Search results for: Ad-Hoc networks
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2703

Search results for: Ad-Hoc networks

1413 Feedforward Neural Network with Backpropagation for Epilepsy Seizure Detection

Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

Abstract:

Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

Procedia PDF Downloads 196
1412 An Improved Cuckoo Search Algorithm for Voltage Stability Enhancement in Power Transmission Networks

Authors: Reza Sirjani, Nobosse Tafem Bolan

Abstract:

Many optimization techniques available in the literature have been developed in order to solve the problem of voltage stability enhancement in power systems. However, there are a number of drawbacks in the use of previous techniques aimed at determining the optimal location and size of reactive compensators in a network. In this paper, an Improved Cuckoo Search algorithm is applied as an appropriate optimization algorithm to determine the optimum location and size of a Static Var Compensator (SVC) in a transmission network. The main objectives are voltage stability improvement and total cost minimization. The results of the presented technique are then compared with other available optimization techniques.

Keywords: cuckoo search algorithm, optimization, power system, var compensators, voltage stability

Procedia PDF Downloads 531
1411 Novel Approach to Design of a Class-EJ Power Amplifier Using High Power Technology

Authors: F. Rahmani, F. Razaghian, A. R. Kashaninia

Abstract:

This article proposes a new method for application in communication circuit systems that increase efficiency, PAE, output power and gain in the circuit. The proposed method is based on a combination of switching class-E and class-J and has been termed class-EJ. This method was investigated using both theory and simulation to confirm ~72% PAE and output power of > 39 dBm. The combination and design of the proposed power amplifier accrues gain of over 15dB in the 2.9 to 3.5 GHz frequency bandwidth. This circuit was designed using MOSFET and high power transistors. The load- and source-pull method achieved the best input and output networks using lumped elements. The proposed technique was investigated for fundamental and second harmonics having desirable amplitudes for the output signal.

Keywords: power amplifier (PA), high power, class-J and class-E, high efficiency

Procedia PDF Downloads 470
1410 Intelligent Indoor Localization Using WLAN Fingerprinting

Authors: Gideon C. Joseph

Abstract:

The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

Procedia PDF Downloads 326
1409 Analysis and Performance of Handover in Universal Mobile Telecommunications System (UMTS) Network Using OPNET Modeller

Authors: Latif Adnane, Benaatou Wafa, Pla Vicent

Abstract:

Handover is of great significance to achieve seamless connectivity in wireless networks. This paper gives an impression of the main factors which are being affected by the soft and the hard handovers techniques. To know and understand the handover process in The Universal Mobile Telecommunications System (UMTS) network, different statistics are calculated. This paper focuses on the quality of service (QoS) of soft and hard handover in UMTS network, which includes the analysis of received power, signal to noise radio, throughput, delay traffic, traffic received, delay, total transmit load, end to end delay and upload response time using OPNET simulator.

Keywords: handover, UMTS, mobility, simulation, OPNET modeler

Procedia PDF Downloads 300
1408 Mitigating the Unwillingness of e-Forums Members to Engage in Information Exchange

Authors: Dora Triki, Irena Vida, Claude Obadia

Abstract:

Social networks such as e-Forums or dating sites often face the reluctance of key members to participate. Relying on the conation theory, this study investigates this phenomenon and proposes solutions to mitigate the issue. We show that highly experienced e-Forum members refuse to share business information in a peer to peer information exchange forums. However, forums managers can mitigate this behavior by developing a sentiment of belongingness to the network. Furthermore, by selecting only elite forum participants with ample experience, they can reduce the reluctance of key information providers to engage in information exchange. Our hypotheses are tested with PLS structural equations modeling using survey data from members of a French e-Forum dedicated to the exchange of business information about exporting.

