Search results for: fault detection and recovery

Authors: Laxman H. Surwase, Lalit V. Sonawane, Bhagwat N. Poul

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A simple stability indicating high performance liquid chromatographic method has been developed for the simultaneous determination of Levosalbutamol Sulphate and Ipratropium Bromide in bulk and pharmaceutical dosage form using reverse phase Zorbax Eclipse Plus C8 column (250mm×4.6mm), with mobile phase phosphate buffer (0.05M KH2PO4): acetonitrile (55:45v/v) pH 3.5 adjusted with ortho-phosphoric acid, the flow rate was 1.0 mL/min and the detection was carried at 212 nm. The retention times of Levosalbutamol Sulphate and Ipratropium Bromide were 2.2007 and 2.6611 min respectively. The correlation coefficient of Levosalbutamol Sulphate and Ipratropium Bromide was found to be 0.997 and 0.998.Calibration plots were linear over the concentration ranges 10-100µg/mL for both Levosalbutamol Sulphate and Ipratropium Bromide. The LOD and LOQ of Levosalbutamol Sulphate were 2.520µg/mL and 7.638µg/mL while for Ipratropium Bromide was 1.201µg/mL and 3.640 µg/mL. The accuracy of the proposed method was determined by recovery studies and found to be 100.15% for Levosalbutamol Sulphate and 100.19% for Ipratropium Bromide respectively. The method was validated for accuracy, linearity, sensitivity, precision, robustness, system suitability. The proposed method could be utilized for routine analysis of Levosalbutamol Sulphate and Ipratropium Bromide in bulk and pharmaceutical capsule dosage form.

Keywords: levosalbutamol sulphate, ipratropium bromide, RP-HPLC, phosphate buffer, acetonitrile

Procedia PDF Downloads 352

Authors: Tae-Uk Yun, Pullip Chung, Kee-Young Kwahk, Hyunchul Ahn

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Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection using machine learning techniques over the past years. But, there have been no prior studies proposed an automated fake news detection method for Korean news to our best knowledge. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (topic modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as logistic regression, backpropagation network, support vector machine, and deep neural network can be applied. To validate the effectiveness of the proposed method, we collected about 200 short Korean news from Seoul National University’s FactCheck. which provides with detailed analysis reports from 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

Keywords: fake news detection, Korean news, machine learning, text mining

Procedia PDF Downloads 279

Authors: Bhuyain Mobarok Hossain

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Image classification and localization research is currently an important strategy in the field of computer vision. The evolution and advancement of deep learning and convolutional neural networks (CNN) have greatly improved the capabilities of object detection and image-based classification. Target detection is important to research in the field of computer vision, especially in video surveillance systems. To solve this problem, we will be applying a convolutional neural network of multiple scales at multiple locations in the image in one sliding window. Most translation networks move away from the bounding box around the area of interest. In contrast to this architecture, we consider the problem to be a classification problem where each pixel of the image is a separate section. Image classification is the method of predicting an individual category or specifying by a shoal of data points. Image classification is a part of the classification problem, including any labels throughout the image. The image can be classified as a day or night shot. Or, likewise, images of cars and motorbikes will be automatically placed in their collection. The deep learning of image classification generally includes convolutional layers; the invention of it is referred to as a convolutional neural network (CNN).

Keywords: image classification, object detection, localization, particle filter

Procedia PDF Downloads 313

Authors: Koichi Kurita

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In this study, an effective non-contact technique for the detection of human physical activity is proposed. The technique is based on detecting the electrostatic induction current generated by the walking motion under non-contact and non-attached conditions. A theoretical model for the electrostatic induction current generated because of a change in the electric potential of the human body is proposed. By comparing the obtained electrostatic induction current with the theoretical model, it becomes obvious that this model effectively explains the behavior of the waveform of the electrostatic induction current. The normal walking motions are recorded using a portable sensor measurement located in a passageway　of office building. The obtained results show that detailed information regarding physical activity such as a walking cycle can be estimated using our proposed technique. This suggests that the proposed technique which is based on the detection of the walking signal, can be successfully applied to the detection of human walking motion in a secured building.

Keywords: human walking motion, access control, electrostatic induction, alarm monitoring

Procedia PDF Downloads 360

Authors: H. Al-Baghli

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Laboratory trial results of mixing crumb rubber produced from discarded tires with 60/70 pen grade Kuwaiti bitumen are presented on this paper. PG grading and multiple stress creep recovery tests were conducted on Kuwaiti bitumen blended with 15% and 18% crumb rubber at temperatures ranging from 40 to 70 °C. The results from elastic recovery and non-recoverable creep presented optimum performance at 18% rubber content. The optimum rubberized-bitumen mix was next transformed into a pelletized form (PelletPave^®), and was used as a partial replacement to the conventional bitumen in the manufacture of continuously graded hot mix asphalts at a number of binder contents. The trialed PelletPave^® contents were at 2.5%, 3.0%, and 3.5% by mass of asphalt mix. In this investigation, it was not possible to utilize the results of standard Marshall method of mix design (i.e. volumetric, stability and flow tests) and subsequently additional assessment of mix compactability was carried out using gyratory compactor in order to determine the optimum PelletPave^® and total binder contents.

