Search results for: computational accuracy

Authors: Nafsi K. Ashraf, C. V. Vipin, V. Anantha Subramanian

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This paper reports the design of a waterjet propulsion system for an amphibious vehicle based on circulation distribution over the camber line for the sections of the impeller and stator. In contrast with the conventional waterjet design, the inlet duct is straight for water entry parallel and in line with the nozzle exit. The extended nozzle after the stator bowl makes the flow more axial further improving thrust delivery. Waterjet works on the principle of volume flow rate through the system and unlike the propeller, it is an internal flow system. The major difference between the propeller and the waterjet occurs at the flow passing the actuator. Though a ducted propeller could constitute the equivalent of waterjet propulsion, in a realistic situation, the nozzle area for the Waterjet would be proportionately larger to the inlet area and propeller disc area. Moreover, the flow rate through impeller disk is controlled by nozzle area. For these reasons the waterjet design is based on pump systems rather than propellers and therefore it is important to bring out the characteristics of the flow from this point of view. The analysis is carried out using computational fluid dynamics. Design of waterjet propulsion is carried out adapting the axial flow pump design and performance analysis was done with three-dimensional computational fluid dynamics (CFD) code. With the varying environmental conditions as well as with the necessity of high discharge and low head along with the space confinement for the given amphibious vehicle, an axial pump design is suitable. The major problem of inlet velocity distribution is the large variation of velocity in the circumferential direction which gives rise to heavy blade loading that varies with time. The cavitation criteria have also been taken into account as per the hydrodynamic pump design. Generally, waterjet propulsion system can be parted into the inlet, the pump, the nozzle and the steering device. The pump further comprises an impeller and a stator. Analytical and numerical approaches such as RANSE solver has been undertaken to understand the performance of designed waterjet propulsion system. Unlike in case of propellers the analysis was based on head flow curve with efficiency and power curves. The modeling of the impeller is performed using rigid body motion approach. The realizable k-ϵ model has been used for turbulence modeling. The appropriate boundary conditions are applied for the domain, domain size and grid dependence studies are carried out.

Keywords: amphibious vehicle, CFD, impeller design, waterjet propulsion

Procedia PDF Downloads 229

Authors: Michelle Rippy

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Medicolegal death investigation historically is a field that does not receive much research attention or advancement, as all of the subjects are deceased. Public health threats, drug epidemics and contagious diseases are typically recognized in decedents first, with thorough and accurate death investigations able to assist in epidemiology research and prevention programs. One vital component of medicolegal death investigation is determining the decedent’s time of death. An accurate time of death can assist in corroborating alibies, determining sequence of death in multiple casualty circumstances and provide vital facts in civil situations. Popular television portrays an unrealistic forensic ability to provide the exact time of death to the minute for someone found deceased with no witnesses present. The actuality of unattended decedent time of death determination can generally only be narrowed to a 4-6 hour window. In the mid- to late-20th century, liver temperatures were an invasive action taken by death investigators to determine the decedent’s core temperature. The core temperature was programmed into an equation to determine an approximate time of death. Due to many inconsistencies with the placement of the thermometer and other variables, the accuracy of the liver temperatures was dispelled and this once common place action lost scientific support. Currently, medicolegal death investigators utilize three major after death or post-mortem changes at a death scene. Many factors are considered in the subjective determination as to the time of death, including the cooling of the decedent, stiffness of the muscles, release of blood internally, clothing, ambient temperature, disease and recent exercise. Current research is utilizing non-invasive hospital grade tympanic thermometers to measure the temperature in the each of the decedent’s ears. This tool can be used at the scene and in conjunction with scene indicators may provide a more accurate time of death. The research is significant and important to investigations and can provide an area of accuracy to a historically inaccurate area, considerably improving criminal and civil death investigations. The goal of the research is to provide a scientific basis to unwitnessed deaths, instead of the art that the determination currently is. The research is currently in progress with expected termination in December 2018. There are currently 15 completed case studies with vital information including the ambient temperature, decedent height/weight/sex/age, layers of clothing, found position, if medical intervention occurred and if the death was witnessed. This data will be analyzed with the multiple variables studied and available for presentation in January 2019.

