Search results for: selection methodology
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7271

Search results for: selection methodology

6821 The Effect of Program Type on Mutation Testing: Comparative Study

Authors: B. Falah, N. E. Abakouy

Abstract:

Due to its high computational cost, mutation testing has been neglected by researchers. Recently, many cost and mutants’ reduction techniques have been developed, improved, and experimented, but few of them has relied the possibility of reducing the cost of mutation testing on the program type of the application under test. This paper is a comparative study between four operators’ selection techniques (mutants sampling, class level operators, method level operators, and all operators’ selection) based on the program code type of each application under test. It aims at finding an alternative approach to reveal the effect of code type on mutation testing score. The result of our experiment shows that the program code type can affect the mutation score and that the programs using polymorphism are best suited to be tested with mutation testing.

Keywords: equivalent mutant, killed mutant, mutation score, mutation testing, program code type, software testing

Procedia PDF Downloads 533
6820 A Hybrid System for Boreholes Soil Sample

Authors: Ali Ulvi Uzer

Abstract:

Data reduction is an important topic in the field of pattern recognition applications. The basic concept is the reduction of multitudinous amounts of data down to the meaningful parts. The Principal Component Analysis (PCA) method is frequently used for data reduction. The Support Vector Machine (SVM) method is a discriminative classifier formally defined by a separating hyperplane. In other words, given labeled training data, the algorithm outputs an optimal hyperplane which categorizes new examples. This study offers a hybrid approach that uses the PCA for data reduction and Support Vector Machines (SVM) for classification. In order to detect the accuracy of the suggested system, two boreholes taken from the soil sample was used. The classification accuracies for this dataset were obtained through using ten-fold cross-validation method. As the results suggest, this system, which is performed through size reduction, is a feasible system for faster recognition of dataset so our study result appears to be very promising.

Keywords: feature selection, sequential forward selection, support vector machines, soil sample

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6819 Functional Mortality of Anopheles stephensi, the Urban Malaria Vector as Induced by the Sublethal Exposure to Deltamethrin

Authors: P. Aarumugam, N. Krishnamoorthy, K. Gunasekaran

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The mosquitoes with loss of minimum three legs especially the hind legs have the negative impact on the survival hood of mosquitoes. Three days old unfed adult female laboratory strain was selected in each generation against sublethal dosages (0.004%, 0.005%, 0.007% and 0.01%) of deltamethrin upto 40 generations. Impregnated papers with acetone were used for control. Every fourth generation, survived mosquitoes were observed for functional mortality. Hind legs lost were significantly (P< 0.05) higher in treated than the controls up to generation 24, thereafter no significant lost. In contrary, no significant forelegs lost among exposed mosquitoes. Middle legs lost were also not significant in the exposed mosquitoes except first generation (F1). The field strain (Chennai) did not show any significant loss of legs (fore or mid or hind) compared to the control. The selection pressure on mosquito population influences strong natural selection to develop various adaptive mechanisms.

Keywords: Anopheles stephensi, deltamethrin, functional mortality, synthetic pyrethroids

Procedia PDF Downloads 382
6818 Understanding the 3R's Element in the Creation of Ecological Form That Leads to Ecodesign

Authors: Mohd Hasni Chumiran

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The rapid growth of global industrialism over the past few decades has led to various environmental issues and ecological instability, all due to human activity. In order to solve this global issue, the manufacturers alike have begun to embrace the use of ecodesign products. However, when considering a specific field, multiple questions have been raised and industrial designers (the practising designer's R&D group) have been unable to define the ecological cycle methodology. In this paper, we investigate the validation of problematic in the creation of ecodesign products with the 'reduce, reuse and recycle' (3R’s) method, which is an untested product design theory. The aim of this research is to address the 3R’s method can be extracted in order to transmit an ecological form of ecodesign, specifically among Malaysian furniture manufacturers. By operating the Descriptive Study I (DS-I) phase: Design Research Methodology (DRM), the research has applied two research approaches by the methodological triangulation tradition. To achieve the result, this validation of descriptive structure (design theory) shall be matched with the research hypothesis along the use of research questions.

Keywords: design research methodology, ecodesign, ecological form, industrial design

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6817 Applications of Digital Tools, Satellite Images and Geographic Information Systems in Data Collection of Greenhouses in Guatemala

Authors: Maria A. Castillo H., Andres R. Leandro, Jose F. Bienvenido B.

