Search results for: indoor network performance
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16466

Search results for: indoor network performance

14126 To Ensure Maximum Voter Privacy in E-Voting Using Blockchain, Convolutional Neural Network, and Quantum Key Distribution

Authors: Bhaumik Tyagi, Mandeep Kaur, Kanika Singla

Abstract:

The advancement of blockchain has facilitated scholars to remodel e-voting systems for future generations. Server-side attacks like SQL injection attacks and DOS attacks are the most common attacks nowadays, where malicious codes are injected into the system through user input fields by illicit users, which leads to data leakage in the worst scenarios. Besides, quantum attacks are also there which manipulate the transactional data. In order to deal with all the above-mentioned attacks, integration of blockchain, convolutional neural network (CNN), and Quantum Key Distribution is done in this very research. The utilization of blockchain technology in e-voting applications is not a novel concept. But privacy and security issues are still there in a public and private blockchains. To solve this, the use of a hybrid blockchain is done in this research. This research proposed cryptographic signatures and blockchain algorithms to validate the origin and integrity of the votes. The convolutional neural network (CNN), a normalized version of the multilayer perceptron, is also applied in the system to analyze visual descriptions upon registration in a direction to enhance the privacy of voters and the e-voting system. Quantum Key Distribution is being implemented in order to secure a blockchain-based e-voting system from quantum attacks using quantum algorithms. Implementation of e-voting blockchain D-app and providing a proposed solution for the privacy of voters in e-voting using Blockchain, CNN, and Quantum Key Distribution is done.

Keywords: hybrid blockchain, secure e-voting system, convolutional neural networks, quantum key distribution, one-time pad

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14125 MMSE-Based Beamforming for Chip Interleaved CDMA in Aeronautical Mobile Radio Channel

Authors: Sherif K. El Dyasti, Esam A. Hagras, Adel E. El-Hennawy

Abstract:

This paper addresses the performance of antenna array beam-forming on Chip-Interleaved Code Division Multiple Access (CI_CDMA) system based on Minimum Mean Square Error (MMSE) detector in aeronautical mobile radio channel. Multipath fading, Doppler shifts caused by the speed of the aircraft, and Multiple Access Interference (MAI) are the most important reasons that affect and reduce the performance of aeronautical system. In this paper, we suggested the CI-CDMA with antenna array to combat this fading and improve the bit error rate (BER) performance. We further evaluate the performance of the proposed system in the four standard scenarios in aeronautical mobile radio channel.

Keywords: aeronautical channel, CI-CDMA, beamforming, communication, information

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14124 Financial Intermediation: A Transaction Two-Sided Market Model Approach

Authors: Carlo Gozzelino

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Since the early 2000s, the phenomenon of the two-sided markets has been of growing interest in academic literature as such kind of markets differs by having cross-side network effects and same-side network effects characterizing the transactions, which make the analysis different when compared to traditional seller-buyer concept. Due to such externalities, pricing strategies can be based on subsidizing the participation of one side (i.e. considered key for the platform to attract the other side) while recovering the loss on the other side. In recent years, several players of the Italian financial intermediation industry moved from an integrated landscape (i.e. selling their own products) to an open one (i.e. intermediating third party products). According to academic literature such behavior can be interpreted as a merchant move towards a platform, operating in a two-sided market environment. While several application of two-sided market framework are available in academic literature, purpose of this paper is to use a two-sided market concept to suggest a new framework applied to financial intermediation. To this extent, a model is developed to show how competitors behave when vertically integrated and how the peculiarities of a two-sided market act as an incentive to disintegrate. Additionally, we show that when all players act as a platform, the dynamics of a two-sided markets can allow at least a Nash equilibrium to exist, in which platform of different sizes enjoy positive profit. Finally, empirical evidences from Italian market are given to sustain – and to challenge – this interpretation.

Keywords: financial intermediation, network externalities, two-sided markets, vertical differentiation

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14123 Consumption and Diffusion Based Model of Tissue Organoid Development