Keywords: algor mortis, forensic pathology, investigations, medicolegal, time of death, tympanic

Procedia PDF Downloads 120

Authors: Nuwan Kuruwitaarachchi, M. K. M. Peiris, C. N. Madawala, K. M. A. R. Perera, V. U. N Perera

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Dealing with businesses with the foreign market always took a special place in a country’s economy. Political and social factors came into play making currency rate changes fluctuate rapidly. Currency rate prediction has become an important factor for larger international businesses since large amounts of money exchanged between countries. This research focuses on comparing the accuracy of mainly three models; Autoregressive Integrated Moving Average (ARIMA), Artificial Neural Networks(ANN) and Support Vector Machines(SVM). series of data import, export, USD currency exchange rate respect to LKR has been selected for training using above mentioned algorithms. After training the data set and comparing each algorithm, it was able to see that prediction in SVM performed better than other models. It was improved more by combining SVM and SVR models together.

Keywords: ARIMA, ANN, FFNN, RMSE, SVM, SVR

Procedia PDF Downloads 213

Authors: G. Nitesh

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The shear strength of soils is a crucial parameter instability analysis. Therefore, it is important to determine reliable values for the accuracy of stability analysis. Direct shear tests are mostly performed to determine the shear strength of cohesionless soils. The major limitation of the direct shear test is that the failure takes place through the pre-defined failure plane but the failure is not along pre-defined plane and is along the weakest plane in actual shearing mechanism that goes on in the field. This leads to overestimating the strength parameter; hence, a new apparatus called simple shear is developed and used in this study to determine the shear strength parameter that simulates the field conditions.

Keywords: direct shear, simple shear, angle of shear resistance, cohesionless soils

Procedia PDF Downloads 411

Authors: Nawaporn Thongnut

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The objective was to study the process and how to prepare the accounting of the Thai temples and to study the performance and quality in the accounting preparation of the temples in accordance with the regulation. The population was the accountants and individuals involved in the accounting preparation of 17 temples in the suburban Bangkok. The measurement used in this study was questionnaire. The statistics used in the analysis are the descriptive statistic. The data was presented in the form of percentage tables to describe the data on the demographic characteristics. The study found that temple wardens were responsible for the accounting and reporting of the temples. Abbots were to check the accuracy of the accounts in the monasteries. Mostly, there was no account auditing of the monasteries from the outside. The practice when receiving income for most of the monasteries had been keeping financial document in an orderly manner.

Keywords: corporate social responsibility, creating shared value, management accountant’s roles, stock exchange of Thailand

Procedia PDF Downloads 232

Authors: Senol Dogan, Gunay Karli

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Identification of relevant publications based on a Medline query is time-consuming and error-prone. An all based process has the potential to solve this problem without any manual work. To the best of our knowledge, our study is the first to investigate the ability of machine learning to identify relevant articles accurately. 5 different machine learning algorithms were tested using 23 predictors based on several metadata fields attached to publications. We find that the Boosted model is the best-performing algorithm and its overall accuracy is 96%. In addition, specificity and sensitivity of the algorithm is 97 and 93%, respectively. As a result of the work, we understood that we can apply the same procedure to understand cancer gene expression big data.

Keywords: prediction of publications, machine learning, algorithms, bariatric surgery, comparison of algorithms, boosted, tree, logistic regression, ANN model

Procedia PDF Downloads 210

Authors: Félix David Suárez Bonilla

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A sentiment analysis service to detect polarity (positive, neural, and negative), based on transfer learning, was built using a Spanish version of BERT and applied to tweets written in Spanish. The dataset that was used consisted of 11975 reviews, which were extracted from Google Play using the google-play-scrapper package. The BETO trained model used: the AdamW optimizer, a batch size of 16, a learning rate of 2x10⁻⁵ and 10 epochs. The system was tested using tweets of three presidential pre-candidates from Costa Rica. The system was finally validated using human labeled examples, achieving an accuracy of 83.3%.

Keywords: NLP, transfer learning, BERT, sentiment analysis, social media, opinion mining

Procedia PDF Downloads 174

Authors: Mkhinini Maher, Knani Jilani

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We present in this work the performances of a mobile omnidirectional robot through evaluating its management of the redundancy of actuation. Thus we come to the predictive control implemented. The distribution of the wringer on the robot actions, through the inverse pseudo of Moore-Penrose, corresponds to a -geometric- distribution of efforts. We will show that the load on vehicle wheels would not be equi-distributed in terms of wheels configuration and of robot movement. Thus, the threshold of sliding is not the same for the three wheels of the vehicle. We suggest exploiting the redundancy of actuation to reduce the risk of wheels sliding and to ameliorate, thereby, its accuracy of displacement. This kind of approach was the subject of study for the legged robots.

