Search results for: multiple regression

Authors: Hui-Chuan Chu, Min-Ju Liao, Wei-Kai Cheng, William Wei-Jen Tsai, Yuh-Min Chen

Abstract:

Avoiding learning failures in mathematics e-learning environments caused by emotional problems in students with autism has become an important topic for combining of special education with information and communications technology. This study presents an adaptive emotional adjustment model in mathematics e-learning for students with autism, emphasizing the lack of emotional perception in mathematics e-learning systems. In addition, an emotion classification for students with autism was developed by inducing emotions in mathematical learning environments to record changes in the physiological signals and facial expressions of students. Using these methods, 58 emotional features were obtained. These features were then processed using one-way ANOVA and information gain (IG). After reducing the feature dimension, methods of support vector machines (SVM), k-nearest neighbors (KNN), and classification and regression trees (CART) were used to classify four emotional categories: baseline, happy, angry, and anxious. After testing and comparisons, in a situation without feature selection, the accuracy rate of the SVM classification can reach as high as 79.3-%. After using IG to reduce the feature dimension, with only 28 features remaining, SVM still has a classification accuracy of 78.2-%. The results of this research could enhance the effectiveness of eLearning in special education.

Keywords: Emotion classification, Physiological and facial Expression measures, Students with autism, Mathematics e-learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1781

Authors: Gi-Ryun Park, Gye-Wan Moon, Dong-Hoon Yang

Abstract:

This study aims to explore the positive effects of self-leadership and innovative behavior that'd been proven in the existing researches proactively and understand the regulation effects of smartphone addiction which has recently become an issue in Korea. This study conducted a convenient sampling of college students attending the four colleges located at Daegu. A total of 210 questionnaires in 5-point Likert scale were distributed to college students. Among which, a total of 200 questionnaires were collected for our final analysis data. Both correlation analysis and regression analysis were carried out to verify those questionnaires through SPSS 20.0. As a result, college students' self-leadership had a significantly positive impact on innovative behavior (B= .210, P= .003). In addition, it is found that the relationship between self-leadership and innovative behavior can be adjusted depending on the degree of smartphone addiction in college students (B= .264, P= .000). This study could first understand the negative effects of smartphone addiction and find that if students' self-leadership is improved in terms of self-management and unnecessary use of smartphone is controlled properly, innovative behavior can be improved. In addition, this study is significant in that it attempts to identify a new impact of smartphone addiction with the recent environmental changes, unlike the existing researches that'd been carried out from the perspective of organizational behavior theory.

Keywords: Innovative Behavior, Revolutionary Behavior, Self-leadership, Smartphone Addiction.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3072

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

Abstract:

In the last few years, resting-state functional MRI (rs-fMRI) was widely used to investigate the architecture of brain networks by investigating the Blood Oxygenation Level Dependent response. This technique represented an interesting, robust and reliable approach to compare pathologic and healthy subjects in order to investigate neurodegenerative diseases evolution. On the other hand, the elaboration of rs-fMRI data resulted to be very prone to noise due to confounding factors especially the head motion. Head motion has long been known to be a source of artefacts in task-based functional MRI studies, but it has become a particularly challenging problem in recent studies using rs-fMRI. The aim of this work was to evaluate in MS patients a well-known motion correction algorithm from the FMRIB's Software Library - MCFLIRT - that could be applied to minimize the head motion distortions, allowing to correctly interpret rs-fMRI results.

Keywords: Head motion correction, MCFLIRT algorithm, multiple sclerosis, resting state fMRI.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1183

Authors: S. Balaji, E. Golden Julie, M. Rajaram, Y. Harold Robinson

Abstract:

Network lifetime improvement and uncertainty in multiple systems are the issues of wireless sensor network routing. This paper presents fuzzy based particle swarm optimization routing technique to improve the network scalability. Significantly, in the cluster formation procedure, fuzzy based system is used to solve the uncertainty and network balancing. Cluster heads play an important role to reduce the energy consumption using particle swarm optimization algorithm, the cluster head sends its information along data packets to the heads with link. The simulation results show that the presented routing protocol can perform load balancing effectively and reduce the energy consumption of cluster heads.

