Search results for: receiver operating characteristic histogram
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3857

Search results for: receiver operating characteristic histogram

3617 Simulation of the Performance of the Reforming of Methane in a Primary Reformer

Authors: A. Alkattib, M. Boumaza

Abstract:

Steam reforming is industrially important as it is incorporated in several major chemical processes including the production of ammonia, methanol, hydrogen and ox alcohols. Due to the strongly endothermic nature of the process, a large amount of heat is supplied by fuel burning (commonly natural gas) in the furnace chamber. Reaction conversions, tube catalyst life, energy consumption and CO2 emission represent the principal factors affecting the performance of this unit and are directly influenced by the high operating temperatures and pressures. This study presents a simulation of the performance of the reforming of methane in a primary reformer, through a developed empirical relation which enables to investigate the effects of operating parameters such as the pressure, temperature, steam to carbon ratio on the production of hydrogen, as well as the fraction of non-converted methane. It appears from this analysis that the exit temperature Te, the operating pressure as well the steam to carbon ratio has an important effect on the reforming of methane.

Keywords: reforming, methane, performance, hydrogen, parameters

Procedia PDF Downloads 191
3616 A Segmentation Method for Grayscale Images Based on the Firefly Algorithm and the Gaussian Mixture Model

Authors: Donatella Giuliani

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In this research, we propose an unsupervised grayscale image segmentation method based on a combination of the Firefly Algorithm and the Gaussian Mixture Model. Firstly, the Firefly Algorithm has been applied in a histogram-based research of cluster means. The Firefly Algorithm is a stochastic global optimization technique, centered on the flashing characteristics of fireflies. In this context it has been performed to determine the number of clusters and the related cluster means in a histogram-based segmentation approach. Successively these means are used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The parametric probability density function of a Gaussian Mixture Model is represented as a weighted sum of Gaussian component densities, whose parameters are evaluated applying the iterative Expectation-Maximization technique. The coefficients of the linear super-position of Gaussians can be thought as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities have been evaluated, therefore their maxima are used to assign each pixel to the clusters, according to their gray-level values. The proposed approach appears fairly solid and reliable when applied even to complex grayscale images. The validation has been performed by using different standard measures, more precisely: the Root Mean Square Error (RMSE), the Structural Content (SC), the Normalized Correlation Coefficient (NK) and the Davies-Bouldin (DB) index. The achieved results have strongly confirmed the robustness of this gray scale segmentation method based on a metaheuristic algorithm. Another noteworthy advantage of this methodology is due to the use of maxima of responsibilities for the pixel assignment that implies a consistent reduction of the computational costs.

Keywords: clustering images, firefly algorithm, Gaussian mixture model, meta heuristic algorithm, image segmentation

Procedia PDF Downloads 189
3615 Photovoltaic Cells Characteristics Measurement Systems

Authors: Rekioua T., Rekioua D., Aissou S., Ouhabi A.

Abstract:

Power provided by the photovoltaic array varies with solar radiation and temperature, since these parameters influence the electrical characteristic (Ipv-Vpv) of solar cells. In Scientific research, there are different methods to obtain these characteristics. In this paper, we present three methods. A simulation one using Matlab/Simulink. The second one is the standard experimental voltage method and the third one is by using LabVIEW software. This latter is based on an electronic circuit to test PV modules. All details of this electronic schemes are presented and obtained results of the three methods with a comparison and under different meteorological conditions are presented. The proposed method is simple and very efficiency for testing and measurements of electrical characteristic curves of photovoltaic panels.

Keywords: photovoltaic cells, measurement standards, temperature sensors, data acquisition

Procedia PDF Downloads 429
3614 Electrodynamic Principles for Generation and Wireless Transfer of Energy

Authors: Steven D. P. Moore

Abstract:

An electrical discharge in the air induces an electromagnetic (EM) wave capable of wireless transfer, reception, and conversion back into electrical discharge at a distant location. Following Norton’s ground wave principles, EM wave radiation (EMR) runs parallel to the Earth’s surface. Energy in an EMR wave can move through the air and be focused to create a spark at a distant location, focused by a receiver to generate a local electrical discharge. This local discharge can be amplified and stored but also has the propensity to initiate another EMR wave. In addition to typical EM waves, lightning is also associated with atmospheric events, trans-ionospheric pulse pairs, the most powerful natural EMR signal on the planet. With each lightning strike, regardless of global position, it generates naturally occurring pulse-pairs that are emitted towards space within a narrow cone. An EMR wave can self-propagate, travel at the speed of light, and, if polarized, contain vector properties. If this reflective pulse could be directed by design through structures that have increased probabilities for lighting strikes, it could theoretically travel near the surface of the Earth at light speed towards a selected receiver for local transformation into electrical energy. Through research, there are several influencing parameters that could be modified to model, test, and increase the potential for adopting this technology towards the goal of developing a global grid that utilizes natural sources of energy.