Authors: Elena Petersen, Inna Kornienko, Svetlana Guryeva, Sergey Simakov

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In vitro organoid cultivation requires the simultaneous provision of necessary vascularization and nutrients perfusion of cells during organoid development. However, many aspects of this problem are still unsolved. The functionality of vascular network intergrowth is limited during early stages of organoid development since a function of the vascular network initiated on final stages of in vitro organoid cultivation. Therefore, a microchannel network should be created in early stages of organoid cultivation in hydrogel matrix aimed to conduct and maintain minimally required the level of nutrients perfusion for all cells in the expanding organoid. The network configuration should be designed properly in order to exclude hypoxic and necrotic zones in expanding organoid at all stages of its cultivation. In vitro vascularization is currently the main issue within the field of tissue engineering. As perfusion and oxygen transport have direct effects on cell viability and differentiation, researchers are currently limited only to tissues of few millimeters in thickness. These limitations are imposed by mass transfer and are defined by the balance between the metabolic demand of the cellular components in the system and the size of the scaffold. Current approaches include growth factor delivery, channeled scaffolds, perfusion bioreactors, microfluidics, cell co-cultures, cell functionalization, modular assembly, and in vivo systems. These approaches may improve cell viability or generate capillary-like structures within a tissue construct. Thus, there is a fundamental disconnect between defining the metabolic needs of tissue through quantitative measurements of oxygen and nutrient diffusion and the potential ease of integration into host vasculature for future in vivo implantation. A model is proposed for growth prognosis of the organoid perfusion based on joint simulations of general nutrient diffusion, nutrient diffusion to the hydrogel matrix through the contact surfaces and microchannels walls, nutrient consumption by the cells of expanding organoid, including biomatrix contraction during tissue development, which is associated with changed consumption rate of growing organoid cells. The model allows computing effective microchannel network design giving minimally required the level of nutrients concentration in all parts of growing organoid. It can be used for preliminary planning of microchannel network design and simulations of nutrients supply rate depending on the stage of organoid development.

Keywords: 3D model, consumption model, diffusion, spheroid, tissue organoid

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14122 Performance Evaluation of Lithium Bromide Absorption Chiller

Authors: Z. Neffah, L. Merabti, N. Hatraf

Abstract:

Absorption refrigeration technology has been used for cooling purposes over a hundred years. Today, the technology developments have made of the absorption refrigeration an economic and effective alternative to the vapour compression cooling cycle. A parametric study was conducted over the entire admissible ranges of the generator and absorber temperatures. On the other hand, simultaneously raising absorber temperatures was seen to result in deterioration of coefficient of performance. The influence of generator, absorber temperatures, as well as solution concentration on the different performance indicators was also calculated and examined.

Keywords: absorption system, Aqueous solution, chiller, water-lithium bromide

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14121 Performance, Scalability and Reliability Engineering: Shift Left and Shift Right Approach

Authors: Jyothirmayee Pola

Abstract:

Ideally, a test-driven development (TDD) or agile or any other process should be able to define and implement performance, scalability, and reliability (PSR) of the product with a higher quality of service (QOS) and should have the ability to fix any PSR issues with lesser cost before it hits the production. Most PSR test strategies for new product introduction (NPI) include assumptions about production load requirements but never accurate. NPE (New product Enhancement) include assumptions for new features that are being developed whilst workload distribution for older features can be derived by analyzing production transactions. This paper talks about how to shift left PSR towards design phase of release management process to get better QOS w.r.t PSR for any product under development. It also explains the ROI for future customer onboarding both for Service Oriented Architectures (SOA) and Microservices architectures and how to define PSR requirements.

Keywords: component PSR, performance engineering, performance tuning, reliability, return on investment, scalability, system PSR

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14120 Investigation of Physical Performance of Denim Fabrics Washed with Sustainable Foam Washing Process

Authors: Hazal Yılmaz, Hale Karakaş

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In the scope of the study, it is aimed to investigate and review the performance of denim fabrics that are foam washed. Foam washing was compared as an alternative to stone washing in terms of sustainability and performance parameters. For this purpose, seven different denim fabrics, which are both stone washed and foam washed separately in 3 different washing durations (30-60-90 mins), were compared. In the study, the same fabrics were processed with both foam and stone separately. The washing process steps were reviewed, and their water consumption values were compared. After washing, a total of 42 fabric samples were obtained, and tensile strength, tear strength, abrasion, weight loss after abrasion, rubbing fastness, color fastness tests were carried out on the fabric samples. The obtained test results were reviewed and evaluated. As a result of tests, it has been observed that the performance of foam washed fabrics in terms of tensile, tear strength and rubbing fastness test results are better than stone washed fabrics, and it has been seen that foam washed fabrics' color fastness test results are as stone washed. As a result of all these tests, it can be seen that foam washing is an alternative to stone washing due to its performance parameters and its sustainability performance with less water usage.

Keywords: denim fabrics, denim washing, foam washing, performance properties, stone washing, sustainability

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14119 Research on the Feasibility of Evaluating Low-Temperature Cracking Performance of Asphalt Mixture Using Fracture Energy

Authors: Tao Yang, Yongli Zhao

Abstract:

