Search results for: mobile network communication

Authors: Boukari Nassim

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This paper describes the use of odd pair autoregressive coefficients (Yule _Walker and Burg) for the feature extraction of electroencephalogram (EEG) signals. In the classification: the radial basis function neural network neural network (RBFNN) is employed. The RBFNN is described by his architecture and his characteristics: as the RBF is defined by the spread which is modified for improving the results of the classification. Five types of EEG signals are defined for this work: Set A, Set B for normal signals, Set C, Set D for interictal signals, set E for ictal signal (we can found that in Bonn university). In outputs, two classes are given (AC, AD, AE, BC, BD, BE, CE, DE), the best accuracy is calculated at 99% for the combined odd pair autoregressive coefficients. Our method is very effective for the diagnosis of epileptic EEG signals.

Keywords: epilepsy, EEG signals classification, combined odd pair autoregressive coefficients, radial basis function neural network

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Authors: Irina A. Gudkova, Yousra Demigha

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Scientific research is moving more and more towards the study of complex systems in several areas of economics, biology physics, and computer science. In this paper, we will work on complex systems in communication networks, Wireless Sensor Networks (WSN) that are considered as stochastic systems composed of interacting entities. The current advancements of the sensing in computing and communication systems is an investment ground for research in several tracks. A detailed presentation was made for the WSN, their use, modeling, different problems that can occur in their application and some solutions. The main goal of this work reintroduces the idea of mean field method since it is a powerful technique to solve this type of models especially systems that evolve according to a Continuous Time Markov Chain (CTMC). Modeling of a CTMC has been focused; we obtained a large system of interacting Continuous Time Markov Chain with population entities. The main idea was to work on one entity and replace the others with an average or effective interaction. In this context to make the solution easier, we consider a wireless sensor network as a multi-body problem and we reduce it to one body problem. The method was applied to a system of WSN modeled as a Markovian queue showing the results of the used technique.

Keywords: Continuous-Time Markov Chain, Hidden Markov Chain, mean field method, Wireless sensor networks

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Authors: Zeta Dooly, Aidan Duane

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The collaborative European funded research and development landscape provides prime environmental conditions for multi-disciplinary teams to learn and enhance their knowledge beyond the capability of training and learning within their own organisation cocoons. Whilst the emergence of the academic entrepreneur has changed the focus of educational institutions to that of quasi-businesses, the training and professional development of lecturers and academic staff are often not formalised to the same level as industry. This research focuses on industry and academic collaborative research funded by the European Commission. The impact of research is scalable if an optimum research network is created and managed effectively. This paper investigates network embeddedness, the nature of relationships, links, and nodes within a research network, and the enhancement of the network’s knowledge. The contribution of this paper extends our understanding of establishing and maintaining effective collaborative research networks. The effects of network embeddedness are recognized in the literature as pertinent to innovation and the economy. Network theory literature claims that networks are essential to innovative clusters such as Silicon valley and innovation in high tech industries. This research provides evidence to support the impact collaborative research has on the disparate individuals toward their innovative contributions to their organisations and their own professional development. This study adopts a qualitative approach and uncovers some of the challenges of multi-disciplinary research through case study insights. The contribution of this paper recommends the establishment of scaffolding to accommodate cooperation in research networks, role appointment, and addressing contextual complexities early to avoid problem cultivation. Furthermore, it suggests recommendations in relation to network formation, intra-network challenges in relation to open data, competition, friendships, and competency enhancement. The network capability is enhanced by the adoption of the relevant theories; network theory, open innovation, and social exchange, with the understanding that the network structure has an impact on innovation and social exchange in research networks. The research concludes that there is an opportunity to deepen our understanding of the impact of network reuse and network hoping that provides scaffolding for the network members to enhance and build upon their knowledge using a progressive approach.

Keywords: research networks, competency building, network theory, case study

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Authors: Stefano A. Denes, Riccardo Tieghi, Giovanni Elia

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The buccal fat pad is a well-established tool in oral and maxillofacial surgery and its use has proved of value for the closure of oroantral communications. Oroantral communication may be a common complication after sequestrectomy in "Bisphosphonate-related osteonecrosis of the jaws". We report a clinical case of a 70-year-old female patient in bisphosphonate therapy presented with right maxillary sinusitis and oroantral communication after implants insertion. The buccal fat pad was used to close the defect. The case had an uneventful postoperative healing without dehiscence, infection and necrosis. We postulate that the primary closure of the site with buccal fat pad may ensure a sufficient blood supply and adequate protection for an effective bone-healing response to occur.

