Search results for: real time locating system (RTLS)

Authors: Ons Sassi, Wahiba Ramdane Cherif-Khettaf, Ammar Oulamara

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In this paper, we consider a new real-life Heterogenous Electric Vehicle Routing Problem with Time Dependant Charging Costs and a Mixed Fleet (HEVRP-TDMF), in which a set of geographically scattered customers have to be served by a mixed fleet of vehicles composed of a heterogenous fleet of Electric Vehicles (EVs), having different battery capacities and operating costs, and Conventional Vehicles (CVs). We include the possibility of charging EVs in the available charging stations during the routes in order to serve all customers. Each charging station offers charging service with a known technology of chargers and time-dependent charging costs. Charging stations are also subject to operating time windows constraints. EVs are not necessarily compatible with all available charging technologies and a partial charging is allowed. Intermittent charging at the depot is also allowed provided that constraints related to the electricity grid are satisfied. The objective is to minimize the number of employed vehicles and then minimize the total travel and charging costs. In this study, we present a Mixed Integer Programming Model and develop a Charging Routing Heuristic and a Local Search Heuristic based on the Inject-Eject routine with three different insertion strategies. All heuristics are tested on real data instances.

Keywords: charging problem, electric vehicle, heuristics, local search, optimization, routing problem

Procedia PDF Downloads 457

Authors: Srivatsav Sanjay Sridhar, Asvitha Raja, Prathit Kalra, Soni Gupta

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Database management is a system that keeps track of details about a person in an organisation. Not a lot of orphanages these days are shifting to a computer and program-based system, but unfortunately, most have only pen and paper-based records, which not only consumes space but it is also not eco-friendly. It comes as a hassle when one has to view a record of a person as they have to search through multiple records, and it will consume time. This program will organise all the data and can pull out any information about anyone whose data is entered. This is also a safe way of storage as physical data gets degraded over time or, worse, destroyed due to natural disasters. In this developing world, it is only smart enough to shift all data to an electronic-based storage system. The program comes with all features, including creating, inserting, searching, and deleting the data, as well as printing them.

Keywords: database, orphans, programming, C⁺⁺

Procedia PDF Downloads 134

Authors: Minghui Zhang, Sirine Fkaier, Sabri Fernana, Svetlana Kiseleva, Denis Kiselev

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The real-time identification of bacteria and fungi is difficult because they emit much weaker signals than pollen. In 2020, Plair developed Rapid-E+, which extends abilities of Rapid-E to detect smaller bioaerosols such as bacteria and fungal spores with diameters down to 0.3 µm, while keeping the similar or even better capability for measurements of large bioaerosols like pollen. Rapid-E+ enables simultaneous measurements of (1) time-resolved, polarization and angle dependent Mie scattering patterns, (2) fluorescence spectra resolved in 16 channels, and (3) fluorescence lifetime of individual particles. Moreover, (4) it provides 2D Mie scattering images which give the full information on particle morphology. The parameters of every single bioaerosol aspired into the instrument are subsequently analysed by machine learning. Firstly, pure species of microbes, e.g., Bacillus subtilis (a species of bacteria), and Penicillium chrysogenum (a species of fungal spores), were aerosolized in a bioaerosol chamber for Rapid-E+ training. Afterwards, we tested microbes under different concentrations. We used several steps of data analysis to classify and identify microbes. All single particles were analysed by the parameters of light scattering and fluorescence in the following steps. (1) They were treated with a smart filter block to get rid of non-microbes. (2) By classification algorithm, we verified the filtered particles were microbes based on the calibration data. (3) The probability threshold (defined by the user) step provides the probability of being microbes ranging from 0 to 100%. We demonstrate how Rapid-E+ identified simultaneously microbes based on the results of Bacillus subtilis (bacteria) and Penicillium chrysogenum (fungal spores). By using machine learning, Rapid-E+ achieved identification precision of 99% against the background. The further classification suggests the precision of 87% and 89% for Bacillus subtilis and Penicillium chrysogenum, respectively. The developed algorithm was subsequently used to evaluate the performance of microbe classification and quantification in real-time. The bacteria and fungi were aerosolized again in the chamber with different concentrations. Rapid-E+ can classify different types of microbes and then quantify them in real-time. Rapid-E+ enables classifying different types of microbes and quantifying them in real-time. Rapid-E+ can identify pollen down to species with similar or even better performance than the previous version (Rapid-E). Therefore, Rapid-E+ is an all-in-one instrument which classifies and quantifies not only pollen, but also bacteria and fungi. Based on the machine learning platform, the user can further develop proprietary algorithms for specific microbes (e.g., virus aerosols) and other aerosols (e.g., combustion-related particles that contain polycyclic aromatic hydrocarbons).