Abstract:

During the last 20 years, the globalization of economies, population growth, and the increase in the consumption of fresh agricultural products have generated greater demand for ornamentals, flowers, fresh fruits, and vegetables, mainly from tropical areas. This market situation has demanded greater competitiveness and control over production, with more efficient protected agriculture technologies, which provide greater productivity and allow us to guarantee the quality and quantity that is required in a constant and sustainable way. Guatemala, located in the north of Central America, is one of the largest exporters of agricultural products in the region and exports fresh vegetables, flowers, fruits, ornamental plants, and foliage, most of which were grown in greenhouses. Although there are no official agricultural statistics on greenhouse production, several thesis works, and congress reports have presented consistent estimates. A wide range of protection structures and roofing materials are used, from the most basic and simple ones for rain control to highly technical and automated structures connected with remote sensors for monitoring and control of crops. With this breadth of technological models, it is necessary to analyze georeferenced data related to the cultivated area, to the different existing models, and to the covering materials, integrated with altitude, climate, and soil data. The georeferenced registration of the production units, the data collection with digital tools, the use of satellite images, and geographic information systems (GIS) provide reliable tools to elaborate more complete, agile, and dynamic information maps. This study details a methodology proposed for gathering georeferenced data of high protection structures (greenhouses) in Guatemala, structured in four phases: diagnosis of available information, the definition of the geographic frame, selection of satellite images, and integration with an information system geographic (GIS). It especially takes account of the actual lack of complete data in order to obtain a reliable decision-making system; this gap is solved through the proposed methodology. A summary of the results is presented in each phase, and finally, an evaluation with some improvements and tentative recommendations for further research is added. The main contribution of this study is to propose a methodology that allows to reduce the gap of georeferenced data in protected agriculture in this specific area where data is not generally available and to provide data of better quality, traceability, accuracy, and certainty for the strategic agricultural decision öaking, applicable to other crops, production models and similar/neighboring geographic areas.

Keywords: greenhouses, protected agriculture, GIS, Guatemala, satellite image, digital tools, precision agriculture

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6816 Determining the Appropriate Methodology for the Security Evaluation of Equipment Related to Information and Communication Technology in the Industry

Authors: Sofia Ahanj Sofia Ahanj, Mahsa Rahmani Mahsa Rahmani, Zahra Sadeghigol, Vida Nobakht Vida Nobakht

Abstract:

Providing security in the electricity industry, as one of the vital infrastructures of the country, is one of the essential operations that must be taken in order to improve the security of the country. Resistant security strategies need to be regularly implemented as a dynamic process to improve security, and security evaluation is one of the most important steps in this process. Methodology in the field of evaluation in both technical and managerial dimensions is discussed in the laboratory. There are various standards in the field of general ICT technical-security evaluation. The most important are ISO / IEC 15408, ISO / IEC 27001 and NIST SP 800-53. In the present paper, these standards are first examined. Then, the standards and reports in the industrial field have been reviewed and compared, and finally, based on the results and special considerations of information and communication technology equipment in the electricity industry, the appropriate methodology has been presented.

Keywords: security standards, ISO/IEC 15408, ISA/IEC 62443 series, NIST SP 800-53, NISTIR 7628

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6815 Automatic Product Identification Based on Deep-Learning Theory in an Assembly Line

Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: deep-learning, image classification, image identification, industrial engineering.

Procedia PDF Downloads 142
6814 Multi-Disciplinary Optimisation Methodology for Aircraft Load Prediction

Authors: Sudhir Kumar Tiwari

Abstract:

The paper demonstrates a methodology that can be used at an early design stage of any conventional aircraft. This research activity assesses the feasibility derivation of methodology for aircraft loads estimation during the various phases of design for a transport category aircraft by utilizing potential of using commercial finite element analysis software, which may drive significant time saving. Early Design phase have limited data and quick changing configuration results in handling of large number of load cases. It is useful to idealize the aircraft as a connection of beams, which can be very accurately modelled using finite element analysis (beam elements). This research explores the correct approach towards idealizing an aircraft using beam elements. FEM Techniques like inertia relief were studied for implementation during course of work. The correct boundary condition technique envisaged for generation of shear force, bending moment and torque diagrams for the aircraft. The possible applications of this approach are the aircraft design process, which have been investigated.

