Search results for: dimension reducing distribution load flow algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 17930

Search results for: dimension reducing distribution load flow algorithm

7220 Caged Compounds as Light-Dependent Initiators for Enzyme Catalysis Reactions

Authors: Emma Castiglioni, Nigel Scrutton, Derren Heyes, Alistair Fielding

Abstract:

By using light as trigger, it is possible to study many biological processes, such as the activity of genes, proteins, and other molecules, with precise spatiotemporal control. Caged compounds, where biologically active molecules are generated from an inert precursor upon laser photolysis, offer the potential to initiate such biological reactions with high temporal resolution. As light acts as the trigger for cleaving the protecting group, the ‘caging’ technique provides a number of advantages as it can be intracellular, rapid and controlled in a quantitative manner. We are developing caging strategies to study the catalytic cycle of a number of enzyme systems, such as nitric oxide synthase and ethanolamine ammonia lyase. These include the use of caged substrates, caged electrons and the possibility of caging the enzyme itself. In addition, we are developing a novel freeze-quench instrument to study these reactions, which combines rapid mixing and flashing capabilities. Reaction intermediates will be trapped at low temperatures and will be analysed by using electron paramagnetic resonance (EPR) spectroscopy to identify the involvement of any radical species during catalysis. EPR techniques typically require relatively long measurement times and very often, low temperatures to fully characterise these short-lived species. Therefore, common rapid mixing techniques, such as stopped-flow or quench-flow are not directly suitable. However, the combination of rapid freeze-quench (RFQ) followed by EPR analysis provides the ideal approach to kinetically trap and spectroscopically characterise these transient radical species. In a typical RFQ experiment, two reagent solutions are delivered to the mixer via two syringes driven by a pneumatic actuator or stepper motor. The new mixed solution is then sprayed into a cryogenic liquid or surface, and the frozen sample is then collected and packed into an EPR tube for analysis. The earliest RFQ instrument consisted of a hydraulic ram unit as a drive unit with direct spraying of the sample into a cryogenic liquid (nitrogen, isopentane or petroleum). Improvements to the RFQ technique have arisen from the design of new mixers in order to reduce both the volume and the mixing time. In addition, the cryogenic isopentane bath has been coupled to a filtering system or replaced by spraying the solution onto a surface that is frozen via thermal conductivity with a cryogenic liquid. In our work, we are developing a novel RFQ instrument which combines the freeze-quench technology with flashing capabilities to enable the studies of both thermally-activated and light-activated biological reactions. This instrument also uses a new rotating plate design based on magnetic couplings and removes the need for mechanical motorised rotation, which can otherwise be problematic at cryogenic temperatures.

Keywords: caged compounds, freeze-quench apparatus, photolysis, radicals

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7219 Traditional Terms, Spaces, Forms and Artifacts in Cultural Semiotics of Southwest Nigeria

Authors: Ajibade Adeyemo

Abstract:

The paper examined local terms used for spaces, forms and building practices in southwest Nigeria as cultural semiotics. Housing has more cultural meaning than mere shelter as shown in building terms such as ‘roof over my head’. The study is significant in the study area because its people were traditionally orally centered until ‘culture contact’ led to graphical presentation and appreciation in the form of drawings which is a modern language of architecture. This semiotic study will facilitate the understanding of the wholesomeness of traditional building practices and thoughts. This is in the culture of the traditional multi-sensory appreciation of architecture, urban design and the arts. It will analyze traditional aphoristic words and terms which are like proverbs which are significant in language because of their metaphorical essence. Many of such terms in the dominant Yoruba language of the study area are oftentimes phenomenal reducing universal terms like the earth and heaven to the simple module of housing. These words could be worth investigating because they are symbolic serve as codes which are cultural tool of regional ethnic significance. Sassure’s and Pierce’s concepts of Semiotics in line with Eco’s concept of semiotics of metaphor shall be deployed.