Keywords: buccal fat pad, oroantral communication, oral surgery, dehiscence

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Authors: Razali Bin Abidin

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This paper presents the development of a portable water jet cutter for soft materials such as meat. Twelve geometries of nozzles were simulated using finite element method. Water pressure was set to 1500 lb/in². Through the simulation, highest average water output speed was 133.04 m/s. The nozzle was fabricated from Al - alloy 5052 with the Factor of Safety~ 3. This indicates that the nozzle made of Al-alloy 5052 is capable of performing the cutting process without any fracture. Preliminary design of mobile water jet hand tool is presented at the end of this paper.

Keywords: water jet, finite element, Al-alloy 5052, nozzle geometry

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Authors: Wanida Suwunniponth

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The purpose of this research was to investigate the relationship between the factors of using online social network for tourism destination in case of Bangkok area in Thailand, by extending the use of technology acceptance model (TAM). This study employed by quantitative research and the target population were entrepreneurs and local people in Bangkok who use social network-Facebook concerning tourist destinations in Bangkok. Questionnaire was used to collect data from 300 purposive samples. The multiple regression analysis and path analysis were used to analyze data. The results revealed that most people who used Facebook for promoting tourism destinations in Bangkok perceived ease of use, perceived usefulness, perceived trust in using Facebook and influenced by social normative as well as having positive attitude towards using this application. Addition, the hypothesis results indicate that acceptance of online social network-Facebook was related to the positive attitude towards using of Facebook and related to their intention to use this application for tourism.

Keywords: Facebook, online social network, technology acceptance model, tourism destination

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Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

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This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

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Authors: A. Hakimiyan, H. Namazi

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Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

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Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

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Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat (APT), malware, network security, network packet, exploit kits

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Authors: Jiawen Wang, Qijun Chen

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The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

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Authors: Chioma Ifeoma Agbasimelo, Stephen Afam Kenechukwu

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The study examined consumers’ responses to non-traditional marketing communication strategies in advertising herbal products. The study identified the following non-traditional marketing communication strategies: (a) trado-instrumental marketing strategy, (b) trado-demonstrative marketing strategy, and (c) trado-iconographic marketing strategy. Anchored on the Black Box Theory, it adopted the survey design of three metropolises (Awka, Onitsha, and Nnewi) in Anambra State, Nigeria. Major findings indicated that among the identified strategies, the trado-instrumental marketing strategy is the most dominant strategy. Other strategies: (b) trado-demonstrative marketing strategy and (c) trado-iconographic marketing strategy are sparingly used in semi-urban cities. It also found that consumers’ preferences and adoption of non-traditional marketing communication were minimal. Based on the findings, there is a need to create a unified system of integration of both traditional and non-traditional marketing communication strategies due to technology interfaces.

Keywords: advertising, consumers’ responses, herbal products, non-traditional marketing communication strategies

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Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

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Authors: Valentina Alessandra Carvalho do Vale, Elmo Thiago Lins Cöuras Ford

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Increasingly telecommunications sectors are adopting optical technologies, due to its ability to transmit large amounts of data over long distances. However, as in all systems of data transmission, optical communication channels suffer from undesirable and non-deterministic effects, being essential to know the same. Thus, this research allows the assessment of these effects, as well as their characterization and beneficial uses of these effects.

Keywords: optical communication, optical fiber, non-deterministic effects, telecommunication

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Authors: Trupti Chavan, Ramachandra Guda, Kameshwar Rao

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The lack of data is a pain problem in medical image analysis using a convolutional neural network (CNN). This work uses various spatial transformation techniques to address the medical image augmentation issue for knee detection and localization using an enhanced single shot detector (SSD) network. The spatial transforms like a negative, histogram equalization, power law, sharpening, averaging, gaussian blurring, etc. help to generate more samples, serve as pre-processing methods, and highlight the features of interest. The experimentation is done on the OpenKnee dataset which is a collection of knee images from the openly available online sources. The CNN called enhanced single shot detector (SSD) is utilized for the detection and localization of the knee joint from a given X-ray image. It is an enhanced version of the famous SSD network and is modified in such a way that it will reduce the number of prediction boxes at the output side. It consists of a classification network (VGGNET) and an auxiliary detection network. The performance is measured in mean average precision (mAP), and 99.96% mAP is achieved using the proposed enhanced SSD with spatial transformations. It is also seen that the localization boundary is comparatively more refined and closer to the ground truth in spatial augmentation and gives better detection and localization of knee joints.