Keywords: mobile robot, actuation, redundancy, omnidirectional, inverse pseudo moore-penrose, reductive control

Procedia PDF Downloads 513

Authors: Edna T. Bernabe, Joshua Bilolo, Sheila Mae Artillero, Catlicia Joy Caseda, Liezel Once, Donne Ynah Grace Quirante

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Internal communication is significant for an organization to function to its full extent. A strategic communication plan builds an organization’s structure and makes it more systematic. Information is a vital part of communication inside the organization as this lays every possible outcome—be it positive or negative. It is, therefore, imperative to assess the communication structure of a particular organization to secure a better and harmonious communication environment in any organization. Thus, this research was intended to identify the internal communication channels used in Polytechnic University of the Philippines-College of Communication (PUP-COC) as an organization, to identify the flow of information specifically in downward, upward, and horizontal communication, to assess the accuracy, consistency, and timeliness of its internal communication channels; and to come up with a proposed strategic communication plan of information dissemination to improve the existing communication flow in the college. The researchers formulated a framework from Input-Throughout-Output-Feedback-Goal of General System Theory and gathered data to assess the PUP-COC’s internal communication. The communication model links the objectives of the study to know the internal organization of the college. The qualitative approach and case study as the tradition of inquiry were used to gather deeper understanding of the internal organizational communication in PUP-COC, using Interview, as the primary methods for the study. This was supported with a quantitative data which were gathered through survey from the students of the college. The researchers interviewed 17 participants: the College dean, the 4 chairpersons of the college departments, the 11 faculty members and staff, and the acting Student Council president. An interview guide and a standardized questionnaire were formulated as instruments to generate the data. After a thorough analysis of the study, it was found out that two-way communication flow exists in PUP-COC. The type of communication channel the internal stakeholders use varies as to whom a particular person is communicating with. The members of the PUP-COC community also use different types of communication channels depending on the flow of communication being used. Moreover, the most common types of internal communication are the letters and memoranda for downward communication, while letters, text messages, and interpersonal communication are often used in upward communication. Various forms of social media have been found out to be of use in horizontal communication. Accuracy, consistency, and timeliness play a significant role in information dissemination within the college. However, some problems have also been found out in the communication system. The most common problem are the delay in the dissemination of memoranda and letters and the uneven distribution of information and instruction to faculty, staff, and students. This has led the researchers to formulate a strategic communication plan which aims to propose strategies that will solve the communication problems that are being experienced by the internal stakeholders.

Keywords: communication plan, downward communication, internal communication, upward communication

Procedia PDF Downloads 519

Authors: Li Ziming, He Cunfu, Liu Zenghua

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With aim for delamination type defects detection in manufacturing process of seamless pipe,this paper studies the interaction of the circumferential lamb wave with delamination in aluminum pipe.The delamination is located in the middle of pipe wall.A numerical study is carried out,the circumferential lamb wave used here is CL0 mode,which is generated with a finite element method code.Wave structures from the simulation are compared with theoretical results to verify the model’s accuracy.Delamination along the circumferential direction is established by demerging nodes of the same coordinates.When CL0 mode is incident at the entrance and exit of a delamination,it generates new mode-CL1,undergoes multiple reverberation and mode conversions between the two ends of the delamination. Signals of different receptions are obtained to provide insight in using CL0 mode for locating the delamination.

Keywords: circumferential lamb wave, delamination, FEM, seamless pipe

Procedia PDF Downloads 314

Authors: Mekha Mathew, Varun P Gopi

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Wireless Capsule Endoscopy (WCE) has become a great device in Gastrointestinal (GI) tract diagnosis, which can examine the entire GI tract, especially the small intestine without invasiveness and sedation. Bleeding in the digestive tract is a symptom of a disease rather than a disease itself. Hence the detection of bleeding is important in diagnosing many diseases. In this paper we proposes a novel method for distinguishing bleeding regions from normal regions based on Contourlet transform and Local Binary Pattern (LBP). Experiments show that this method provides a high accuracy rate of 96.38% in CIE XYZ colour space for k-Nearest Neighbour (k-NN) classifier.