Low-temperature cracking is one of the major challenges for asphalt pavement in the cold region. Fracture energy could determine from various test methods, which is a commonly used parameter to evaluate the low-temperature cracking resistance of asphalt mixture. However, the feasibility of evaluating the low-temperature cracking performance of asphalt mixture using fracture energy is not investigated comprehensively. This paper aims to verify whether fracture energy is an appropriate parameter to evaluate the low-temperature cracking performance. To achieve this goal, this paper compared the test results of thermal stress restrained specimen test (TSRST) and semi-circular bending test (SCB) of asphalt mixture with different types of aggregate, TSRST and indirect tensile test (IDT) of asphalt mixture with different additives, and single-edge notched beam test (SENB) and TSRST of asphalt mixture with different asphalt. Finally, the correlation between in-suit cracking performance and fracture energy was surveyed. The experimental results showed the evaluation result of critical cracking temperature and fracture energy are not always consistent; the in-suit cracking performance is also not correlated well with fracture energy. These results indicated that it is not feasible to evaluate low-temperature performance by fracture energy. Then, the composition of fracture energy of TSRST, SCB, disk-shaped compact tension test (DCT), three-point bending test (3PB) and IDT was analyzed. The result showed: the area of thermal stress versus temperature curve is the multiple of fracture energy and could be used to represent fracture energy of TSRST, as the multiple is nearly equal among different asphalt mixtures for a specific specimen; the fracture energy, determined from TSRST, SCB, DCT, 3PB, SENB and IDT, is mainly the surface energy that forms the fracture face; fracture energy is inappropriate to evaluate the low-temperature cracking performance of asphalt mixture, as the relaxation/viscous performance is not considered; if the fracture energy was used, it is recommended to combine this parameter with an index characterizing the relaxation or creep performance of asphalt mixture.

Keywords: asphalt pavement, cold region, critical cracking temperature, fracture energy, low-temperature cracking

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14118 Algorithm and Software Based on Multilayer Perceptron Neural Networks for Estimating Channel Use in the Spectral Decision Stage in Cognitive Radio Networks

Authors: Danilo López, Johana Hernández, Edwin Rivas

Abstract:

The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Keywords: cognitive radio, neural network, prediction, primary user

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14117 Factors Impacting Training and Adult Education Providers’ Business Performance: The Singapore Context

Authors: Zan Chen, D. Kwok

Abstract:

The SkillsFuture Singapore’s mission to develop a responsive and forward-looking Training and Adult Education (TAE) and workforce development system is undergirded by how successful TAE providers are in their business performance and strategies that strengthen their operational efficiency and processes. Therefore, understanding the factors that drive the business performance of TAE providers is critical to the success of SkillsFuture Singapore’s initiatives. This study aims to investigate how business strategy, work autonomy, work intensity and professional development support impact the business performance of private TAE providers. Specifically, the three research questions are: (1) Are there significant relationships between the above-mentioned four factors and TAE providers’ business performance?; (2) Are there significant differences on the four factors between low and high TAE providers’ business performance groups?; and (3) To what extent and in what manner do the four factors predict TAE providers’ business performance? This was part of the first national study on organizations and professionals working in the Training and Adult Education (TAE) sector. Data from 265 private TAE providers where respondents were Chief Executive Officers representatives from the Senior Management were analyzed. The results showed that business strategy (the extent that the organization leads the way in terms of developing new products and services; uses up-to-date learning technologies; customizes its products and services to the client’s needs), work autonomy (the extent that the staff personally have an influence on how hard they work; deciding what tasks they are to do; deciding how they are to do the tasks, and deciding the quality standards to which they work) and professional development support (both monetary and non-monetary support and incentives) had positive and significant relationships with business performance. However, no significant relationship is found between work intensity and business performance. A business strategy, work autonomy and professional development support were significantly higher in the high business performance group compared to the low-performance group among the TAE providers. Results of hierarchical regression analyses controlling for the size of the TAE providers showed significant impacts of business strategy, work autonomy and professional development support on TAE providers’ business performance. Overall, the model accounted for 27% of the variance in TAE providers’ business performance. This study provides policymakers with insights into improving existing policies, designing new initiatives and implementing targeting interventions to support TAE providers. The findings also have implications on how the TAE providers could better formulate their organizational strategies and business models. Finally, limitations of study, along with directions for future research will be discussed in the paper.

Keywords: adult education, business performance, business strategy, training, work autonomy

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14116 Self-Efficacy and Attitude of the Graduating Pre-Service Teachers as Influenced in Their Student Teaching Performance

Authors: Sonia Arradaza-Pajaron, Maria Aida Manila

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Teaching is considered the noblest yet believed to be one of the most complicated and challenging professions. Along this view, every teacher-producing institution should look into producing quality pre-service graduates who are efficacious enough with the right attitude and to deal with the task accorded to them. This study investigated the association between self-efficacy and attitude of graduating pre-service teachers with their actual student teaching performance. Survey questionnaires on self-efficacy and attitude toward practice teaching were fielded to the 90 actual respondents while their practice teaching grade was extracted to serve as the other main variable. Data were analyzed and treated statistically utilizing weighted mean and Pearson r to determine the relationship of variables of the study. Findings revealed that attitude of respondents of the three curricular programs was favorable, and they are self-efficacious. Their practice teaching performance was interpreted as very good. Results further showed a significant positive relationship between their self-efficacy and practice teaching performance. It showed that their rating was a manifestation of self- efficacious group. Although they exude positive attitude towards practice teaching, yet no significant relationship was seen with their attitude and performance. Moreover, data manifested that most of them can pay attention during their conduct of lessons in the class, as well as, listen attentively to their cooperating teachers during post conferences. They can perform student teaching tasks better even when there were other interesting things to do. Most of all, they can regulate or suppress not so pleasant thoughts or feelings and take things lightly even in most challenging situations. As gleaned from the results, it can be concluded that there was an association between self-efficacy and practice teaching performance of the respondents.