Keywords: Wireless sensor networks, fuzzy logic, PSO, LEACH.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1283

Authors: F. Mehran

Abstract:

In this paper, we study a class of serially concatenated block codes (SCBC) based on matrix interleavers, to be employed in fixed wireless communication systems. The performances of SCBC¬coded systems are investigated under various interleaver dimensions. Numerical results reveal that the matrix interleaver could be a competitive candidate over conventional block interleaver for frame lengths of 200 bits; hence, the SCBC coding based on matrix interleaver is a promising technique to be employed for speech transmission applications in many international standards such as pan-European Global System for Mobile communications (GSM), Digital Cellular Systems (DCS) 1800, and Joint Detection Code Division Multiple Access (JD-CDMA) mobile radio systems, where the speech frame contains around 200 bits.

Keywords: Matrix Interleaver, serial concatenated block codes (SCBC), turbo codes, wireless communications.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1940

Authors: Wuthichai Wongthatsanekorn

Abstract:

Plastic waste is a big issue in Thailand, but the amount of recycled plastic in Thailand is still low due to the high investment and operating cost. Hence, the rest of plastic waste are burnt to destroy or sent to the landfills. In order to be financial viable, an effective reverse logistics infrastructure is required to support the product recovery activities. However, there is a conflict between reducing the cost and raising environmental protection level. The purpose of this study is to build a goal programming (GP) so that it can be used to help analyze the proper planning of the Thailand-s plastic recycling system that involves multiple objectives. This study considers three objectives; reducing total cost, increasing the amount of plastic recovery, and raising the desired plastic materials in recycling process. The results from two priority structures show that it is necessary to raise the total cost budget in order to achieve targets on amount of recycled plastic and desired plastic materials.

Keywords: Goal Programming, Plastic Recycling, Thailand.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2656

Authors: Alicia Y. C. Tang, Sharifuddin M. Zain, Noorsaadah A. Rahman, Rukaini Abdullah

Abstract:

This paper discusses a qualitative simulator QRiOM that uses Qualitative Reasoning (QR) technique, and a process-based ontology to model, simulate and explain the behaviour of selected organic reactions. Learning organic reactions requires the application of domain knowledge at intuitive level, which is difficult to be programmed using traditional approach. The main objective of QRiOM is to help learners gain a better understanding of the fundamental organic reaction concepts, and to improve their conceptual comprehension on the subject by analyzing the multiple forms of explanation generated by the software. This paper focuses on the generation of explanation based on causal theories to explicate various phenomena in the chemistry subject. QRiOM has been tested with three classes problems related to organic chemistry, with encouraging results. This paper also presents the results of preliminary evaluation of QRiOM that reveal its explanation capability and usefulness.

Keywords: Artificial intelligence, explanation, ontology, organicreactions, qualitative reasoning, QPT.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1648

Authors: Ahmed Tawfik, Fausto Giunchiglia, Vincenzo Maltese

Abstract:

Ontologies provide a common understanding of a specific domain of interest that can be communicated between people and used as background knowledge for automated reasoning in a wide range of applications. In this paper, we address the design of multilingual ontologies following well-defined knowledge engineering methodologies with the support of novel collaborative development approaches. In particular, we present a collaborative platform which allows ontologies to be developed incrementally in multiple languages. This is made possible via an appropriate mapping between language independent concepts and one lexicalization per language (or a lexical gap in case such lexicalization does not exist). The collaborative platform has been designed to support the development of the Universal Knowledge Core, a multilingual ontology currently in English, Italian, Chinese, Mongolian, Hindi and Bangladeshi. Its design follows a workflow-based development methodology that models resources as a set of collaborative objects and assigns customizable workflows to build and maintain each collaborative object in a community driven manner, with extensive support of modern web 2.0 social and collaborative features.

