Search results for: fault detection and recovery

Authors: Catrin Morgan, Atholl Johnston

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Creatine supplementation should theoretically increase total muscle creatine and so enhance the generation of intramuscular phosphocreatine and subsequent ATP formation. The use of creatine as a potential ergogenic aid in sport has been an area of significant scientific research for a number of years. However the effect of creatine supplementation and swimming performance is a relatively new area of research and is the subject of this review. In swimming creatine supplementation could help maintain maximal power output, aid recovery and increase lean body mass. After investigating the underlying theory and science behind creatine supplementation, a literature review was conducted to identify the best evidence looking at the effect of creatine supplementation on swimming performance. The search identified 27 potential studies, and of these 17 were selected for review. The studies were then categorised into single sprint performance, which involves swimming a short distance race, or repeated interval performance, which involves swimming a series of sprints with intervals of rest between them. None of the studies on the effect of creatine controlled for the multiple confounding factors associated with measurement of swimming performance. The sample size in the studies was limited and this reduced the reliability of the studies and introduced the possibility of bias. The studies reviewed provided insufficient evidence to determine if creatine supplementation is beneficial to swimming performance. However, what data there was supported the use of creatine supplementation in repeated interval swimming rather than in single sprint swimming. From a review of the studies, it was calculated on average, there was a 1.37% increase in swimming performance with the use of creatine for repeated intervals and a 0.86% increase in performance for single sprint. While this may seem minor, it should be remembered that swimming races are often won by much smaller margins. In the 2012 London Olympics the Men’s 100 metres freestyle race was won by a margin of only 0.01 of a second. Therefore any potential benefit could make a dramatic difference to the final outcome of the race. Overall more research is warranted before the benefits of creatine supplementation in swimming performance can be further clarified.

Keywords: creatine supplementation, repeated interval, single sprint, swimming performance

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Authors: Aisulu Tileukulova, Zhexebay Dauren

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Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

Procedia PDF Downloads 355

Authors: Gerardette Darkwah, Gloria Ankar Brewoo, John Barimah, Gilbert Owiah Sampson, Vincent Abe-Inge

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Soft drinks which are widely consumed in Ghana have been reported in other countries to contain toxic heavy metals beyond the acceptable limits in other countries. Therefore, the objective of this study was to assess the quality characteristics of selected locally produced and marketed soft drinks. Three (3) different batches of 23 soft drinks were sampled from the Takoradi markets. The samples were prescreened for the presence of reducing sugars, phosphates, alcohol and carbon dioxide. The heavy metal contents and physicochemical properties were also determined with AOAC methods. The results indicated the presence of reducing sugars, carbon dioxide and the absence of alcohol in all the selected soft drink samples. The pH, total sugars, moisture, total soluble solids (TSS) and titratable acidity ranged from 2.42 – 3.44, 3.30 – 10.44%, 85.63 – 94.85%, 5.00 – 13.33°Brix, and 0.21 – 1.99% respectively. The concentration of heavy metals were also below detection limits in all samples. The quality of the selected were within specifications prescribed by regulatory bodies.

Keywords: heavy metal contamination, locally manufactured, quality, soft drinks

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Authors: J. E. O. Hernandez

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In the next 20 years, energy production by burning fuels will increase and so will the atmospheric concentration of CO2 and its well-known threats to life on Earth. The technologies available for capturing CO2 are still dubious and this keeps fostering an interest in bio-inspired approaches. The leading one is the application of carbonic anhydrase (CA) –a superfast biocatalyst able to convert up to one million molecules of CO2 into carbonates in water. However, natural CA underperforms when applied to real smoky CO2 in chimneys and, so far, the efforts to create superior CAs in the lab rely on screening methods running under pristine conditions at the micro level, which are far from resembling those in chimneys. For the evolution of man-made enzymes, selection rather than screening would be ideal but this is challenging because of the need for a suitable artificial environment that is also sustainable for our society. Herein we present the stepwise design and construction of a bioprocess (from bench-scale to semi-pilot) for evolutionary selection experiments. In this bioprocess, reaction and adsorption took place simultaneously at atmospheric pressure in a spray tower. The scrubbing solution was fed countercurrently by reusing municipal pressure and it was mainly prepared with water, carbonic anhydrase and calcium chloride. This bioprocess allowed for the enzymatic carbonation of smoky CO2; the reuse of process water and the recovery of solid carbonates without cooling of smoke, pretreatments, solvent amines and compression of CO2. The average yield of solid carbonates was 0.54 g min-1 or 12-fold the amount produced in serum bottles at lab bench scale. This bioprocess could be used as a tailor-made environment for driving the selection of superior CAs. The bioprocess and its match CA could be sustainably used to reduce global warming by CO2 emissions from exhausts.