Keywords: electricity, sparkgap, wireless, electromagnetic

Procedia PDF Downloads 163
3613 Research on the Risks of Railroad Receiving and Dispatching Trains Operators: Natural Language Processing Risk Text Mining

Authors: Yangze Lan, Ruihua Xv, Feng Zhou, Yijia Shan, Longhao Zhang, Qinghui Xv

Abstract:

Receiving and dispatching trains is an important part of railroad organization, and the risky evaluation of operating personnel is still reflected by scores, lacking further excavation of wrong answers and operating accidents. With natural language processing (NLP) technology, this study extracts the keywords and key phrases of 40 relevant risk events about receiving and dispatching trains and reclassifies the risk events into 8 categories, such as train approach and signal risks, dispatching command risks, and so on. Based on the historical risk data of personnel, the K-Means clustering method is used to classify the risk level of personnel. The result indicates that the high-risk operating personnel need to strengthen the training of train receiving and dispatching operations towards essential trains and abnormal situations.

Keywords: receiving and dispatching trains, natural language processing, risk evaluation, K-means clustering

Procedia PDF Downloads 43
3612 Economic Impacts of Nitrogen Fertilizer Use into Tropical Pastures for Beef Cattle in Brazil

Authors: Elieder P. Romanzini, Lutti M. Delevatti, Rhaony G. Leite, Ricardo A. Reis, Euclides B. Malheiros

Abstract:

Brazilian beef cattle production systems are an important profitability source for the national gross domestic product. The main characteristic of these systems is forage utilization as the exclusive feed source. Forage utilization had been causing on owners the false feeling of low production costs. However, this low cost is followed to low profit causing a lot times worst animal index what can result in activities changes or until land sold. Aiming to evaluate economic impacts into Brazilian beef cattle systems were evaluated four nitrogen fertilizer (N) application levels (0, 90, 180 and 270 kg per hectare [kg.ha-1]). Research was developed during 2015 into Forage Crops and Grasslands section of São Paulo State University, “Júlio de Mesquita Filho” (Unesp) (Jaboticabal, São Paulo, Brazil). Pastures were seeded with Brachiaria brizantha Stapf. ‘Marandu’ (Palisade grass) handled using continuous grazing system, with variable stocking rate, sward height maintained at 25 cm. The economic evaluation was developed in rearing e finishing phases. We evaluated the cash flows inside each phase on different N levels. Economic valuations were considering: cost-effective operating (CEO), cost-total operating (CTO), gross revenue (GR), operating profit (OP) and net income (NI), every measured in US$. Complementary analyses were developed, profitability was calculated by [OP/GR]. Pay back (measured in years) was calculated considering average capital stocktaking pondered by area in use (ACS) divided by [GR-CEO]. And the internal rate of return (IRR) was calculated by 100/(pay back). Input prices were prices during 2015 and were obtained from Anuário Brasileiro da Pecuária, Centro de Estudos Avançados em Economia Aplicada and quotation in the same region of animal production (northeast São Paulo State) during the period above mentioned. Values were calculated in US$ according exchange rate US$1.00 equal R$3.34. The CEO, CTO, GR, OP and NI per hectare for each N level were respectively US$1,919.66; US$2,048.47; US$2,905.72; US$857.25 and US$986.06 to 0 kg.ha-1; US$2,403.20; US$2,551.80; US$3,530.19; US$978.39 and US$1,126.99 to 90 kg.ha-1; US$3,180.42; US$3,364.81; US$4,985.03; US$1,620.23 and US$1,804.62 to 180 kg.ha-1andUS$3,709.14; US$3,915.15; US$5,554.95; US$1,639.80 and US$1,845.81 to 270 kg.ha-1. Relationship to another economic indexes, profitability, pay back and IRR, the results were respectively 29.50%, 6.44 and 15.54% to 0 kg.ha-1; 27.72%, 6.88 and 14.54% to 90 kg.ha-1; 32.50%, 4.08 and 24.50% to 180 kg.ha-1 and 29.52%, 3.42 and 29.27% to 270 kg.ha-1. Values previously presented in this evaluation allowing to affirm that the best result was obtained to N level 270 kg.ha-1. These results among all N levels evaluated could be explained by improve occurred on stocking rate caused by increase on N level. However, a crucial information about high N level application into pastures is the efficiency of N utilization (associated to environmental impacts) that normally decrease with the increase on N level. Hence, considering all situations (efficiency of N utilization and economic results) into tropical pastures used to beef cattle production could be recommended N level equal to 180kg.ha-1, which had better profitability and cause lesser environmental impacts, proved by other studies developed in the same area.

