Search results for: memory network

Authors: Chiu-Yin Leung

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This research investigates a complex assemblage among indigenous identities, socio-political organization and national apparatus in the border landscape of post-colonial Hong Kong. This former British colony had designated a transient mode of governance in its New Territories and particularly the northernmost borderland in 1951-2012. With a discriminated system of land provisions for the indigenous villagers, the place has been inherited with distinctive village-based culture, historic monuments and agrarian practices until its sovereignty return into the People’s Republic of China. In its latest development imperatives by the national strategic planning, the frontier area of Hong Kong has been identified as a strategy site for regional economic integration in South China, with cross-border projects of innovation and technology zones, mega-transport infrastructure and inter-jurisdictional arrangement. Contemporary literature theorizes borders as the material and discursive production of territoriality, which manifest in state apparatus and the daily lives of its citizens and condense in the contested articulations of power, security and citizenship. Drawing on the concept of assemblage, this paper attempts to tract how the border regime and infrastructure in Hong Kong as a city are deeply ingrained in the everyday lived spaces of the local communities but also the changing urban and regional strategies across different longitudinal moments. Through an intensive ethnographic fieldwork among the borderland villages since 2008 and the extensive analysis of colonial archives, new development plans and spatial planning frameworks, the author navigates the genealogy of the border landscape in Ta Kwu Ling frontier area and its implications as the milieu for new state space, covering heterogeneous fields particularly in indigenous rights, heritage preservation, rural sustainability and regional economy. Empirical evidence suggests an apparent bias towards indigenous power and colonial representation in classifying landscape values and conserving historical monuments. Squatter and farm tenants are often deprived of property rights, statutory participation and livelihood option in the planning process. The postcolonial bureaucracies have great difficulties in mobilizing resources to catch up with the swift, political-first approach of the mainland counterparts. Meanwhile, the cultural heritage, lineage network and memory landscape are not protected altogether with any holistic view or collaborative effort across the border. The enactment of land resumption and compensation scheme is furthermore disturbed by lineage-based customary law, technocratic bureaucracy, intra-community conflicts and multi-scalar political mobilization. As many traces of colonial misfortune and tyranny have been whitewashed without proper management, the author argues that postcolonial justice is yet reconciled in this fragmented border landscape. The assemblage of border in mainstream representation has tended to oversimplify local struggles as a collective mist and setup a wider production of schizophrenia experiences in the discussion of further economic integration among Hong Kong and other mainland cities in the Pearl River Delta Region. The research is expected to shed new light on the theorizing of border regions and postcolonialism beyond Eurocentric perspectives. In reassembling the borderland experiences with other arrays in state governance, village organization and indigenous identities, the author also suggests an alternative epistemology in reconciling socio-spatial differences and opening up imaginaries for positive interventions.

Keywords: heritage conservation, indigenous communities, post-colonial borderland, regional development, rural sustainability

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Authors: Linda Smail, Zineb Azouz

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Given a Bayesian network relative to a set I of discrete random variables, we are interested in computing the probability distribution P(S) where S is a subset of I. The general idea is to write the expression of P(S) in the form of a product of factors where each factor is easy to compute. More importantly, it will be very useful to give an interpretation of each of the factors in terms of conditional probabilities. This paper considers a semantic interpretation of the factors involved in computing marginal probabilities in Bayesian networks. Establishing such a semantic interpretations is indeed interesting and relevant in the case of large Bayesian networks.

Keywords: Bayesian networks, D-Separation, level two Bayesian networks, factorization of computation

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: R. Loukil, M. Chtourou, T. Damak

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This paper investigates the training of multilayer neural network using the classic approach. Then, for estimation purposes, we suggest the use of a specific neural observer that we study its training algorithm which is the back-propagation one in the case of the disponibility of the state and in the case of an unmeasurable state. A MATLAB simulation example will be studied to highlight the usefulness of this kind of observer.