Keywords: biological carbon capture and sequestration, carbonic anhydrase, directed evolution, global warming

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Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

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Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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Authors: Martyna Ekiert, Andrzej Mlyniec

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Tendons are the biological structures, which primary function is to transfer force generated by muscles to the bones. Unfortunately, damages of tendons are also one of the most common injuries of the human musculoskeletal system. For the most severe cases of tendon rupture, such as the tear of calcaneus tendon or anterior cruciate ligament of the knee, a surgical procedure is the only possible way of full recovery. Tendons used as biological grafts are usually subjected to the process of deep freezing and subsequent thawing. This, in particular for multiple freezing/thawing cycles, may result in changes of tendon internal structure causing deterioration of mechanical properties of the tissue. Therefore, studies on the influence of freezing on tendons biomechanics, including internal water content in soft tissue, seems to be greatly needed. An experimental study of the influence of freezing on mechanical properties of the tendon was performed on fascicles samples dissected form bovine flexor tendons. The preparation procedure was performed with the presence of 0.9% saline solution in order to prevent an excessive tissue drying. All prepared samples were subjected to the different number of freezing/thawing cycles. For freezing part of the protocol we used -80°C temperature while for slow thawing we used fridge temperature (4°C) combined with equalizing temperatures in the standard state (25°C). After final thawing, the mechanical properties of each sample was examined using cyclic loading test. Our results may contribute for better understanding of negative effects of soft tissues freezing, resulting from abnormal thermal expansion of water. This also may help to determine the limit of freezing/thawing cycles disqualifying tissue for surgical purposes and thus help optimize tissues storage conditions.

Keywords: freezing, soft tissue, tendon, bovine fascicles

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Authors: E. Kam, G. Karahan, H. Aslıyuksek, A. Bozkurt

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This study aims to determine the natural radioactivity levels in some foodstuffs produced in Turkey. For this purpose, 48 different foods samples were collected from different land parcels throughout the country. All samples were analyzed to designate both gross alpha and gross beta radioactivities and the radionuclides’ concentrations. The gross alpha radioactivities were measured as below 1 Bq kg^-1 in most of the samples, some of them being due to the detection limit of the counting system. The gross beta radioactivity levels ranged from 1.8 Bq kg^-1 to 453 Bq kg^-1, larger levels being observed in leguminous seeds while the highest level being in haricot bean. The concentrations of natural radionuclides in the foodstuffs were investigated by the method of gamma spectroscopy. High levels of ⁴⁰K were measured in all the samples, the highest activities being again in leguminous seeds. Low concentrations of ²³⁸U and ²²⁶Ra were found in some of the samples, which are comparable to the reported results in the literature. Based on the activity concentrations obtained in this study, average annual effective dose equivalents for the radionuclides ²²⁶Ra, ²³⁸U, and ⁴⁰K were calculated as 77.416 µSv y^-1, 0.978 µSv y^-1, and 140.55 µSv y^-1, respectively.

Keywords: foods, radioactivity, gross alpha, gross beta, annual equivalent dose, Turkey

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Authors: Marinos Xagoraris, Iliada K. Lappa, Charalambos Kanakis, Dimitra Daferera, Christina Papadopoulou, Georgios Sourounis, Charilaos Giotis, Pavlos Bouchagier, Christos S. Pappas, Petros A. Tarantilis, Efstathia Skotti

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The aim of this work was to recover phenolic compounds from grape skins produced in Greek varieties of the Ionian Islands in order to form the basis of calculations for their further utilization in the context of the circular economy. Isolation and further utilization of phenolic compounds is an important issue in winery by-products. For this purpose, 37 samples were collected, extracted, and analyzed in an attempt to provide the appropriate basis for their sustainable exploitation. Extraction of the bioactive compounds was held using an eco-friendly, non-toxic, and highly effective water-glycerol solvent system. Then, extracts were analyzed using UV-Vis, liquid chromatography-mass spectrometry (LC-MS), FTIR, and Raman spectroscopy. Also, total phenolic content and antioxidant activity were measured. LC-MS chromatography showed qualitative differences between different varieties. Peaks were attributed to monomeric 3-flavanols as well as monomeric, dimeric, and trimeric proanthocyanidins. The FT-IR and Raman spectra agreed with the chromatographic data and contributed to identifying phenolic compounds. Grape skins exhibited high total phenolic content (TPC), and it was proved that during vinification, a large number of polyphenols remained in the pomace. This study confirmed that grape skins from Ionian Islands are a promising source of bioactive compounds, suggesting their utilization under a bio-economic and environmental strategic framework.

