Search results for: neural networks multi-layer perceptron

Authors: Feng Guolin, Gong Zhiqiang

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In order to study the spatial structure and dynamical mechanism of extreme precipitation in East Asia, a corresponding climate network is constructed by employing the method of event synchronization. It is found that the area of East Asian summer extreme precipitation can be separated into two regions: one with high area weighted connectivity receiving heavy precipitation mostly during the active phase of the East Asian Summer Monsoon (EASM), and another one with low area weighted connectivity receiving heavy precipitation during both the active and the retreat phase of the EASM. Besides，a way for the prediction of extreme precipitation is also developed by constructing a directed climate networks. The simulation accuracy in East Asia is 58% with a 0-day lead, and the prediction accuracy is 21% and average 12% with a 1-day and an n-day (2≤n≤10) lead, respectively. Compare to the normal EASM year, the prediction accuracy is lower in a weak year and higher in a strong year, which is relevant to the differences in correlations and extreme precipitation rates in different EASM situations. Recognizing and identifying these effects is good for understanding and predicting extreme precipitation in East Asia.

Keywords: synchronization, climate network, prediction, rainfall

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Authors: Olawale-Olakunle Olajumoke Elizabeth

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There are many challenges which are been encountered in the area of tourism in Nigeria. This research work on Tourism Challenges and Prospects: The Nigerian Experience with a case study of Benin City, was carried out so as to identify the various challenges. Questionnaires were designed and administered in the various locations of Benin City, using the designed objectives and hypothesis. Use is made of both primary and secondary data collections, to gather information. The obtained data were subjected to statistical analysis where results were obtained for discussion. The results obtained showed that Tourism in the area is grossly affected by factors such as lack of preferred destination, lack of consistency in policy, erratic power-supply, bad road networks, insecurity in the city and perennial conflicts, no enabling environment for investors or tourists among others. It was revealed that touristic activities in the area are at low level due to economic hardship and this is rubbing the city of its contribution to the national economy. It is however recommended that the government should create an enabling environment for both investors and tourists, as this will fasten the development of tourism in the city.

Keywords: destination, network, tourists and investors, Nigeria, industry

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Authors: Hafiza Khaddija Saman, Muhammad Sufyan

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The increase in availability and popularity of mobile wireless devices has led researchers to develop a wide variety of Mobile Ad-hoc Networking (MANET) protocols to exploit the unique communication opportunities presented by these devices. Devices are able to communicate directly using the wireless spectrum in a peer-to-peer fashion, and route messages through intermediate nodes, however, the nature of wireless shared communication and mobile devices result in many routing and security challenges which must be addressed before deploying a MANET. In this paper, we investigate the range of MANET routing protocols available and discuss the functionalities of several ranging from early protocols such as DSDV to more advanced such as MAODV, our protocol study focuses upon works by Perkins in developing and improving MANET routing. A range of literature relating to the field of MANET routing was identified and reviewed, we also reviewed literature on the topic of securing AODV based MANETs as this may be the most popular MANET protocol. The literature review identified a number of trends within research papers such as exclusive use of the random waypoint mobility model, excluding key metrics from simulation results and not comparing protocol performance against available alternatives.

Keywords: protocol, MANET, ad-Hoc, communication

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Authors: Hossein Mohammadi Rouzbahani, Hadis Karimipour, Evan Fraser, Ali Dehghantanha, Emily Duncan, Arthur Green, Conchobhair Russell

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Human population growth has driven rising demand for food that has, in turn, imposed huge impacts on the environment. In an effort to reconcile our need to produce more sustenance while also protecting the world’s ecosystems, farming is becoming more reliant on smart tools and communication technologies. Developing a smart farming framework allows farmers to make more efficient use of inputs, thus protecting water quality and biodiversity habitat. Internet of Things (IoT), which has revolutionized every sphere of the economy, is being applied to agriculture by connecting on-farm devices and providing real-time monitoring of everything from environmental conditions to market signals through to animal health data. However, utilizing IoT means farming networks are now vulnerable to malicious activities, mostly when wireless communications are highly employed. With that in mind, this research aims to review different utilized communication technologies in smart farming. Moreover, possible cyber-attacks are investigated to discover the vulnerabilities of communication technologies considering the most frequent cyber-attacks that have been happened.

