Search results for: automated analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 28172

Search results for: automated analysis

27242 Opinion Mining and Sentiment Analysis on DEFT

Authors: Najiba Ouled Omar, Azza Harbaoui, Henda Ben Ghezala

Abstract:

Current research practices sentiment analysis with a focus on social networks, DEfi Fouille de Texte (DEFT) (Text Mining Challenge) evaluation campaign focuses on opinion mining and sentiment analysis on social networks, especially social network Twitter. It aims to confront the systems produced by several teams from public and private research laboratories. DEFT offers participants the opportunity to work on regularly renewed themes and proposes to work on opinion mining in several editions. The purpose of this article is to scrutinize and analyze the works relating to opinions mining and sentiment analysis in the Twitter social network realized by DEFT. It examines the tasks proposed by the organizers of the challenge and the methods used by the participants.

Keywords: opinion mining, sentiment analysis, emotion, polarity, annotation, OSEE, figurative language, DEFT, Twitter, Tweet

Procedia PDF Downloads 135
27241 ELectromagnetic-Thermal Coupled Analysis of PMSM with Cooling Channel

Authors: Hyun-Woo Jun, Tae-Chul Jeong, Huai-Cong Liu, Ju Lee

Abstract:

The paper presents the electromagnetic-thermal flow coupled analysis of permanent magnet synchronous motor (PMSM) which has cooling channel in stator core for forced air cooling. Unlike the general PMSM design, to achieve ohmic loss reduction for high efficiency, cooling channel actively used in the stator core. Equivalent thermal network model was made to analyze the effect of the formation of the additional flow path in the core. According to the shape and position changing of the channel design, electromagnetic-thermal coupled analysis results were reviewed.

Keywords: coupled problems, electric motors, equivalent circuits, fluid flow, thermal analysis

Procedia PDF Downloads 617
27240 An Innovation Decision Process View in an Adoption of Total Laboratory Automation

Authors: Chia-Jung Chen, Yu-Chi Hsu, June-Dong Lin, Kun-Chen Chan, Chieh-Tien Wang, Li-Ching Wu, Chung-Feng Liu

Abstract:

With fast advances in healthcare technology, various total laboratory automation (TLA) processes have been proposed. However, adopting TLA needs quite high funding. This study explores an early adoption experience by Taiwan’s large-scale hospital group, the Chimei Hospital Group (CMG), which owns three branch hospitals (Yongkang, Liouying and Chiali, in order by service scale), based on the five stages of Everett Rogers’ Diffusion Decision Process. 1.Knowledge stage: Over the years, two weaknesses exists in laboratory department of CMG: 1) only a few examination categories (e.g., sugar testing and HbA1c) can now be completed and reported within a day during an outpatient clinical visit; 2) the Yongkang Hospital laboratory space is dispersed across three buildings, resulting in duplicated investment in analysis instruments and inconvenient artificial specimen transportation. Thus, the senior management of the department raised a crucial question, was it time to process the redesign of the laboratory department? 2.Persuasion stage: At the end of 2013, Yongkang Hospital’s new building and restructuring project created a great opportunity for the redesign of the laboratory department. However, not all laboratory colleagues had the consensus for change. Thus, the top managers arranged a series of benchmark visits to stimulate colleagues into being aware of and accepting TLA. Later, the director of the department proposed a formal report to the top management of CMG with the results of the benchmark visits, preliminary feasibility analysis, potential benefits and so on. 3.Decision stage: This TLA suggestion was well-supported by the top management of CMG and, finally, they made a decision to carry out the project with an instrument-leasing strategy. After the announcement of a request for proposal and several vendor briefings, CMG confirmed their laboratory automation architecture and finally completed the contracts. At the same time, a cross-department project team was formed and the laboratory department assigned a section leader to the National Taiwan University Hospital for one month of relevant training. 4.Implementation stage: During the implementation, the project team called for regular meetings to review the results of the operations and to offer an immediate response to the adjustment. The main project tasks included: 1) completion of the preparatory work for beginning the automation procedures; 2) ensuring information security and privacy protection; 3) formulating automated examination process protocols; 4) evaluating the performance of new instruments and the instrument connectivity; 5)ensuring good integration with hospital information systems (HIS)/laboratory information systems (LIS); and 6) ensuring continued compliance with ISO 15189 certification. 5.Confirmation stage: In short, the core process changes include: 1) cancellation of signature seals on the specimen tubes; 2) transfer of daily examination reports to a data warehouse; 3) routine pre-admission blood drawing and formal inpatient morning blood drawing can be incorporated into an automatically-prepared tube mechanism. The study summarizes below the continuous improvement orientations: (1) Flexible reference range set-up for new instruments in LIS. (2) Restructure of the specimen category. (3) Continuous review and improvements to the examination process. (4) Whether installing the tube (specimen) delivery tracks need further evaluation.