Keywords: multi-disciplinary optimization, aircraft load, finite element analysis, stick model

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6813 Using Greywolf Optimized Machine Learning Algorithms to Improve Accuracy for Predicting Hospital Readmission for Diabetes

Authors: Vincent Liu

Abstract:

Machine learning algorithms (ML) can achieve high accuracy in predicting outcomes compared to classical models. Metaheuristic, nature-inspired algorithms can enhance traditional ML algorithms by optimizing them such as by performing feature selection. We compare ten ML algorithms to predict 30-day hospital readmission rates for diabetes patients in the US using a dataset from UCI Machine Learning Repository with feature selection performed by Greywolf nature-inspired algorithm. The baseline accuracy for the initial random forest model was 65%. After performing feature engineering, SMOTE for class balancing, and Greywolf optimization, the machine learning algorithms showed better metrics, including F1 scores, accuracy, and confusion matrix with improvements ranging in 10%-30%, and a best model of XGBoost with an accuracy of 95%. Applying machine learning this way can improve patient outcomes as unnecessary rehospitalizations can be prevented by focusing on patients that are at a higher risk of readmission.

Keywords: diabetes, machine learning, 30-day readmission, metaheuristic

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6812 The BL-5D Model: The Development of a Model of Instructional Design for Blended Learning Activities

Authors: Damian Gordon, Paul Doyle, Anna Becevel, Júlia Vilafranca Molero, Cinta Gascon, Arianna Vitiello, Tina Baloh

Abstract:

It has long been recognized that the creation of any teaching content can be enhanced if the development process follows a pre-defined approach, which is often referred to as an instructional design methodology. These methodologies typically define a number of stages, or phases, that an educator should undertake to help ensure the quality of the final teaching content that is developed. In this paper, we present an instructional design methodology that is focused specifically on the introduction of blended resources into a heretofore bricks-and-mortar course. To achieve this, research was undertaken concerning a range of models of instructional design, as well as literature covering some of the key challenges and “pain points” of blending. Following this, our model, the BL-5D model, is presented, which incorporates some key questions at each stage of this five-stage methodology to guide the development process. Finally, a discussion of some of the key themes and issues that have been uncovered in this work is presented, as well as a template for a blended learning case study that emerged from this approach.

Keywords: blended learning, challenges of blended learning, design methodologies, instructional design

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6811 Design of Broadband Power Divider for 3G and 4G Applications

Authors: A. M. El-Akhdar, A. M. El-Tager, H. M. El-Hennawy

Abstract:

This paper presents a broadband power divider with equal power division ratio. Two sections of transmission line transformers based on coupled microstrip lines are applied to obtain broadband performance. In addition, design methodology is proposed for the novel structure. A prototype is designed, simulated to operate in the band from 2.1 to 3.8 GHz to fulfill the requirements of 3G and 4G applications. The proposed structure features reduced size and less resistors than other conventional techniques. Simulation verifies the proposed idea and design methodology.

Keywords: power dividers, coupled lines, microstrip, 4G applications

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6810 Novel Bioinspired Design to Capture Smoky CO2 by Reactive Absorption with Aqueous Scrubber

Authors: J. E. O. Hernandez

Abstract:

In the next 20 years, energy production by burning fuels will increase and so will the atmospheric concentration of CO2 and its well-known threats to life on Earth. The technologies available for capturing CO2 are still dubious and this keeps fostering an interest in bio-inspired approaches. The leading one is the application of carbonic anhydrase (CA) –a superfast biocatalyst able to convert up to one million molecules of CO2 into carbonates in water. However, natural CA underperforms when applied to real smoky CO2 in chimneys and, so far, the efforts to create superior CAs in the lab rely on screening methods running under pristine conditions at the micro level, which are far from resembling those in chimneys. For the evolution of man-made enzymes, selection rather than screening would be ideal but this is challenging because of the need for a suitable artificial environment that is also sustainable for our society. Herein we present the stepwise design and construction of a bioprocess (from bench-scale to semi-pilot) for evolutionary selection experiments. In this bioprocess, reaction and adsorption took place simultaneously at atmospheric pressure in a spray tower. The scrubbing solution was fed countercurrently by reusing municipal pressure and it was mainly prepared with water, carbonic anhydrase and calcium chloride. This bioprocess allowed for the enzymatic carbonation of smoky CO2; the reuse of process water and the recovery of solid carbonates without cooling of smoke, pretreatments, solvent amines and compression of CO2. The average yield of solid carbonates was 0.54 g min-1 or 12-fold the amount produced in serum bottles at lab bench scale. This bioprocess could be used as a tailor-made environment for driving the selection of superior CAs. The bioprocess and its match CA could be sustainably used to reduce global warming by CO2 emissions from exhausts.