Keywords: traditional terms, spaces, forms, artifacts, cultural semiotics, southwest

Procedia PDF Downloads 269
7218 Integrating Wound Location Data with Deep Learning for Improved Wound Classification

Authors: Mouli Banga, Chaya Ravindra

Abstract:

Wound classification is a crucial step in wound diagnosis. An effective classifier can aid wound specialists in identifying wound types with reduced financial and time investments, facilitating the determination of optimal treatment procedures. This study presents a deep neural network-based classifier that leverages wound images and their corresponding locations to categorize wounds into various classes, such as diabetic, pressure, surgical, and venous ulcers. By incorporating a developed body map, the process of tagging wound locations is significantly enhanced, providing healthcare specialists with a more efficient tool for wound analysis. We conducted a comparative analysis between two prominent convolutional neural network models, ResNet50 and MobileNetV2, utilizing a dataset of 730 images. Our findings reveal that the RestNet50 outperforms MovileNetV2, achieving an accuracy of approximately 90%, compared to MobileNetV2’s 83%. This disparity highlights the superior capability of ResNet50 in the context of this dataset. The results underscore the potential of integrating deep learning with spatial data to improve the precision and efficiency of wound diagnosis, ultimately contributing to better patient outcomes and reducing healthcare costs.

Keywords: wound classification, MobileNetV2, ResNet50, multimodel

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7217 Seismic Response of Large-Scale Rectangular Steel-Plate Concrete Composite Shear Walls

Authors: Siamak Epackachi, Andrew S. Whittaker, Amit H. Varma

Abstract:

An experimental program on steel-plate concrete (SC) composite shear walls was executed in the NEES laboratory at the University at Buffalo. Four large-size specimens were tested under displacement-controlled cyclic loading. The design variables considered in the testing program included wall thickness, reinforcement ratio, and faceplate slenderness ratio. The aspect ratio (height-to-length) of the four walls was 1.0. Each SC wall was installed on top of a re-usable foundation block. A bolted baseplate to RC foundation connection was used for all four walls. The walls were identified to be flexure-critical. This paper presents the damage to SC walls at different drift ratios, the cyclic force-displacement relationships, energy dissipation and equivalent viscous damping ratios, the strain and stress fields in the steel faceplates and the contribution of the steel faceplates to the total shear load, the variation of vertical strain in the steel faceplates along the length of the wall, near the base, at different drift ratios, the contributions of shear, flexure, and base rotation to the total lateral displacement, the displacement ductility of the SC walls, and the cyclic secant stiffness of the four SC walls.

Keywords: steel-plate composite shear wall, safety-related nuclear structure, flexure-critical wall, cyclic loading

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7216 Novel Steviosides Analogs Induced Apoptosis in Breast Cancers

Authors: Ahmed Malki

Abstract:

Breast cancer has been identified as the most lethal form of cancer today. In our study, we designed and screened 16 steviosides derivatives for their cytotoxic activities in MCF-7human breast cancer cells and normal MCF-12a cells. Our data indicated that steviosides derivatives 9 and 15 decreased cell proliferation and induced apoptosis in MCF-7 breast cancer cells more thannormal breast cells epithelial cells. Flow cytometric analysis showed that both steviosides, derivatives 9 and 15 arrested the MCF-7 cells in G1 phase, which is further confirmed by the increased expression level of p21. Moreover, both steviosides derivatives increased caspase-9 activity, and the induction of apoptosis was significantly reduced after treating cells with caspase-9 inhibitor LEHD-CHO. Both steviosides derivatives increased Caspase 3 activities and induced Parp-1 cleavage in H1299 cells. Based on previous results, we have identified two novel steviosides derivatives which provoked apoptosis in breast cancer cells by arresting cells in G1 phase and increasing caspase-9 and caspase-3 activities which merits further development and investigations.

Keywords: steviosides, breast cancer, p53, cell cycle

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7215 The Laser Line Detection for Autonomous Mapping Based on Color Segmentation

Authors: Pavel Chmelar, Martin Dobrovolny

Abstract:

Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

Procedia PDF Downloads 426
7214 Improving Decision Support for Organ Transplant

Authors: Ian McCulloh, Andrew Placona, Darren Stewart, Daniel Gause, Kevin Kiernan, Morgan Stuart, Christopher Zinner, Laura Cartwright

Abstract:

An estimated 22-25% of viable deceased donor kidneys are discarded every year in the US, while waitlisted candidates are dying every day. As many as 85% of transplanted organs are refused at least once for a patient that scored higher on the match list. There are hundreds of clinical variables involved in making a clinical transplant decision and there is rarely an ideal match. Decision makers exhibit an optimism bias where they may refuse an organ offer assuming a better match is imminent. We propose a semi-parametric Cox proportional hazard model, augmented by an accelerated failure time model based on patient specific suitable organ supply and demand to estimate a time-to-next-offer. Performance is assessed with Cox-Snell residuals and decision curve analysis, demonstrating improved decision support for up to a 5-year outlook. Providing clinical decision makers with quantitative evidence of likely patient outcomes (e.g., time to next offer and the mortality associated with waiting) may improve decisions and reduce optimism bias, thus reducing discarded organs and matching more patients on the waitlist.