Keywords: innovation decision process, total laboratory automation, health care

Procedia PDF Downloads 415
27239 Time-Frequency Modelling and Analysis of Faulty Rotor

Authors: B. X. Tchomeni, A. A. Alugongo, T. B. Tengen

Abstract:

In this paper, de Laval rotor system has been characterized by a hinge model and its transient response numerically treated for a dynamic solution. The effect of the ensuing non-linear disturbances namely rub and breathing crack is numerically simulated. Subsequently, three analysis methods: Orbit Analysis, Fast Fourier Transform (FFT) and Wavelet Transform (WT) are employed to extract features of the vibration signal of the faulty system. An analysis of the system response orbits clearly indicates the perturbations due to the rotor-to-stator contact. The sensitivities of WT to the variation in system speed have been investigated by Continuous Wavelet Transform (CWT). The analysis reveals that features of crack, rubs and unbalance in vibration response can be useful for condition monitoring. WT reveals its ability to detect non-linear signal, and obtained results provide a useful tool method for detecting machinery faults.

Keywords: Continuous wavelet, crack, discrete wavelet, high acceleration, low acceleration, nonlinear, rotor-stator, rub

Procedia PDF Downloads 343
27238 Evaluating The Effects of Fundamental Analysis on Earnings Per Share Concept in Stock Valuation in the Zimbabwe Stock Exchange Market

Authors: Brian Basvi

Abstract:

A technique for analyzing a security's intrinsic value is called fundamental analysis. It involves looking at relevant financial, economic, and other qualitative and quantitative aspects. Earnings Per Share (EPS), a crucial metric in fundamental analysis, is calculated by dividing a company's net income by the total number of outstanding shares. With more than 70 listed businesses, the Zimbabwe Stock Exchange (ZSE) is the primary stock exchange in Zimbabwe. This study applies the EPS financial ratio and stock valuation techniques to historical stock data from 68 companies listed on the Zimbabwe Stock Exchange. According to a ZSE study, EPS significantly affects share prices that are listed on the market. The study's objective was to assess how fundamental analysis affected the idea of EPS in ZSE stock valuation. It concluded that EPS is an important consideration for investors when they make judgments about their investments. According to the study's findings, fundamental analysis is a useful tool for ZSE investors since it offers insightful information about a company's financial performance and aids in decision-making. Investors can have a better understanding of a company's underlying worth and prospects for future growth by looking into EPS and other basic aspects.

Keywords: fundamental analysis, stock valuation, EPS, share pricing

Procedia PDF Downloads 36
27237 Investigation of Gas Tungsten Arc Welding Parameters on Residual Stress of Heat Affected Zone in Inconel X750 Super Alloy Welding Using Finite Element Method

Authors: Kimia Khoshdel Vajari, Saber Saffar

Abstract:

Reducing the residual stresses caused by welding is desirable for the industry. The effect of welding sequence, as well as the effect of yield stress on the number of residual stresses generated in Inconel X750 superalloy sheets and beams, have been investigated. The finite element model used in this research is a three-dimensional thermal and mechanical model, and the type of analysis is indirect coupling. This analysis is done in two stages. First, thermal analysis is performed, and then the thermal changes of the first analysis are used as the applied load in the second analysis. ABAQUS has been used for modeling, and the Dflux subroutine has been used in the Fortran programming environment to move the arc and the molten pool. The results of this study show that the amount of tensile residual stress in symmetric, discontinuous, and symmetric-discontinuous welds is reduced to a maximum of 27%, 54%, and 37% compared to direct welding, respectively. The results also show that the amount of residual stresses created by welding increases linearly with increasing yield stress with a slope of 40%.

