Search results for: Developmentally responsive learning environments
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2577

Search results for: Developmentally responsive learning environments

1137 An Agent-Based Scheduling Framework for Flexible Manufacturing Systems

Authors: Iman Badr

Abstract:

The concept of flexible manufacturing is highly appealing in gaining a competitive edge in the market by quickly adapting to the changing customer needs. Scheduling jobs on flexible manufacturing systems (FMSs) is a challenging task of managing the available flexibility on the shop floor to react to the dynamics of the environment in real-time. In this paper, an agent-oriented scheduling framework that can be integrated with a real or a simulated FMS is proposed. This framework works in stochastic environments with a dynamic model of job arrival. It supports a hierarchical cooperative scheduling that builds on the available flexibility of the shop floor. Testing the framework on a model of a real FMS showed the capability of the proposed approach to overcome the drawbacks of the conventional approaches and maintain a near optimal solution despite the dynamics of the operational environment.

Keywords: Autonomous agents, Flexible manufacturing systems(FMS), Manufacturing scheduling, Real-time systems.

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1136 A Review and Comparative Analysis on Cluster Ensemble Methods

Authors: S. Sarumathi, P. Ranjetha, C. Saraswathy, M. Vaishnavi, S. Geetha

Abstract:

Clustering is an unsupervised learning technique for aggregating data objects into meaningful classes so that intra cluster similarity is maximized and inter cluster similarity is minimized in data mining. However, no single clustering algorithm proves to be the most effective in producing the best result. As a result, a new challenging technique known as the cluster ensemble approach has blossomed in order to determine the solution to this problem. For the cluster analysis issue, this new technique is a successful approach. The cluster ensemble's main goal is to combine similar clustering solutions in a way that achieves the precision while also improving the quality of individual data clustering. Because of the massive and rapid creation of new approaches in the field of data mining, the ongoing interest in inventing novel algorithms necessitates a thorough examination of current techniques and future innovation. This paper presents a comparative analysis of various cluster ensemble approaches, including their methodologies, formal working process, and standard accuracy and error rates. As a result, the society of clustering practitioners will benefit from this exploratory and clear research, which will aid in determining the most appropriate solution to the problem at hand.

Keywords: Clustering, cluster ensemble methods, consensus function, data mining, unsupervised learning.

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1135 Dynamic Load Balancing Strategy for Grid Computing

Authors: Belabbas Yagoubi, Yahya Slimani

Abstract:

Workload and resource management are two essential functions provided at the service level of the grid software infrastructure. To improve the global throughput of these software environments, workloads have to be evenly scheduled among the available resources. To realize this goal several load balancing strategies and algorithms have been proposed. Most strategies were developed in mind, assuming homogeneous set of sites linked with homogeneous and fast networks. However for computational grids we must address main new issues, namely: heterogeneity, scalability and adaptability. In this paper, we propose a layered algorithm which achieve dynamic load balancing in grid computing. Based on a tree model, our algorithm presents the following main features: (i) it is layered; (ii) it supports heterogeneity and scalability; and, (iii) it is totally independent from any physical architecture of a grid.

Keywords: Grid computing, load balancing, workload, tree based model.

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1134 Adaptation Learning Speed Control for a High- Performance Induction Motor using Neural Networks

Authors: M. Zerikat, S. Chekroun

Abstract:

This paper proposes an effective adaptation learning algorithm based on artificial neural networks for speed control of an induction motor assumed to operate in a high-performance drives environment. The structure scheme consists of a neural network controller and an algorithm for changing the NN weights in order that the motor speed can accurately track of the reference command. This paper also makes uses a very realistic and practical scheme to estimate and adaptively learn the noise content in the speed load torque characteristic of the motor. The availability of the proposed controller is verified by through a laboratory implementation and under computation simulations with Matlab-software. The process is also tested for the tracking property using different types of reference signals. The performance and robustness of the proposed control scheme have evaluated under a variety of operating conditions of the induction motor drives. The obtained results demonstrate the effectiveness of the proposed control scheme system performances, both in steady state error in speed and dynamic conditions, was found to be excellent and those is not overshoot.