Keywords: antioxidant activity, grape skin, phenolic compounds, waste recovery

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Authors: Walid Mousa, Mohamed Nayel, Ahmed Zaghawa, Akram Salama, Ahmed El-Sify, Hesham Rashad, Dina El-Shafey

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Mycoplasmosis in small ruminants constitutes a serious contagious problem in smallholders causing severe economic losses worldwide. This study was conducted to determine the clinical, Minimum Inhibitory Concentration (MIC) and molecular characterization of Mycoplasma species associated in sheep breeding herds in Menoufiya governorate, Egypt. Out of the examination of 400 sheep, 104 (26%) showed respiratory manifestations, nasal discharges, cough and conjunctivitis with systemic body reaction. Meanwhile, out of these examined sheep, only 56 (14%) were positive for mycoplasma isolation onto PPLO(Pleuropneumonia-like organisms) specific medium. The MIC for evaluating the efficacy of sensitivity of Mycoplasma isolates against different antibiotics groups revealed that both the Linospectin and Tylosin with 2ug, 0.25ug/ml concentration were the most effective antibiotics for Mycoplasma isolates. The application of PCR was the rapid, specific and sensitive molecular approach for detection of M. ovipneumoniae, and M. arginine at 390 and 326 bp, respectively, in all tested isolates. In conclusion, the diagnosis of Mycoplsamosis in sheep is important to achieve effective control measures and minimizing the disease dissemination among sheep herds.

Keywords: MIC, mycoplasmosis, PCR, sheep

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Authors: Sanjay Adhikesaven

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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

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Authors: Rozalina Keremedchieva, Ivan Svinyarov, Milen G. Bogdanov

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In continuation of a research project on the application of ionic liquids (ILs) as an alternative to the conventional organic solvents used in the recovery of value added chemicals of industrial interest1-3 we developed a procedure for back extraction and isolation in pure form of the biologically active alkaloid glaucine from IL-based aqueous solutions. One of the approaches applied was the formation of two-phase systems (IL-ATPS) by the addition of kosmotropic salts to the plant extract. The ability of the salts (Na2CO3, MgSO4, (NH4)2SO4, NaH2PO4) to induce the formation of two-phase systems and the influence of pH value on the partition coefficients of glaucine was comprehensively studied. As a result, it was found that the target alkaloid is preferably partitioned into the IL-rich phase regardless of the pH value of the medium and thus shows the inapplicability of the approach used for the isolation of the target compound from the ionic liquid. However, the results obtained can be used as a platform for the development of an analytical method for the quantitative determination of low concentrations of glaucine in biological samples. We further examined the ability of a series of organic solvents such as diethyl ether, Tert-butylmethyl ether, ethyl acetate, butyl acetate, toluene, chloroform, dichloromethane to recover glaucine form raw IL-based aqueous extracts. Optimal conditions for quantitative extraction of glaucine into chloroform were found from which, after removal of the solvent and subsequent recrystallization from ethanol, the target compound was isolated in a high purity as a hydrobromide salt – The form in which it entrance as an active ingredient in various medicines.

Keywords: natural products, ionic liquids, solid-liquid extraction, liquid-liquid extraction

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Authors: Carla Nardelli, Jérome Holtzmann, Céline Baeyens, Catherine Bortolon

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Background. Emotion regulation (ER) is a process associated with difficulties in mental health. Given its transdiagnostic features, its improvement could facilitate the recovery of various psychological issues. A limit of current studies is the lack of knowledge regarding whether available interventionsimprove ER flexibility (i.e., the ability to implement ER strategies in line with contextual demands), even though this capacity has been associated with better mental health and well-being. Therefore, the aim of the study is to test the efficacy of a 9-weeks ER group program (the Affect Regulation Training-ART), using the most appropriate measures (i.e., experience sampling method) in a student population. Plus, the goal of the study is to explore the potential mediative role of ER flexibility on mental health improvement. Method. This Randomized Controlled Trial will comparethe ER program group to an active control group (a relaxation program) in 100 participants. To test the mediative role of ER flexibility on mental health, daily measures will be used before, during, and after the interventions to evaluate the extent to which participants are flexible in their ER. Expected outcomes. Using multilevel analyses, we expect an improvement in anxious-depressive symptomatology for both groups. However, we expect the ART group to improve specifically on ER flexibility ability and the last to be a mediative variable on mental health. Conclusion. This study will enhance knowledge on interventions for students and the impact of interventions on ER flexibility. Also, this research will improve knowledge on ecological measures for assessing the effect of interventions. Overall, this project represents new opportunities to improve ER skills to improve mental health in undergraduate students.