Keywords: residual stress, X750 superalloy, finite element, welding, thermal analysis

Procedia PDF Downloads 109
27236 A Sequential Approach for Random-Effects Meta-Analysis

Authors: Samson Henry Dogo, Allan Clark, Elena Kulinskaya

Abstract:

The objective in meta-analysis is to combine results from several independent studies in order to create generalization and provide evidence based for decision making. But recent studies show that the magnitude of effect size estimates reported in many areas of research finding changed with year publication and this can impair the results and conclusions of meta-analysis. A number of sequential methods have been proposed for monitoring the effect size estimates in meta-analysis. However they are based on statistical theory applicable to fixed effect model (FEM). For random-effects model (REM), the analysis incorporates the heterogeneity variance, tau-squared and its estimation create complications. In this paper proposed the use of Gombay and Serbian (2005) truncated CUSUM-type test with asymptotically valid critical values for sequential monitoring of REM. Simulation results show that the test does not control the Type I error well, and is not recommended. Further work required to derive an appropriate test in this important area of application.

Keywords: meta-analysis, random-effects model, sequential test, temporal changes in effect sizes

Procedia PDF Downloads 466
27235 Spectral Analysis of Heart Rate Variability for Normal and Preeclamptic Pregnants

Authors: Abdulnasir Hossen, Alaa Barhoum, Deepali Jaju, V. Gowri, L. Al-Kharusi, M. Hassan, K. Al-Hashmi

Abstract:

Preeclampsia is a pregnancy disorder associated with increase in blood pressure and excess amount of protein in the urine. HRV analysis has been used by many researchers to identify preeclamptic pregnancy from normal pregnancy. A study in this regard to identify preeclamptic pregnancy in Oman from normal pregnant was conducted on 40 subjects (20 patients and 20 normal). The subjects were collected from two hospitals in Oman. A Fast Fourier transform (FFT) spectral analysis has shown that patients with preeclamptic pregnancy have a reduction in the power of the HF band and an increase in the power of the LF band of HRV compared with subjects with normal pregnancy. The accuracy of identification obtained was 80%.

Keywords: preelampsia, pregnancy hypertension, normal pregnant, FFT, spectral analysis, HRV

Procedia PDF Downloads 552
27234 Enhancing Transfer Path Analysis with In-Situ Component Transfer Path Analysis for Interface Forces Identification

Authors: Raef Cherif, Houssine Bakkali, Wafaa El Khatiri, Yacine Yaddaden

Abstract:

The analysis of how vibrations are transmitted between components is required in many engineering applications. Transfer path analysis (TPA) has been a valuable engineering tool for solving Noise, Vibration, and Harshness (NVH problems using sub-structuring applications. The most challenging part of a TPA analysis is estimating the equivalent forces at the contact points between the active and the passive side. Component TPA in situ Method calculates these forces by inverting the frequency response functions (FRFs) measured at the passive subsystem, relating the motion at indicator points to forces at the interface. However, matrix inversion could pose problems due to the ill-conditioning of the matrices leading to inaccurate results. This paper establishes a TPA model for an academic system consisting of two plates linked by four springs. A numerical study has been performed to improve the interface forces identification. Several parameters are studied and discussed, such as the singular value rejection and the number and position of indicator points chosen and used in the inversion matrix.

Keywords: transfer path analysis, matrix inverse method, indicator points, SVD decomposition

Procedia PDF Downloads 81
27233 Mineralogy and Thermobarometry of Xenoliths in Basalt from the Chanthaburi-Trat Gem Fields, Thailand

Authors: Apichet Boonsoong

Abstract:

In the Chanthaburi-Trat basalts, xenoliths are composed of essentially ultramafic xenoliths (particularly spinel lherzolite) with a few of an aggregate of feldspar. Some 19 ultramafic xenoliths were collected from 13 different locations. They range in size from 3.5 to 60mm across. Most are weathered and oxidized on the surface but fresh samples are obtained from cut surfaces. Chemical analyses were performed on carbon-coated polished thin sections using a fully automated CAMECA SX-50 electron microprobe (EMPA) in wavelength-dispersive mode. In thin section, they are seen to consist of variable amounts of olivine, clinopyroxene, orthopyroxene with minor spinel and plagioclase, and are classed as lherzolite. Modal compositions of the ultramafic nodules vary with olivine (60-75%), clinopyroxene (20-30%), orthopyroxene (0-15%), minor spinel (1-3%) and plagioclase (<1%). The essential minerals form an equigranular, medium- to coarse-grained, granoblastic texture, and all are in mutual contact indicating attainment of equilibrium. Reaction rims are common along the nodule margins and in some are also present along grain boundaries. Zoning occurs in clinopyroxene, and to a lesser extent in orthopyroxene. The homogeneity of mineral compositions in lherzolite xenoliths suggests the attainment of equilibrium. The equilibration temperatures of these xenoliths are estimated to be in the range of 973 to 1063°C. Pressure estimates are not so easily obtained because no suitable barometer exists for garnet-free lherzolites and so an indirect method was used. The general mineral assemblage of the lherzolite xenoliths and the absence of garnet indicate a pressure range of approximately 12–19kbar, which is equivalent to depths approximately of 38 to 60km.

