Search results for: graph representation of circuit networks

Authors: Ahmed Alutaibi, Ganti Sudhakar

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Providing better Quality-of-Service (QoS) to end users has been a challenging problem for researchers and service providers. Building applications relying on best effort network protocols hindered the adoption of guaranteed service parameters and, ultimately, Quality of Service. The introduction of Software Defined Networking (SDN) opened the door for a new paradigm shift towards a more controlled programmable configurable behavior. Openflow has been and still is the main implementation of the SDN vision. To facilitate better QoS for applications, the network must calculate and measure certain parameters. One of those parameters is the delay between the two ends of the connection. Using the power of SDN and the knowledge of application and network behavior, SDN networks can adjust to different conditions and specifications. In this paper, we use the capabilities of SDN to implement multiple algorithms to measure delay end-to-end not only inside the SDN network. The results of applying the algorithms on an emulated environment show that we can get measurements close to the emulated delay. The results also show that depending on the algorithm, load on the network and controller can differ. In addition, the transport layer handshake algorithm performs best among the tested algorithms. Out of the results and implementation, we show the limitations of Openflow and develop suggestions to solve them.

Keywords: software defined networking, quality of service, delay measurement, openflow, mininet

Procedia PDF Downloads 165

Authors: Ashraf Aly

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The aim of this study is to examine the impact of 5G communication technology radiation on human health and airport safety. The term 5G refers to the fifth generation of wireless mobile technology. The 5G wireless technology will increase the number of high-frequency-powered base stations and other devices and browsing and download speeds, as well as improve the network connectivity and play a big part in improving the performance of integrated applications, such as self-driving cars, medical devices, and robotics. 4G was the latest embedded version of mobile networking technology called 4G, and 5G is the new version of wireless technology. 5G networks have more features than 4G networks, such as lower latency, higher capacity, and increased bandwidth compared to 4G. 5G network improvements over 4G will have big impacts on how people live, business, and work all over the world. But neither 4G nor 5G have been tested for safety and show harmful effects from this wireless radiation. This paper presents biological factors on the effects of 5G radiation on human health. 5G services use C-band radio frequencies; these frequencies are close to those used by radio altimeters, which represent important equipment for airport and aircraft safety. The aviation industry, telecommunications companies, and their regulators have been discussing and weighing these interference concerns for years.

Keywords: wireless communication, radiofrequency, Electromagnetic field, environmental issues

Procedia PDF Downloads 65

Authors: Mark Pizzato

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How do ideas, images, and emotions in stage-plays and videos affect us? Do they evoke a greater awareness (or cognitive reappraisal of emotions) through possible shifts between left-cortical, right-cortical, and subcortical networks? To address these questions, this presentation summarizes the research of various neuroscientists, especially Bernard Baars and others involved in Global Workspace Theory, Matthew Lieberman in social neuroscience, Iain McGilchrist on left and right cortical functions, and Jaak Panksepp on the subcortical circuits of primal emotions. Through such research, this presentation offers an ‘inner theatre’ model of the brain, regarding major hubs of neural networks and our animal ancestry. It also considers recent experiments, by Mario Beauregard, on the cognitive reappraisal of sad, erotic, and aversive film clips. Finally, it applies the inner-theatre model and related research to survey results of theatre students who read and then watched the ‘To be or not to be’ speech in 8 different video versions (from stage and screen productions) of William Shakespeare’s Hamlet. Findings show that students become aware of left-cortical, right-cortical, and subcortical brain functions—and shifts between them—through staging and movie-making choices in each of the different videos.

Keywords: cognitive reappraisal, Hamlet, neuroscience, Shakespeare, theatre

Procedia PDF Downloads 315

Authors: Y. Wang

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The Traveling salesman problem (TSP) is NP-hard in combinatorial optimization. The research shows the algorithms for TSP on the sparse graphs have the shorter computation time than those for TSP according to the complete graphs. We present an improved iterative algorithm to compute the sparse graphs for TSP by frequency graphs computed with frequency quadrilaterals. The iterative algorithm is enhanced by adjusting two parameters of the algorithm. The computation time of the algorithm is O(CN_maxn²) where C is the iterations, N_max is the maximum number of frequency quadrilaterals containing each edge and n is the scale of TSP. The experimental results showed the computed sparse graphs generally have less than 5n edges for most of these Euclidean instances. Moreover, the maximum degree and minimum degree of the vertices in the sparse graphs do not have much difference. Thus, the computation time of the methods to resolve the TSP on these sparse graphs will be greatly reduced.