Keywords: bioaerosols, laser-induced fluorescence, Mie-scattering, microorganisms

Procedia PDF Downloads 83

Authors: Dauda A. Oladosu, Kamorudeen A Olaiya, Abdurahman Bello

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The deployment of smart meters by utility providers to gather fine grained spatiotemporal consumption data has grossly influenced the consumers’ emotion and behavior towards energy utilization. The quest for reduction in power consumption is now a subject of concern and one the methods adopted by the consumers to achieve this is Non-intrusive Load (appliance) Monitoring. Hence, this work presents performance Analysis of Domotics System as a tool for load monitoring when integrated with Consumer Control Unit of residential building. The system was developed with basic elements which enhance remote sensing, DTMF (Dual Tone Multi-frequency) recognition and cryptic messaging when specific task was performed. To demonstrate its applicability and suitability, this prototype was used consistently for six months at different load demands and the utilities consumed were documented. The results obtained shows good response when phone dialed, and the packet delivery of feedback SMS was quite satisfactory, making the implemented system to be of good quality with affordable cost and performs the desired functions. Besides, comparative analysis showed notable reduction in energy consumption and invariably lessened electrical bill of the consumer.

Keywords: automation, domotics, energy, load, remote, schedule

Procedia PDF Downloads 305

Authors: Soumaya Sallem, Marc Olivas

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This contribution presents a method for detecting, locating, and characterizing soft faults in a complex wired network. The proposed method is based on multi-carrier reflectometry MCTDR (Multi-Carrier Time Domain Reflectometry) combined with a multi-objective genetic algorithm. In order to ensure complete network coverage and eliminate diagnosis ambiguities, the MCTDR test signal is injected at several points on the network, and the data is merged between different reflectometers (sensors) distributed on the network. An adapted multi-objective genetic algorithm is used to merge data in order to obtain more accurate faults location and characterization. The proposed method performances are evaluated from numerical and experimental results.

Keywords: wired network, reflectometry, network distributed diagnosis, multi-objective genetic algorithm

Procedia PDF Downloads 181

Authors: Min-Tsai Lai, Taqwa Hariguna

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This paper presents a periodical replacement model for a system, considering the concept of single and cumulative repair cost limits simultaneously. The failures are divided into two types. Minor failure can be corrected by minimal repair and serious failure makes the system breakdown completely. When a minor failure occurs, if the repair cost is less than a single repair cost limit L1 and the accumulated repair cost is less than a cumulative repair cost limit L2, then minimal repair is executed, otherwise, the system is preventively replaced. The system is also replaced at time T or at serious failure. The optimal period T minimizing the long-run expected cost per unit time is verified to be finite and unique under some specific conditions.

Keywords: repair-cost limit, cumulative repair-cost limit, minimal repair, periodical replacement policy

Procedia PDF Downloads 350

Authors: Kailash C. Madan

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We study four models of a three server queueing system with Bernoulli schedule optional server vacations. Customers arriving at the system one by one in a Poisson process are provided identical exponential service by three parallel servers according to a first-come, first served queue discipline. In model A, all three servers may be allowed a vacation at one time, in Model B at the most two of the three servers may be allowed a vacation at one time, in model C at the most one server is allowed a vacation, and in model D no server is allowed a vacation. We study steady the state behavior of the four models and obtain steady state probability generating functions for the queue size at a random point of time for all states of the system. In model D, a known result for a three server queueing system without server vacations is derived.

Keywords: a three server queue, Bernoulli schedule server vacations, queue size distribution at a random epoch, steady state

Procedia PDF Downloads 289

Authors: Ognjen Vukovic

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Chern-Simons equation represents the cornerstone of quantum physics. The question that is often asked is if the aforementioned equation can be successfully applied to the interaction in international financial markets. By analysing the time series in financial theory, it is proved that Chern-Simons equation can be successfully applied to financial time-series. The aforementioned statement is based on one important premise and that is that the financial time series follow the fractional Brownian motion. All variants of Chern-Simons equation and theory are applied and analysed. Financial theory time series movement is, firstly, topologically analysed. The main idea is that exchange rate represents two-dimensional projections of three-dimensional Brownian motion movement. Main principles of knot theory and topology are applied to financial time series and setting is created so the Chern-Simons equation can be applied. As Chern-Simons equation is based on small particles, it is multiplied by the magnifying factor to mimic the real world movement. Afterwards, the following equation is optimised using Solver. The equation is applied to n financial time series in order to see if it can capture the interaction between financial time series and consequently explain it. The aforementioned equation represents a novel approach to financial time series analysis and hopefully it will direct further research.