Keywords: Electric drive, Induction motor, speed control, Adaptive control, neural network, High Performance.

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1133 Bayesian Network Model for Students- Laboratory Work Performance Assessment: An Empirical Investigation of the Optimal Construction Approach

Authors: Ifeyinwa E. Achumba, Djamel Azzi, Rinat Khusainov

Abstract:

There are three approaches to complete Bayesian Network (BN) model construction: total expert-centred, total datacentred, and semi data-centred. These three approaches constitute the basis of the empirical investigation undertaken and reported in this paper. The objective is to determine, amongst these three approaches, which is the optimal approach for the construction of a BN-based model for the performance assessment of students- laboratory work in a virtual electronic laboratory environment. BN models were constructed using all three approaches, with respect to the focus domain, and compared using a set of optimality criteria. In addition, the impact of the size and source of the training, on the performance of total data-centred and semi data-centred models was investigated. The results of the investigation provide additional insight for BN model constructors and contribute to literature providing supportive evidence for the conceptual feasibility and efficiency of structure and parameter learning from data. In addition, the results highlight other interesting themes.

Keywords: Bayesian networks, model construction, parameterlearning, structure learning, performance index, model comparison.

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1132 A Multi-Feature Deep Learning Algorithm for Urban Traffic Classification with Limited Labeled Data

Authors: Rohan Putatunda, Aryya Gangopadhyay

Abstract:

Acoustic sensors, if embedded in smart street lights, can help in capturing the activities (car honking, sirens, events, traffic, etc.) in cities. Needless to say, the acoustic data from such scenarios are complex due to multiple audio streams originating from different events, and when decomposed to independent signals, the amount of retrieved data volume is small in quantity which is inadequate to train deep neural networks. So, in this paper, we address the two challenges: a) separating the mixed signals, and b) developing an efficient acoustic classifier under data paucity. So, to address these challenges, we propose an architecture with supervised deep learning, where the initial captured mixed acoustics data are analyzed with Fast Fourier Transformation (FFT), followed by filtering the noise from the signal, and then decomposed to independent signals by fast independent component analysis (Fast ICA). To address the challenge of data paucity, we propose a multi feature-based deep neural network with high performance that is reflected in our experiments when compared to the conventional convolutional neural network (CNN) and multi-layer perceptron (MLP).

Keywords: FFT, ICA, vehicle classification, multi-feature DNN, CNN, MLP.

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1131 Detection of Ultrasonic Images in the Presence of a Random Number of Scatterers: A Statistical Learning Approach

Authors: J. P. Dubois, O. M. Abdul-Latif

Abstract:

Support Vector Machine (SVM) is a statistical learning tool that was initially developed by Vapnik in 1979 and later developed to a more complex concept of structural risk minimization (SRM). SVM is playing an increasing role in applications to detection problems in various engineering problems, notably in statistical signal processing, pattern recognition, image analysis, and communication systems. In this paper, SVM was applied to the detection of medical ultrasound images in the presence of partially developed speckle noise. The simulation was done for single look and multi-look speckle models to give a complete overlook and insight to the new proposed model of the SVM-based detector. The structure of the SVM was derived and applied to clinical ultrasound images and its performance in terms of the mean square error (MSE) metric was calculated. We showed that the SVM-detected ultrasound images have a very low MSE and are of good quality. The quality of the processed speckled images improved for the multi-look model. Furthermore, the contrast of the SVM detected images was higher than that of the original non-noisy images, indicating that the SVM approach increased the distance between the pixel reflectivity levels (detection hypotheses) in the original images.

Keywords: LS-SVM, medical ultrasound imaging, partially developed speckle, multi-look model.

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1130 Co-Creation of Non-Economic Values in Islamic Banking: A New Frontier in Service Science

Authors: Amna Javed, Katsuhiro Umemoto, Youji Kohda

Abstract:

The purpose of this paper is to examine co-creation of non-economic values in Islamic banking services and their significance for service science by comparing Islamic and conventional banking services. Although many scholars have discussed co-creation of values in services, most of them have focused on only economic values.