Keywords: Knowledge Diversity, Knowledge Representation, Ontology Development.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2204

Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

Abstract:

Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: Accelerated life test, inverse power law, lithium ion battery, reliability evaluation, Weibull distribution.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 831

Authors: Moustafa Ahmed, Ahmed Bakry, Fumio Koyama

Abstract:

We report on the use of strong external optical feedback to enhance the modulation response of semiconductor lasers over a frequency passband around modulation frequencies higher than 60 GHz. We show that this modulation enhancement is a type of photon-photon resonance (PPR) of oscillating modes in the external cavity formed between the laser and the external reflector. The study is based on a time-delay rate equation model that takes into account both the strong feedback and multiple reflections in the external cavity. We examine the harmonic and intermodulation distortions associated with single and two-tone modulations in the mm-wave band of the resonant modulation. We show that compared with solitary lasers modulated around the carrier-photon resonance frequency, the present mm-wave modulated signal has lower distortions.

Keywords: Distortion, intensity modulation, optical feedback, semiconductor laser.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2582

Authors: Khalid Abd, Kazem Abhary, Romeo Marian

Abstract:

Multiple criteria decision making (MCDM) is an approach to ranking the solutions and finding the best one when two or more solutions are provided. In this study, MCDM approach is proposed to select the most suitable scheduling rule of robotic flexible assembly cells (RFACs). Two MCDM approaches, Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are proposed for solving the scheduling rule selection problem. The AHP method is employed to determine the weights of the evaluation criteria, while the TOPSIS method is employed to obtain final ranking order of scheduling rules. Four criteria are used to evaluate the scheduling rules. Also, four scheduling policies of RFAC are examined to choose the most appropriate one for this purpose. A numerical example illustrates applications of the suggested methodology. The results show that the methodology is practical and works in RFAC settings.

Keywords: AHP, TOPSIS, Scheduling rules selection

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1812

Authors: Jae Moon Lee

Abstract:

Most of researches for conventional simulations were studied focusing on flocks with a single species. While there exist the flocking behaviors with a single species in nature, the flocking behaviors are frequently observed with multi-species. This paper studies on the flocking simulation for heterogeneous agents. In order to simulate the flocks for heterogeneous agents, the conventional method uses the identifier of flock, while the proposed method defines the feature vector of agent and uses the similarity between agents by comparing with those feature vectors. Based on the similarity, the paper proposed the attractive force and repulsive force and then executed the simulation by applying two forces. The results of simulation showed that flock formation with heterogeneous agents is very natural in both cases. In addition, it showed that unlike the existing method, the proposed method can not only control the density of the flocks, but also be possible for two different groups of agents to flock close to each other if they have a high similarity.

Keywords: Flocking behavior, heterogeneous agents, similarity, simulation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1599

Authors: Jameson McFarlane, Thorne J. McFarlane, Leon Bernard

Abstract:

Social network sites (SNS) is an emerging phenomenon that is here to stay. The popularity and the ubiquity of the SNS technology are undeniable. Because most SNS are free and easy to use people from all walks of life and from almost any age are attracted to that technology. College age students are by far the largest segment of the population using SNS. Since most SNS have been adapted for mobile devices, not only do you find students using this technology in their study, while working on labs or on projects, a substantial number of students have been found to use SNS even while listening to lectures. This study found that SNS use has a significant negative impact on the grade point average of college students particularly in the first semester. However, this negative impact is greatly diminished by the end of the third semester partly because the students have adjusted satisfactorily to the challenges of college or because they have learned how to adequately manage their time. It was established that the kinds of activities the students are engaged in during the SNS use are the leading factor affecting academic performance. Of those activities, using SNS during a lecture or while studying is the foremost contributing factor to lower academic performance. This is due to “cognitive” or “information” bottleneck, a condition in which the students find it very difficult to multitask or to switch between resources leading to inefficiency in information retention and thus, educational performance.

