Search results for: communication network

Authors: Yating Yang, Xue Zhang, Chengli Zhao

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In the increasingly interconnected global environment brought about by globalization, it is crucial for countries to timely grasp the development motivations in relevant research fields of other countries and seize development opportunities. Motivation, as the intrinsic driving force behind actions, is abstract in nature, making it difficult to directly measure and evaluate. Drawing on the ideas of social influence network theory, the research motivations of a country can be understood as the driving force behind the development of its science and technology sector, which is simultaneously influenced by both the country itself and other countries/regions. In response to this issue, this paper improves upon Friedkin's social influence network theory and applies it to motivation description, constructing a dynamic alliance network and hostile network centered around the United States and China, as well as a sensitivity matrix, to remotely assess the changes in national research motivations under the influence of international relations. Taking artificial intelligence as a case study, the research reveals that the motivations of most countries/regions are declining, gradually shifting from a neutral attitude to a negative one. The motivation of the United States is hardly influenced by other countries/regions and remains at a high level, while the motivation of China has been consistently increasing in recent years. By comparing the results with real data, it is found that this model can reflect, to some extent, the trends in national motivations.

Keywords: influence network theory, remote assessment, relation matrix, dynamic sensitivity matrix

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Authors: Tim Farrelly

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In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

Procedia PDF Downloads 136

Authors: Sung-Bok Choi, Hyun-Jun Shin, Hyoung-Kyu Song

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This paper proposes a single relay selection scheme in cooperative communication. Decode and forward scheme is considered when a source node wants to cooperate with a single relay for data transmission. To use the proposed single relay selection scheme, the source node make a little different pattern signal which is not complex pattern and broadcasts it. The proposed scheme does not require the channel state information between the source node and candidates of the relay during the relay selection. Therefore, it is able to be used in many fields.

Keywords: relay selection, cooperative communication, df, channel codes

Procedia PDF Downloads 660

Authors: Divvela Vishnu Sai Kumar, Deepak Arora, Sheenu Rizvi

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Forecasting a cyclone through satellite images consists of the estimation of the intensity of the cyclone and predicting it before a cyclone comes. This research work can help people to take safety measures before the cyclone comes. The prediction of the intensity of a cyclone is very important to save lives and minimize the damage caused by cyclones. These cyclones are very costliest natural disasters that cause a lot of damage globally due to a lot of hazards. Authors have proposed five different CNN (Convolutional Neural Network) models that estimate the intensity of cyclones through INSAT-3D IR images. There are a lot of techniques that are used to estimate the intensity; the best model proposed by authors estimates intensity with a root mean squared error (RMSE) of 10.02 kts.

Keywords: estimating cyclone intensity, deep learning, convolution neural network, prediction models

Procedia PDF Downloads 110

Authors: Zohreh Moghaddas, Morteza Yazdani, Farhad Hosseinzadeh

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Nowadays, data envelopment analysis (DEA) models featuring network structures have gained widespread usage for evaluating the performance of production systems and activities (Decision-Making Units (DMUs)) across diverse fields. By examining the relationships between the internal stages of the network, these models offer valuable insights to managers and decision-makers regarding the performance of each stage and its impact on the overall network. To further empower system decision-makers, the inverse data envelopment analysis (IDEA) model has been introduced. This model allows the estimation of crucial information for estimating parameters while keeping the efficiency score unchanged or improved, enabling analysis of the sensitivity of system inputs or outputs according to managers' preferences. This empowers managers to apply their preferences and policies on resources, such as inputs and outputs, and analyze various aspects like production, resource allocation processes, and resource efficiency enhancement within the system. The results obtained can be instrumental in making informed decisions in the future. The top result of this study is an analysis of infeasibility and incorrect estimation that may arise in the theory and application of the inverse model of data envelopment analysis with network structures. By addressing these pitfalls, novel protocols are proposed to circumvent these shortcomings effectively. Subsequently, several theoretical and applied problems are examined and resolved through insightful case studies.

Keywords: inverse models of data envelopment analysis, series network, estimation of inputs and outputs, efficiency, resource allocation, sensitivity analysis, infeasibility

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Authors: B. J. Kim, K. W. Nam, S. J. Lee

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Traditional social network services provide users with more information than is needed, and it is not easy to verify the authenticity of the information. This paper proposes a system that can only post messages where users are located to enhance the reliability of social networking services. The proposed system implements a Google Map API to post postings on the map and to read postings within a range of distances from the users’ location. The proposed system will only provide alerts, memories, and information about locations within a given range depending on the users' current location, providing reliable information that they believe will be necessary in real time. It is expected that the proposed system will be able to meet the real demands of users and create a more reliable social network services environment.