Following Sharia (Islamic principles that are based on Qur’an and Sunnah) traditions, Islamic banking is more concerned with such non-economic values as well-being, partnership, fairness, trust, and justice, than such economic values as money in terms of interest.  Therefore, it may be more sustainable and suitable for today’s unpredictable socio-economic environments.

We also argue that Islamic banking is essentially a value co-creation business model that fits better with the so-called Service-Dominant Logic (SDL) than conventional banking. This paper explores a new frontier of value co-creation in services, thereby contributing to further development of service science.

Keywords: Value co-creation, Islamic banking, Non-economic values, Service science.

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1129 Software Obsolescence Drivers in Aerospace: An Industry Analysis

Authors: Raúl González Muñoz, Essam Shehab, Martin Weinitzke, Chris Fowler, Paul Baguley

Abstract:

Software applications have become crucial for the aerospace industry, providing a wide range of functionalities and capabilities. However, due to the considerable time difference between aircraft and software life cycles, obsolescence has turned into a major challenge for industry in last decades. This paper aims to provide a view on the different causes of software obsolescence within aerospace industry, as well as a perception on the importance of each of them. The key research question addressed is what drives software obsolescence in the aerospace industry, managing large software application portfolios. This question has been addressed by conducting firstly an in depth review of current literature and secondly by arranging an industry workshop with professionals from aerospace and consulting companies. The result is a set of drivers of software obsolescence, distributed among three different environments and several domains. By incorporating monitoring methodologies to assess those software obsolescence drivers, benefits in maintenance efforts and operations disruption avoidance are expected.

Keywords: Aerospace industry, obsolescence drivers, software lifecycle, software obsolescence.

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1128 Designing Information Systems in Education as Prerequisite for Successful Management Results

Authors: Vladimir Simovic, Matija Varga, Tonco Marusic

Abstract:

This research paper shows matrix technology models and examples of information systems in education (in the Republic of Croatia and in the Germany) in support of business, education (when learning and teaching) and e-learning. Here we researched and described the aims and objectives of the main process in education and technology, with main matrix classes of data. In this paper, we have example of matrix technology with detailed description of processes related to specific data classes in the processes of education and an example module that is support for the process: ‘Filling in the directory and the diary of work’ and ‘evaluation’. Also, on the lower level of the processes, we researched and described all activities which take place within the lower process in education. We researched and described the characteristics and functioning of modules: ‘Fill the directory and the diary of work’ and ‘evaluation’. For the analysis of the affinity between the aforementioned processes and/or sub-process we used our application model created in Visual Basic, which was based on the algorithm for analyzing the affinity between the observed processes and/or sub-processes.

Keywords: Designing, education management, information systems, matrix technology, process affinity.

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1127 The Opinions of Nursing Students Regarding Humanized Care through Volunteer Activities at Boromrajonani College of Nursing, Chonburi

Authors: P. Phenpun, S. Wareewan

Abstract:

This qualitative study aimed to describe the opinions in relation to humanized care emerging from the volunteer activities of nursing students at Boromarajonani College of Nursing, Chonburi, Thailand. One hundred and twenty-seven second-year nursing students participated in this study. The volunteer activity model was composed of preparation, implementation, and evaluation through a learning log, in which students were encouraged to write their daily activities after completing practical training at the healthcare center. The preparation content included three main categories: service minded, analytical thinking, and client participation. The preparation process took over three days that accumulates up to 20 hours only. The implementation process was held over 10 days, but with a total of 70 hours only, with participants taking part in volunteer work activities at a healthcare center. A learning log was used for evaluation and data were analyzed using content analysis. The findings were as follows. With service minded, there were two subcategories that emerged from volunteer activities, which were service minded towards patients and within themselves. There were three categories under service minded towards patients, which were rapport, compassion, and empathy service behaviors, and there were four categories under service minded within themselves, which were self-esteem, self-value, management potential, and preparedness in providing good healthcare services. In line with analytical thinking, there were two components of analytical thinking, which were analytical skill for their works and analytical thinking for themselves. There were four subcategories under analytical thinking for their works, which were evidence based thinking, real situational thinking, cause analysis thinking, and systematic thinking, respectively. There were four subcategories under analytical thinking for themselves, which were comparative between themselves, towards their clients that leads to the changing of their service behaviors, open-minded thinking, modernized thinking, and verifying both verbal and non-verbal cues. Lastly, there were three categories under participation, which were mutual rapport relationship; reconsidering client’s needs services and providing useful health care information.