Keywords: biological carbon capture and sequestration, carbonic anhydrase, directed evolution, global warming

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6809 Identifying Applicant Potential Through Admissions Testing

Authors: Belinda Brunner

Abstract:

Objectives: Communicate common test constructs of well-known higher education admissions tests. Discuss influences on admissions test construct definition and design and discuss research on related to factors influencing success in academic study. Discuss how admissions tests can be used to identify relevant talent. Examine how admissions test can be used to facilitate educational mobility and inform selection decisions when the prerequisite curricula is not standardized Observations: Generally speaking, constructs of admissions tests can be placed along a continuum from curriculum-related knowledge to more general reasoning abilities. For example, subject-specific achievement tests are more closely aligned to a prescribed curriculum, while reasoning tests are typically not associated with a specific curriculum. This session will draw reference from the test-constructs of well-known international higher education admissions tests, such as the UK clinical aptitude test (UKCAT) which is used for medicine and dentistry admissions. Conclusions: The purpose of academic admissions testing is to identify potential students with the prerequisite skills set needed to succeed in the academic environment, but how can the test construct help achieve this goal? Determination of the appropriate test construct for tests used in the admissions selection decisions should be influenced by a number of factors, including the preceding academic curricula, other criteria influencing the admissions decision, and the principal purpose for testing. Attendees of this session will learn the types of aptitudes and knowledge that are assessed higher education admissions tests and will have the opportunity to gain insight into how careful and deliberate consideration of the desired test constructs can aid in identifying potential students with the greatest likelihood of success in medical school.

Keywords: admissions, measuring success, selection, identify skills

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6808 Designing and Evaluating Pedagogic Conversational Agents to Teach Children

Authors: Silvia Tamayo-Moreno, Diana Pérez-Marín

Abstract:

In this paper, the possibility of children studying by using an interactive learning technology called Pedagogic Conversational Agent is presented. The main benefit is that the agent is able to adapt the dialogue to each student and to provide automatic feedback. Moreover, according to Math teachers, in many cases students are unable to solve the problems even knowing the procedure to solve them, because they do not understand what they have to do. The hypothesis is that if students are helped to understand what they have to solve, they will be able to do it. Taken that into account, we have started the development of Dr. Roland, an agent to help students understand Math problems following a User-Centered Design methodology. The use of this methodology is proposed, for the first time, to design pedagogic agents to teach any subject from Secondary down to Pre-Primary education. The reason behind proposing a methodology is that while working on this project, we noticed the lack of literature to design and evaluate agents. To cover this gap, we describe how User-Centered Design can be applied, and which usability techniques can be applied to evaluate the agent.

Keywords: pedagogic conversational agent, human-computer interaction, user-centered design, natural language interface

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6807 A Bibliometric Analysis of Trends in Change Management Sciences

Authors: Thomas Lauer

Abstract:

The paper aims to give an overview of change management research by using bibliometric methodology. Based on research papers of the last decade, which are listed on Research Gate, a multidimensional categorization is done. Considering categories like topic (e.g., success factors), industry, or research methodology, the development of the discipline is traced and, in a second step, confronted with external developments of the business environment, such as climate change, gen Z or COVID, to name a few. Based on these findings, a final evaluation concerning the thematical fit of previous research topics is also made, as well as a preview of likely future trends in change management sciences.

Keywords: change management, bibliometrics, scientific trends, research topics

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6806 A Methodology for Optimisation of Water Containment Systems

Authors: Amir Hedjripour

Abstract:

The required dewatering configuration for a contaminated sediment dam is discussed to meet no-spill criteria for a defined Average Recurrence Interval (ARI). There is an option for the sediment dam to pump the contaminated water to another storage facility before its capacity is exceeded. The system is subjected to a range of storm durations belonging to the design ARI with concurrent dewatering to the other storage facility. The model is set up in 1-minute time intervals and temporal patterns of storm events are used to de-segregate the total storm depth into partial durations. By running the model for selected storm durations, the maximum water volume in the dam is recorded as the critical volume, which indicates the required storage capacity for that storm duration. Runoff from upstream catchment and the direct rainfall over the dam open area are calculated by taking into account the time of concentration for the catchment. Total 99 different storm durations from 5 minutes to 72 hours were modelled together with five dewatering scenarios from 50 l/s to 500 l/s. The optimised dam/pump configuration is selected by plotting critical points for all cases and storage-dewatering envelopes. A simple economic analysis is also presented in the paper using Present-Value (PV) analysis to assist with the financial evaluation of each configuration and selection of the best alternative.

