Search results for: mobile networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4173

Search results for: mobile networks

2073 Freedom with Limitations: The Nature of Free Expression in the European Case-Law

Authors: Laszlo Vari

Abstract:

In the digital age, the spread of the mobile world and the nature of the cyberspace, offers many new opportunities for the prevalence of the fundamental right to free expression, and therefore, for free speech and freedom of the press; however, these new information communication technologies carry many new challenges. Defamation, censorship, fake news, misleading information, hate speech, breach of copyright etc., are only some of the violations, all of which can be derived from the harmful exercise of freedom of expression, all which become more salient in the internet. Here raises the question: how can we eliminate these problems, and practice our fundamental freedom rightfully? To answer this question, we should understand the elements and the characteristic of the nature of freedom of expression, and the role of the actors whose duties and responsibilities are crucial in the prevalence of this fundamental freedom. To achieve this goal, this paper will explore the European practice to understand instructions found in the case-law of the European Court of Human rights for the rightful exercise of freedom of expression.

Keywords: collision of rights, European case-law, freedom opinion and expression, media law, freedom of information, online expression

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2072 Probabilistic Modeling Laser Transmitter

Authors: H. S. Kang

Abstract:

Coupled electrical and optical model for conversion of electrical energy into coherent optical energy for transmitter-receiver link by solid state device is presented. Probability distribution for travelling laser beam switching time intervals and the number of switchings in the time interval is obtained. Selector function mapping is employed to regulate optical data transmission speed. It is established that regulated laser transmission from PhotoActive Laser transmitter follows principal of invariance. This considerably simplifies design of PhotoActive Laser Transmission networks.

Keywords: computational mathematics, finite difference Markov chain methods, sequence spaces, singularly perturbed differential equations

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2071 Competences for Learning beyond the Academic Context

Authors: Cristina Galván-Fernández

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Students differentiate the different contexts of their lives as well as employment, hobbies or studies. In higher education is needed to transfer the experiential knowledge to theory and viceversa. However, is difficult to achieve than students use their personal experiences and social readings for get the learning evidences. In an experience with 178 education students from Chile and Spain we have used an e-portfolio system and a methodology for 4 years with the aims of help them to: 1) self-regulate their learning process and 2) use social networks and professional experiences for make the learning evidences. These two objectives have been controlled by interviews to the same students in different moments and two questionnaires. The results of this study show that students recognize the ownership of their learning and progress in planning and reflection of their own learning.

Keywords: competences, e-portfolio, higher education, self-regulation

Procedia PDF Downloads 285
2070 A Smart Visitors’ Notification System with Automatic Secure Door Lock Using Mobile Communication Technology

Authors: Rabail Shafique Satti, Sidra Ejaz, Madiha Arshad, Marwa Khalid, Sadia Majeed

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The paper presents the development of an automated security system to automate the entry of visitors, providing more flexibility of managing their record and securing homes or workplaces. Face recognition is part of this system to authenticate the visitors. A cost effective and SMS based door security module has been developed and integrated with the GSM network and made part of this system to allow communication between system and owner. This system functions in real time as when the visitor’s arrived it will detect and recognizes his face and on the result of face recognition process it will open the door for authorized visitors or notifies and allows the owner’s to take further action in case of unauthorized visitor. The proposed system is developed and it is successfully ensuring security, managing records and operating gate without physical interaction of owner.

Keywords: SMS, e-mail, GSM modem, authenticate, face recognition, authorized

Procedia PDF Downloads 778
2069 CO2 Utilization by Reverse Water-Shift and Fischer-Tropsch Synthesis for Production of Heavier Fraction Hydrocarbons in a Container-Sized Mobile Unit

Authors: Francisco Vidal Vázquez, Pekka Simell, Christian Frilund, Matti Reinikainen, Ilkka Hiltunen, Tim Böltken, Benjamin Andris, Paolo Piermartini

Abstract:

Carbon capture and utilization (CCU) are one of the key topics in mitigation of CO2 emissions. There are many different technologies that are applied for the production of diverse chemicals from CO2 such as synthetic natural gas, Fischer-Tropsch products, methanol and polymers. Power-to-Gas and Power-to-Liquids concepts arise as a synergetic solution for storing energy and producing value added products from the intermittent renewable energy sources and CCU. VTT is a research and technology development company having energy in transition as one of the key focus areas. VTT has extensive experience in piloting and upscaling of new energy and chemical processes. Recently, VTT has developed and commissioned a Mobile Synthesis Unit (MOBSU) in close collaboration with INERATEC, a spin-off company of Karlsruhe Institute of Technology (KIT, Germany). The MOBSU is a multipurpose synthesis unit for CO2 upgrading to energy carriers and chemicals, which can be transported on-site where CO2 emission and renewable energy are available. The MOBSU is initially used for production of fuel compounds and chemical intermediates by combination of two consecutive processes: reverse Water-Gas Shift (rWGS) and Fischer-Tropsch synthesis (FT). First, CO2 is converted to CO by high-pressure rWGS and then, the CO and H2 rich effluent is used as feed for FT using an intensified reactor technology developed and designed by INERATEC. Chemical equilibrium of rWGS reaction is not affected by pressure. Nevertheless, compression would be required in between rWGS and FT in the case when rWGS is operated at atmospheric pressure. This would also require cooling of rWGS effluent, water removal and reheating. For that reason, rWGS is operated using precious metal catalyst in the MOBSU at similar pressure as FT to simplify the process. However, operating rWGS at high pressures has also some disadvantages such as methane and carbon formation, and more demanding specifications for materials. The main parts of FT module are an intensified reactor, a hot trap to condense the FT wax products, and a cold trap to condense the FT liquid products. The FT synthesis is performed using cobalt catalyst in a novel compact reactor technology with integrated highly-efficient water evaporation cooling cycle. The MOBSU started operation in November 2016. First, the FT module is tested using as feedstock H2 and CO. Subsequently, rWGS and FT modules are operated together using CO2 and H2 as feedstock of ca. 5 Nm3/hr total flowrate. On spring 2017, The MOBSU unit will be integrated together with a direct air capture (DAC) of CO2 unit, and a PEM electrolyser unit at Lappeenranta University of Technology (LUT) premises for demonstration of the SoletAir concept. This would be the first time when synthetic fuels are produced by combination of DAC unit and electrolyser unit which uses solar power for H2 production.

Keywords: CO2 utilization, demonstration, Fischer-Tropsch synthesis, intensified reactors, reverse water-gas shift

Procedia PDF Downloads 280
2068 Dual-Polarized Multi-Antenna System for Massive MIMO Cellular Communications

Authors: Naser Ojaroudi Parchin, Haleh Jahanbakhsh Basherlou, Raed A. Abd-Alhameed, Peter S. Excell

Abstract:

In this paper, a multiple-input/multiple-output (MIMO) antenna design with polarization and radiation pattern diversity is presented for future smartphones. The configuration of the design consists of four double-fed circular-ring antenna elements located at different edges of the printed circuit board (PCB) with an FR-4 substrate and overall dimension of 75×150 mm2. The antenna elements are fed by 50-Ohm microstrip-lines and provide polarization and radiation pattern diversity function due to the orthogonal placement of their feed lines. A good impedance bandwidth (S11 ≤ -10 dB) of 3.4-3.8 GHz has been obtained for the smartphone antenna array. However, for S11 ≤ -6 dB, this value is 3.25-3.95 GHz. More than 3 dB realized gain and 80% total efficiency are achieved for the single-element radiator. The presented design not only provides the required radiation coverage but also generates the polarization diversity characteristic.

Keywords: cellular communications, multiple-input/multiple-output systems, mobile-phone antenna, polarization diversity

Procedia PDF Downloads 127
2067 Artificial Intelligence in Duolingo

Authors: Elana Mahboub, Lamar Bakhurji, Hind Alhindi, Sara Alesayi

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Duolingo is a revolutionary language learning platform that offers an interactive and accessible learning experience. Its gamified approach makes language learning engaging and enjoyable, with a diverse range of languages available. The platform's adaptive learning system tailors lessons to individual proficiency levels, ensuring a personalized and efficient learning journey. The incorporation of multimedia elements enhances the learning experience and promotes practical language application. Duolingo's success is attributed to its mobile accessibility, offering basic access to language courses for free, with optional premium features for those seeking additional resources. Research shows positive outcomes for users, and the app's global impact extends beyond individual learning to formal language education initiatives. Duolingo is a transformative force in language education, breaking down barriers and making language learning an attainable goal for millions worldwide.