Keywords: frequency quadrilateral, iterative algorithm, sparse graph, traveling salesman problem

Procedia PDF Downloads 233

Authors: Philipp Ruf, Massiwa Chabbi, Christoph Reich, Djaffar Ould-Abdeslam

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In recent years, convolutional neural networks (CNN) have demonstrated high performance in image analysis, but oftentimes, there is only structured data available regarding a specific problem. By interpreting structured data as images, CNNs can effectively learn and extract valuable insights from tabular data, leading to improved predictive accuracy and uncovering hidden patterns that may not be apparent in traditional structured data analysis. In applying a single neural network for analyzing multimodal data, e.g., both structured and unstructured information, significant advantages in terms of time complexity and energy efficiency can be achieved. Converting structured data into images and merging them with existing visual material offers a promising solution for applying CNN in multimodal datasets, as they often occur in a medical context. By employing suitable preprocessing techniques, structured data is transformed into image representations, where the respective features are expressed as different formations of colors and shapes. In an additional step, these representations are fused with existing images to incorporate both types of information. This final image is finally analyzed using a CNN.

Keywords: CNN, image processing, tabular data, mixed dataset, data transformation, multimodal fusion

Procedia PDF Downloads 123

Authors: Hira Lal Gope, Hidekazu Fukai

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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: convolutional neural networks, coffee bean, peaberry, sorting, support vector machine

Procedia PDF Downloads 144

Authors: Thibaud Berthomier, Ali Mansour, Luc Bressollette, Frédéric Le Roy, Dominique Mottier, Léo Fréchier, Barthélémy Hermenault

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Deep Venous Thrombosis (DVT) occurs when a thrombus is formed within a deep vein (most often in the legs). This disease can be deadly if a part or the whole thrombus reaches the lung and causes a Pulmonary Embolism (PE). This disorder, often asymptomatic, has multifactorial causes: immobilization, surgery, pregnancy, age, cancers, and genetic variations. Our project aims to relate the thrombus epidemiology (origins, patient predispositions, PE) to its structure using ultrasound images. Ultrasonography and elastography were collected using Toshiba Aplio 500 at Brest Hospital. This manuscript compares two classification approaches: spectral clustering and scattering operator. The former is based on the graph and matrix theories while the latter cascades wavelet convolutions with nonlinear modulus and averaging operators.

Keywords: deep venous thrombosis, ultrasonography, elastography, scattering operator, wavelet, spectral clustering

Procedia PDF Downloads 479

Authors: Biswarup Mukherjee, Aniruddha Ghosal

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In this paper, we propose a new technique for implementing a low power full adder using a set of GDI multiplexers. Full adder circuits are used comprehensively in Application Specific Integrated Circuits (ASICs). Thus it is desirable to have low power operation for the sub components. The explored method of implementation achieves a low power design for the full adder. Simulated results using state-of-art Tanner tool indicates the superior performance of the proposed technique over conventional CMOS full adder. Detailed comparison of simulated results for the conventional and present method of implementation is presented.

Keywords: low power full adder, 2-T GDI MUX, ASIC (application specific integrated circuit), 12-T FA, CMOS (complementary metal oxide semiconductor)