Keywords: crumb rubber, Marshall mix design, PG grading, rubberized-bitumen

Procedia PDF Downloads 224

Authors: S. M. Amin Hosseini, Oriol Pons, Albert de la Fuente

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An earthquake hit the Kermanshah province, which is located in the west of Iran, on 12th November 2017 at 18:18 UTC (21:48 Iran Standard Time). This earthquake caused several deaths and injured people. In this disaster, substantial homes were destroyed and many homes were damaged. The Iranian government, local authorities, and several non-governmental organizations responded to affected populations’ needs, such as foods, blanket, water, a tent as a temporary shelter, etc. Considerable national groups, including governmental, non-governmental organizations, and people from non-organized groups, directly and indirectly, tried to bring donated goods to the affected populations. However, some of these aids could not satisfy all the affected populations. Moreover, these impossibilities led to waste extensive resources. In this regard, this research study aims to assess the problems of the Kermanshah disaster responses. At the same time, this project searches possible solutions in order to increase emergency management efficiencies for encountering future events. To this end, this study assesses the problem from all beneficiaries´ point of views. In this regard, a survey and a questionnaire were designed for statistical analyses of the responses of people, who were involved in the Kermanshah earthquake recovery program. Additionally, this research study takes into account diverse strategies, which have been applied in other recovery programs, with the Kermanshah case in order to determine similarities and differences. Finally, this study presents possible solutions taken from other recovery programs that could be applied for the Kermanshah emergency responses. However, the results demonstrate that it is required to customize applied strategies based on local conditions and requirements.

Keywords: disaster response, Kermanshah earthquake, natural disasters, NGOs

Procedia PDF Downloads 173

Authors: Isil Gazioglu, Abdulselam Ertas

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Aflatoxins (AFs) are secondary toxic metabolites of Aspergillus flavus and A. parasiticus. AFs can be absorbed through the skin. Potent carcinogens like AFs should be completely absent from cosmetics, this can be achieved by careful quality control of the raw plant materials. Regulatory limits for aflatoxins have been established in many countries, and reliable testing methodology is needed to implement and enforce the regulatory limits. In this study, ten medicinal plant samples (Bundelia tournefortti, Capsella bursa-pastoris, Carduus tenuiflorus, Cardaria draba, Malva neglecta, Malvella sharardiana, Melissa officinalis, Sideritis libanotica, Stakys thirkei, Thymus nummularius) were investigated for aflatoxin (AF) contaminations by employing an HPLC assay for the determination of AFB1, B2, G1 and G2. The samples were extracted with 70% (v/v) methanol in water before further cleaned up with an immunoaffinity column and followed by the detection of AFs by using an electrochemically post-column derivatization with Kobra-Cell and fluorescence detector. The extraction procedure was optimized in order to obtain the best recovery. The method was successfully carried out with all medicinal plant samples. The results revealed that five (50%) of samples were contaminated with AFs. The association between particular samples and the AF contaminated could not be determined due to the low frequency of positive samples.

Keywords: aflatoxin B1, HPLC-FLD, KOBRA-Cell, mycotoxin

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Authors: Delphine Vendryes, Dushyanth Sekhar, Baojia Tong, Matthew Theisen, Chester Curme

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Much of the data that inform the decisions of governments, corporations and individuals are harvested from unstructured documents. Data extraction is defined here as a process that turns non-machine-readable information into a machine-readable format that can be stored, for instance, in a database. In financial services, introducing more automation in data extraction pipelines is a major challenge. Information sought by financial data consumers is often buried within vast bodies of unstructured documents, which have historically required thorough manual extraction. Automated solutions provide faster access to non-machine-readable datasets, in a context where untimely information quickly becomes irrelevant. Data quality standards cannot be compromised, so automation requires high data integrity. This multifaceted task is broken down into smaller steps: ingestion, table parsing (detection and structure recognition), text analysis (entity detection and disambiguation), schema-based record extraction, user feedback incorporation. Selected intermediary steps are phrased as machine learning problems. Solutions leveraging cutting-edge approaches from the fields of computer vision (e.g. table detection) and natural language processing (e.g. entity detection and disambiguation) are proposed.