Keywords: contaminated water, optimisation, pump, sediment dam

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6805 Solving Dimensionality Problem and Finding Statistical Constructs on Latent Regression Models: A Novel Methodology with Real Data Application

Authors: Sergio Paez Moncaleano, Alvaro Mauricio Montenegro

Abstract:

This paper presents a novel statistical methodology for measuring and founding constructs in Latent Regression Analysis. This approach uses the qualities of Factor Analysis in binary data with interpretations on Item Response Theory (IRT). In addition, based on the fundamentals of submodel theory and with a convergence of many ideas of IRT, we propose an algorithm not just to solve the dimensionality problem (nowadays an open discussion) but a new research field that promises more fear and realistic qualifications for examiners and a revolution on IRT and educational research. In the end, the methodology is applied to a set of real data set presenting impressive results for the coherence, speed and precision. Acknowledgments: This research was financed by Colciencias through the project: 'Multidimensional Item Response Theory Models for Practical Application in Large Test Designed to Measure Multiple Constructs' and both authors belong to SICS Research Group from Universidad Nacional de Colombia.

Keywords: item response theory, dimensionality, submodel theory, factorial analysis

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6804 Optimized Weight Selection of Control Data Based on Quotient Space of Multi-Geometric Features

Authors: Bo Wang

Abstract:

The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

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6803 Comparative Analysis of Forensic Medicine Course Evaluation: A Two Year Study

Authors: Prateek Rastogi

Abstract:

Medical teaching in present era concentrates not only on teaching but on effective teaching. For effective teaching a combination of effective carefully designed curriculum, an educated educator, competent learner and fool proof evaluation system is required. Keeping these parameters in mind and study was undertaken at Kasturba Medical College, Mangalore among medical students. In this study, evaluation of Forensic Medicine syllabus along with its teaching and evaluation methodology was done using 20 different parameters. This questionnaire based study was done over a period of two years i.e. 2013 and 2014. Batch of students who just passed the forensic medicine subject was included for study. Carefully designed questionnaire contained questions related to course content, teaching methodology and evaluation system along with provisions to mention merits and demerits of subject. The feedbacks in first round were analyzed and suggestions were implemented before conducting the second round of study. Overall evaluation of course was done as well as it was compared with other subjects of second MBBS. It was noted that Scores improved in 2nd survey thus stressing the importance of course evaluation and student feedback in teaching improvement.

Keywords: teaching methodology, system of evaluation, course content, bioinformatics, biomedicine

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6802 A Methodology for Seismic Performance Enhancement of RC Structures Equipped with Friction Energy Dissipation Devices

Authors: Neda Nabid

Abstract:

Friction-based supplemental devices have been extensively used for seismic protection and strengthening of structures, however, the conventional use of these dampers may not necessarily lead to an efficient structural performance. Conventionally designed friction dampers follow a uniform height-wise distribution pattern of slip load values for more practical simplicity. This can lead to localizing structural damage in certain story levels, while the other stories accommodate a negligible amount of relative displacement demand. A practical performance-based optimization methodology is developed to tackle with structural damage localization of RC frame buildings with friction energy dissipation devices under severe earthquakes. The proposed methodology is based on the concept of uniform damage distribution theory. According to this theory, the slip load values of the friction dampers redistribute and shift from stories with lower relative displacement demand to the stories with higher inter-story drifts to narrow down the discrepancy between the structural damage levels in different stories. In this study, the efficacy of the proposed design methodology is evaluated through the seismic performance of five different low to high-rise RC frames equipped with friction wall dampers under six real spectrum-compatible design earthquakes. The results indicate that compared to the conventional design, using the suggested methodology to design friction wall systems can lead to, by average, up to 40% reduction of maximum inter-story drift; and incredibly more uniform height-wise distribution of relative displacement demands under the design earthquakes.

Keywords: friction damper, nonlinear dynamic analysis, RC structures, seismic performance, structural damage

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6801 Problems Confronting the Teaching of Sex Education in Some Selected Secondary Schools in the Akoko Region of Ondo State, Nigeria

