Search results for: mobile network communication
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9289

Search results for: mobile network communication

7819 When Mobile Work Creates More Discrimination

Authors: Marie-Therese Claes, Anett Hermann

Abstract:

With the advent of the web and information technology since the end of the 20ᵗʰ century, digitalization has revolutionized our everyday life, from shopping and dating to education and transportation. The world of work is one of the areas that has been highly transformed by changing the time and spatial limits of the work. The expansion of the internet, wireless, and easily portable devices such as laptop computers and mobile phones has enabled us to work almost from any place at any time. As a result, telework, which started in the 1950s and elevated in the 1970s, steeply raised to a new level in 21ˢᵗ century. Telework consists of various forms of work done from outside the traditional workplace by using information technologies. The social distancing and lockdown measures that have been taken to reduce the spread of the virus in many countries worldwide resulted in an increasing number of teleworkers and made “working from home’’ synonymous with telework. Post-COVID-19, the number of teleworkers is still higher than before the pandemic period, and the interest in expanding teleworking has been growing too. Notwithstanding the advantages ushered by telework, it also has a number of drawbacks that negatively affect organizations and employees. The intention of this piece of work is not to indicate a causational relationship between telework and discrimination. Our aim is to indicate some unintended and/or unnoticed deleterious effects of telework in reinforcing discrimination and to instigate discussion on how to mitigate the effects. To do so, this insight indicates how telework reinforces traditional gender roles and how organizational culture towards telework and its access to employees at different levels of the organizational hierarchy opens the room for discrimination.

Keywords: mobile work, discrimination, gender roles, organizational culture

Procedia PDF Downloads 56
7818 Forecast of Polyethylene Properties in the Gas Phase Polymerization Aided by Neural Network

Authors: Nasrin Bakhshizadeh, Ashkan Forootan

Abstract:

A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

Procedia PDF Downloads 128
7817 Study and Analysis of Optical Intersatellite Links

Authors: Boudene Maamar, Xu Mai

Abstract:

Optical Intersatellite Links (OISLs) are wireless communications using optical signals to interconnect satellites. It is expected to be the next generation wireless communication technology according to its inherent characteristics like: an increased bandwidth, a high data rate, a data transmission security, an immunity to interference, and an unregulated spectrum etc. Optical space links are the best choice for the classical communication schemes due to its distinctive properties; high frequency, small antenna diameter and lowest transmitted power, which are critical factors to define a space communication. This paper discusses the development of free space technology and analyses the parameters and factors to establish a reliable intersatellite links using an optical signal to exchange data between satellites.

Keywords: optical intersatellite links, optical wireless communications, free space optical communications, next generation wireless communication

Procedia PDF Downloads 435
7816 Impact of Electronic Guest Relationship Management (e-GRM) on Brand Loyalty: The Case of Croatian Hotels

Authors: Marina Laškarin, Vlado Galičić

Abstract:

Quick adoption of e-business and emerging influence of “Electronic Word of Mouth e-WOM” communication on guests made leading hotel brands successful examples of electronic guest relationship management. Main reasons behind such success are well established procedures in collection, analysis and usage of highly valuable data available on the Internet, generated through some form of e-GRM programme. E-GRM is more than just a technology solution. It’s a system which balance respective guest demands, hotel technological capabilities and organizational culture of employees, discharging the universal approach in guest relations “same for all”. The purpose of this research derives from the necessity of determining the importance of monitoring and applying e-WOM communication as one of the methods used in managing guest relations. This paper analyses and compares different hotelier’s opinions on e-WOM communication.

Keywords: brand loyalty, e-WOM communication, GRM programmes, organizational culture

Procedia PDF Downloads 279
7815 Developing an Online Application for Mental Skills Training and Development

Authors: Arjun Goutham, Chaitanya Sridhar, Sunita Maheshwari, Robin Uthappa, Prasanna Gopinath

Abstract:

In alignment with the growth in the sporting industry, a number of people playing and competing in sports are growing exponentially across the globe. However, the number of sports psychology experts are not growing at a similar rate, especially in the Asian and more so, Indian context. Hence, the access to actionable mental training solutions specific to individual athletes is limited. Also, the time constraint an athlete faces due to their intense training schedule makes one-on-one sessions difficult. One of the means to bridge that gap is through technology. Technology makes individualization possible. It allows for easy access to specific-qualitative content/information and provides a medium to place individualized assessments, analysis, solutions directly into an athlete's hands. This enables mental training awareness, education, and real-time actionable solutions possible for athletes in-spite of the limitation of available sports psychology experts in their region. Furthermore, many athletes are hesitant to seek support due to the stigma of appearing weak. Such individuals would prefer a more discreet way. Athletes who have strong mental performance tend to produce better results. The mobile application helps to equip athletes with assessing and developing their mental strategies directed towards improving performance on an ongoing basis. When an athlete understands their strengths and limitations in their mental application, they can focus specifically on applying the strategies that work and improve on zones of limitation. With reports, coaches get to understand the unique inner workings of an athlete and can utilize the data & analysis to coach them with better precision and use coaching styles & communication that suits better. Systematically capturing data and supporting athletes(with individual-specific solutions) or teams with assessment, planning, instructional content, actionable tools & strategies, reviewing mental performance and the achievement of objectives & goals facilitate for a consistent mental skills development at all levels of sporting stages of an athlete's career. The mobile application will help athletes recognize and align with their stable attributes such as their personalities, learning & execution modalities, challenges & requirements of their sport, etc and help develop dynamic attributes like states, beliefs, motivation levels, focus etc. with practice and training. It will provide measurable analysis on a regular basis and help them stay aligned to their objectives & goals. The solutions are based on researched areas of influence on sporting performance individually or in teams.

Keywords: athletes, mental training, mobile application, performance, sports

Procedia PDF Downloads 252
7814 Analysis and Prediction of COVID-19 by Using Recurrent LSTM Neural Network Model in Machine Learning

Authors: Grienggrai Rajchakit

Abstract:

As we all know that coronavirus is announced as a pandemic in the world by WHO. It is speeded all over the world with few days of time. To control this spreading, every citizen maintains social distance and self-preventive measures are the best strategies. As of now, many researchers and scientists are continuing their research in finding out the exact vaccine. The machine learning model finds that the coronavirus disease behaves in an exponential manner. To abolish the consequence of this pandemic, an efficient step should be taken to analyze this disease. In this paper, a recurrent neural network model is chosen to predict the number of active cases in a particular state. To make this prediction of active cases, we need a database. The database of COVID-19 is downloaded from the KAGGLE website and is analyzed by applying a recurrent LSTM neural network with univariant features to predict the number of active cases of patients suffering from the corona virus. The downloaded database is divided into training and testing the chosen neural network model. The model is trained with the training data set and tested with a testing dataset to predict the number of active cases in a particular state; here, we have concentrated on Andhra Pradesh state.

Keywords: COVID-19, coronavirus, KAGGLE, LSTM neural network, machine learning

Procedia PDF Downloads 143
7813 Video-On-Demand QoE Evaluation across Different Age-Groups and Its Significance for Network Capacity

Authors: Mujtaba Roshan, John A. Schormans

Abstract:

Quality of Experience (QoE) drives churn in the broadband networks industry, and good QoE plays a large part in the retention of customers. QoE is known to be affected by the Quality of Service (QoS) factors packet loss probability (PLP), delay and delay jitter caused by the network. Earlier results have shown that the relationship between these QoS factors and QoE is non-linear, and may vary from application to application. We use the network emulator Netem as the basis for experimentation, and evaluate how QoE varies as we change the emulated QoS metrics. Focusing on Video-on-Demand, we discovered that the reported QoE may differ widely for users of different age groups, and that the most demanding age group (the youngest) can require an order of magnitude lower PLP to achieve the same QoE than is required by the most widely studied age group of users. We then used a bottleneck TCP model to evaluate the capacity cost of achieving an order of magnitude decrease in PLP, and found it be (almost always) a 3-fold increase in link capacity that was required.

Keywords: network capacity, packet loss probability, quality of experience, quality of service

Procedia PDF Downloads 262
7812 A Neural Network for the Prediction of Contraction after Burn Injuries

Authors: Ginger Egberts, Marianne Schaaphok, Fred Vermolen, Paul van Zuijlen

Abstract:

A few years ago, a promising morphoelastic model was developed for the simulation of contraction formation after burn injuries. Contraction can lead to a serious reduction in physical mobility, like a reduction in the range-of-motion of joints. If this is the case in a healing burn wound, then this is referred to as a contracture that needs medical intervention. The morphoelastic model consists of a set of partial differential equations describing both a chemical part and a mechanical part in dermal wound healing. These equations are solved with the numerical finite element method (FEM). In this method, many calculations are required on each of the chosen elements. In general, the more elements, the more accurate the solution. However, the number of elements increases rapidly if simulations are performed in 2D and 3D. In that case, it not only takes longer before a prediction is available, the computation also becomes more expensive. It is therefore important to investigate alternative possibilities to generate the same results, based on the input parameters only. In this study, a surrogate neural network has been designed to mimic the results of the one-dimensional morphoelastic model. The neural network generates predictions quickly, is easy to implement, and there is freedom in the choice of input and output. Because a neural network requires extensive training and a data set, it is ideal that the one-dimensional FEM code generates output quickly. These feed-forward-type neural network results are very promising. Not only can the network give faster predictions, but it also has a performance of over 99%. It reports on the relative surface area of the wound/scar, the total strain energy density, and the evolutions of the densities of the chemicals and mechanics. It is, therefore, interesting to investigate the applicability of a neural network for the two- and three-dimensional morphoelastic model for contraction after burn injuries.

Keywords: biomechanics, burns, feasibility, feed-forward NN, morphoelasticity, neural network, relative surface area wound

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7811 Promoting 21st Century Skills through Telecollaborative Learning

Authors: Saliha Ozcan

Abstract:

Technology has become an integral part of our lives, aiding individuals in accessing higher order competencies, such as global awareness, creativity, collaborative problem solving, and self-directed learning. Students need to acquire these competencies, often referred to as 21st century skills, in order to adapt to a fast changing world. Today, an ever-increasing number of schools are exploring how engagement through telecollaboration can support language learning and promote 21st century skill development in classrooms. However, little is known regarding how telecollaboration may influence the way students acquire 21st century skills. In this paper, we aim to shed light to the potential implications of telecollaborative practices in acquisition of 21st century skills. In our context, telecollaboration, which might be carried out in a variety of settings both synchronously or asynchronously, is considered as the process of communicating and working together with other people or groups from different locations through online digital tools or offline activities to co-produce a desired work output. The study presented here will describe and analyse the implementation of a telecollaborative project between two high school classes, one in Spain and the other in Sweden. The students in these classes were asked to carry out some joint activities, including creating an online platform, aimed at raising awareness of the situation of the Syrian refugees. We conduct a qualitative study in order to explore how language, culture, communication, and technology merge into the co-construction of knowledge, as well as supporting the attainment of the 21st century skills needed for network-mediated communication. To this end, we collected a significant amount of audio-visual data, including video recordings of classroom interaction and external Skype meetings. By analysing this data, we verify whether the initial pedagogical design and intended objectives of the telecollaborative project coincide with what emerges from the actual implementation of the tasks. Our findings indicate that, as well as planned activities, unplanned classroom interactions may lead to acquisition of certain 21st century skills, such as collaborative problem solving and self-directed learning. This work is part of a wider project (KONECT, EDU2013-43932-P; Spanish Ministry of Economy and Finance), which aims to explore innovative, cross-competency based teaching that can address the current gaps between today’s educational practices and the needs of informed citizens in tomorrow’s interconnected, globalised world.

Keywords: 21st century skills, telecollaboration, language learning, network mediated communication

Procedia PDF Downloads 115
7810 The Paralinguistic Function of Emojis in Twitter Communication

Authors: Yasmin Tantawi, Mary Beth Rosson

Abstract:

In response to the dearth of information about emoji use for different purposes in different settings, this paper investigates the paralinguistic function of emojis within Twitter communication in the United States. To conduct this investigation, the Twitter feeds from 16 population centers spread throughout the United States were collected from the Twitter public API. One hundred tweets were collected from each population center, totaling to 1,600 tweets. Tweets containing emojis were next extracted using the “emot” Python package; these were then analyzed via the IBM Watson API Natural Language Understanding module to identify the topics discussed. A manual content analysis was then conducted to ascertain the paralinguistic and emotional features of the emojis used in these tweets. We present our characterization of emoji usage in Twitter and discuss implications for the design of Twitter and other text-based communication tools.

Keywords: computer-mediated communication, content analysis, paralinguistics, sociology

Procedia PDF Downloads 150
7809 Conceptual Knowledge Structure Updates after Instructor Provided Structural Feedback: An Exploratory Study Applied with Undergraduate Architectural Engineering Students

Authors: Roy B. Clariana, Ryan L. Solnosky

Abstract:

Structural feedback is any form of feedback that aims to improve the quality of students’ domain-normative conceptual interrelationships. Research with structural feedback points to the potential mediating role of network graphs as feedback for tuning students’ conceptual understanding; for example, improved content knowledge and motivation were observed for undergraduate students who accessed the instructor’s networks of course content. This exploratory study uses a one-group pretest-posttest design to examine the effects of instructor-provided network feedback during lectures on students’ knowledge structure measured using a concept sorting task at the pretest and posttest. Undergraduate students in an architectural engineering course (n = 32) completed a lesson module and then an end-of-unit quiz on building with wood and wood framing. Three weeks later, as a review, students completed a sorting task that used 26 terms from that lesson, then a week later, the sorting task data were used to create a group-average network, this network along with the instructor’s expert network were added to that week’s lecture slides and were compared and discussed during class time. A week later, students completed the sorting task again. The pre and post-sorting data were rendered into pathfinder networks, and then these students’ networks were compared to five referent networks, specifically the textbook chapter network, the lecture slides network, a network of the end-of-unit quiz, the actual expert network that served as the feedback intervention, and the group-average network. Inspection of means shows that knowledge structure measures improved for all five measures from pre-to-post, becoming more like the lesson content and like the expert. Repeated measures analysis with follow-up paired samples t-tests showed pre-to-post significant increases for both the end-of-unit quiz and the expert network referents. The findings show that instructor presentation of structural feedback as networks improved or ‘tuned’ students’ knowledge structure of the lesson content. This approach only takes a few extra minutes of class time and is fairly simple to implement in ordinary classrooms, and so it has wide potential to support classroom instruction and student learning. Further research is needed to determine how critical it is to present both the group-average network along with the expert network for comparison in order to highlight group-level misconceptions, or is presenting only the expert network sufficient? If a group-level network is necessary, then a simple clicker-like classroom tool could be developed to collect sorting task data during lectures that could then immediately provide the group-average network for class discussion and reflection.

Keywords: classroom instruction, engineering education, knowledge structure, pathfinder networks, structural feedback

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7808 Mobile Based Long Range Weather Prediction System for the Farmers of Rural Areas of Pakistan

Authors: Zeeshan Muzammal, Usama Latif, Fouzia Younas, Syed Muhammad Hassan, Samia Razaq

Abstract:

Unexpected rainfall has always been an issue in the lifetime of crops and brings destruction for the farmers who harvest them. Unfortunately, Pakistan is one of the countries in which untimely rain impacts badly on crops like wash out of seeds and pesticides etc. Pakistan’s GDP is related to agriculture, especially in rural areas farmers sometimes quit farming because leverage of huge loss to their crops. Through our surveys and research, we came to know that farmers in the rural areas of Pakistan need rain information to avoid damages to their crops from rain. We developed a prototype using ICTs to inform the farmers about rain one week in advance. Our proposed solution has two ways of informing the farmers. In first we send daily messages about weekly prediction and also designed a helpline where they can call us to ask about possibility of rain.

Keywords: ICTD, farmers, mobile based, Pakistan, rural areas, weather prediction

Procedia PDF Downloads 555
7807 Evaluation of Collect Tree Protocol for Structural Health Monitoring System Using Wireless Sensor Networks

Authors: Amira Zrelli, Tahar Ezzedine

Abstract:

Routing protocol may enhance the lifetime of sensor network, it has a highly importance, especially in wireless sensor network (WSN). Therefore, routing protocol has a big effect in these networks, thus the choice of routing protocol must be studied before setting up our network. In this work, we implement the routing protocol collect tree protocol (CTP) which is one of the hierarchic protocols used in structural health monitoring (SHM). Therefore, to evaluate the performance of this protocol, we choice to work with Contiki system and Cooja simulator. By throughput and RSSI evaluation of each node, we will deduce about the utility of CTP in structural monitoring system.

Keywords: CTP, WSN, SHM, routing protocol

Procedia PDF Downloads 278
7806 DeepLig: A de-novo Computational Drug Design Approach to Generate Multi-Targeted Drugs

Authors: Anika Chebrolu

Abstract:

Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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7805 The Decision Making of Students to Study at Rajabhat University in Thailand

Authors: Pisit Potjanajaruwit

Abstract:

TThe research objective was to study the integrated marketing communication strategy that is affecting the student’s decision making to study at Rajabhat University in Thailand. This research is a quantitative research. The sampling for this study is the first year students of Rajabhat University for 400 sampling. The data collection is made by a questionnaire. The data analysis by the descriptive statistic include frequency, percentage, mean and standardization and influence statistic as the multiple regression. The results show that integrated marketing communication including the advertising, public relation, sale promotion is important and significant with the student’s making decision in terms of brand awareness and brand recognized. The university scholar and word of mouth have an impact on decision-making of the student. The direct marketing such as Facebook also relate to the student decision. In addition, we found that the marketing communication budget, university brand positioning and university mission have the direct effect on the marketing communication.