Keywords: emotion regulation flexibility, experience sampling method, psychological intervention, emotion regulation skills

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Authors: Stephen Tullis, M. David DiDonato, Hong Sung Park

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Rowing boats (shells) are often steered by a small rudder operated by one of the backward-facing rowers; the attention required of that athlete then slightly decreases the power that that athlete can provide. Reducing the steering distraction would then increase the overall boat speed. Races are straight 2000 m courses with each boat in a 13.5 m wide lane marked by small (~15 cm) widely-spaced (~10 m) buoys, and the boat trajectory is affected by both cross-currents and winds. An optical buoy recognition and tracking system has been developed that provides the boat’s location and orientation with respect to the lane edges. This information is provided to the steering athlete as either: a simple overlay on a video display, or fed to a simplified autopilot system giving steering directions to the athlete or directly controlling the rudder. The system is then effectively a “lane-assist” device but with small, widely-spaced lane markers viewed from a very shallow angle due to constraints on camera height. The image is captured with a lightweight 1080p webcam, and most of the image analysis is done in OpenCV. The colour RGB-image is converted to a grayscale using the difference of the red and blue channels, which provides good contrast between the red/yellow buoys and the water, sky, land background and white reflections and noise. Buoy detection is done with thresholding within a tight mask applied to the image. Robust linear regression using Tukey’s biweight estimator of the previously detected buoy locations is used to develop the mask; this avoids the false detection of noise such as waves (reflections) and, in particular, buoys in other lanes. The robust regression also provides the current lane edges in the camera frame that are used to calculate the displacement of the boat from the lane centre (lane location), and its yaw angle. The interception of the detected lane edges provides a lane vanishing point, and yaw angle can be calculated simply based on the displacement of this vanishing point from the camera axis and the image plane distance. Lane location is simply based on the lateral displacement of the vanishing point from any horizontal cut through the lane edges. The boat lane position and yaw are currently fed what is essentially a stripped down marine auto-pilot system. Currently, only the lane location is used in a PID controller of a rudder actuator with integrator anti-windup to deal with saturation of the rudder angle. Low Kp and Kd values decrease unnecessarily fast return to lane centrelines and response to noise, and limiters can be used to avoid lane departure and disqualification. Yaw is not used as a control input, as cross-winds and currents can cause a straight course with considerable yaw or crab angle. Mapping of the controller with rudder angle “overall effectiveness” has not been finalized - very large rudder angles stall and have decreased turning moments, but at less extreme angles the increased rudder drag slows the boat and upsets boat balance. The full system has many features similar to automotive lane-assist systems, but with the added constraints of the lane markers, camera positioning, control response and noise increasing the challenge.

Keywords: auto-pilot, lane-assist, marine, optical, rowing

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Authors: Ghada Ben Brahim, Aicha El Rabia, Mohamed Hedi Inoubli

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Climate change has exacerbated disparities in the distribution of water resources in Tunisia, resulting in significant degradation in quantity and quality over the past five decades. The Mio-Plio-Quaternary aquifer, the primary water source in the Zarzis region, is subject to climatic, geographical, and geological challenges, as well as human stress. The region is experiencing uneven distribution and growing threats from groundwater salinity and saltwater intrusion. Addressing this challenge is critical for the arid region’s socioeconomic development, and effective water resource management is required to combat climate change and reduce water deficits. This study uses a multidisciplinary approach to determine the groundwater potential of this aquifer, involving geophysics and hydrogeology data analysis. We used advanced techniques such as 3D Euler deconvolution and power spectrum analysis to generate detailed anomaly maps and estimate the depths of density sources, identifying significant Bouguer anomalies trending E-W, NW-SE, and NE-SW. Various techniques, such as wavelength filtering, upward continuation, and horizontal and vertical derivatives, were used to improve the gravity data, resulting in consistent results for anomaly shapes and amplitudes. The Euler deconvolution method revealed two prominent surface faults, trending NE-SW and NW-SE, that have a significant impact on the distribution of sedimentary facies and water quality within the Mio-Plio-Quaternary aquifer. Additionally, depth maxima greater than 1400 m to the North indicate the presence of a Cretaceous paleo-fault. Geoelectrical models and resistivity pseudo-sections were used to interpret the distribution of electrical facies in the Mio-Plio-Quaternary aquifer, highlighting lateral variation and depositional environment type. AI optimises the analysis and interpretation of exploration data, which is important to long-term management and water security. Machine learning algorithms and deep learning models analyse large datasets to provide precise interpretations of subsurface conditions, such as aquifer salinisation. However, AI has limitations, such as the requirement for large datasets, the risk of overfitting, and integration issues with traditional geological methods.