Keywords: academic achievement, attitude, self-efficacy, student teaching performance

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14115 Thermodynamic Performance Tests for 3D Printed Steel Slag Powder Concrete Walls

Authors: Li Guoyou, Zhang Tao, Ji Wenzhan, Huo Liang, Lin Xiqiang, Zhang Nan

Abstract:

The three dimensional (3D) printing technology has undergone rapid development in the last few years and it is possible to print engineering structures. 3D printing buildings use wastes from constructions, industries and mine tailings as “ink”, and mix it with property improved materials, such as cement, fiber etc. This paper presents a study of the Thermodynamic performance of 3D printed walls using cement and steel slag powder. Analyses the thermal simulation regarding 3D printed walls and solid brick wall by the way of the hot-box methods and the infrared technology, and the results were contrasted with theoretical calculation. The results show that the excellent thermodynamic performance of 3D printed concrete wall made it suitable as the partial materials for self-thermal insulation walls in residential buildings. The thermodynamic performance of 3D printed concrete walls depended on the density of materials, distribution of holes, and the filling materials. Decreasing the density of materials, increasing the number of holes or replacing the filling materials with foamed concrete could improve its thermodynamic performance significantly. The average of heat transfer coefficient and thermal inertia index of 3D printed steel slag powder concrete wall all better than the traditional solid brick wall with a thickness of 240mm.

Keywords: concrete, 3D printed walls, thermodynamic performance, steel slag powder

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14114 Needs Analysis Survey of Hearing Impaired Students’ Teachers in Elementary Schools for Designing Curriculum Plans and Improving Human Resources

Authors: F. Rashno Seydari, M. Nikafrooz

Abstract:

This paper intends to study needs analysis of hearing-impaired students’ teachers in elementary schools all over Iran. The subjects of this study were 275 teachers who were teaching hearing-impaired students in elementary schools. The participants were selected by a quota sampling method. To collect the data, questionnaires of training needs consisting of 41 knowledge items and 31 performance items were used. The collected data were analyzed by using SPSS software in the form of descriptive analyses (frequency and mean) and inferential analyses (one sample t-test, paired t-test, independent t-test, and Pearson correlation coefficient). The findings of the study indicated that teachers generally have considerable needs in knowledge and performance domains. In 32 items out of the total 41 knowledge domain items and in the 27 items out of the total 31 performance domain items, the teachers had considerable needs. From the quantitative point of view, the needs of the performance domain were more than those of the knowledge domain, so they have to be considered as the first priority in training these teachers. There was no difference between the level of the needs of male and female teachers. There was a significant difference between the knowledge and performance domain needs and the teachers’ teaching experience, 0.354 and 0.322 respectively. The teachers who had been trained in working with hearing-impaired students expressed more training needs (both knowledge and performance).

Keywords: educational needs analysis, teachers of hearing impaired students, knowledge domain, function domain

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14113 Constrained RGBD SLAM with a Prior Knowledge of the Environment

Authors: Kathia Melbouci, Sylvie Naudet Collette, Vincent Gay-Bellile, Omar Ait-Aider, Michel Dhome

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In this paper, we handle the problem of real time localization and mapping in indoor environment assisted by a partial prior 3D model, using an RGBD sensor. The proposed solution relies on a feature-based RGBD SLAM algorithm to localize the camera and update the 3D map of the scene. To improve the accuracy and the robustness of the localization, we propose to combine in a local bundle adjustment process, geometric information provided by a prior coarse 3D model of the scene (e.g. generated from the 2D floor plan of the building) along with RGBD data from a Kinect camera. The proposed approach is evaluated on a public benchmark dataset as well as on real scene acquired by a Kinect sensor.

Keywords: SLAM, global localization, 3D sensor, bundle adjustment, 3D model

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14112 Static and Dynamic Hand Gesture Recognition Using Convolutional Neural Network Models

Authors: Keyi Wang

Abstract:

Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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14111 Effect of Three Resistance Training Methods on Performance-Related Variables of Powerlifters