Keywords: conation, e-Forum, information exchange, members participation

Procedia PDF Downloads 141
1407 The Territorial Expression of Religious Identity: A Case Study of Catholic Communities

Authors: Margarida Franca

Abstract:

The influence of the ‘cultural turn’ movement and the consequent deconstruction of scientific thought allowed geography and other social sciences to open or deepen their studies based on the analysis of multiple identities, on singularities, on what is particular or what marks the difference between individuals. In the context of postmodernity, the geography of religion has gained a favorable scientific, thematic and methodological focus for the qualitative and subjective interpretation of various religious identities, sacred places, territories of belonging, religious communities, among others. In the context of ‘late modernity’ or ‘net modernity’, sacred places and the definition of a network of sacred territories allow believers to attain the ‘ontological security’. The integration on a religious group or a local community, particularly a religious community, allows human beings to achieve a sense of belonging, familiarity or solidarity and to overcome, in part, some of the risks or fears that society has discovered. The importance of sacred places comes not only from their inherent characteristics (eg transcendent, mystical and mythical, respect, intimacy and abnegation), but also from the possibility of adding and integrating members of the same community, creating bonds of belonging, reference and individual and collective memory. In addition, the formation of different networks of sacred places, with multiple scales and dimensions, allows the human being to identify and structure his times and spaces of daily life. Thus, each individual, due to his unique identity and life and religious paths, creates his own network of sacred places. The territorial expression of religious identity allows to draw a variable and unique geography of sacred places. Through the case study of the practicing Catholic population in the diocese of Coimbra (Portugal), the aim is to study the territorial expression of the religious identity of the different local communities of this city. Through a survey of six parishes in the city, we sought to identify which factors, qualitative or not, define the different territorial expressions on a local, national and international scale, with emphasis on the socioeconomic profile of the population, the religious path of the believers, the religious group they belong to and the external interferences, religious or not. The analysis of these factors allows us to categorize the communities of the city of Coimbra and, for each typology or category, to identify the specific elements that unite the believers to the sacred places, the networks and religious territories that structure the religious practice and experience and also the non-representational landscape that unifies and creates memory. We conclude that an apparently homogeneous group, the Catholic community, incorporates multitemporalities and multiterritorialities that are necessary to understand the history and geography of a whole country and of the Catholic communities in particular.

Keywords: geography of religion, sacred places, territoriality, Catholic Church

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1406 A Review of Literature for Online Social Network Business Continuance Intention and the Hypotheses Thereof

Authors: Akwesi Assensoh-Kodua

Abstract:

Online Social Networks (OSN) has come and gone, yet the explosion of business activities on such platforms continuous to surge high, giving advantage to the bold entrepreneurs. It is therefore a practical requirement that practitioners and researchers understand the key determinants of costumers’ online social network business activities and continuance intention. An exploratory literature research to examine OSN continuous intention of business participants on OSN revealed that the practice of doing business on social network has come to stay and the following factors are the likely drivers for this new business model: perceived trust, perceived ease of use, confirmation, habit, social norm, perceived behavioural control, expected benefit, and satisfaction are the most probable factors that can lead to online social network (OSN) continuance intention.

Keywords: online social network, continuance intention, business continuance

Procedia PDF Downloads 475
1405 Presenting a Model Based on Artificial Neural Networks to Predict the Execution Time of Design Projects

Authors: Hamed Zolfaghari, Mojtaba Kord

Abstract:

After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

Procedia PDF Downloads 66
1404 Classification of Cochannel Signals Using Cyclostationary Signal Processing and Deep Learning

Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

Abstract:

The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

Procedia PDF Downloads 89
1403 Artificial Intelligence Based Meme Generation Technology for Engaging Audience in Social Media

Authors: Andrew Kurochkin, Kostiantyn Bokhan

Abstract:

In this study, a new meme dataset of ~650K meme instances was created, a technology of meme generation based on the state of the art deep learning technique - GPT-2 model was researched, a comparative analysis of machine-generated memes and human-created was conducted. We justified that Amazon Mechanical Turk workers can be used for the approximate estimating of users' behavior in a social network, more precisely to measure engagement. It was shown that generated memes cause the same engagement as human memes that produced low engagement in the social network (historically). Thus, generated memes are less engaging than random memes created by humans.