Keywords: data augmentation, enhanced SSD, knee detection and localization, medical image analysis, openKnee, Spatial transformations

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Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

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The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

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Authors: Aynura Valiyeva, Basil John Thomas

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Intra-firm communication is critical for building synergy amongst internal business units of a firm, where employees from various functional departments and ranks incorporate their decision-making, understanding of organizational objectives, as well as common norms and culture for better organizational effectiveness. This study builds on and assesses a framework of the causes and consequences of effective communication in business interactions between customer and supplier firms, and the path for efficient communication within a firm. The proposed study’s structural equation modeling (SEM) analysis based on 352 sample responses collected from firm representatives at different job positions ranging from marketing to logistics operations, reveals that, in the frame of reference of intra-organizational communication, organization characteristics and shared values, top management support and style of leadership, as well as information technology, are all significantly related to communication effectiveness. Furthermore, the frequency and variety of interactions enhance the outcome of communication, that improves a company’s performance. The results reveal that cultural factors are significantly related to communication effectiveness, as well as the shared beliefs and goals. In terms of organizational factors, leadership style, top management support and information technology are significant determinants of effective communication. Among the contextual factors, interaction frequency and diversity are found to be priority factors. This study also tests the relationship between supplier and supplier firm performance in the context of communication effectiveness, and finds that they are closely related, when trust and commitment is built between business partners. When firms do business in other multicultural contexts, language and shared values with destination country must be considered significant elements of communication process.

Keywords: business performance, intra-firm communication, inter-firm communication, structural equation modeling

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Authors: V. B. Bastos, M. P. Lima, P. R. G. Kurka

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This paper applies to the creation of virtual 3D environments for the study and development of mobile robot image based navigation algorithms and techniques, which need to operate robustly and efficiently. The test of these algorithms can be performed in a physical way, from conducting experiments on a prototype, or by numerical simulations. Current simulation platforms for robotic applications do not have flexible and updated models for image rendering, being unable to reproduce complex light effects and materials. Thus, it is necessary to create a test platform that integrates sophisticated simulated applications of real environments for navigation, with data and image processing. This work proposes the development of a high-level platform for building 3D model’s environments and the test of image-based navigation algorithms for mobile robots. Techniques were used for applying texture and lighting effects in order to accurately represent the generation of rendered images regarding the real world version. The application will integrate image processing scripts, trajectory control, dynamic modeling and simulation techniques for physics representation and picture rendering with the open source 3D creation suite - Blender.

Keywords: simulation, visual navigation, mobile robot, data visualization

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Authors: Dorota Galeza

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This paper argues that networks, such as the ECN and the American network, are affected by certain small events which are inherent to path dependence and preclude the full evolution towards efficiency. It is advocated that the American network is superior to the ECN in many respects due to its greater flexibility and longer history. This stems in particular from the creation of the American network, which was based on a small number of cases. Such structure encourages further changes and modifications which are not necessarily radical. The ECN, by contrast, was established by legislative action, which explains its rigid structure and resistance to change. It might be the case that the ECN is subject not so much to path dependence but to past dependence. It might have to be replaced, as happened to its predecessor. This paper is an attempt to transpose the superiority of the American network on to the ECN. It looks at concepts such as judicial cooperation, harmonization of procedure, peer review and regulatory impact assessments (RIAs), and dispute resolution procedures. The aim is to adopt these concepts into the EU setting without recourse to legal transplantation. The major difficulty is that many of these concepts have been tested only in the US and it is difficult to tell whether they could be modified to meet EU standards. Concepts such as judicial cooperation might be difficult due to different language traditions in EU member states. It is hoped that greater flexibility, as in the American network, would boost legitimacy and transparency.

Keywords: ECN, networks, regulation, competition

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Authors: Rabail Khalid

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Social media has changed the business communication strategies in the corporate world. Firms are using social media to reach their maximum stakeholders in minimum time at different social media forums. The current study examines the role of firm-created social media communication on consumer brand perceptions and their loyalty to brand. An online survey is conducted through social media forums including Facebook and Twitter to collect data regarding social media communication of a well-reputed clothing company’s brand in Pakistan. A link is sent to 900 customers of that company. Out of 900 questionnaires, 534 were received. So, the response rate is 59.33%. During data screening and entry, 13 questionnaires are rejected due to incomplete answer. Therefore, 521 questionnaires are completed in all respect and seem to be helpful for the study. So, the positive response rate is 57.89%. The empirical results report positive and significant influence of company-generated social media communication on brand trust, brand equity, and brand loyalty. The findings of this study provide important information to the marketing professionals and brand managers to understand consumer behavior through social media communication.