Keywords: training, estimation purposes, neural observer, back-propagation, unmeasurable state

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Authors: Desmond Young

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In building services electrical design, a key element of any project will be assessing the electrical load requirements. This needs to be done early in the design process to allow the selection of infrastructure that would be required to meet the electrical needs of the type of building. The type of building will define the type of assessment made, and the values applied in defining the maximum demand for the building, and ultimately the size of supply or infrastructure required, and the application that needs to be made to the distribution network operator, or alternatively to an independent network operator. The fact that this assessment needs to be undertaken early in the design process provides limits on the type of assessment that can be used, as different methods require different types of information, and sometimes this information is not available until the latter stages of a project. A common method applied in the earlier design stages of a project, typically during stages 1,2 & 3, is the use of benchmarks. It is a possibility that some of the benchmarks applied are excessive in relation to the current loads that exist in a modern installation. This lack of accuracy is based on information which does not correspond to the actual equipment loads that are used. This includes lighting and small power loads, where the use of more efficient equipment and lighting has reduced the maximum demand required. The electrical load can be used as part of the process to assess the heat generated from the equipment, with the heat gains from other sources, this feeds into the sizing of the infrastructure required to cool the building. Any overestimation of the loads would contribute to the increase in the design load for the heating and ventilation systems. Finally, with the new policies driving the industry to decarbonise buildings, a prime example being the recently introduced London Plan, loads are potentially going to increase. In addition, with the advent of the pandemic and changes to working practices, and the adoption of electric heating and vehicles, a better understanding of the loads that should be applied will aid in ensuring that infrastructure is not oversized, as a cost to the client, or undersized to the detriment of the building. In addition, more accurate benchmarks and methods will allow assessments to be made for the incorporation of energy storage and renewable technologies as these technologies become more common in buildings new or refurbished.

Keywords: energy, ADMD, electrical load assessment, energy benchmarks

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Authors: Grace Rademacher

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Trauma” of the Kingdom of Hungary and the “Lost Cause” of the American Confederacy. Applying Nicole Maurantonio’s articulation of “confederate exceptionalism” and Svetlana Boym’s definition of “restorative nostalgia”, this article argues that, via memorialization and public discourse, both far right bodies flood their constituencies with narratives of nostalgia and martyrdom to sow existential anxieties about past and prophetic victimhood, all under the guise of protecting or restoring heritage. Linking this practice to gamification and conspiracy theorizing and following the work of Patrick Jagoda, this article identifies such industries of nostalgia as means by which the far right in both nations can partake in the “immanent and improvisational process of problem making.” Reified through monuments and references to the Trianon Trauma and the American confederacy, political actors “problem make” by alleging that they are victims of the West or the Left, subject to the cruel whims of liberalism and denial of historical legitimacy. In both nations, relying on their victimhood, pundits and politicians can appeal to white supremacists and distract citizens from legitimate active conflicts, such as wars or democratic rollbacks, redirecting them to fictional, mythical attacks on Hungarian or American society and civilization. This article will examine memorials and monuments as “lieux de memoire” and identify the purposeful similarities between the discourse of public figures and politicians such as María Schmidt, János Lázár, and Viktor Orbán, with that of Donald Trump and pundits such as Tucker Carlson.

Keywords: nationalism, political memory, white supremacy, trianon

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Authors: R. M. López-Gutiérrez, L. Cardoza-Avendaño, H. Cervantes-de Ávila, J. A. Michel-Macarty, C. Cruz-Hernández, A. Arellano-Delgado, R. Carmona-Rodríguez

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In this paper, synchronization of multiple chaotic semiconductor lasers is achieved by appealing to complex system theory. In particular, we consider dynamical networks composed by semiconductor laser, as interconnected nodes, where the interaction in the networks are defined by coupling the first state of each node. An interesting case is synchronized with master-slave configuration in star topology. Nodes of these networks are modeled for the laser and simulated by Matlab. These results are applicable to private communication.

Keywords: chaotic laser, network, star topology, synchronization

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Authors: Sonia Boscenco, Zihan Wang, Euclides José de Mendoça Filho, João Paulo Hoppe, Irina Pokhvisneva, Geoffrey B.C. Hall, Michael J. Meaney, Patricia Pelufo Silveira