Procedia PDF Downloads 348

Authors: C. E. Laburu, M. A. Barros, A. F. Zompero, O. H. M. Silva

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The work presents a teaching strategy that employs syntagmatic and paradigmatic linguistic relations in order to monitor the understanding of physics students’ concepts. Syntagmatic and paradigmatic relations are theoretical elements of semiotics studies and our research circumstances and justified them within the research program of multi-modal representations. Among the multi-modal representations to learning scientific knowledge, the scope of action of syntagmatic and paradigmatic relations belongs to the discursive writing form. The use of such relations has the purpose to seek innovate didactic work with discourse representation in the write form before translate to another different representational form. The research was conducted with a sample of first year high school students. The students were asked to produce syntagmatic and paradigmatic of Newton’ first law statement. This statement was delivered in paper for each student that should individually write the relations. The student’s records were collected for analysis. It was possible observed in one student used here as example that their monemes replaced and rearrangements produced by, respectively, syntagmatic and paradigmatic relations, kept the original meaning of the law. In paradigmatic production he specified relevant significant units of the linguistic signs, the monemas, which constitute the first articulation and each word substituted kept equivalence to the original meaning of original monema. Also, it was noted a number of diverse and many monemas were chosen, with balanced combination of grammatical (grammatical monema is what changes the meaning of a word, in certain positions of the syntagma, along with a relatively small number of other monemes. It is the smallest linguistic unit that has grammatical meaning) and lexical (lexical monema is what belongs to unlimited inventories; is the monema endowed with lexical meaning) monemas. In syntagmatic production, monemas ordinations were syntactically coherent, being linked with semantic conservation and preserved number. In general, the results showed that the written representation mode based on linguistic relations paradigmatic and syntagmatic qualifies itself to be used in the classroom as a potential identifier and accompanist of meanings acquired from students in the process of scientific inquiry.

Keywords: semiotics, language, high school, physics teaching

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Authors: Yadavalli Venkata Sridhar

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Finalization of Substation sizing and location is an important task to be carried out by electrical designers in an oil field. Practical issues influence the selection of size and location of the source substations that feed multiple production facilities are listed. Importance of selection of appropriately rated short circuit level for 11KV switchboards and constraints pertaining to availability of manufacturers are highlighted. Without being lost in the research of absolute optimum solution, under time constraints, the importance of practical approach is brought out. Focus on identifying near optimum solutions by process of elimination of unfeasible substation locations with the support of cost figures, is emphasized through a case study.

Keywords: substation, size, location, oil field

Procedia PDF Downloads 664

Authors: Hanaa Sameen Ameen Bajilan

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Human rights should be protected and promoted without regard to race, ethnicity, religion, political philosophy, or sexual orientation, following our firm convictions. Thus, any infringement of these rights or disdain for; any use of violence against women undermines the principles and human values of equality and endangers the entire society, including its potential to live in peace and to make growth and development. This paper represents the condition of the new Iraqi women regarding issues such as the gender wage gap, education, health, and violence against women. The study aims to determine the impact of traditions and customs on the legal position of Iraqi women. First, it seeks to assess the effects of culture as a historical agency on the legal status of Iraqi women. Second, the influence of cultural developments in the later part of the twentieth century on Iraqi women's legal standing, and third, the importance of cultural variety as a progressive cultural component in women's legal position. Finally, the study highlights the representation of women in Iraq: Gender wage Gap, Women's liberation between culture and law, and the role of women within Iraqi society based on an Iraqi novel named (Orange Light) in Arabic: برتقالو ضو. in her book, the Iraqi writer Nadia Al-Abru succeeds in portraying the post-war society's devotion to the sexual, emotional and mental marginalization of women in terms of the value of attendance. Since the study of Iraqi women's literature in Arabic-English translation is a new avenue of research that contributes to all three areas, this investigation aims to establish critical lines of engagement between contemporary Iraqi women's literature in English translation and feminist translation conceptual frameworks, and this is accomplished by first focusing on why analyzing Iraqi women writers' novels in Arabic-English translation is a timeline of inquiry that contributes to existing and emerging knowledge fields concerning Iraqi women writers' contemporary critical contexts and scholarship on Arab women's literature in Arabic-English translation.