Keywords: smart farming, Internet of Things, communication layer, cyber-attack

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Authors: Ali Abdrhman M. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The color image is decomposed into red, green, and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using a key image that has same original size and is generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours of color image recovery can be obtained with accepted level of distortion using Canny edge detector. Experiments have demonstrated that proposed algorithm can fully encrypt 2D color image and completely reconstructed without any distortion. It has shown that the color image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: color image, wavelet transform, edge detector, Arnold transform, lossy image encryption

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Authors: Jong Han Joo, Jung Hoon Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

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In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. We propose a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector

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Authors: Arash Najmaei, Jo Rhodes, Peter Lok, Zahra Sadeghinejad

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In this article, we endeavor to explore how a new business model comes into existence in the Australian cloud-computing eco-system. Findings from multiple case study methodology reveal that to develop a business model new ventures adopt a three-phase approach. In the first phase, labelled as business model ideation (BMID) various ideas for a viable business model are generated from both internal and external networks of the entrepreneurial team and the most viable one is chosen. Strategic consensus and commitment are generated in the second phase. This phase is a business modelling strategic action phase. We labelled this phase as business model strategic commitment (BMSC) because through commitment and the subsequent actions of executives resources are pooled, coordinated and allocated to the business model. Three complementary sets of resources shape the business model: managerial (MnRs), marketing (MRs) and technological resources (TRs). The third phase is the market-test phase where the business model is reified through the delivery of the intended value to customers and conversion of revenue into profit. We labelled this phase business model actualization (BMAC). Theoretical and managerial implications of these findings will be discussed and several directions for future research will be illuminated.

Keywords: entrepreneur business model, high-tech venture, resources, conversion of revenue

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Authors: Ana Sofia Saldanha

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The globalization is changing the translation world day after day, year after year. The need to know more about new technologies, clients, companies and social networks is becoming more and more demanding and competitive. The recently graduated translators usually do not know where to go, what to do or even who to contact to start their careers in translation. It is well known that there are innumerous webinars, books, blogs, webpages and even Facebook pages indicating what to do, what not to do, rates, how your CV should look like, etc. but are these pieces of advice of real translators? Translators, who work daily with clients, who understand their demands, requests, questions? As far as today`s trends, the answer is NO. Most of these pieces of advice are just theoretical and far away from the real translation world. Therefore, mentoring is becoming a very important tool to help and guide new translators starting their career. An effective and well-oriented mentoring is a powerful way to orient these translators on how to create their CVs, where to send CVs, how to approach clients, how to answer emails and how to negotiate rates in an efficient way. Mentoring is crucial when properly delivered by professional and experienced translators, to help developing careers. The advice and orientation sessions are almost a 'weapon' to destroy the barriers created by opinions, by influences or even by universities. This new trend is the future path of new translators and is the future of the translation industry and professionals, however minds and spirits need to be opened and engaged in this new way of developing skills.

Keywords: mentoring, translation, translators, orientation, professional path

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Authors: Aaminah Hassan

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Advertisements carry a great potential to influence our lives because they are crafted to meet particular ends. Stereotypical representation in advertisements is capable of forming unconscious attitudes among people towards any gender and their abilities. This study focuses on gender representation in Pakistani prime time advertisements. For this purpose, 13 advertisements were selected from three different categories of foods and beverages, cosmetics, cell phones and cellular networks from the prime time slots of one of the leading Pakistani entertainment channel, ‘Urdu 1’. Both quantitative and qualitative analyses are carried out for range of variables like gender, age, roles, activities, setting, appearance and voice overs. The results revealed that gender representation in advertisements is stereotypical. Moreover, in few instances, the portrayal of women is not only culturally inappropriate but is demeaning to the image of women as well. Their bodily charm is used to promote products. Comparing different entertainment channels for their prime time advertisements and broadening the scope of this research will yield greater implications for the researchers who want to carry out the similar research. It is hoped that the current study would help in the promotion of media literacy among the viewers and media authorities in Pakistan.