Keywords: duolingo, artificial intelligence, artificial intelligence in duolingo, benefit of artificial intelligence

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2066 Capital Mobility in Savings and Investment across China and the ASEAN-5: Evidence from Recursive Cointegration

Authors: Chang Lee Shu-Jung, Mei-Se Chien, Chien-Chiang Lee, Hui-Ting Hu

Abstract:

This paper applies recursive cointegration analysis to examine the dynamic changes in Feldstein-Horioka saving-investment (S-I) coefficients across China and the ASEAN-5 countries over time. To the extent that the S-I coefficients measure international capital mobility, the main empirical results are as follows. The recursive trace statistics show that the investment- savings nexus varies in these six countries. There is no cointegration between investment and savings in three countries (China, Malaysia, and Singapore), which means that the mobility of the capital markets in the three is high and that domestic investment in them will be financed by the global pool of capital. As to the other three countries (Indonesia, Thailand, and Philippines), there is cointegration between investment and savings for part of the sample period in the three, including before 2002 for Thailand, before 2001 for Indonesia, and before 2002 for Philippines. This shows these three countries achieved highly mobile and open capital markets later.

Keywords: investment, savings, recursive cointegration test, ASEAN, China

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2065 Determine the Optimal Path of Content Adaptation Services with Max Heap Tree

Authors: Shilan Rahmani Azr, Siavash Emtiyaz

Abstract:

Recent development in computing and communicative technologies leads to much easier mobile accessibility to the information. Users can access to the information in different places using various deceives in which the care variety of abilities. Meanwhile, the format and details of electronic documents are changing each day. In these cases, a mismatch is created between content and client’s abilities. Recently the service-oriented content adaption has been developed which the adapting tasks are dedicated to some extended services. In this method, the main problem is to choose the best appropriate service among accessible and distributed services. In this paper, a method for determining the optimal path to the best services, based on the quality control parameters and user preferences, is proposed using max heap tree. The efficiency of this method in contrast to the other previous methods of the content adaptation is related to the determining the optimal path of the best services which are measured. The results show the advantages and progresses of this method in compare of the others.

Keywords: service-oriented content adaption, QoS, max heap tree, web services

Procedia PDF Downloads 243
2064 Revolutionizing Financial Forecasts: Enhancing Predictions with Graph Convolutional Networks (GCN) - Long Short-Term Memory (LSTM) Fusion

Authors: Ali Kazemi

Abstract:

Those within the volatile and interconnected international economic markets, appropriately predicting market trends, hold substantial fees for traders and financial establishments. Traditional device mastering strategies have made full-size strides in forecasting marketplace movements; however, monetary data's complicated and networked nature calls for extra sophisticated processes. This observation offers a groundbreaking method for monetary marketplace prediction that leverages the synergistic capability of Graph Convolutional Networks (GCNs) and Long Short-Term Memory (LSTM) networks. Our suggested algorithm is meticulously designed to forecast the traits of inventory market indices and cryptocurrency costs, utilizing a comprehensive dataset spanning from January 1, 2015, to December 31, 2023. This era, marked by sizable volatility and transformation in financial markets, affords a solid basis for schooling and checking out our predictive version. Our algorithm integrates diverse facts to construct a dynamic economic graph that correctly reflects market intricacies. We meticulously collect opening, closing, and high and low costs daily for key inventory marketplace indices (e.g., S&P 500, NASDAQ) and widespread cryptocurrencies (e.g., Bitcoin, Ethereum), ensuring a holistic view of marketplace traits. Daily trading volumes are also incorporated to seize marketplace pastime and liquidity, providing critical insights into the market's shopping for and selling dynamics. Furthermore, recognizing the profound influence of the monetary surroundings on financial markets, we integrate critical macroeconomic signs with hobby fees, inflation rates, GDP increase, and unemployment costs into our model. Our GCN algorithm is adept at learning the relational patterns amongst specific financial devices represented as nodes in a comprehensive market graph. Edges in this graph encapsulate the relationships based totally on co-movement styles and sentiment correlations, enabling our version to grasp the complicated community of influences governing marketplace moves. Complementing this, our LSTM algorithm is trained on sequences of the spatial-temporal illustration discovered through the GCN, enriched with historic fee and extent records. This lets the LSTM seize and expect temporal marketplace developments accurately. Inside the complete assessment of our GCN-LSTM algorithm across the inventory marketplace and cryptocurrency datasets, the version confirmed advanced predictive accuracy and profitability compared to conventional and opportunity machine learning to know benchmarks. Specifically, the model performed a Mean Absolute Error (MAE) of 0.85%, indicating high precision in predicting day-by-day charge movements. The RMSE was recorded at 1.2%, underscoring the model's effectiveness in minimizing tremendous prediction mistakes, which is vital in volatile markets. Furthermore, when assessing the model's predictive performance on directional market movements, it achieved an accuracy rate of 78%, significantly outperforming the benchmark models, averaging an accuracy of 65%. This high degree of accuracy is instrumental for techniques that predict the course of price moves. This study showcases the efficacy of mixing graph-based totally and sequential deep learning knowledge in economic marketplace prediction and highlights the fee of a comprehensive, records-pushed evaluation framework. Our findings promise to revolutionize investment techniques and hazard management practices, offering investors and economic analysts a powerful device to navigate the complexities of cutting-edge economic markets.