Keywords: women in İraq, equality, violence, gender wage gap, Nadia Al-Abru, (orange light), women's liberation, İraqi women's literature,

Procedia PDF Downloads 91

Authors: Naveed Ghani

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With the arrival of higher speed communication links and mature application running over the internet, the requirement for reliable, efficient and robust network designs rising day by day. Multi-Protocol Label Switching technology (MPLS) Virtual Private Networks (VPNs) have committed to provide optimal network services. They are gaining popularity in industry day by day. Enterprise customers are moving to service providers that offer MPLS VPNs. The main reason for this shifting is the capability of MPLS VPN to provide built in security features and any-to-any connectivity. MPLS VPNs improved the network performance due to fast label switching as compare to traditional IP Forwarding but traffic classification and policing was still required on per hop basis to enhance the performance of real time traffic which is delay sensitive (particularly voice and video). QoS (Quality of service) is the most important factor to prioritize enterprise networks’ real time traffic such as voice and video. This thesis is focused on the study of QoS parameters (e.g. delay, jitter and MOS (Mean Opinion Score)) for the real time traffic over MPLS VPNs. DiffServ (Differentiated Services) QoS model will be used over MPLS VPN network to get end-to-end service quality.

Keywords: network, MPLS, VPN, DiffServ, MPLS VPN, DiffServ QoS, QoS Model, GNS2

Procedia PDF Downloads 426

Authors: Divya Pradip Roy, Md. Zahirul Alam Chowdhury

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Electromyography (EMG) sensors are generally used to record the electrical activity produced by skeletal muscles. The conventional EMG sensors available in the market are expensive. This research suggests a low cost EMG sensor design which can be built with simple devices within our reach. In this research, one instrumentation amplifier, two high pass filters, two low pass filters and an inverting amplifier is connected sequentially. The output from the circuit exhibits electrical potential generated by the muscle cells when they are neurologically activated. This electromyography signal is used to control prosthetic devices, identifying neuromuscular diseases and for various other purposes.

Keywords: EMG, high pass filter, instrumentation amplifier, inverting amplifier, low pass filter, neuromuscular

Procedia PDF Downloads 175

Authors: Mehran Asadi, Afrand Agah

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In data mining, partitioning is used as a fundamental tool for classification. With the help of partitioning, we study the structure of data, which allows us to envision decision rules, which can be applied to classification trees. In this research, we used online social network dataset and all of its attributes (e.g., Node features, labels, etc.) to determine what constitutes an above average chance of being a divergent node. We used the R statistical computing language to conduct the analyses in this report. The data were found on the UC Irvine Machine Learning Repository. This research introduces the basic concepts of classification in online social networks. In this work, we utilize overfitting and describe different approaches for evaluation and performance comparison of different classification methods. In classification, the main objective is to categorize different items and assign them into different groups based on their properties and similarities. In data mining, recursive partitioning is being utilized to probe the structure of a data set, which allow us to envision decision rules and apply them to classify data into several groups. Estimating densities is hard, especially in high dimensions, with limited data. Of course, we do not know the densities, but we could estimate them using classical techniques. First, we calculated the correlation matrix of the dataset to see if any predictors are highly correlated with one another. By calculating the correlation coefficients for the predictor variables, we see that density is strongly correlated with transitivity. We initialized a data frame to easily compare the quality of the result classification methods and utilized decision trees (with k-fold cross validation to prune the tree). The method performed on this dataset is decision trees. Decision tree is a non-parametric classification method, which uses a set of rules to predict that each observation belongs to the most commonly occurring class label of the training data. Our method aggregates many decision trees to create an optimized model that is not susceptible to overfitting. When using a decision tree, however, it is important to use cross-validation to prune the tree in order to narrow it down to the most important variables.

Keywords: online social networks, data mining, social cloud computing, interaction and collaboration