Keywords: decision science, KDPI, optimism bias, organ transplant

Procedia PDF Downloads 100
7213 Genomic Analysis of Whole Genome Sequencing of Leishmania Major

Authors: Fatimazahrae Elbakri, Azeddine Ibrahimi, Meryem Lemrani, Dris Belghyti

Abstract:

Leishmaniasis represents a major public health problem because of the number of cases recorded each year and the wide distribution of the disease. It is a parasitic disease of flagellated protozoa transmitted by the bite of certain species of sandfly, causing a spectrum of clinical pathology in humans ranging from disfiguring skin lesions to fatal visceral leishmaniasis. Cutaneous leishmaniasis due to Leishmania major is a polymorphic disease; in fact, the infection can be asymptomatic, localized, or disseminated. The objective of this work is to determine the genomic diversity that contributes to clinical variability by trying to identify the variation in chromosome number and to extract SNPs and SNPs and InDels; it is based on four sequences (WGS) of Leishmania major available on NCBI in Fastq form, from three countries: Tunisia, Algeria, and Israel, the analysis is set up from a pipeline to facilitate the discovery of genetic diversity, in particular SNP and chromosomal somy.

Keywords: Leshmania major, cutaneous Leishmania, NGS, genomic, somy, variant calling

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7212 A Portable Device for Pulse Wave Velocity Measurements

Authors: Chien-Lin Wang, Cha-Ling Ko, Tainsong Chen

Abstract:

Pulse wave velocity (PWV) of blood flow provides important information of vessel property and blood pressure which can be used to assess cardiovascular disease. However, the above measurements need expensive equipment, such as Doppler ultrasound, MRI, angiography etc. The photoplethysmograph (PPG) signals are commonly utilized to detect blood volume changes. In this study, two infrared (IR) probes are designed and placed at a fixed distance from finger base and fingertip. An analog circuit with automatic gain adjustment is implemented to get the stable original PPG signals from above two IR probes. In order to obtain the time delay precisely between two PPG signals, we obtain the pulse transit time from the second derivative of the original PPG signals. To get a portable, wireless and low power consumption PWV measurement device, the low energy Bluetooth 4.0 (BLE) and the microprocessor (Cortex™-M3) are used in this study. The PWV is highly correlated with blood pressure. This portable device has potential to be used for continuous blood pressure monitoring.

Keywords: pulse wave velocity, photoplethysmography, portable device, biomedical engineering

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7211 Friction and Wear Behavior of Zr-Nb Alloy Under Different Conditions

Authors: Bharat Kumar, Deepak Kumar, Vijay Chaudhry

Abstract:

Zirconium alloys are generally used for designing the core components of nuclear reactors due to their good mechanical and tribological properties. Some core components are subjected to flow-induced vibrations resulting in wear of these components due to their interaction with one another. To simulate these conditions, low amplitude reciprocating wear tests are conducted at room temperature and high temperature (260 degrees Celsius) between Zr-2.5Nb alloy and SS-410. The tests are conducted at a frequency range of 5 Hz to 25 Hz and an amplitude range of 200 µm to 600 µm. Friction and wear responses were recorded and correlated with the change in parameters. Worn surfaces are analysed using scanning electron microscopy (SEM) and optical profilometer. Elemental changes on the worn surfaces were determined using energy dispersive spectroscopy (EDS). The coefficient of friction (COF) increases with increasing temperature and decreases with increasing frequency. Adhesive wear is found to be the dominant wear mechanism which increases at high temperature.

Keywords: nuclear reactor, Zr-2.5Nb, SS-410, friction and wear

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7210 Measuring Corruption from Public Justifications: Insights from the Brazilian Anti-Corruption Agency

Authors: Ana Luiza Aranha

Abstract:

This paper contributes to the discussions that consider corruption as a challenge to the establishment of more democratically inclusive societies in Latin America. The paper advocates an intrinsic connection between democratic principles and corruption control – it is only possible to achieve just forms of democratic life if accountability institutions are able to control corruption, and therefore control the political exclusions that it brings. Departing from a non-trivial approach to corruption, and recognizing a gap in democratic theory when thinking about this phenomenon, corruption is understood as the breakdown of the democratic inclusive rule, whereby political decisions are made (and actions were taken) in spite of those potentially affected by them. Based on this idea, this paper proposes a new way of measuring corruption, moving away from usual aggregate measures – such as the Corruption Perception Index – and case studies of corruption scandals. The main argument sustains that corruption is intrinsically connected with the ability to be accountable and to provide public justification for the political conduct. The point advocated is that corruption involves a dimension of political exclusion. It generates a private benefit which is, from a democratic point of view, illegitimate, since it benefits some at the expense of the decisions made by the political community. Corruption is then a form of exclusion based on deception and opacity - for corruption, there is no plausible justification. Empirically, the paper uses the audit reports produced by the Brazilian anti-corruption agency (the CGU - Office of the Comptroller General) in its Inspections From Public Lotteries Program to exemplify how we can use this definition to separate corruption cases from mismanagement irregularities. On one side, there is poor management and inefficiencies, and, on the other, corruption, defined by the implausibility of public justifications – because the public officials would have to publicize illegitimate privileges and undue advantages. CGU reports provide the justifications given by the public officials for the irregularities found and also the acceptance or not by the control agency of these justifications. The analysis of this dialogue – between public officials and control agents – makes it possible to divide the irregularities on those that can be publicly justified versus those that cannot. In order to hold public officials accountable for their actions, making them responsible for the exclusions that they may cause (such as corruption), the accountability institutions fulfil an important role in reinforcing and empowering democracy and its basic inclusive condition.

Keywords: accountability, brazil, corruption, democracy

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7209 Determinants of Aggregate Electricity Consumption in Ghana: A Multivariate Time Series Analysis

Authors: Renata Konadu

Abstract:

In Ghana, electricity has become the main form of energy which all sectors of the economy rely on for their businesses. Therefore, as the economy grows, the demand and consumption of electricity also grow alongside due to the heavy dependence on it. However, since the supply of electricity has not increased to match the demand, there has been frequent power outages and load shedding affecting business performances. To solve this problem and advance policies to secure electricity in Ghana, it is imperative that those factors that cause consumption to increase be analysed by considering the three classes of consumers; residential, industrial and non-residential. The main argument, however, is that, export of electricity to other neighbouring countries should be included in the electricity consumption model and considered as one of the significant factors which can decrease or increase consumption. The author made use of multivariate time series data from 1980-2010 and econometric models such as Ordinary Least Squares (OLS) and Vector Error Correction Model. Findings show that GDP growth, urban population growth, electricity exports and industry value added to GDP were cointegrated. The results also showed that there is unidirectional causality from electricity export and GDP growth and Industry value added to GDP to electricity consumption in the long run. However, in the short run, there was found to be a directional causality among all the variables and electricity consumption. The results have useful implication for energy policy makers especially with regards to electricity consumption, demand, and supply.

Keywords: electricity consumption, energy policy, GDP growth, vector error correction model

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7208 Reducing Phytic Acid in Rice Grain by Targeted Mutagenesis of a Phospholipase D Gene

Authors: Muhammad Saad Shoaib Khan, Rasbin Basnet, Qingyao Shu

Abstract:

Phospholipids are one of the major classes of lipid comprising 10% of total grain lipid in rice. Phospholipids are the main phosphorus containing lipid in the rice endosperm, contributing to rice palatability and seed storage property. However, in the rice grain, the majority of phosphorus occur in the form of phytic acid and are highly abundant in the bran. Phytic acid, also known as hexaphosphorylated inositol (IP6), are strong chelating agents which reduces the bioavailability of essential dietary nutrients and are therefore less desirable by rice breeders. We used the CRISPR/Cas9 system to generate mutants of a phospholipase D gene (PLDα1), which is responsible for the degradation of phospholipids into phosphatidic acid (PA). In the mutants, we found a significant reduction in the concentration of phytic acid in the grain as compared to the wild-type. The biochemical analysis of the PLDα1 mutants showed that the decrease in production of phosphatidic acid is due to reduced accumulation of CDP-diacylglycerolderived phosphatidylinositol (PI), ultimately leading to lower accumulation of phytic acid in mutants. These results showed that loss of function of PLD in rice leads to lower production of phytic acid, suggesting the potential application of Ospldα1 in breeding rice with less phytic acid.