Keywords: mio-plio-quaternary aquifer, Southeastern Tunisia, geophysical methods, hydrogeological analysis, artificial intelligence

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Authors: Wei Ji

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This study was conducted in the Kansas City metropolitan area of the United States, which has experienced significant urban sprawling in recent decades. The remote sensing of land cover changes in this area spanned over four decades from 1972 through 2010. The project was implemented in two stages: the first stage focused on detection of long-term trends of urban land cover change, while the second one examined how to detect the coupled effects of human impact and climate change on urban landscapes. For the first-stage study, six Landsat images were used with a time interval of about five years for the period from 1972 through 2001. Four major land cover types, built-up land, forestland, non-forest vegetation land, and surface water, were mapped using supervised image classification techniques. The study found that over the three decades the built-up lands in the study area were more than doubled, which was mainly at the expense of non-forest vegetation lands. Surprisingly and interestingly, the area also saw a significant gain in surface water coverage. This observation raised questions: How have human activities and precipitation variation jointly impacted surface water cover during recent decades? How can we detect such coupled impacts through remote sensing analysis? These questions led to the second stage of the study, in which we designed and developed approaches to detecting fine-scale surface waters and analyzing coupled effects of human impact and precipitation variation on the waters. To effectively detect urban landscape changes that might be jointly shaped by precipitation variation, our study proposed “urban wetscapes” (loosely-defined urban wetlands) as a new indicator for remote sensing detection. The study examined whether urban wetscape dynamics was a sensitive indicator of the coupled effects of the two driving forces. To better detect this indicator, a rule-based classification algorithm was developed to identify fine-scale, hidden wetlands that could not be appropriately detected based on their spectral differentiability by a traditional image classification. Three SPOT images for years 1992, 2008, and 2010, respectively were classified with this technique to generate the four types of land cover as described above. The spatial analyses of remotely-sensed wetscape changes were implemented at the scales of metropolitan, watershed, and sub-watershed, as well as based on the size of surface water bodies in order to accurately reveal urban wetscape change trends in relation to the driving forces. The study identified that urban wetscape dynamics varied in trend and magnitude from the metropolitan, watersheds, to sub-watersheds in response to human impacts at different scales. The study also found that increased precipitation in the region in the past decades swelled larger wetlands in particular while generally smaller wetlands decreased mainly due to human development activities. These results confirm that wetscape dynamics can effectively reveal the coupled effects of human impact and climate change on urban landscapes. As such, remote sensing of this indicator provides new insights into the relationships between urban land cover changes and driving forces.

Keywords: urban land cover, human impact, climate change, rule-based classification, across-scale analysis

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Authors: Li Minghui, Min Shaorong, Zhang Jun

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This paper aims for studying the operational efficiency of surface warship’s motorized evasion to acoustic homing torpedo. It orderly developed trajectory model, self-guide detection model, vessel evasion model, as well as anti-torpedo error model in three-dimensional space to make up for the deficiency of precious researches analyzing two-dimensionally confrontational models. Then, making use of the Monte Carlo method, it carried out the simulation for the confrontation process of evasion in the environment of MATLAB. At last, it quantitatively analyzed the main factors which determine vessel’s survival probability. The results show that evasion relative bearing and speed will affect vessel’s survival probability significantly. Thus, choosing appropriate evasion relative bearing and speed according to alarming range and alarming relative bearing for torpedo, improving alarming range and positioning accuracy and reducing the response time against torpedo will improve the vessel’s survival probability significantly.

Keywords: acoustic homing torpedo, vessel evasion, monte carlo method, torpedo defense, vessel's survival probability

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Authors: Montaceur Zaghdoud, Mohamed Moussaoui, Jalel Akaichi

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Frequent subgraph mining refers usually to graph matching and it is widely used in when analyzing big data with large graphs. A lot of research works dealt with structural exact or inexact graph matching but a little attention is paid to semantic matching when graph vertices and/or edges are attributed and typed. Therefore, it seems very interesting to integrate background knowledge into the analysis and that extracted frequent subgraphs should become more pruned by applying a new semantic filter instead of using only structural similarity in graph matching process. Consequently, this paper focuses on developing a new hybrid approximate structuralsemantic graph matching to discover a set of frequent subgraphs. It uses simultaneously an approximate structural similarity function based on graph edit distance function and a possibilistic vertices similarity function based on affinity function. Both structural and semantic filters contribute together to prune extracted frequent set. Indeed, new hybrid structural-semantic frequent subgraph mining approach searches will be suitable to be applied to several application such as community detection in social networks.

Keywords: approximate graph matching, hybrid frequent subgraph mining, graph mining, possibility theory

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Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

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Authors: Zakiullah Kalwar, Shabeer Abbassi

