradish peroxidase was used as biomolecule of the prepared electrodes. Various phenolics were tested at the biosensor. Phenol detection was realized by electrochemical reduction of quinones produced by enzymatic activity. Analytical parameters were calculated and the results were compared with each other.

Keywords: carbon nanotube, phenol biosensor, polypyrrole, poly (glutaraldehyde)

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Authors: Ki Moo Lim, Iman R. Tayibnapis

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According to WHO estimation, 38 out of 56 million (68%) global deaths in 2012, were due to noncommunicable diseases (NCDs). To avert NCD, one of the solutions is early detection of diseases. In order to do that, we developed 'U-Healthcare Mirror', which is able to measure vital sign such as heart rate (HR) and respiration rate without any physical contact and consciousness. To measure HR in the mirror, we utilized digital camera. The camera records red, green, and blue (RGB) discoloration from user's facial image sequences. We extracted blood volume pulse (BVP) from the RGB discoloration because the discoloration of the facial skin is accordance with BVP. We used blind source separation (BSS) to extract BVP from the RGB discoloration and adaptive filters for removing noises. We utilized singular value decomposition (SVD) method to implement the BSS and the adaptive filters. HR was estimated from the obtained BVP. We did experiment for HR measurement by using our method and previous method that used independent component analysis (ICA) method. We compared both of them with HR measurement from commercial oximeter. The experiment was conducted under various distance between 30~110 cm and light intensity between 5~2000 lux. For each condition, we did measurement 7 times. The estimated HR showed 2.25 bpm of mean error and 0.73 of pearson correlation coefficient. The accuracy has improved compared to previous work. The optimal distance between the mirror and user for HR measurement was 50 cm with medium light intensity, around 550 lux.

Keywords: blood volume pulse, heart rate, photoplethysmography, independent component analysis

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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 MRImages, multi-agent systems, vector field convolution

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Authors: Retno Supriyanti, Ahmad Chuzaeri, Yogi Ramadhani, A. Haris Budi Widodo

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The use of ultrasonography in the medical world has been very popular including the diagnosis of pregnancy. In determining pregnancy, ultrasonography has many roles, such as to check the position of the fetus, abnormal pregnancy, fetal age and others. Unfortunately, all these things still need to analyze the role of the obstetrician in the sense of image raised by ultrasonography. One of the most striking is the determination of gestational age. Usually, it is done by measuring the length of the fetus manually by obstetricians. In this study, we developed a computer-aided diagnosis for the determination of gestational age by measuring the length of the fetus automatically using edge detection method and image morphology. Results showed that the system is sufficiently accurate in determining the gestational age based image processing.

Keywords: computer aided diagnosis, gestational age, and diameter of uterus, length of fetus, edge detection method, morphology image

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Authors: Alden Boby, Dane Brown, James Connan

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Character recognition is a well-researched topic across disciplines. Regardless, creating a solution that can cater to multiple situations is still challenging. Vehicle licence plates lack an international standard, meaning that different countries and regions have their own licence plate format. A problem that arises from this is that the typefaces and designs from different regions make it difficult to create a solution that can cater to a wide range of licence plates. The main issue concerning detection is the character recognition stage. This paper aims to create an object detection-based character recognition model trained on a custom dataset that consists of typefaces of licence plates from various regions. Given that characters have featured consistently maintained across an array of fonts, YOLO can be trained to recognise characters based on these features, which may provide better performance than OCR methods such as Tesseract OCR.

Keywords: computer vision, character recognition, licence plate recognition, object detection

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

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With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

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Authors: Jooyoung Park, Junkyeong Kim, Aoqi Zhang, Seunghee Park

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Non-destructive testing on cable is in great demand due to safety accidents at sites where many equipments using cables are installed. In this paper, the quantitative change of the obtained signal was analyzed using a magnetic flux leakage (MFL) method. A two-dimensional simulation was conducted with a FEM model replicating real elevator cables. The simulation data were compared for three parameters (depth of defect, width of defect and inspection velocity). Then, an experiment on same conditions was carried out to verify the results of the simulation. Signals obtained from both the simulation and the experiment were transformed to characterize the properties of the damage. Throughout the results, a cable damage detection based on an MFL method was confirmed to be feasible. In further study, it is expected that the MFL signals of an entire specimen will be gained and visualized as well.