Authors: Jimoh Abiodun Alaba

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Context: In many traditional African societies, sex education is often considered a taboo topic. However, the importance of sex education is becoming increasingly evident. This study aims to investigate the challenges faced in teaching sex education in selected secondary schools in the Akoko region of Ondo state, Nigeria. Research Aim: The aim of this study is to identify and examine the problems confronting the teaching of sex education in selected secondary schools in the Akoko region of Ondo state, Nigeria. Methodology: The study utilized a multi-stage sampling method. The first stage involved a purposive selection of ten (10) secondary schools in the Akoko region of Ondo State, while the second stage was a random selection of twenty (20) students, each in the selected secondary schools of the study area. This makes a total of two (200) hundred students that were considered for the survey. Descriptive analysis using percentages was employed to analyze the collected data. Factor analysis was also used to identify the most significant problems. Findings: The study revealed that sex education has been neglected in the sampled secondary schools due to traditional African beliefs that do not support the teaching and learning of this subject. Furthermore, there was evidence to suggest that parents also displayed reluctance towards the teaching of sex education, fearing that it might expose students to inappropriate behavior. Consequently, students were deprived of this essential aspect of education necessary for self-awareness and development. Theoretical Importance: This study contributes to the understanding of the challenges faced in teaching sex education in traditional African societies, specifically in the selected secondary schools in the Akoko region of Ondo state, Nigeria. Data Collection: Data were collected through the administration of 200 questionnaires in ten selected secondary schools. Additionally, information was gathered from federal, state, and local government authorities. Analysis Procedures: The collected data were analyzed using descriptive analysis, employing percentage calculations for better interpretation. Furthermore, factor analysis was conducted to isolate the most significant problems identified. Conclusion: The study concludes that sex education in the sampled secondary schools in the Akoko region of Ondo state, Nigeria, has suffered neglect due to traditional African beliefs and parental concerns. Consequently, students are denied an important aspect of education necessary for their self-awareness and development. Recommendations are made to change the negative perception of sex education, enrich the curriculum, and employ qualified personnel for its teaching. Additionally, it is suggested that sex education should be integrated with moral instruction.

Keywords: African traditional belief, sex, sex education, sexual misdemeanor, morality

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6800 Combination between Intrusion Systems and Honeypots

Authors: Majed Sanan, Mohammad Rammal, Wassim Rammal

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Today, security is a major concern. Intrusion Detection, Prevention Systems and Honeypot can be used to moderate attacks. Many researchers have proposed to use many IDSs ((Intrusion Detection System) time to time. Some of these IDS’s combine their features of two or more IDSs which are called Hybrid Intrusion Detection Systems. Most of the researchers combine the features of Signature based detection methodology and Anomaly based detection methodology. For a signature based IDS, if an attacker attacks slowly and in organized way, the attack may go undetected through the IDS, as signatures include factors based on duration of the events but the actions of attacker do not match. Sometimes, for an unknown attack there is no signature updated or an attacker attack in the mean time when the database is updating. Thus, signature-based IDS fail to detect unknown attacks. Anomaly based IDS suffer from many false-positive readings. So there is a need to hybridize those IDS which can overcome the shortcomings of each other. In this paper we propose a new approach to IDS (Intrusion Detection System) which is more efficient than the traditional IDS (Intrusion Detection System). The IDS is based on Honeypot Technology and Anomaly based Detection Methodology. We have designed Architecture for the IDS in a packet tracer and then implemented it in real time. We have discussed experimental results performed: both the Honeypot and Anomaly based IDS have some shortcomings but if we hybridized these two technologies, the newly proposed Hybrid Intrusion Detection System (HIDS) is capable enough to overcome these shortcomings with much enhanced performance. In this paper, we present a modified Hybrid Intrusion Detection System (HIDS) that combines the positive features of two different detection methodologies - Honeypot methodology and anomaly based intrusion detection methodology. In the experiment, we ran both the Intrusion Detection System individually first and then together and recorded the data from time to time. From the data we can conclude that the resulting IDS are much better in detecting intrusions from the existing IDSs.

Keywords: security, intrusion detection, intrusion prevention, honeypot, anomaly-based detection, signature-based detection, cloud computing, kfsensor

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6799 Using Machine Learning Techniques for Autism Spectrum Disorder Analysis and Detection in Children

Authors: Norah Mohammed Alshahrani, Abdulaziz Almaleh

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Autism Spectrum Disorder (ASD) is a condition related to issues with brain development that affects how a person recognises and communicates with others which results in difficulties with interaction and communication socially and it is constantly growing. Early recognition of ASD allows children to lead safe and healthy lives and helps doctors with accurate diagnoses and management of conditions. Therefore, it is crucial to develop a method that will achieve good results and with high accuracy for the measurement of ASD in children. In this paper, ASD datasets of toddlers and children have been analyzed. We employed the following machine learning techniques to attempt to explore ASD and they are Random Forest (RF), Decision Tree (DT), Na¨ıve Bayes (NB) and Support Vector Machine (SVM). Then Feature selection was used to provide fewer attributes from ASD datasets while preserving model performance. As a result, we found that the best result has been provided by the Support Vector Machine (SVM), achieving 0.98% in the toddler dataset and 0.99% in the children dataset.