Keywords: Social network sites, social network analysis, regression coefficient, psychological engagement.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 917

Authors: Ghulam Rasool, Ilka Philippow

Abstract:

Modernizing legacy applications is the key issue facing IT managers today because there's enormous pressure on organizations to change the way they run their business to meet the new requirements. The importance of software maintenance and reengineering is forever increasing. Understanding the architecture of existing legacy applications is the most critical issue for maintenance and reengineering. The artifacts recovery can be facilitated with different recovery approaches, methods and tools. The existing methods provide static and dynamic set of techniques for extracting architectural information, but are not suitable for all users in different domains. This paper presents a simple and lightweight pattern extraction technique to extract different artifacts from legacy systems using regular expression pattern specifications with multiple language support. We used our custom-built tool DRT to recover artifacts from existing system at different levels of abstractions. In order to evaluate our approach a case study is conducted.

Keywords: Artifacts recovery, Pattern matching, Reverseengineering, Program understanding, Regular expressions, Sourcecode analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1897

Authors: Maria Jokela, Matti Kutila, Jukka Laitinen, Florian Ahlers, Nicolas Hautière, TobiasSchendzielorz

Abstract:

It has been shown that in most accidents the driver is responsible due to being distracted or misjudging the situation. In order to solve such problems research has been dedicated to developing driver assistance systems that are able to monitor the traffic situation around the vehicle. This paper presents methods for recognizing several circumstances on a road. The methods use both the in-vehicle warning systems and the roadside infrastructure. Preliminary evaluation results for fog and ice-on-road detection are presented. The ice detection results are based on data recorded in a test track dedicated to tyre friction testing. The achieved results anticipate that ice detection could work at a performance of 70% detection with the right setup, which is a good foundation for implementation. However, the full benefit of the presented cooperative system is achieved by fusing the outputs of multiple data sources, which is the key point of discussion behind this publication.

Keywords: Smart roads, traffic monitoring, traffic scenedetection.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1627

Authors: Boontita Suchyukorn, Raweewan Auepanwiriyakul

Abstract:

A Data Warehouses is a repository of information integrated from source data. Information stored in data warehouse is the form of materialized in order to provide the better performance for answering the queries. Deciding which appropriated views to be materialized is one of important problem. In order to achieve this requirement, the constructing search space close to optimal is a necessary task. It will provide effective result for selecting view to be materialized. In this paper we have proposed an approach to reoptimize Multiple View Processing Plan (MVPP) by using global common subexpressions. The merged queries which have query processing cost not close to optimal would be rewritten. The experiment shows that our approach can help to improve the total query processing cost of MVPP and sum of query processing cost and materialized view maintenance cost is reduced as well after views are selected to be materialized.

Keywords: Data Warehouse, materialized views, query rewriting, common subexpressions.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1678

Authors: I. Bolis, S. N. Morioka, L. I. Sznelwar

Abstract:

The growing importance of sustainability in corporate policies represents a great opportunity for workers to gain more consideration, with great benefits to their well being. Sustainable work is believed to be one which improves the organization-s performance and fosters professional development as well as workers- health. In a multiple case study based on document research, information was sought about work activities and their sustainability or corporate social responsibility (CSR) policies, as disseminated by corporations. All the companies devoted attention to work activities and delivered a good amount of information about them. Nevertheless, the information presented was generic; all the actions developed were top-down and there was no information about the impact of changes aimed at sustainability on the workers- activities. It was found that the companies seemed to be at an early stage. In the future, they need to show more commitment through concrete goals: they must be aware that workers contribute directly to the corporations- sustainability. This would allow room for Ergonomics and Work Psychodynamics to be incorporated and to be useful for both companies and society, so as to promote and ensure work sustainability.