Keywords: magnetic flux leakage (mfl), cable damage detection, non-destructive testing, numerical simulation

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Authors: Sunil Mittal, Sukhpreet Singh, Hardeep Kaur

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The affinity of thiol group with heavy metals is a well-established phenomenon. The present investigation has been focused on electrochemical response of cysteine and thioredoxin against arsenite (As III) on indium tin oxide (ITO) electrodes. It was observed that both the compounds produce distinct response in free and immobilised form at the electrode. The SEM, FTIR, and impedance studies of the modified electrode were conducted for characterization. Various parameters were optimized to achieve As (III) effect on the reduction potential of the compounds. Cyclic voltammetry and linear sweep voltammetry were employed as the analysis techniques. The optimum response was observed at neutral pH in both the cases, at optimum concentration of 2 mM and 4.27 µM for cysteine and thioredoxin respectively. It was observed that presence of As (III) increases the reduction current of both the moieties. The linear range of detection for As (III) with cysteine was from 1 to 10 mg L⁻¹ with detection limit of 0.8 mg L⁻¹. The thioredoxin was found more sensitive to As (III) and displayed a linear range from 0.1 to 1 mg L⁻¹ with detection limit of 10 µg L⁻¹.

Keywords: arsenite, cyclic voltammetry, cysteine, thioredoxin

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Authors: M. R. Ghasemi, R. Ghiasi, H. Varaee

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Model updating method has received increasing attention in damage detection structures based on measured modal parameters. Therefore, a probability-based damage detection (PBDD) procedure based on a model updating procedure is presented in this paper, in which a one-stage model-based damage identification technique based on the dynamic features of a structure is investigated. The presented framework uses a finite element updating method with a Monte Carlo simulation that considers the uncertainty caused by measurement noise. Enhanced ideal gas molecular movement (EIGMM) is used as the main algorithm for model updating. Ideal gas molecular movement (IGMM) is a multiagent algorithm based on the ideal gas molecular movement. Ideal gas molecules disperse rapidly in different directions and cover all the space inside. This is embedded in the high speed of molecules, collisions between them and with the surrounding barriers. In IGMM algorithm to accomplish the optimal solutions, the initial population of gas molecules is randomly generated and the governing equations related to the velocity of gas molecules and collisions between those are utilized. In this paper, an enhanced version of IGMM, which removes unchanged variables after specified iterations, is developed. The proposed method is implemented on two numerical examples in the field of structural damage detection. The results show that the proposed method can perform well and competitive in PBDD of structures.

Keywords: enhanced ideal gas molecular movement (EIGMM), ideal gas molecular movement (IGMM), model updating method, probability-based damage detection (PBDD), uncertainty quantification

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Authors: Fariha Akhter Chowdhury, Mohammad Nurul Islam, Anamika Saha, Sabrina Mahboob, Abu Syed Md. Mosaddek, Md. Omar Faruque, Most. Fahmida Begum, Rajib Bhattacharjee

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Urinary tract infection (UTI) is one of the most common infectious diseases in Bangladesh where Escherichia coli is the prevalent organism and responsible for most of the infections. Lipopolysaccharide (LPS) is known to act as a major virulence factor of E. coli. The present study aimed to purify, extract and visualize LPS of E. coli clinical isolates from urine samples of patients with UTI. The E. coli strain was isolated from the urine samples of 10 patients with UTI and then the antibiotic sensitivity pattern of the isolates was determined. The purification of LPS was carried out using the hot aqueous-phenol method and separated by sodium dodecyl sulfate polyacrylamide gel electrophoresis, which was directly stained using the modified silver staining method and Coomassie blue. The silver-stained gel demonstrated both smooth and rough type LPS by showing trail-like band patterns with the presence and lacking O-antigen region, respectively. Coomassie blue staining showed no band assuring the absence of any contaminating protein. Our successful extraction of purified LPS from E. coli isolates of UTI patients’ urine samples can be an important step to understand the UTI disease conditions.