Authors: K. Shyamnath, K. Suresh Kutty

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The purpose of the study was to find out the effect of three resistance training methods on performance-related variables of powerlifters. A total of forty male students (N=40) who had participated in Kannur University powerlifting championship were selected as subjects. The age group of the subjects ranged from 18 years old to 25 years old. The selected subjects were equally divided into four groups (n=10) of three experimental groups and a control group. The experimental Group I underwent traditional resistance training (TRTG), Group II underwent combined traditional resistance training and plyometrics (TRTPG), and Group III underwent combined traditional resistance training and resistance training with high rhythm (TRTHRG). Group IV acted as the control group (CG) receiving no training during the experimental period. The duration of the experimental period was sixteen weeks, five days per week. Powerlifting performance was assessed by the 1RM test in the squat, bench press and deadlift. Performance-related variables assessed were chest girth, arm girth, forearm girth, thigh girth, and calf girth. Pre-test and post-test were conducted a day before and two days after the experimental period on all groups. Analysis of covariance (ANCOVA) was applied to analyze the significant difference. The 0.05 level of confidence was fixed as the level of significance to test the F ratio obtained by the analysis of covariance. The result indicates that there is a significant effect of all the selected resistance training methods on the performance and selected performance-related variables of powerlifters. Combined traditional resistance training and plyometrics and combined traditional resistance training and resistance training with high rhythm proved better than the traditional resistance training in improving performance and selected performance-related variables of powerlifters. There was no significant difference between combined traditional resistance training and plyometrics and combined traditional resistance training and resistance training with high rhythm in improving performance and selected performance-related variables of powerlifters.

Keywords: girth, plyometrics, powerlifting, resistance training

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14110 Economized Sensor Data Processing with Vehicle Platooning

Authors: Henry Hexmoor, Kailash Yelasani

Abstract:

We present vehicular platooning as a special case of crowd-sensing framework where sharing sensory information among a crowd is used for their collective benefit. After offering an abstract policy that governs processes involving a vehicular platoon, we review several common scenarios and components surrounding vehicular platooning. We then present a simulated prototype that illustrates efficiency of road usage and vehicle travel time derived from platooning. We have argued that one of the paramount benefits of platooning that is overlooked elsewhere, is the substantial computational savings (i.e., economizing benefits) in acquisition and processing of sensory data among vehicles sharing the road. The most capable vehicle can share data gathered from its sensors with nearby vehicles grouped into a platoon.

Keywords: cloud network, collaboration, internet of things, social network

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14109 Comparative Analysis of Teachers’ Performance in Private and Public Primary Schools in Oyo State

Authors: Babajide Solomon Faloore

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This study on the comparative analysis of the performance of teachers in private and public schools was carried out in Ibadan North West Local Government Area of Oyo State. This study examined the justification for the claim that there is a difference in the performance of teachers in private and public primary schools and at the same time identified factors responsible for the difference in the performance of these teachers. A descriptive survey research design was used for the study. Data generated were analyzed using t-test and regression analysis. The findings of the study revealed that there is significance difference in the performance of teachers in private and private primary schools in Ibadan North West Local Government Area of Oyo State( t=64.09; df=459; p,.05). The findings also revealed that the method of teaching in private primary schools is significantly different from the method of teaching in public primary schools in Ibadan North West Local Government Area of Oyo State (t=73.08; df=459; p,.05). Findings revealed that school leadership and management have a significant contribution on the performance of private and public primary school teachers in Ibadan North West Local Area of Oyo State. Based on the finding, the following recommendations were made: Primary school teachers need to be motivated and rewarded for excellent performance. Primary schools should be properly equipped with teaching–aid facilities, laboratories, and libraries. The government should use the findings of this study to improve on teaching materials provided to the primary school teachers in Nigeria. Public primary schools should be designed by education planners, administrators, and government. Headmasters, proprietors, and teachers of primary schools should look inward and give a performance appraisal and evaluation of themselves from time to time based on the subject they taught. Finally, school administrators should be conscious of the way they manage the teachers in schools not only in informal situations but also in formal settings.

Keywords: private education, public education, school leadership, school management, teachers performance

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14108 Parameters Influencing Human Machine Interaction in Hospitals

Authors: Hind Bouami

Abstract:

Handling life-critical systems complexity requires to be equipped with appropriate technology and the right human agents’ functions such as knowledge, experience, and competence in problem’s prevention and solving. Human agents are involved in the management and control of human-machine system’s performance. Documenting human agent’s situation awareness is crucial to support human-machine designers’ decision-making. Knowledge about risks, critical parameters and factors that can impact and threaten automation system’s performance should be collected using preventive and retrospective approaches. This paper aims to document operators’ situation awareness through the analysis of automated organizations’ feedback. The analysis of automated hospital pharmacies feedbacks helps to identify and control critical parameters influencing human machine interaction in order to enhance system’s performance and security. Our human machine system evaluation approach has been deployed in Macon hospital center’s pharmacy which is equipped with automated drug dispensing systems since 2015. Automation’s specifications are related to technical aspects, human-machine interaction, and human aspects. The evaluation of drug delivery automation performance in Macon hospital center has shown that the performance of the automated activity depends on the performance of the automated solution chosen, and also on the control of systemic factors. In fact, 80.95% of automation specification related to the chosen Sinteco’s automated solution is met. The performance of the chosen automated solution is involved in 28.38% of automation specifications performance in Macon hospital center. The remaining systemic parameters involved in automation specifications performance need to be controlled.