Keywords: financial market prediction, graph convolutional networks (GCNs), long short-term memory (LSTM), cryptocurrency forecasting

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2063 The Use of Social Media in the Recruitment Process as HR Strategy

Authors: Seema Sant

Abstract:

In the 21st century were four generation workforces are working, it’s crucial for organizations to build talent management strategy, as tech-savvy Gen Y has entered the work force. They are more connected to each other than ever – through the internet enabled Social media networks Social media has become important in today’s world. The users of such Social media sites have increased in multiple. From sharing their opinion for a brand/product to researching a company before going for an interview, making a conception about a company’s culture or following a Company’s updates due to sheer interest or for job vacancy, Work force today is constantly in touch with social networks. Thus corporate world has rightly realized its potential uses for business purpose. Companies now use social media for marketing, advertising, consumer survey, etc. For HR professionals, it is used for networking and connecting to the Talent pool- through Talent Community. Social recruiting is the process of sourcing or hiring candidates through the use of social sites such as LinkedIn, Facebook Twitter which provide them with an array of information about potential employee; this study represents an exploratory investigation on the role of social networking sites in recruitment. The primarily aim is to analyze the factors that can enhance the channel of recruitment used by of the recruiter with specific reference to the IT organizations in Mumbai, India. Particularly, the aim is to identify how and why companies use social media to attract and screen applicants during their recruitment processes. It also examines the advantages and limitations of recruitment through social media for employers. This is done by literature review. Further, the papers examine the recruiter impact and understand the various opportunities which have created due to technology, thus, to analyze and examine these factors, both primary, as well as secondary data, are collected for the study. The primary data are gathered from five HR manager working in five top IT organizations in Mumbai and 100 HR consultants’ i.e., recruiter. The data was collected by conducting a survey and supplying a closed-ended questionnaire. A comprehension analysis of the study is depicted through graphs and figures. From the analysis, it was observed that there exists a positive relationship between the level of employee recruited through social media and their organizational commitment. Finally the findings show that company’s i.e. recruiters are currently using social media in recruitment, but perhaps not as effective as they could be. The paper gives recommendations and conditions for success that can help employers to make the most out of social media in recruitment.

Keywords: recruitment, social media, social sites, workforce

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2062 Syndromic Surveillance Framework Using Tweets Data Analytics

Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

Abstract:

Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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2061 New Method for the Determination of Montelukast in Human Plasma by Solid Phase Extraction Using Liquid Chromatography Tandem Mass Spectrometry

Authors: Vijayalakshmi Marella, NageswaraRaoPilli

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This paper describes a simple, rapid and sensitive liquid chromatography / tandem mass spectrometry assay for the determination of montelukast in human plasma using montelukast d6 as an internal standard. Analyte and the internal standard were extracted from 50 µL of human plasma via solid phase extraction technique without evaporation, drying and reconstitution steps. The chromatographic separation was achieved on a C18 column by using a mixture of methanol and 5mM ammonium acetate (80:20, v/v) as the mobile phase at a flow rate of 0.8 mL/min. Good linearity results were obtained during the entire course of validation. Method validation was performed as per FDA guidelines and the results met the acceptance criteria. A run time of 2.5 min for each sample made it possible to analyze more number of samples in short time, thus increasing the productivity. The proposed method was found to be applicable to clinical studies.

Keywords: Montelukast, tandem mass spectrometry, montelukast d6, FDA guidelines

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2060 Musical Tesla Coil with Faraday Box Controlled by a GNU Radio

Authors: Jairo Vega, Fabian Chamba, Jordy Urgiles

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In this work, the implementation of a Matlabcontrolled Musical Tesla Coil and external audio signals was presented. First, the audio signal was obtained from a mobile device and processed in Matlab to modify it, adding noise or other desired effects. Then, the processed signal was passed through a preamplifier to increase its amplitude to a level suitable for further amplification through a power amplifier, which was part of the current driver circuit of the Tesla coil. To get the Tesla coil to generate music, a circuit capable of modulating and generating the audio signal by manipulating electrical discharges was used. To visualize and listen to these discharges, a small Faraday cage was built to attenuate the external electric fields. Finally, the implementation of the musical Tesla coil was concluded. However, it was observed that the audio signal volume was very low, and the components used heated up quickly. Due to these limitations, it was determined that the project could not be connected to power for long periods of time.