Keywords: decision making of higher education, integrated marketing communication, rajabhat university, social media

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7804 An Improved Transmission Scheme in Cooperative Communication System

Authors: Seung-Jun Yu, Young-Min Ko, Hyoung-Kyu Song

Abstract:

Recently developed cooperative diversity scheme enables a terminal to get transmit diversity through the support of other terminals. However, most of the introduced cooperative schemes have a common fault of decreased transmission rate because the destination should receive the decodable compositions of symbols from the source and the relay. In order to achieve high data rate, we propose a cooperative scheme that employs hierarchical modulation. This scheme is free from the rate loss and allows seamless cooperative communication.

Keywords: cooperative communication, hierarchical modulation, high data rate, transmission scheme

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7803 Artificial Neural Network for Forecasting of Daily Reservoir Inflow: Case Study of the Kotmale Reservoir in Sri Lanka

Authors: E. U. Dampage, Ovindi D. Bandara, Vinushi S. Waraketiya, Samitha S. R. De Silva, Yasiru S. Gunarathne

Abstract:

The knowledge of water inflow figures is paramount in decision making on the allocation for consumption for numerous purposes; irrigation, hydropower, domestic and industrial usage, and flood control. The understanding of how reservoir inflows are affected by different climatic and hydrological conditions is crucial to enable effective water management and downstream flood control. In this research, we propose a method using a Long Short Term Memory (LSTM) Artificial Neural Network (ANN) to assist the aforesaid decision-making process. The Kotmale reservoir, which is the uppermost reservoir in the Mahaweli reservoir complex in Sri Lanka, was used as the test bed for this research. The ANN uses the runoff in the Kotmale reservoir catchment area and the effect of Sea Surface Temperatures (SST) to make a forecast for seven days ahead. Three types of ANN are tested; Multi-Layer Perceptron (MLP), Convolutional Neural Network (CNN), and LSTM. The extensive field trials and validation endeavors found that the LSTM ANN provides superior performance in the aspects of accuracy and latency.

Keywords: convolutional neural network, CNN, inflow, long short-term memory, LSTM, multi-layer perceptron, MLP, neural network

Procedia PDF Downloads 134
7802 Succinct Perspective on the Implications of Intellectual Property Rights and 3rd Generation Partnership Project in the Rapidly Evolving Telecommunication Industry

Authors: Arnesh Vijay

Abstract:

Ever since its early introduction in the late 1980s, the mobile industry has been rapidly evolving with each passing year. The development witnessed is not just in its ability to support diverse applications, but also its extension into diverse technological means to access and offer various services to users. Amongst the various technologies present, radio systems have clearly emerged as a strong contender, due to its fine attributes of accessibility, reachability, interactiveness, and cost efficiency. These advancements have no doubt guaranteed unprecedented ease, utility and sophistication to the cell phone users, but caused uncertainty due to the interdependence of various systems, making it extremely complicated to exactly map concepts on to 3GPP (3rd Generation Partnership Project) standards. Although the close interrelation and interdependence of intellectual property rights and mobile standard specifications have been widely acknowledged by the technical and legal community; there, however, is a requirement for clear distinction between the scope and future-proof of inventions to influence standards and its market place adoptability. For this, collaborative work is required between intellectual property professionals, researchers, standardization specialists and country specific legal experts. With the evolution into next generation mobile technology, i.e., to 5G systems, there is a need for further work to be done in this field, which has been felt now more than ever before. Based on these lines, this poster will briefly describe the importance of intellectual property rights in the European market. More specifically, will analyse the role played by intellectual property in various standardization institutes, such as 3GPP (3rd generation partnership project) and ITU (International Telecommunications Union). The main intention: to ensure the scope and purpose is well defined, and concerned parties on all four sides are well informed on the clear significance of good proposals which not only bring economic revenue to the company but those that are capable of improving the technology and offer better services to mankind. The poster will comprise different sections. The first segment begins with a background on the rapidly evolving mobile technology, with a brief insight on the industrial impact of standards and its relation to intellectual property rights. Next, section two will succinctly outline the interplay between patents and standards; explicitly discussing the ever changing and rapidly evolving relationship between the two sectors. Then the remaining sections will examine ITU and its role played in international standards development, touching upon the various standardization process and the common patent policies and related guidelines. Finally, it proposes ways to improve the collaboration amongst various sectors for a more evolved and sophisticated next generation mobile telecommunication system. The sole purpose here is to discuss methods to reduce the gap and enhance the exchange of information between the two sectors to offer advanced technologies and services to mankind.