Keywords: life-critical systems, situation awareness, human-machine interaction, decision-making

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14107 GAILoc: Improving Fingerprinting-Based Localization System Using Generative Artificial Intelligence

Authors: Getaneh Berie Tarekegn

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A precise localization system is crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. The most common method for providing continuous positioning services in outdoor environments is by using a global navigation satellite system (GNSS). Due to nonline-of-sight, multipath, and weather conditions, GNSS systems do not perform well in dense urban, urban, and suburban areas.This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 39 cm, and more than 90% of the errors are less than 82 cm. That is, numerical results proved that, in comparison to traditional methods, the proposed SRCLoc method can significantly improve positioning performance and reduce radio map construction costs.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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14106 Reliability Verification of the Performance Evaluation of Multiphase Pump

Authors: Joon-Hyung Kim, Him-Chan Lee, Jin-Hyuk Kim, Yong-Kab Lee, Young-Seok Choi

Abstract:

The crude oil in an oil well exists in various phases such as gas, seawater, and sand, as well as oil. Therefore, a phase separator is needed at the front of a single-phase pump for pressurization and transfer. On the other hand, the application of a multiphase pump can provide such advantages as simplification of the equipment structure and cost savings, because there is no need for a phase separation process. Therefore, the crude oil transfer method using a multiphase pump is being applied to recently developed oil wells. Due to this increase in demand, technical demands for the development of multiphase pumps are sharply increasing, but the progress of research into related technologies is insufficient, due to the nature of multiphase pumps that require high levels of skills. This study was conducted to verify the reliability of pump performance evaluation using numerical analysis, which is the basis of the development of a multiphase pump. For this study, a model was designed by selecting the specifications of the pump under study. The performance of the designed model was evaluated through numerical analysis and experiment, and the results of the performance evaluation were compared to verify the reliability of the result using numerical analysis.

Keywords: multiphase pump, numerical analysis, experiment, performance evaluation, reliability verification

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14105 The Importance of Training in Supply Chain Management on Personnel Differentiation and Business Performance

Authors: Arawati Agus, Rahmah Ismail

Abstract:

An effective training has been increasingly recognized as critical factors in enhancing the skills and knowledge of employee or personnel in the organization. More and more manufacturing companies in Malaysia are increasingly incorporating training as an important element in supply chain management (SCM) to improve their employee skills and knowledge and ultimately organizational performances. In order to understand the connection of training in SCM and the performance of an organization, this paper considers of many arguments from various research papers. This paper presents the findings of a research which examines the relationship between training in SCM, personnel differentiation and business performance of manufacturing companies in Malaysia. The study measures perception of senior management regarding the incorporation of training in SCM and the level of personnel differentiation and business performance measurements in their companies. The associations between training in SCM, personnel differentiation and business performance dimensions are analyzed through methods such as Pearson’s correlations and Smart partial least squares (smart PLS) using 126 respondents’ data. The correlation results demonstrate that training in SCM has significant correlations with personnel differentiation determinants (comprises of variables namely employee differentiation and service differentiation). The findings also suggest that training in SCM has significant correlations with business performance determinants (comprises of indicators, namely market share, profitability, ROA and ROS). Specifically, both personnel differentiation and business performance have high correlations with training in SCM, namely ‘Employee training on production skills’, ‘On the job production employee training’ and ‘Management training on supply chain effectiveness’ and ‘Employee training on supply chain technologies’. The smart PLS result also reveals that training in SCM exhibits significant impact on both personnel differentiation (directly) and business performance (indirectly mediated by personnel differentiation). The findings of the study provide a demonstration of the importance of training in SCM in enhancing competitive performances in Malaysian manufacturing companies.

Keywords: training in SCM, personnel differentiation, business performance, Pearson’s correlation, Smart PLS

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14104 A Comparison between Fuzzy Analytic Hierarchy Process and Fuzzy Analytic Network Process for Rationality Evaluation of Land Use Planning Locations in Vietnam

Authors: X. L. Nguyen, T. Y. Chou, F. Y. Min, F. C. Lin, T. V. Hoang, Y. M. Huang

Abstract:

In Vietnam, land use planning is utilized as an efficient tool for the local government to adjust land use. However, planned locations are facing disapproval from people who live near these planned sites because of environmental problems. The selection of these locations is normally based on the subjective opinion of decision-makers and is not supported by any scientific methods. Many researchers have applied Multi-Criteria Analysis (MCA) methods in which Analytic Hierarchy Process (AHP) is the most popular techniques in combination with Fuzzy set theory for the subject of rationality assessment of land use planning locations. In this research, the Fuzzy set theory and Analytic Network Process (ANP) multi-criteria-based technique were used for the assessment process. The Fuzzy Analytic Hierarchy Process was also utilized, and the output results from two methods were compared to extract the differences. The 20 planned landfills in Hung Ha district, Thai Binh province, Vietnam was selected as a case study. The comparison results indicate that there are different between weights computed by AHP and ANP methods and the assessment outputs produced from these two methods also slight differences. After evaluation of existing planned sites, some potential locations were suggested to the local government for possibility of land use planning adjusts.