Keywords: Tesla coil, plasma, electrical signals, GNU Radio

Procedia PDF Downloads 80
2059 QI Wireless Charging a Scope of Magnetic Inductive Coupling

Authors: Sreenesh Shashidharan, Umesh Gaikwad

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QI or 'Chee' which is an interface standard for inductive electrical power transfer over distances of up to 4 cm (1.6 inches). The Qi system comprises a power transmission pad and a compatible receiver in a portable device which is placed on top of the power transmission pad, which charges using the principle of electromagnetic induction. An alternating current is passed through the transmitter coil, generating a magnetic field. This, in turn, induces a voltage in the receiver coil; this can be used to power a mobile device or charge a battery. The efficiency of the power transfer depends on the coupling (k) between the inductors and their quality (Q) The coupling is determined by the distance between the inductors (z) and the relative size (D2 /D). The coupling is further determined by the shape of the coils and the angle between them. If the receiver coil is at a certain distance to the transmitter coil, only a fraction of the magnetic flux, which is generated by the transmitter coil, penetrates the receiver coil and contributes to the power transmission. The more flux reaches the receiver, the better the coils are coupled.

Keywords: inductive electric power, electromagnetic induction, magnetic flux, coupling

Procedia PDF Downloads 720
2058 Sensor Network Routing Optimization by Simulating Eurygaster Life in Wheat Farms

Authors: Fariborz Ahmadi, Hamid Salehi, Khosrow Karimi

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A sensor network is set of sensor nodes that cooperate together to perform a predefined tasks. The important problem in this network is power consumption. So, in this paper one algorithm based on the eurygaster life is introduced to minimize power consumption by the nodes of these networks. In this method the search space of problem is divided into several partitions and each partition is investigated separately. The evaluation results show that our approach is more efficient in comparison to other evolutionary algorithm like genetic algorithm.

Keywords: evolutionary computation, genetic algorithm, particle swarm optimization, sensor network optimization

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2057 International Relations and the Transformation of Political Regimes in Post-Soviet States

Authors: Sergey Chirun

Abstract:

Using of a combination of institutional analysis and network access has allowed the author to identify the characteristics of the informal institutions of regional political power and political regimes. According to the author, ‘field’ of activity of post-Soviet regimes, formed under the influence of informal institutions, often contradicts democratic institutional regional changes which are aimed at creating of a legal-rational type of political domination and balanced model of separation of powers. This leads to the gap between the formal structure of institutions and the real nature of power, predetermining the specific character of the existing political regimes.

Keywords: authoritarianism, institutions, political regime, social networks, transformation

Procedia PDF Downloads 480
2056 All at Sea: Why OT / IT Infrastructure Is So Complex and the Challenges of Securing These on a Cruise Ship

Authors: Ken Munro

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Cruise ships are possibly the most complex collection of systems it is possible to find in one physical, moving location. Propulsion, navigation, power generation and more, combined with a hotel, restaurant, casino, theatre etc, with safety and fire control systems to boot. That complexity creates huge challenges with keeping OT and IT systems apart. Ships engines are often remotely managed, network segregation is often defeated through troubleshooting when at sea. This session will refer to multiple entertaining and informative tales of taking control of ships, including accessing a ships Azipods via a game simulator for passengers. Fortunately, genuine attacks against vessels are very rare, but the effects and impacts to world trade are becoming increasingly obvious.

Keywords: maritime security, cybersecurity, OT, IT, networks

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2055 Exploring Causes of Irregular Migration: Evidence from Rural Punjab, India

Authors: Kulwinder Singh

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Punjab is one of the major labour exporting states of India. Every year more than 20,000 youths from Punjab attempt irregular migration. About 84 irregular migrants are from rural areas and 16 per cent from urban areas. Irregular migration could only be achieved if be organized through highly efficient international networks with the countries of origin, transit, and destination. A good number of Punjabis continue to immigrate into the UK for work through unauthorized means entering the country on visit visas and overstaying or getting ‘smuggled into’ the country with the help of transnational networks of agents. Although, the efforts are being made by the government to curb irregular migration through The Punjab Prevention of Human Smuggling Rules (2012, 2014) and Punjab Travel Regulation Act (2012), but yet it exists parallel to regular migration. Despite unprecedented miseries of irregular migrants and strict laws implemented by the state government to check this phenomenon, ‘why do Punjabis migrate abroad irregularly’ is the important question to answer. This study addresses this question through the comparison of irregular migration with regular one. In other words, this analysis reveals major causes, specifically economic ones, of irregular migration from rural Punjab. This study is unique by presenting economics of irregular migration, given previous studies emphasize the role of sociological and psychological factors. Addressing important question “why do Punjabis migrate abroad irregularly?”, the present study reveals that Punjabi, being far-sighted, endeavor irregular migration as it is, though, economically nonviable in short run, but offers lucrative economic gains as gets older. Despite its considerably higher cost viz-a-viz regular migration, it is the better employment option to irregular migrants with higher permanent income than local low paid jobs for which risking life has become the mindset of the rural Punjabis. Although, it carries considerably lower economic benefits as compared to regular migration, but provides the opportunity of migrating abroad to less educated, semi-skilled and language-test ineligible Punjabis who cannot migrate through regular channels. As its positive impacts on source and destination countries are evident, it might not be restricted, rather its effective management, through liberalising restrictive migration policies by destination nations, can protect the interests of all involved stakeholders.