Keywords: chanthaburi-trat basalts, spinel lherzolite, xenoliths, 973 to 1063°C, 38 to 60km

Procedia PDF Downloads 116
27232 Exponential Spline Solution for Singularly Perturbed Boundary Value Problems with an Uncertain-But-Bounded Parameter

Authors: Waheed Zahra, Mohamed El-Beltagy, Ashraf El Mhlawy, Reda Elkhadrawy

Abstract:

In this paper, we consider singular perturbation reaction-diffusion boundary value problems, which contain a small uncertain perturbation parameter. To solve these problems, we propose a numerical method which is based on an exponential spline and Shishkin mesh discretization. While interval analysis principle is used to deal with the uncertain parameter, sensitivity analysis has been conducted using different methods. Numerical results are provided to show the applicability and efficiency of our method, which is ε-uniform convergence of almost second order.

Keywords: singular perturbation problem, shishkin mesh, two small parameters, exponential spline, interval analysis, sensitivity analysis

Procedia PDF Downloads 271
27231 Estimating the Life-Distribution Parameters of Weibull-Life PV Systems Utilizing Non-Parametric Analysis

Authors: Saleem Z. Ramadan

Abstract:

In this paper, a model is proposed to determine the life distribution parameters of the useful life region for the PV system utilizing a combination of non-parametric and linear regression analysis for the failure data of these systems. Results showed that this method is dependable for analyzing failure time data for such reliable systems when the data is scarce.

Keywords: masking, bathtub model, reliability, non-parametric analysis, useful life

Procedia PDF Downloads 557
27230 A Survey of Skin Cancer Detection and Classification from Skin Lesion Images Using Deep Learning

Authors: Joseph George, Anne Kotteswara Roa

Abstract:

Skin disease is one of the most common and popular kinds of health issues faced by people nowadays. Skin cancer (SC) is one among them, and its detection relies on the skin biopsy outputs and the expertise of the doctors, but it consumes more time and some inaccurate results. At the early stage, skin cancer detection is a challenging task, and it easily spreads to the whole body and leads to an increase in the mortality rate. Skin cancer is curable when it is detected at an early stage. In order to classify correct and accurate skin cancer, the critical task is skin cancer identification and classification, and it is more based on the cancer disease features such as shape, size, color, symmetry and etc. More similar characteristics are present in many skin diseases; hence it makes it a challenging issue to select important features from a skin cancer dataset images. Hence, the skin cancer diagnostic accuracy is improved by requiring an automated skin cancer detection and classification framework; thereby, the human expert’s scarcity is handled. Recently, the deep learning techniques like Convolutional neural network (CNN), Deep belief neural network (DBN), Artificial neural network (ANN), Recurrent neural network (RNN), and Long and short term memory (LSTM) have been widely used for the identification and classification of skin cancers. This survey reviews different DL techniques for skin cancer identification and classification. The performance metrics such as precision, recall, accuracy, sensitivity, specificity, and F-measures are used to evaluate the effectiveness of SC identification using DL techniques. By using these DL techniques, the classification accuracy increases along with the mitigation of computational complexities and time consumption.

Keywords: skin cancer, deep learning, performance measures, accuracy, datasets

Procedia PDF Downloads 126
27229 Analysis on Prediction Models of TBM Performance and Selection of Optimal Input Parameters

Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

Abstract:

An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

Procedia PDF Downloads 306
27228 Vehicle Speed Estimation Using Image Processing

Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

Abstract:

In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

Procedia PDF Downloads 80
27227 Microgravity, Hydrological and Metrological Monitoring of Shallow Ground Water Aquifer in Al-Ain, UAE

Authors: Serin Darwish, Hakim Saibi, Amir Gabr

Abstract:

The United Arab Emirates (UAE) is situated within an arid zone where the climate is arid and the recharge of the groundwater is very low. Groundwater is the primary source of water in the United Arab Emirates. However, rapid expansion, population growth, agriculture, and industrial activities have negatively affected these limited water resources. The shortage of water resources has become a serious concern due to the over-pumping of groundwater to meet demand. In addition to the deficit of groundwater, the UAE has one of the highest per capita water consumption rates in the world. In this study, a combination of time-lapse measurements of microgravity and depth to groundwater level in selected wells in Al Ain city was used to estimate the variations in groundwater storage. Al-Ain is the second largest city in Abu Dhabi Emirates and the third largest city in the UAE. The groundwater in this region has been overexploited. Relative gravity measurements were acquired using the Scintrex CG-6 Autograv. This latest generation gravimeter from Scintrex Ltd provides fast, precise gravity measurements and automated corrections for temperature, tide, instrument tilt and rejection of data noise. The CG-6 gravimeter has a resolution of 0.1μGal. The purpose of this study is to measure the groundwater storage changes in the shallow aquifers based on the application of microgravity method. The gravity method is a nondestructive technique that allows collection of data at almost any location over the aquifer. Preliminary results indicate a possible relationship between microgravity and water levels, but more work needs to be done to confirm this. The results will help to develop the relationship between monthly microgravity changes with hydrological and hydrogeological changes of shallow phreatic. The study will be useful in water management considerations and additional future investigations.

Keywords: Al-Ain, arid region, groundwater, microgravity

Procedia PDF Downloads 148
27226 Unsupervised Echocardiogram View Detection via Autoencoder-Based Representation Learning

Authors: Andrea Treviño Gavito, Diego Klabjan, Sanjiv J. Shah

Abstract:

Echocardiograms serve as pivotal resources for clinicians in diagnosing cardiac conditions, offering non-invasive insights into a heart’s structure and function. When echocardiographic studies are conducted, no standardized labeling of the acquired views is performed. Employing machine learning algorithms for automated echocardiogram view detection has emerged as a promising solution to enhance efficiency in echocardiogram use for diagnosis. However, existing approaches predominantly rely on supervised learning, necessitating labor-intensive expert labeling. In this paper, we introduce a fully unsupervised echocardiographic view detection framework that leverages convolutional autoencoders to obtain lower dimensional representations and the K-means algorithm for clustering them into view-related groups. Our approach focuses on discriminative patches from echocardiographic frames. Additionally, we propose a trainable inverse average layer to optimize decoding of average operations. By integrating both public and proprietary datasets, we obtain a marked improvement in model performance when compared to utilizing a proprietary dataset alone. Our experiments show boosts of 15.5% in accuracy and 9.0% in the F-1 score for frame-based clustering, and 25.9% in accuracy and 19.8% in the F-1 score for view-based clustering. Our research highlights the potential of unsupervised learning methodologies and the utilization of open-sourced data in addressing the complexities of echocardiogram interpretation, paving the way for more accurate and efficient cardiac diagnoses.

Keywords: artificial intelligence, echocardiographic view detection, echocardiography, machine learning, self-supervised representation learning, unsupervised learning

Procedia PDF Downloads 26
27225 Sustainable Tourism from a Multicriteria Analysis Perspective

Authors: Olga Blasco-Blasco, Vicente Liern

Abstract:

The development of tourism since the mid-20th century has raised problems of overcrowding, indiscriminate construction in seaside areas and gentrification. Increasingly, the World Tourism Organisation and public institutions are promoting policies that encourage sustainability. From the perspective of sustainability, three types of tourism can be established: traditional tourism, sustainable tourism and sustainable impact tourism. Measuring sustainability is complex due to its multiple dimensions of different relative importance and diversity in nature. In order to try to answer this problem and to identify the benefits of applying policies that promote sustainable tourism, a decision-making analysis will be carried out through the application of a multicriteria analysis method. The proposal is applied to hotel reservations and to the evaluation and management of tourism sustainability in the Spanish Autonomous Communities.

Keywords: sustainable tourism, multicriteria analysis, flexible optimization, composite indicators

Procedia PDF Downloads 308
27224 An Analysis of Mongolian Possessive Markers

Authors: Yaxuan Wang

Abstract:

It has long been a mystery that why the Mongolian possessive suffix, which is constrained by Condition A of binding theory, has the ability to probe a potential antecedent outside of its binding domain. This squib argues that binding theory alone is not sufficient to explain the linguistic facts and proposes an analysis adopting the Agree operation. The current analysis correctly predicts all the possible and impossible structures, with an additional hypothesis that Mongolian possessive suffixes serve as an antecedent for PROs in adjunct. The findings thus provide insights into how Agree operates in Mongolian language.