Procedia PDF Downloads 158

Authors: Lienjang Zeite

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Over the past few years, Turkish and Indian series have been distributed worldwide to countless households and have found ardent followers across different age group. The series have captured numerous hearts. Turkish and Indian series have become not only one of the best means of entertainment and relaxation but also a platform to learn and appreciate shared emotions and social messages. The popularity of the series has created a kind of interest in representing human emotions and stories like never before. The demands for such series have totally shifted the entertainment industry at a new level. The interest and vibe created by the series have had impacts on various departments spanning from technology to the fashion industry and it has also become the bridge to connect viewers across the globe. The series have amassed avid admirers who find solace in the beautiful visual representations of human relationships whether it is of lovers, family or friendship. The influence of Turkish and Indian series in many parts of the world has created a cultural phenomenon that has taken viewers beyond cultural and language differences. From China to Latin America, Arab countries and the Caucasus region, the series have been accepted and loved by millions of viewers. It has captivated audiences ranging from grandmothers to teenagers. Issues like language barrier are easily solved by means of translation or dubbing making it easier to understand and enjoy the series. Turkey and India are two different countries with their own unique culture and traditions. Both the countries are exporters of series in large scale. The series function as a platform to reveal the plots and shed lights on characters of all kinds. Both the countries produce series that are more or less similar in nature. However, there are also certain issues that are shown in different ways and light. The paper will discuss how emotions are represented in Turkish and Indian series. It will also discuss the ways the series have impacted the art of representing emotions and characters in the digital era. The representation of culture through Turkish and Indian series will be explored as well. The paper will also locate the issue of gender roles and how relationships are forged or abandoned in the series. The issue of character formation and importance of moral factors will be discussed. It will also examine the formula and ingredients of turning human emotions and characters into a much loved series.

Keywords: characters, cultural phenomenon, emotions, Turkish and Indian series

Procedia PDF Downloads 137

Authors: Franco Ferrucci, Driss Stitou, Pascal Ortega, Franck Lucas

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The energy situation in tropical insular regions, as found in the French Polynesian islands, presents a number of challenges, such as high dependence on imported fuel, high transport costs from the mainland and weak electricity grids. Alternatively, these regions have a variety of renewable energy resources, which favor the exploitation of smart microgrids and energy storage technologies. With regards to the electrical energy demand, the high temperatures in these regions during the entire year implies that a large proportion of consumption is used for cooling buildings, even during the evening hours. In this context, this paper presents an air conditioning system driven by photovoltaic (PV) electricity that combines a refrigeration system and a thermochemical storage process. Thermochemical processes are able to store energy in the form of chemical potential with virtually no losses, and this energy can be used to produce cooling during the evening hours without the need to run a compressor (thus no electricity is required). Such storage processes implement thermochemical reactors in which a reversible chemical reaction between a solid compound and a gas takes place. The solid/gas pair used in this study is BaCl2 reacting with ammonia (NH3), which is also the coolant fluid in the refrigeration circuit. In the proposed system, the PV-driven electric compressor is used during the daytime either to run the refrigeration circuit when a cooling demand occurs or to decompose the ammonia-charged salt and remove the gas from thermochemical reactor when no cooling is needed. During the evening, when there is no electricity from solar source, the system changes its configuration and the reactor reabsorbs the ammonia gas from the evaporator and produces the cooling effect. In comparison to classical PV-driven air conditioning units equipped with electrochemical batteries (e.g. Pb, Li-ion), the proposed system has the advantage of having a novel storage technology with a much longer charge/discharge life cycle, and no self-discharge. It also allows a continuous operation of the electric compressor during the daytime, thus avoiding the problems associated with the on-off cycling. This work focuses on the system concept and on the efficiency study of its main components. It also compares the thermochemical with electrochemical storage as well as with other forms of thermal storage, such as latent (ice) and sensible heat (chilled water). The preliminary results show that the system seems to be a promising alternative to simultaneously fulfill cooling and energy storage needs in tropical insular regions.

Keywords: microgrid, solar air-conditioning, solid/gas sorption, thermochemical storage, tropical and insular regions