Keywords: Brachiaria brizantha, cost-total operating, gross revenue, profitability

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3611 Preliminary Study on Using of Thermal Energy from Effluent Water for the SBR Process of RO

Authors: Gyeong-Sung Kim, In-soo Ahn, Yong Cho

Abstract:

SBR (Sequencing Batch Reactor) process is usually applied to membrane water treatment plants to treat its concentrated wastewater. The role of SBR process is to remove COD (Chemical Oxygen Demand) and NH3 from wastewater before discharging it outside of the water treatment plant using microorganism. Microorganism’s nitrification capability is influenced by water temperature because the nitrification rate of the concentrated wastewater becomes ‘zero’ as water temperature approach 0℃. Heating system is necessary to operate SBR in winter season even though the operating cost increase sharply. The operating cost of SBR at ‘D’ RO water treatment plant in Korea was 51.8 times higher in winter (October to March) compare to summer (April to September) season in 2014. Otherwise the effluent water temperature maintained around 8℃ constantly in winter. This study focuses on application heat pump system to recover the thermal energy from the effluent water of ‘D’ RO plant so that the operating cost will be reduced.

Keywords: water treatment, water thermal energy, energy saving, RO, SBR

Procedia PDF Downloads 488
3610 Computational Fluids Dynamics Investigation of the Effect of Geometric Parameters on the Ejector Performance

Authors: Michel Wakim, Rodrigo Rivera Tinoco

Abstract:

Supersonic ejector is an economical device that use high pressure vapor to compress a low pressure vapor without any rotating parts or external power sources. Entrainment ratio is a major characteristic of the ejector performance, so the ejector performance is highly dependent on its geometry. The aim of this paper is to design ejector geometry, based on pre-specified operating conditions, and to study the flow behavior inside the ejector by using computational fluid dynamics ‘CFD’ by using ‘ANSYS FLUENT 15.0’ software. In the first section; 1-D mathematical model is carried out to predict the ejector geometry. The second part describes the flow behavior inside the designed model. CFD is the most reliable tool to reveal the mixing process at different parts of the supersonic turbulent flow and to study the effect of the geometry on the effective ejector area. Finally, the results show the effect of the geometry on the entrainment ratio.

Keywords: computational fluids dynamics, ejector, entrainment ratio, geometry optimization, performance

Procedia PDF Downloads 246
3609 Enhancing Financial Security: Real-Time Anomaly Detection in Financial Transactions Using Machine Learning

Authors: Ali Kazemi

Abstract:

The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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3608 Parametric Study on Water-Cooling Plates to Improve Cooling Performance on 18650 Li-Ion Battery

Authors: Raksit Nanthatanti, Jarruwat Charoensuk, S. Hirai, Manop Masomtop

Abstract:

In this study, the effect of channel geometry and operating circumstances on a liquid cooling plate for Lithium-ion Battery modules has been investigated Inlet temperature, water velocity, and channel count were the main factors. According to the passage, enhancing the number of cooling channels[2,3,4,6channelperbases] will affect water flow distribution caused by varying the velocity inlet inside the cooling block[0.5,1.0,1.5,2.0 m/sec] and intake temperatures[25,30,35,40oC], The findings indicate that the battery’s temperature drops as the number of channels increases. The maximum battery's operating temperature [45 oC] rises, but ∆t is needed to be less than 5 oC [v≤1m/sec]. Maximum temperature and local temperature difference of the battery change significantly with the change of the velocity inlet in the cooling channel and its thermal conductivity. The results of the simulation will help to increase cooling efficiency on the cooling system for Li-ion Battery based on a Mini channel in a liquid-cooling configuration

Keywords: cooling efficiency, channel count, lithium-ion battery, operating

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3607 The Effect of Psychological Capital and Psychological Empowerment on Employees' Commitment to Change

Authors: Muthmainah Mufidah, Wustari L. H. Mangundjaya

Abstract:

Organizations nowadays have to change and adjust themselves to the changing external environment in order to survive the globalization era. However, not all the organizational change had been succeeded. Commitment to change is one important factor why the change process often failed. Even so, this commitment to change cannot be separated with the individual’s characteristic. The aim of this study is to identify the role of psychological capital and psychological empowerment as the individual’s positive characteristic on commitment to change. This research was conducted on Indonesian employees who have or are currently experiencing a change in their organization. Data was collected using Commitment to Change Inventory, Psychological Empowerment Questionnaire, and Psychological Capital Questionnaire. The results showed that both psychological capital and psychological empowerment have a positive and significant influence on commitment to change.