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This research encompasses the study of structural styles and evaluation of the hydrocarbon potential of Kotrum and Drigri anticlines located in Rajanpur Area, Midddle Indus Basin of Pakistan with the approach of geophysical data integration. The study area is situated between the Sulaiman Foldbelt on the west and Indus River in the east. It is an anticlinal fold, located to the southeast of Sakhi Sarwar anticline and separated from a prominent syncline. The structure has a narrow elongated crest, with the axis running in SSW-NNE direction. In the east, the structure is bounded by a gentle syncline. Structural Styles are trending East-West and perpendicular to tectonic transport and stress direction and the base of the structures gradually dipping Eastward beneath the deformation frontal part in Eastern Sulaiman Fold Belt. Middle Indus Basin can be divided into Foreland, Sulaiman fold belt and a broad foredeep. Sulaiman represents a blind thrust front, which suggests that all frontal folds of the fold belt are cored by blind thrust. The deformation of frontal part of Sulaiman Lobe represents the passive roof duplex stacked beneath the frontal passive roof thrust. The passive roof thrust, which has a back thrust sense of motion and extends into the interior of Fold belt. Left lateral Kingri Fault separates Eastern and Central Sulaiman fold belt. In Central Sulaiman fold belt the deformation front moved further towards fore deep as compared to Eastern Sulaiman. Two wells (Kotrum-01, Drigri-01) have been drilled in the study area with the objective to determine the potential of oil and gas in Habib Rahi Limestone of Eocene age, Dunghan Limestone of Paleocene age and Pab Sandstone of cretaceous age and role of structural styles in hydrocarbon potential of study area. Kotrum-01 well was drilled to its T.D of 4798m. Besides fishing and side tracking, tight whole conditions, high pressure, and losses of circulation were also encountered. During production, testing Pab sandstone were tested but abandoned found. Drigri-01 well was drilled to its T.D 3250 m. RFT was carried out at different points, but all points showed no pressure / seal failure and the well was plugged and declared abandoned.

Keywords: hydrocarbon potential, structural style, reserve calculation, enhance production

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Authors: Rahul Agarwal, Ashutosh Singh

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Colorectal cancer (CRC) also refers as bowel cancer or colon cancer. It involves the development of abnormal growth of cells in colon or rectum part of the body. This work leads to the development of a miRNA database in colorectal cancer. We named this database- miCoRe. This database comprises of all validated colon-rectal cancer miRNAs information from various published literature with an effectual knowledge based information retrieval system. miRNAs have been collected from various published literature reports. MySQL is used for main-framework of miCoRe while the front-end was developed in PHP script. The aim of developing miCoRe is to create a comprehensive central repository of colorectal carcinoma miRNAs with all germane information of miRNAs and their target genes. The current version of miCoRe consists of 238 miRNAs which are known to be implicated in malignancy of CRC. Alongside with miRNA information, miCoRe also contains the information related to the target genes of these miRNA. miCoRe furnishes the information about the mechanism of incidence and progression of the disease, which would further help the researchers to look for colorectal specific miRNAs therapies and CRC specific targeted drug designing. Moreover, it will also help in development of biomarkers for the better and early detection of CRC and will help in better clinical management of the disease.

Keywords: colorectal cancer, database, miCoRe, miRNAs

Procedia PDF Downloads 280

Authors: Myung-Soo Lee, Sun-Jin Jo, Kyoung-Sae Na, Joo-Eon Park

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Early intervention after a disaster is important for recovery of disaster victims and each country has its own professional mental health service system such as Disaster Psychiatric Assistant Team in Japan and Crisis Counseling Program in the USA. The purpose of this study was to determine key prior components of the Korean Disaster Psychiatric Assistant Team (K-DPAT) for building up Korean disaster mental health service system. We conducted an Analytic Hierarchy Process(AHP) with disaster mental health experts using pairwise comparison questionnaire which compares the relative importance of the key components of Korean disaster mental health service system. Forty-one experts answered the first online survey, and among them, 36 responded to the second. Ten experts were participated in panel meeting and discussed the results of the survey and AHP process. Participants decided the relative importance of the Korean disaster mental health service system regarding initial professional intervention as follows. K-DPAT could be organized at a national level (43.0%) or regional level (40.0%). K-DPAT members should be managed (59.0%) and educated (52.1%) by national level than regional or local level. K-DPAT should be organized independent of the preexisting mental health system (70.1%). Funding for K-DPAT should be from the Ministry of Public Safety and the system could be managed by Ministry of Health (65.8%). Experts agreed K-DPAT leader is suitable for key decision maker for most types of disaster except infectious disease. We expect new model for disaster mental health services can improve insufficiency of the system such as fragmentation and decrease the unmet needs of early professional intervention for the disaster victims.

Keywords: analytic hierarchy process, decision making, disaster, DPAT, mental health services

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Authors: F. Al-Sheikh, C. Moralejo, M. Pritzker, W. A. Anderson, A. Elkamel