Keywords: Brownian motion, Chern-Simons theory, financial time series, econophysics

Procedia PDF Downloads 461

Authors: Mahdy Elhusseiny, Richard Gearhart, Mariam Alyammahi

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In this study we analyse the impact of a number of major macroeconomic variables on industry-specific excess rates of return. In later specifications, we include time and recession fixed effects, to potentially capture time-specific trends that may have been changing over our panel. We have a number of results that bear mentioning. Seasonal and temporal factors found to have very large role in sector-specific excess returns. Increases in M1(money supply) decreases bank, insurance, real estate, and telecommunications, while increases industrial and transportation excess returns. The results indicate that the market return increases every sector-specific rate of return. The 2007 to 2009 recession significantly reduced excess returns in the bank, real estate, and transportation sectors.

Keywords: macroeconomic factors, industry returns, fixed effects, temporal factors

Procedia PDF Downloads 68

Authors: Elsadig Naseraddeen Ahmed Mohamed

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In contrast to the uncertainty and complementary principle, it will be shown in the present paper that the probability of the simultaneous occupation event of any definite values of coordinates by any definite values of momentum and energy at any definite instance of time can be described by a binary definite function equivalent to the difference between their numbers of occupation and evacuation epochs up to that time and also equivalent to the number of exchanges between those occupation and evacuation epochs up to that times modulus two, these binary definite quantities can be defined at all point in the time’s real-line so it form a binary signal represent a complete mechanical description of physical reality, the time of these exchanges represent the boundary of occupation and evacuation epochs from which we can calculate these binary signals using the fact that the time of universe events actually extends in the positive and negative of time’s real-line in one direction of extension when these number of exchanges increase, so there exists noninvertible transformation matrix can be defined as the matrix multiplication of invertible rotation matrix and noninvertible scaling matrix change the direction and magnitude of exchange event vector respectively, these noninvertible transformation will be called actual transformation in contrast to information transformations by which we can navigate the universe’s events transformed by actual transformations backward and forward in time’s real-line, so these information transformations will be derived as an elements of a group can be associated to their corresponded actual transformations. The actual and information model of the universe will be derived by assuming the existence of time instance zero before and at which there is no coordinate occupied by any definite values of momentum and energy, and then after that time, the universe begin its expanding in spacetime, this assumption makes the need for the existence of Laplace’s demon who at one moment can measure the positions and momentums of all constituent particle of the universe and then use the law of classical mechanics to predict all future and past of universe’s events, superfluous, we only need for the establishment of our analog to digital converters to sense the binary signals that determine the boundaries of occupation and evacuation epochs of the definite values of coordinates relative to its origin by the definite values of momentum and energy as present events of the universe from them we can predict approximately in high precision it's past and future events.

Keywords: binary-signal mechanics, actual-information model of the universe, actual-transformation, information-transformation, uncertainty principle, Laplace's demon

Procedia PDF Downloads 168

Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

Procedia PDF Downloads 313

Authors: William J. Crowther, Conor Marsh

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Object-based flow simulation allows fast computation of arbitrarily complex aerodynamic models made up of simple objects with limited flow interactions. The proposed approach is universally applicable to objects made from arbitrarily scaled ellipsoid primitives at arbitrary aerodynamic attitude and angular rate. The use of a component-based aerodynamic modelling approach increases efficiency by allowing selective inclusion of different physics models at run-time and allows extensibility through the development of new models. Insight into the numerical stability of the model under first order fixed-time step integration schemes is provided by stability analysis of the drag component. The compute cost of model components and functions is evaluated and compared against numerical benchmarks. Model static outputs are verified against theoretical expectations and dynamic behaviour using falling plate data from the literature. The model is applied to a range of case studies to demonstrate the efficacy of its application in extensibility, ease of use, and low computational cost. Dynamically complex multi-body systems can be implemented in a transparent and efficient manner, and we successfully demonstrate large scenes with hundreds of objects interacting with diverse flow fields.