Keywords: Humanized care service, volunteer activity, nursing student, and learning log.

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1126 Social Entrepreneurship: The Role of Intangible Resources in the Resource Scarce Environment

Authors: Seham Ghalwash, Ayman Ismail

Abstract:

Resources are crucial to the development and sustainability of social ventures. Thus, resources and resources scarcity are central concepts to study and understand the phenomenon of social entrepreneurship specially in developing countries where resources are very limited. Social entrepreneurs in developing countries face bigger challenges because financial resources are scarce. The empirical findings in this paper suggest that social enterprises in poor resources environments survive and grow because of the existence of social and human capitals in which they serve as prerequisites for the physical resources required for sustainability. This research paper explores how governments and policymakers might take nativities to support and foster social entrepreneurial activities in a resource-constraints environment reflecting on the experiences of Egypt-based social enterprises.

Keywords: Social ventures, financial constraints, intangible resources, scarce resources, legitimacy, developing countries, Egypt.

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1125 Investigation on the Fate Pesticides in Water and Sediments Iraqi Marshland

Authors: Abdal-Kader Saeed Latif, Reyam Naji Ajmi, Huda Farooq Zeki, Wathiq Abaas Hatit

Abstract:

These studies have been carried out on the behavior of pesticides in aquatic environments of marshes to monitoring water and sediment. A total of 25 water and 25 sediment samples were collected at five sampling station during April, June and September. 2013 the levels of organochlorine (OCP) pesticide as a case study to find out the extent of pesticide contamination and accumulation, in water was the concentration of OCPs (0.02, 0.066, 0.7, 0.8, 0.072, 0.058) ppb. In sediment was the concentration of OCPs (5.897, 10.987, 0.089, 0.096, 7.897, and 12.389) ppb respectively in DDT, DDE, Chlordane, Heptachlor, Lindane, and Endosulfan. There is a relationship between pesticides and sediment and water with physical properties because the concentrations of pesticide in water and sediment are not always in equilibrium Furthermore, when sediments are smaller, the rate of deposition is slower. There the wetlands of pesticides due to factors of high temperature and evaporation but used in the control of pesticides in water and sediment also there still exist a variety of organochlorine pesticide residues in water and sediments of wetlands.

Keywords: Bioindicators, Iraqi marshes, Pesticides, Sediment, Water.

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1124 The Impact of Physics Taught with Simulators and Texts in Brazilian High School: A Study in the Adult and Youth Education

Authors: Leandro Marcos Alves Vaz

Abstract:

The teaching of physics in Brazilian public schools emphasizes strongly the theoretical aspects of this science, showing its philosophical and mathematical basis, but neglecting its experimental character. Perhaps the lack of science laboratories explains this practice. In this work, we present a method of teaching physics using the computer. As alternatives to real experiments, we have the trials through simulators, many of which are free software available on the internet. In order to develop a study on the use of simulators in teaching, knowing the impossibility of simulations on all topics in a given subject, we combined these programs with phenomenological and/or experimental texts in order to mitigate this limitation. This study proposes the use of simulators and the debate using phenomenological/experimental texts on electrostatic theme in groups of the 3rd year of EJA (Adult and Youth Education) in order to verify the advantages of this methodology. Some benefits of the hybridization of the traditional method with the tools used were: Greater motivation of the students in learning, development of experimental notions, proactive socialization to learning, greater easiness to understand some concepts and the creation of collaborative activities that can reduce timidity of part of the students.

Keywords: Physics teaching, simulators, youth and adult education, experimentation, electrostatic.

