Search results for: classification algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5311

Search results for: classification algorithm

2281 To Determine the Effects of Regulatory Food Safety Inspections on the Grades of Different Categories of Retail Food Establishments across the Dubai Region

Authors: Shugufta Mohammad Zubair

Abstract:

This study explores the Effect of the new food System Inspection system also called the new inspection color card scheme on reduction of critical & major food safety violations in Dubai. Data was collected from all retail food service establishments located in two zones in the city. Each establishment was visited twice, once before the launch of the new system and one after the launch of the system. In each visit, the Inspection checklist was used as the evaluation tool for observation of the critical and major violations. The old format of the inspection checklist was concerned with scores based on the violations; but the new format of the checklist for the new inspection color card scheme is divided into administrative, general major and critical which gives a better classification for the inspectors to identify the critical and major violations of concerned. The study found that there has been a better and clear marking of violations after the launch of new inspection system wherein the inspectors are able to mark and categories the violations effectively. There had been a 10% decrease in the number of food establishment that was previously given A grade. The B & C grading were also considerably dropped by 5%.

Keywords: food inspection, risk assessment, color card scheme, violations

Procedia PDF Downloads 318
2280 Global Differences in Job Satisfaction of Healthcare Professionals

Authors: Jonathan H. Westover, Ruthann Cunningham, Jaron Harvey

Abstract:

Purpose: Job satisfaction is one of the most critical attitudes among employees. Understanding whether employees are satisfied with their jobs and what is driving that satisfaction is important for any employer, but particularly for healthcare organizations. This study looks at the question of job satisfaction and drivers of job satisfaction among healthcare professionals at a global scale, looking for trends that generalize across 37 countries. Study: This study analyzed job satisfaction responses to the 2015 Work Orientations IV wave of the International Social Survey Programme (ISSP) to understand differences in antecedents for and levels of job satisfaction among healthcare professionals. A total of 18,716 respondents from 37 countries participated in the annual survey. Findings: Respondents self-identified their occupational category based on corresponding International Standard Classification of Occupations (ISCO-08) codes. Results suggest that mean overall job satisfaction was highest among health service managers and generalist medical practitioners and lowest among environmental hygiene professionals and nursing professionals. Originality: Many studies have addressed the issue of job satisfaction in healthcare, examining small samples of specific healthcare workers. In this study, using a large international dataset, we are able to examine questions of job satisfaction across large groups of healthcare workers in different occupations within the healthcare field.

Keywords: job satisfaction, healthcare industry, global comparisons, workplace

Procedia PDF Downloads 139
2279 Review and Classification of the Indicators and Trends Used in Bridge Performance Modeling

Authors: S. Rezaei, Z. Mirzaei, M. Khalighi, J. Bahrami

Abstract:

Bridges, as an essential part of road infrastructures, are affected by various deterioration mechanisms over time due to the changes in their performance. As changes in performance can have many negative impacts on society, it is essential to be able to evaluate and measure the performance of bridges throughout their life. This evaluation includes the development or the choice of the appropriate performance indicators, which, in turn, are measured based on the selection of appropriate models for the existing deterioration mechanism. The purpose of this article is a statistical study of indicators and deterioration mechanisms of bridges in order to discover further research capacities in bridges performance assessment. For this purpose, some of the most common indicators of bridge performance, including reliability, risk, vulnerability, robustness, and resilience, were selected. The researches performed on each index based on the desired deterioration mechanisms and hazards were comprehensively reviewed. In addition, the formulation of the indicators and their relationship with each other were studied. The research conducted on the mentioned indicators were classified from the point of view of deterministic or probabilistic method, the level of study (element level, object level, etc.), and the type of hazard and the deterioration mechanism of interest. For each of the indicators, a number of challenges and recommendations were presented according to the review of previous studies.

Keywords: bridge, deterioration mechanism, lifecycle, performance indicator

Procedia PDF Downloads 101
2278 An Approximation Algorithm for the Non Orthogonal Cutting Problem

Authors: R. Ouafi, F. Ouafi

Abstract:

We study the problem of cutting a rectangular material entity into smaller sub-entities of trapezoidal forms with minimum waste of the material. This problem will be denoted TCP (Trapezoidal Cutting Problem). The TCP has many applications in manufacturing processes of various industries: pipe line design (petro chemistry), the design of airfoil (aeronautical) or cuts of the components of textile products. We introduce an orthogonal build to provide the optimal horizontal and vertical homogeneous strips. In this paper we develop a general heuristic search based upon orthogonal build. By solving two one-dimensional knapsack problems, we combine the horizontal and vertical homogeneous strips to give a non orthogonal cutting pattern.