Keywords: social network, location, reliability, posting

Procedia PDF Downloads 247

Authors: Cristian Pauna

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Trading the financial markets is a widespread activity today. A large number of investors, companies, public of private funds are buying and selling every day in order to make profit. Algorithmic trading is the prevalent method to make the trade decisions after the electronic trading release. The orders are sent almost instantly by computers using mathematical models. This paper will present a price prediction methodology based on a multi-dimensional neural network. Using the Fisher transform, the neural network will be instructed for a low-latency auto-adaptive process in order to predict the price evolution for the next period of time. The model is designed especially for algorithmic trading and uses the real-time price series. It was found that the characteristics of the Fisher function applied at the nodes scale level can generate reliable trading signals using the neural network methodology. After real time tests it was found that this method can be applied in any timeframe to trade the financial markets. The paper will also include the steps to implement the presented methodology into an automated trading system. Real trading results will be displayed and analyzed in order to qualify the model. As conclusion, the compared results will reveal that the neural network methodology applied together with the Fisher transform at the nodes level can generate a good price prediction and can build reliable trading signals for algorithmic trading.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, neural network

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Authors: Si-Gwan Kim

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Small-size and low-power sensors with sensing, signal processing and wireless communication capabilities is suitable for the wireless sensor networks. Due to the limited resources and battery constraints, complex routing algorithms used for the ad-hoc networks cannot be employed in sensor networks. In this paper, we propose node-disjoint multi-path hexagon-based routing algorithms in wireless sensor networks. We suggest the details of the algorithm and compare it with other works. Simulation results show that the proposed scheme achieves better performance in terms of efficiency and message delivery ratio.

Keywords: clustering, multi-path, routing protocol, sensor network

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Authors: Giuseppe Timperio, Robert De Souza

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The combination of factors such as temperamental climate change, rampant urbanization of risk exposed areas, political and social instabilities, is posing an alarming base for the further growth of number and magnitude of humanitarian crises worldwide. Given the unique features of humanitarian supply chain such as unpredictability of demand in space, time, and geography, spike in the number of requests for relief items in the first days after the calamity, uncertain state of logistics infrastructures, large volumes of unsolicited low-priority items, a proactive approach towards design of disaster response operations is needed to achieve high agility in mobilization of emergency supplies in the immediate aftermath of the event. This paper is an attempt in that direction, and it provides decision makers with crucial strategic insights for a more effective network design for disaster response. Decision sciences and ICT are integrated to analyse the robustness and resilience of a prepositioned network of emergency strategic stockpiles for a real-life case about Indonesia, one of the most vulnerable countries in Asia-Pacific, with the model being built upon a rich set of quantitative data. At this aim, a network optimization approach was implemented, with several what-if scenarios being accurately developed and tested. Findings of this study are able to support decision makers facing challenges related with disaster relief chains resilience, particularly about optimal configuration of supply chain facilities and optimal flows across the nodes, while considering the network structure from an end-to-end in-country distribution perspective.

Keywords: disaster preparedness, humanitarian logistics, network optimization, resilience

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Authors: Gurmail Singh

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Effective supply chain is the main priority of every organization which is the outcome of strategic corporate investments with deliberate management action. Value-driven supply chain is defined through development, procurement and by configuring the appropriate resources, metrics and processes. However, responsiveness of the supply chain can be improved by proper coordination. So the Bullwhip effect (BWE) and Net stock amplification (NSAmp) values were anticipated and used for the control of inventory in organizations by both discrete wavelet transform-Artificial neural network (DWT-ANN) and Adaptive Network-based fuzzy inference system (ANFIS). This work presents a comparative methodology of forecasting for the customers demand which is non linear in nature for a multilevel supply chain structure using hybrid techniques such as Artificial intelligence techniques including Artificial neural networks (ANN) and Adaptive Network-based fuzzy inference system (ANFIS) and Discrete wavelet theory (DWT). The productiveness of these forecasting models are shown by computing the data from real world problems for Bullwhip effect and Net stock amplification. The results showed that these parameters were comparatively less in case of discrete wavelet transform-Artificial neural network (DWT-ANN) model and using Adaptive network-based fuzzy inference system (ANFIS).