Keywords: Sustainability, ergonomics, work psychodynamics, multinational companies.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1966

Authors: Bruno B. Oliveira, Arnaldo P. Mourão, Teógenes A. da Silva

Abstract:

The Brazilian legislation has only established diagnostic reference levels (DRLs) in terms of Multiple Scan Average Dose (MSAD) as a quality control parameter for computed tomography (CT) scanners. Compliance with DRLs can be verified by measuring the Computed Tomography Kerma Index (Ca,100) with a pencil ionization chamber or by obtaining the kerma distribution in CT scans with radiochromic films or rod shape lithium fluoride termoluminescent dosimeters (TLD-100). TL dosimeters were used to record kerma profiles and to determine MSAD values of a Bright Speed model GE CT scanner. Measurements were done with radiochromic films and TL dosimeters distributed in cylinders positioned in the center and in four peripheral bores of a standard polymethylmethacrylate (PMMA) body CT dosimetry phantom. Irradiations were done using a protocol for adult chest. The maximum values were found at the midpoint of the longitudinal axis. The MSAD values obtained with three dosimetric techniques were compared.

Keywords: Kerma profile, CT, MSAD, patient dosimetry

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2062

Authors: Masaki Yamaguchi, Daimei Sasayama, Shinsuke Washizuka

Abstract:

The goal of this study was to examine the possibility of salivary cytokines for the screening of attention deficit hyperactivity disorder (ADHD) in children. We carried out a case-control study, including 19 children with ADHD and 17 healthy children (controls). A multiplex bead array immunoassay was used to conduct a multi-analysis of 27 different salivary cytokines. Six salivary cytokines (interleukin (IL)-1β, IL-8, IL12p70, granulocyte colony-stimulating factor (G-CSF), interferon gamma (IFN-γ), and vascular endothelial growth factor (VEGF)) were significantly associated with the presence of ADHD (p < 0.05). An informative salivary cytokine panel was developed using VEGF by logistic regression analysis (odds ratio: 0.251). Receiver operating characteristic analysis revealed that assessment of a panel using VEGF showed “good” capability for discriminating between ADHD patients and controls (area under the curve: 0.778). ADHD has been hypothesized to be associated with reduced cerebral blood flow in the frontal cortex, due to reduced VEGF levels. Our study highlights the possibility of utilizing differential salivary cytokine levels for point-of-care testing (POCT) of biomarkers in children with ADHD.

Keywords: Cytokine, saliva, attention deficit hyperactivity disorder, child, biomarker.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 713

Authors: A. A. Hossam-Eldin, E. N. Abdallah, M. S. El-Nozahy

Abstract:

The identification and elimination of bad measurements is one of the basic functions of a robust state estimator as bad data have the effect of corrupting the results of state estimation according to the popular weighted least squares method. However this is a difficult problem to handle especially when dealing with multiple errors from the interactive conforming type. In this paper, a self adaptive genetic based algorithm is proposed. The algorithm utilizes the results of the classical linearized normal residuals approach to tune the genetic operators thus instead of making a randomized search throughout the whole search space it is more likely to be a directed search thus the optimum solution is obtained at very early stages(maximum of 5 generations). The algorithm utilizes the accumulating databases of already computed cases to reduce the computational burden to minimum. Tests are conducted with reference to the standard IEEE test systems. Test results are very promising.

Keywords: Bad Data, Genetic Algorithms, Linearized Normal residuals, Observability, Power System State Estimation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1346

Authors: L. A. Muhammad, M. S. Argungu

Abstract:

Educational data mining (EDM) has recorded substantial considerations. Techniques of data mining in one way or the other have been proposed to dig out out-of-sight knowledge in educational data. The result of the study got assists academic institutions in further enhancing their process of learning and methods of passing knowledge to students. Consequently, the performance of students boasts and the educational products are by no doubt enhanced. This study adopted a student performance prediction model premised on techniques of data mining with Students' Essential Features (SEF). SEF are linked to the learner's interactivity with the e-learning management system. The performance of the student's predictive model is assessed by a set of classifiers, viz. Bayes Network, Logistic Regression, and Reduce Error Pruning Tree (REP). Consequently, ensemble methods of Bagging, Boosting, and Random Forest (RF) are applied to improve the performance of these single classifiers. The study reveals that the result shows a robust affinity between learners' behaviors and their academic attainment. Result from the study shows that the REP Tree and its ensemble record the highest accuracy of 83.33% using SEF. Hence, in terms of the Receiver Operating Curve (ROC), boosting method of REP Tree records 0.903, which is the best. This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, bagging, Random Forest, boosting, data mining, classifiers, machine learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 760