Keywords: combinatorial optimization, cutting problem, heuristic

Procedia PDF Downloads 536
2277 Multichannel Object Detection with Event Camera

Authors: Rafael Iliasov, Alessandro Golkar

Abstract:

Object detection based on event vision has been a dynamically growing field in computer vision for the last 16 years. In this work, we create multiple channels from a single event camera and propose an event fusion method (EFM) to enhance object detection in event-based vision systems. Each channel uses a different accumulation buffer to collect events from the event camera. We implement YOLOv7 for object detection, followed by a fusion algorithm. Our multichannel approach outperforms single-channel-based object detection by 0.7% in mean Average Precision (mAP) for detection overlapping ground truth with IOU = 0.5.

Keywords: event camera, object detection with multimodal inputs, multichannel fusion, computer vision

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2276 Deep Learning based Image Classifiers for Detection of CSSVD in Cacao Plants

Authors: Atuhurra Jesse, N'guessan Yves-Roland Douha, Pabitra Lenka

Abstract:

The detection of diseases within plants has attracted a lot of attention from computer vision enthusiasts. Despite the progress made to detect diseases in many plants, there remains a research gap to train image classifiers to detect the cacao swollen shoot virus disease or CSSVD for short, pertinent to cacao plants. This gap has mainly been due to the unavailability of high quality labeled training data. Moreover, institutions have been hesitant to share their data related to CSSVD. To fill these gaps, image classifiers to detect CSSVD-infected cacao plants are presented in this study. The classifiers are based on VGG16, ResNet50 and Vision Transformer (ViT). The image classifiers are evaluated on a recently released and publicly accessible KaraAgroAI Cocoa dataset. The best performing image classifier, based on ResNet50, achieves 95.39\% precision, 93.75\% recall, 94.34\% F1-score and 94\% accuracy on only 20 epochs. There is a +9.75\% improvement in recall when compared to previous works. These results indicate that the image classifiers learn to identify cacao plants infected with CSSVD.

Keywords: CSSVD, image classification, ResNet50, vision transformer, KaraAgroAI cocoa dataset

Procedia PDF Downloads 94
2275 Glushkov's Construction for Functional Subsequential Transducers

Authors: Aleksander Mendoza

Abstract:

Glushkov's construction has many interesting properties, and they become even more evident when applied to transducers. This article strives to show the vast range of possible extensions and optimisations for this algorithm. Special flavour of regular expressions is introduced, which can be efficiently converted to e-free functional subsequential weighted finite state transducers. Produced automata are very compact, as they contain only one state for each symbol (from input alphabet) of original expression and only one transition for each range of symbols, no matter how large. Such compactified ranges of transitions allow for efficient binary search lookup during automaton evaluation. All the methods and algorithms presented here were used to implement open-source compiler of regular expressions for multitape transducers.

Keywords: weighted automata, transducers, Glushkov, follow automata, regular expressions

Procedia PDF Downloads 153
2274 Developement of a New Wearable Device for Automatic Guidance Service

Authors: Dawei Cai

Abstract:

In this paper, we present a new wearable device that provide an automatic guidance servie for visitors. By combining the position information from NFC and the orientation information from a 6 axis acceleration and terrestrial magnetism sensor, the head's direction can be calculated. We developed an algorithm to calculate the device orientation based on the data from acceleration and terrestrial magnetism sensor. If visitors want to know some explanation about an exhibit in front of him, what he has to do is just lift up his mobile device. The identification program will automatically identify the status based on the information from NFC and MEMS, and start playing explanation content for him. This service may be convenient for old people or disables or children.