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1123 A Novel Nucleus-Based Classifier for Discrimination of Osteoclasts and Mesenchymal Precursor Cells in Mouse Bone Marrow Cultures

Authors: Andreas Heindl, Alexander K. Seewald, Martin Schepelmann, Radu Rogojanu, Giovanna Bises, Theresia Thalhammer, Isabella Ellinger

Abstract:

Bone remodeling occurs by the balanced action of bone resorbing osteoclasts (OC) and bone-building osteoblasts. Increased bone resorption by excessive OC activity contributes to malignant and non-malignant diseases including osteoporosis. To study OC differentiation and function, OC formed in in vitro cultures are currently counted manually, a tedious procedure which is prone to inter-observer differences. Aiming for an automated OC-quantification system, classification of OC and precursor cells was done on fluorescence microscope images based on the distinct appearance of fluorescent nuclei. Following ellipse fitting to nuclei, a combination of eight features enabled clustering of OC and precursor cell nuclei. After evaluating different machine-learning techniques, LOGREG achieved 74% correctly classified OC and precursor cell nuclei, outperforming human experts (best expert: 55%). In combination with the automated detection of total cell areas, this system allows to measure various cell parameters and most importantly to quantify proteins involved in osteoclastogenesis.

Keywords: osteoclasts, machine learning, ellipse fitting.

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1122 Play in College: Shifting Perspectives and Creative Problem-Based Play

Authors: Agni Stylianou-Georgiou, Eliza Pitri

Abstract:

This study is a design narrative that discusses researchers’ new learning based on changes made in pedagogies and learning opportunities in the context of a Cognitive Psychology and an Art History undergraduate course. The purpose of this study was to investigate how to encourage creative problem-based play in tertiary education engaging instructors and student-teachers in designing educational games. Course instructors modified content to encourage flexible thinking during game design problem-solving. Qualitative analyses of data sources indicated that Thinking Birds’ questions could encourage flexible thinking as instructors engaged in creative problem-based play. However, student-teachers demonstrated weakness in adopting flexible thinking during game design problem solving. Further studies of student-teachers’ shifting perspectives during different instructional design tasks would provide insights for developing the Thinking Birds’ questions as tools for creative problem solving.

Keywords: Creative problem-based play, educational games, flexible thinking, tertiary education.

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1121 Fenestration Effects on Cross Ventilation for a Typical Taiwanese School Building When Applying Wind Profile

Authors: Wei-Hwa Chiang, Hao-Hsiang Hsu, Jian-Sheng Huang

Abstract:

Appropriate ventilation in a classroom is helpful for enhancing air exchange rate and student concentration. This study focuses on the effects of fenestration in a four-story school building by performing numerical simulation of a building when considering indoor and outdoor environments simultaneously. The wind profile function embedded in PHOENICS code was set as the inlet boundary condition in a suburban environment. Sixteen fenestration combinations were compared in a classroom containing thirty seats. This study evaluates mean age of air (AGE) and airflow pattern of a classroom on different floors. Considering both wind profile and fenestration effects, the airflow on higher floors is channeled toward the area near ceiling in a room and causes older mean age of air in the breathing zone. The results in this study serve as a useful guide for enhancing natural ventilation in a typical school building.

Keywords: Cross ventilation, Fenestration effect, Wind profile, Mean age of air, CFD

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1120 Time Organization for Urban Mobility Decongestion: A Methodology for People’s Profile Identification

Authors: Yassamina Berkane, Leïla Kloul, Yoann Demoli

Abstract:

Quality of life, environmental impact, congestion of mobility means, and infrastructures remain significant challenges for urban mobility. Solutions like car sharing, spatial redesign, eCommerce, and autonomous vehicles will likely increase the unit veh-km and the density of cars in urban traffic, thus reducing congestion. However, the impact of such solutions is not clear for researchers. Congestion arises from growing populations that must travel greater distances to arrive at similar locations (e.g., workplaces, schools) during the same time frame (e.g., rush hours). This paper first reviews the research and application cases of urban congestion methods through recent years. Rethinking the question of time, it then investigates people’s willingness and flexibility to adapt their arrival and departure times from workplaces. We use neural networks and methods of supervised learning to apply a methodology for predicting peoples’ intentions from their responses in a questionnaire. We created and distributed a questionnaire to more than 50 companies in the Paris suburb. Obtained results illustrate that our methodology can predict peoples’ intentions to reschedule their activities (work, study, commerce, etc.).

