Search results for: transformer neural networks

Authors: Driss Bouyahya

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During the late 1960s, Islam-oriented social movements have encroached to reach the Moroccan public spheres and mobilize huge waves of people from different walks of life under the banners of a rhetoric that resonates with the Muslim way of life away from Modernity and globalization tenets. In this respect, the present study investigates and explores some of the ways utilized by the Movement for Unity and Reform in Morocco as an Islam-oriented movement to recruit students massively at universities. The significance of this study lies in demystifying the recruitment strategies and mechanisms, considered essential for the Islam-oriented social movements to mobilize. This research paper uses a quantitative method to collect and analyze data through two different structured questionnaires. One of the major findings is that this Islam-oriented movement uses different techniques to recruit students, namely social networks, its websites and You-tube as three main modern and sophisticated means of communication. In a nutshell, this paper´s findings fill some of the gaps in the literature in regard to Islam-oriented movements ‘mobilization strategies.

Keywords: changing, ideology, Islam, party

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Authors: Mohammed Fakehy, Mohammed Haggag

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The problem of test anxiety considered as one of the most important and most complex psychological problems faced by students of King Saud University, where university students in a need to bring their reassurance and psychological comfort, relieves feeling pain and difficulties of the study. Recently, there are programs and science that help human to change, including the science Linguistic Programming this neural science stems from not just the tips of the need to make the effort or continue to work, but provides the keys in which one can be controlled in the internal environment. Even human potential energy is extracted seeking to achieve success and happiness and excellence. Through the work of the researchers as members of the teaching staff at King Saud University and specialists in the field of psychology noticed the suffering of some students of King Saud University, test anxiety. In an attempt by the researchers to mitigate as much as possible of the unity of this concern, students will have a training program in Neuro Linguistic Programming. The main Question of this study is What is the effectiveness of the impact of a training program using NLP to reduce test anxiety by using a biological feedback. Therefore, the results of this study might serve as a good announcement about the usefulness of NLP programs which influence future research to significant effect of NLP on test anxiety.

Keywords: neuro linguistic programming, test anxiety, biological feedback, king saud

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Authors: Kang Won Lee, Jung Won Lee

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Characterizing the network flow is of fundamental importance to understand the complex dynamics of networks. And passenger flow characteristics of the subway network are very relevant for an effective transportation management in urban cities. In this study, passenger flow of Seoul metropolitan subway network is investigated and characterized through statistical analysis. Traditional betweenness centrality measure considers only topological structure of the network and ignores the transportation factors. This paper proposes a weighted betweenness centrality measure that incorporates monthly passenger flow volume. We apply the proposed measure on the Seoul metropolitan subway network involving 493 stations and 16 lines. Several interesting insights about the network are derived from the new measures. Using Kolmogorov-Smirnov test, we also find out that monthly passenger flow between any two stations follows a power-law distribution and other traffic characteristics such as congestion level and throughflow traffic follow exponential distribution.

Keywords: betweenness centrality, correlation coefficient, power-law distribution, Korea traffic DB

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Authors: Ukpaka Paschal

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Margret Boden argues that a creative product is one that is new, surprising, and valuable as a result of the combination, exploration, or transformation involved in producing it. Boden uses examples of artificial intelligence systems that fit all of these criteria and argues that real creativity involves autonomy, intentionality, valuation, emotion, and consciousness. This paper provides an analysis of all these elements in order to try to understand whether they are sufficient to account for creativity, especially human creativity. This paper focuses on Generative Adversarial Networks (GANs), which is a class of artificial intelligence algorithms that are said to have disproved the common perception that creativity is something that only humans possess. This paper will then argue that Boden’s listed properties of creativity, which capture the creativity exhibited by GANs, are not sufficient to account for human creativity, and this paper will further identify “first-person phenomenological experience” as an essential property of human creativity. The rationale behind the proposed essential property is that if creativity involves comprehending our experience of the world around us into a form of self-expression, then our experience of the world really matters with regard to creativity.