Keywords: computer vision, entity recognition, finance, information retrieval, machine learning, natural language processing

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Authors: Bilal Saoud

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In this paper, we propose a new method to find the community structure in networks. Our method is based on bee colony and the maximization of modularity to find the community structure. We use a bee colony algorithm to find the first community structure that has a good value of modularity. To improve the community structure, that was found, we merge communities until we get a community structure that has a high value of modularity. We provide a general framework for implementing our approach. We tested our method on computer-generated and real-world networks with a comparison to very known community detection methods. The obtained results show the effectiveness of our proposition.

Keywords: bee colony, networks, modularity, normalized mutual information

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Authors: Arth J. Shah, Madhu R. Kamble

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Voice biometric liveness detection is customized to certify an authentication process of the voice data presented is genuine and not a recording or synthetic voice. With the rise of deepfakes and other equivalently sophisticated spoofing generation techniques, it’s becoming challenging to ensure that the person on the other end is a live speaker or not. Voice Liveness Detection (VLD) system is a group of security measures which detect and prevent voice spoofing attacks. Motivated by the recent development of the Kolmogorov-Arnold Network (KAN) based on the Kolmogorov-Arnold theorem, we proposed KAN for the VLD task. To date, multilayer perceptron (MLP) based classifiers have been used for the classification tasks. We aim to capture not only the compositional structure of the model but also to optimize the values of univariate functions. This study explains the mathematical as well as experimental analysis of KAN for VLD tasks, thereby opening a new perspective for scientists to work on speech and signal processing-based tasks. This study emerges as a combination of traditional signal processing tasks and new deep learning models, which further proved to be a better combination for VLD tasks. The experiments are performed on the POCO and ASVSpoof 2017 V2 database. We used Constant Q-transform, Mel, and short-time Fourier transform (STFT) based front-end features and used CNN, BiLSTM, and KAN as back-end classifiers. The best accuracy is 91.26 % on the POCO database using STFT features with the KAN classifier. In the ASVSpoof 2017 V2 database, the lowest EER we obtained was 26.42 %, using CQT features and KAN as a classifier.

Keywords: Kolmogorov Arnold networks, multilayer perceptron, pop noise, voice liveness detection

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Authors: Bina Gupta, Rashmi Singh, Harshit Mahandra

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Molybdenum is a strategic metal and finds applications in petroleum refining, thermocouples, X-ray tubes and in making of steel alloy owing to its high melting temperature and tensile strength. The growing significance and economic value of molybdenum have increased interest in the development of efficient processes aiming its recovery from secondary sources. Main secondary sources of Mo are molybdenum catalysts which are used for hydrodesulphurisation process in petrochemical refineries. The activity of these catalysts gradually decreases with time during the desulphurisation process as the catalysts get contaminated with toxic material and are dumped as waste which leads to environmental issues. In this scenario, recovery of molybdenum from spent catalyst is significant from both economic and environmental point of view. Recently ionic liquids have gained prominence due to their low vapour pressure, high thermal stability, good extraction efficiency and recycling capacity. Present study reports recovery of molybdenum from Mo-Co spent leach liquor using Cyphos IL 102[trihexyl(tetradecyl)phosphonium bromide] as an extractant. Spent catalyst was leached with 3 mol/L HCl and the leach liquor containing Mo-870 ppm, Co-341 ppm, Al-508 ppm and Fe-42 ppm was subjected to extraction step. The effect of extractant concentration on the leach liquor was investigated and almost 85% extraction of Mo was achieved with 0.05 mol/L Cyphos IL 102. Results of stripping studies revealed that 2 mol/L HNO3 can effectively strip 94% of the extracted Mo from the loaded organic phase. McCabe-Thiele diagrams were constructed to determine the number of stages required for quantitative extraction and stripping of molybdenum and were confirmed by counter current simulation studies. According to McCabe-Thiele extraction and stripping isotherms, two stages are required for quantitative extraction and stripping of molybdenum at A/O= 1:1. Around 95.4% extraction of molybdenum was achieved in two stage counter current at A/O= 1:1 with negligible extraction of Co and Al. However, iron was coextracted and removed from the loaded organic phase by scrubbing with 0.01 mol/L HCl. Quantitative stripping (~99.5 %) of molybdenum was achieved with 2.0 mol/L HNO3 in two stages at O/A=1:1. Overall ~95.0% molybdenum with 99 % purity was recovered from Mo-Co spent catalyst. From the strip solution, MoO3 was obtained by crystallization followed by thermal decomposition. The product obtained after thermal decomposition was characterized by XRD, FE-SEM and EDX techniques. XRD peaks of MoO3correspond to molybdite Syn-MoO3 structure. FE-SEM depicts the rod like morphology of synthesized MoO3. EDX analysis of MoO3 shows 1:3 atomic percentage of molybdenum and oxygen. The synthesised MoO3 can find application in gas sensors, electrodes of batteries, display devices, smart windows, lubricants and as catalyst.