Keywords: Urban mobility, decongestion, machine learning, neural network.

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1119 Distributional Semantics Approach to Thai Word Sense Disambiguation

Authors: Sunee Pongpinigpinyo, Wanchai Rivepiboon

Abstract:

Word sense disambiguation is one of the most important open problems in natural language processing applications such as information retrieval and machine translation. Many approach strategies can be employed to resolve word ambiguity with a reasonable degree of accuracy. These strategies are: knowledgebased, corpus-based, and hybrid-based. This paper pays attention to the corpus-based strategy that employs an unsupervised learning method for disambiguation. We report our investigation of Latent Semantic Indexing (LSI), an information retrieval technique and unsupervised learning, to the task of Thai noun and verbal word sense disambiguation. The Latent Semantic Indexing has been shown to be efficient and effective for Information Retrieval. For the purposes of this research, we report experiments on two Thai polysemous words, namely  /hua4/ and /kep1/ that are used as a representative of Thai nouns and verbs respectively. The results of these experiments demonstrate the effectiveness and indicate the potential of applying vector-based distributional information measures to semantic disambiguation.

Keywords: Distributional semantics, Latent Semantic Indexing, natural language processing, Polysemous words, unsupervisedlearning, Word Sense Disambiguation.

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1118 Inflating the Public: A Series of Urban Interventions

Authors: Veronika Antoniou, Rene Carraz, Yiorgos Hadjichristou

Abstract:

The Green Urban Lab took the form of public installations that were placed at various locations in four cities in Cyprus. These installations - through which a series of events, activities, workshops and research took place - were the main tools in regenerating a series of urban public spaces in Cyprus. The purpose of this project was to identify issues and opportunities related to public space and to offer guidelines on how design and participatory democracy improvements could strengthen civil society, while raising the quality of the urban public scene. Giant inflatable structures were injected in important urban fragments in order to accommodate series of events. The design and playful installation generated a wide community engagement. The fluid presence of the installations acted as a catalyst for social interaction. They were accessed and viewed effortlessly and surprisingly, creating opportunities to rediscover public spaces.

Keywords: Bottom-up initiatives, creativity, public space, social innovation, urban environments.

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1117 Understanding Health Behavior Using Social Network Analysis

Authors: Namrata Mishra

Abstract:

Health of a person plays a vital role in the collective health of his community and hence the well-being of the society as a whole. But, in today’s fast paced technology driven world, health issues are increasingly being associated with human behaviors – their lifestyle. Social networks have tremendous impact on the health behavior of individuals. Many researchers have used social network analysis to understand human behavior that implicates their social and economic environments. It would be interesting to use a similar analysis to understand human behaviors that have health implications. This paper focuses on concepts of those behavioural analyses that have health implications using social networks analysis and provides possible algorithmic approaches. The results of these approaches can be used by the governing authorities for rolling out health plans, benefits and take preventive measures, while the pharmaceutical companies can target specific markets, helping health insurance companies to better model their insurance plans.

Keywords: Health behaviors, social network analysis, directed graph, breadth first search.

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1116 Impact of Metallic Furniture on UWB Channel Statistical Characteristics by BER

Authors: Yu-Shuai Chen , Chien-Ching Chiu , Chung-Hsin Huang, Chien-Hung Chen

Abstract:

The bit error rate (BER) performance for ultra-wide band (UWB) indoor communication with impact of metallic furniture is investigated. The impulse responses of different indoor environments for any transmitter and receiver location are computed by shooting and bouncing ray/image and inverse Fourier transform techniques. By using the impulse responses of these multipath channels, the BER performance for binary pulse amplitude modulation (BPAM) impulse radio UWB communication system are calculated. Numerical results have shown that the multi-path effect by the metallic cabinets is an important factor for BER performance. Also the outage probability for the UWB multipath environment with metallic cabinets is more serious (about 18%) than with wooden cabinets. Finally, it is worth noting that in these cases the present work provides not only comparative information but also quantitative information on the performance reduction.