Keywords: artificial intelligence, creativity, GANs, first-person experience

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Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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Authors: Thomas D. Collin, Rachel Cunningham, Bruce Jefferson, Raffaella Villa

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Fats, oils and grease (FOG) are by-products of food preparation and cooking processes. FOG enters wastewater systems through a variety of sources such as households, food service establishments, and industrial food facilities. Over time, if no source control is in place, FOG builds up on pipe walls, leading to blockages, and potentially to sewer overflows which are a major risk to the Environment and Human Health. UK water utilities spend millions of pounds annually trying to control FOG. Despite UK legislation specifying that discharge of such material is against the law, it is often complicated for water companies to identify and prosecute offenders. Hence, it leads to uncertainties regarding the attitude to take in terms of FOG management. Research is needed to seize the full potential of implementing current practices. The aim of this research was to undertake a comprehensive study to document the extent of FOG problems in sewer lines and reinforce existing knowledge. Data were collected to develop a model estimating quantities of FOG available for recovery within Thames Water wastewater catchments. Geographical Information System (GIS) software was used in conjunction to integrate data with a geographical component. FOG was responsible for at least 1/3 of sewer blockages in Thames Water waste area. A waste-based approach was developed through an extensive review to estimate the potential for FOG collection and recovery. Three main sources were identified: residential, commercial and industrial. Commercial properties were identified as one of the major FOG producers. The total potential FOG generated was estimated for the 354 wastewater catchments. Additionally, raw and settled sewage were sampled and analysed for FOG (as hexane extractable material) monthly at 20 sewage treatment works (STW) for three years. A good correlation was found with the sampled FOG and population equivalent (PE). On average, a difference of 43.03% was found between the estimated FOG (waste-based approach) and sampled FOG (raw sewage sampling). It was suggested that the approach undertaken could overestimate the FOG available, the sampling could only capture a fraction of FOG arriving at STW, and/or the difference could account for FOG accumulating in sewer lines. Furthermore, it was estimated that on average FOG could contribute up to 12.99% of the primary sludge removed. The model was further used to investigate the relationship between estimated FOG and number of blockages. The higher the FOG potential, the higher the number of FOG-related blockages is. The GIS-based tool was used to identify critical areas (i.e. high FOG potential and high number of FOG blockages). As reported in the literature, FOG was one of the main causes of sewer blockages. By identifying critical areas (i.e. high FOG potential and high number of FOG blockages) the model further explored the potential for source-control in terms of ‘sewer relief’ and waste recovery. Hence, it helped targeting where benefits from implementation of management strategies could be the highest. However, FOG is still likely to persist throughout the networks, and further research is needed to assess downstream impacts (i.e. at STW).

Keywords: fat, FOG, GIS, grease, oil, sewer blockages, sewer networks

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Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov

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Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).

Keywords: cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing

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Authors: Helen S. Ghali, Haidy S. Ghali, Salma Ibrahim, Ossama Hosny, Hatem S. Elbehairy

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Infrastructure systems are essential assets in any community; accordingly, authorities aim to maximize its life span while minimizing the life cycle cost. This requires studying the asset conditions throughout its operation and forming a cost-efficient maintenance strategy plan. The objective of this study is to develop a highway management system that provides medium-term maintenance plans with the minimum life cycle cost subject to budget constraints. The model is applied to data collected for the highway network in India with the aim to output a 5-year maintenance plan strategy from 2019 till 2023. The main element considered is the surface coarse, either rigid or flexible pavement. The model outputs a 5-year maintenance plan for each segment given the budget constraint while maximizing the new pavement condition rating and minimizing its life cycle cost.

Keywords: infrastructure, asset management, optimization, maintenance plan

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Authors: Khalid Obaed Mahmod, Mesut Cevik

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The term smart city has appeared recently and was accompanied by many definitions and concepts, but as a simplified and clear definition, it can be said that the smart city is a geographical location that has gained efficiency and flexibility in providing public services to citizens through its use of technological and communication technologies, and this is what distinguishes it from other cities. Smart cities connect the various components of the city through the main and sub-networks in addition to a set of applications and thus be able to collect data that is the basis for providing technological solutions to manage resources and provide services. The basis of the work of the smart city is the use of artificial intelligence and the technology of the Internet of Things. The work presents the concept of smart cities, the pillars, standards, and evaluation indicators on which smart cities depend, and the reasons that prompted the world to move towards its establishment. It also provides a simplified hypothetical way to measure the ideal smart city model by defining some indicators and key pillars, simulating them with logic circuits, and testing them to determine if the city can be considered an ideal smart city or not.