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Entropy can be described as a measure of the number of states of a system, and when used in the context of physiological time-based signals, it serves as a measure of complexity. In functional connectivity data, entropy can account for the moment-to-moment variability that is neglected in traditional functional magnetic resonance imaging (fMRI) analyses. While brain fMRI resting state entropy has been associated with some pathological conditions like schizophrenia, no investigations have explored the association between brain entropy measures and individual differences in child behavior in healthy children. We describe a novel exploratory approach to evaluate brain fMRI resting state data in two child cohorts, and MAVAN (N=54, 4.5 years, 48% males) and GUSTO (N = 206, 4.5 years, 48% males) and its associations to child behavior, that can be used in future research in the context of child exposures and long-term health. Following rs-fMRI data pre-processing and Shannon entropy calculation across 32 network regions of interest to acquire 496 unique functional connections, partial correlation coefficient analysis adjusted for sex was performed to identify associations between entropy data and Strengths and Difficulties questionnaire in MAVAN and Child Behavior Checklist domains in GUSTO. Significance was set at p < 0.01, and we found eight significant associations in GUSTO. Negative associations were found between two frontoparietal regions and cerebellar posterior and oppositional defiant problems, (r = -0.212, p = 0.006) and (r = -0.200, p = 0.009). Positive associations were identified between somatic complaints and four default mode connections: salience insula (r = 0.202, p < 0.01), dorsal attention intraparietal sulcus (r = 0.231, p = 0.003), language inferior frontal gyrus (r = 0.207, p = 0.008) and language posterior superior temporal gyrus (r = 0.210, p = 0.008). Positive associations were also found between insula and frontoparietal connection and attention deficit / hyperactivity problems (r = 0.200, p < 0.01), and insula – default mode connection and pervasive developmental problems (r = 0.210, p = 0.007). In MAVAN, ten significant associations were identified. Two positive associations were found = with prosocial scores: the salience prefrontal cortex and dorsal attention connection (r = 0.474, p = 0.005) and the salience supramarginal gyrus and dorsal attention intraparietal sulcus (r = 0.447, p = 0.008). The insula and prefrontal connection were negatively associated with peer problems (r = -0.437, p < 0.01). Conduct problems were negatively associated with six separate connections, the left salience insula and right salience insula (r = -0.449, p = 0.008), left salience insula and right salience supramarginal gyrus (r = -0.512, p = 0.002), the default mode and visual network (r = -0.444, p = 0.009), dorsal attention and language network (r = -0.490, p = 0.003), and default mode and posterior parietal cortex (r = -0.546, p = 0.001). Entropy measures of resting state functional connectivity can be used to identify individual differences in brain function that are correlated with variation in behavioral problems in healthy children. Further studies applying this marker into the context of environmental exposures are warranted.

Keywords: child behaviour, functional connectivity, imaging, Shannon entropy

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Authors: Marina Vicario, Amadeo Argüelles, Pilar Gómez, Carlos Hernández

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In this paper, the Computer Research Network of the National Polytechnic Institute of Mexico proposes a paradigmatic model for the inference of cognitive patterns in digital learning systems. This model leads to metadata architecture useful for analysis and prediction in online learning systems; especially on MOOc's architectures. The model is in the design phase and expects to be tested through an institutional of courses project which is going to develop for the MOOc.

Keywords: cognitive footprints, learning analytics, predictive learning, digital learning, educational computing, educational informatics

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Authors: Wen-Bin Chiou, Hsiao-Chiao Weng

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Social networking sites (SNS) such as Facebook and Twitter are low-cost tools that can promote the creation of social connections by providing a convenient platform that can be accessed at any time. In the current research, a laboratory experiment was conducted test the hypothesis that reminders of losing SNS would alter the impact of social events, especially those involving social exclusion. Specifically, this study explored whether losing SNS would intensify perceived social distress induced by exclusionary bogus feedback. Eighty-eight Facebook users (46 females, 42 males; mean age = 22.6 years, SD = 3.1 years) were recruited via campus posters and flyers at a national university in southern Taiwan. After participants provided consent, they were randomly assigned to a 2 (SNS non-use vs. neutral) between-subjects experiment. Participants completed an ostensible survey about online social networking in which we included an item about the time spent on SNS per day. The last question was used to manipulate thoughts about losing SNS access. Participants under the non-use condition were asked to record three conditions that would render them unable to use SNS (e.g., a network adaptor problem, malfunctioning cable modem, or problems with Internet service providers); participants under the neutral condition recorded three conditions that would render them unable to log onto the college website (e.g., server maintenance, local network or firewall problems). Later, this experiment employed a bogus-feedback paradigm to induce social exclusion. Participants then rated their social distress on a four-item scale, identical to that of Experiment 1 (α = .84). The results showed that thoughts of losing SNS intensified distress caused by social exclusion, suggesting that the loss of SNS has a similar effect to the loss of a primary source for social reconnections. Moreover, the priming effects of SNS on perceived distress were more prominent for heavy users. The demonstrated link between the idea of losing SNS use and increased pain of social exclusion manifests the importance of SNS as a crucial gateway for acquiring and rebuilding social connections. Use of online social networking appears to be a two-edged sword for coping with social exclusion in human lives in the e-society.