Keywords: cyphos IL 102, extraction, Mo-Co spent catalyst, recovery

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Authors: Salim Ahmed

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In many countries, water pollution from industrial effluents is a real problem. It may have a negative impact on the environment. To minimize the adverse effects of these contaminants, various methods are used to improve effluent purification, including physico-chemical processes such as adsorption.The present study focuses on applying a naturally biodegradable adsorbent based on argan (southern Morocco) in a physico-chemical adsorption process to reduce the harmful effects of pollutants on the environment. Tests were carried out with the cationic dye methylene blue (MB) and revealed that removal is significantly higher within the first 15 minutes. The parameters studied in this study are adsorbent mass and concentration. The Freundlich model provides an excellent example of the adsorption phenomenon of BMs over argan powder. The results of this study show that argan kernels are a highly beneficial alternative for local communities, as they help to achieve a triple objective: pollution reduction, waste recovery and water recycling.

Keywords: environmental protection, activated carbon, water treatment, adsorption

Procedia PDF Downloads 66

Authors: Nabat Gojaeva, Mikayil Naghiyev, Sultan Jafarov, Gular Mikayilova

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Chovdar ore area is located in the contact of Dashkesan caldera and Shamkir horst-graben uplift, which comprises the central part of Lok-Karabakh Island arcs of South Caucasus metallogenic province in terms of regional tectonics. One of the main structural features of formation of the Mereh and Aghyokhush group of low sulfidation epithermal gold deposits, locating in the north peripheric part of the ore area, is involving the crossing areas of ore-hosting and ore-forming Pan-Caucasian-direction structurally-compound faults with the meridional, rhombically shaped faults. In addition, another significant feature is the temporally two- or three-stage ore formation. In the first stage -an early phase of Upper Bathonian age, sulfides are the dominant minerals, in the second stage- late ‘productive’ phase of Upper Bathonian age, mainly gold mineralization is formed. Also, in the Upper Jurassic – Lower Cretaceous ages, rarely-encountered Cu-polymetallic ore formations are documented. Finally, in the last stage, the re-dislocation of ore-formation is foreseen in the previously-formed mineralization areas. The faults in the strike and dip directions formed shearing, brecciation, sulfide mineralization aureoles, and hydrothermal alteration zones in the wall rocks along with the local depression blocks. The geological-structural analysis of the area shows that multiple and various morphogenetic volcano-tectonically fault systems have developed in the area. These fault systems have played a trap role for ore-formation in the intersected parts of faults mentioned above. Thus, in the referred parts, mostly predominance of felsic volcanism and metasomatic alteration (silicification, argillitic, etc.) of wall rocks, as well as the products of this volcanism, account for the inclusion of hydrothermal ore-forming fluids along these faults. It is possible to determine temporally and lithological-structural connection between the ore-formation along with local depression blocks and faults as borders for products of felsic volcanism of Upper Cretaceous-Lesser Jurassic ages, in the results of the replacement of hydrothermal alteration zones with relatively low-temperature metasomatic alterations while moving from the felsic parts to the margins, and due to being non-ore bearing intermediate and intermediate-felsic magmatic facies.

Keywords: Aghyokhush, fault, gold deposit, Mereh

Procedia PDF Downloads 220

Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

Procedia PDF Downloads 171

Authors: Lae-Jeong Park

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The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: pedestrian detection, color segmentation, false positive, feature extraction

Procedia PDF Downloads 283

Authors: Yuhao Jin, Zhou Zhou, Katsumi Yoshida, Zhengcao Li, Tadashi Maruyama, Toyohiko Yano

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Four kinds of nuclear graphite, IG-110U, ETP-10, CX-2002U and IG-430U were neutron-irradiated at different fluences and temperatures, ranged from 1.38 x 1024 to 7.4 x 1025 n/m2 (E > 1.0 MeV) at 473K, 573K and 673K. To take into account the disorder in the microstructure, such as stacking faults and anisotropic coherent lengths, the X-ray diffraction patterns were interpreted using a comprehensive structural model and a refinement program CARBONXS. The deduced structural parameters show the changes of lattice parameters, coherent lengths along the c-axis and the basal plane, and the degree of turbostratic disorder as a function of the irradiation dose. Our results reveal neutron irradiation effects on the microstructure and macroscopic dimension, which are consistent with previous work. The methodology used in this work enables the quantification of the damage on the microstructure of nuclear graphite induced by neutron irradiation.