Keywords: commitment to change, psychological capital, psychological empowerment, organizational change

Procedia PDF Downloads 283
3606 Modeling and Optimal Control of Acetylene Catalytic Hydrogenation Reactor in Olefin Plant by Artificial Neural Network

Authors: Faezeh Aghazadeh, Mohammad Javad Sharifi

Abstract:

The application of neural networks to model a full-scale industrial acetylene hydrogenation in olefin plant has been studied. The operating variables studied are the, input-temperature of the reactor, output-temperature of the reactor, hydrogen ratio of the reactor, [C₂H₂]input, and [C₂H₆]input. The studied operating variables were used as the input to the constructed neural network to predict the [C₂H₆]output at any time as the output or the target. The constructed neural network was found to be highly precise in predicting the quantity of [C₂H₆]output for the new input data, which are kept unaware of the trained neural network showing its applicability to determine the [C₂H₆]output for any operating conditions. The enhancement of [C₂H₆]output as compared with [C₂H₆]input was a consequence of low selective acetylene hydrogenation to ethylene.

Keywords: acetylene hydrogenation, Pd-Ag/Al₂O₃, artificial neural network, modeling, optimal design

Procedia PDF Downloads 237
3605 An Exploratory Study on 'Sub-Region Life Circle' in Chinese Big Cities Based on Human High-Probability Daily Activity: Characteristic and Formation Mechanism as a Case of Wuhan

Authors: Zhuoran Shan, Li Wan, Xianchun Zhang

Abstract:

With an increasing trend of regionalization and polycentricity in Chinese contemporary big cities, “sub-region life circle” turns to be an effective method on rational organization of urban function and spatial structure. By the method of questionnaire, network big data, route inversion on internet map, GIS spatial analysis and logistic regression, this article makes research on characteristic and formation mechanism of “sub-region life circle” based on human high-probability daily activity in Chinese big cities. Firstly, it shows that “sub-region life circle” has been a new general spatial sphere of residents' high-probability daily activity and mobility in China. Unlike the former analysis of the whole metropolitan or the micro community, “sub-region life circle” has its own characteristic on geographical sphere, functional element, spatial morphology and land distribution. Secondly, according to the analysis result with Binary Logistic Regression Model, the research also shows that seven factors including land-use mixed degree and bus station density impact the formation of “sub-region life circle” most, and then analyzes the index critical value of each factor. Finally, to establish a smarter “sub-region life circle”, this paper indicates that several strategies including jobs-housing fit, service cohesion and space reconstruction are the keys for its spatial organization optimization. This study expands the further understanding of cities' inner sub-region spatial structure based on human daily activity, and contributes to the theory of “life circle” in urban's meso-scale.

Keywords: sub-region life circle, characteristic, formation mechanism, human activity, spatial structure

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3604 Failure Analysis of Electrode, Nozzle Plate, and Powder Injector during Air Plasma Spray Coating

Authors: Nemes Alexandra

Abstract:

The aim of the research is to develop an optimum microstructure of steel coatings on aluminum surfaces for application on the crankcase cylinder bores. For the proper design of the microstructure of the coat, it is important to control the plasma gun unit properly. The maximum operating time was determined while the plasma gun could optimally work before its destruction. Objectives: The aim of the research is to determine the optimal operating time of the plasma gun between renovations (the renovation shall involve the replacement of the test components of the plasma gun: electrode, nozzle plate, powder injector. Methodology: Plasma jet and particle flux analysis with PFI (PFI is a diagnostic tool for all kinds of thermal spraying processes), CT reconstruction and analysis on the new and the used plasma guns, failure analysis of electrodes, nozzle plates, and powder injectors, microscopic examination of the microstructure of the coating. Contributions: As the result of the failure analysis detailed above, the use of the plasma gun was maximized at 100 operating hours in order to get optimal microstructure for the coat.