Keywords: bullwhip effect, hybrid techniques, net stock amplification, supply chain flexibility

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Authors: Suphaphon Udomluck, Pannathorn Chachvarat

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Information Communication Technology (ICT) using management is essential for effective decision making in organization. The Concerns Based Adoption Model (CBAM) was employed as the conceptual framework. The purposes of the study were to assess the situation of Information Communication Technology (ICT) using management in College of Nursing under the Praboromarajchanok Institute. The samples were multi – stage sampling of 10 colleges of nursing that participated include directors, vice directors, head of learning groups, teachers, system administrator and responsible for ICT. The total participants were 280; the instrument used were questionnaires that include 4 parts, general information, Information Communication Technology (ICT) using management, the Stage of concern Questionnaires (SoC), and the Levels of Use (LoU) ICT Questionnaires respectively. Reliability coefficients were tested; alpha coefficients were 0.967for Information Communication Technology (ICT) using management, 0.884 for SoC and 0.945 for LoU. The data were analyzed by frequency, percentage, mean, standard deviation, Pearson Product Moment Correlation and Multiple Regression. They were founded as follows: The high level overall score of Information Communication Technology (ICT) using management and issue were administration, hardware, software, and people. The overall score of the Stage of concern (SoC)ICTis at high level and the overall score of the Levels of Use (LoU) ICTis at moderate. The Information Communication Technology (ICT) using management had the positive relationship with the Stage of concern (SoC)ICTand the Levels of Use (LoU) ICT(p < .01). The results of Multiple Regression revealed that administration hardwear, software and people ware could predict SoC of ICT (18.5%) and LoU of ICT (20.8%).The factors that were significantly influenced by SoCs were people ware. The factors that were significantly influenced by LoU of ICT were administration hardware and people ware.

Keywords: information communication technology (ICT), management, the concerns-based adoption model (CBAM), stage of concern(SoC), the levels of use(LoU)

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Authors: Pierre Nicole Patriarca

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This study examined the attachment styles, parent-child relationship, and romantic relationship quality of five illegitimate emerging adults aged 18 to 23 years old. The researcher used self-report measures, inventory of parent and peer attachment, attachment style questionnaire, and network of relationship – relationship quality version in obtaining data. A semi-structured interview was also used to acquire qualitative data about the detailed perception and experiences on the attachment styles and parent-child relationship. Common themes of each variable were identified through thematic analysis. Results showed that four out of five participants depicted positive relationship to their fathers, while all of them reported to have positive relationship to their mothers. It was also found that four participants have preoccupied attachment style, while the other one has fearful attachment style. Common themes in describing their relationship with their mother include being close, influential to participants’ life, unbounded communication, favorable reason of trusting, and sometimes being inattentive. On the other hand, having distant relationship, limited communication about romantic relationship, uninfluential to participant’s life, and favorable reason of trusting were the common themes in describing relationship with father. Lastly, less trusting, being dependent, and emphasis on valuing intimacy were the common themes in describing their style of attachment.

Keywords: illegitimate, emerging adult, attachment, parent-child relationship, relationship quality

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Authors: Shokoufeh Monjezi Kouchak

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Cognitive radio network (CRN) is future network .Without this network wireless devices can’t work appropriately in the next decades. Today, wireless devices use static spectrum access methods and these methods don’t use spectrums optimum so we need use dynamic spectrum access methods to solve shortage spectrum challenge and CR is a great device for DSA but first of all its challenges should be solved .security is one of these challenges .In this paper we provided a survey about CR security. You can see this survey in tables 1 to 7 .After that we proposed a multi criteria authentication method in CRN. Our criteria in this method are: sensing results, following sending data rules, position of secondary users and no talk zone. Finally we compared our method with other authentication methods.

Keywords: authentication, cognitive radio, security, radio networks

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Authors: Mouhammad Alkasassbeh, Mohammad Almseidin

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Network security engineers work to keep services available all the time by handling intruder attacks. Intrusion Detection System (IDS) is one of the obtainable mechanisms that is used to sense and classify any abnormal actions. Therefore, the IDS must be always up to date with the latest intruder attacks signatures to preserve confidentiality, integrity, and availability of the services. The speed of the IDS is a very important issue as well learning the new attacks. This research work illustrates how the Knowledge Discovery and Data Mining (or Knowledge Discovery in Databases) KDD dataset is very handy for testing and evaluating different Machine Learning Techniques. It mainly focuses on the KDD preprocess part in order to prepare a decent and fair experimental data set. The J48, MLP, and Bayes Network classifiers have been chosen for this study. It has been proven that the J48 classifier has achieved the highest accuracy rate for detecting and classifying all KDD dataset attacks, which are of type DOS, R2L, U2R, and PROBE.