Keywords: autism spectrum disorder, machine learning, feature selection, support vector machine

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6798 GIS Model for Sanitary Landfill Site Selection Based on Geotechnical Parameters

Authors: Hecson Christian, Joel Macwan

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Landfill site selection in an urban area is a critical issue in the planning process. With the growth of the urbanization, it has a mammoth impact on the economy, ecology, and environmental health of the region. Outsized amount of wastes are produced and the problem gets soared every day. Hence, selection of ideal site for sanitary landfill is a challenge for urban planners and solid waste managers. Disposal site is a function of many parameters. Among all, Geotechnical parameters are very vital as the same is related to surrounding open land. Moreover, the accessible safe and acceptable land is also scarce. Therefore, in this paper geotechnical parameters are used to develop a GIS model to identify an ideal location for landfill purpose. Metropolitan city of Surat is highly populated and fastest growing urban area in India. The research objectives are to conduct field experiments to collect data and to transfer the facts in GIS platform to evolve a model, to find ideal location. Planners’ preferences were obtained to use analytical hierarchical process (AHP) to find weights of each parameter. Integration of GIS and Multi-Criteria Decision Analysis (MCDA) techniques are applied to improve decision-making. It augments an environment for transformation and combination of geographical data and planners’ preferences. GIS performs deterministic overlay and buffer operations. MCDA methods evaluate alternatives based on the decision makers’ subjective values and priorities. Research results have shown many alternative locations. Economic analysis of selected site from actual operations point of view is not included in this research.

Keywords: GIS, AHP, MCDA, Geo-technical

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6797 Using New Machine Algorithms to Classify Iranian Musical Instruments According to Temporal, Spectral and Coefficient Features

Authors: Ronak Khosravi, Mahmood Abbasi Layegh, Siamak Haghipour, Avin Esmaili

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In this paper, a study on classification of musical woodwind instruments using a small set of features selected from a broad range of extracted ones by the sequential forward selection method was carried out. Firstly, we extract 42 features for each record in the music database of 402 sound files belonging to five different groups of Flutes (end blown and internal duct), Single –reed, Double –reed (exposed and capped), Triple reed and Quadruple reed. Then, the sequential forward selection method is adopted to choose the best feature set in order to achieve very high classification accuracy. Two different classification techniques of support vector machines and relevance vector machines have been tested out and an accuracy of up to 96% can be achieved by using 21 time, frequency and coefficient features and relevance vector machine with the Gaussian kernel function.

Keywords: coefficient features, relevance vector machines, spectral features, support vector machines, temporal features

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6796 Optimization of Temperature for Crystal Violet Dye Adsorption Using Castor Leaf Powder by Response Surface Methodology

Authors: Vipan Kumar Sohpal

Abstract:

Temperature effect on the adsorption of crystal violet dye (CVD) was investigated using a castor leaf powder (CLP) that was prepared from the mature leaves of castor trees, through chemical reaction. The optimum values of pH (8), adsorbent dose (10g/L), initial dye concentration (10g/L), time (2hrs), and stirrer speed (120 rpm) were fixed to investigate the influence of temperature on adsorption capacity, percentage of removal of dye and free energy. A central composite design (CCD) was successfully employed for experimental design and analysis of the results. The combined effect of temperature, absorbance, and concentration on the dye adsorption was studied and optimized using response surface methodology. The optimum values of adsorption capacity, percentage of removal of dye and free energy were found to be 0.965(mg/g), 93.38 %, -8202.7(J/mol) at temperature 55.97 °C having desirability > 90% for removal of crystal violet dye respectively. The experimental values were in good agreement with predicted values.

Keywords: crystal violet dye, CVD, castor leaf powder, CLP, response surface methodology, temperature, optimization

Procedia PDF Downloads 113
6795 Creation of a Care Robot Impact Assessment

Authors: Eduard Fosch-Villaronga

Abstract:

This paper pioneers Care Robot Impact Assessment (CRIA), a methodology used to identify, analyze, mitigate and eliminate the risks posed by the insertion of non-medical personal care robots (PCR) in medical care facilities. Its precedent instruments (Privacy and Surveillance Impact Assessment (PIA and SIA)) fall behind in coping with robots. Indeed, personal care robots change dramatically how care is delivered. The paper presents a specific risk-sector methodology, identifies which robots are under its scope and presents some of the challenges introduced by these robots.