Keywords: Escherichia coli, electrophoresis, polyacrylamide gel, silver staining, sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE)

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Authors: Shang-Yu Chiang, Yu-Shan Tsai, Shih-Hsien Sung, Chung-Ming Lo

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Mitral regurgitation (MR) is a heart disorder which the mitral valve does not close properly when the heart pumps out blood. MR is the most common form of valvular heart disease in the adult population. The diagnostic echocardiographic finding of MR is straightforward due to the well-known clinical evidence. In the determination of MR severity, quantification of sonographic findings would be useful for clinical decision making. Clinically, the vena contracta is a standard for MR evaluation. Vena contracta is the point in a blood stream where the diameter of the stream is the least, and the velocity is the maximum. The quantification of vena contracta, i.e. the vena contracta width (VCW) at mitral valve, can be a numeric measurement for severity assessment. However, manually delineating the VCW may not accurate enough. The result highly depends on the operator experience. Therefore, this study proposed an automatic method to quantify VCW to evaluate MR severity. Based on color Doppler ultrasound, VCW can be observed from the blood flows to the probe as the appearance of red or yellow area. The corresponding brightness represents the value of the flow rate. In the experiment, colors were firstly transformed into HSV (hue, saturation and value) to be closely align with the way human vision perceives red and yellow. Using ellipse to fit the high flow rate area in left atrium, the angle between the mitral valve and the ultrasound probe was calculated to get the vertical shortest diameter as the VCW. Taking the manual measurement as the standard, the method achieved only 0.02 (0.38 vs. 0.36) to 0.03 (0.42 vs. 0.45) cm differences. The result showed that the proposed automatic VCW extraction can be efficient and accurate for clinical use. The process also has the potential to reduce intra- or inter-observer variability at measuring subtle distances.

Keywords: mitral regurgitation, vena contracta, color doppler, image processing

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Authors: Hamidullah Binol, Abdullah Bal

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Nowadays, food safety is a great public concern; therefore, robust and effective techniques are required for detecting the safety situation of goods. Hyperspectral Imaging (HSI) is an attractive material for researchers to inspect food quality and safety estimation such as meat quality assessment, automated poultry carcass inspection, quality evaluation of fish, bruise detection of apples, quality analysis and grading of citrus fruits, bruise detection of strawberry, visualization of sugar distribution of melons, measuring ripening of tomatoes, defect detection of pickling cucumber, and classification of wheat kernels. HSI can be used to concurrently collect large amounts of spatial and spectral data on the objects being observed. This technique yields with exceptional detection skills, which otherwise cannot be achieved with either imaging or spectroscopy alone. This paper presents a nonlinear technique based on kernel Fukunaga-Koontz transform (KFKT) for detection of fat content in ground meat using HSI. The KFKT which is the nonlinear version of FKT is one of the most effective techniques for solving problems involving two-pattern nature. The conventional FKT method has been improved with kernel machines for increasing the nonlinear discrimination ability and capturing higher order of statistics of data. The proposed approach in this paper aims to segment the fat content of the ground meat by regarding the fat as target class which is tried to be separated from the remaining classes (as clutter). We have applied the KFKT on visible and nearinfrared (VNIR) hyperspectral images of ground meat to determine fat percentage. The experimental studies indicate that the proposed technique produces high detection performance for fat ratio in ground meat.

Keywords: food (ground meat) inspection, Fukunaga-Koontz transform, hyperspectral imaging, kernel methods

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Authors: Jyoti Kumari, Pavuluri Srinivasa Rao

Abstract:

Jackfruit (ArtocarpusheterophyllusL.) is an underutilized yet highly nutritious fruit with unique flavour, known for its therapeutic and culinary properties. Fresh jackfruit bulb has a very short shelf life due to high moisture and sugar content leading to microbial and enzymatic browning, hindering its consumer acceptability and marketability. An attempt has been made for the preservation of the ripe jackfruit bulbs, by the application of high pressure (HP) over a range of 200-500 MPa at ambient temperature for dwell times ranging from 5 to 20 min. The physicochemical properties of jackfruit bulbs such as the pH, TSS, and titrable acidity were not affected by the pressurization process. The ripening index of the fruit bulb also decreased following HP treatment. While the ascorbic acid and antioxidant activity of jackfruit bulb were well retained by high pressure processing (HPP), the total phenols and carotenoids showed a slight increase. The HPP significantly affected the colour and textural properties of jackfruit bulb. High pressure processing was highly effective in reducing the browning index of jackfruit bulbs in comparison to untreated bulbs. The firmness of the bulbs improved upon the pressure treatment with longer dwelling time. The polyphenol oxidase has been identified as the most prominent oxidative enzyme in the jackfruit bulb. The enzymatic activity of polyphenol oxidase and peroxidase were significantly reduced by up to 40% following treatment at 400 MPa/15 min. HPP of jackfruit bulbs at ambient temperatures is shown to be highly beneficial in improving the shelf stability, retaining its nutrient profile, color, and appearance while ensuring the maximum inactivation of the spoilage enzymes.