Keywords: aerodynamics, real-time simulation, low-order model, flight dynamics

Procedia PDF Downloads 89

Authors: Leandros A. Maglaras, Jianmin Jiang

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The protection of the national infrastructures from cyberattacks is one of the main issues for national and international security. The funded European Framework-7 (FP7) research project CockpitCI introduces intelligent intrusion detection, analysis and protection techniques for Critical Infrastructures (CI). The paradox is that CIs massively rely on the newest interconnected and vulnerable Information and Communication Technology (ICT), whilst the control equipment, legacy software/hardware, is typically old. Such a combination of factors may lead to very dangerous situations, exposing systems to a wide variety of attacks. To overcome such threats, the CockpitCI project combines machine learning techniques with ICT technologies to produce advanced intrusion detection, analysis and reaction tools to provide intelligence to field equipment. This will allow the field equipment to perform local decisions in order to self-identify and self-react to abnormal situations introduced by cyberattacks. In this paper, an intrusion detection module capable of detecting malicious network traffic in a Supervisory Control and Data Acquisition (SCADA) system is presented. Malicious data in a SCADA system disrupt its correct functioning and tamper with its normal operation. OCSVM is an intrusion detection mechanism that does not need any labeled data for training or any information about the kind of anomaly is expecting for the detection process. This feature makes it ideal for processing SCADA environment data and automates SCADA performance monitoring. The OCSVM module developed is trained by network traces off line and detects anomalies in the system real time. The module is part of an IDS (intrusion detection system) developed under CockpitCI project and communicates with the other parts of the system by the exchange of IDMEF messages that carry information about the source of the incident, the time and a classification of the alarm.

Keywords: cyber-security, SCADA systems, OCSVM, intrusion detection

Procedia PDF Downloads 533

Authors: Marjan Majdi, MohammadAli Moradi, Elham Samarikhalaj

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Income distribution is one of the most topics in macro economic theories. There are many categories in economy such as income distribution that have the most influenced by economic policies. Human capital has an impact on economic growth and it has significant effect on income distributions. The results of this study confirm that the effects of oil revenue and human capital on income distribution are negative and significant but the value of the estimated coefficient is too small in a real sample in period time (1969-2006).

Keywords: gini coefficient, human capital, income distribution, oil revenue

Procedia PDF Downloads 624

Authors: Hao Cheng, Zhiwu Wang, Guozheng Yan, Pingping Jiang, Shijia Qin, Shuai Kuang

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Autofluorescence Imaging (AFI) is a technology for detecting early carcinogenesis of the gastrointestinal tract in recent years. Compared with traditional white light endoscopy (WLE), this technology greatly improves the detection accuracy of early carcinogenesis, because the colors of normal tissues are different from cancerous tissues. Thus, edge detection can distinguish them in grayscale images. In this paper, based on the traditional Sobel edge detection method, optimization has been performed on this method which considers the environment of the gastrointestinal, including adaptive threshold and morphological processing. All of the processes are implemented on our self-designed system based on the image sensor OV6930 and Field Programmable Gate Array (FPGA), The system can capture the gastrointestinal image taken by the lens in real time and detect edges. The final experiments verified the feasibility of our system and the effectiveness and accuracy of the edge detection algorithm.

Keywords: AFI, edge detection, adaptive threshold, morphological processing, OV6930, FPGA

Procedia PDF Downloads 221

Authors: Maria A. Murtiati, Ancella A. Hermawan

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The objective of this study is to examine whether the firm’s eligibility to get a bank loan is influenced by earnings management. The earnings management is distinguished between accruals and real earnings management. Hypothesis testing is carried out with logistic regression model using sample of 285 companies listed at Indonesian Stock Exchange in 2010. The result provides evidence that a greater magnitude in accruals earnings management increases the firm’s probability to be eligible to get bank loan. In contrast, real earnings management through abnormal cash flow and abnormal discretionary expenses decrease firm’s probability to be eligible to get bank loan, while real management through abnormal production cost increases such probability. The result of this study suggests that if the earnings management is assumed to be opportunistic purpose, the accruals based earnings management can distort the banks credit analysis using financial statements. Real earnings management has more impact on the cash flows, and banks are very concerned on the firm’s cash flow ability. Therefore, this study indicates that banks are more able to detect real earnings management, except abnormal production cost in real earning management.

Keywords: discretionary accruals, real earning management, bank loan, credit worthiness

Procedia PDF Downloads 336

Authors: Evgenia Iakovleva, Juha Koivisto, Pasi Karppinen, J. Inkinen, Mikko Alava