Keywords: Wireless Capsule Endoscopy, local binary pattern, k-NN classifier, contourlet transform

Procedia PDF Downloads 487

Authors: Aya Mousa, Mahmoud Alsaheb

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Question Answering System (QAS) aims to provide the most suitable answer to the user's question in any natural language. In the recent future, it will be a future version of web search. Much research has already been done on answering Arabic factoid questions and achieved good accuracy. In contrast, the progress in research on Arabic non-factoid question answering is still immature. In this survey, we summarize, discuss, and compare the existing Arab non-factoid question-answering systems to identify the limitations and the achievements that were accomplished. Furthermore, we investigate the challenges in developing non-factoid Arabic QAS and the possible future improvements. The survey is written to help the researchers to understand the field of Arabic non-factoid QAS and to motivate them to utilize different approaches to develop and enhance the Non-factoid Arabic QAS

Keywords: Arabic question answering system, non-factoid question answering, Arabic NLP, question answering

Procedia PDF Downloads 102

Authors: Sushil Kumar, M. Dakshina Murty

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Thermal network modelling has proven to be important tool for thermal analysis of electrical machine. This article investigates numerical thermal network model and experimental performance of a large-scale AC motor. Experimental temperatures were measured using RTD in the stator which have been compared with the numerical data. Thermal network modelling fairly predicts the temperature of various components inside the large-scale AC motor. Results of stator winding temperature is compared with experimental results which are in close agreement with accuracy of 6-10%. This method of predicting hot spots within AC motors can be readily used by the motor designers for estimating the thermal hot spots of the machine.

Keywords: AC motor, thermal network, heat transfer, modelling

Procedia PDF Downloads 327

Authors: R. Srinivas, K. V. Ramana

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This paper presents a novel method called VESTAL to label vertebrae and inter vertebral discs. Each vertebra has certain statistical features properties. To label vertebrae and discs, a new equation to model the path of spinal cord is derived using statistical properties of the spinal canal. VESTAL uses this equation for labeling vertebrae and discs. For each vertebrae and inter vertebral discs both posterior, interior width, height are measured. The calculated values are compared with real values which are measured using venires calipers and the comparison produced 95% efficiency and accurate results. The VESTAL is applied on 50 patients 350 MR images and obtained 100% accuracy in labeling.

Keywords: spine, vertebrae, inter vertebral disc, labeling, statistics, texture, disc

Procedia PDF Downloads 363

Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

Procedia PDF Downloads 78

Authors: Hassan Manouzi, Taous-Meriem Laleg-Kirati

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In this paper we study mathematically the eigenvalue problem for stochastic elliptic partial differential equation of Wick type. Using the Wick-product and the Wiener-Ito chaos expansion, the stochastic eigenvalue problem is reformulated as a system of an eigenvalue problem for a deterministic partial differential equation and elliptic partial differential equations by using the Fredholm alternative. To reduce the computational complexity of this system, we shall use a decomposition-coordination method. Once this approximation is performed, the statistics of the numerical solution can be easily evaluated.

Keywords: eigenvalue problem, Wick product, SPDEs, finite element, Wiener-Ito chaos expansion

Procedia PDF Downloads 359

Authors: Flora Babongo, Valerie Chavez

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Inferring causality from observational data is one of the fundamental subjects, especially in quantitative finance. So far most of the papers analyze additive noise models with either linearity, nonlinearity or Gaussian noise. We fill in the gap by providing a nonlinear and non-gaussian causal multiplicative noise model that aims to distinguish the cause from the effect using a two steps method based on Bayesian additive models for location, scale and shape (BAMLSS) and on causal additive models (CAM). We have tested our method on simulated and real data and we reached an accuracy of 0.86 on average. As real data, we considered the causality between financial indices such as S&P 500, Nasdaq, CAC 40 and Nikkei, and companies' log-returns. Our results can be useful in inferring causality when the data is heteroskedastic or non-injective.

Keywords: causal inference, DAGs, BAMLSS, financial index

Procedia PDF Downloads 152

Authors: Yang Zhong, Heng Liu

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The decoupling method and the modified Naiver method are combined for accurate bending analysis of rectangular thick plates with all edges clamped supported. The basic governing equations for Mindlin plates are first decoupled into independent partial differential equations which can be solved separately. Using modified Navier method, the analytic solution of rectangular thick plate with all edges clamped supported is then derived. The solution method used in this paper leave out the complicated derivation for calculating coefficients and obtain the solution to problems directly. Numerical comparisons show the correctness and accuracy of the results at last.