Keywords: antioxidant capacity, ascorbic acid, carotenoids, color, HPP-high pressure processing, jackfruit bulbs, polyphenol oxidase, peroxidase, total phenolic content

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Authors: Aymen Sekhri, Emmanuel Kwabena Frimpong, Bolaji Mubarak Ayeyemi, Aleksi Hirvonen, Matias Hirvonen, Tedros Tesfay Andemichael

Abstract:

Fixation identification, which involves isolating and identifying fixations and saccades in eye-tracking protocols, is an important aspect of eye-movement data processing that can have a big impact on higher-level analyses. However, fixation identification techniques are frequently discussed informally and rarely compared in any meaningful way. With two state-of-the-art algorithms, we will implement fixation detection and analysis in this work. The velocity threshold fixation algorithm is the first algorithm, and it identifies fixation based on a threshold value. For eye movement detection, the second approach is U'n' Eye, a deep neural network algorithm. The goal of this project is to analyze and visualize eye-tracking data from an eye gaze dataset that has been provided. The data was collected in a scenario in which individuals were shown photos and asked whether or not they recognized them. The results of the two-fixation detection approach are contrasted and visualized in this paper.

Keywords: human-computer interaction, eye-tracking, CNN, fixations, saccades

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Authors: Reza Sadeghi

Abstract:

In this study, microwave heating was employed for controlling Oryzaephilus mercator. adults infesting stored Iranian dried fig. For this purpose, the dried fig samples were artificially infested with O. mercator and then heated in a microwave oven (2450 MHz) at the power outputs of 450, 720, and 900 W for 10, 20, 30, and 40 s, respectively. Subsequently, changes in the colors of the product samples under the effects of the varied microwave applications were investigated in terms of lightness (ΔL*), redness (Δa*), and yellowness (Δb*) using an image processing technique. The results revealed that both parameters of microwave power and exposure time had significant impacts on the pest mortality rates (p<0.01). In fact, a direct positive relationship was obtained between the mortality rate and microwave irradiation power. Complete mortality was achieved for the pest at the power of 900 W and exposure time of 40 s. The dried fig samples experienced fewer changes in their color parameters. Considering the successful pest control and acceptable changes in the product quality, microwave irradiation can be introduced as an appropriate alternative to chemical fumigants.

Keywords: colorimetric assay, microwave heating, Oryzaephilus mercator, mortality

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Authors: Ana M. T. Mata, Alexiane Ligneul

Abstract:

Textile effluents are usually heavily loaded with organic carbon and color compounds, the latter being azo dyes in an estimated 70% of the case effluent posing a major challenge in environmental protection. In this study, the ecotoxicity of simulated textile effluent after biological treatment with anaerobic and aerobic phase (aerobic granular sludge, AGS) and after advanced oxidation processes (AOP) namely ozonation and UV irradiation as post-treatment, were tested to evaluate the fitness of this treatments for ecotoxicity abatement. AGS treatment achieved an 80% removal in both COD and color. AOP was applied with the intention to mineralize the metabolites resulting from biodecolorization of the azo dye Acid Red 14, especially the stable aromatic amine (4-amino-1-naphthalenesulfonic acid, 4A1NS). The ecotoxicity evaluation was based on growth inhibition of the algae Pseudokirchneriella subcapitata following OECD TG 201 except regarding the medium, MBL medium was used instead. Five replicate control cultures and samples were performed with an average STD of 2.7% regarding specific algae growth rate determination. It was found that untreated textile effluent holds an inhibition of specific growth rate of 82%. AGS treatment by itself is able to lower ecotoxicity to 53%. This is probably due to the high color removal of the treatment. AOP post-treatment with Ozone and UV irradiation improves the ecotoxicity abatment to 49 and 43% inhibition respectively, less significantly than previously thought. Since over 85% of 4A1NS was removed by either of the AOP (followed by HPLC), an individual ecotoxicity test of 4A1NS was performed showing that 4A1NS does not inhibit algae growth (0% inhibition). It was concluded that AGS treatment is able by itself to achieve a significant ecotoxicity abatement of textile effluent. The cost-benefit of AOP as a post-treatment have to be better accessed since their application resulted in an improvement of only 10% regarding ecotoxicity effluent removal. It was also found that the 4A1NS amine had no apparent effect on ecotoxicity. Further studies will be conducted to study where ecotoxicity is coming from after AGS biological treatment and how to eliminate it.