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Preventing the spread of infectious diseases throughout the worldwide is one of the most important tasks of modern health care. Infectious diseases not only account for one fifth of the deaths in the world, but also cause many pathological complications for the human health. Touch surfaces pose an important vector for the spread of infections by varying microorganisms, including antimicrobial resistant organisms. Further, antimicrobial resistance is reply of bacteria to the overused or inappropriate used of antibiotics everywhere. The biggest challenges in bacterial detection by existing methods are non-direct determination, long time of analysis, the sample preparation, use of chemicals and expensive equipment, and availability of qualified specialists. Therefore, a high-performance, rapid, real-time detection is demanded in rapid practical bacterial detection and to control the epidemiological hazard. Among the known methods for determining bacteria on the surfaces, Hyperspectral methods can be used as direct and rapid methods for microorganism detection on different kind of surfaces based on fluorescence without sampling, sample preparation and chemicals. The aim of this study was to assess the relevance of such systems to remote sensing of surfaces for microorganisms detection to prevent a global spread of infectious diseases. Bacillus subtilis and Escherichia coli with different concentrations (from 0 to 10x8 cell/100µL) were detected with hyperspectral camera using different filters as visible visualization of bacteria and background spots on the steel plate. A method of internal standards was applied for monitoring the correctness of the analysis results. Distances from sample to hyperspectral camera and light source are 25 cm and 40 cm, respectively. Each sample is optically imaged from the surface by hyperspectral imaging system, utilizing a JAI CM-140GE-UV camera. Light source is BeamZ FLATPAR DMX Tri-light, 3W tri-colour LEDs (red, blue and green). Light colors are changed through DMX USB Pro interface. The developed system was calibrated following a standard procedure of setting exposure and focused for light with λ=525 nm. The filter is ThorLabs KuriousTM hyperspectral filter controller with wavelengths from 420 to 720 nm. All data collection, pro-processing and multivariate analysis was performed using LabVIEW and Python software. The studied human eye visible and invisible bacterial stains clustered apart from a reference steel material by clustering analysis using different light sources and filter wavelengths. The calculation of random and systematic errors of the analysis results proved the applicability of the method in real conditions. Validation experiments have been carried out with photometry and ATP swab-test. The lower detection limit of developed method is several orders of magnitude lower than for both validation methods. All parameters of the experiments were the same, except for the light. Hyperspectral imaging method allows to separate not only bacteria and surfaces, but also different types of bacteria, such as Gram-negative Escherichia coli and Gram-positive Bacillus subtilis. Developed method allows skipping the sample preparation and the use of chemicals, unlike all other microbiological methods. The time of analysis with novel hyperspectral system is a few seconds, which is innovative in the field of microbiological tests.

Keywords: Escherichia coli, Bacillus subtilis, hyperspectral imaging, microorganisms detection

Procedia PDF Downloads 209

Authors: Jiří F. Urbánek, Alena Oulehlová, Hana Malachová, Jiří J. Urbánek Jr.

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Crisis situations investigation and modelling are introduced and made within the complex system of energetic critical infrastructure, operating on peril´s environments. Every crisis situations and perils has an origin in the emergency/ crisis event occurrence and they need critical/ crisis interfaces assessment. Here, the emergency events can be expected - then crisis scenarios can be pre-prepared by pertinent organizational crisis management authorities towards their coping; or it may be unexpected - without pre-prepared scenario of event. But the both need operational coping by means of crisis management as well. The operation, forms, characteristics, behaviour and utilization of crisis management have various qualities, depending on real critical infrastructure organization perils, and prevention training processes. An aim is always - better security and continuity of the organization, which successful obtainment needs to find and investigate critical/ crisis zones and functions in critical infrastructure organization models, operating in pertinent perils environment. Our DYVELOP (Dynamic Vector Logistics of Processes) method is disposables for it. Here, it is necessary to derive and create identification algorithm of critical/ crisis interfaces. The locations of critical/ crisis interfaces are the flags of crisis situation in organization of critical infrastructure models. Then, the model of crisis situation will be displayed at real organization of Czech energetic crisis infrastructure subject in real peril environment. These efficient measures are necessary for the infrastructure protection. They will be derived for peril mitigation, crisis situation coping and for environmentally friendly organization survival, continuity and its sustainable development advanced possibilities.

Keywords: algorithms, energetic infrastructure complex system, modelling, peril´s environment

Procedia PDF Downloads 391

Authors: Sayed Ali Garossi, Azar Heidarizadi, Shahla Mohammad Ganji

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Context: Colorectal cancer is the second type of cancer-related mortality globally. Expression of cas8 (caspase 8) is closely connected to growth and metastasis of colorectal cancer.Cas8/Rip1 plays a vital role in the apoptosis pathway and resistance to chemotherapy. The aim of the present study is to investigate the pattern of gene expression in colorectal cancer and compare the differences using Real-Time PCR to find a potential biomarker candidate for colorectal cancer. Methodology: This study conducted real-time PCR to evaluate gene expression of Cas8 in colorectal cancer patients. The gene-specific primer sequences exon–exon junction was designed by OLIGO7 software for the expression of the gene under investigation. Forty-six patient samples without any chemotherapy were selected, including tumoral tissue and adjacent normal tissue samples. The age of the patients was 50 and the size of the tumors was 5.5 cm. The categories were before and after age 50. Findings: Here, we found that Caspase 8 was overexpressed in CRC tissues compared to corresponding adjacent colon tissues (Cas8: 5.2 vs. 1 ratio); high expression of Cas8 was associated with poor overall survival and independent risk factors for the prognosis of CRC patients. Conclusion: In conclusion, our study pioneered the reporting of high Casp8 expression as a predictor of poor prognosis and chemical resistance in CRC patients.Cas8 overexpression suppressed Cas 8 / Rip1-dependent apoptosis and activated the proliferation of tumor cells by activating necroptosis. The necroptosis pathway has also emerged as a new approach to anti-tumor in cancer treatment.