Authors: Yao-Hong Tsai

Abstract:

This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: Image fusion, iris recognition, local binary pattern, wavelet.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2217

Authors: Mohamed R. Mhereeg

Abstract:

The paper discusses the design of a .NET Windows Service based agent system called MACS (Multi-Agent Classification System). MACS is a system aims to accurately classify spreadsheet developers competency over a network. It is designed to automatically and autonomously monitor spreadsheet users and gather their development activities based on the utilization of the software multi-agent technology (MAS). This is accomplished in such a way that makes management capable to efficiently allow for precise tailor training activities for future spreadsheet development. The monitoring agents of MACS are intended to be distributed over the WWW in order to satisfy the monitoring and classification of the multiple developer aspect. The Prometheus methodology is used for the design of the agents of MACS. Prometheus has been used to undertake this phase of the system design because it is developed specifically for specifying and designing agent-oriented systems. Additionally, Prometheus specifies also the communication needed between the agents in order to coordinate to achieve their delegated tasks.

Keywords: Classification, Design, MACS, MAS, Prometheus.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1689

Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

Abstract:

Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine (SVM), Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: Student performance, supervised machine learning, prediction, classification, cross-validation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 548

Authors: S. Boughanem, D. A. Jesson, M. J. Mulheron, P.A. Smith C. Eddie, S. Psomas, M. Rimes

Abstract:

Cements, which are intrinsically brittle materials, can exhibit a degree of pseudo-ductility when reinforced with a sufficient volume fraction of a fibrous phase. This class of materials, called Engineered Cement Composites (ECC) has the potential to be used in future tunneling applications where a level of pseudo-ductility is required to avoid brittle failures. However uncertainties remain regarding mechanical performance. Previous work has focused on comparatively thin specimens; however for future civil engineering applications, it is imperative that the behavior in tension of thicker specimens is understood. In the present work, specimens containing cement powder and admixtures have been manufactured following two different processes and tested in tension. Multiple matrix cracking has been observed during tensile testing, leading to a “strain-hardening" behavior, confirming the possible suitability of ECC material when used as thick sections (greater than 50mm) in tunneling applications.

Keywords: Cement composite, polymeric fibers, pseudoductility, test-geometry.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2468

Authors: Meysam Naeimi, Zili Li, Rolf Dollevoet

Abstract:

A new small–scale test rig developed for rolling contact fatigue (RCF) investigations in wheel–rail material. This paper presents the scaling strategy of the rig based on dimensional analysis and mechanical modelling. The new experimental rig is indeed a spinning frame structure with multiple wheel components over a fixed rail-track ring, capable of simulating continuous wheelrail contact in a laboratory scale. This paper describes the dimensional design of the rig, to derive its overall scaling strategy and to determine the key elements’ specifications. Finite element (FE) modelling is used to simulate the mechanical behavior of the rig with two sample scale factors of 1/5 and 1/7. The results of FE models are compared with the actual railway system to observe the effectiveness of the chosen scales. The mechanical properties of the components and variables of the system are finally determined through the design process.

Keywords: New test rig, rolling contact fatigue, rail, small scale.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2340

Authors: Azhar Hussain, Kashif Shahzad, Chunming Tang

Abstract:

this paper gives a novel approach towards real-time speed estimation of multiple traffic vehicles using fuzzy logic and image processing techniques with proper arrangement of camera parameters. The described algorithm consists of several important steps. First, the background is estimated by computing median over time window of specific frames. Second, the foreground is extracted using fuzzy similarity approach (FSA) between estimated background pixels and the current frame pixels containing foreground and background. Third, the traffic lanes are divided into two parts for both direction vehicles for parallel processing. Finally, the speeds of vehicles are estimated by Maximum a Posterior Probability (MAP) estimator. True ground speed is determined by utilizing infrared sensors for three different vehicles and the results are compared to the proposed algorithm with an accuracy of ± 0.74 kmph.