Keywords: factors, indicators, logic gates, pillars, smart city

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Authors: Hamid Vahidkia

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The International Health Regulations (IHR), the sole worldwide regulations for managing infectious diseases, have remained largely unchanged since their initial release in 1951. The WHO is currently involved in updating the IHR. This article evaluates WHO's updated IHR draft and suggests enhancements to enhance global health, such as a strong focus on the organization's fundamental public health goals, activities, and crucial services; wide-reaching coverage for various health risks; establishing global monitoring through official and unofficial data networks; setting benchmarks for national public health systems, evaluating results, and ensuring accountability from countries; safeguarding human rights by implementing evidence-based guidelines and just processes; and promoting good governance by embracing fairness, impartiality, and openness. The World Health Organization needs to guarantee that countries follow health regulations and provide ample economic and technical support to less privileged nations. A crucial concern for the global community is how independent nations can collaborate to ensure that global health benefits all individuals, regardless of their economic status.

Keywords: IHR, law, health, international, WHO

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Authors: Luis Andrey Fajardo Fajardo

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We are immersed in complex systems. The human brain, the galaxies, the snowflakes are examples of complex systems. An area of interest in Complex systems is the chaos theory. This revolutionary field of science presents different ways of study than determinism and reductionism. Here is where in junction with the Nonlinear DSP, chaos theory offer valuable techniques that establish a link between time series and complex theory in terms of complex networks, so that, the study of signals can be explored from the graph theory. Recently, some people had purposed a method to transform time series in graphs, but no one had developed a suitable implementation in Python with signals extracted from Chaotic Systems or Complex systems. That’s why the implementation in Python of an existing method to transform one dimensional chaotic signals from time domain to graph domain and some measures that may reveal information not extracted in the time domain is proposed.

Keywords: Python, complex systems, graph theory, dynamical systems

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Authors: A. Anitha, M. Aishwariya

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The realization of truly ubiquitous wireless sensor networks (WSN) demands Ultra-low power wireless communication capability. Because the radio transceiver in a wireless sensor node consumes more power when compared to the computation part it is necessary to reduce the power consumption. Hence, a low power transceiver is designed and implemented in a 120 nm CMOS technology for wireless sensor nodes. The power consumption of the transceiver is reduced still by maintaining the sensitivity. The transceiver designed combines the blocks including differential oscillator, mixer, envelope detector, power amplifiers, and LNA. RF signal modulation and demodulation is carried by On-Off keying method at 2.4 GHz which is said as ISM band. The transmitter demonstrates an output power of 2.075 mW while consuming a supply voltage of range 1.2 V-5.0 V. Here the comparison of LNA and power amplifier is done to obtain an amplifier which produces a high gain of 1.608 dB at receiver which is suitable to produce a desired sensitivity. The multistage RF amplifier is used to improve the gain at the receiver side. The power dissipation of the circuit is in the range of 0.183-0.323 mW. The receiver achieves a sensitivity of about -95 dBm with data rate of 1 Mbps.

Keywords: CMOS, envelope detector, ISM band, LNA, low power electronics, PA, wireless transceiver

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Authors: Ruth Mandujano Lopez

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During the second half of the 19th century, in the transition from sail to steam navigation, the transpacific space underwent major transformation. This paper examines the role that the steamship companies between Mexico, the rest of North America and Asia played in that process. Based on primary sources found in Mexico, California, London and Hong Kong, it argues that these companies actively participated in the redefining of the Pacific space as they opened new routes, transported thousands of people and had an impact on regional geopolitics. In order to prove this, the text will present the cases of a handful of companies that emerged between 1867 and 1910 and of some of their passengers. By looking at the way the Mexican ports incorporated to the transpacific steam maritime network, this work contributes to have a better understanding of the role that Latin American ports have played in the formation of a global order. From a theoretical point of view, it proposes the conceptualization of space in the form of transnational networks as a point of departure to conceive a history that is truly global.