Keywords: Cas8, necroptosis, apoptosis, Real-Time PCR

Procedia PDF Downloads 45

Authors: Öznur Özge Özcan, Canan Sercan, Hamza Kulaksız, Mesut Karahan, Korkut Ulucan

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Genetic structure is very important to understand the brain dopamine system which is related to athletic performance. Hopefully, there will be enough studies about athletics performance in the terms of addiction-related genetic markers in the future. In the present study, we intended to investigate the Receptor-2 Gene (DRD2) rs1800497, which is related to brain dopaminergic system. 10 sprinter and 10 endurance athletes were enrolled in the study. Real-Time Polymerase Chain Reaction method was used for genotyping. According to results, A1A1, A1A2 and A2A2 genotypes in athletes were 0 (%0), 3 (%15) and 17 (%85). A1A1 genotype was not found and A2 allele was counted as the dominating allele in our cohort. These findings show that dopaminergic mechanism effects on sport genetic may be explained by the polygenic and multifactorial view.

Keywords: addiction, athletic performance, genotype, sport genetics

Procedia PDF Downloads 202

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

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Pulse Blood pressure (BP) is one of the vital signs, and is an index that helps determining the stability of life. In this respect, some spinal cord injury patients need to take the tilt table test. While doing the test, the posture changes abruptly, and may cause a patient’s BP to change abnormally. This may cause patients to feel discomfort, and even feel as though their life is threatened. Therefore, if a continuous non-invasive BP assessment system were built, it could help to alert health care professionals in the process of rehabilitation when the BP value is out of range. In our research, BP assessed by the pulse transit time technique was developed. In the system, we use a self-made photoplethysmograph (PPG) sensor and filter circuit to detect two PPG signals and to calculate the time difference. The BP can immediately be assessed by the trend line. According to the results of this study, the relationship between the systolic BP and PTT has a highly negative linear correlation (R2=0.8). Further, we used the trend line to assess the value of the BP and compared it to a commercial sphygmomanometer (Omron MX3); the error rate of the system was found to be in the range of ±10%, which is within the permissible error range of a commercial sphygmomanometer. The continue blood pressure measurement from pulse transit time technique may have potential to become a convenience method for clinical rehabilitation.

Keywords: continous blood pressure measurement, PPG, time transit time, transit velocity

Procedia PDF Downloads 341

Authors: Michael Moeti, Khuliso Sigama, Thapelo Samuel Matlala

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One of the principal challenges that the world is confronted with is insecurity. The crime rate is increasing exponentially, and protecting our physical assets especially in the motorist industry, is becoming impossible when applying our own strength. The need to develop technological solutions that detect and report theft without any human interference is inevitable. This is critical, especially for vehicle owners, to ensure theft detection and speedy identification towards recovery efforts in cases where a vehicle is missing or attempted theft is taking place. The vehicle theft detection system uses Convolutional Neural Network (CNN) to recognize the driver's face captured using an installed mobile phone device. The location identification function uses a Global Positioning System (GPS) to determine the real-time location of the vehicle. Upon identification of the location, Global System for Mobile Communications (GSM) technology is used to report or notify the vehicle owner about the whereabouts of the vehicle. The installed mobile app was implemented by making use of python as it is undoubtedly the best choice in machine learning. It allows easy access to machine learning algorithms through its widely developed library ecosystem. The graphical user interface was developed by making use of JAVA as it is better suited for mobile development. Google's online database (Firebase) was used as a means of storage for the application. The system integration test was performed using a simple percentage analysis. Sixty (60) vehicle owners participated in this study as a sample, and questionnaires were used in order to establish the acceptability of the system developed. The result indicates the efficiency of the proposed system, and consequently, the paper proposes the use of the system can effectively monitor the vehicle at any given place, even if it is driven outside its normal jurisdiction. More so, the system can be used as a database to detect, locate and report missing vehicles to different security agencies.