Keywords: IDS, DDoS, MLP, KDD

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Authors: A. Azari, S. S. K. Seyyedi

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One of the unaddressed and open challenges in the nano-networking is the characteristics of noise. The previous analysis, however, has concentrated on end-to-end communication model with no separate modelings for propagation channel and noise. By considering a separate signal propagation and noise model, the design and implementation of an optimum receiver will be much easier. In this paper, we justify consideration of a separate additive Gaussian noise model of a nano-communication system based on the molecular communication channel for which are applicable for MSK and MOSK modulation schemes. The presented noise analysis is based on the Brownian motion process, and advection molecular statistics, where the received random signal has a probability density function whose mean is equal to the mean number of the received molecules. Finally, the justification of received signal magnitude being uncorrelated with additive non-stationary white noise is provided.

Keywords: molecular, noise, diffusion, channel

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Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

Procedia PDF Downloads 453

Authors: Nidal F. Shilbayeh, Sameh T. Khuffash, Mohammad H. Allymoun, Reem Al-Saidi

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There is a real threat on the VIPs personal pages on the Social Network Sites (SNS). The real threats to these pages is violation of privacy and theft of identity through creating fake pages that exploit their names and pictures to attract the victims and spread of lies. In this paper, we propose a new secure architecture that improves the trusting and finds an effective solution to reduce fake pages and possibility of recognizing VIP pages on SNS. The proposed architecture works as a third party that is added to Facebook to provide the trust service to personal pages for VIPs. Through this mechanism, it works to ensure the real identity of the applicant through the electronic authentication of personal information by storing this information within content of their website. As a result, the significance of the proposed architecture is that it secures and provides trust to the VIPs personal pages. Furthermore, it can help to discover fake page, protect the privacy, reduce crimes of personality-theft, and increase the sense of trust and satisfaction by friends and admirers in interacting with SNS.

Keywords: social network sites, online social network, privacy, trust, security and authentication

Procedia PDF Downloads 372

Authors: Laura Hervai

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One of the most significant phenomena of the 2000s was the emergence of social media sites and web 2.0 that revolutionized communication processes. Social networking platforms have fundamentally changed social and political participation of the public, which require organisations in the public and non-profit sector not only to adapt to these new trends but also to actively engage their audiences. Opportunity for interaction, freer expression of opinion and the proliferation of user generated content are major changes brought by web 2.0 technologies. Furthermore, due to the wide penetration of mobile technologies, social media sites are capable of connecting underdeveloped regions to the global flow of information. Taking advantage of these characteristics, organisations have the opportunity to engage much wider audiences, exploit new ways to raise awareness or reach out to regions that are difficult to access. The early adopters of these new communication tools soon recognized the need of developing social media guidelines for their organisations as well as the increased workload that they require. While ten years ago communication officers could handle their organisation’s social media presence, today it is a separate profession. International organisations face several challenges related to their social media presence. Early adopters have contributed to the development of best practices among which the ethics of social media usage still remained problematic. Another challenge for international organisations is to adapt to country-specific social media trends while they have to comply with the requirements of their parent organisation as well. However in the 21st century social media presence can be crucial to the successful operation of international organisations, their importance is still not taken seriously enough. The measurement of the effects and influence of social networking on the organisations’ productivity is an unsolved problem thus further research should focus on this matter. Research methods included primary research of major IGOs’ and NGOs’ social media presence and guidelines along with secondary research of social media statistics and scientific articles in the topic.

Keywords: international organisations, non-profit sector, NGO, social media, social network

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Authors: Manoj Kumar Dutta

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Wavelength division multiplexing (WDM) technology is the most promising technology for the proper utilization of huge raw bandwidth provided by an optical fiber. One of the key problems in implementing the all-optical WDM network is the packet contention. This problem can be solved by several different techniques. In time domain approach the packet contention can be reduced by incorporating fiber delay lines (FDLs) as optical buffer in the switch architecture. Different types of buffering architectures are reported in literatures. In the present paper a comparative performance analysis of three most popular FDL architectures are presented in order to obtain the best contention resolution performance. The analysis is further extended to consider the effect of different fiber non-linearities on the network performance.