Keywords: mexico, steamships, transpacific, maritime companies

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Authors: Rima Hleiss, Elie Bitar, Mahmoud Hassan, Mohamad Khalil

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A comprehensive study of object recognition in the human brain requires combining both spatial and temporal analysis of brain activity. Here, we are mainly interested in three issues: the time perception of visual objects, the ability of discrimination between two particular categories (objects vs. animals), and the possibility to identify a particular spatial representation of visual objects. Our experiment consisted of acquiring dense electroencephalographic (EEG) signals during a picture-naming task comprising a set of objects and animals’ images. These EEG responses were recorded from nine participants. In order to determine the time perception of the presented visual stimulus, we analyzed the Event Related Potentials (ERPs) derived from the recorded EEG signals. The analysis of these signals showed that the brain perceives animals and objects with different time instants. Concerning the discrimination of the two categories, the support vector machine (SVM) was applied on the instantaneous EEG (excellent temporal resolution: on the order of millisecond) to categorize the visual stimuli into two different classes. The spatial differences between the evoked responses of the two categories were also investigated. The results showed a variation of the neural activity with the properties of the visual input. Results showed also the existence of a spatial pattern of electrodes over particular regions of the scalp in correspondence to their responses to the visual inputs.

Keywords: brain activity, categorization, dense EEG, evoked responses, spatio-temporal analysis, SVM, time perception

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Authors: Ghazi Al Sukkar, Yazid Khattabi, Shifen Zhong

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Most of the recent wireless LANs, broadband access networks, and digital broadcasting use Orthogonal Frequency Division Multiplexing techniques. In addition, the increasing demand of Data and Internet makes fiber optics an important technology, as fiber optics has many characteristics that make it the best solution for transferring huge frames of Data from a point to another. Radio over fiber is the place where high quality RF is converted to optical signals over single mode fiber. Optimum values for the bias level and the switching voltage for Mach-Zehnder modulator are important for the performance of radio over fiber links. In this paper, we propose a method to optimize the two parameters simultaneously; the bias and the switching voltage point of the external modulator of a radio over fiber system considering RF gain. Simulation results show the optimum gain value under these two parameters.

Keywords: OFDM, Mach Zehnder bias voltage, switching voltage, radio-over-fiber, RF gain

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Authors: Niklas Panten, Eberhard Abele

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This paper presents a novel approach for real-time and near-optimal control of industrial smart grids by deep reinforcement learning (DRL). To achieve highly energy-efficient factory systems, the energetic linkage of machines, technical building equipment and the building itself is desirable. However, the increased complexity of the interacting sub-systems, multiple time-variant target values and stochastic influences by the production environment, weather and energy markets make it difficult to efficiently control the energy production, storage and consumption in the hybrid industrial smart grids. The studied deep reinforcement learning approach allows to explore the solution space for proper control policies which minimize a cost function. The deep neural network of the DRL agent is based on a multilayer perceptron (MLP), Long Short-Term Memory (LSTM) and convolutional layers. The agent is trained within multiple Modelica-based factory simulation environments by the Advantage Actor Critic algorithm (A2C). The DRL controller is evaluated by means of the simulation and then compared to a conventional, rule-based approach. Finally, the results indicate that the DRL approach is able to improve the control performance and significantly reduce energy respectively operating costs of industrial smart grids.