Keywords: firm-created social media communication, brand trust, brand equity, consumer behavior, brand loyalty

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Authors: Han Nguyen

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The objective of this study is to investigate the impact of culture on advertising appeals in mobile phone industry via social media channel in UK, Brazil and India. Content analysis on Samsung and Nokia commercials in YouTube is conducted. The result indicates that the advertising appeals are both congruent and incongruent with cultural dimensions in UK, Brazil and India. The result suggests that Hofstede and value paradoxes might be the tools to predict the relationship between cultural values and advertising appeals.

Keywords: mobile phone advertising, international advertising, social media advertising.

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Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

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A functional model to mimic the functional correctness of a neural network compute accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of GCC compilers to the BF-16 datatype, which we addressed with a native BF-16 generator integrated into our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex neural network accelerator design by proposing a functional model-based scoreboard or software model using SystemC. The proposed functional model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT, bringing up micro-steps of execution.

Keywords: ISA, neural network, Brain Float-16, DUT

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Authors: Yeong-Seop Ahn, Myoung-Jin Kim, Young-Min Ko, Hyoung-Kyu Song

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This paper proposes a relay selection scheme utilizing an orthogonal variable spreading factor (OVSF) code in a cooperative communication. The relay selection scheme influences on the communication performance in the cooperative communication. Conventional relay selection schemes such as the best harmonic mean relay selection scheme or the threshold-based relay selection scheme should know information such as channel state information (CSI) in advance. The proposed relay selection scheme does not require information in advance by using a reference signal utilizing the OVSF code. The simulation result shows that bit error rate (BER) performance of proposed relay selection scheme is similar to the best harmonic mean relay selection scheme that is known as one of the optimal relay selection schemes.

Keywords: cooperative communication, relay selection, OFDM, OVSF code

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Authors: Eden Teshome Hunde

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Wireless sensor and actuator networks (WSANs) are of great significance in the realm of industrial automation systems. However, the aspect of security in WSANs has been somewhat overlooked. One particular security concern is the rank attack, where malicious actors actively manipulate the transmission of messages from neighboring nodes. This undermines the entire network's data collection and routing operations, resulting in a significant degradation of network performance. This attack adversely affects crucial metrics such as packet delivery ratio (PDR), latency, and power consumption, ultimately reducing the network's overall lifespan. In order to foster trust among nodes, ensure accurate delivery of data to end users, safeguard shared data in the cloud from security breaches, and prevent rank attacks within the network, it is crucial to protect the network against such malicious activities. This research paper aims to introduce an enhanced version of the Routing Protocol for Low-Power and Lossy Networks (RPL) protocol, specifically tailored to identify and eliminate rank attacks within existing WSANs. The effectiveness of the new protocol will be assessed through experimentation using Zolertia (Z1) sensors in the Cooja network simulator. To minimize network overhead on the sensors' side, the proposed scheme limits cryptographic operations to symmetric key-based mechanisms such as XORing, hash functions, and encryption. These operations will be implemented using a C-compiler and verified through the ModelSIM Altera SE edition 11.0 simulator.

Keywords: ModelSIM Altera SE, RPL, WSANs, Zolertia

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Authors: Harsh Sadawarti, Kamal Malik

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Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

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Authors: Rakelane A. Mendes, Sandro T. M. Goncalves, Raphaella L. R. Silva