Keywords: APS, air plasma spray, failure analysis, electrode, nozzle plate, powder injector

Procedia PDF Downloads 79
3603 Reduction of Defects Using Seven Quality Control Tools for Productivity Improvement at Automobile Company

Authors: Abdul Sattar Jamali, Imdad Ali Memon, Maqsood Ahmed Memon

Abstract:

Quality of production near to zero defects is an objective of every manufacturing and service organization. In order to maintain and improve the quality by reduction in defects, Statistical tools are being used by any organizations. There are many statistical tools are available to assess the quality. Keeping in view the importance of many statistical tools, traditional 7QC tools has been used in any manufacturing and automobile Industry. Therefore, the 7QC tools have been successfully applied at one of the Automobile Company Pakistan. Preliminary survey has been done for the implementation of 7QC tool in the assembly line of Automobile Industry. During preliminary survey two inspection points were decided to collect the data, which are Chassis line and trim line. The data for defects at Chassis line and trim line were collected for reduction in defects which ultimately improve productivity. Every 7QC tools has its benefits observed from the results. The flow charts developed for better understanding about inspection point for data collection. The check sheets developed for helps for defects data collection. Histogram represents the severity level of defects. Pareto charts show the cumulative effect of defects. The Cause and Effect diagrams developed for finding the root causes of each defects. Scatter diagram developed the relation of defects increasing or decreasing. The P-Control charts developed for showing out of control points beyond the limits for corrective actions. The successful implementation of 7QC tools at the inspection points at Automobile Industry concluded that the considerable amount of reduction on defects level, as in Chassis line from 132 defects to 13 defects. The total 90% defects were reduced in Chassis Line. In Trim line defects were reduced from 157 defects to 28 defects. The total 82% defects were reduced in Trim Line. As the Automobile Company exercised only few of the 7 QC tools, not fully getting the fruits by the application of 7 QC tools. Therefore, it is suggested the company may need to manage a mechanism for the application of 7 QC tools at every section.

Keywords: check sheet, cause and effect diagram, control chart, histogram

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3602 Proficient Estimation Procedure for a Rare Sensitive Attribute Using Poisson Distribution

Authors: S. Suman, G. N. Singh

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The present manuscript addresses the estimation procedure of population parameter using Poisson probability distribution when characteristic under study possesses a rare sensitive attribute. The generalized form of unrelated randomized response model is suggested in order to acquire the truthful responses from respondents. The resultant estimators have been proposed for two situations when the information on an unrelated rare non-sensitive characteristic is known as well as unknown. The properties of the proposed estimators are derived, and the measure of confidentiality of respondent is also suggested for respondents. Empirical studies are carried out in the support of discussed theory.

Keywords: Poisson distribution, randomized response model, rare sensitive attribute, non-sensitive attribute

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3601 Flow Characteristic Analysis for Hatch Type Air Vent Head of Bulk Cargo Ship by Computational Fluid Dynamics

Authors: Hanik Park, Kyungsook Jeon, Suchul Shin, Youngchul Park

Abstract:

The air vent head prevents the inflow of seawater into the cargo holds when it is used for the ballast tank on heavy weather. In this study, the flow characteristics and the grid size were created by the application of Computational Fluid Dynamics by taking into the consideration of comparison of test results. Then, the accuracy of the analysis was verified by comparing with experimental results. Based on this analysis, accurate turbulence model and grid size can be selected. Thus, the design characteristic of air vent head for bulk carrier contributes the reliability based on the research results.

Keywords: bulk carrier, FEM, SST, vent

Procedia PDF Downloads 493
3600 Robust Fuzzy PID Stabilizer: Modified Shuffled Frog Leaping Algorithm

Authors: Oveis Abedinia, Noradin Ghadimi, Nasser Mikaeilvand, Roza Poursoleiman, Asghar Poorfaraj

Abstract:

In this paper a robust Fuzzy Proportional Integral Differential (PID) controller is applied to multi-machine power system based on Modified Shuffled Frog Leaping (MSFL) algorithm. This newly proposed controller is more efficient because it copes with oscillations and different operating points. In this strategy the gains of the PID controller is optimized using the proposed technique. The nonlinear problem is formulated as an optimization problem for wide ranges of operating conditions using the MSFL algorithm. The simulation results demonstrate the effectiveness, good robustness and validity of the proposed method through some performance indices such as ITAE and FD under wide ranges operating conditions in comparison with TS and GSA techniques. The single-machine infinite bus system and New England 10-unit 39-bus standard power system are employed to illustrate the performance of the proposed method.

Keywords: fuzzy PID, MSFL, multi-machine, low frequency oscillation

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3599 Predicting Suicidal Behavior by an Accurate Monitoring of RNA Editing Biomarkers in Blood Samples

Authors: Berengere Vire, Nicolas Salvetat, Yoann Lannay, Guillaume Marcellin, Siem Van Der Laan, Franck Molina, Dinah Weissmann

Abstract:

Predicting suicidal behaviors is one of the most complex challenges of daily psychiatric practices. Today, suicide risk prediction using biological tools is not validated and is only based on subjective clinical reports of the at-risk individual. Therefore, there is a great need to identify biomarkers that would allow early identification of individuals at risk of suicide. Alterations of adenosine-to-inosine (A-to-I) RNA editing of neurotransmitter receptors and other proteins have been shown to be involved in etiology of different psychiatric disorders and linked to suicidal behavior. RNA editing is a co- or post-transcriptional process leading to a site-specific alteration in RNA sequences. It plays an important role in the epi transcriptomic regulation of RNA metabolism. On postmortem human brain tissue (prefrontal cortex) of depressed suicide victims, Alcediag found specific alterations of RNA editing activity on the mRNA coding for the serotonin 2C receptor (5-HT2cR). Additionally, an increase in expression levels of ADARs, the RNA editing enzymes, and modifications of RNA editing profiles of prime targets, such as phosphodiesterase 8A (PDE8A) mRNA, have also been observed. Interestingly, the PDE8A gene is located on chromosome 15q25.3, a genomic region that has recurrently been associated with the early-onset major depressive disorder (MDD). In the current study, we examined whether modifications in RNA editing profile of prime targets allow identifying disease-relevant blood biomarkers and evaluating suicide risk in patients. To address this question, we performed a clinical study to identify an RNA editing signature in blood of depressed patients with and without the history of suicide attempts. Patient’s samples were drawn in PAXgene tubes and analyzed on Alcediag’s proprietary RNA editing platform using next generation sequencing technology. In addition, gene expression analysis by quantitative PCR was performed. We generated a multivariate algorithm comprising various selected biomarkers to detect patients with a high risk to attempt suicide. We evaluated the diagnostic performance using the relative proportion of PDE8A mRNA editing at different sites and/or isoforms as well as the expression of PDE8A and the ADARs. The significance of these biomarkers for suicidality was evaluated using the area under the receiver-operating characteristic curve (AUC). The generated algorithm comprising the biomarkers was found to have strong diagnostic performances with high specificity and sensitivity. In conclusion, we developed tools to measure disease-specific biomarkers in blood samples of patients for identifying individuals at the greatest risk for future suicide attempts. This technology not only fosters patient management but is also suitable to predict the risk of drug-induced psychiatric side effects such as iatrogenic increase of suicidal ideas/behaviors.

Keywords: blood biomarker, next-generation-sequencing, RNA editing, suicide

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3598 Toward Indoor and Outdoor Surveillance using an Improved Fast Background Subtraction Algorithm

Authors: El Harraj Abdeslam, Raissouni Naoufal

Abstract:

The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes in variance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: video surveillance, background subtraction, contrast limited histogram equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes

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3597 Supply and Marketing of Floriculture in Ethiopia

Authors: Assefa Mitike Janko, Gosa Alemu

Abstract:

The review of supply and marketing of floriculture in Ethiopia was conducted to analyses the production potential and to know the marketing share of the country. The data was collected from secondary and primary. Ethiopia has been operating in the floriculture industry for over 20 years. As is the case in many developing countries, the major export items of Ethiopia are dominated by few agricultural products that earn very small amounts in the international market. Moreover, most of the exports are destined to only few countries. Given the highly capital intensive nature of production and processing, rose farming is not a smallholder activity. It is also important to note the extremely tightly controlled time dimension of the logistics process, given the product attributes desired and the fragility and perishability of the roses. Another characteristic of the Ethiopian floriculture sector is the lack of domestically produced inputs that flower producers can access. The export volume and value of cut-flowers accounts for a small proportion of the total exports of Ethiopia. In recent years the sector is showing improvements in terms of the quality and quantity of exports to the international market.

Keywords: roses, production, value chain, floriculture, supply

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3596 Seashore Debris Detection System Using Deep Learning and Histogram of Gradients-Extractor Based Instance Segmentation Model

Authors: Anshika Kankane, Dongshik Kang

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Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.

Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching

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3595 A Study on Improvement of the Electromagnetic Vibration of a Polygon Mirror Scanner Motor

Authors: Yongmin You

Abstract:

Electric machines for office automation device such as printer and scanner have been required the low noise and vibration performance. Many researches about the low noise and vibration of polygon mirror scanner motor have been also progressed. The noise and vibration of polygon mirror scanner motor can be classified by aerodynamic, structural and electromagnetic. Electromagnetic noise and vibration can be occurred by high cogging torque and nonsinusoidal back EMF. To improve the cogging torque and back EMF characteristic, we apply unequal air-gap. To analyze characteristic of a polygon mirror scanner motor, two dimensional finite element method is used. To minimize the cogging torque of a polygon mirror motor, Kriging based on latin hypercube sampling (LHS) is utilized. Compared to the initial model, the torque ripple of the optimized unequal air-gap model was reduced by 23.4 % while maintaining the back EMF and average torque. To verify the optimal design results, the experiment was performed. We measured the vibration in motors at 23,600 rpm which is the rated velocity. The radial and axial gravitational acceleration of the optimal model were declined more than seven times and three times, respectively. From these results, a shape optimized unequal polygon mirror scanner motor has shown the usefulness of an improvement in the torque ripple and electromagnetic vibration characteristic.