Keywords: wearable device, ubiquitous computing, guide sysem, MEMS sensor, NFC

Procedia PDF Downloads 417
2273 Global Optimization Techniques for Optimal Placement of HF Antennas on a Shipboard

Authors: Mustafa Ural, Can Bayseferogulari

Abstract:

In this work, radio frequency (RF) coupling between two HF antennas on a shipboard platform is minimized by determining an optimal antenna placement. Unlike the other works, the coupling is minimized not only at single frequency but over the whole frequency band of operation. Similarly, GAO and PSO, are used in order to determine optimal antenna placement. Throughout this work, outputs of two optimization techniques are compared with each other in terms of antenna placements and coupling results. At the end of the work, far-field radiation pattern performances of the antennas at their optimal places are analyzed in terms of directivity and coverage in order to see that.

Keywords: electromagnetic compatibility, antenna placement, optimization, genetic algorithm optimization, particle swarm optimization

Procedia PDF Downloads 225
2272 Decision Tree Analysis of Risk Factors for Intravenous Infiltration among Hospitalized Children: A Retrospective Study

Authors: Soon-Mi Park, Ihn Sook Jeong

Abstract:

This retrospective study was aimed to identify risk factors of intravenous (IV) infiltration for hospitalized children. The participants were 1,174 children for test and 424 children for validation, who admitted to a general hospital, received peripheral intravenous injection therapy at least once and had complete records. Data were analyzed with frequency and percentage or mean and standard deviation were calculated, and decision tree analysis was used to screen for the most important risk factors for IV infiltration for hospitalized children. The decision tree analysis showed that the most important traditional risk factors for IV infiltration were the use of ampicillin/sulbactam, IV insertion site (lower extremities), and medical department (internal medicine) both in the test sample and validation sample. The correct classification was 92.2% in the test sample and 90.1% in the validation sample. More careful attention should be made to patients who are administered ampicillin/sulbactam, have IV site in lower extremities and have internal medical problems to prevent or detect infiltration occurrence.

Keywords: decision tree analysis, intravenous infiltration, child, validation

Procedia PDF Downloads 166
2271 Mineralogy and Classification of Altered Host Rocks in the Zaghia Iron Oxide Deposit, East of Bafq, Central Iran

Authors: Azat Eslamizadeh, Neda Akbarian

Abstract:

The Zaghia Iron ore, in 15 km east of a town named Bafq, is located in Precambrian formation of Central Iran in form of a small local deposit. The Volcano-sedimentary rocks of Precambrian-Cambrian age, belonging to Rizu series have spread through the region. Substantial portion of the deposit is covered by alluvial deposits. The rocks hosting the Zaghia iron ore have a main combination of rhyolitic tuffs along with clastic sediments, carbonate include sandstone, limestone, dolomite, conglomerate and is somewhat metamorphed causing them to have appeared as slate and phyllite. Moreover, carbonate rocks are in existence as skarn compound of marble bearing tremolite with mineralization of magnetite-hematite. The basic igneous rocks have dramatically altered into green rocks consist of actinolite-tremolite and chlorite along with amount of iron (magnetite + Martite). The youngest units of ore-bearing rocks in the area are found as dolerite - diabase dikes. The dikes are cutting the rhyolitic tuffs and carbonate rocks.

Keywords: Zaghia, iron ore deposite, mineralogy, petrography Bafq, Iran

Procedia PDF Downloads 518
2270 An Online Adaptive Thresholding Method to Classify Google Trends Data Anomalies for Investor Sentiment Analysis

Authors: Duygu Dere, Mert Ergeneci, Kaan Gokcesu

Abstract:

Google Trends data has gained increasing popularity in the applications of behavioral finance, decision science and risk management. Because of Google’s wide range of use, the Trends statistics provide significant information about the investor sentiment and intention, which can be used as decisive factors for corporate and risk management fields. However, an anomaly, a significant increase or decrease, in a certain query cannot be detected by the state of the art applications of computation due to the random baseline noise of the Trends data, which is modelled as an Additive white Gaussian noise (AWGN). Since through time, the baseline noise power shows a gradual change an adaptive thresholding method is required to track and learn the baseline noise for a correct classification. To this end, we introduce an online method to classify meaningful deviations in Google Trends data. Through extensive experiments, we demonstrate that our method can successfully classify various anomalies for plenty of different data.