Keywords: WDM network, contention resolution, optical buffering, non-linearity, throughput

Procedia PDF Downloads 438

Authors: Kamel Allaw, Jocelyne Adjizian Gerard, Makram Chehayeb, Nada Badaro Saliba

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In developing countries, such as Lebanon, the demographic data are hardly available due to the absence of the mechanization of population system. The aim of this study is to evaluate, using only remote sensing data, the correlations between the number of population and the characteristics of roads network (length of primary roads, length of secondary roads, total length of roads, density and percentage of roads and the number of intersections). In order to find the influence of the different factors on the demographic data, we studied the degree of correlation between each factor and the number of population. The results of this study have shown a strong correlation between the number of population and the density of roads and the number of intersections.

Keywords: population, road network, statistical correlations, remote sensing

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Authors: Gunasekaran Raja, Ramkumar Jayaraman

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In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed.

Keywords: cross layer network topology, concurrent scheduling, modularity value, network communities and weighted load balancing

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Authors: Lim Teck Beng, Thiha Kyaw, Poh Boon Kiat, Lee Ngai Meng

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This work presents discussion on the possibility of merging two emerging technologies in microwave; wireless power transfer (WPT) and RF energy harvesting. The current state of art of the two technologies is discussed and the strength and weakness of the two technologies is also presented. The equivalent circuit of wireless power transfer is modeled and explained as how the range and efficiency can be further increased by controlling certain parameters in the receiver. The different techniques of harvesting the RF energy from the ambient are also extensive study. Last but not least, we demonstrate that a low power wireless sensor network (WSN) can be power up by RF energy harvesting. The WSN is designed to transmit every 3 minutes of information containing the temperature of the environment and also the voltage of the node. One thing worth mention is both the sensors that are used for measurement are also powering up by the RF energy harvesting system.

Keywords: energy harvesting, wireless power transfer, wireless sensor network and magnetic coupled resonator

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Authors: Supranee Wattanasin

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This research study was a qualitative documentary research by using an in-depth interview with many experts in the field who has both knowledge and experience to provide information to create a strategic plan to enhance the students’ ethics. The findings revealed that there were five areas that require an attention. The five areas included honesty, accurate fact, human right, speed, and responsibility. The development of the strategic plan to enhance the ethics for students who major in communication arts can be concluded as follows. First, the government, private, and religion sectors need to come up together and set up the activities to promote the ethical standard in schools, universities, and organizations. Second, it is important to cultivate the knowledge that ethics is important of the professional jobs, especially in the mass communication and media. Third, the Philosophy of Sufficiency Economy should be brought to explain to students in order for them to have some immunity to the negative attitude such as drinking alcohol, gambling, cut classes, and cheating at exams. Fourth, experts in the field of ethics should be found to provide more knowledge to students and allow students to participate in activities that will increase their experience and knowledge of the real world problem.

Keywords: communication arts, ethics, mass communication, media, strategy

Procedia PDF Downloads 329

Authors: Jenny K. Ubaque, Edward P. Guillen, Juan S. Solórzano, Leonardo J. Ramírez

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The health care must be a right for people around the world, but in order to guarantee the access to all, it is necessary to overcome geographical barriers. Telemedicine take advantage of Information Communication Technologies to deploy health care services around the world. To achieve those goals, it is necessary to use existing last mile solution to create access for home users, which is why is necessary to establish the channel characteristics for those kinds of services. This paper presents an analysis of network performance of last mile solution for the use of IPTV broadcasting with the application of streaming for telemedicine apps.

Keywords: telemedicine, IPTV, GPON, ADSL2+, coaxial, jumbogram

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Authors: Carla Teixeira, Diana Azevedo, Jonatas Bessa, Maria Guilam