Keywords: Mindlin plates, decoupling method, modified Navier method, bending rectangular plates

Procedia PDF Downloads 602

Authors: Qiang Wang, Hongyang Yu, MingRong Lai, Miao Luo

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This paper presents a method for accurately localizing and interacting with known surface defects by overlaying patterns onto real-world surfaces using a projection system. Given the world coordinates of the defects, we project corresponding patterns onto the surfaces, providing an intuitive visualization of the specific defect locations. To enable users to interact with and retrieve more information about individual defects, we implement a gesture recognition system based on a pruned and optimized version of YOLOv6. This lightweight model achieves an accuracy of 82.8% and is suitable for deployment on low-performance devices. Our approach demonstrates the potential for enhancing defect identification, inspection processes, and user interaction in various applications.

Keywords: defect localization, projection mapping, gesture recognition, YOLOv6

Procedia PDF Downloads 89

Authors: Alaa Al Hawari, Mohammad Khader, Tarek Zayed, Osama Moselhi

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In this paper, an effective non-destructive, non-invasive approach for leak detection was proposed. The process relies on analyzing thermal images collected by an IR viewer device that captures thermo-grams. In this study a statistical analysis of the collected thermal images of the ground surface along the expected leak location followed by a visual inspection of the thermo-grams was performed in order to locate the leak. In order to verify the applicability of the proposed approach the predicted leak location from the developed approach was compared with the real leak location. The results showed that the expected leak location was successfully identified with an accuracy of more than 95%.

Keywords: thermography, leakage, water pipelines, thermograms

Procedia PDF Downloads 355

Authors: Maha Al-Soudani, Gilles Klysz, Jean-Paul Balayssac

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The aim of this paper is to use Ground Penetrating Radar (GPR) as a non-destructive testing (NDT) method to increase its accuracy in recognizing the geometric reinforced concrete structures and in particular, the position of steel bars. This definition will help the managers to assess the state of their structures on the one hand vis-a-vis security constraints and secondly to quantify the need for maintenance and repair. Several configurations of acquisition and processing of the simulated signal were tested to propose and develop an appropriate imaging algorithm in the propagation medium to locate accurately the rebar. A subsequent experimental validation was used by testing the imaging algorithm on real reinforced concrete structures. The results indicate that, this algorithm is capable of estimating the reinforcing steel bar position to within (0-1) mm.

Keywords: GPR, NDT, Reinforced concrete structures, Rebar location.

Procedia PDF Downloads 504

Authors: Alireza Abbasi Moshaii, Shaghayegh Nasiri, Mehdi Tale Masouleh

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The main purpose of this study is static analysis of two three-degree of freedom parallel mechanisms: 3-RCC and 3-RRS. Geometry of these mechanisms is expressed and static equilibrium equations are derived for the whole chains. For these mechanisms due to the equal number of equations and unknowns, the solution is as same as 3-RCC mechanism. Mathematical software is used to solve the equations. In order to prove the results obtained from solving the equations of mechanisms, their CAD model has been simulated and their static is analysed in ADAMS software. Due to symmetrical geometry of the mechanisms, the force and external torque acting on the end-effecter have been considered asymmetric to prove the generality of the solution method. Finally, the results of both softwares, for both mechanisms are extracted and compared as graphs. The good achieved comparison between the results indicates the accuracy of the analysis.

Keywords: robotic, static analysis, 3-RCC, 3-RRS

Procedia PDF Downloads 385

Authors: K. Abuzayan, H. Alabed, J. Ezarrugh, M. Agila

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Static and dynamic balance are essential in daily and sports life. Many factors have been identified as influencing static balance control. Therefore, the aim of this study was to apply the (XCoM) method and other relevant variables (CoP, CoM, Fh, KE, P, Q, and, AI) to investigate sport related activities such as hopping and jumping. Many studies have represented the CoP data without mentioning its accuracy, so several experiments were done to establish the agreement between the CoP and the projected CoM in a static condition. Five male healthy (Mean ± SD:- age 24.6 years ±4.5, height 177 cm ± 6.3, body mass 72.8 kg ± 6.6) participated in this study. Results found that The implementation of the XCoM method was found to be practical for evaluating both static and dynamic balance. The general findings were that the CoP, the CoM, the XCoM, Fh, and Q were more informative than the other variables (e.g. KE, P, and AI) during static and dynamic balance. The XCoM method was found to be applicable to dynamic balance as well as static balance.