Keywords: Advertisements, Content Analysis, Gender, Prime time

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Authors: Ahmed Noor Al-Qayyim

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During the past decades, the bridge structures are considered very important portions of transportation networks, due to the fast urban sprawling. With the failure of bridges that under operating conditions lead to focus on updating the default bridge inspection methodology. The structures health monitoring (SHM) using the vibration response appeared as a promising method to evaluate the condition of structures. The rapid development in the sensors technology and the condition assessment techniques based on the vibration-based damage detection made the SHM an efficient and economical ways to assess the bridges. SHM is set to assess state and expects probable failures of designated bridges. In this paper, a presentation for Frequency Response function method that uses the captured vibration test information of structures to evaluate the structure condition. Furthermore, the main steps of the assessment of bridge using the vibration information are presented. The Frequency Response function method is applied to the experimental data of a full-scale bridge.

Keywords: bridge assessment, health monitoring, damage detection, frequency response function (FRF), signal processing, structure identification

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Authors: Panagiotis I. Mallios, Vassilis S. Moustakis

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The research reported herein presents a conceptual model that explores the relationship between social media factors and entrepreneurial intention, with a focus on the Greek startup ecosystem. The significance of the study is that social media have gained importance in explaining the entrepreneurial process, and through them, nascent and potential entrepreneurs seem to get inspired and motivated to initiate their businesses. The research methodology employed in this study included a qualitative research approach, utilizing in-depth interviews with a sample of 15 startup entrepreneurs providing valuable retrospective information. The data collected were analyzed using the content analysis method. The major findings of the study are that social media factors such as usefulness, influence, and credibility have a significant impact on entrepreneurial intention. We also found that social media can be a powerful tool for entrepreneurs to access resources, knowledge and networks that can help them in their venture creation. Overall, this research contributes to the entrepreneurship literature by uncovering the relationship between social media factors and entrepreneurial intention and has implications for entrepreneurial education, policymakers, and official partners, highlighting the potential of social media to enhance the startup ecosystem.

Keywords: entrepreneurial intention, social media, start up ecosystem, entrepreneurship

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Authors: Arindam Roy, Madhushree Das, Apurba Manna, Samir Maity

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In this research paper, an algorithmic approach is developed to solve a novel multi-objective four-dimensional traveling salesman problem (MO4DTSP) where different paths with various numbers of conveyances are available to travel between two cities. NSGA-II and Decomposition algorithms are modified to solve MO4DTSP in an IoT-based transport system. This IoT-based transport system can be widely observed, analyzed, and controlled by an extensive distribution of traffic networks consisting of various types of sensors and actuators. Due to urbanization, most of the cities are connected using an intelligent traffic management system. Practically, for a traveler, multiple routes and vehicles are available to travel between any two cities. Thus, the classical TSP is reformulated as multi-route and multi-vehicle i.e., 4DTSP. The proposed MO4DTSP is designed with traveling cost, time, and customer satisfaction as objectives. In reality, customer satisfaction is an important parameter that depends on travel costs and time reflects in the present model.

Keywords: multi-objective four-dimensional traveling salesman problem (MO4DTSP), decomposition, NSGA-II, IoT-based transport system, customer satisfaction

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Authors: Hamed Alqahtani, Manolya Kavakli-Thorne

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The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classifier network in latent space. The proposed approach employs a modified generative adversarial network framework consisting of an encoder-decoder structure embedded with a classifier in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with significant attribute variations. Experimental results and comparison with state of the art in the field prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classification losses.

Keywords: disentanglement, face detection, generative adversarial networks, video surveillance

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Authors: Arūnas Burinskas

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Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

Keywords: Bertrand and Cournot Competition, competition model, industry 4.0, industrial organisation, monopolistic competition

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Authors: Salwa Salman

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On February 2016, Egypt’s President Abdel Fattah Al-Sisi ordered the former Prime Minister, Ibrahim Mehleb, to establish a committee responsible for retrieving looted state lands or providing squatters with land titles according to their individual cases. The specificity of desert lands emerges from its unique position in both Islamic law and Egypt’s Civil Code. In Egypt, desert lands can be transferred to private ownership through peaceful occupation and cultivation. This study explores the (re-) conceptualization of land rights, state territoriality, and sovereignty as a part of an emerging narrative on informal land tenure. Through the lens of an informal settlement, the study employs methodological insights from studies in the anthropology of development and their interpretation of Foucauldian discourse analysis to examine official representations on squatting over state lands and put them in conversation with individual narratives on land ownership and dispossession. It also employs Bruno Latour’s actor-network theory to explore the development of social networks through primary land contracts and informal local resource management.