Keywords: content generation, computational social science, memes generation, Reddit, social networks, social media interaction

Procedia PDF Downloads 115
1402 Scheduling in Cloud Networks Using Chakoos Algorithm

Authors: Masoumeh Ali Pouri, Hamid Haj Seyyed Javadi

Abstract:

Nowadays, cloud processing is one of the important issues in information technology. Since scheduling of tasks graph is an NP-hard problem, considering approaches based on undeterminisitic methods such as evolutionary processing, mostly genetic and cuckoo algorithms, will be effective. Therefore, an efficient algorithm has been proposed for scheduling of tasks graph to obtain an appropriate scheduling with minimum time. In this algorithm, the new approach is based on making the length of the critical path shorter and reducing the cost of communication. Finally, the results obtained from the implementation of the presented method show that this algorithm acts the same as other algorithms when it faces graphs without communication cost. It performs quicker and better than some algorithms like DSC and MCP algorithms when it faces the graphs involving communication cost.

Keywords: cloud computing, scheduling, tasks graph, chakoos algorithm

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1401 Routing in IP/LEO Satellite Communication Systems: Past, Present and Future

Authors: Mohammed Hussein, Abualseoud Hanani

Abstract:

In Low Earth Orbit (LEO) satellite constellation system, routing data from the source all the way to the destination constitutes a daunting challenge because LEO satellite constellation resources are spare and the high speed movement of LEO satellites results in a highly dynamic network topology. This situation limits the applicability of traditional routing approaches that rely on exchanging topology information upon change or setup of a connection. Consequently, in recent years, many routing algorithms and implementation strategies for satellite constellation networks with Inter Satellite Links (ISLs) have been proposed. In this article, we summarize and classify some of the most representative solutions according to their objectives, and discuss their advantages and disadvantages. Finally, with a look into the future, we present some of the new challenges and opportunities for LEO satellite constellations in general and routing protocols in particular.

Keywords: LEO satellite constellations, dynamic topology, IP routing, inter-satellite-links

Procedia PDF Downloads 356
1400 Automated Detection of Related Software Changes by Probabilistic Neural Networks Model

Authors: Yuan Huang, Xiangping Chen, Xiaonan Luo

Abstract:

Current software are continuously updating. The change between two versions usually involves multiple program entities (e.g., packages, classes, methods, attributes) with multiple purposes (e.g., changed requirements, bug fixing). It is hard for developers to understand which changes are made for the same purpose. Whether two changes are related is not decided by the relationship between this two entities in the program. In this paper, we summarized 4 coupling rules(16 instances) and 4 state-combination types at the class, method and attribute levels for software change. Related Change Vector (RCV) are defined based on coupling rules and state-combination types, and applied to classify related software changes by using Probabilistic Neural Network during a software updating.

Keywords: PNN, related change, state-combination, logical coupling, software entity

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1399 New Gas Geothermometers for the Prediction of Subsurface Geothermal Temperatures: An Optimized Application of Artificial Neural Networks and Geochemometric Analysis

Authors: Edgar Santoyo, Daniel Perez-Zarate, Agustin Acevedo, Lorena Diaz-Gonzalez, Mirna Guevara

Abstract:

Four new gas geothermometers have been derived from a multivariate geo chemometric analysis of a geothermal fluid chemistry database, two of which use the natural logarithm of CO₂ and H2S concentrations (mmol/mol), respectively, and the other two use the natural logarithm of the H₂S/H₂ and CO₂/H₂ ratios. As a strict compilation criterion, the database was created with gas-phase composition of fluids and bottomhole temperatures (BHTM) measured in producing wells. The calibration of the geothermometers was based on the geochemical relationship existing between the gas-phase composition of well discharges and the equilibrium temperatures measured at bottomhole conditions. Multivariate statistical analysis together with the use of artificial neural networks (ANN) was successfully applied for correlating the gas-phase compositions and the BHTM. The predicted or simulated bottomhole temperatures (BHTANN), defined as output neurons or simulation targets, were statistically compared with measured temperatures (BHTM). The coefficients of the new geothermometers were obtained from an optimized self-adjusting training algorithm applied to approximately 2,080 ANN architectures with 15,000 simulation iterations each one. The self-adjusting training algorithm used the well-known Levenberg-Marquardt model, which was used to calculate: (i) the number of neurons of the hidden layer; (ii) the training factor and the training patterns of the ANN; (iii) the linear correlation coefficient, R; (iv) the synaptic weighting coefficients; and (v) the statistical parameter, Root Mean Squared Error (RMSE) to evaluate the prediction performance between the BHTM and the simulated BHTANN. The prediction performance of the new gas geothermometers together with those predictions inferred from sixteen well-known gas geothermometers (previously developed) was statistically evaluated by using an external database for avoiding a bias problem. Statistical evaluation was performed through the analysis of the lowest RMSE values computed among the predictions of all the gas geothermometers. The new gas geothermometers developed in this work have been successfully used for predicting subsurface temperatures in high-temperature geothermal systems of Mexico (e.g., Los Azufres, Mich., Los Humeros, Pue., and Cerro Prieto, B.C.) as well as in a blind geothermal system (known as Acoculco, Puebla). The last results of the gas geothermometers (inferred from gas-phase compositions of soil-gas bubble emissions) compare well with the temperature measured in two wells of the blind geothermal system of Acoculco, Puebla (México). Details of this new development are outlined in the present research work. Acknowledgements: The authors acknowledge the funding received from CeMIE-Geo P09 project (SENER-CONACyT).

Keywords: artificial intelligence, gas geochemistry, geochemometrics, geothermal energy

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1398 Application of Digital Tools for Improving Learning

Authors: José L. Jiménez

Abstract:

The use of technology in the classroom is an issue that is constantly evolving. Digital age students learn differently than their teachers did, so now the teacher should be constantly evolving their methods and teaching techniques to be more in touch with the student. In this paper a case study presents how were used some of these technologies by accompanying a classroom course, this in order to provide students with a different and innovative experience as their teacher usually presented the activities to develop. As students worked in the various activities, they increased their digital skills by employing unknown tools that helped them in their professional training. The twenty-first century teacher should consider the use of Information and Communication Technologies in the classroom thinking in skills that students of the digital age should possess. It also takes a brief look at the history of distance education and it is also highlighted the importance of integrating technology as part of the student's training.

Keywords: digital tools, on-line learning, social networks, technology

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1397 The Female Jihad: A Case Study of Jamaah Islamiyah’s Women in Indonesia

Authors: Milda Istiqomah

Abstract:

The current trends demonstrate that the number of women involved in terrorism is steadily increasing. There are at least two types of roles that women assume in terrorism; the ‘visible role’ and ‘invisible role’. Both roles are very important to the sustainability of terrorism and terrorist organizations. The findings of this paper are based on the analysis of multiple case study from two terrorism verdicts in Indonesia, media reports and academic journals. This paper argues that women in Jemaah Islamiyah (JI) play an important role in both categories. They are involved in this organization by marital and kinship linkages which aim to secure the networks and regenerate the Jihadi ideology within JI. Finally, this paper states that the role of women in JI is significant due to its importance in delivering the idea of Jihad to younger generations.

Keywords: terrorism, women, jihadi movement, case study

Procedia PDF Downloads 107
1396 Review on Rainfall Prediction Using Machine Learning Technique

Authors: Prachi Desai, Ankita Gandhi, Mitali Acharya

Abstract:

Rainfall forecast is mainly used for predictions of rainfall in a specified area and determining their future rainfall conditions. Rainfall is always a global issue as it affects all major aspects of one's life. Agricultural, fisheries, forestry, tourism industry and other industries are widely affected by these conditions. The studies have resulted in insufficient availability of water resources and an increase in water demand in the near future. We already have a new forecast system that uses the deep Convolutional Neural Network (CNN) to forecast monthly rainfall and climate changes. We have also compared CNN against Artificial Neural Networks (ANN). Machine Learning techniques that are used in rainfall predictions include ARIMA Model, ANN, LR, SVM etc. The dataset on which we are experimenting is gathered online over the year 1901 to 20118. Test results have suggested more realistic improvements than conventional rainfall forecasts.