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The concepts of energy harvesting and wireless energy transfer have been widely discussed in recent times. There are some ways to create autonomous systems for collecting ambient energy, such as solar, vibratory, thermal, electromagnetic, radiofrequency (RF), among others. In the case of the RF it is possible to collect up to 100 μW / cm². To collect and/or transfer energy in RF systems, a device called rectenna is used, which is defined by the junction of an antenna and a rectifier circuit. The rectenna presented in this work is resonant at the frequencies of 1.8 GHz and 2.45 GHz. Frequencies at 1.8 GHz band are e part of the GSM / LTE band. The GSM (Global System for Mobile Communication) is a frequency band of mobile telephony, it is also called second generation mobile networks (2G), it came to standardize mobile telephony in the world and was originally developed for voice traffic. LTE (Long Term Evolution) or fourth generation (4G) has emerged to meet the demand for wireless access to services such as Internet access, online games, VoIP and video conferencing. The 2.45 GHz frequency is part of the ISM (Instrumentation, Scientific and Medical) frequency band, this band is internationally reserved for industrial, scientific and medical development with no need for licensing, and its only restrictions are related to maximum power transfer and bandwidth, which must be kept within certain limits (in Brazil the bandwidth is 2.4 - 2.4835 GHz). The rectenna presented in this work was designed to present efficiency above 50% for an input power of -15 dBm. It is known that for wireless energy capture systems the signal power is very low and varies greatly, for this reason this ultra-low input power was chosen. The Rectenna was built using the low cost FR4 (Flame Resistant) substrate, the antenna selected is a microfita antenna, consisting of a Meandered dipole, and this one was optimized using the software CST Studio. This antenna has high efficiency, high gain and high directivity. Gain is the quality of an antenna in capturing more or less efficiently the signals transmitted by another antenna and/or station. Directivity is the quality that an antenna has to better capture energy in a certain direction. The rectifier circuit used has series topology and was optimized using Keysight's ADS software. The rectifier circuit is the most complex part of the rectenna, since it includes the diode, which is a non-linear component. The chosen diode is the Schottky diode SMS 7630, this presents low barrier voltage (between 135-240 mV) and a wider band compared to other types of diodes, and these attributes make it perfect for this type of application. In the rectifier circuit are also used inductor and capacitor, these are part of the input and output filters of the rectifier circuit. The inductor has the function of decreasing the dispersion effect on the efficiency of the rectifier circuit. The capacitor has the function of eliminating the AC component of the rectifier circuit and making the signal undulating.

Keywords: dipole antenna, double-band, high efficiency, rectenna

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Authors: A. Elmethnani, A. Jroud

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This coastal crude oil refinery is situated north of a big city west of Tripoli; the city then could be highly prone to downwind refinery emissions where the NNE wind direction is prevailing through most seasons of the year. Furthermore, due to the absence of an air quality monitoring network and scarce emission data available for the neighboring community, nearby residents have serious worries about the impacts of the oil refining operations on local air quality. In responding to these concerns, a short term survey has performed for three consecutive days where a semi-continues mobile monitoring approach has developed effectively in this study; the monitoring station (Compact AQM 65 AeroQual) was mounted on a vehicle to move quickly between locations, measurements of 10 minutes averaging of 60 seconds then been taken at each fixed sampling point. The downwind ambient concentration of CO, H₂S, NOₓ, NO₂, SO₂, PM₁, PM₂.₅ PM₁₀, and TSP were measured at carefully chosen sampling locations, ranging from 200m nearby the fence-line passing through the city center up to 4.7 km east to attain best spatial coverage. Results showed worrying levels of PM₂.₅ PM₁₀, and TSP at one sampling location in the city center, southeast of the refinery site, with an average mean of 16.395μg/m³, 33.021μg/m³, and 42.426μg/m³ respectively, which could be attributed to road traffic. No significant concentrations have been detected for other pollutants of interest over the study area, as levels observed for CO, SO₂, H₂S, NOₓ, and NO₂ haven’t respectively exceeded 1.707 ppm, 0.021ppm, 0.134 ppm, 0.4582 ppm, and 0.0018 ppm, which was at the same sampling locations as well. Although it wasn’t possible to compare the results with the Libyan air quality standards due to the difference in the averaging time period, the technique was adequate for the baseline air quality screening procedure. Overall, findings primarily suggest modeling of dispersion of the refinery emissions to assess the likely impact and spatial-temporal distribution of air pollutants.

Keywords: air quality, mobil monitoring, oil refinery

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Authors: Teklu Urgessa, Joong Seek Lee

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Social media is becoming the primary choice of activists to make their voices heard. This fact is coupled by two main reasons. The first reason is the emergence web 2.0, which gave the users opportunity to become content creators than passive recipients. Secondly the control of the mainstream mass media outlets by the governments and individuals with their political and economic interests. This paper aimed at exploring twitter data of network actors talking about the marathon silver medalists on Rio2016, who showed solidarity with the Oromo protesters in Ethiopia on the marathon race finish line when he won silver. The aim is to discover important insight using social network analysis and mining. The hashtag #FeyisaLelisa was used for Twitter network search. The actors’ network was visualized and analyzed. It showed the central influencers during first 10 days in August, were international media outlets while it was changed to individual activist in September. The degree distribution of the network is scale free where the frequency of degrees decay by power low. Text mining was also used to arrive at meaningful themes from tweet corpus about the event selected for analysis. The semantic network indicated important clusters of concepts (15) that provided different insight regarding the why, who, where, how of the situation related to the event. The sentiments of the words in the tweets were also analyzed and indicated that 95% of the opinions in the tweets were either positive or neutral. Overall, the finding showed that Olympic stage protest of the marathoner brought the issue of Oromo protest to the global stage. The new research framework is proposed based for event-based social network analysis and mining based on the practical procedures followed in this research for event-based social media sense making.