Keywords: centre of mass, static balance, dynamic balance, extrapolated centre of mass

Procedia PDF Downloads 420

Authors: Ebrahim Alrashed

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Wireless sensor networks are vulnerable to attacks from adversaries attempting to disrupt their operations. Sink-hole attacks are a type of attack where an adversary node drops data forwarded through it and hence affecting the reliability and accuracy of the network. Since sensor nodes have limited battery power, it is essential that any solution to the sinkhole attack problem be very energy-aware. In this paper, we present a reliable and energy efficient scheme to forward data from source nodes to the base station while under sink-hole attack. The scheme also detects sink-hole attack nodes and avoid paths that includes them.

Keywords: energy-aware routing, reliability, sink-hole attack, WSN

Procedia PDF Downloads 397

Authors: Angela U. Makolo

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Protein-coding and Non-coding regions determine the biology of a sequenced transcriptome. Research advances have shown that Non-coding regions are important in disease progression and clinical diagnosis. Existing bioinformatics tools have been targeted towards Protein-coding regions alone. Therefore, there are challenges associated with gaining biological insights from transcriptome sequence data. These tools are also limited to computationally intensive sequence alignment, which is inadequate and less accurate to identify both Protein-coding and Non-coding regions. Alignment-free techniques can overcome the limitation of identifying both regions. Therefore, this study was designed to develop an efficient sequence alignment-free model for identifying both Protein-coding and Non-coding regions in sequenced transcriptomes. Feature grouping and randomization procedures were applied to the input transcriptomes (37,503 data points). Successive iterations were carried out to compute the gradient vector that converged the developed Protein-coding and Non-coding Region Identifier (PNRI) model to the approximate coefficient vector. The logistic regression algorithm was used with a sigmoid activation function. A parameter vector was estimated for every sample in 37,503 data points in a bid to reduce the generalization error and cost. Maximum Likelihood Estimation (MLE) was used for parameter estimation by taking the log-likelihood of six features and combining them into a summation function. Dynamic thresholding was used to classify the Protein-coding and Non-coding regions, and the Receiver Operating Characteristic (ROC) curve was determined. The generalization performance of PNRI was determined in terms of F1 score, accuracy, sensitivity, and specificity. The average generalization performance of PNRI was determined using a benchmark of multi-species organisms. The generalization error for identifying Protein-coding and Non-coding regions decreased from 0.514 to 0.508 and to 0.378, respectively, after three iterations. The cost (difference between the predicted and the actual outcome) also decreased from 1.446 to 0.842 and to 0.718, respectively, for the first, second and third iterations. The iterations terminated at the 390th epoch, having an error of 0.036 and a cost of 0.316. The computed elements of the parameter vector that maximized the objective function were 0.043, 0.519, 0.715, 0.878, 1.157, and 2.575. The PNRI gave an ROC of 0.97, indicating an improved predictive ability. The PNRI identified both Protein-coding and Non-coding regions with an F1 score of 0.970, accuracy (0.969), sensitivity (0.966), and specificity of 0.973. Using 13 non-human multi-species model organisms, the average generalization performance of the traditional method was 74.4%, while that of the developed model was 85.2%, thereby making the developed model better in the identification of Protein-coding and Non-coding regions in transcriptomes. The developed Protein-coding and Non-coding region identifier model efficiently identified the Protein-coding and Non-coding transcriptomic regions. It could be used in genome annotation and in the analysis of transcriptomes.

Keywords: sequence alignment-free model, dynamic thresholding classification, input randomization, genome annotation

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Authors: Ilgin Gökaşar, Saman Ghaffarian

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The need for fast processed big data of transportation ridership (eg., smartcard data) and traffic operation (e.g., traffic detectors data) which requires a lot of computational power is incontrovertible in Intelligent Transportation Systems. Nowadays cloud computing is one of the important subjects and popular information technology solution for data processing. It enables users to process enormous measure of data without having their own particular computing power. Thus, it can also be a good selection for transportation big data processing as well. This paper intends to examine how the cloud computing can enhance transportation big data process with contrasting its advantages and disadvantages, and discussing cloud computing features.