Keywords: Analytic Hierarchy Process, Analytic Network Process, Fuzzy set theory, land use planning

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14103 Intrusion Detection in SCADA Systems

Authors: Leandros A. Maglaras, Jianmin Jiang

Abstract:

The protection of the national infrastructures from cyberattacks is one of the main issues for national and international security. The funded European Framework-7 (FP7) research project CockpitCI introduces intelligent intrusion detection, analysis and protection techniques for Critical Infrastructures (CI). The paradox is that CIs massively rely on the newest interconnected and vulnerable Information and Communication Technology (ICT), whilst the control equipment, legacy software/hardware, is typically old. Such a combination of factors may lead to very dangerous situations, exposing systems to a wide variety of attacks. To overcome such threats, the CockpitCI project combines machine learning techniques with ICT technologies to produce advanced intrusion detection, analysis and reaction tools to provide intelligence to field equipment. This will allow the field equipment to perform local decisions in order to self-identify and self-react to abnormal situations introduced by cyberattacks. In this paper, an intrusion detection module capable of detecting malicious network traffic in a Supervisory Control and Data Acquisition (SCADA) system is presented. Malicious data in a SCADA system disrupt its correct functioning and tamper with its normal operation. OCSVM is an intrusion detection mechanism that does not need any labeled data for training or any information about the kind of anomaly is expecting for the detection process. This feature makes it ideal for processing SCADA environment data and automates SCADA performance monitoring. The OCSVM module developed is trained by network traces off line and detects anomalies in the system real time. The module is part of an IDS (intrusion detection system) developed under CockpitCI project and communicates with the other parts of the system by the exchange of IDMEF messages that carry information about the source of the incident, the time and a classification of the alarm.

Keywords: cyber-security, SCADA systems, OCSVM, intrusion detection

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14102 Parameter Selection for Computationally Efficient Use of the Bfvrns Fully Homomorphic Encryption Scheme

Authors: Cavidan Yakupoglu, Kurt Rohloff

Abstract:

In this study, we aim to provide a novel parameter selection model for the BFVrns scheme, which is one of the prominent FHE schemes. Parameter selection in lattice-based FHE schemes is a practical challenges for experts or non-experts. Towards a solution to this problem, we introduce a hybrid principles-based approach that combines theoretical with experimental analyses. To begin, we use regression analysis to examine the parameters on the performance and security. The fact that the FHE parameters induce different behaviors on performance, security and Ciphertext Expansion Factor (CEF) that makes the process of parameter selection more challenging. To address this issue, We use a multi-objective optimization algorithm to select the optimum parameter set for performance, CEF and security at the same time. As a result of this optimization, we get an improved parameter set for better performance at a given security level by ensuring correctness and security against lattice attacks by providing at least 128-bit security. Our result enables average ~ 5x smaller CEF and mostly better performance in comparison to the parameter sets given in [1]. This approach can be considered a semiautomated parameter selection. These studies are conducted using the PALISADE homomorphic encryption library, which is a well-known HE library. The abstract goes here.

Keywords: lattice cryptography, fully homomorphic encryption, parameter selection, LWE, RLWE

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14101 Unsupervised Images Generation Based on Sloan Digital Sky Survey with Deep Convolutional Generative Neural Networks

Authors: Guanghua Zhang, Fubao Wang, Weijun Duan

Abstract:

Convolution neural network (CNN) has attracted more and more attention on recent years. Especially in the field of computer vision and image classification. However, unsupervised learning with CNN has received less attention than supervised learning. In this work, we use a new powerful tool which is deep convolutional generative adversarial networks (DCGANs) to generate images from Sloan Digital Sky Survey. Training by various star and galaxy images, it shows that both the generator and the discriminator are good for unsupervised learning. In this paper, we also took several experiments to choose the best value for hyper-parameters and which could help to stabilize the training process and promise a good quality of the output.