Keywords: CRISPR/Cas9, phospholipase D, phytic acid, rice

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7207 Bi-Criteria Objective Network Design Model for Multi Period Multi Product Green Supply Chain

Authors: Shahul Hamid Khan, S. Santhosh, Abhinav Kumar Sharma

Abstract:

Environmental performance along with social performance is becoming vital factors for industries to achieve global standards. With a good environmental policy global industries are differentiating them from their competitors. This paper concentrates on multi stage, multi product and multi period manufacturing network. Bi-objective mathematical models for total cost and total emission for the entire forward supply chain are considered. Here five different problems are considered by varying the number of suppliers, manufacturers, and environmental levels, for illustrating the taken mathematical model. GA, and Random search are used for finding the optimal solution. The input parameters of the optimal solution are used to find the tradeoff between the initial investment by the industry and the long term benefit of the environment.

Keywords: closed loop supply chain, genetic algorithm, random search, green supply chain

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7206 Damage of Laminated Corrugated Sandwich Panels under Inclined Impact Loading

Authors: Muhammad Kamran, Xue Pu, Naveed Ahmed

Abstract:

Sandwich foam structures are efficient in impact energy absorption and making components lightweight; however their efficient use require a detailed understanding of its mechanical response. In this study, the foam core, laminated facings’ sandwich panel with internal triangular rib configuration is impacted by a spherical steel projectile at different angles using ABAQUS finite element package and damage mechanics is studied. Laminated ribs’ structure is sub-divided into three formations; all zeros, all 45 and optimized combination of zeros and 45 degrees. Impact velocity is varied from 250 m/s to 500 m/s with an increment of 50 m/s. The impact damage can significantly demolish the structural integrity and energy absorption due to fiber breakage, matrix cracking, and de-bonding. Macroscopic fracture study of the panel and core along with load-displacement responses and failure modes are the key parameters in the design of smart ballistic resistant structures. Ballistic impact characteristics of panels are studied on different speed, different inclination angles and its dependency on the base, and core materials, ribs formation, and cross-sectional spaces among them are determined. Impact momentum, penetration and kinetic energy absorption data and curves are compiled to predict the first and proximity impact in an effort to enhance the dynamic energy absorption.

Keywords: dynamic energy absorption, proximity impact, sandwich panels, impact momentum

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7205 A Background Subtraction Based Moving Object Detection Around the Host Vehicle

Authors: Hyojin Lim, Cuong Nguyen Khac, Ho-Youl Jung

Abstract:

In this paper, we propose moving object detection method which is helpful for driver to safely take his/her car out of parking lot. When moving objects such as motorbikes, pedestrians, the other cars and some obstacles are detected at the rear-side of host vehicle, the proposed algorithm can provide to driver warning. We assume that the host vehicle is just before departure. Gaussian Mixture Model (GMM) based background subtraction is basically applied. Pre-processing such as smoothing and post-processing as morphological filtering are added.We examine “which color space has better performance for detection of moving objects?” Three color spaces including RGB, YCbCr, and Y are applied and compared, in terms of detection rate. Through simulation, we prove that RGB space is more suitable for moving object detection based on background subtraction.

Keywords: gaussian mixture model, background subtraction, moving object detection, color space, morphological filtering

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7204 Traffic Calming Measures at Rural Roads in Dhofar

Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

Abstract:

Traffic calming measures are different design features or strategies used to reduce the speed of a traveling vehicle on a particular road. These calming measures are common on rural roads of Oman. Some of these measures are road speed limits, vertical deflections, horizontal deflections, and road signs. In general, vertical deflections such as rumble strips, road studs (cat’s eye), speed tables, and speed humps are widely used. In this paper, as vehicle speeding is a major cause of road traffic crashes and high fatalities in Oman, the effectiveness of existing traffic calming measures at current locations on rural roads is assessed. The study was conducted on the rural roads of Dhofar Governorate, which is located in the south of Oman. A special focus is given to the calming measures implemented on the mountain roads of Dhofar. It is shown that vertical deflection calming measures are effective in reducing vehicle speed to 20 to 40 kph, depending on the vertical deflection type and spacing. Calming measures are also proposed at locations with a high probability of traffic crashes based on the number of traffic crashes at these locations, road type, and road geometry.

Keywords: road safety, rural roads, speed, traffic calming measures, traffic crash

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7203 A Study of Structural Damage Detection for Spacecraft In-Orbit Based on Acoustic Sensor Array

Authors: Lei Qi, Rongxin Yan, Lichen Sun

Abstract:

With the increasing of human space activities, the number of space debris has increased dramatically, and the possibility that spacecrafts on orbit are impacted by space debris is growing. A method is of the vital significance to real-time detect and assess spacecraft damage, determine of gas leak accurately, guarantee the life safety of the astronaut effectively. In this paper, acoustic sensor array is used to detect the acoustic signal which emits from the damage of the spacecraft on orbit. Then, we apply the time difference of arrival and beam forming algorithm to locate the damage and leakage. Finally, the extent of the spacecraft damage is evaluated according to the nonlinear ultrasonic method. The result shows that this method can detect the debris impact and the structural damage, locate the damage position, and identify the damage degree effectively. This method can meet the needs of structural damage detection for the spacecraft in-orbit.