Keywords: ANN, CNN, supervised learning, machine learning, deep learning

Procedia PDF Downloads 170
1395 Using Data from Foursquare Web Service to Represent the Commercial Activity of a City

Authors: Taras Agryzkov, Almudena Nolasco-Cirugeda, Jose L. Oliver, Leticia Serrano-Estrada, Leandro Tortosa, Jose F. Vicent

Abstract:

This paper aims to represent the commercial activity of a city taking as source data the social network Foursquare. The city of Murcia is selected as case study, and the location-based social network Foursquare is the main source of information. After carrying out a reorganisation of the user-generated data extracted from Foursquare, it is possible to graphically display on a map the various city spaces and venues –especially those related to commercial, food and entertainment sector businesses. The obtained visualisation provides information about activity patterns in the city of Murcia according to the people`s interests and preferences and, moreover, interesting facts about certain characteristics of the town itself.

Keywords: social networks, spatial analysis, data visualization, geocomputation, Foursquare

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1394 55 dB High Gain L-Band EDFA Utilizing Single Pump Source

Authors: M. H. Al-Mansoori, W. S. Al-Ghaithi, F. N. Hasoon

Abstract:

In this paper, we experimentally investigate the performance of an efficient high gain triple-pass L-band Erbium-Doped Fiber (EDF) amplifier structure with a single pump source. The amplifier gain and noise figure variation with EDF pump power, input signal power and wavelengths have been investigated. The generated backward Amplified Spontaneous Emission (ASE) noise of the first amplifier stage is suppressed by using a tunable band-pass filter. The amplifier achieves a signal gain of 55 dB with low noise figure of 3.8 dB at -50 dBm input signal power. The amplifier gain shows significant improvement of 12.8 dB compared to amplifier structure without ASE suppression.

Keywords: optical amplifiers, EDFA, L-band, optical networks

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1393 Make Up Flash: Web Application for the Improvement of Physical Appearance in Images Based on Recognition Methods

Authors: Stefania Arguelles Reyes, Octavio José Salcedo Parra, Alberto Acosta López

Abstract:

This paper presents a web application for the improvement of images through recognition. The web application is based on the analysis of picture-based recognition methods that allow an improvement on the physical appearance of people posting in social networks. The basis relies on the study of tools that can correct or improve some features of the face, with the help of a wide collection of user images taken as reference to build a facial profile. Automatic facial profiling can be achieved with a deeper study of the Object Detection Library. It was possible to improve the initial images with the help of MATLAB and its filtering functions. The user can have a direct interaction with the program and manually adjust his preferences.

Keywords: Matlab, make up, recognition methods, web application

Procedia PDF Downloads 123
1392 Polish Police in the Fight against Terrorism and Cyberterrorism

Authors: Izabela Nowicka, Jacek Dworzecki

Abstract:

The paper will be presented to selected legal and organizational solutions for the prevention and combating of terrorism by the police in Poland. Development will include information on the organization and functioning of the police anti-terrorist sub-units, whose officers are on the front line of the fight against terrorism. They will be presented to the conditions and cases of use of firearms by police officers in the course of special operations aimed against organizations and terrorist groups, and the perpetrators of criminal acts of terrorism as well as the legal foundation for the Polish police to take immediate counterterrorism operations. Article will be prepared in the context of an international research project entitled. Understand the Dimensions of Organised Crime and Terrorist Networks for Developing Effective and Efficient Security Solutions for First-line-practitioners and Professionals [Project: H2020-FCT-2015, No: 700688].