Keywords: adaptive data processing, behavioral finance , convex optimization, online learning, soft minimum thresholding

Procedia PDF Downloads 160
2269 Recovery of Dredged Sediments With Lime or Cement as Platform Materials for Use in a Roadway

Authors: Abriak Yassine, Zri Abdeljalil, Benzerzour Mahfoud., Hadj Sadok Rachid, Abriak Nor-Edine

Abstract:

In this study, firstly, the study of the capacity reuse of dredged sediments and treated sediments with lime or cement were used in an establishment layer and the base layer of the roadway. Also, the analysis of mineral changes caused by the addition of lime or cement on the way as described in the mechanical results of stabilised sediments. After determining the quantity of lime and cement required to stabilise the sediment, the compaction characteristics were studied using the modified Proctor method. Then the evolution of the three parameters, that is, ideal water content and maximum dry density had been determined. Mechanical exhibitions can be assessed across the resistance to compression, flexibility modulus and the resistance under traction. The resistance of the formulation treated with cement addition (ROLAC®645) increase with the quantity of ROLAC®645. Traction resistances and the elastic modulus were utilized to assess the potential of the formulation as road construction materials utilizing classification diagram. The results show the various formulations with ROLAC® 645may be employed in subgrades and foundation layers for roads.

Keywords: cement, dredged, sediment, foundation layer, resistance

Procedia PDF Downloads 93
2268 Decomposition of Funds Transfer Pricing Components in Islamic Bank: The Exposure Effect of Shariah Non-Compliant Event Rectification Process

Authors: Azrul Azlan Iskandar Mirza

Abstract:

The purpose of Funds Transfer Pricing (FTP) for Islamic Bank is to promote prudent liquidity risk-taking behavior of business units. The acquirer of stable deposits will be rewarded whilst a business unit that generates long-term assets will be charged for added liquidity funding risks. In the end, it promotes risk-adjusted pricing by incorporating profit rate risk and liquidity risk component in the product pricing. However, in the event of Shariah non-compliant (SNCE), FTP components will be examined in the rectification plan especially when Islamic banks need to purify the non-compliance income. The finding shows that the determination between actual and provision cost will defer the decision among Shariah committee in Islamic banks. This paper will review each of FTP components to ensure the classification of actual and provision costs reflect the decision on rectification process on SNCE. This will benefit future decision and its consistency of Islamic banks.

Keywords: fund transfer pricing, Islamic banking, Islamic finance, shariah non-compliant event

Procedia PDF Downloads 187
2267 Efficient Alias-Free Level Crossing Sampling

Authors: Negar Riazifar, Nigel G. Stocks

Abstract:

This paper proposes strategies in level crossing (LC) sampling and reconstruction that provide alias-free high-fidelity signal reconstruction for speech signals without exponentially increasing sample number with increasing bit-depth. We introduce methods in LC sampling that reduce the sampling rate close to the Nyquist frequency even for large bit-depth. The results indicate that larger variation in the sampling intervals leads to an alias-free sampling scheme; this is achieved by either reducing the bit-depth or adding jitter to the system for high bit-depths. In conjunction with windowing, the signal is reconstructed from the LC samples using an efficient Toeplitz reconstruction algorithm.

Keywords: alias-free, level crossing sampling, spectrum, trigonometric polynomial

Procedia PDF Downloads 206
2266 A Video Surveillance System Using an Ensemble of Simple Neural Network Classifiers

Authors: Rodrigo S. Moreira, Nelson F. F. Ebecken

Abstract:

This paper proposes a maritime vessel tracker composed of an ensemble of WiSARD weightless neural network classifiers. A failure detector analyzes vessel movement with a Kalman filter and corrects the tracking, if necessary, using FFT matching. The use of the WiSARD neural network to track objects is uncommon. The additional contributions of the present study include a performance comparison with four state-of-art trackers, an experimental study of the features that improve maritime vessel tracking, the first use of an ensemble of classifiers to track maritime vessels and a new quantization algorithm that compares the values of pixel pairs.