Keywords: mobile technology, mobile standards, intellectual property rights, 3GPP

Procedia PDF Downloads 118
7801 Students’ Level of Knowledge Construction and Pattern of Social Interaction in an Online Forum

Authors: K. Durairaj, I. N. Umar

Abstract:

The asynchronous discussion forum is one of the most widely used activities in learning management system environment. Online forum allows participants to interact, construct knowledge, and can be used to complement face to face sessions in blended learning courses. However, to what extent do the students perceive the benefits or advantages of forum remain to be seen. Through content and social network analyses, instructors will be able to gauge the students’ engagement and knowledge construction level. Thus, this study aims to analyze the students’ level of knowledge construction and their participation level that occur through online discussion. It also attempts to investigate the relationship between the level of knowledge construction and their social interaction patterns. The sample involves 23 students undertaking a master course in one public university in Malaysia. The asynchronous discussion forum was conducted for three weeks as part of the course requirement. The finding indicates that the level of knowledge construction is quite low. Also, the density value of 0.11 indicating that the overall communication among the participants in the forum is low. This study reveals that strong and significant correlations between SNA measures (in-degree centrality, out-degree centrality) and level of knowledge construction. Thus, allocating these active students in a different groups aids the interactive discussion takes place. Finally, based upon the findings, some recommendations to increase students’ level of knowledge construction and also for further research are proposed.

Keywords: asynchronous discussion forums, content analysis, knowledge construction, social network analysis

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7800 Further the Future: The Exploratory Study in 3D Animation Marketing Trend and Industry in Thailand

Authors: Pawit Mongkolprasit, Proud Arunrangsiwed

Abstract:

Lately, many media organizations in Thailand have started to produce 3D animation, so the quality of personnel should be identified. As an instructor in the school of Animation and Multimedia, the researchers have to prepare the students, suitable for the need of industry. The current study used exploratory research design to establish the knowledge of about this issue, including the required qualification of employees and the potential of animation industry in Thailand. The interview sessions involved three key informants from three well-known organizations. The interview data was used to design a questionnaire for the confirmation phase. The overall results showed that the industry needed an individual with 3D animation skill, computer graphic skills, good communication skills, a high responsibility, and an ability to finish the project on time. Moreover, it is also found that there were currently various kinds of media where 3D animation has been involved, such as films, TV variety, TV advertising, online advertising, and application on mobile device.

Keywords: 3D animation, animation industry, marketing trend, Thailand animation

Procedia PDF Downloads 278
7799 Artificial Intelligent-Based Approaches for Task ‎Offloading, ‎Resource ‎Allocation and Service ‎Placement of ‎Internet of Things ‎Applications: State of the Art

Authors: Fatima Z. Cherhabil, Mammar Sedrati, Sonia-Sabrina Bendib‎

Abstract:

In order to support the continued growth, critical latency of ‎IoT ‎applications, and ‎various obstacles of traditional data centers, ‎mobile edge ‎computing (MEC) has ‎emerged as a promising solution that extends cloud data-processing and decision-making to edge devices. ‎By adopting a MEC structure, IoT applications could be executed ‎locally, on ‎an edge server, different fog nodes, or distant cloud ‎data centers. However, we are ‎often ‎faced with wanting to optimize conflicting criteria such as ‎minimizing energy ‎consumption of limited local capabilities (in terms of CPU, RAM, storage, bandwidth) of mobile edge ‎devices and trying to ‎keep ‎high performance (reducing ‎response time, increasing throughput and service availability) ‎at the same ‎time‎. Achieving one goal may affect the other, making task offloading (TO), ‎resource allocation (RA), and service placement (SP) complex ‎processes. ‎It is a nontrivial multi-objective optimization ‎problem ‎to study the trade-off between conflicting criteria. ‎The paper provides a survey on different TO, SP, and RA recent multi-‎objective optimization (MOO) approaches used in edge computing environments, particularly artificial intelligent (AI) ones, to satisfy various objectives, constraints, and dynamic conditions related to IoT applications‎.