Keywords: nuclear graphite, neutron irradiation, thermal annealing, recovery behavior, dimensional change, CARBONX, XRD analysis

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Authors: Yagahira E. Castro-Sesquen, Chloe Kim, Robert H. Gilman, David J. Sullivan, Peter C. Searson

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Diagnosis of severe malaria is particularly important in highly endemic regions since most patients are positive for parasitemia and treatment differs from non-severe malaria. Diagnosis can be challenging due to the prevalence of diseases with similar symptoms. Accurate diagnosis is increasingly important to avoid overprescribing antimalarial drugs, minimize drug resistance, and minimize costs. A nanoparticle-based assay for detection and quantification of Plasmodium falciparum histidine-rich protein 2 (HRP2) in urine and serum is reported. The assay uses magnetic beads conjugated with anti-HRP2 antibody for protein capture and concentration, and antibody-conjugated quantum dots for optical detection. Western Blot analysis demonstrated that magnetic beads allows the concentration of HRP2 protein in urine by 20-fold. The concentration effect was achieved because large volume of urine can be incubated with beads, and magnetic separation can be easily performed in minutes to isolate beads containing HRP2 protein. Magnetic beads and Quantum Dots 525 conjugated to anti-HRP2 antibodies allows the detection of low concentration of HRP2 protein (0.5 ng mL-1), and quantification in the range of 33 to 2,000 ng mL-1 corresponding to the range associated with non-severe to severe malaria. This assay can be easily adapted to a non-invasive point-of-care test for classification of severe malaria.

Keywords: HRP2 protein, malaria, magnetic beads, Quantum dots

Procedia PDF Downloads 336

Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

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Image restoration in the process of communication is one of the emerging fields in the image processing. The motion analysis processing is the simplest case to detect motion in an image. Applications of motion analysis widely spread in many areas such as surveillance, remote sensing, film industry, navigation of autonomous vehicles, etc. The scene may contain multiple moving objects, by using motion analysis techniques the blur caused by the movement of the objects can be enhanced by filling-in occluded regions and reconstruction of transparent objects, and it also removes the motion blurring. This paper presents the design and comparison of various motion detection and enhancement filters. Median filter, Linear image deconvolution, Inverse filter, Pseudoinverse filter, Wiener filter, Lucy Richardson filter and Blind deconvolution filters are used to remove the blur. In this work, we have considered different types and different amount of blur for the analysis. Mean Square Error (MSE) and Peak Signal to Noise Ration (PSNR) are used to evaluate the performance of the filters. The designed system has been implemented in Matlab software and tested for synthetic and real-time images.

Keywords: image enhancement, motion analysis, motion detection, motion estimation

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Authors: Anne Giles

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Trauma is generally defined as an experience, or multiple experiences, overwhelming a person's ability to cope. Over time, many people recover from the neurobiological, physical, and emotional effects of trauma on their own. For some people, however, troubling symptoms develop over time that can result in distress and disability. This cluster of symptoms is classified as Post-traumatic Stress Disorder (PTSD). People who meet the criteria for PTSD and other trauma-related disorder diagnoses often hold a set of understandable but unfounded beliefs about traumatic events that cause undue suffering. Becoming aware of unhelpful beliefs—termed "cognitive distortions"—and challenging them is the realm of Cognitive Behavior Therapy (CBT). A form of CBT found by researchers to be especially effective for PTSD is Cognitive Processing Therapy (CPT). Through the compassionate use of CPT, people identify, examine, challenge, and relinquish unhelpful beliefs, thereby reducing symptoms and suffering. Widely-held cultural beliefs can interfere with the progress of recovery from trauma-related disorders. Although highly revered, largely unquestioned, and often stabilizing, cultural beliefs can be founded in simplistic, dichotomous thinking, i.e., things are all right, or all wrong, all good, or all bad. The reality, however, is nuanced and complex. After studying examples of cultural beliefs from China and the United States and how these might interfere with trauma recovery, trauma counselors can help clients derive criteria for preserving helpful beliefs, discover, examine, and jettison unhelpful beliefs, reduce trauma symptoms, and live their lives more freely and fully.