Keywords: syntax, Mongolian, agreement, possessive particles

Procedia PDF Downloads 97
27223 Automated Detection of Targets and Retrieve the Corresponding Analytics Using Augmented Reality

Authors: Suvarna Kumar Gogula, Sandhya Devi Gogula, P. Chanakya

Abstract:

Augmented reality is defined as the collection of the digital (or) computer generated information like images, audio, video, 3d models, etc. and overlay them over the real time environment. Augmented reality can be thought as a blend between completely synthetic and completely real. Augmented reality provides scope in a wide range of industries like manufacturing, retail, gaming, advertisement, tourism, etc. and brings out new dimensions in the modern digital world. As it overlays the content, it makes the users enhance the knowledge by providing the content blended with real world. In this application, we integrated augmented reality with data analytics and integrated with cloud so the virtual content will be generated on the basis of the data present in the database and we used marker based augmented reality where every marker will be stored in the database with corresponding unique ID. This application can be used in wide range of industries for different business processes, but in this paper, we mainly focus on the marketing industry which helps the customer in gaining the knowledge about the products in the market which mainly focus on their prices, customer feedback, quality, and other benefits. This application also focuses on providing better market strategy information for marketing managers who obtain the data about the stocks, sales, customer response about the product, etc. In this paper, we also included the reports from the feedback got from different people after the demonstration, and finally, we presented the future scope of Augmented Reality in different business processes by integrating with new technologies like cloud, big data, artificial intelligence, etc.

Keywords: augmented reality, data analytics, catch room, marketing and sales

Procedia PDF Downloads 232
27222 Unlocking Justice: Exploring the Power and Challenges of DNA Analysis in the Criminal Justice System

Authors: Sandhra M. Pillai

Abstract:

This article examines the relevance, difficulties, and potential applications of DNA analysis in the criminal justice system. A potent tool for connecting suspects to crime sites, clearing the innocent of wrongdoing, and resolving cold cases, DNA analysis has transformed forensic investigations. The scientific foundations of DNA analysis, including DNA extraction, sequencing, and statistical analysis, are covered in the article. To guarantee accurate and trustworthy findings, it also discusses the significance of quality assurance procedures, chain of custody, and DNA sample storage. DNA analysis has significantly advanced science, but it also brings up substantial moral and legal issues. To safeguard individual rights and uphold public confidence, privacy concerns, possible discrimination, and abuse of DNA information must be properly addressed. The paper also emphasises the effects of the criminal justice system on people and communities while highlighting the necessity of equity, openness, and fair access to DNA testing. The essay describes the obstacles and future directions for DNA analysis. It looks at cutting-edge technology like next-generation sequencing, which promises to make DNA analysis quicker and more affordable. To secure the appropriate and informed use of DNA evidence, it also emphasises the significance of multidisciplinary collaboration among scientists, law enforcement organisations, legal experts, and policymakers. In conclusion, DNA analysis has enormous potential for improving the course of criminal justice. We can exploit the potential of DNA technology while respecting the ideals of justice, fairness, and individual rights by navigating the ethical, legal, and societal issues and encouraging discussion and collaboration.

Keywords: DNA analysis, DNA evidence, reliability, validity, legal frame, admissibility, ethical considerations, impact, future direction, challenges

Procedia PDF Downloads 63
27221 Finite Element Analysis of the Ordinary Reinforced Concrete Bridge Piers

Authors: Nabin Raj Chaulagain

Abstract:

Most of the concrete bridges in Nepal constructed during 90's and before are made up of low strength ordinary concrete which might be one of the reasons for damage in higher magnitude earthquake. Those bridges were designed by the outdated bridge codes which might not account the large seismic loads. This research investigates the seismic vulnerability of the existing single column ordinary concrete bridge pier by finite element modeling, using the software Seismostruct. The existing bridge pier capacity has been assessed using nonlinear pushover analysis and performance is compared after retrofitting those pier models with CFRP. Furthermore, the seismic evaluation was made by conducting cyclic loading test at different drift percentage. The performance analysis of bridge pier by nonlinear pushover analysis is further validated by energy dissipation phenomenon measured from the hysteric loop for each model of ordinary concrete piers.