Keywords: UWB, multipath, outage probability.

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1115 Education for Sustainability Using PBL on an Engineering Course at the National University of Colombia

Authors: Hernán G. Cortés-Mora, José I. Péna-Reyes, Alfonso Herrera-Jiménez

Abstract:

This article describes the implementation experience of Project-Based Learning (PBL) in an engineering course of the Universidad Nacional de Colombia, with the aim of strengthening student skills necessary for the exercise of their profession under a sustainability framework. Firstly, we present a literature review on the education for sustainability field, emphasizing the skills and knowledge areas required for its development, as well as the commitment of the Faculty of Engineering of the Universidad Nacional de Colombia, and other engineering faculties of the country, regarding education for sustainability. This article covers the general aspects of the course, describes how students team were formed, and how their experience was during the first semester of 2017. During this period two groups of students decided to develop their course project aiming to solve a problem regarding a Non-Governmental Organization (NGO) that works with head-of-household mothers in a low-income neighborhood in Bogota (Colombia). Subsequently, we show how sustainability is involved in the course, how tools are provided to students, and how activities are developed as to strengthen their abilities, which allows them to incorporate sustainability in their projects while also working on the methodology used to develop said projects. Finally, we introduce the results obtained by the students who sent the prototypes of their projects to the community they were working on and the conclusions reached by them regarding the course experience.

Keywords: Sustainability, project based learning, engineering education, higher education for sustainability.

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1114 Art Street as a Way for Reflective Thinking in the Field of Adult and Primary Education: Examples of Educational Techniques

Authors: Georgia H. Mega

Abstract:

Street art, a category of artwork displayed in public spaces, has been recognized as a potential tool for promoting reflective thinking in both adult and primary education. Educational techniques that encourage critical and creative thinking, as well as deeper reflection, have been developed and applied in educational curricula. This paper aims to explore the potential of art street in cultivating learners' reflective awareness towards multiculturalism. More specifically, two artworks displayed in public spaces have been selected: the artwork of Kleomenis Kostopoulos and the artwork of Rustam Obic. The reason of this selection is because of their strong symbolism towards multiculturalism. The street arts have been elaborated by adult (+18) and minor students (K-12) in educational settings, under the same educator’s guidance, following appropriate for each age learning techniques. Adults cultivate their reflection using Freire’s learning method, whereas minors cultivate critical thinking using visible thinking techniques from Project Zero. Through qualitative methodology (context analysis) the depth of reflection/critical thinking has been emphasized for both age groups. The case study shows that street art can play a significant role to the promotion/cultivation of deep thinking towards challenging contemporary phenomena like multiculturalism.

Keywords: Street art, observation of art works, reflective awareness, educational techniques, multiculturalism.

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1113 e-Service Innovation within Open Innovation Networks

Authors: Hung T. Tsou, Hsuan Y. Hsu

Abstract:

Service innovations are central concerns in fast changing environment. Due to the fitness in customer demands and advances in information technologies (IT) in service management, an expanded conceptualization of e-service innovation is required. Specially, innovation practices have become increasingly more challenging, driving managers to employ a different open innovation model to maintain competitive advantages. At the same time, firms need to interact with external and internal customers in innovative environments, like the open innovation networks, to co-create values. Based on these issues, an important conceptual framework of e-service innovation is developed. This paper aims to examine the contributing factors on e-service innovation and firm performance, including financial and non-financial aspects. The study concludes by showing how e-service innovation will play a significant role in growing the overall values of the firm. The discussion and conclusion will lead to a stronger understanding of e-service innovation and co-creating values with customers within open innovation networks.

Keywords: e-Service innovation, performance, open innovation networks, co-create value.

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1112 Towards Finite Element Modeling of the Accoustics of Human Head

Authors: Maciej Paszynski, Leszek Demkowicz, Jason Kurtz

Abstract:

In this paper, a new formulation for acoustics coupled with linear elasticity is presented. The primary objective of the work is to develop a three dimensional hp adaptive finite element method code destinated for modeling of acoustics of human head. The code will have numerous applications e.g. in designing hearing protection devices for individuals working in high noise environments. The presented work is in the preliminary stage. The variational formulation has been implemented and tested on a sequence of meshes with concentric multi-layer spheres, with material data representing the tissue (the brain), skull and the air. Thus, an efficient solver for coupled elasticity/acoustics problems has been developed, and tested on high contrast material data representing the human head.