Keywords: textile wastewate, ecotoxicity, aerobic granular sludge, AOP

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Authors: Bopit Puyati, Anchittha Kaewchana, Nuntita Ruksachat

Abstract:

In January 2018, a male wild elephant, approximately 2 years old, was found dead in Phu Luang Wildlife Sanctuary, Loei province. The elephant was likely to die around 2 weeks earlier. The carcass was decayed without any signs of attack or bullet. No organs were removed. A deadly viral disease was suspected. Different organs including lung, liver, intestine and tongue were collected and submitted to the veterinary research and development center, Surin province for viral detection. The samples were then examined with real-time PCR for detecting U41 Major DNA binding protein (MDBP) gene and with conventional PCR for the presence of specific polymerase gene. We used tumor necrosis factor (TNF) gene as the internal control. In our real-time PCR, elephant endotheliotropic herpesvirus (EEHV) was recovered from lung, liver, and tongue whereas only tongue provided a positive result in the conventional PCR. All samples were positive with TNF gene detection. To our knowledge, this is the first report of EEHV detection in wild elephant in Thailand. EEHV surveillance in this wild population is strongly suggested. Linkage between EEHV in wild and domestic elephants should be further explored.

Keywords: elephant endotheliotropic herpes virus, PCR, Thailand, wild Asian elephant

Procedia PDF Downloads 133

Authors: Ying Li, Rui Hu, Shizhen Chen, Xin Zhou, Yunhuang Yang

Abstract:

Prostate cancer is one of the leading causes of cancer-related death among men. Prostate-specific antigen (PSA), a specific product of prostatic epithelial cells, is an important indicator of prostate cancer. Though PSA is not a specific serum biomarker for the screening of prostate cancer, it is recognized as an indicator for prostate cancer recurrence and response to therapy for patient’s post-prostatectomy. Since radical prostatectomy eliminates the source of PSA production, serum PSA levels fall below 50 pg/mL, and may be below the detection limit of clinical immunoassays (current clinical immunoassay lower limit of detection is around 10 pg/mL). Many clinical studies have shown that intervention at low PSA levels was able to improve patient outcomes significantly. Therefore, ultra-sensitive and precise assays that can accurately quantify extremely low levels of PSA (below 1-10 pg/mL) will facilitate the assessment of patients for the possibility of early adjuvant or salvage treatment. Currently, the commercially available ultra-sensitive ELISA kit (not used clinically) can only reach a detection limit of 3-10 pg/mL. Other platforms developed by different research groups could achieve a detection limit as low as 0.33 pg/mL, but they relied on sophisticated instruments to get the final readout. Herein we report a microfluidic platform for point-of-care (POC) detection of PSA with a detection limit of 0.5 pg/mL and without the assistance of any equipment. This platform is based on a previously reported volumetric-bar-chart chip (V-Chip), which applies platinum nanoparticles (PtNPs) as the ELISA probe to convert the biomarker concentration to the volume of oxygen gas that further pushes the red ink to form a visualized bar-chart. The length of each bar is used to quantify the biomarker concentration of each sample. We devised a long reading channel V-Chip (LV-Chip) in this work to achieve a wide detection window. In addition, LV-Chip employed a unique enzyme-free ELISA probe that enriched PtNPs significantly and owned 500-fold enhanced catalytic ability over that of previous V-Chip, resulting in a significantly improved detection limit. LV-Chip is able to complete a PSA assay for five samples in 20 min. The device was applied to detect PSA in 50 patient serum samples, and the on-chip results demonstrated good correlation with conventional immunoassay. In addition, the PSA levels in finger-prick whole blood samples from healthy volunteers were successfully measured on the device. This completely stand-alone LV-Chip platform enables convenient POC testing for patient follow-up in the physician’s office and is also useful in resource-constrained settings.

Keywords: point-of-care detection, microfluidics, PSA, ultra-sensitive

Procedia PDF Downloads 102