Keywords: the fight against terrorism, police, Poland, takedown

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1391 Familiarity With Civil Engineering and Types of Construction and Its Methods

Authors: Mokhtar Nikgoo

Abstract:

Civil engineering is one of the disciplines that shows the application of science in creating construction and civil engineering. That is, everything that returns to the population of a country, such as dams, airports, roads, bridges, towers, tunnels, telecommunication towers, buildings resistant to earthquakes, floods and fires, power plants and light, cheap and quality materials for construction. And the construction is included in the scope of work of the civil engineer. Civil engineering covers a wide range of tasks. That is, for the construction of buildings, bridges, towers, tunnels, roads, silos, or sewage networks, an efficient civil engineer is needed at the beginning, in addition to complying with the technical and operational aspects, he also works economically. Because being economical is a principle in civil engineering. Is. This field at the undergraduate level has three majors: civil-building, civil-mapping and civil-water.

Keywords: civil engineering, construction, surveying, mapping, pile

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1390 Evaluation of Low Power Wi-Fi Modules in Simulated Ocean Environments

Authors: Gabriel Chenevert, Abhilash Arora, Zeljko Pantic

Abstract:

The major problem underwater acoustic communication faces is the low data rate due to low signal frequency. By contrast, the Wi-Fi communication protocol offers high throughput but limited operating range due to the attenuation effect of the sea and ocean medium. However, short-range near-field underwater wireless power transfer systems offer an environment where Wi-Fi communication can be effectively integrated to collect data and deliver instructions to sensors in underwater sensor networks. In this paper, low-power, low-cost off-the-shelf Wi-Fi modules are explored experimentally for four selected parameters for different distances between units and water salinities. The results reveal a shorter operating range and stronger dependence on water salinity than reported so far for high-end Wi-Fi modules.

Keywords: Wi-Fi, wireless power transfer, underwater communications, ESP

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1389 #Push Mo Yan: A Study of the Influence of Facebook and Twitter to Adolescent Communication

Authors: Rebecca Cervantes, Elishah Maro Pangilinan

Abstract:

The current research used Uses and gratifications theory to further understand the motivations and satisfaction students get from Facebook and Twitter. The researchers relate the objectives in developing uses and gratifications theory 1) to explain how individuals use mass communication to gratify their needs, “what do people do with the media” many of these young adults use social media networks to communicate with family, friends, and even strangers. Social media sites have created new and non-personal ways for people to interact with others and young adults have taken advantage of this technological trend; 2) to discover underlying motives for individuals’ media use 3) to identify the positive and the negative consequences of individual media use. The researchers use survey questionnaires to gather information that is used in this study. A descriptive analysis was used to measure the answers to a 24-item questionnaire.

Keywords: adolescent, communication, social media, #Hashtag

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1388 Cyber Security in Nigeria: A Collaboration between Communities and Professionals

Authors: Alese Boniface K., Adu Michael K., Owa Victor K.

Abstract:

Security can be defined as the degree of resistance to, or protection from harm. It applies to any vulnerable and valuable assets, such as persons, dwellings, communities, nations or organizations. Cybercrime is any crime committed or facilitated via the Internet. It is any criminal activity involving computers and networks. It can range from fraud to unsolicited emails (spam). It includes the distant theft of government or corporate secrets through criminal trespass into remote systems around the globe. Nigeria like any other nations of the world is currently having their own share of the menace that has been used even as tools by terrorists. This paper is an attempt at presenting cyber security as an issue that requires a coordinated national response. It also acknowledges and advocates the key roles to be played by stakeholders and the importance of forging strong partnerships to prevent and tackle cybercrime in Nigeria.

Keywords: security, cybercrime, internet, government, stakeholders, partnerships

Procedia PDF Downloads 510
1387 Secure Network Coding-Based Named Data Network Mutual Anonymity Transfer Protocol

Authors: Tao Feng, Fei Xing, Ye Lu, Jun Li Fang

Abstract:

NDN is a kind of future Internet architecture. Due to the NDN design introduces four privacy challenges,Many research institutions began to care about the privacy issues of naming data network(NDN).In this paper, we are in view of the major NDN’s privacy issues to investigate privacy protection,then put forwards more effectively anonymous transfer policy for NDN.Firstly,based on mutual anonymity communication for MP2P networks,we propose NDN mutual anonymity protocol.Secondly,we add interest package authentication mechanism in the protocol and encrypt the coding coefficient, security of this protocol is improved by this way.Finally, we proof the proposed anonymous transfer protocol security and anonymity.