Keywords: cognitive processing therapy (CPT), cultural beliefs, post-traumatic stress disorder (PTSD), trauma recovery

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Authors: Ahmed Abdulrahman, Jalal Foroozesh

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CO₂ based enhanced oil recovery (EOR) techniques have gained massive attention from major oil firms since they resolve the industry's two main concerns of CO₂ contribution to the greenhouse effect and the declined oil production. Carbonated water injection (CWI) is a promising EOR technique that promotes safe and economic CO₂ storage; moreover, it mitigates the pitfalls of CO₂ injection, which include low sweep efficiency, early CO₂ breakthrough, and the risk of CO₂ leakage in fractured formations. One of the main challenges that hinder the wide adoption of this EOR technique is the complexity of accurate modeling of the kinetics of CO₂ mass transfer. The mechanisms of CO₂ mass transfer during CWI include the slow and gradual cross-phase CO₂ diffusion from carbonated water (CW) to the oil phase and the CO₂ dispersion (within phase diffusion and mechanical mixing), which affects the oil physical properties and the spatial spreading of CO₂ inside the reservoir. A 2D non-equilibrium compositional simulator has been developed using a fully implicit finite difference approximation. The material balance term (k) was added to the governing equation to account for the slow cross-phase diffusion of CO₂ from CW to the oil within the gird cell. Also, longitudinal and transverse dispersion coefficients have been added to account for CO₂ spatial distribution inside the oil phase. The CO₂-oil diffusion coefficient was calculated using the Sigmund correlation, while a scale-dependent dispersivity was used to calculate CO₂ mechanical mixing. It was found that the CO₂-oil diffusion mechanism has a minor impact on oil recovery, but it tends to increase the amount of CO₂ stored inside the formation and slightly alters the residual oil properties. On the other hand, the mechanical mixing mechanism has a huge impact on CO₂ spatial spreading (accurate prediction of CO₂ production) and the noticeable change in oil physical properties tends to increase the recovery factor. A sensitivity analysis has been done to investigate the effect of formation heterogeneity (porosity, permeability) and injection rate, it was found that the formation heterogeneity tends to increase CO₂ dispersion coefficients, and a low injection rate should be implemented during CWI.

Keywords: CO₂ mass transfer, carbonated water injection, CO₂ dispersion, CO₂ diffusion, cross phase CO₂ diffusion, within phase CO2 diffusion, CO₂ mechanical mixing, non-equilibrium simulation

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Authors: Behrang Tavousi Tehrani, Mohammad-Zaman Kabir

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Shape memory alloys (SMA) are often implemented in smart structures as the active components. Their ability to recover large displacements has been used in many applications, including structural stability/response enhancement and active structural acoustic control. SMA wires or fibers can be embedded with composite cylinders to increase their critical buckling load, improve their load-deflection behavior, and reduce the radial deflections under various thermo-mechanical loadings. This paper presents a semi-analytical investigation on the non-linear load-deflection response of SMA-reinforced composite circular cylindrical shells. The cylinder shells are under uniform external pressure load. Based on first-order shear deformation shell theory (FSDT), the equilibrium equations of the structure are derived. One-dimensional simplified Brinson’s model is used for determining the SMA recovery force due to its simplicity and accuracy. Airy stress function and Galerkin technique are used to obtain non-linear load-deflection curves. The results are verified by comparing them with those in the literature. Several parametric studies are conducted in order to investigate the effect of SMA volume fraction, SMA pre-strain value, and SMA activation temperature on the response of the structure. It is shown that suitable usage of SMA wires results in a considerable enhancement in the load-deflection response of the shell due to the generation of the SMA tensile recovery force.

Keywords: airy stress function, cylindrical shell, Galerkin technique, load-deflection curve, recovery stress, shape memory alloy

Procedia PDF Downloads 193

Authors: A. J. Babajanyan, T. A. Abrahamyan, H. A. Minasyan, K. V. Nerkararyan

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Optical radiation emitted from a metal-coated fiber tip apex at liquid-air interface was measured. The intensity of the output radiation was strongly depending on the relative position of the tip to a liquid-air interface and varied with surface fluctuations. This phenomenon permits in-situ real-time investigation of nano-metric vibrations of the liquid surface and provides a basis for development of various origin ultrasensitive vibration detecting sensors. The described method can be used for detection of week seismic vibrations.

Keywords: fiber-tip, liquid-air interface, nano vibration, opto-mechanical sensor

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Authors: Rajesh Kumar, Roopali Dogra, Puneet Aggarwal

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In recent advancements in electric machine and drives, wound rotor motor is extensively used. The merit of using wound rotor induction motor is to control speed/torque characteristics by inserting external resistance. Wound rotor induction motor can be used in the cases such as (a) low inrush current, (b) load requiring high starting torque, (c) lower starting current is required, (d) loads having high inertia, and (e) gradual built up of torque. Examples include conveyers, cranes, pumps, elevators, and compressors. This paper includes speed control of wound induction motor using MATLAB/Simulink for rotor resistance and slip power recovery method. The characteristics of these speed control methods are hence analyzed.