Keywords: mobile edge computing, multi-objective optimization, artificial ‎intelligence ‎approaches, task offloading, resource allocation, ‎ service placement

Procedia PDF Downloads 96
7798 Development of Terrorist Threat Prediction Model in Indonesia by Using Bayesian Network

Authors: Hilya Mudrika Arini, Nur Aini Masruroh, Budi Hartono

Abstract:

There are more than 20 terrorist threats from 2002 to 2012 in Indonesia. Despite of this fact, preventive solution through studies in the field of national security in Indonesia has not been conducted comprehensively. This study aims to provide a preventive solution by developing prediction model of the terrorist threat in Indonesia by using Bayesian network. There are eight stages to build the model, started from literature review, build and verify Bayesian belief network to what-if scenario. In order to build the model, four experts from different perspectives are utilized. This study finds several significant findings. First, news and the readiness of terrorist group are the most influent factor. Second, according to several scenarios of the news portion, it can be concluded that the higher positive news proportion, the higher probability of terrorist threat will occur. Therefore, the preventive solution to reduce the terrorist threat in Indonesia based on the model is by keeping the positive news portion to a maximum of 38%.

Keywords: Bayesian network, decision analysis, national security system, text mining

Procedia PDF Downloads 379
7797 Synchronization of Semiconductor Laser Networks

Authors: R. M. López-Gutiérrez, L. Cardoza-Avendaño, H. Cervantes-de Ávila, J. A. Michel-Macarty, C. Cruz-Hernández, A. Arellano-Delgado, R. Carmona-Rodríguez

Abstract:

In this paper, synchronization of multiple chaotic semiconductor lasers is achieved by appealing to complex system theory. In particular, we consider dynamical networks composed by semiconductor laser, as interconnected nodes, where the interaction in the networks are defined by coupling the first state of each node. An interesting case is synchronized with master-slave configuration in star topology. Nodes of these networks are modeled for the laser and simulated by Matlab. These results are applicable to private communication.

Keywords: chaotic laser, network, star topology, synchronization

Procedia PDF Downloads 547
7796 Combining an Optimized Closed Principal Curve-Based Method and Evolutionary Neural Network for Ultrasound Prostate Segmentation

Authors: Tao Peng, Jing Zhao, Yanqing Xu, Jing Cai

Abstract:

Due to missing/ambiguous boundaries between the prostate and neighboring structures, the presence of shadow artifacts, as well as the large variability in prostate shapes, ultrasound prostate segmentation is challenging. To handle these issues, this paper develops a hybrid method for ultrasound prostate segmentation by combining an optimized closed principal curve-based method and the evolutionary neural network; the former can fit curves with great curvature and generate a contour composed of line segments connected by sorted vertices, and the latter is used to express an appropriate map function (represented by parameters of evolutionary neural network) for generating the smooth prostate contour to match the ground truth contour. Both qualitative and quantitative experimental results showed that our proposed method obtains accurate and robust performances.

Keywords: ultrasound prostate segmentation, optimized closed polygonal segment method, evolutionary neural network, smooth mathematical model, principal curve

Procedia PDF Downloads 179
7795 Forecasting Optimal Production Program Using Profitability Optimization by Genetic Algorithm and Neural Network

Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

Abstract:

In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

Procedia PDF Downloads 426
7794 Optimizing Road Transportation Network Considering the Durability Factors

Authors: Yapegue Bayogo, Ahmadou Halassi Dicko, Brahima Songore

Abstract:

In developing countries, the road transportation system occupies an important place because of its flexibility and the low prices of infrastructure and rolling stock. While road transport is necessary for economic development, the movement of people and their goods, it is urgent to use transportation systems that minimize carbon emissions in order to ensure sustainable development. One of the main objectives of OEDC and the Word Bank is to ensure sustainable economic’ development. This paper aims to develop a road transport network taking into account environmental impacts. The methodology adopted consists of formulating a model optimizing the flow of goods and then collecting information relating to the transport of products. Our model was tested with data on product transport in CMDT areas in the Republic of Mali. The results of our study indicate that emissions from the transport sector can be significantly reduced by minimizing the traffic volume. According to our study, optimizing the transportation network, we benefit from a significant amount of tons of CO₂.

Keywords: road transport, transport sustainability, pollution, flexibility, optimized network

Procedia PDF Downloads 133
7793 An Analysis of Brand-Building Characteristics in the Iran Airline Websites

Authors: Pedram Behyar, Zahra Bayat

Abstract:

The internet and web are changing ways of “far reaching scope and potential for transformation of the marketing functions”. The web is developing in a faster rate than any previous new communication medium. The website of destination has become a crucial branding channel, that is why all businesses are changing their way to communicate with their customers to encounter their needs and wants in better ways. Website provides numerous opportunities for businesses to strengthen their relationship with their customers. One of these opportunities is website component that enables internet users to make two-way communication with the businesses.