Procedia PDF Downloads 241

Authors: Claudia Pisano

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The Italian shockumentary Mondo cane (1962), directed by Gualtiero Jacopetti, Paolo Cavara, and Franco Prosperi, has often been criticized for its supposed racist and colonialist stances. Several critics consider it a film that proclaims, without explicitly mentioning it, the superiority of the white Euro-American individual over the people who do not belong to white-western societies. This paper proposes a different interpretation of the way in which Mondo cane engages with the discourse of race. Through an analysis of crucial scenes and of the relationship between images and voice-over, and through a comparison between the representation of non-white societies in Mondo cane and in some popular Italian newsreels of the 50s-60s, such as 'La Settimana Incom' and 'Mondo Libero,' the paper argues that Mondo cane debunks the western-white superiority that, according to some critics, the film would promote. The continuous and rapid alternance of scenes set in the western world, for example in Europe or in the United States, and scenes set in exotic countries inhabited by non-white peoples highlights the commonalities between these far-away realities, rather than pointing out the superiority of the white-western one. In addition, the subtle irony employed by the voice-over distances Mondo cane from the newsreels that it much resembles for its documentary style. Mondo cane’s treatment and representation of race is analyzed in the light of the work of Australian Aboriginal anthropologist Aileen Moreton-Robinson, which is based on key concepts such as whiteness and whiteness invisibility. Whiteness is defined as the invisible and omnipresent norm based on which everything that does not belong to the white world is labeled as an odd and inferior 'other.' To overcome racial discrimination, it is necessary to make whiteness visible; that is to say, to deprive it of that aura of normalcy and unquestionable righteousness that surrounds it. This essay argues that Mondo cane participates in the process of making whiteness visible through the confrontation of the white people with the visible 'other'. Because the film shows that the common features on which this confrontation is based are violence and bestiality, the paper suggests that the film does not support the idea of the white world being superior to the non-white; on the contrary, it underlines that the entire world is characterized by the same shocking savagery.

Keywords: irony, race, shockumentary, whiteness, whiteness invisibility

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Authors: Ved Kulkarni, Karthik Kini

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This experiment aims to understand how the media affects the power markets in the mainland United States and study the duration of reaction time between news updates and actual price movements. it have taken into account electric utility companies trading in the NYSE and excluded companies that are more politically involved and move with higher sensitivity to Politics. The scrapper checks for any news related to keywords, which are predefined and stored for each specific company. Based on this, the classifier will allocate the effect into five categories: positive, negative, highly optimistic, highly negative, or neutral. The effect on the respective price movement will be studied to understand the response time. Based on the response time observed, neural networks would be trained to understand and react to changing market conditions, achieving the best strategy in every market. The stock trader would be day trading in the first phase and making option strategy predictions based on the black holes model. The expected result is to create an AI-based system that adjusts trading strategies within the market response time to each price movement.

Keywords: data mining, language processing, artificial neural networks, sentiment analysis

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Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

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In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

Procedia PDF Downloads 186

Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli

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Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: earthquake prediction, ANN, seismic bumps

Procedia PDF Downloads 127

Authors: WenYing Claire Shih, Konstantinos Agrafiotis

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The circular economy has become one of the seven fundamental pillars of Taiwan’s economic development, as this is promulgated by the government. The model of the circular economy, with its fundamental premise of waste elimination, can transform the textile and clothing sectors from major pollutant industries to a much cleaner alternative for a better quality of all citizens’ lives. In a related vein, the notion of the creative economy and more specifically the fashion industry can prompt similar results in terms of jobs and wealth creation. The combining forces of the circular and creative economies and their beneficial output have resulted in the configuration of ethical urban networks which potentially may lead to sources of competitive advantage. All actors involved in the configuration of this urban ethical fashion network from public authorities to private enterprise can bring about positive changes in the urban setting. Preliminary results through action research show that this configuration is an attainable task in terms of circularity by reducing fabric waste produced from local textile mills and through innovative methods of design, production and retail around urban spaces where the network has managed to generate a stream of jobs and financial revenues for all participants. The municipal authorities as the facilitating platform have been of paramount importance in this public-private partnership. In the explorative pilot study conducted about a network of production, consumption in terms of circularity of fashion products, we have experienced a positive disposition. As the network will be fully functional by attracting more participant firms from the textile and clothing sectors, it can be beneficial to Taiwan’s soft power in the region and simultaneously elevate citizens’ awareness on circular methods of fashion production, consumption and disposal which can also lead to the betterment of urban lifestyle and may open export horizons for the firms.

Keywords: the circular economy, the creative economy, ethical urban networks, action research

Procedia PDF Downloads 136

Authors: Fatma El-Zahraa El-Taher, Ayman Taha, Jane Courtney, Susan Mckeever

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Understanding road networks plays an important role in navigation applications such as self-driving vehicles and route planning for individual journeys. Intersections of roads are essential components of road networks. Understanding the features of an intersection, from a simple T-junction to larger multi-road junctions, is critical to decisions such as crossing roads or selecting the safest routes. The identification and profiling of intersections from satellite images is a challenging task. While deep learning approaches offer the state-of-the-art in image classification and detection, the availability of training datasets is a bottleneck in this approach. In this paper, a labelled satellite image dataset for the intersection recognition problem is presented. It consists of 14,692 satellite images of Washington DC, USA. To support other users of the dataset, an automated download and labelling script is provided for dataset replication. The challenges of construction and fine-grained feature labelling of a satellite image dataset is examined, including the issue of how to address features that are spread across multiple images. Finally, the accuracy of the detection of intersections in satellite images is evaluated.