Keywords: ethics, impact assessment, law, personal care robots

Procedia PDF Downloads 557
6794 Tandem Concentrated Photovoltaic-Thermoelectric Hybrid System: Feasibility Analysis and Performance Enhancement Through Material Assessment Methodology

Authors: Shuwen Hu, Yuancheng Lou, Dongxu Ji

Abstract:

Photovoltaic (PV) power generation, as one of the most commercialized methods to utilize solar power, can only convert a limited range of solar spectrum into electricity, whereas the majority of the solar energy is dissipated as heat. To address this problem, thermoelectric (TE) module is often integrated with the concentrated PV module for waste heat recovery and regeneration. In this research, a feasibility analysis is conducted for the tandem concentrated photovoltaic-thermoelectric (CPV-TE) hybrid system considering various operational parameters as well as TE material properties. Furthermore, the power output density of the CPV-TE hybrid system is maximized by selecting the optimal TE material with application of a systematic assessment methodology. In the feasibility analysis, CPV-TE is found to be more advantageous than sole CPV system except under high optical concentration ratio with low cold side convective coefficient. It is also shown that the effects of the TE material properties, including Seebeck coefficient, thermal conductivity, and electrical resistivity, on the feasibility of CPV-TE are interacted with each other and might have opposite effect on the system performance under different operational conditions. In addition, the optimal TE material selected by the proposed assessment methodology can improve the system power output density by 227 W/m2 under highly concentrated solar irradiance hence broaden the feasible range of CPV-TE considering optical concentration ratio.

Keywords: feasibility analysis, material assessment methodology, photovoltaic waste heat recovery, tandem photovoltaic-thermoelectric

Procedia PDF Downloads 56
6793 Selection of Intensity Measure in Probabilistic Seismic Risk Assessment of a Turkish Railway Bridge

Authors: M. F. Yilmaz, B. Ö. Çağlayan

Abstract:

Fragility curve is an effective common used tool to determine the earthquake performance of structural and nonstructural components. Also, it is used to determine the nonlinear behavior of bridges. There are many historical bridges in the Turkish railway network; the earthquake performances of these bridges are needed to be investigated. To derive fragility curve Intensity measures (IMs) and Engineering demand parameters (EDP) are needed to be determined. And the relation between IMs and EDP are needed to be derived. In this study, a typical simply supported steel girder riveted railway bridge is studied. Fragility curves of this bridge are derived by two parameters lognormal distribution. Time history analyses are done for selected 60 real earthquake data to determine the relation between IMs and EDP. Moreover, efficiency, practicality, and sufficiency of three different IMs are discussed. PGA, Sa(0.2s) and Sa(1s), the most common used IMs parameters for fragility curve in the literature, are taken into consideration in terms of efficiency, practicality and sufficiency.

Keywords: railway bridges, earthquake performance, fragility analyses, selection of intensity measures

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6792 Performance Measurement by Analytic Hierarchy Process in Performance Based Logistics

Authors: M. Hilmi Ozdemir, Gokhan Ozkan

Abstract:

Performance Based Logistics (PBL) is a strategic approach that enables creating long-term and win-win relations among stakeholders in the acquisition. Contrary to the traditional single transactions, the expected value is created by the performance of the service pertaining to the strategic relationships in this approach. PBL motivates all relevant stakeholders to focus on their core competencies to produce the desired outcome in a collective way. The desired outcome can only be assured with a cost effective way as long as it is periodically measured with the right performance parameters. Thus, defining these parameters is a crucial step for the PBL contracts. In performance parameter determination, Analytic Hierarchy Process (AHP), which is a multi-criteria decision making methodology for complex cases, was used within this study for a complex system. AHP has been extensively applied in various areas including supply chain, inventory management, outsourcing, and logistics. This methodology made it possible to convert end-user’s main operation and maintenance requirements to sub criteria contained by a single performance parameter. Those requirements were categorized and assigned weights by the relevant stakeholders. Single performance parameter capable of measuring the overall performance of a complex system is the major outcome of this study. The parameter deals with the integrated assessment of different functions spanning from training, operation, maintenance, reporting, and documentation that are implemented within a complex system. The aim of this study is to show the methodology and processes implemented to identify a single performance parameter for measuring the whole performance of a complex system within a PBL contract. AHP methodology is recommended as an option for the researches and the practitioners who seek for a lean and integrated approach for performance assessment within PBL contracts. The implementation of AHP methodology in this study may help PBL practitioners from methodological perception and add value to AHP in becoming prevalent.

Keywords: analytic hierarchy process, performance based logistics, performance measurement, performance parameters

Procedia PDF Downloads 268