Keywords: cost, migration, income, irregular, regular, remittances

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2054 Evaluation of Random Forest and Support Vector Machine Classification Performance for the Prediction of Early Multiple Sclerosis from Resting State FMRI Connectivity Data

Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

Abstract:

The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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2053 Effective Health Promotion Interventions Help Young Children to Maximize Their Future Well-Being by Early Childhood Development

Authors: Nadeesha Sewwandi, Dilini Shashikala, R. Kanapathy, S. Viyasan, R. M. S. Kumara, Duminda Guruge

Abstract:

Early childhood development is important to the emotional, social, and physical development of young children and it has a direct effect on their overall development and on the adult they become. Play is so important to optimal child developments including skill development, social development, imagination, creativity and it fulfills a baby’s inborn need to learn. So, health promotion approach empowers people about the development of early childhood. Play area is a new concept and this study focus how this play areas helps to the development of early childhood of children in rural villages in Sri Lanka. This study was conducted with a children society in a rural village called Welankulama in Sri Lanka. Survey was conducted with children society about emotional, social and physical development of young children (Under age eight) in this village using questionnaires. It described most children under eight years age have poor level of emotional, social and physical development in this village. Then children society wanted to find determinants for this problem and among them they prioritized determinants like parental interactions, learning environment and social interaction and address them using an innovative concept called play area. In this village there is a common place as play area under a big tamarind tree. It consists of a playhouse, innovative playing toys, mobile library, etc. Twice a week children, parents, grandparents gather to this nice place. Collective feeding takes place in this area once a week and it was conducted by several mothers groups in this village. Mostly grandparents taught about handicrafts and this is a very nice place to share their experiences with all. Healthy competitions were conducted in this place through playing to motivate the children. Happy calendar (mood of the children) was marked by children before and after coming to the play area. In terms of results qualitative changes got significant place in this study. By learning about colors and counting through playing the thinking and reasoning skills got developed among children. Children were widening their imagination by means of storytelling. We observed there were good developments of fine and gross motor skills of two differently abled children in this village. Children learn to empathize with other people, sharing, collaboration, team work and following of rules. And also children gain knowledge about fairness, through role playing, obtained insight on the right ways of displaying emotions such as stress, fear, anger, frustration, and develops knowledge of how they can manage their feelings. The reading and writing ability of the children got improved by 83% because of the mobile library. The weight of children got increased by 81% in the village. Happiness was increased by 76% among children in the society. Playing is very important for learning during early childhood period of a person. Health promotion interventions play a major role to the development of early childhood and it help children to adjust to the school setting and even to enhance children’s learning readiness, learning behaviors and problem solving skills.

Keywords: early childhood development, health promotion approach, play and learning, working with children

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2052 A Low Power Consumption Routing Protocol Based on a Meta-Heuristics

Authors: Kaddi Mohammed, Benahmed Khelifa D. Benatiallah

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A sensor network consists of a large number of sensors deployed in areas to monitor and communicate with each other through a wireless medium. The collected routing data in the network consumes most of the energy of the sensor nodes. For this purpose, multiple routing approaches have been proposed to conserve energy resource at the sensors and to overcome the challenges of its limitation. In this work, we propose a new low energy consumption routing protocol for wireless sensor networks based on a meta-heuristic methods. Our protocol is to operate more fairly energy when routing captured data to the base station.