Keywords: ram memory, WiSARD weightless neural network, object tracking, quantization

Procedia PDF Downloads 304
2265 Reactive Power Cost Evaluation with FACTS Devices in Restructured Power System

Authors: A. S. Walkey, N. P. Patidar

Abstract:

It is not always economical to provide reactive power using synchronous alternators. The cost of reactive power can be minimized by optimal placing of FACTS devices in power systems. In this paper a Particle Swarm Optimization- Sequential Quadratic Programming (PSO-SQP) algorithm is applied to minimize the cost of reactive power generation along with real power generation to alleviate the bus voltage violations. The effectiveness of proposed approach tested on IEEE-14 bus systems. In this paper in addition to synchronous generators, an opportunity of FACTS devices are also proposed to procure the reactive power demands in the power system.

Keywords: reactive power, reactive power cost, voltage security margins, capability curve, FACTS devices

Procedia PDF Downloads 496
2264 Cross-Layer Design of Event-Triggered Adaptive OFDMA Resource Allocation Protocols with Application to Vehicle Clusters

Authors: Shaban Guma, Naim Bajcinca

Abstract:

We propose an event-triggered algorithm for the solution of a distributed optimization problem by means of the projected subgradient method. Thereby, we invoke an OFDMA resource allocation scheme by applying an event-triggered sensitivity analysis at the access point. The optimal resource assignment of the subcarriers to the involved wireless nodes is carried out by considering the sensitivity analysis of the overall objective function as defined by the control of vehicle clusters with respect to the information exchange between the nodes.

Keywords: consensus, cross-layer, distributed, event-triggered, multi-vehicle, protocol, resource, OFDMA, wireless

Procedia PDF Downloads 325
2263 Second-Order Complex Systems: Case Studies of Autonomy and Free Will

Authors: Eric Sanchis

Abstract:

Although there does not exist a definitive consensus on a precise definition of a complex system, it is generally considered that a system is complex by nature. The presented work illustrates a different point of view: a system becomes complex only with regard to the question posed to it, i.e., with regard to the problem which has to be solved. A complex system is a couple (question, object). Because the number of questions posed to a given object can be potentially substantial, complexity does not present a uniform face. Two types of complex systems are clearly identified: first-order complex systems and second-order complex systems. First-order complex systems physically exist. They are well-known because they have been studied by the scientific community for a long time. In second-order complex systems, complexity results from the system composition and its articulation that are partially unknown. For some of these systems, there is no evidence of their existence. Vagueness is the keyword characterizing this kind of systems. Autonomy and free will, two mental productions of the human cognitive system, can be identified as second-order complex systems. A classification based on the properties structure makes it possible to discriminate complex properties from the others and to model this kind of second order complex systems. The final outcome is an implementable synthetic property that distinguishes the solid aspects of the actual property from those that are uncertain.

Keywords: autonomy, free will, synthetic property, vaporous complex systems

Procedia PDF Downloads 195
2262 Optimal Pressure Control and Burst Detection for Sustainable Water Management

Authors: G. K. Viswanadh, B. Rajasekhar, G. Venkata Ramana

Abstract:

Water distribution networks play a vital role in ensuring a reliable supply of clean water to urban areas. However, they face several challenges, including pressure control, pump speed optimization, and burst event detection. This paper combines insights from two studies to address these critical issues in Water distribution networks, focusing on the specific context of Kapra Municipality, India. The first part of this research concentrates on optimizing pressure control and pump speed in complex Water distribution networks. It utilizes the EPANET- MATLAB Toolkit to integrate EPANET functionalities into the MATLAB environment, offering a comprehensive approach to network analysis. By optimizing Pressure Reduce Valves (PRVs) and variable speed pumps (VSPs), this study achieves remarkable results. In the Benchmark Water Distribution System (WDS), the proposed PRV optimization algorithm reduces average leakage by 20.64%, surpassing the previous achievement of 16.07%. When applied to the South-Central and East zone WDS of Kapra Municipality, it identifies PRV locations that were previously missed by existing algorithms, resulting in average leakage reductions of 22.04% and 10.47%. These reductions translate to significant daily Water savings, enhancing Water supply reliability and reducing energy consumption. The second part of this research addresses the pressing issue of burst event detection and localization within the Water Distribution System. Burst events are a major contributor to Water losses and repair expenses. The study employs wireless sensor technology to monitor pressure and flow rate in real time, enabling the detection of pipeline abnormalities, particularly burst events. The methodology relies on transient analysis of pressure signals, utilizing Cumulative Sum and Wavelet analysis techniques to robustly identify burst occurrences. To enhance precision, burst event localization is achieved through meticulous analysis of time differentials in the arrival of negative pressure waveforms across distinct pressure sensing points, aided by nodal matrix analysis. To evaluate the effectiveness of this methodology, a PVC Water pipeline test bed is employed, demonstrating the algorithm's success in detecting pipeline burst events at flow rates of 2-3 l/s. Remarkably, the algorithm achieves a localization error of merely 3 meters, outperforming previously established algorithms. This research presents a significant advancement in efficient burst event detection and localization within Water pipelines, holding the potential to markedly curtail Water losses and the concomitant financial implications. In conclusion, this combined research addresses critical challenges in Water distribution networks, offering solutions for optimizing pressure control, pump speed, burst event detection, and localization. These findings contribute to the enhancement of Water Distribution System, resulting in improved Water supply reliability, reduced Water losses, and substantial cost savings. The integrated approach presented in this paper holds promise for municipalities and utilities seeking to improve the efficiency and sustainability of their Water distribution networks.