Keywords: State lands, squatter community, Islamic law, Egypt’s Civil Code

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Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

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This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

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Authors: Esmeralda Hysenbelliu

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Over the last years, the demand for high bandwidth services, such as live (IPTV Service) and on-demand video streaming, steadily and rapidly increased. It has been predicted that video traffic (IPTV, VoD, and WEB TV) will account more than 90% of global Internet Protocol traffic that will cross the globe in 2016. Consequently, the importance and consideration on requirements and challenges of service providers faced today in supporting user’s requests for entertainment video across the various IPTV services through virtualization over Software Defined Networks (SDN), is tremendous in the highest stage of attention. What is necessarily required, is to deliver optimized live and on-demand services like Internet Protocol Service (IPTV Service) with low cost and good quality by strictly fulfill the essential requirements of Clients and ISP’s (Internet Service Provider’s) in the same time. The aim of this study is to present an overview of the important requirements and challenges of IPTV service with two network trends on solving challenges through virtualization (SDN and Network Function Virtualization). This paper provides an overview of researches published in the last five years.

Keywords: challenges, IPTV service, requirements, software defined networking (SDN)

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Authors: Luana Parisi, Sohrab Donyavi

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Cities have become the nodes of global networks, standing at the intersection points of the flows of capital, goods, workers, businesses and travellers, making them the spots where innovation, progress and economic development occur. The primary challenge for them is to create the most fertile ecosystems for triggering innovation activities. Design emerges as an essential feature in this process of laboratorisation of cities. This paper aims at exploring the spatial hubs of transformation within the knowledge economy, providing an overview of the current models of innovation spaces, before focusing on the innovation district of one of the cities that are riding the innovation wave, namely, Boston, USA. Useful lessons will be drawn from the case study of the innovation district in Boston, allowing to define precious tools for policymakers, in the form of a range of factors that define the broad strategy able to implement the model successfully. A mixed methodology is implemented, including information from observations, exploratory interviews to key stakeholders and on-desk data.

Keywords: Innovation District, innovation ecosystem, economic development, urban regeneration

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Authors: Kate Smith, Shuming Liu, Yi Liu, Dragan Savic, Gustaf Olsson, Tian Chang, Xue Wu

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In a water supply system, a great deal of care goes into sourcing, treating and delivering water to consumers, but less thought is given to the energy consumed during these processes. This study uses 2011 data to quantify energy use for urban water supply in China and investigates population density as a possible influencing factor. The objective is to provide information that can be used to develop energy-conscious water infrastructure policy, calculate the energy co-benefits of water conservation and compare energy use between China and other countries. The average electrical energy intensity and per capita electrical energy consumption for urban water supply in China in 2011 were 0.29 kWh/m3 and 33.2 kWh/cap•yr, respectively. Comparison between provinces revealed a direct correlation between energy intensity of urban water supply and population served per unit length of pipe. This could imply energy intensity is lower when more densely populated areas are supplied by relatively dense networks of pipes. This study also found that whereas the percentage of energy used for urban water supply tends to increase with the percentage of population served this increase is slower where water supply is more energy efficient and where a larger percentage of population is already supplied.

Keywords: china, electrical energy use, water-energy nexus, water supply

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Alexander Hempfing

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The desire to understand business cycle fluctuations, trade interdependencies and co-movement has a long tradition in economic thinking. From input-output economics to business cycle theory, researchers aimed to find appropriate answers from an empirical as well as a theoretical perspective. This paper empirically analyses how the production structure of the global economy and several states developed over time, what their distributional properties are and if there are network specific metrics that allow identifying structurally important nodes, on a global, national and sectoral scale. For this, the World Input-Output Database was used, and different statistical methods were applied. Empirical evidence is provided that the importance of the Eastern hemisphere in the global production network has increased significantly between 2000 and 2014. Moreover, it was possible to show that the sectoral eigenvector centrality indices on a global level are power-law distributed, providing evidence that specific national sectors exist which are more critical to the world economy than others while serving as a hub within the global production network. However, further findings suggest, that global production cannot be characterized as a scale-free network.