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Ammonia in mining wastewater is a significant problem, and treatment can be especially difficult in cold climates where biological treatment is not feasible. An adsorption process is one of the alternative processes that can be used to reduce ammonia concentrations to acceptable limits, and therefore a LEWATIT resin strongly acidic H+ form ion exchange resin and a Bowie Chabazite Na form AZLB-Na zeolite were tested to assess their effectiveness. For these adsorption tests, two packed bed columns (a mini-column constructed from a 32-cm long x 1-cm diameter piece of glass tubing, and a 60-cm long x 2.5-cm diameter Ace Glass chromatography column) were used containing varying quantities of the adsorbents. A mining wastewater with ammonia concentrations of 22.7 mg/L was fed through the columns at controlled flowrates. In the experimental work, maximum capacities of the LEWATIT ion exchange resin were 0.438, 0.448, and 1.472 mg/g for 3, 6, and 9 g respectively in a mini column and 1.739 mg/g for 141.5 g in a larger Ace column while the capacities for the AZLB-Na zeolite were 0.424, and 0.784 mg/g for 3, and 6 g respectively in the mini column and 1.1636 mg/g for 38.5 g in the Ace column. In the theoretical work, Thomas, Adams-Bohart, and Yoon-Nelson models were constructed to describe a breakthrough curve of the adsorption process and find the constants of the above-mentioned models. In the regeneration tests, 5% hydrochloric acid, HCl (v/v) and 10% sodium hydroxide, NaOH (w/v) were used to regenerate the LEWATIT resin and AZLB-Na zeolite with 44 and 63.8% recovery, respectively. In conclusion, continuous flow adsorption using a LEWATIT ion exchange resin and an AZLB-Na zeolite is efficient when using a co-flow technique for removal of the ammonia from wastewater. Thomas, Adams-Bohart, and Yoon-Nelson models satisfactorily fit the data with R² closer to 1 in all cases.

Keywords: AZLB-Na zeolite, continuous adsorption, Lewatit resin, models, regeneration

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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Authors: Muthukumarasamy Govindarajan

Abstract:

Detection of unwanted, unsolicited mails called spam from email is an interesting area of research. It is necessary to evaluate the performance of any new spam classifier using standard data sets. Recently, ensemble-based classifiers have gained popularity in this domain. In this research work, an efficient email filtering approach based on ensemble methods is addressed for developing an accurate and sensitive spam classifier. The proposed approach employs Naive Bayes (NB), Support Vector Machine (SVM) and Genetic Algorithm (GA) as base classifiers along with different ensemble methods. The experimental results show that the ensemble classifier was performing with accuracy greater than individual classifiers, and also hybrid model results are found to be better than the combined models for the e-mail dataset. The proposed ensemble-based classifiers turn out to be good in terms of classification accuracy, which is considered to be an important criterion for building a robust spam classifier.

Keywords: accuracy, arcing, bagging, genetic algorithm, Naive Bayes, sentiment mining, support vector machine

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Authors: Riad Benelmir, Muhammad Shoaib Ahmed Khan

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The socio-economic importance of the olive oil production is significant in the Mediterranean region, both in terms of wealth and tradition. However, the extraction of olive oil generates huge quantities of wastes that may have a great impact on land and water environment because of their high phytotoxicity. Especially olive mill wastewater (OMWW) is one of the major environmental pollutants in olive oil industry. This work projects to design a smart and sustainable integrated thermochemical catalytic processes of residues from olive mills by hydrothermal carbonization (HTC) of olive mill wastewater (OMWW) and fast pyrolysis of olive mill wastewater sludge (OMWS). The byproducts resulting from OMWW-HTC treatment are a solid phase enriched in carbon, called biochar and a liquid phase (residual water with less dissolved organic and phenolic compounds). HTC biochar can be tested as a fuel in combustion systems and will also be utilized in high-value applications, such as soil bio-fertilizer and as catalyst or/and catalyst support. The HTC residual water is characterized, treated and used in soil irrigation since the organic and the toxic compounds will be reduced under the permitted limits. This project’s concept includes also the conversion of OMWS to a green diesel through a catalytic pyrolysis process. The green diesel is then used as biofuel in an internal combustion engine (IC-Engine) for automotive application to be used for clean transportation. In this work, a theoretical study is considered for the use of heat from the pyrolysis non-condensable gases in a sorption-refrigeration machine for pyrolysis gases cooling and condensation of bio-oil vapors.

Keywords: biomass, olive oil extraction, adsorption cooling, pyrolisis

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Authors: Shu-Min Tsao, Chung-Ming Lo, Shao-Chun Chen

Abstract:

Most diabetes patients tend to suffer from its complication of retina diseases. Therefore, early detection and early treatment are important. In clinical examinations, using color fundus image was the most convenient and available examination method. According to the exudates appeared in the retinal image, the status of retina can be confirmed. However, the routine screening of diabetic retinopathy by color fundus images would bring time-consuming tasks to physicians. This study thus proposed a computer-aided exudate diagnosis for the screening of diabetic retinopathy. After removing vessels and optic disc in the retinal image, six quantitative features including region number, region area, and gray-scale values etc… were extracted from the remaining regions for classification. As results, all six features were evaluated to be statistically significant (p-value < 0.001). The accuracy of classifying the retinal images into normal and diabetic retinopathy achieved 82%. Based on this system, the clinical workload could be reduced. The examination procedure may also be improved to be more efficient.