Keywords: pressure reduce valve, complex networks, variable speed pump, wavelet transform, burst detection, CUSUM (Cumulative Sum), water pipeline monitoring

Procedia PDF Downloads 79
2261 Facies, Diagenetic Analysis and Sequence Stratigraphy of Habib Rahi Formation Dwelling in the Vicinity of Jacobabad Khairpur High, Southern Indus Basin, Pakistan

Authors: Muhammad Haris, Syed Kamran Ali, Mubeen Islam, Tariq Mehmood, Faisal Shah

Abstract:

Jacobabad Khairpur High, part of a Sukkur rift zone, is the separating boundary between Central and Southern Indus Basin, formed as a result of Post-Jurassic uplift after the deposition of Middle Jurassic Chiltan Formation. Habib Rahi Formation of Middle to Late Eocene outcrops in the vicinity of Jacobabad Khairpur High, a section at Rohri near Sukkur is measured in detail for lithofacies, microfacies, diagenetic analysis and sequence stratigraphy. Habib Rahi Formation is richly fossiliferous and consists of mostly limestone with subordinate clays and marl. The total thickness of the formation in this section is 28.8m. The bottom of the formation is not exposed, while the upper contact with the Sirki Shale of the Middle Eocene age is unconformable in some places. A section is measured using Jacob’s Staff method, and traverses were made perpendicular to the strike. Four different lithofacies were identified based on outcrop geology which includes coarse-grained limestone facies (HR-1 to HR-5), massive bedded limestone facies (HR-6 HR-7), and micritic limestone facies (HR-8 to HR-13) and algal dolomitic limestone facie (HR-14). Total 14 rock samples were collected from outcrop for detailed petrographic studies, and thin sections of respective samples were prepared and analyzed under the microscope. On the basis of Dunham’s (1962) classification systems after studying textures, grain size, and fossil content and using Folk’s (1959) classification system after reviewing Allochems type, four microfacies were identified. These microfacies include HR-MF 1: Benthonic Foraminiferal Wackstone/Biomicrite Microfacies, HR-MF 2: Foramineral Nummulites Wackstone-Packstone/Biomicrite Microfacies HR-MF 3: Benthonic Foraminiferal Packstone/Biomicrite Microfacies, HR-MF 4: Bioclasts Carbonate Mudstone/Micrite Microfacies. The abundance of larger benthic Foraminifera’s (LBF), including Assilina sp., A. spiral abrade, A. granulosa, A. dandotica, A. laminosa, Nummulite sp., N. fabiani, N. stratus, N. globulus, Textularia, Bioclasts, and Red algae indicates shallow marine (Tidal Flat) environment of deposition. Based on variations in rock types, grain size, and marina fauna Habib Rahi Formation shows progradational stacking patterns, which indicates coarsening upward cycles. The second order of sea-level rise is identified (spanning from Y-Persian to Bartonian age) that represents the Transgressive System Tract (TST) and a third-order Regressive System Tract (RST) (spanning from Bartonian to Priabonian age). Diagenetic processes include fossils replacement by mud, dolomitization, pressure dissolution associated stylolites features and filling with dark organic matter. The presence of the microfossils includes Nummulite. striatus, N. fabiani, and Assilina. dandotica, signify Bartonian to Priabonian age of Habib Rahi Formation.