Keywords: satellite images, remote sensing images, data acquisition, autonomous vehicles

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Authors: Sanghoon Park, Ki-Jin Kim, Kwang-Ho Ahn

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This paper discusses the undesirable charge transfer by the parasitic capacitances of the input transistors in a voltage sense amplifier. Due to its intrinsic rail-to-rail voltage transition, the input sides are inevitably disturbed. It can possible disturb the stabilities of the reference voltage levels. Moreover, it becomes serious in multi-channel systems by altering them for other channels, and so degrades the linearity of the systems. In order to alleviate the internal node voltage transition, the internal node stabilization technique is proposed by utilizing an additional biasing circuit. It achieves 47% and 43% improvements for node stabilization and input referred disturbance, respectively.

Keywords: voltage sense amplifier, voltage transition, node stabilization, biasing circuits

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Authors: Abdulrahman S. Alqahtani

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The revolution of computing and networks could revolutionise terrorism in the same way that it has brought about changes in other aspects of life. The modern technological era has faced countries with a new set of security challenges. There are many states and potential adversaries who have the potential and capacity in cyberspace, which makes them able to carry out cyber-attacks in the future. Some of them are currently conducting surveillance, gathering and analysis of technical information, and mapping of networks and nodes and infrastructure of opponents, which may be exploited in future conflicts. This poster presents the results of the quantitative study (survey) to test the validity of the proposed theoretical framework for the cyber terrorist threats. This theoretical framework will help to in-depth understand these new digital terrorist threats. It may also be a practical guide for managers and technicians in critical infrastructure, to understand and assess the threats they face. It might also be the foundation for building a national strategy to counter cyberterrorism. In the beginning, it provides basic information about the data. To purify the data, reliability and exploratory factor analysis, as well as confirmatory factor analysis (CFA) were performed. Then, Structural Equation Modelling (SEM) was utilised to test the final model of the theory and to assess the overall goodness-of-fit between the proposed model and the collected data set.

Keywords: cyberterrorism, critical infrastructure, , national security, theoretical framework, terrorism

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Authors: Zina Saheb, Ezz El-Masry

Abstract:

As CMOS technology scaling down, Silicon oxide thickness (SiO2) become very thin (few Nano meters). When SiO2 is less than 3nm, gate direct tunneling (DT) leakage current becomes a dormant problem that impacts the transistor performance. Floating gate MOSFET (FGMOSFET) has been used in many low-voltage and low-power applications. Most of the available simulation models of FGMOSFET for analog circuit design does not account for gate DT current and there is no accurate analysis for the gate DT. It is a crucial to use an accurate mode in order to get a realistic simulation result that account for that DT impact on FGMOSFET performance effectively.

Keywords: CMOS transistor, direct-tunneling current, floating-gate, gate-leakage current, simulation model

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Authors: Christopher Hardly Joseph, Nicola Pelagalli, Davide Mencarelli, Luca Pierantoni

Abstract:

In this contribution, we report the electromagnetic response of a split ring resonator (SRR) based magnetic metamaterial unit cell in free space nature by means of a full-wave electromagnetic simulation. The effective parameters of these designed structures have been analyzed. The structures have been specifically designed to work at high frequency considering the development of many microwave and lower mm-wave devices. In addition to that, the application of the designed metamaterial structures is also proposed, namely metamaterial loaded planar transmission lines, potentially useful to optimize size and quality factor of circuit components and radiating elements.