Keywords: Defuzzification, Fuzzy similarity approach, lane cropping, Maximum a Posterior Probability (MAP) estimator, Speed estimation

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2806

Authors: K. C. Meher, R. K. Swain, C. K. Chanda

Abstract:

This paper gives an intuition regarding glowworm swarm optimization (GSO) technique to solve dynamic economic dispatch (DED) problems of thermal generating units. The objective of the problem is to schedule optimal power generation of dedicated thermal units over a specific time band. In this study, Glowworm swarm optimization technique enables a swarm of agents to split into subgroup, exhibit simultaneous taxis towards each other and rendezvous at multiple optima (not necessarily equal) of a given multimodal function. The feasibility of the GSO method has been tested on ten-unit-test systems where the power balance constraints, operating limits, valve point effects, and ramp rate limits are taken into account. The results obtained by the proposed technique are compared with other heuristic techniques. The results show that GSO technique is capable of producing better results.

Keywords: Dynamic economic dispatch, Glowworm swarm optimization, Luciferin, Valve–point loading effect, Ramp rate limits.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1315

Authors: Dinesh Kumar, Y. S. Brar, V. K. Banga

Abstract:

Multicast Network Technology has pervaded our lives-a few examples of the Networking Techniques and also for the improvement of various routing devices we use. As we know the Multicast Data is a technology offers many applications to the user such as high speed voice, high speed data services, which is presently dominated by the Normal networking and the cable system and digital subscriber line (DSL) technologies. Advantages of Multi cast Broadcast such as over other routing techniques. Usually QoS (Quality of Service) Guarantees are required in most of Multicast applications. The bandwidth-delay constrained optimization and we use a multi objective model and routing approach based on genetic algorithm that optimizes multiple QoS parameters simultaneously. The proposed approach is non-dominated routes and the performance with high efficiency of GA. Its betterment and high optimization has been verified. We have also introduced and correlate the result of multicast GA with the Broadband wireless to minimize the delay in the path.

Keywords: GA (genetic Algorithms), Quality of Service, MOGA, Steiner Tree.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1556

Authors: Tanwarat Kajsongkram, Saowalux Rotamporn, Sirinat Limbunruang, Sirinan Thubthimthed

Abstract:

High Performance Liquid Chromatography (HPLC) method was developed and validated for simultaneous estimation of 6-Gingerol(6G) and 6-Shogaol(6S) in joint pain relief gel containing ginger extract. The chromatographic separation was achieved by using C18 column, 150 x 4.6mm i.d., 5μ Luna, mobile phase containing acetonitrile and water (gradient elution). The flow rate was 1.0 ml/min and the absorbance was monitored at 282 nm. The proposed method was validated in terms of the analytical parameters such as specificity, accuracy, precision, linearity, range, limit of detection (LOD), limit of quantification (LOQ), and determined based on the International Conference on Harmonization (ICH) guidelines. The linearity ranges of 6G and 6S were obtained over 20- 60 and 6-18 μg/ml respectively. Good linearity was observed over the above-mentioned range with linear regression equation Y= 11016x- 23778 for 6G and Y = 19276x-19604 for 6S (x is concentration of analytes in μg/ml and Y is peak area). The value of correlation coefficient was found to be 0.9994 for both markers. The limit of detection (LOD) and limit of quantification (LOQ) for 6G were 0.8567 and 2.8555 μg/ml and for 6S were 0.3672 and 1.2238 μg/ml respectively. The recovery range for 6G and 6S were found to be 91.57 to 102.36 % and 84.73 to 92.85 % for all three spiked levels. The RSD values from repeated extractions for 6G and 6S were 3.43 and 3.09% respectively. The validation of developed method on precision, accuracy, specificity, linearity, and range were also performed with well-accepted results.

Keywords: Ginger, 6-gingerol, HPLC, 6-shogaol.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3423