Keywords: Jacobabad Khairpur High, Habib Rahi Formation, lithofacies, microfacies, sequence stratigraphy, diagenetic history

Procedia PDF Downloads 457
2260 Evaluation of Random Forest and Support Vector Machine Classification Performance for the Prediction of Early Multiple Sclerosis from Resting State FMRI Connectivity Data

Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

Procedia PDF Downloads 233
2259 Enhancing the Recruitment Process through Machine Learning: An Automated CV Screening System

Authors: Kaoutar Ben Azzou, Hanaa Talei

Abstract:

Human resources is an important department in each organization as it manages the life cycle of employees from recruitment training to retirement or termination of contracts. The recruitment process starts with a job opening, followed by a selection of the best-fit candidates from all applicants. Matching the best profile for a job position requires a manual way of looking at many CVs, which requires hours of work that can sometimes lead to choosing not the best profile. The work presented in this paper aims at reducing the workload of HR personnel by automating the preliminary stages of the candidate screening process, thereby fostering a more streamlined recruitment workflow. This tool introduces an automated system designed to help with the recruitment process by scanning candidates' CVs, extracting pertinent features, and employing machine learning algorithms to decide the most fitting job profile for each candidate. Our work employs natural language processing (NLP) techniques to identify and extract key features from unstructured text extracted from a CV, such as education, work experience, and skills. Subsequently, the system utilizes these features to match candidates with job profiles, leveraging the power of classification algorithms.

Keywords: automated recruitment, candidate screening, machine learning, human resources management

Procedia PDF Downloads 48
2258 Adaptive Routing Protocol for Dynamic Wireless Sensor Networks

Authors: Fayez Mostafa Alhamoui, Adnan Hadi Mahdi Al- Helali

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The main issue in designing a wireless sensor network (WSN) is the finding of a proper routing protocol that complies with the several requirements of high reliability, short latency, scalability, low power consumption, and many others. This paper proposes a novel routing algorithm that complies with these design requirements. The new routing protocol divides the WSN into several sub-networks and each sub-network is divided into several clusters. This division is designed to reduce the number of radio transmission and hence decreases the power consumption. The network division may be changed dynamically to adapt with the network changes and allows the realization of the design requirements.

Keywords: wireless sensor networks, routing protocols, AD HOC topology, cluster, sub-network, WSN design requirements

Procedia PDF Downloads 531
2257 Performance Measurement of Logistics Systems for Thailand's Wholesales and Retails Industries by Data Envelopment Analysis

Authors: Pornpimol Chaiwuttisak

Abstract:

The study aims to compare the performance of the logistics for Thailand’s wholesale and retail trade industries (except motor vehicles, motorcycle, and stalls) by using data (data envelopment analysis). Thailand Standard Industrial Classification in 2009 (TSIC - 2009) categories that industries into sub-group no. 45: wholesale and retail trade (except for the repair of motor vehicles and motorcycles), sub-group no. 46: wholesale trade (except motor vehicles and motorcycles), and sub-group no. 47: retail trade (except motor vehicles and motorcycles. Data used in the study is collected by the National Statistical Office, Thailand. The study consisted of four input factors include the number of companies, the number of personnel in logistics, the training cost in logistics, and outsourcing logistics management. Output factor includes the percentage of enterprises having inventory management. The results showed that the average relative efficiency of small-sized enterprises equals to 27.87 percent and 49.68 percent for the medium-sized enterprises.

Keywords: DEA, wholesales and retails, logistics, Thailand

Procedia PDF Downloads 409
2256 Image Segmentation: New Methods

Authors: Flaurence Benjamain, Michel Casperance

Abstract:

We present in this paper, first, a comparative study of three mathematical theories to achieve the fusion of information sources. This study aims to identify the characteristics inherent in theories of possibilities, belief functions (DST) and plausible and paradoxical reasoning to establish a strategy of choice that allows us to adopt the most appropriate theory to solve a problem of fusion in order, taking into account the acquired information and imperfections that accompany them. Using the new theory of plausible and paradoxical reasoning, also called Dezert-Smarandache Theory (DSmT), to fuse information multi-sources needs, at first step, the generation of the composites events witch is, in general, difficult. Thus, we present in this paper a new approach to construct pertinent paradoxical classes based on gray levels histograms, which also allows to reduce the cardinality of the hyper-powerset. Secondly, we developed a new technique for order and coding generalized focal elements. This method is exploited, in particular, to calculate the cardinality of Dezert and Smarandache. Then, we give an experimentation of classification of a remote sensing image that illustrates the given methods and we compared the result obtained by the DSmT with that resulting from the use of the DST and theory of possibilities.