Keywords: economic integration, industrial organization, input-output economics, network economics, production networks

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Authors: Moataz Ammar, Ahdab Elmorshedy

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The distributed generation hosting capacity of a distribution network is typically limited at a given connection point by the upper voltage limit that can be violated due to the injection of active power into the distribution network. The upper voltage limit violation concern becomes more important as the network equivalent resistance increases with respect to its equivalent reactance. This paper investigates the impact of modifying the distribution network equivalent reactance at the point of connection such that the upper voltage limit is violated at a higher distributed generation penetration, than it would without the addition of series reactive compensation. The results show that series reactive compensation proves efficient in certain situations (based on the ratio of equivalent network reactance to equivalent network resistance at the point of connection). As opposed to the conventional case of capacitive compensation of a distribution network to reduce voltage drop, inductive compensation is seen to be more appropriate for alleviation of distributed-generation-induced voltage rise.

Keywords: distributed generation, distribution networks, series compensation, voltage rise

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Authors: Arsenio Jose Mindu

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The concern to carry out a study related to Energy Efficiency arose based on the various debates in international television networks and not only, but also in several forums of national debates. The concept of Energy Efficiency is not yet widely disseminated and /or taken into account in terms of energy consumption, not only at the domestic level but also at the industrial level in Mozambique. In the context of the energy audit, the time during which each of the appliances is connected to the voltage source, the time during which they are in standby mode was recorded on a spreadsheet basis. Based on these data, daily and monthly consumption was calculated. In order to have more accurate information on the daily levels of daily consumption, the electricity consumption was read every hour of the day (from 5:00 am to 11:00 pm), since after 23:00 the energy consumption remains constant. For ten days. Based on the daily energy consumption and the maximum consumption power, the design of the photovoltaic system for the residence was made. With the implementation of the photovoltaic system in order to guarantee energy efficiency, there was a significant reduction in the use of electricity from the public grid, increasing from approximately 17 kwh per day to around 11 kwh, thus achieving an energy efficiency of 67.4 %. That is to say, there was a reduction not only in terms of the amount of energy consumed but also of the monthly expenses with electricity, having increased from around 2,500,00Mt (2,500 meticais) to around 800Mt per month.

Keywords: energy efficiency, photovoltaic system, residential sector, Mozambique

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Authors: John Onyima, Ikechukwu Ezepue

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Virtualization and cloud computing are among the fast-growing computing innovations in recent times. Organisations all over the world are moving their computing services towards the cloud this is because of its rapid transformation of the organization’s infrastructure and improvement of efficient resource utilization and cost reduction. However, this technology brings new security threats and challenges about safety, reliability and data confidentiality. Evidently, no single security technique can guarantee security or protection against malicious attacks on a cloud computing network hence an integrated model of intrusion detection and prevention system has been proposed. Anomaly-based and signature-based detection techniques will be integrated to enable the network and its host defend themselves with some level of intelligence. The anomaly-base detection was implemented using the local deviation factor graph-based (LDFGB) algorithm while the signature-based detection was implemented using the snort algorithm. Results from this collaborative intrusion detection and prevention techniques show robust and efficient security architecture for cloud computing networks.

Keywords: anomaly-based detection, cloud computing, intrusion detection, intrusion prevention, signature-based detection

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Authors: Vishwanath Pethri Kamath, Jayantha Gowda Sarapanahalli, Vishal Mishra, Siddhesh Balwant Bandgar

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Recognition of emotional information is essential in any form of communication. Growing HCI (Human-Computer Interaction) in recent times indicates the importance of understanding of emotions expressed and becomes crucial for improving the system or the interaction itself. In this research work, textual data for emotion recognition is used. The text being the least expressive amongst the multimodal resources poses various challenges such as contextual information and also sequential nature of the language construction. In this research work, the proposal is made for a neural architecture to resolve not less than 8 emotions from textual data sources derived from multiple datasets using google pre-trained word2vec word embeddings and a Multi-head attention-based bidirectional LSTM model with a one-vs-all Multi-Level Classification. The emotions targeted in this research are Anger, Disgust, Fear, Guilt, Joy, Sadness, Shame, and Surprise. Textual data from multiple datasets were used for this research work such as ISEAR, Go Emotions, Affect datasets for creating the emotions’ dataset. Data samples overlap or conflicts were considered with careful preprocessing. Our results show a significant improvement with the modeling architecture and as good as 10 points improvement in recognizing some emotions.