Keywords: human rights, Olympics, social media, network analysis, social network ming

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Authors: Chrysavgi Papagianni

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The tension between global and local has been a usual topic in discussions regarding globalization. Instead of reproducing the usual ‘gloom and doom’ arguments surrounding many of these discussions, the present paper will focus on Emirati film production and more particularly on the work of the acclaimed director Nojoom Alghanem, in order to highlight how local culture can, in fact, become a force of resistance, or else a medium of localization. As a matter of fact, Alghanem’s films, especially Sounds of the Sea, Hamama and Nearby Sky are apt examples of a localizing force in action as they tap into the audience’s dormant memories of the pre-oil past, in a country that has been swept by unprecedented development and globalization in the last 60 years. What becomes evident is that the remediation of memories in Alghanem’s films makes them more ‘mobile’ and thus allows them to circulate better in today’s network society.

Keywords: culture, film, globalization, identity

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Authors: Mari A. Virtanen, Elina Haavisto, Eeva Liikanen, Maria Kääriäinen

Abstract:

Rapid technological development and digitalization has affected also on higher education. During last twenty years multiple of electronic and mobile learning (e-learning, m-learning) platforms have been developed and have become prevalent in many universities and in the all fields of education. Ubiquitous learning (u-learning) is not that widely known or used. Ubiquitous learning environments (ULE) are the new era of computer-assisted learning. They are based on ubiquitous technology and computing that fuses the learner seamlessly into learning process by using sensing technology as tags, badges or barcodes and smart devices like smartphones and tablets. ULE combines real-life learning situations into virtual aspects and can be flexible used in anytime and anyplace. The aim of this study was to assess the effects of ubiquitous 360 o learning environment on higher education students’ clinical histotechnology competence. A quasi-experimental study design was used. 57 students in biomedical laboratory science degree program was assigned voluntarily to experiment (n=29) and to control group (n=28). Experimental group studied via ubiquitous 360o learning environment and control group via traditional web-based learning environment (WLE) in a 8-week educational intervention. Ubiquitous 360o learning environment (ULE) combined authentic learning environment (histotechnology laboratory), digital environment (virtual laboratory), virtual microscope, multimedia learning content, interactive communication tools, electronic library and quick response barcodes placed into authentic laboratory. Web-based learning environment contained equal content and components with the exception of the use of mobile device, interactive communication tools and quick response barcodes. Competence of clinical histotechnology was assessed by using knowledge test and self-report developed for this study. Data was collected electronically before and after clinical histotechnology course and analysed by using descriptive statistics. Differences among groups were identified by using Wilcoxon test and differences between groups by using Mann-Whitney U-test. Statistically significant differences among groups were identified in both groups (p<0.001). Competence scores in post-test were higher in both groups, than in pre-test. Differences between groups were very small and not statistically significant. In this study the learning environment have developed based on 360o technology and successfully implemented into higher education context. And students’ competence increases when ubiquitous learning environment were used. In the future, ULE can be used as a learning management system for any learning situation in health sciences. More studies are needed to show differences between ULE and WLE.

Keywords: competence, higher education, histotechnology, ubiquitous learning, u-learning, 360o

Procedia PDF Downloads 275

Authors: Haowei Chen, Kaiqi Xiong

Abstract:

This paper aims to answer how malware will propagate in Wireless Mesh Networks (WMNs) and how communication radius and distributed density of nodes affects the process of spreading. The above analysis is essential for devising network-wide strategies to counter malware. We answer these questions by developing an improved dynamical system that models malware propagation in the area where nodes were uniformly distributed. The proposed model captures both the spatial and temporal dynamics regarding the malware spreading process. Equilibrium and stability are also discussed based on the threshold of the system. If the threshold is less than one, the infected nodes disappear, and if the threshold is greater than one, the infected nodes asymptotically stabilize at the endemic equilibrium. Numerical simulations are investigated about communication radius and distributed density of nodes in WMNs, which allows us to draw various insights that can be used to guide security defense.

Keywords: Bluetooth security, malware propagation, wireless mesh networks, stability analysis

Procedia PDF Downloads 78