Keywords: industrial smart grids, energy efficiency, deep reinforcement learning, optimal control

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Authors: Julio Kauss, Miguel Cadillo, David Mauricio

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E-commerce is a business model that allows companies to optimize the processes of buying, selling, transferring goods and exchanging services through computer networks or the Internet. In Peru, the electronic commerce is used infrequently. This situation is due, in part to the fact that there is no model that allows companies to implement an e-commerce solution, which means that most SMEs do not have adequate knowledge to adapt to electronic commerce. In this work, a reference model is proposed for the implementation of an e-commerce solution in Peruvian SMEs in the retail sector. It consists of five phases: Business Analysis, Business Modeling, Implementation, Post Implementation and Results. The present model was validated in a SME of the Peruvian retail sector through the implementation of an electronic commerce platform, through which the company increased its sales through the delivery channel by 10% in the first month of deployment. This result showed that the model is easy to implement, is economical and agile. In addition, it allowed the company to increase its business offer, adapt to e-commerce and improve customer loyalty.

Keywords: e-commerce, retail, SMEs, reference model

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Authors: Zhaohan Xie, Yining Yu, Mingliang Chen

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As research has shown a convergent tendency for aversion to AI recommendation, it is imperative to find a way to promote AI usage and better harness the technology. In the context of e-commerce, this study has found evidence that people show less avoidance of algorithms when recommending search products compared to experience products. This is due to people’s different attribution of mind to AI versus humans, as suggested by mind perception theory. While people hold the belief that an algorithm owns sufficient capability to think and calculate, which makes it competent to evaluate search product attributes that can be obtained before actual use, they doubt its capability to sense and feel, which is essential for evaluating experience product attributes that must be assessed after experience in person. The result of the behavioral investigation (Study 1, N=112) validated that consumers show low purchase intention to experience products recommended by AI. Further consumer neuroscience study (Study 2, N=26) using Event-related potential (ERP) showed that consumers have a higher level of cognitive conflict when faced with AI recommended experience product as reflected by larger N2 component, while the effect disappears for search product. This research has implications for the effective employment of AI recommenders, and it extends the literature on e-commerce and marketing communication.

Keywords: algorithm recommendation, consumer behavior, e-commerce, event-related potential, experience product, search product

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Authors: Mohamed Abdelrahman Abdalla

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Apart from their function in producing CSF, the brain ventricles have been recognized as the mere remnant of the embryological neural tube with no clear role. The lack of proper definition of the function of the brain ventricles and the central spinal canal has made it difficult to ascertain the pathophysiology of its different disease conditions or to treat them. This study aims to review the simple physics that could explain the basic function of the CNS ventricular system and to suggest new ways of approaching its pathology. There are probably more physical factors to consider than only the pressure. Monro-Killie hypothesis focuses on volume and subsequently pressure to direct our surgical management in different disease conditions. However, the enlarged volume of the ventricles in normal pressure hydrocephalus does not move any blood or brain outside the skull. Also, in idiopathic intracranial hypertension, the very high intracranial pressure rarely causes brain herniation. On this note, the continuum of the intracranial cavity with the spinal canal makes it a whole unit and hence the defect in the theory. In this study, adding different factors to the equation like brain and CSF density and positions of the brain in space, in addition to the volume and pressure, aims to identify how the ventricles are important in the CNS homeostasis. In addition, increasing the variables that we analyze to treat different CSF pathological conditions should increase our understanding and hence accuracy of treatment of such conditions.

Keywords: communicating hydrocephalus, functions of the ventricles, idiopathic intracranial hypertension physics of CSF

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Authors: Leonardo Alfredo Mendoza, Cristian Munoz, Marco Aurelio Pacheco, Manoela Kohler, Evelyn Batista, Rodrigo Moura

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Natural Language Processing (NLP) techniques are increasingly more powerful to be able to interpret the feelings and reactions of a person to a product or service. Sentiment analysis has become a fundamental tool for this interpretation but has few applications in languages other than English. This paper presents a classification of sentiment analysis in Portuguese with a base of comments from social networks in Portuguese. A word embedding's representation was used with a 50-Dimension GloVe pre-trained model, generated through a corpus completely in Portuguese. To generate this classification, the bidirectional long short-term memory and bidirectional Gated Recurrent Unit (GRU) models are used, reaching results of 99.1%.