Keywords: finite element method, acoustics, coupled problems, biomechanics

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1111 Zamzam Water as Corrosion Inhibitor for Steel Rebar in Rainwater and Simulated Acid Rain

Authors: Ahmed A. Elshami, Stéphanie Bonnet, Abdelhafid Khelidj

Abstract:

Corrosion inhibitors are widely used in concrete industry to reduce the corrosion rate of steel rebar which is present in contact with aggressive environments. The present work aims to using Zamzam water from well located within the Masjid al-Haram in Mecca, Saudi Arabia 20 m (66 ft) east of the Kaaba, the holiest place in Islam as corrosion inhibitor for steel in rain water and simulated acid rain. The effect of Zamzam water was investigated by electrochemical impedance spectroscopy (EIS) and Potentiodynamic polarization techniques in Department of Civil Engineering - IUT Saint-Nazaire, Nantes University, France. Zamzam water is considered to be one of the most important steel corrosion inhibitor which is frequently used in different industrial applications. Results showed that zamzam water gave a very good inhibition for steel corrosion in rain water and simulated acid rain.

Keywords: Zamzam water, corrosion inhibitor, rain water and simulated acid rain.

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1110 A Comparative Analysis of Machine Learning Techniques for PM10 Forecasting in Vilnius

Authors: M. A. S. Fahim, J. Sužiedelytė Visockienė

Abstract:

With the growing concern over air pollution (AP), it is clear that this has gained more prominence than ever before. The level of consciousness has increased and a sense of knowledge now has to be forwarded as a duty by those enlightened enough to disseminate it to others. This realization often comes after an understanding of how poor air quality indices (AQI) damage human health. The study focuses on assessing air pollution prediction models specifically for Lithuania, addressing a substantial need for empirical research within the region. Concentrating on Vilnius, it specifically examines particulate matter concentrations 10 micrometers or less in diameter (PM10). Utilizing Gaussian Process Regression (GPR) and Regression Tree Ensemble, and Regression Tree methodologies, predictive forecasting models are validated and tested using hourly data from January 2020 to December 2022. The study explores the classification of AP data into anthropogenic and natural sources, the impact of AP on human health, and its connection to cardiovascular diseases. The study revealed varying levels of accuracy among the models, with GPR achieving the highest accuracy, indicated by an RMSE of 4.14 in validation and 3.89 in testing.

Keywords: Air pollution, anthropogenic and natural sources, machine learning, Gaussian process regression, tree ensemble, forecasting models, particulate matter.

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1109 Adaptive Hierarchical Key Structure Generation for Key Management in Wireless Sensor Networks using A*

Authors: Jin Myoung Kim, Tae Ho Cho

Abstract:

Wireless Sensor networks have a wide spectrum of civil and military applications that call for secure communication such as the terrorist tracking, target surveillance in hostile environments. For the secure communication in these application areas, we propose a method for generating a hierarchical key structure for the efficient group key management. In this paper, we apply A* algorithm in generating a hierarchical key structure by considering the history data of the ratio of addition and eviction of sensor nodes in a location where sensor nodes are deployed. Thus generated key tree structure provides an efficient way of managing the group key in terms of energy consumption when addition and eviction event occurs. A* algorithm tries to minimize the number of messages needed for group key management by the history data. The experimentation with the tree shows efficiency of the proposed method.

Keywords: Heuristic search, key management, security, sensor network.

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1108 Blind Image Deconvolution by Neural Recursive Function Approximation

Authors: Jiann-Ming Wu, Hsiao-Chang Chen, Chun-Chang Wu, Pei-Hsun Hsu

Abstract:

This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.

Keywords: Blind image deconvolution, linear shift-invariant(LSI), linear image degradation model, radial basis functions (rbf), recursive function, annealed Hopfield neural networks.

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