Keywords: big data, cloud computing, Intelligent Transportation Systems, ITS, traffic data processing

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Authors: Andrew Lock, Alastair Allen

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Fragile watermarking has been proposed as a means of adding additional security or functionality to biometric systems, particularly for authentication and tamper detection. In this paper we describe an experimental study on the effect of watermarking iris images with a particular class of fragile algorithm, reversible algorithms, and the ability to correctly perform iris recognition. We investigate two scenarios, matching watermarked images to unmodified images, and matching watermarked images to watermarked images. We show that different watermarking schemes give very different results for a given capacity, highlighting the importance of investigation. At high embedding rates most algorithms cause significant reduction in recognition performance. However, in many cases, for low embedding rates, recognition accuracy is improved by the watermarking process.

Keywords: biometrics, iris recognition, reversible watermarking, vision engineering

Procedia PDF Downloads 459

Authors: An-Shik Yang, Chin-Ting Kuo, Yung-Chun Yang, Wen-Hsin Hsieh, Chiang-Ho Cheng

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Optical biosensors have become a powerful detection and analysis tool for wide-ranging applications in biomedical research, pharmaceuticals and environmental monitoring. This study carried out the computational fluid dynamics (CFD)-based simulations to explore the dispersion phenomenon in the microchannel of a optical biosensor. The predicted time sequences of concentration contours were utilized to better understand the dispersion development occurred in different geometric shapes of microchannels. The simulation results showed the surface concentrations at the sensing probe (with the best performance of a grating coupler) in respect of time to appraise the dispersion effect and therefore identify the design configurations resulting in minimum dispersion.

Keywords: CFD simulations, dispersion, microfluidic, optical waveguide sensors

Procedia PDF Downloads 545

Authors: Supunmali Ahangama, Danny Chiang Choon Poo

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Health analytics (HA) is used in healthcare systems for effective decision-making, management, and planning of healthcare and related activities. However, user resistance, the unique position of medical data content, and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. The success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose an HA process model with features from the rational unified process (RUP) model and agile methodology.

Keywords: agile methodology, health analytics, unified process model, UML

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Authors: A. M. Byrne, E. Bonfiglio, C. Rigby, N. Edelstyn

Abstract:

Introduction: Neuromarketing employs numerous methodologies when investigating products and advertisement effectiveness. Electroencephalography (EEG), a non-invasive measure of electrical activity from the brain, is commonly used in neuromarketing. EEG data can be considered using time-frequency (TF) analysis, where changes in the frequency of brainwaves are calculated to infer participant’s mental states, or event-related potential (ERP) analysis, where changes in amplitude are observed in direct response to a stimulus. This presentation discusses the findings of a systematic review of EEG measures in neuromarketing. A systematic review summarises evidence on a research question, using explicit measures to identify, select, and critically appraise relevant research papers. Thissystematic review identifies which EEG measures are the most robust predictor of customer preference and purchase intention. Methods: Search terms identified174 papers that used EEG in combination with marketing-related stimuli. Publications were excluded if they were written in a language other than English or were not published as journal articles (e.g., book chapters). The review investigated which TF effect (e.g., theta-band power) and ERP component (e.g., N400) most consistently reflected preference and purchase intention. Machine-learning prediction was also investigated, along with the use of EEG combined with physiological measures such as eye-tracking. Results: Frontal alpha asymmetry was the most reliable TF signal, where an increase in activity over the left side of the frontal lobe indexed a positive response to marketing stimuli, while an increase in activity over the right side indexed a negative response. The late positive potential, a positive amplitude increase around 600 ms after stimulus presentation, was the most reliable ERP component, reflecting the conscious emotional evaluation of marketing stimuli. However, each measure showed mixed results when related to preference and purchase behaviour. Predictive accuracy was greatly improved through machine-learning algorithms such as deep neural networks, especially when combined with eye-tracking or facial expression analyses. Discussion: This systematic review provides a novel catalogue of the most effective use of each EEG measure commonly used in neuromarketing. Exciting findings to emerge are the identification of the frontal alpha asymmetry and late positive potential as markers of preferential responses to marketing stimuli. Predictive accuracy using machine-learning algorithms achieved predictive accuracies as high as 97%, and future research should therefore focus on machine-learning prediction when using EEG measures in neuromarketing.

Keywords: EEG, ERP, neuromarketing, machine-learning, systematic review, time-frequency

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