Keywords: MATLAB/Simulink, rotor resistance method, slip power recovery method, wound rotor induction motor

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Authors: Kenneth Fon Mbah, Arash Habibi Lashkari, Ali A. Ghorbani

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Phishing e-mails are a security issue that not only annoys online users, but has also resulted in significant financial losses for businesses. Phishing advertisements and pornographic e-mails are difficult to detect as attackers have been becoming increasingly intelligent and professional. Attackers track users and adjust their attacks based on users’ attractions and hot topics that can be extracted from community news and journals. This research focuses on deceptive Phishing attacks and their variants such as attacks through advertisements and pornographic e-mails. We propose a framework called Phishing Alerting System (PHAS) to accurately classify e-mails as Phishing, advertisements or as pornographic. PHAS has the ability to detect and alert users for all types of deceptive e-mails to help users in decision making. A well-known email dataset has been used for these experiments and based on previously extracted features, 93.11% detection accuracy is obtainable by using J48 and KNN machine learning techniques. Our proposed framework achieved approximately the same accuracy as the benchmark while using this dataset.

Keywords: phishing e-mail, phishing detection, anti phishing, alarm system, machine learning

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Authors: Mahdi Shamsi, Tohid Yousefi Rezaii, Siavash Eftekharifar

Abstract:

Compressed sensing (CS) is a new powerful mathematical theory concentrating on sparse signals which is widely used in signal processing. The main idea is to sense sparse signals by far fewer measurements than the Nyquist sampling rate, but the reconstruction process becomes nonlinear and more complicated. Common dilemma in sparse signal recovery in CS is the lack of knowledge about sparsity order of the signal, which can be viewed as model order selection procedure. In this paper, we address the problem of sparsity order estimation in sparse signal recovery. This is of main interest in situations where the signal sparsity is unknown or the signal to be recovered is approximately sparse. It is shown that the proposed method also leads to some kind of signal denoising, where the observations are contaminated with noise. Finally, the performance of the proposed approach is evaluated in different scenarios and compared to an existing method, which shows the effectiveness of the proposed method in terms of order selection as well as denoising.

Keywords: compressed sensing, data denoising, model order selection, sparse representation

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Authors: Ngozi Claribelle Nwogu, Mohammed Nasir Kajama, Oyoh Kechinyere, Edward Gobina

Abstract:

Atmospheric carbon dioxide emissions are considered as the greatest environmental challenge the world is facing today. The challenges to control the emissions include the recovery of CO2 from flue gas. This concern has been improved due to recent advances in materials process engineering resulting in the development of inorganic gas separation membranes with excellent thermal and mechanical stability required for most gas separations. This paper therefore evaluates the performance of a highly selective inorganic membrane for CO2 recovery applications. Analysis of results obtained is in agreement with experimental literature data. Further results show the prediction performance of the membranes for gas separation and the future direction of research. The materials selection and the membrane preparation techniques are discussed. Method of improving the interface defects in the membrane and its effect on the separation performance has also been reviewed and in addition advances to totally exploit the potential usage of this innovative membrane.

Keywords: carbon dioxide, gas separation, inorganic ceramic membrane, permselectivity

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Authors: Afsal Mohammed Kadavilpparampu, Haider A. J. Al Lawati, Fakhr Eldin O. Suliman, Salma M. Z. Al Kindy

Abstract:

In this work, we evaluated the appropriateness of various oxidants that can be used potentially with Ru(bipy)32+ CL system while performing CL detection in a microfluidic device using eight common active pharmaceutical ingredients- ciprofloxacin, hydrochlorothiazide, norfloxacin, buspirone, fexofenadine, cetirizine, codeine, and dextromethorphan. This is because, microfludics have very small channel volume and the residence time is also very short. Hence, a highly efficient oxidant is required for on-chip CL detection to obtain analytically acceptable CL emission. Three common oxidants were evaluated, lead dioxide, cerium ammonium sulphate and ammonium peroxydisulphate. Results obtained showed that ammonium peroxydisulphate is the most appropriate oxidant which can be used in microfluidic setup and all the tested analyte give strong CL emission while using this oxidant. We also found that Ru(bipy)33+ generated off-line by oxidizing [Ru(bipy)3]Cl2.6H2O in acetonitrile under acidic condition with lead dioxide was stable for more than 72 hrs. A highly sensitive microbore HPLC- CL method using ammonium peroxydisulphate as an oxidant in a microfluidic on-chip CL detection has been developed for the analyses of fixed-dose combinations of pseudoephedrine (PSE), fexofenadine (FEX) and cetirizine (CIT) in biological fluids and pharmaceutical formulations with minimum sample pre-treatment.