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The flipped classroom is a blended learning modality that combines face-to-face and virtual activities of self-learning, mediated by digital information and communication technologies, which reverses traditional teaching approaches and presents, as a presupposition, the previous study of contents by students. In the following face-to-face activities, the contents are discussed, producing active learning. This work aims to describe the systematization process of the use of flipped classrooms as a method to develop complementary national activities in PROFSAÚDE, a professional master's program in the area of public health, offered as a distance learning course, in the network, in Brazil. The complementary national activities were organized with the objective of strengthening and qualifying students´ learning process. The network gathers twenty-two public institutions of higher education in the country. Its national coordination conducted a survey to detect complementary educational needs, supposed to improve the formative process and align important content sums for the program nationally. The activities were organized both asynchronously, making study materials available in Google classrooms, and synchronously in a tele presential way, organized on virtual platforms to reach the largest number of students in the country. The asynchronous activities allowed each student to study at their own pace and the synchronous activities were intended for deepening and reflecting on the themes. The national team identified some professors' areas of expertise, who were contacted for the production of audiovisual content such as video classes and podcasts, guidance for supporting bibliographic materials and also to conduct synchronous activities together with the technical team. The contents posted in the virtual classroom were organized by modules and made available before the synchronous meeting; these modules, in turn, contain “pills of experience” that correspond to reports of teachers' experiences in relation to the different themes. In addition, activity was proposed, with questions aimed to expose doubts about the contents and a learning challenge, as a practical exercise. Synchronous activities are built with different invited teachers, based on the participants 'discussions, and are the forum where teachers can answer students' questions, providing feedback on the learning process. At the end of each complementary activity, an evaluation questionnaire is available. The responses analyses show that this institutional network experience, as pedagogical innovation, provides important tools to support teaching and research due to its potential in the participatory construction of learning, optimization of resources, the democratization of knowledge and sharing and strengthening of practical experiences on the network. One of its relevant aspects was the thematic diversity addressed through this method.

Keywords: active learning, flipped classroom, network education experience, pedagogic innovation

Procedia PDF Downloads 154

Authors: Abbas Raza Ali

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Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

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Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Christian Nounkeu Tatchou

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The concept of mediatization of politics describes changes with regards to media and politics, as the political sphere is increasingly shaped by the media and conforms to its logic. The mediatization of politics in established democracies of the West has been the object of several researches. However, there is an overwhelming paucity of literature on this reconfiguration of the political life around the media in the emerging democracies of the Sub-Saharan Africa. A majority of Sub-Saharan countries have been progressively experiencing the modernization of their societies and significant developments with respect to political communication since the early 1990s. This has been facilitated by factors such as the adoption of democratic reforms, the development of mass media, the advent of social media and the rapid spread of new information and communication technologies. Thus, this paper investigates the extent to which political communication in Sub-Saharan Africa is mediatized, especially with regards to the social media. Through in-depths interviews with twenty political leaders and political observers in Cameroon and Ghana, this article argues that the social media has become the main arena of voters’ mobilization and political participation in Sub-Saharan Africa. However, a greater extent of freedom for political activism on social media is observed in the new democracy of Ghana, unlike in the enduring authoritarian political system of Cameroon where the government attempts to control the use and content of political discourse on social media.

Keywords: mediatization, political communication, social media, sub-saharan africa

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Authors: Vladimir V. Nikulin, Bekmurza H. Aitchanov, Olimzhon A. Baimuratov

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Quantum communication technology takes advantage of the intrinsic properties of laser carriers, such as very high data rates and low power requirements, to offer unprecedented data security. Quantum processes at the physical layer of encryption are used for signal encryption with very competitive performance characteristics. The ultimate range of applications for QC systems spans from fiber-based to free-space links and from secure banking operations to mobile airborne and space-borne networking where they are subjected to channel distortions. Under practical conditions, the channel can alter the optical wave front characteristics, including its phase. In addition, phase noise of the communication source and photo-detection noises alter the signal to bring additional ambiguity into the measurement process. If quantized values of photons are used to encrypt the signal, exploitation of quantum communication links becomes extremely difficult. In this paper, we present the results of analysis and simulation studies of the effects of noise on phase estimation for quantum systems with different number of encryption bases and operating at different power levels.

Keywords: encryption, phase distortion, quantum communication, quantum noise

Procedia PDF Downloads 546

Authors: JaeHwan Yang, Da-Woon Jeong, Seung-Young Kho, Dong-Kyu Kim

Abstract:

In terms of ITS, information on link characteristic is an essential factor for plan or operation. But in practical cases, not every link has installed sensors on it. The link that does not have data on it is called “Missing Link”. The purpose of this study is to impute data of these missing links. To get these data, this study applies the machine learning method. With the machine learning process, especially for the deep learning process, missing link data can be estimated from present link data. For deep learning process, this study uses “Recurrent Neural Network” to take time-series data of road. As input data, Dedicated Short-range Communications (DSRC) data of Dalgubul-daero of Daegu Metropolitan Area had been fed into the learning process. Neural Network structure has 17 links with present data as input, 2 hidden layers, for 1 missing link data. As a result, forecasted data of target link show about 94% of accuracy compared with actual data.

Keywords: data estimation, link data, machine learning, road network

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