Keywords: acoustic sensor array, spacecraft, damage assessment, leakage location

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7202 An Energy Efficient Clustering Approach for Underwater ‎Wireless Sensor Networks

Authors: Mohammad Reza Taherkhani‎

Abstract:

Wireless sensor networks that are used to monitor a special environment, are formed from a large number of sensor nodes. The role of these sensors is to sense special parameters from ambient and to make a connection. In these networks, the most important challenge is the management of energy usage. Clustering is one of the methods that are broadly used to face this challenge. In this paper, a distributed clustering protocol based on learning automata is proposed for underwater wireless sensor networks. The proposed algorithm that is called LA-Clustering forms clusters in the same energy level, based on the energy level of nodes and the connection radius regardless of size and the structure of sensor network. The proposed approach is simulated and is compared with some other protocols with considering some metrics such as network lifetime, number of alive nodes, and number of transmitted data. The simulation results demonstrate the efficiency of the proposed approach.

Keywords: underwater sensor networks, clustering, learning automata, energy consumption

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7201 Economic Design of a Quality Control Chart for the Proportion of Defective Items

Authors: Encarnación Álvarez-Verdejo, Raúl Amor-Pulido, Pablo J. Moya-Fernández, Juan F. Muñoz-Rosas, Francisco J. Blanco-Encomienda

Abstract:

Many companies use the statistical tool named as statistical quality control, and which can have a high cost for the companies interested on these statistical tools. The evaluation of the quality of products and services is an important topic, but the reduction of the cost of the implantation of the statistical quality control also has important benefits for the companies. For this reason, it is important to implement a economic design for the various steps included into the statistical quality control. In this paper, we describe some relevant aspects related to the economic design of a quality control chart for the proportion of defective items. They are very important because the suggested issues can reduce the cost of implementing a quality control chart for the proportion of defective items. Note that the main purpose of this chart is to evaluate and control the proportion of defective items of a production process.

Keywords: proportion, type I error, economic plan, distribution function

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7200 Credit Risk Assessment Using Rule Based Classifiers: A Comparative Study

Authors: Salima Smiti, Ines Gasmi, Makram Soui

Abstract:

Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

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7199 Analysis and Prediction of Netflix Viewing History Using Netflixlatte as an Enriched Real Data Pool

Authors: Amir Mabhout, Toktam Ghafarian, Amirhossein Farzin, Zahra Makki, Sajjad Alizadeh, Amirhossein Ghavi

Abstract:

The high number of Netflix subscribers makes it attractive for data scientists to extract valuable knowledge from the viewers' behavioural analyses. This paper presents a set of statistical insights into viewers' viewing history. After that, a deep learning model is used to predict the future watching behaviour of the users based on previous watching history within the Netflixlatte data pool. Netflixlatte in an aggregated and anonymized data pool of 320 Netflix viewers with a length 250 000 data points recorded between 2008-2022. We observe insightful correlations between the distribution of viewing time and the COVID-19 pandemic outbreak. The presented deep learning model predicts future movie and TV series viewing habits with an average loss of 0.175.

Keywords: data analysis, deep learning, LSTM neural network, netflix

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7198 Orthosis and Finite Elements: A Study for Development of New Designs through Additive Manufacturing

Authors: M. Volpini, D. Alves, A. Horta, M. Borges, P. Reis

Abstract:

The gait pattern in people that present motor limitations foment the demand for auxiliary locomotion devices. These artifacts for movement assistance vary according to its shape, size and functional features, following the clinical applications desired. Among the ortheses of lower limbs, the ankle-foot orthesis aims to improve the ability to walk in people with different neuromuscular limitations, although they do not always answer patients' expectations for their aesthetic and functional characteristics. The purpose of this study is to explore the possibility of using new design in additive manufacturer to reproduce the shape and functional features of a ankle-foot orthesis in an efficient and modern way. Therefore, this work presents a study about the performance of the mechanical forces through the analysis of finite elements in an ankle-foot orthesis. It will be demonstrated a study of distribution of the stress on the orthopedic device in orthostatism and during the movement in the course of patient's walk.