Keywords: CNN, location identification, tracking, GPS, GSM

Procedia PDF Downloads 146

Authors: Osaretin Rosemary Uyi, A. O. Ogungbemi

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Female involvement in policy making and partnership in a man-driven-world is fast gaining international recognition. The Nigeria commercial real estate is one of the sectors of the economy that has a significant number of the male in the business. This study was conducted to assess the participation of females in estate management in Lagos state, Nigeria. Lagos is the commercial nerve center of Nigeria having the highest number of real estate practitioners and investors. The population due to the daily influx of people has made real estate business to continue to grow in this part of Nigeria. A structured questionnaire duly pre-tested and validated was used to elicit information from the respondents. The data collected were presented using tables and charts and were analyzed using descriptive statistical tools such as frequency counts, percentages, were used to test the hypothesis. The results also indicated that most females that participated in commercial real estate business are educated (80%), fell within 31-40 years of age (75%) and of high income status (88%) earn above ₦800,000 per year, while 10% are real estate investors and 82% of the female in the sector are employee. The study concluded that the number of female participating in various aspect of commercial real estate business in the study area was moderate while the numbers of female investors are low when compared to male. This might be due to the problems associated with rent collection, land disputes and other issues that are associated with property management in Nigeria. It is therefore recommended that females in real estate should be empowered and encouraged to match with their male counterpart.

Keywords: commercial real estate, empowerment, female, participation, property management

Procedia PDF Downloads 318

Authors: Hesham A. Elkaranshawy, Amr M. Abdelrazek, Hosam M. Ezzat

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The system of ordinary nonlinear differential equations describing sliding velocity during impact with friction for a three-dimensional rigid-multibody system is developed. No analytical solutions have been obtained before for this highly nonlinear system. Hence, a power series solution is proposed. Since the validity of this solution is limited to its convergence zone, a suitable time step is chosen and at the end of it a new series solution is constructed. For a case study, the trajectory of the sliding velocity using the proposed method is built using 6 time steps, which coincides with a Runge-Kutta solution using 38 time steps.

Keywords: impact with friction, nonlinear ordinary differential equations, power series solutions, rough collision

Procedia PDF Downloads 475

Authors: Bipasha Sen, Aditya Agarwal

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Multilingual automatic speech recognition (ASR) system is a single entity capable of transcribing multiple languages sharing a common phone space. Performance of such a system is highly dependent on the compatibility of the languages. State of the art speech recognition systems are built using sequential architectures based on recurrent neural networks (RNN) limiting the computational parallelization in training. This poses a significant challenge in terms of time taken to bootstrap and validate the compatibility of multiple languages for building a robust multilingual system. Complex architectural choices based on self-attention networks are made to improve the parallelization thereby reducing the training time. In this work, we propose Reed, a simple system based on 1D convolutions which uses very short context to improve the training time. To improve the performance of our system, we use raw time-domain speech signals directly as input. This enables the convolutional layers to learn feature representations rather than relying on handcrafted features such as MFCC. We report improvement on training and inference times by atleast a factor of 4x and 7.4x respectively with comparable WERs against standard RNN based baseline systems on SpeechOcean's multilingual low resource dataset.

Keywords: convolutional neural networks, language compatibility, low resource languages, multilingual automatic speech recognition

Procedia PDF Downloads 106

Authors: Reyhaneh Saeedi

Abstract:

Iran is one of the regions which are most prone for earthquakes annually having a large number of financial and mortality and financial losses. Every year around the world, a large number of people lose their home and life due to natural disasters such as earthquakes. It is necessary to provide and specify some suitable places for settling the homeless people before the occurrence of the earthquake, one of the most important factors in crisis planning and management. Some of the natural disasters can be Modeling and shown by Geospatial Information System (GIS). By using GIS, it would be possible to manage the spatial data and reach several goals by making use of the analyses existing in it. GIS has a determining role in disaster management because it can determine the best places for temporary resettling after such a disaster. In this research QuantumGIS software is used that It is an OpenSource software so that easy to access codes and It is also free. In this system, AHP method is used as decision model and to locate the best places for temporary resettling, is done based on the related organizations criteria with their weights and buffers. Also in this research are made the buffer layers of criteria and change them to the raster layers. Later on, the raster layers are multiplied on desired weights then, the results are added together. Eventually, there are suitable places for resettling of victims by desired criteria by different colors with their optimum rate in QuantumGIS platform.

Keywords: disaster management, temporary resettlement, earthquake, QuantumGIS

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Authors: Mina Mortazavi, Hamid Ronagh, Pezhman Sharafi

Abstract:

The new concept of a cold formed-hot rolled hybrid steel wall panel system is introduced to overcome the deficiency in lateral load resisting capacity of cold-formed steel structures. The hybrid system is composed of a cold-formed steel part laterally connected to hot rolled part. The hot rolled steel part is responsible for carrying the whole lateral load; while the cold formed steel part is only required to transfer the lateral load to the hot rolled part without any local failure. The vertical load is beared by both hot rolled, and cold formed steel part, proportionally. In order to investigate the lateral performance of the proposed system, it should be tested under simultaneous lateral and vertical load. The main concern is to deliver the loads to each part during the test to simulate the real load distribution in the structure. In this paper, a detailed description of the proposed wall panel system and the designed testing rig is provided.