Keywords: computer-aided diagnosis, diabetic retinopathy, exudate, image processing

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Authors: Mamta M. Barapatre, V. N. Sahare

Abstract:

Since from long time two wheeled vehicle self-balancing has always been a back-breaking task for both human and robots. Leaning a bicycle driving is long time process and goes through building knowledge base for parameter decision making while balancing robots. In order to create this machine learning phase with embedded system the proposed system is designed. The system proposed aims to construct a bicycle automaton, power-driven by an electric motor, which could balance by itself and move along a specific path. This path could be wavy with bumps and varying widths. The key aim was to construct a cycle which self-balances itself by controlling its handle. In order to take a turn, the mass was transferred to the center. In order to maintain the stability, the bicycle bot automatically turned the handle and a turn. Some problems were faced by the team which were Speed, Steering mechanism through mass- distribution (leaning), Center of mass location and gyroscopic effect of its wheel. The idea proposed have potential applications in automation of transportation system and is most efficient.

Keywords: gyroscope-flywheel, accelerometer, servomotor-controller, self stability concept

Procedia PDF Downloads 279

Authors: Aleksandra Łochowicz, Daria Świętochowska, Loredano Pollegioni, Nazim Ocal, Franck Charmantray, Laurence Hecquet, Katarzyna Szymańska

Abstract:

Multienzymatic cascade reactions are nowadays widely used in pharmaceutical, chemical and cosmetics industries to produce high valuable compounds. They can be carried out in two ways, step by step and one-pot. If two or more enzymes are in the same reaction vessel is necessary to work out the compromise to run the reaction in optimal conditions for each enzyme. So far most of the reports of multienzymatic cascades concern on usage of free enzymes. Unfortunately using free enzymes as catalysts of reactions accomplish high cost. What is more, free enzymes are soluble in solvents which makes reuse impossible. To overcome this obstacle enzymes can be immobilized what provides heterogeneity of biocatalyst that enables reuse and easy separation of the enzyme from solvents and reaction products. Usually, immobilization increase also the thermal and operational stability of enzyme. The advantages of using immobilized multienzymes are enhanced enzyme stability, improved cascade enzymatic activity via substrate channeling, and ease of recovery for reuse. The one-pot immobilized multienzymatic cascade can be carried out in mixed or coimmobilized type. When biocatalysts are coimmobilized on the same carrier the are in close contact to each other which increase the reaction rate and catalytic efficiency, and eliminate the lag time. However, in this type providing the optimal conditions both in the process of immobilization and cascade reaction for each enzyme is complicated. Herein, we examined immobilization of 3 enzymes: D-amino acid oxidase from Rhodotorula gracilis, commercially available catalase and transketolase from Geobacillus stearothermophilus. As a support we used silica monoliths with hierarchical structure of pores. Then we checked their stability and reusability in one-pot cascade of L-erythrulose and hydroxypuryvate acid synthesis.

Keywords: biocatalysts, enzyme immobilization, multienzymatic reaction, silica carriers

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Authors: J. Hidalgo de Quintana, I. Stoner, M. Tackett, G. Doran, C. Rafferty, A. Windemuth, J. Tytell, D. Pregibon

Abstract:

We have developed the Multiplexed Circulating microRNA assay that allows the detection of up to 68 microRNA targets per sample. The assay combines particle­based multiplexing, using patented Firefly hydrogel particles, with single­ step RT-PCR signal. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target­-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are interpreted using Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. Here we present the data from several studies investigating circulating and tumor microRNA, showcasing the ability of the technology to sensitively and specifically detect microRNA biomarker signatures from fluid specimens.

Keywords: biomarkers, biofluids, miRNA, photolithography, flowcytometry

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Authors: Md. Mazharul Anwar, Md. Samim Hossain Molla, Md. Akkas Ali, Mian Sayeed Hassan

Abstract:

After 68 years, the agreement between Bangladesh and India was ratified on 6 June 2015 and Bangladesh received 111 Indian enclaves. Millions of farm household lived in these previous enclaves, being detached from the mainland of the country, they were socially, economically and educationally deprived people in the world. This study was undertaken to compare of the Stochastic Frontier Analysis (SFA) and the constant returns to scale (CRS) and variable returns to scale (VRS) output-oriented DEA models, based on a sample of 300 farms from the three largest enclaves of Bangladesh in 2017. However, the aim of the study was not only to compare estimates of technical efficiency obtained from the two approaches, but also to examine the determinants of inefficiency. The results from both the approaches indicated that there is a potential for increasing farm production through efficiency improvement and that farmers' age, educational level, new technology dissemination and training on crop production technology have a significant effect on efficiency. The detection and measurement of technical inefficiency and its determinants can be used as a basis of policy recommendations.

Keywords: DEA approach, previous enclaves, SFA approach, technical inefficiency

Procedia PDF Downloads 130