Keywords: natural processing language, sentiment analysis, bidirectional long short-term memory, BI-LSTM, gated recurrent unit, GRU

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Authors: Mujtaba Roshan, John A. Schormans

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

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

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Authors: Hemalatha Rallapalli, K. Lal Kishore

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In comparison to systems that are typically designed to provide capabilities over a narrow frequency range through hardware elements, the next generation cognitive radios are intended to implement a broader range of capabilities through efficient spectrum exploitation. This offers the user the promise of greater flexibility, seamless roaming possible on different networks, countries, frequencies, etc. It requires true paradigm shift i.e., liberalization over a wide band of spectrum as well as a growth path to more and greater capability. This work contributes towards the design and implementation of an open spectrum access (OSA) feature to unlicensed users thus offering a frequency agile radio platform that is capable of performing spectrum sensing over a wideband. Thus, an ultra-wideband (UWB) radio, which has the intelligence of spectrum sensing only, unlike the cognitive radio with complete intelligence, is named as a Smart Software Radio (SSR). The spectrum sensing mechanism is implemented based on energy detection. Simulation results show the accuracy and validity of this method.

Keywords: cognitive radio, energy detection, software radio, spectrum sensing

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Authors: Alireza Pour Ebrahimi, Vahid Abasi

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Recently by the extension of internet usage, Research on the intrusion detection system takes a significant importance. Many of improvement systems prevent internal and external network attacks by providing security through firewalls and antivirus. In recently years, intrusion detection systems gradually turn from host-based systems and depend on O.S to the distributed systems which are running on multiple O.S. In this work, by considering the diversity of computer networks whit respect to structure, architecture, resource, services, users and also security goals requirement a fully distributed collaborative intrusion detection system based on peer to peer architecture is suggested. in this platform each partner device (matched device) considered as a peer-to-peer network. All transmitted information to network are visible only for device that use security scanning of a source. Experimental results show that the distributed architecture is significantly upgradeable in respect to centralized approach.

Keywords: network, intrusion detection system, peer to peer, internal and external network

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Authors: Qais M. Yousef, Yasmeen A. Alshaer

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Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization

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Authors: Yosra Mefteh Rekik

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A computational agent-based model of financial markets stresses interactions and dynamics among a very diverse set of traders. The growing body of research in this area relies heavily on computational tools which by-pass the restrictions of an analytical method. The main goal of this research is to understand how the stock market operates and behaves how to invest in the stock market and to study traders’ behavior within the context of the artificial stock markets populated by heterogeneous agents. All agents are characterized by adaptive learning behavior represented by the Artificial Neuron Networks. By using agent-based simulations on artificial market, we show that the existence of heterogeneous agents can explain the price dynamics in the financial market. We investigate the relation between market diversity and market efficiency. Our empirical findings demonstrate that greater market heterogeneity play key roles in market efficiency.

Keywords: agent-based modeling, artificial stock market, heterogeneous expectations, financial stylized facts, computational finance

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Authors: Bruno Vilić Belina, Ivan Župan

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Smart industry concepts and digital transformation are very popular in many industries. They develop their own digital platforms, which have an important role in innovations and transactions. The main idea of smart industry digital platforms is central data collection, industrial data integration, and data usage for smart applications and services. This paper presents the development of a digital platform for building critical infrastructure protection systems in smart industries. Different service contraction modalities in service level agreements (SLAs), customer relationship management (CRM) relations, trends, and changes in business architectures (especially process business architecture) for the purpose of developing infrastructural production and distribution networks, information infrastructure meta-models and generic processes by critical infrastructure owner demanded by critical infrastructure law, satisfying cybersecurity requirements and taking into account hybrid threats are researched.

Keywords: cybersecurity, critical infrastructure, smart industries, digital platform

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Authors: A. Assif

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This paper presents the modeling of a prototype distribution static compensator (D-STATCOM) for voltage sag and swell mitigation in an unbalanced distribution system. Here the concept that an inverter can be used as generalized impedance converter to realize either inductive or capacitive reactance has been used to mitigate power quality issues of distribution networks. The D-STATCOM is here supposed to replace the widely used StaticVar Compensator (SVC). The scheme is based on the Voltage Source Converter (VSC) principle. In this model PWM based control scheme has been implemented to control the electronic valves of VSC. Phase shift control Algorithm method is used for converter control. The D-STATCOM injects a current into the system to mitigate the voltage sags. In this paper the modeling of D¬STATCOM has been designed using MATLAB SIMULINIC. Accordingly, simulations are first carried out to illustrate the use of D-STATCOM in mitigating voltage sag in a distribution system. Simulation results prove that the D-STATCOM is capable of mitigating voltage sag as well as improving power quality of a system.