Keywords: convolution neural network, discriminator, generator, unsupervised learning

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14100 Subjective Well-Being, Emotional Regulation and Motivational Orientation of Competition Athletes

Authors: Cristina Costa-Lobo, Priscila Martins, Silvia Amado Cordeiro, Ana Campina

Abstract:

Behavior directed toward high levels of sports performance and excellence implies task-focused processes, processes of cognitive and emotional regulation. This research aims to understand if subjective well-being, emotional regulation, and motivational orientation influence the performance of competitive athletes. The sample of this study is a non-probabilistic convenience sample, consisting of 50 male athletes, aged 14 to 15 years, who belong to training teams integrated in the pedagogical department of a sports club in the North of Portugal. In terms of performance, the distinction between team A and team B is due to the championships in which the respective athletes participate. Team A participates in national championships where the levels of demand and challenge are more pronounced and the team B only participates in championships at the district level. Was verified the internal consistency of the subjective happiness scale, the emotional regulation scale, and the motivational orientation questionnaire. SPSS, version 22.0, was used in the data treatment. When comparing the dimensions of emotional regulation with performance, it can be seen that athletes with lower sports scores have higher levels of emotional control and emotional self-awareness. As far as situational responsiveness is concerned, only the emotional self-control dimension and the emotional self-awareness dimension show an influence on the income, although, contrary to what would be expected, they appear to be associated with lower incomes. When comparing the motivational orientation with the athletic performance, it is verified that the athletes with the highest performance present an ego-oriented motivation, evidencing the athletes with a lower performance athletic tendency towards the task orientation. Only the ego-oriented dimension seems to be associated with high sport performance. The motivational orientation for the ego and the dimensions emotional control and emotional self-awareness are presented in this study as having influence on sports performance. Following these studies that have shown concern with the characterization of the best athletes and the promotion of higher sports performances, this work contributes to the signaling of psychological variables associated with high sports income.

Keywords: subjective well-being, emotional regulation, motivational orientation, sports performance

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14099 Adhesion Performance According to Lateral Reinforcement Method of Textile

Authors: Jungbhin You, Taekyun Kim, Jongho Park, Sungnam Hong, Sun-Kyu Park

Abstract:

Reinforced concrete has been mainly used in construction field because of excellent durability. However, it may lead to reduction of durability and safety due to corrosion of reinforcement steels according to damage of concrete surface. Recently, research of textile is ongoing to complement weakness of reinforced concrete. In previous research, only experiment of longitudinal length were performed. Therefore, in order to investigate the adhesion performance according to the lattice shape and the embedded length, the pull-out test was performed on the roving with parameter of the number of lateral reinforcement, the lateral reinforcement length and the lateral reinforcement spacing. As a result, the number of lateral reinforcement and the lateral reinforcement length did not significantly affect the load variation depending on the adhesion performance, and only the load analysis results according to the reinforcement spacing are affected.

Keywords: adhesion performance, lateral reinforcement, pull-out test, textile

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14098 Modified RSA in Mobile Communication

Authors: Nagaratna Rajur, J. D. Mallapur, Y. B. Kirankumar

Abstract:

The security in mobile communication is very different from the internet or telecommunication, because of its poor user interface and limited processing capacity, as well as combination of complex network protocols. Hence, it poses a challenge for less memory usage and low computation speed based security system. Security involves all the activities that are undertaken to protect the value and on-going usability of assets and the integrity and continuity of operations. An effective network security strategies requires identifying threats and then choosing the most effective set of tools to combat them. Cryptography is a simple and efficient way to provide security in communication. RSA is an asymmetric key approach that is highly reliable and widely used in internet communication. However, it has not been efficiently implemented in mobile communication due its computational complexity and large memory utilization. The proposed algorithm modifies the current RSA to be useful in mobile communication by reducing its computational complexity and memory utilization.

Keywords: M-RSA, sensor networks, sensor applications, security

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14097 Advantages of Neural Network Based Air Data Estimation for Unmanned Aerial Vehicles

Authors: Angelo Lerro, Manuela Battipede, Piero Gili, Alberto Brandl

Abstract:

Redundancy requirements for UAV (Unmanned Aerial Vehicle) are hardly faced due to the generally restricted amount of available space and allowable weight for the aircraft systems, limiting their exploitation. Essential equipment as the Air Data, Attitude and Heading Reference Systems (ADAHRS) require several external probes to measure significant data as the Angle of Attack or the Sideslip Angle. Previous research focused on the analysis of a patented technology named Smart-ADAHRS (Smart Air Data, Attitude and Heading Reference System) as an alternative method to obtain reliable and accurate estimates of the aerodynamic angles. This solution is based on an innovative sensor fusion algorithm implementing soft computing techniques and it allows to obtain a simplified inertial and air data system reducing external devices. In fact, only one external source of dynamic and static pressures is needed. This paper focuses on the benefits which would be gained by the implementation of this system in UAV applications. A simplification of the entire ADAHRS architecture will bring to reduce the overall cost together with improved safety performance. Smart-ADAHRS has currently reached Technology Readiness Level (TRL) 6. Real flight tests took place on ultralight aircraft equipped with a suitable Flight Test Instrumentation (FTI). The output of the algorithm using the flight test measurements demonstrates the capability for this fusion algorithm to embed in a single device multiple physical and virtual sensors. Any source of dynamic and static pressure can be integrated with this system gaining a significant improvement in terms of versatility.

Keywords: aerodynamic angles, air data system, flight test, neural network, unmanned aerial vehicle, virtual sensor

Procedia PDF Downloads 209