Keywords: WSN, routing, energy, heuristic

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2051 A Design of an Augmented Reality Based Virtual Heritage Application

Authors: Stephen Barnes, Ian Mills, Frances Cleary

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Augmented and virtual reality-based applications offer many benefits for the heritage and tourism sector. This technology provides a platform to showcase the regions of interest to people without the need for them to be physically present, which has had a positive impact on enticing tourists to visit those locations. However, the technology also provides the opportunity to present historical artefacts in a form that accurately represents their original, intended appearance. Three sites of interest were identified in the Lingaun Valley in South East Ireland, wherein virtual representations of site-specific artefacts of interest were created via a multidisciplinary team encompassing archaeology, art history, 3D modelling, design, and software development. The collated information has been presented to users via an augmented reality mobile-based application that provides information in an engaging manner that encourages an interest in history as well as visits to the sites in the Lingaun Valley.

Keywords: augmented reality, virtual heritage, 3D modelling, archaeology, virtual representation

Procedia PDF Downloads 73
2050 Requirements for a Shared Management of State-Owned Building in the Archaeological Park of Pompeii

Authors: Maria Giovanna Pacifico

Abstract:

Maintenance, in Italy, is not yet a consolidated practice despite the benefits that could come from. Among the main reasons, there are the lack of financial resources and personnel in the public administration and a general lack of knowledge about how to activate and to manage a prevented and programmed maintenance. The experimentation suggests that users and tourists could be involved in the maintenance process from the knowledge phase to the monitoring ones by using mobile devices. The goal is to increase the quality of Facility Management for cultural heritage, prioritizing usage needs, and limiting interference between the key stakeholders. The method simplifies the consolidated procedures for the Information Systems, avoiding a loss in terms of quality and amount of information by focusing on the users' requirements: management economy, user safety, accessibility, and by receiving feedback information to define a framework that will lead to predictive maintenance. This proposal was designed to be tested in the Archaeological Park of Pompeii on the state property asset.

Keywords: asset maintenance, key stakeholders, Pompeii, user requirement

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2049 Petri Net Modeling and Simulation of a Call-Taxi System

Authors: T. Godwin

Abstract:

A call-taxi system is a type of taxi service where a taxi could be requested through a phone call or mobile app. A schematic functioning of a call-taxi system is modeled using Petri net, which provides the necessary conditions for a taxi to be assigned by a dispatcher to pick a customer as well as the conditions for the taxi to be released by the customer. A Petri net is a graphical modeling tool used to understand sequences, concurrences, and confluences of activities in the working of discrete event systems. It uses tokens on a directed bipartite multi-graph to simulate the activities of a system. The Petri net model is translated into a simulation model and a call-taxi system is simulated. The simulation model helps in evaluating the operation of a call-taxi system based on the fleet size as well as the operating policies for call-taxi assignment and empty call-taxi repositioning. The developed Petri net based simulation model can be used to decide the fleet size as well as the call-taxi assignment policies for a call-taxi system.

Keywords: call-taxi, discrete event system, petri net, simulation modeling

Procedia PDF Downloads 412
2048 A Survey of Attacks and Security Requirements in Wireless Sensor Networks

Authors: Vishnu Pratap Singh Kirar

Abstract:

Wireless sensor network (WSN) is a network of many interconnected networked systems, they equipped with energy resources and they are used to detect other physical characteristics. On WSN, there are many researches are performed in past decades. WSN applicable in many security systems govern by military and in many civilian related applications. Thus, the security of WSN gets attention of researchers and gives an opportunity for many future aspects. Still, there are many other issues are related to deployment and overall coverage, scalability, size, energy efficiency, quality of service (QoS), computational power and many more. In this paper we discus about various applications and security related issue and requirements of WSN.

Keywords: wireless sensor network (WSN), wireless network attacks, wireless network security, security requirements

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2047 A Survey on Positive Real and Strictly Positive Real Scalar Transfer Functions

Authors: Mojtaba Hakimi-Moghaddam

Abstract:

Positive real and strictly positive real transfer functions are important concepts in the control theory. In this paper, the results of researches in these areas are summarized. Definitions together with their graphical interpretations are mentioned. The equivalent conditions in the frequency domain and state space representations are reviewed. Their equivalent electrical networks are explained. Also, a comprehensive discussion about a difference between behavior of real part of positive real and strictly positive real transfer functions in high frequencies is presented. Furthermore, several illustrative examples are given.