Keywords: marketing communication, brand image, usability, privacy and security, personalization and customization, responsiveness, customer online web experience

Procedia PDF Downloads 483
7792 A Case Study of Remote Location Viewing, and Its Significance in Mobile Learning

Authors: James Gallagher, Phillip Benachour

Abstract:

As location aware mobile technologies become ever more omnipresent, the prospect of exploiting their context awareness to enforce learning approaches thrives. Utilizing the growing acceptance of ubiquitous computing, and the steady progress both in accuracy and battery usage of pervasive devices, we present a case study of remote location viewing, how the application can be utilized to support mobile learning in situ using an existing scenario. Through the case study we introduce a new innovative application: Mobipeek based around a request/response protocol for the viewing of a remote location and explore how this can apply both as part of a teacher lead activity and informal learning situations. The system developed allows a user to select a point on a map, and send a request. Users can attach messages alongside time and distance constraints. Users within the bounds of the request can respond with an image, and accompanying message, providing context to the response. This application can be used alongside a structured learning activity such as the use of mobile phone cameras outdoors as part of an interactive lesson. An example of a learning activity would be to collect photos in the wild about plants, vegetation, and foliage as part of a geography or environmental science lesson. Another example could be to take photos of architectural buildings and monuments as part of an architecture course. These images can be uploaded then displayed back in the classroom for students to share their experiences and compare their findings with their peers. This can help to fosters students’ active participation while helping students to understand lessons in a more interesting and effective way. Mobipeek could augment the student learning experience by providing further interaction with other peers in a remote location. The activity can be part of a wider study between schools in different areas of the country enabling the sharing and interaction between more participants. Remote location viewing can be used to access images in a specific location. The choice of location will depend on the activity and lesson. For example architectural buildings of a specific period can be shared between two or more cities. The augmentation of the learning experience can be manifested in the different contextual and cultural influences as well as the sharing of images from different locations. In addition to the implementation of Mobipeek, we strive to analyse this application, and a subset of other possible and further solutions targeted towards making learning more engaging. Consideration is given to the benefits of such a system, privacy concerns, and feasibility of widespread usage. We also propose elements of “gamification”, in an attempt to further the engagement derived from such a tool and encourage usage. We conclude by identifying limitations, both from a technical, and a mobile learning perspective.

Keywords: context aware, location aware, mobile learning, remote viewing

Procedia PDF Downloads 276
7791 An Integrated Label Propagation Network for Structural Condition Assessment

Authors: Qingsong Xiong, Cheng Yuan, Qingzhao Kong, Haibei Xiong

Abstract:

Deep-learning-driven approaches based on vibration responses have attracted larger attention in rapid structural condition assessment while obtaining sufficient measured training data with corresponding labels is relevantly costly and even inaccessible in practical engineering. This study proposes an integrated label propagation network for structural condition assessment, which is able to diffuse the labels from continuously-generating measurements by intact structure to those of missing labels of damage scenarios. The integrated network is embedded with damage-sensitive features extraction by deep autoencoder and pseudo-labels propagation by optimized fuzzy clustering, the architecture and mechanism which are elaborated. With a sophisticated network design and specified strategies for improving performance, the present network achieves to extends the superiority of self-supervised representation learning, unsupervised fuzzy clustering and supervised classification algorithms into an integration aiming at assessing damage conditions. Both numerical simulations and full-scale laboratory shaking table tests of a two-story building structure were conducted to validate its capability of detecting post-earthquake damage. The identifying accuracy of a present network was 0.95 in numerical validations and an average 0.86 in laboratory case studies, respectively. It should be noted that the whole training procedure of all involved models in the network stringently doesn’t rely upon any labeled data of damage scenarios but only several samples of intact structure, which indicates a significant superiority in model adaptability and feasible applicability in practice.

Keywords: autoencoder, condition assessment, fuzzy clustering, label propagation

Procedia PDF Downloads 83
7790 Design of Bidirectional Wavelength Division Multiplexing Passive Optical Network in Optisystem Environment

Authors: Ashiq Hussain, Mahwash Hussain, Zeenat Parveen

Abstract:

Now a days the demand for broadband service has increased. Due to which the researchers are trying to find a solution to provide a large amount of service. There is a shortage of bandwidth because of the use of downloading video, voice and data. One of the solutions to overcome this shortage of bandwidth is to provide the communication system with passive optical components. We have increased the data rate in this system. From experimental results we have concluded that the quality factor has increased by adding passive optical networks.

Keywords: WDM-PON, optical fiber, BER, Q-factor, eye diagram

Procedia PDF Downloads 487