Keywords: D-STATCOM, voltage sag, voltage source converter (VSC), phase shift control

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Authors: Awal Liman Sale

Abstract:

The world is fast becoming a global village; and a necessary tool for this process is communication, of which telecommunication is a key player. The quantum development is very rapid as one innovation replaces another in a matter of weeks. Interconnected phone calls across the different Nigerian Telecom service providers are mostly difficult to connect and often diverted, incurring unnecessary charges on the customers. This compels the consumers to register and use multiple subscriber information modules (SIM) so that they can switch to another if one fails. This study aims to identify and prioritize the key factors in selecting telecom service providers by subscribers in Nigeria using the Analytical Hierarchy Process (AHP) in order to match the factors with the GSM network providers and create a hierarchical structure. Opinions of 400 random subscribers of different service providers will be sought using the questionnaire. In general, four components and ten sub-components will be examined in this study. After determining the weight of these components, the importance of each in choosing the service will be prioritized in Nigeria.

Keywords: analytical hierarchy process, global village, Nigerian telecommunication, subscriber information modules

Procedia PDF Downloads 244

Authors: G. M. Komba

Abstract:

The Internet Gateway (IGW) has extra ability than a simple Mesh Router (MR) and the responsibility to route mostly the all traffic from Mesh Clients (MCs) to the Internet backbone however, IGWs are more expensive. Choosing strategic locations for the Internet Gateways (IGWs) best location in Backbone Wireless Mesh (BWM) precarious to the Wireless Mesh Network (WMN) and the location of IGW can improve a quantity of performance related problem. In this paper, we propose a novel algorithm, namely New Gateway Location Algorithm (NGLA), which aims to achieve four objectives, decreasing the network cost effective, minimizing delay, optimizing the throughput capacity, Different from existing algorithms, the NGLA increasingly recognizes IGWs, allocates mesh routers (MRs) to identify IGWs and promises to find a feasible IGW location and install minimum as possible number of IGWs while regularly conserving the all Quality of Service (QoS) requests. Simulation results showing that the NGLA outperforms other different algorithms by comparing the number of IGWs with a large margin and it placed 40% less IGWs and 80% gain of throughput. Furthermore the NGLA is easy to implement and could be employed for BWM.

Keywords: Wireless Mesh Network, Gateway Location Algorithm, Quality of Service, BWM

Procedia PDF Downloads 370

Authors: Bi Zhao

Abstract:

Neural network technology has greatly improved the output of machine translation in terms of both fluency and accuracy, which greatly increases its appeal for young users. The present exploratory study aims to find out how the Chinese undergraduates perceive and use machine translation in their daily life. A survey is conducted to collect data from 100 undergraduate students from multiple Chinese universities and with varied academic backgrounds, including arts, business, science, engineering, and medicine. The survey questions inquire about their use (including frequency, scenarios, purposes, and preferences) of and attitudes (including trust, quality assessment, justifications, and ethics) toward machine translation. Interviews and tasks of evaluating machine translation output are also employed in combination with the survey on a sample of selected respondents. The results indicate that Chinese undergraduate students use machine translation on a daily basis for a wide range of purposes in academic, communicative, and entertainment scenarios. Most of them have preferred machine translation tools, but the availability of machine translation tools within a certain scenario, such as the embedded machine translation tool on the webpage, is also the determining factor in their choice. The results also reveal that despite the reportedly limited trust in the accuracy of machine translation output, most students lack the ability to critically analyze and evaluate such output. Furthermore, the evidence is revealed of the inadequate awareness of ethical responsibility as machine translation users among Chinese undergraduate students.

Keywords: Chinese undergraduates, machine translation, trust, usage

Procedia PDF Downloads 137