Keywords: CPW, Microwave Components, Negative Permeability, Split Ring Resonator (SRR)

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Authors: Yong Zhao, Jian He, Cheng Zhang

Abstract:

Cardiovascular diseases caused by hypertension are extremely threatening to human health, and early diagnosis of hypertension can save a large number of lives. Traditional hypertension detection methods require special equipment and are difficult to detect continuous blood pressure changes. In this regard, this paper first analyzes the principle of heart rate variability (HRV) and introduces sliding window and power spectral density (PSD) to analyze the time domain features and frequency domain features of HRV, and secondly, designs an HRV-based hypertension prediction network by combining Resnet, attention mechanism, and multilayer perceptron, which extracts the frequency domain through the improved ResNet18 features through a modified ResNet18, its fusion with time-domain features through an attention mechanism, and the auxiliary prediction of hypertension through a multilayer perceptron. Finally, the network was trained and tested using the publicly available SHAREE dataset on PhysioNet, and the test results showed that this network achieved 92.06% prediction accuracy for hypertension and outperformed K Near Neighbor(KNN), Bayes, Logistic, and traditional Convolutional Neural Network(CNN) models in prediction performance.

Keywords: feature extraction, heart rate variability, hypertension, residual networks

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Authors: Armana Sabiha Huq, Tahmina Rahman Chowdhury

Abstract:

In this paper, based on the stated preference experiment, the service quality of Bangladesh Railway has been assessed, and particular importance has been given to investigate if there exists a relationship between service quality and safety. For investigation purposes, environmental and organizational factors were assumed to determine the safety performance of the railway. Data collected from the survey has been analyzed by importance-performance analysis (IPA). In this paper, a modification of the well-known importance-performance analysis (IPA) has been done by adopting the importance of the weights determined through a structural equation modeling (SEM) approach and by plotting the gap between importance and performance on a visual graph. It has been found that there exists a relationship between safety and serviceability to some extent. Limited resources are an important factor to improve the safety and serviceability condition of the BD railway. Moreover, it is observed that the limited resources available to monitor and improve the safety performance of railway.

Keywords: importance-performance analysis, GAP-IPA, SEM, serviceability, safety, factor analysis

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Authors: Soulayma Smirani, Mourad Aidi, Taoufik Aguili

Abstract:

Energy harvesting has arisen as a prominent research area for low power delivery to RF devices. Rectennas have become a key element in this technology. In this paper, electromagnetic modeling of a rectenna system is presented. In our approach, a hybrid technique was demonstrated to associate both the method of auxiliary sources (MAS) and MoM-GEC (the method of moments combined with the generalized equivalent circuit technique). Auxiliary sources were used in order to substitute specific electronic devices. Therefore, a simple and controllable model is obtained. Also, it can easily be interconnected to form different topologies of rectenna arrays for more energy harvesting. At last, simulation results show the feasibility and simplicity of the proposed rectenna model with high precision and computation efficiency.

Keywords: computational electromagnetics, MoM-GEC method, rectennas, RF energy harvesting

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Authors: Christina Adly, Meena Abdelmeseeh, Tamer Basha

Abstract:

This paper proposes a system for hand movement recognition using multichannel surface EMG(sEMG) signals obtained from 40 subjects using 40 different exercises, which are available on the Ninapro(Non-Invasive Adaptive Prosthetics) database. First, we applied processing methods to the raw sEMG signals to convert them to their amplitudes. Second, we used deep learning methods to solve our problem by passing the preprocessed signals to Fully connected neural networks(FCNN) and recurrent neural networks(RNN) with Long Short Term Memory(LSTM). Using intrasubject evaluation, The accuracy using the FCNN is 72%, with a processing time for training around 76 minutes, and for RNN's accuracy is 79.9%, with 8 minutes and 22 seconds processing time. Third, we applied some postprocessing methods to improve the accuracy, like majority voting(MV) and Movement Error Rate(MER). The accuracy after applying MV is 75% and 86% for FCNN and RNN, respectively. The MER value has an inverse relationship with the prediction delay while varying the window length for measuring the MV. The different part uses the RNN with the intersubject evaluation. The experimental results showed that to get a good accuracy for testing with reasonable processing time, we should use around 20 subjects.

Keywords: hand movement recognition, recurrent neural network, movement error rate, intrasubject evaluation, intersubject evaluation

Procedia PDF Downloads 142