Keywords: polygon mirror scanner motor, optimal design, finite element method, vibration

Procedia PDF Downloads 313
3594 Expert System: Debugging Using MD5 Process Firewall

Authors: C. U. Om Kumar, S. Kishore, A. Geetha

Abstract:

An Operating system (OS) is software that manages computer hardware and software resources by providing services to computer programs. One of the important user expectations of the operating system is to provide the practice of defending information from unauthorized access, disclosure, modification, inspection, recording or destruction. Operating system is always vulnerable to the attacks of malwares such as computer virus, worm, Trojan horse, backdoors, ransomware, spyware, adware, scareware and more. And so the anti-virus software were created for ensuring security against the prominent computer viruses by applying a dictionary based approach. The anti-virus programs are not always guaranteed to provide security against the new viruses proliferating every day. To clarify this issue and to secure the computer system, our proposed expert system concentrates on authorizing the processes as wanted and unwanted by the administrator for execution. The Expert system maintains a database which consists of hash code of the processes which are to be allowed. These hash codes are generated using MD5 message-digest algorithm which is a widely used cryptographic hash function. The administrator approves the wanted processes that are to be executed in the client in a Local Area Network by implementing Client-Server architecture and only the processes that match with the processes in the database table will be executed by which many malicious processes are restricted from infecting the operating system. The add-on advantage of this proposed Expert system is that it limits CPU usage and minimizes resource utilization. Thus data and information security is ensured by our system along with increased performance of the operating system.

Keywords: virus, worm, Trojan horse, back doors, Ransomware, Spyware, Adware, Scareware, sticky software, process table, MD5, CPU usage and resource utilization

Procedia PDF Downloads 388
3593 An Experimental Study on the Optimum Installation of Fire Detector for Early Stage Fire Detecting in Rack-Type Warehouses

Authors: Ki Ok Choi, Sung Ho Hong, Dong Suck Kim, Don Mook Choi

Abstract:

Rack type warehouses are different from general buildings in the kinds, amount, and arrangement of stored goods, so the fire risk of rack type warehouses is different from those buildings. The fire pattern of rack type warehouses is different in combustion characteristic and storing condition of stored goods. The initial fire burning rate is different in the surface condition of materials, but the running time of fire is closely related with the kinds of stored materials and stored conditions. The stored goods of the warehouse are consisted of diverse combustibles, combustible liquid, and so on. Fire detection time may be delayed because the residents are less than office and commercial buildings. If fire detectors installed in rack type warehouses are inadaptable, the fire of the warehouse may be the great fire because of delaying of fire detection. In this paper, we studied what kinds of fire detectors are optimized in early detecting of rack type warehouse fire by real-scale fire tests. The fire detectors used in the tests are rate of rise type, fixed type, photo electric type, and aspirating type detectors. We considered optimum fire detecting method in rack type warehouses suggested by the response characteristic and comparative analysis of the fire detectors.

Keywords: fire detector, rack, response characteristic, warehouse

Procedia PDF Downloads 713
3592 Educating Children with the Child-Friendly Smartphone Operation System

Authors: Wildan Maulana Wildan, Siti Annisa Rahmayani Icha

Abstract:

Nowadays advances in information technology are needed by all the inhabitants of the earth for the sake of ease all their work, but it is worth to introduced the technological advances in the world of children. Before the technology is growing rapidly, children busy with various of traditional games and have high socialization. Moreover, after it presence, almost all of children spend more their time for playing gadget, It can affect the education of children and will change the character and personality children. However, children also can not be separated with the technology. Because the technology insight knowledge of children will be more extensive. Because the world can not be separated with advances in technology as well as with children, there should be developed a smartphone operating system that is child-friendly. The operating system is able to filter contents that do not deserve children, even in this system there is a reminder of a time study, prayer time and play time for children and there are interactive contents that will help the development of education and children's character. Children need technology, and there are some ways to introduce it to children. We must look at the characteristics of children in different environments. Thus advances in technology can be beneficial to the world children and their parents, and educators do not have to worry about advances in technology. We should be able to take advantage of advances in technology best possible.