Keywords: oxidants, microbore High Performance Liquid Chromatography, chemiluminescence, microfluidics

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Authors: Sai Snehitha Yadavalli, K. Sruthi, Swati Ghosh Acharyya

Abstract:

Heavy metal ions are toxic to humans and all living species when exposed in large quantities or for long durations. Though Fe acts as a nutrient, when intake is in large quantities, it becomes toxic. These toxic heavy metal ions, when consumed through water, will cause many disorders and are harmful to all flora and fauna through biomagnification. Specifically, humans are prone to innumerable diseases ranging from skin to gastrointestinal, neurological, etc. In higher quantities, they even cause cancer in humans. Detection of these toxic heavy metal ions in water is thus important. Traditionally, the detection of heavy metal ions in water has been done by techniques like Inductively Coupled Plasma Mass Spectroscopy (ICPMS) and Atomic Absorption Spectroscopy (AAS). Though these methods offer accurate quantitative analysis, they require expensive equipment and cannot be used for on-site measurements. Anodic Stripping Voltammetry is a good alternative as the equipment is affordable, and measurements can be made at the river basins or lakes. In the current study, Square Wave Anodic Stripping Voltammetry (SWASV) was used to detect the heavy metal ions in water. Literature reports various electrodes on which deposition of heavy metal ions was carried out like Bismuth, Polymers, etc. The working electrode used in this study is a polyvinyl chloride (PVC) modified glassy carbon electrode (GCE). Ag/AgCl reference electrode and Platinum counter electrode were used. Biologic Potentiostat SP 300 was used for conducting the experiments. Through this work of simultaneous detection, four heavy metal ions were successfully detected at a time. The influence of modifying GCE with PVC was studied in comparison with unmodified GCE. The simultaneous detection of Cd⁺², Fe⁺², Co⁺², Pb⁺² heavy metal ions was done using PVC modified GCE by drop casting 1 wt.% of PVC dissolved in Tetra Hydro Furan (THF) solvent onto GCE. The concentration of all heavy metal ions was 0.2 mg/L, as shown in the figure. The scan rate was 0.1 V/s. Detection parameters like pH, scan rate, temperature, time of deposition, etc., were optimized. It was clearly understood that PVC helped in increasing the sensitivity and selectivity of detection as the current values are higher for PVC-modified GCE compared to unmodified GCE. The peaks were well defined when PVC-modified GCE was used.

Keywords: cadmium, cobalt, electrochemical sensing, glassy carbon electrodes, heavy metal Ions, Iron, lead, polyvinyl chloride, potentiostat, square wave anodic stripping voltammetry

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Authors: Zyad Elkhadir, Khalid Chougdali, Mohammed Benattou

Abstract:

Most of the existing intrusion detection systems works on quantitative network traffic data with many irrelevant and redundant features, which makes detection process more time’s consuming and inaccurate. A several feature extraction methods, such as linear discriminant analysis (LDA), have been proposed. However, LDA suffers from the small sample size (SSS) problem which occurs when the number of the training samples is small compared with the samples dimension. Hence, classical LDA cannot be applied directly for high dimensional data such as network traffic data. In this paper, we propose two solutions to solve SSS problem for LDA and apply them to a network IDS. The first method, reduce the original dimension data using principal component analysis (PCA) and then apply LDA. In the second solution, we propose to use the pseudo inverse to avoid singularity of within-class scatter matrix due to SSS problem. After that, the KNN algorithm is used for classification process. We have chosen two known datasets KDDcup99 and NSLKDD for testing the proposed approaches. Results showed that the classification accuracy of (PCA+LDA) method outperforms clearly the pseudo inverse LDA method when we have large training data.

Keywords: LDA, Pseudoinverse, PCA, IDS, NSL-KDD, KDDcup99

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Authors: M. K. Deore

Abstract:

The thick films of undoped and Al2O3 doped- ZnO were prepared by screen printing technique. AR grade (99.9 % pure) Zinc Oxide powder were mixed mechanochemically in acetone medium with Aluminium Chloride (AlCl2) material in various weight percentages such as 0.5, 1, 3 and 5 wt % to obtain Al2O3 - ZnO composite. The prepared materials were sintered at 1000oC for 12h in air ambience and ball milled to ensure sufficiently fine particle size. The electrical, structural and morphological properties of the films were investigated. The X-ray diffraction analysis of pure and doped ZnO shows the polycrystalline nature. The surface morphology of the films was studied by SEM. The final composition of each film was determined by EDAX analysis. The gas response of undoped and Al2O3- doped ZnO films were studied for different gases such as CO, H2, NH3, and H2S at operating temperature ranging from 50 oC to 450 o C. The pure film shows the response to H2S gas (500ppm) at 300oC while the film doped with 3 wt.% Al2O3 gives the good response to H2S gas(ppb) at 350oC. The selectivity, response and recovery time of the sensor were measured and presented.

Keywords: thick films, ZnO-Al2O3, H2S gas, sensitivity, selectivity, response and recovery time

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