Keywords: real rational transfer functions, positive realness property, strictly positive realness property, equivalent conditions

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2046 Examining Media Literacy Strategies through Questionnaires and Analyzing the Behavioral Patterns of Middle-Aged and Elderly Persons

Authors: Chia Yen Li, Wen Huei Chou, Mieko Ohsuga, Tsuyoshi Inoue

Abstract:

The evolution of the digital age has led to people’s lives being pervaded by both facts and misinformation, challenging media literacy (ML). Middle-aged and elderly persons (MEPs) are prone to disseminating large amounts of misinformation, which often endangers their lives due to erroneously believing such information. At present, several countries have actively established fact-checking platforms to combat misinformation, but they are unable to keep pace with the rapid proliferation of such information on social media. In this study, the questionnaire survey method was used to collect data on MEPs’ behavior, cognition, attitudes, and concepts of social media when using a mobile instant messaging app called LINE; analyze their behavioral patterns and reasons for sharing misinformation; and summarize design strategies for improving their ML. The findings can serve as a reference in future related research.

Keywords: media literacy, middle-aged and elderly persons, social media, misinformation

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2045 Using Wiki for Enhancing the Knowledge Transfer to Newcomers: An Experience Report

Authors: Hualter Oliveira Barbosa, Raquel Feitosa do Vale Cunha, Erika Muniz dos Santos, Fernanda Belmira Souza, Fabio Sousa, Luis Henrique Pascareli, Franciney de Oliveira Lima, Ana Cláudia Reis da Silva, Christiane Moreira de Almeida

Abstract:

Software development is intrinsic human-based knowledge-intensive. Due to globalization, software development has become a complex challenge and we usually face barriers related to knowledge management, team building, costly testing processes, especially in distributed settings. For this reason, several approaches have been proposed to minimize barriers caused by geographic distance. In this paper, we present as we use experimental studies to improve our knowledge management process using the Wiki system. According to the results, it was possible to identify learning preferences from our software projects leader team, organize and improve the learning experience of our Wiki and; facilitate collaboration by newcomers to improve Wiki with new contents available in the Wiki.

Keywords: mobile product, knowledge transfer, knowledge management process, wiki, GSD

Procedia PDF Downloads 164
2044 Comparison of the Effect of Heart Rate Variability Biofeedback and Slow Breathing Training on Promoting Autonomic Nervous Function Related Performance

Authors: Yi Jen Wang, Yu Ju Chen

Abstract:

Background: Heart rate variability (HRV) biofeedback can promote autonomic nervous function, sleep quality and reduce psychological stress. In HRV biofeedback training, it is hoped that through the guidance of machine video or audio, the patient can breathe slowly according to his own heart rate changes so that the heart and lungs can achieve resonance, thereby promoting the related effects of autonomic nerve function; while, it is also pointed out that if slow breathing of 6 times per minute can also guide the case to achieve the effect of cardiopulmonary resonance. However, there is no relevant research to explore the comparison of the effectiveness of cardiopulmonary resonance by using video or audio HRV biofeedback training and metronome-guided slow breathing. Purpose: To compare the promotion of autonomic nervous function performance between using HRV biofeedback and slow breathing guided by a metronome. Method: This research is a kind of experimental design with convenient sampling; the cases are randomly divided into the heart rate variability biofeedback training group and the slow breathing training group. The HRV biofeedback training group will conduct HRV biofeedback training in a four-week laboratory and use the home training device for autonomous training; while the slow breathing training group will conduct slow breathing training in the four-week laboratory using the mobile phone APP breathing metronome to guide the slow breathing training, and use the mobile phone APP for autonomous training at home. After two groups were enrolled and four weeks after the intervention, the autonomic nervous function-related performance was repeatedly measured. Using the chi-square test, student’s t-test and other statistical methods to analyze the results, and use p <0.05 as the basis for statistical significance. Results: A total of 27 subjects were included in the analysis. After four weeks of training, the HRV biofeedback training group showed significant improvement in the HRV indexes (SDNN, RMSSD, HF, TP) and sleep quality. Although the stress index also decreased, it did not reach statistical significance; the slow breathing training group was not statistically significant after four weeks of training, only sleep quality improved significantly, while the HRV indexes (SDNN, RMSSD, TP) all increased. Although HF and stress indexes decreased, they were not statistically significant. Comparing the difference between the two groups after training, it was found that the HF index improved significantly and reached statistical significance in the HRV biofeedback training group. Although the sleep quality of the two groups improved, it did not reach that level in a statistically significant difference. Conclusion: HRV biofeedback training is more effective in promoting autonomic nervous function than slow breathing training, but the effects of reducing stress and promoting sleep quality need to be explored after increasing the number of samples. The results of this study can provide a reference for clinical or community health promotion. In the future, it can also be further designed to integrate heart rate variability biological feedback training into the development of AI artificial intelligence wearable devices, which can make it more convenient for people to train independently and get effective feedback in time.

Keywords: autonomic nervous function, HRV biofeedback, heart rate variability, slow breathing

Procedia PDF Downloads 166