Keywords: cold-formed steel, hybrid system, wall panel system, testing rig design

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Authors: M. Pushparani, A. Sagaya

Abstract:

Embedded systems have emerged as important elements in various domains with extensive applications in automotive, commercial, consumer, healthcare and transportation markets, as there is emphasis on intelligent devices. On the other hand, Business Intelligence (BI) has also been extensively used in a range of applications, especially in the agriculture domain which is the area of this research. The aim of this research is to create a framework for Embedded Weight Comparison Algorithm with Business Intelligence (EWCA-BI). The weight comparison algorithm will be embedded within the plantation management system and the weighbridge system. This algorithm will be used to estimate the weight at the site and will be compared with the actual weight at the plantation. The algorithm will be used to build the necessary alerts when there is a discrepancy in the weight, thus enabling better decision making. In the current practice, data are collected from various locations in various forms. It is a challenge to consolidate data to obtain timely and accurate information for effective decision making. Adding to this, the unstable network connection leads to difficulty in getting timely accurate information. To overcome the challenges embedding is done on a portable device that will have the embedded weight comparison algorithm to also assist in data capture and synchronize data at various locations overcoming the network short comings at collection points. The EWCA-BI will provide real-time information at any given point of time, thus enabling non-latent BI reports that will provide crucial information to enable efficient operational decision making. This research has a high potential in bringing embedded system into the agriculture industry. EWCA-BI will provide BI reports with accurate information with uncompromised data using an embedded system and provide alerts, therefore, enabling effective operation management decision-making at the site.

Keywords: embedded business intelligence, weight comparison algorithm, oil palm plantation, embedded systems

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Authors: Rita U. Onolemhemhen, Saheed L. Bello, Akin P. Iwayemi

Abstract:

The effectiveness of energy demand policy depends on identifying the key drivers of energy demand both in the short-run and the long-run. This paper examines the influence of regional differences on the link between energy demand and other explanatory variables for Nigeria, China and USA using the Vector Error Correction Model (VECM) approach. This study employed annual time series data on energy consumption (ED), real gross domestic product (GDP) per capita (RGDP), real energy prices (P) and urbanization (N) for a thirty-six-year sample period. The utilized time-series data are sourced from World Bank’s World Development Indicators (WDI, 2016) and US Energy Information Administration (EIA). Results from the study, shows that all the independent variables (income, urbanization, and price) substantially affect the long-run energy consumption in Nigeria, USA and China, whereas, income has no significant effect on short-run energy demand in USA and Nigeria. In addition, the long-run effect of urbanization is relatively stronger in China. Urbanization is a key factor in energy demand, it therefore recommended that more attention should be given to the development of rural communities to reduce the inflow of migrants into urban communities which causes the increase in energy demand and energy excesses should be penalized while energy management should be incentivized.

Keywords: economic growth, energy demand, income, real GDP, urbanization, VECM

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Authors: Amita Jain, Shantanu Prakash, Suruchi Shukla

Abstract:

Introduction: Acute encephalitis syndrome (AES) is a complex multi etiology syndrome posing a great public health problem in the northern part of India. Japanese encephalitis (JE) virus is an established etiology of AES in this region. Recently, Scrub typhus (ST) is being recognized as an emerging aetiology of AES in JE endemic belt. This study was conducted to establish the direct evidence of Central nervous system invasion by Orientia tsutsugamushi leading to AES. Methodology: A total of 849 cases with clinical diagnosis of AES were enrolled from six districts (Deoria and its adjoining area) of the traditional north Indian Japanese encephalitis (JE) belt. Serum and Cerebrospinal fluid samples were collected and tested for major agent causing acute encephalitis. AES cases either positive for anti-ST IgM antibodies or negative for all tested etiologies were investigated for ST-DNA by real-time PCR. Results: Of these 505 cases, 250 patients were laboratory confirmed for O. tsutsugamushi infection either by anti-ST IgM antibodies positivity (n=206) on serum sample or by ST-DNA detection by real-time PCR assay on CSF sample (n=2) or by both (n=42).Total 29 isolate could be sequenced for 56KDa gene. Conclusion: All the strains were found to cluster with Gilliam strains. The majority of the isolates showed a 97–99% sequence similarity with Thailand and Cambodian strains. Gilliam strain of O.tsusugamushi is an emerging as one of the major aetiologies leading to AES in northern part of India.

Keywords: acute encephalitis syndrome, O. tsutsugamushi, Gilliam strain, North India, cerebrospinal fluid

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