Keywords: information technology, smartphone operating system, education, character

Procedia PDF Downloads 474
3591 A Survey on Routh-Hurwitz Stability Criterion

Authors: Mojtaba Hakimi-Moghaddam

Abstract:

Routh-Hurwitz stability criterion is a powerful approach to determine stability of linear time invariant systems. On the other hand, applying this criterion to characteristic equation of a system, whose stability or marginal stability can be determined. Although the command roots (.) of MATLAB software can be easily used to determine the roots of a polynomial, the characteristic equation of closed loop system usually includes parameters, so software cannot handle it; however, Routh-Hurwitz stability criterion results the region of parameter changes where the stability is guaranteed. Moreover, this criterion has been extended to characterize the stability of interval polynomials as well as fractional-order polynomials. Furthermore, it can help us to design stable and minimum-phase controllers. In this paper, theory and application of this criterion will be reviewed. Also, several illustrative examples are given.

Keywords: Hurwitz polynomials, Routh-Hurwitz stability criterion, continued fraction expansion, pure imaginary roots

Procedia PDF Downloads 283
3590 TACTICAL: Ram Image Retrieval in Linux Using Protected Mode Architecture’s Paging Technique

Authors: Sedat Aktas, Egemen Ulusoy, Remzi Yildirim

Abstract:

This article explains how to get a ram image from a computer with a Linux operating system and what steps should be followed while getting it. What we mean by taking a ram image is the process of dumping the physical memory instantly and writing it to a file. This process can be likened to taking a picture of everything in the computer’s memory at that moment. This process is very important for tools that analyze ram images. Volatility can be given as an example because before these tools can analyze ram, images must be taken. These tools are used extensively in the forensic world. Forensic, on the other hand, is a set of processes for digitally examining the information on any computer or server on behalf of official authorities. In this article, the protected mode architecture in the Linux operating system is examined, and the way to save the image sample of the kernel driver and system memory to disk is followed. Tables and access methods to be used in the operating system are examined based on the basic architecture of the operating system, and the most appropriate methods and application methods are transferred to the article. Since there is no article directly related to this study on Linux in the literature, it is aimed to contribute to the literature with this study on obtaining ram images. LIME can be mentioned as a similar tool, but there is no explanation about the memory dumping method of this tool. Considering the frequency of use of these tools, the contribution of the study in the field of forensic medicine has been the main motivation of the study due to the intense studies on ram image in the field of forensics.

Keywords: linux, paging, addressing, ram-image, memory dumping, kernel modules, forensic

Procedia PDF Downloads 78
3589 New Modification Negative Stiffness Device with Constant Force-Displacement Characteristic for Seismic Protection of Structures

Authors: Huan Li, Jianchun Li, Yancheng Li, Yang Yu

Abstract:

As a seismic protection method of civil and engineering structures, weakening and damping is effective during the elastic region, while it somehow leads to the early yielding of the entire structure accompanying with large excursions and permanent deformations. Adaptive negative stiffness device is attractive for realizing yielding property without changing the stiffness of the primary structure. In this paper, a new modification negative stiffness device (MNSD) with constant force-displacement characteristic is proposed by combining a magnetic negative stiffness spring, a piecewise linear positive spring and a passive damper with a certain adaptive stiffness device. The proposed passive control MNSD preserves no effect under small excitation. When the displacement amplitude increases beyond the pre-defined yielding point, the force-displacement characteristics of the system with MNSD will keep constant. The seismic protection effect of the MNSD is evaluated by employing it to a single-degree-of-freedom system under sinusoidal excitation, and real earthquake waves. By comparative analysis, the system with MNSD performs better on reducing acceleration and displacement response under different displacement amplitudes than the scenario without it and the scenario with unmodified certain adaptive stiffness device.

Keywords: negative stiffness, adaptive stiffness, weakening and yielding, constant force-displacement characteristic

Procedia PDF Downloads 124
3588 Stochastic Analysis of Linux Operating System through Copula Distribution

Authors: Vijay Vir Singh

Abstract:

This work is focused studying the Linux operating system connected in a LAN (local area network). The STAR topology (to be called subsystem-1) and BUS topology (to be called subsystem-2) are taken into account, which are placed at two different locations and connected to a server through a hub. In the both topologies BUS topology and STAR topology, we have assumed n clients. The system has two types of failures i.e. partial failure and complete failure. Further, the partial failure has been categorized as minor and major partial failure. It is assumed that the minor partial failure degrades the sub-systems and the major partial failure make the subsystem break down mode. The system may completely fail due to failure of server hacking and blocking etc. The system is studied using supplementary variable technique and Laplace transform by using different types of failure and two types of repair. The various measures of reliability for example, availability of system, reliability of system, MTTF, profit function for different parametric values have been discussed.

Keywords: star topology, bus topology, blocking, hacking, Linux operating system, Gumbel-Hougaard family copula, supplementary variable

Procedia PDF Downloads 335