Keywords: finite element modeling, ordinary concrete bridge pier, performance analysis, retrofitting

Procedia PDF Downloads 316
27220 Meta-Analysis of Exercise Interventions for Children and Adolescents Diagnosed with Pediatric Metabolic Syndrome

Authors: James M. Geidner

Abstract:

Objective: The purpose of this meta-analysis was to examine the evidence for the effectiveness of exercise interventions on reducing metabolic components in children and/or adolescents diagnosed with Paediatric Metabolic Syndrome. Methods: A computerized search was made from four databases: PubMed, PsycInfo, SPORTDiscus, Cochrane Central Register. The analysis was restricted to children and adolescents with metabolic syndrome examining the effect of exercise interventions on metabolic components. Effect size and 95% confidence interval were calculated and the heterogeneity of the studies was estimated using Cochran’s Q-statistic and I2. Bias was assessed using multiple tools and statistical analyses. Results: Thirteen studies, consisting of 19 separate trials, were selected for the meta-analysis as they fulfilled the inclusion criteria (n=908). Exercise interventions resulted in decreased waist circumference, systolic blood pressure, diastolic blood pressure, fasting glucose, insulin resistance, triglycerides, and High-Density Lipoprotein Cholesterol (HDL-C). Conclusions: This meta-analysis provides insights into the effectiveness of exercise interventions on markers of Paediatric Metabolic Syndrome in children and adolescents.

Keywords: metabolic syndrome, syndrome x, pediatric, meta-analysis

Procedia PDF Downloads 169
27219 Pre- and Post-Analyses of Disruptive Quay Crane Scheduling Problem

Authors: K. -H. Yang

Abstract:

In the past, the quay crane operations have been well studied. There were a certain number of scheduling algorithms for quay crane operations, but without considering some nuisance factors that might disrupt the quay crane operations. For example, bad grapples make a crane unable to load or unload containers or a sudden strong breeze stops operations temporarily. Although these disruptive conditions randomly occur, they influence the efficiency of quay crane operations. The disruption is not considered in the operational procedures nor is evaluated in advance for its impacts. This study applies simulation and optimization approaches to develop structures of pre-analysis and post-analysis for the Quay Crane Scheduling Problem to deal with disruptive scenarios for quay crane operation. Numerical experiments are used for demonstrations for the validity of the developed approaches.

Keywords: disruptive quay crane scheduling, pre-analysis, post-analysis, disruption

Procedia PDF Downloads 218
27218 Determination of Identification and Antibiotic Resistance Rates of Pseudomonas aeruginosa Strains from Various Clinical Specimens in a University Hospital for Two Years, 2013-2015

Authors: Recep Kesli, Gulsah Asik, Cengiz Demir, Onur Turkyilmaz

Abstract:

Objective: Pseudomonas aeruginosa (P. aeruginosa) is an important nosocomial pathogen which causes serious hospital infections and is resistant to many commonly used antibiotics. P. aeruginosa can develop resistance during therapy and also it is very resistant to disinfectant chemicals. It may be found in respiratory support devices in hospitals. In this study, the antibiotic resistance of P. aeruginosa strains isolated from bronchial aspiration samples was evaluated retrospectively. Methods: Between October 2013 and September 2015, a total of 318 P. aeruginosa were isolated from clinical samples obtained from various intensive care units and inpatient patients hospitalized at Afyon Kocatepe University, ANS Practice and Research Hospital. Isolated bacteria identified by using both the conventional methods and automated identification system-VITEK 2 (bioMerieux, Marcy l’etoile France). Antibacterial resistance tests were performed by using Kirby-Bauer disc (Oxoid, Hampshire, England) diffusion method following the recommendations of CLSI. Results: Antibiotic resistance rates of identified 318 P. aeruginosa strains were found as follows for tested antibiotics; 32 % amikacin, 42% gentamicin, 43% imipenem, 43% meropenem, 50% ciprofloxacin, 57% levofloxacin, 38% cefepime, 63% ceftazidime, and 85% piperacillin/tazobactam. Conclusion: Resistance profiles change according to years and provinces for P. aeruginosa, so these findings should be considered empirical treatment choices. In this study, the highest and lowest resistance rates found against piperacillin/tazobactam % 85, and amikacin %32.

Keywords: Pseudomonas aeruginosa, antibiotic resistance rates, intensive care unit, Pseudomonas spp.

Procedia PDF Downloads 287
27217 Big Data Analysis with RHadoop

Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

Abstract:

It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

Procedia PDF Downloads 433
27216 Development of Standard Evaluation Technique for Car Carpet Floor

Authors: In-Sung Lee, Un-Hwan Park, Jun-Hyeok Heo, Tae-Hyeon Oh, Dae-Gyu Park

Abstract:

Statistical Energy Analysis is to be the most effective CAE Method for air-born noise analysis in the Automotive area. This study deals with a method to predict the noise level inside of the car under the steady-state condition using the SEA model of car for air-born noise analysis. We can identify weakened part due to the acoustic material properties using it. Therefore, it is useful for the material structural design.