Keywords: additive manufacture, new designs, orthoses, finite elements

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7197 Investigation Of The Catalyst's Effect On Nickel Sulfide Thin Films

Authors: Randa Slatnia

Abstract:

In this study, the nanostructured stable phase identification elaborated by nickel nitrate hyxahydrate and thiourea compounds. After the preparation of the solution (Stirred mixture with methanol as solvent), a deposition of eight layers of this solution on a glass substrate and annealed at 300 °C for energy applications. The annealed sample was analyzed by X-ray Grazing incidence diffraction (GID) with a Bruker D8 Advance diffractometer using Cu Kα1 radiation at 40 kV and 40 mA (1600 W) and Scanning electron microscopy (Thermo Fisher environmental SEM). The results of XRD-GID analysis for the prepared sample showed the formation of an identified stable phase NiS2 and the XRD-GID pattern of the elaborated sample with eight layers prepared solution and annealed show wide and characteristic peaks of the NiS2 with cubic structure (ICDD card no. PDF 01-078-4702). The morphology of the NiS2 thin films confirmed by XRD-GID analysis was investigated by ESEM showed a surface with a uniform and homogeneous distribution nanostructure.

Keywords: nickel sulfide, thin films, XRD, ESEM

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7196 Comparison Analysis on the Safety Culture between the Executives and the Operators: Case Study in the Aircraft Manufacturer in Taiwan

Authors: Wen-Chen Hwang, Yu-Hsi Yuan

Abstract:

According to the estimation made by researchers of safety and hygiene, 80% to 90% of workplace accidents in enterprises could be attributed to human factors. Nevertheless, human factors are not the only cause for accidents; instead, happening of accidents is also closely associated with the safety culture of the organization. Therefore, the most effective way of reducing accident rate would be to improve the social and the organizational factors that influence organization’s safety performance. Overview the present study is to understand the current level of safety culture in manufacturing enterprises. A tool for evaluating safety culture matching the needs and characteristics of manufacturing enterprises was developed by reviewing literature of safety culture, and taking the special backgrounds of the case enterprises into consideration. Expert validity was also implied for developing the questionnaire. Moreover, safety culture assessment was conducted through the practical investigation of the case enterprises. Total 505 samples were involved, 53 were executives and 452 were operators. The result of this study in comparison of the safety culture level between the executives and the operators was reached the significant level in 8 dimensions: Safety Commitment, Safety System, Safety Training, Safety Involvement, Reward and Motivation, Communication and Reporting, Leadership and Supervision, Learning and Changing. In general, the overall safety culture were executive level higher than operators level (M: 74.98 > 69.08; t=2.87; p < 0.01).

Keywords: questionnaire survey, safety culture, t-test, media studies

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7195 Self-Assembly of Monodisperse Oleic Acid-Capped Superparamagnetic Iron Oxide Nanoparticles

Authors: Huseyin Kavas

Abstract:

Oleic acid (OA) capped superparamagnetic iron oxide nanoparticles (SPION) were synthesized by a thermal decomposition method. The composition of nanoparticles was confirmed by X-ray powder diffraction, and the morphology of particles was investigated by Atomic Force Microscopy (AFM), Scanning Electron Microscopy (SEM), and Transmission electron microscopy (TEM). The crystalline and particle size distribution of SPIONS capped with OA were investigated with a mean size of 6.99 nm and 8.9 nm, respectively. It was found that SPIONS have superparamagnetic characteristics with a saturation magnetization value of 64 emu/g. The thin film form of self-assembled SPIONS was fabricated by coating techniques of spin coating and dip coating. SQUID-VSM magnetometer and FMR techniques were performed in order to evaluate the magnetic properties of thin films, especially the existence of magnetic anisotropy. The thin films with magnetic anisotropy were obtained by self-assembled monolayers of SPION.

Keywords: magnetic materials, nanostructures, self-assembly, FMR

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7194 Review of Cyber Security in Oil and Gas Industry with Cloud Computing Perspective: Taxonomy, Issues and Future Direction

Authors: Irfan Mohiuddin, Ahmad Al Mogren

Abstract:

In recent years, cloud computing has earned substantial attention in the Oil and Gas Industry and provides services in all the phases of the industry lifecycle. Oil and gas supply infrastructure, in particular, is more vulnerable to accidental, natural and intentional threats because of its widespread distribution. Numerous surveys have been conducted on cloud security and privacy. However, to the best of our knowledge, hardly any survey is carried out that reviews cyber security in all phases with a cloud computing perspective. Moreover, a distinctive classification is performed for all the cloud-based cyber security measures based on the cloud component in use. The classification approach will enable researchers to identify the required technique used to enhance the security in specific cloud components. Also, the limitation of each component will allow the researchers to design optimal algorithms. Lastly, future directions are given to point out the imminent challenges that can pave the way for researchers to further enhance the resilience to cyber security threats in the oil and gas industry.