Keywords: text emotion recognition, bidirectional LSTM, multi-head attention, multi-level classification, google word2vec word embeddings

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Authors: A. Alem, Y. Dahmani, A. Hadjali, A. Boualem

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Managing the problem of the conflict, either by using the Dempster-Shafer theory, or by the application of the fusion process to push researchers in recent years to find ways to get to make best decisions especially; for information systems, vision, robotic and wireless sensor networks. In this paper we are interested to take account of the conflict in the combination step that took the conflict into account and tries to manage such a way that it does not influence the decision step, the conflict what from reliable sources. According to [1], the conflict lead to erroneous decisions in cases where was with strong degrees between sources of information, if the conflict is more than the maximum of the functions of belief mass K > max1...n (mi (A)), then the decision becomes impossible. We will demonstrate in this paper that the multiplication of mass functions by coefficients of reliability is a decreasing function; it leads to the reduction of conflict and a good decision. The definition of reliability coefficients accurately and multiply them by the mass functions of each information source to resolve the conflict and allow deciding whether the degree of conflict. The evaluation of this technique is done by a use case; a comparison of the combination of springs with a maximum conflict without, and with reliability coefficients.

Keywords: Dempster-Shafer theory, fusion process, conflict managing, reliability factors, decision

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Authors: Muhammad Rehan Usman, Muhammad Arslan Usman, Soo Young Shin

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The new era of digital communication has brought up many challenges that network operators need to overcome. The high demand of mobile data rates require improved networks, which is a challenge for the operators in terms of maintaining the quality of experience (QoE) for their consumers. In live video transmission, there is a sheer need for live surveillance of the videos in order to maintain the quality of the network. For this purpose objective algorithms are employed to monitor the quality of the videos that are transmitted over a network. In order to test these objective algorithms, subjective quality assessment of the streamed videos is required, as the human eye is the best source of perceptual assessment. In this paper we have conducted subjective evaluation of videos with varying spatial and temporal impairments. These videos were impaired with frame freezing distortions so that the impact of frame freezing on the quality of experience could be studied. We present subjective Mean Opinion Score (MOS) for these videos that can be used for fine tuning the objective algorithms for video quality assessment.

Keywords: frame freezing, mean opinion score, objective assessment, subjective evaluation

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Authors: A. Fayad, Q. Alqhazaly, T. Cinkler

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In light of the substantial increase in end-user requirements and the incessant need of network operators to upgrade the capabilities of access networks, in this paper, the performance of the different modulation formats on eight-channels Time and Wavelength Division Multiplexing Passive Optical Network (TWDM-PON) transmission system has been examined and compared. Limitations and features of modulation formats have been determined to outline the most suitable design to enhance the data rate and transmission reach to obtain the best performance of the network. The considered modulation formats are On-Off Keying Non-Return-to-Zero (NRZ-OOK), Carrier Suppressed Return to Zero (CSRZ), Duo Binary (DB), Modified Duo Binary (MODB), Quadrature Phase Shift Keying (QPSK), and Differential Quadrature Phase Shift Keying (DQPSK). The performance has been analyzed by varying transmission distances and bit rates under different channel spacing. Furthermore, the system is evaluated in terms of minimum Bit Error Rate (BER) and Quality factor (Qf) without applying any dispersion compensation technique, or any optical amplifier. Optisystem software was used for simulation purposes.

Keywords: BER, DuoBinary, NRZ-OOK, TWDM-PON

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Authors: Zhou Mo, Dennis Chow

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In the dynamic positioning system (DPS) for vessels, the reliable information transmission between each note basically relies on the wireless protocols. From the perspective of cluster-based routing protocols for wireless sensor networks, the data fusion technology based on the sleep scheduling mechanism and remaining energy in network layer is proposed, which applies the sleep scheduling mechanism to the routing protocols, considering the remaining energy of node and location information when selecting cluster-head. The problem of uneven distribution of nodes in each cluster is solved by the Equilibrium. At the same time, Classified Forwarding Mechanism as well as Redelivery Policy strategy is adopted to avoid congestion in the transmission of huge amount of data, reduce the delay in data delivery and enhance the real-time response. In this paper, a simulation test is conducted to improve the routing protocols, which turn out to reduce the energy consumption of nodes and increase the efficiency of data delivery.

Keywords: DPS for vessel, wireless sensor network, data fusion, routing protocols

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Authors: Raymond Xu, Ashley Hua, Andrew Wang, Yuru Lin

Abstract:

During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.

Keywords: artificial intelligence, COVID-19, depression detection, psychiatric disorder

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