Keywords: NDN, mutual anonymity, anonymous routing, network coding, authentication mechanism

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1386 Developing an AI-Driven Application for Real-Time Emotion Recognition from Human Vocal Patterns

Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

Abstract:

This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

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1385 Stimuli Responsives of Crosslinked Poly on 2-HydroxyEthyl MethAcrylate – Optimization of Parameters by Experimental Design

Authors: Tewfik Bouchaour, Salah Hamri, Yasmina Houda Bendahma, Ulrich Maschke

Abstract:

Stimuli-responsive materials based on UV crosslinked acrylic polymer networks are fabricated. A various kinds of polymeric systems, hydrophilic polymers based on 2-Hydroxyethyl methacrylate have been widely studied because of their ability to simulate biological tissues, which leads to many applications. The acrylic polymer network PHEMA developed by UV photopolymerization has been used for dye retention. For these so-called smart materials, the properties change in response to an external stimulus. In this contribution, we report the influence of some parameters (initial composition, temperature, and nature of components) in the properties of final materials. Optimization of different parameters is examined by experimental design.

Keywords: UV photo-polymerization, PHEMA, external stimulus, optimization

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1384 An Exploration of Policy-related Documents on District Heating and Cooling in Flanders: a Slow and Bottom-up Process

Authors: Isaura Bonneux

Abstract:

District heating and cooling (DHC) is increasingly recognized as a viable path towards sustainable heating and cooling. While some countries like Sweden and Denmark have a longstanding tradition of DHC, Belgium is lacking behind. The Northern part of Belgium, Flanders, had only a total of 95 heating networks in July 2023. Nevertheless, it is increasingly exploring its possibilities to enhance the scope of DHC. DHC is a complex energy system, requiring a lot of collaboration between various stakeholders on various levels. Therefore, it is of interest to look closer at policy-related documents at the Flemish (regional) level, as these policies set the scene for DHC development in the Flemish region. This kind of analysis has not been undertaken so far. This paper has the following research question: “Who talks about DHC, and in which way and context is DHC discussed in Flemish policy-related documents?” To answer this question, the Overton policy database was used to search and retrieve relevant policy-related documents. Overton retrieves data from governments, think thanks, NGOs, and IGOs. In total, out of the 244 original results, 117 documents between 2009 and 2023 were analyzed. Every selected document included theme keywords, policymaking department(s), date, and document type. These elements were used for quantitative data description and visualization. Further, qualitative content analysis revealed patterns and main themes regarding DHC in Flanders. Four main conclusions can be drawn: First, it is obvious from the timeframe that DHC is a new topic in Flanders with still limited attention; 2014, 2016 and 2017 were the years with the most documents, yet this number is still only 12 documents. In addition, many documents talked about DHC but not much in depth and painted it as a future scenario with a lot of uncertainty around it. The largest part of the issuing government departments had a link to either energy or climate (e.g. Flemish Environmental Agency) or policy (e.g. Socio-Economic Council of Flanders) Second, DHC is mentioned most within an ‘Environment and Sustainability’ context, followed by ‘General Policy and Regulation’. This is intuitive, as DHC is perceived as a sustainable heating and cooling technique and this analysis compromises policy-related documents. Third, Flanders seems mostly interested in using waste or residual heat as a heating source for DHC. The harbors and waste incineration plants are identified as potential and promising supply sources. This approach tries to conciliate environmental and economic incentives. Last, local councils get assigned a central role and the initiative is mostly taken by them. The policy documents and policy advices demonstrate that Flanders opts for a bottom-up organization. As DHC is very dependent on local conditions, this seems a logic step. Nevertheless, this can impede smaller councils to create DHC networks and slow down systematic and fast implementation of DHC throughout Flanders.

Keywords: district heating and cooling, flanders, overton database, policy analysis

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