Keywords: cyber security, cloud computing, safety and security, oil and gas industry, security threats, oil and gas pipelines

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7193 Vehicle Timing Motion Detection Based on Multi-Dimensional Dynamic Detection Network

Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

Abstract:

Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

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7192 Internet-Based Architecture for Machine-to-Machine Communication of a Public Security Network

Authors: Ogwueleka Francisca Nonyelum, Jiya Muhammad

Abstract:

Poor communication between the victims of the burglaries, road and fire accidents and the agencies, and lack of quick emergency response by the agencies is solved through Machine-to-Machine (M2M) communication. A distress caller is expected to make a call through a network to the respective agency for emergency response but due to some challenges, this often becomes arduous and futile. This research puts forth an Internet-based architecture for Machine-to-Machine (M2M) communication to enhance information dissemination in National Public Security Communication System (NPSCS) network. M2M enables the flow of data between machines and machines and ultimately machines and people with information flowing from a machine over a network, and then through a gateway to a system where it is reviewed and acted on. The research findings showed that Internet-based architecture for M2M communication is most suitable for deployment of a public security network which will allow machines to use Internet to talk to each other.

Keywords: machine-to-machine (M2M), internet-based architecture, network, gateway

Procedia PDF Downloads 474
7191 Performance Evaluation of Various Displaced Left Turn Intersection Designs

Authors: Hatem Abou-Senna, Essam Radwan

Abstract:

With increasing traffic and limited resources, accommodating left-turning traffic has been a challenge for traffic engineers as they seek balance between intersection capacity and safety; these are two conflicting goals in the operation of a signalized intersection that are mitigated through signal phasing techniques. Hence, to increase the left-turn capacity and reduce the delay at the intersections, the Florida Department of Transportation (FDOT) moves forward with a vision of optimizing intersection control using innovative intersection designs through the Transportation Systems Management & Operations (TSM&O) program. These alternative designs successfully eliminate the left-turn phase, which otherwise reduces the conventional intersection’s (CI) efficiency considerably, and divide the intersection into smaller networks that would operate in a one-way fashion. This study focused on the Crossover Displaced Left-turn intersections (XDL), also known as Continuous Flow Intersections (CFI). The XDL concept is best suited for intersections with moderate to high overall traffic volumes, especially those with very high or unbalanced left turn volumes. There is little guidance on determining whether partial XDL intersections are adequate to mitigate the overall intersection condition or full XDL is always required. The primary objective of this paper was to evaluate the overall intersection performance in the case of different partial XDL designs compared to a full XDL. The XDL alternative was investigated for 4 different scenarios; partial XDL on the east-west approaches, partial XDL on the north-south approaches, partial XDL on the north and east approaches and full XDL on all 4 approaches. Also, the impact of increasing volume on the intersection performance was considered by modeling the unbalanced volumes with 10% increment resulting in 5 different traffic scenarios. The study intersection, located in Orlando Florida, is experiencing recurring congestion in the PM peak hour and is operating near capacity with volume to a capacity ratio closer to 1.00 due to the presence of two heavy conflicting movements; southbound and westbound. The results showed that a partial EN XDL alternative proved to be effective and compared favorably to a full XDL alternative followed by the partial EW XDL alternative. The analysis also showed that Full, EW and EN XDL alternatives outperformed the NS XDL and the CI alternatives with respect to the throughput, delay and queue lengths. Significant throughput improvements were remarkable at the higher volume level with percent increase in capacity of 25%. The percent reduction in delay for the critical movements in the XDL scenarios compared to the CI scenario ranged from 30-45%. Similarly, queue lengths showed percent reduction in the XDL scenarios ranging from 25-40%. The analysis revealed how partial XDL design can improve the overall intersection performance at various demands, reduce the costs associated with full XDL and proved to outperform the conventional intersection. However, partial XDL serving low volumes or only one of the critical movements while other critical movements are operating near or above capacity do not provide significant benefits when compared to the conventional intersection.

Keywords: continuous flow intersections, crossover displaced left-turn, microscopic traffic simulation, transportation system management and operations, VISSIM simulation model

Procedia PDF Downloads 307