Keywords: segmentation, image, approach, vision computing

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2255 Automatic Segmentation of Lung Pleura Based On Curvature Analysis

Authors: Sasidhar B., Bhaskar Rao N., Ramesh Babu D. R., Ravi Shankar M.

Abstract:

Segmentation of lung pleura is a preprocessing step in Computer-Aided Diagnosis (CAD) which helps in reducing false positives in detection of lung cancer. The existing methods fail in extraction of lung regions with the nodules at the pleura of the lungs. In this paper, a new method is proposed which segments lung regions with nodules at the pleura of the lungs based on curvature analysis and morphological operators. The proposed algorithm is tested on 06 patient’s dataset which consists of 60 images of Lung Image Database Consortium (LIDC) and the results are found to be satisfactory with 98.3% average overlap measure (AΩ).

Keywords: curvature analysis, image segmentation, morphological operators, thresholding

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2254 Analysis on Thermococcus achaeans with Frequent Pattern Mining

Authors: Jeongyeob Hong, Myeonghoon Park, Taeson Yoon

Abstract:

After the advent of Achaeans which utilize different metabolism pathway and contain conspicuously different cellular structure, they have been recognized as possible materials for developing quality of human beings. Among diverse Achaeans, in this paper, we compared 16s RNA Sequences of four different species of Thermococcus: Achaeans genus specialized in sulfur-dealing metabolism. Four Species, Barophilus, Kodakarensis, Hydrothermalis, and Onnurineus, live near the hydrothermal vent that emits extreme amount of sulfur and heat. By comparing ribosomal sequences of aforementioned four species, we found similarities in their sequences and expressed protein, enabling us to expect that certain ribosomal sequence or proteins are vital for their survival. Apriori algorithms and Decision Tree were used. for comparison.

Keywords: Achaeans, Thermococcus, apriori algorithm, decision tree

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2253 Numerical Study of a Nanofluid in a Truncated Cone

Authors: B. Mahfoud, A. Bendjaghlouli

Abstract:

Natural convection is simulated in a truncated cone filled with nanofluid. Inclined and top walls have constant temperature where the heat source is located on the bottom wall of the conical container which is thermally insulated. A finite volume approach is used to solve the governing equations using the SIMPLE algorithm for different parameters such as Rayleigh number, inclination angle of inclined walls of the enclosure and heat source length. The results showed an enhancement in cooling system by using a nanofluid, when conduction regime is assisted. The inclination angle of inclined sidewall and heat source length affect the heat transfer rate and the maximum temperature.

Keywords: heat source, truncated cone, nanofluid, natural convection

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2252 RAPD Analysis of Genetic Diversity of Castor Bean

Authors: M. Vivodík, Ž. Balážová, Z. Gálová

Abstract:

The aim of this work was to detect genetic variability among the set of 40 castor genotypes using 8 RAPD markers. Amplification of genomic DNA of 40 genotypes, using RAPD analysis, yielded in 66 fragments, with an average of 8.25 polymorphic fragments per primer. Number of amplified fragments ranged from 3 to 13, with the size of amplicons ranging from 100 to 1200 bp. Values of the polymorphic information content (PIC) value ranged from 0.556 to 0.895 with an average of 0.784 and diversity index (DI) value ranged from 0.621 to 0.896 with an average of 0.798. The dendrogram based on hierarchical cluster analysis using UPGMA algorithm was prepared and analyzed genotypes were grouped into two main clusters and only two genotypes could not be distinguished. Knowledge on the genetic diversity of castor can be used for future breeding programs for increased oil production for industrial uses.

Keywords: dendrogram, polymorphism, RAPD technique, Ricinus communis L.

Procedia PDF Downloads 465