Keywords: air-born noise, material structural design, acoustic material properties, absorbing

Procedia PDF Downloads 419
27215 Design and Synthesis of Copper-Zeolite Composite for Antimicrobial Activity and Heavy Metal Removal From Waste Water

Authors: Feleke Terefe Fanta

Abstract:

Background: The existence of heavy metals and coliform bacteria contaminants in aquatic system of Akaki river basin, a sub city of Addis Ababa, Ethiopia has become a public concern as human population increases and land development continues. Hence, it is the right time to design treatment technologies that can handle multiple pollutants. Results: In this study, we prepared a synthetic zeolites and copper doped zeolite composite adsorbents as cost effective and simple approach to simultaneously remove heavy metals and total coliforms from wastewater of Akaki river. The synthesized copper–zeolite X composite was obtained by ion exchange method of copper ions into zeolites frameworks. Iodine test, XRD, FTIR and autosorb IQ automated gas sorption analyzer were used to characterize the adsorbents. The mean concentrations of Cd, Cr, and Pb in untreated sample were 0.795, 0.654 and 0.7025 mg/L respectively. These concentrations decreased to Cd (0.005 mg/L), Cr (0.052 mg/L) and Pb (bellow detection limit, BDL) for sample treated with bare zeolite X while a further decrease in concentration of Cd (0.005 mg/L), Cr (BDL) and Pb (BDL) was observed for the sample treated with copper–zeolite composite. Zeolite X and copper-modified zeolite X showed complete elimination of total coliforms after 90 and 50 min contact time respectively. Conclusion: The results obtained in this study showed high antimicrobial disinfection and heavy metal removal efficiencies of the synthesized adsorbents. Furthermore, these sorbents are efficient in significantly reducing physical parameters such as electrical conductivity, turbidity, BOD and COD.

Keywords: WASTE WATER, COPPER DOPED ZEOITE X, ADSORPITION, HEAVY METAL, DISINFECTION, AKAKI RIVER

Procedia PDF Downloads 63
27214 Network Analysis and Sex Prediction based on a full Human Brain Connectome

Authors: Oleg Vlasovets, Fabian Schaipp, Christian L. Mueller

Abstract:

we conduct a network analysis and predict the sex of 1000 participants based on ”connectome” - pairwise Pearson’s correlation across 436 brain parcels. We solve the non-smooth convex optimization problem, known under the name of Graphical Lasso, where the solution includes a low-rank component. With this solution and machine learning model for a sex prediction, we explain the brain parcels-sex connectivity patterns.

Keywords: network analysis, neuroscience, machine learning, optimization

Procedia PDF Downloads 145
27213 Restructuring and Revitalising School Leadership Philosophy in Nepal: Embracing Contextual and Equitable Approaches

Authors: Shankar Dhakal, Andrew Jones, Geoffrey W. Lummis

Abstract:

The Federal Democratic Republic of Nepal is a linguistically, culturally, and ethnically diverse country with approximately 123 different spoken languages that represent several ethnic, cultural, and religious groups of people. With a population of about 30 million, long-standing disparities and inequalities in access and achievement in education have constantly been challenging to provide equitable educational opportunities for all students. While the new constitution of federal Nepal (2015) stipulates that all schools serve the interests of diverse communities, leadership practices have failed to adopt local contextual sensitivities, leading to traditional, authoritarian approaches and entrenched inequalities. However, little is known about how Nepali secondary school principals can adapt and implement context-responsive and equitable strategies to ensure equity and inclusiveness in its enormously diverse socio-cultural contexts. To fill this gap, this study explores how educational leadership approaches and philosophies are transformed using a multi-case automated/ethnographic research methodology underpinned by the paradigm of critical constructivism. This paper reconstructs to see if school leadership in Nepal can produce more equitable and contextual outcomes. The results of this study highlight the need for a paradigm shift and the adoption of innovative leadership approaches that foster humility, empathy, and compassion in school leaders to achieve better school outcomes. This research provides valuable insights into existing literary gaps and provides guidance for future school leadership policies and practices at the personal, cultural, and political levels.

Keywords: school leadership, auto/ethnography, equitable and context-responsive leadership, Nepal

Procedia PDF Downloads 72