Keywords: online social networking, perceived distress, social exclusion, SNS

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Authors: Ashiq Hussain, Mahwash Hussain, Zeenat Parveen

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Now a days the demand for broadband service has increased. Due to which the researchers are trying to find a solution to provide a large amount of service. There is a shortage of bandwidth because of the use of downloading video, voice and data. One of the solutions to overcome this shortage of bandwidth is to provide the communication system with passive optical components. We have increased the data rate in this system. From experimental results we have concluded that the quality factor has increased by adding passive optical networks.

Keywords: WDM-PON, optical fiber, BER, Q-factor, eye diagram

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Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: Catia S. A. Sima, K. Bousson

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Congestion in the Terminal Maneuvering Areas (TMAs) of larger airports impacts all aspects of air traffic flow, not only at national level but may also induce arrival delays at international level. Hence, there is a need to monitor appropriately the air traffic flow in TMAs so that efficient decisions may be taken to manage their occupancy rates. It would be desirable to physically increase the existing airspace to accommodate all existing demands, but this question is entirely utopian and, given this possibility, several studies and analyses have been developed over the past decades to meet the challenges that have arisen due to the dizzying expansion of the aeronautical industry. The main objective of the present paper is to propose concepts to manage and reduce the degree of uncertainty in the air traffic operations, maximizing the interest of all involved, ensuring a balance between demand and supply, and developing and/or adapting resources that enable a rapid and effective adaptation of measures to the current context and the consequent changes perceived in the aeronautical industry. A central task is to emphasize the increase in air traffic flow management capacity to the present day, taking into account not only a wide range of methodologies but also equipment and/or tools already available in the aeronautical industry. The efficient use of these resources is crucial as the human capacity for work is limited and the actors involved in all processes related to air traffic flow management are increasingly overloaded and, as a result, operational safety could be compromised. The methodology used to answer and/or develop the issues listed above is based on the advantages promoted by the application of Markov Chain principles that enable the construction of a simplified model of a dynamic network that describes the air traffic flow behavior anticipating their changes and eventual measures that could better address the impact of increased demand. Through this model, the proposed concepts are shown to have potentials to optimize the air traffic flow management combined with the operation of the existing resources at each moment and the circumstances found in each TMA, using historical data from the air traffic operations and specificities found in the aeronautical industry, namely in the Portuguese context.

Keywords: air traffic flow, terminal maneuvering area, TMA, air traffic management, ATM, Markov chains

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Authors: M. K. Benhaoua, A. K. Singh, A. E. H. Benyamina

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In this paper, we propose heuristic for dynamic communications mapping that considers the placement of communications in order to optimize the overall performance. The mapping technique uses a newly proposed Algorithm to place communications between the tasks. The placement we propose of the communications leads to a better optimization of several performance metrics (time and energy consumption). Experimental results show that the proposed mapping approach provides significant performance improvements when compared to those using static routing.

Keywords: Multi-Processor Systems-on-Chip (MPSoCs), Network-on-Chip (NoC), heterogeneous architectures, dynamic mapping heuristics

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Authors: Vikram Kalekar

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Modern Internet Protocol (IP) networks deploy traditional and modern Quality of Service (QoS) management methods to ensure the smooth flow of network packets during regular operations. SDN (Software-defined networking) networks have also made headway into better service delivery by means of novel QoS methodologies. While many of these techniques are experimental, some of them have been tested extensively in controlled environments, and few of them have the potential to be deployed widely in the industry. With this survey, we plan to analyze the approaches to QoS and resource allocation in SDN, and we will try to comment on the possible improvements to QoS management in the context of SDN.

Keywords: QoS, policy, congestion, flow management, latency, delay index terms-SDN, delay

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Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

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Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

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In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

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Authors: Tsegay Giday Woldu, Haibin Zhang, Xin Zhang, Yemane Hailu Fissuh

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It is well known that nonlinear conjugate gradient method is one of the widely used first order methods to solve large scale unconstrained smooth optimization problems. Because of the low memory requirement, attractive theoretical features, practical computational efficiency and nice convergence properties, nonlinear conjugate gradient methods have a special role for solving large scale unconstrained optimization problems. Large scale optimization problems are with important applications in practical and scientific world. However, nonlinear conjugate gradient methods have restricted information about the curvature of the objective function and they are likely less efficient and robust compared to some second order algorithms. To overcome these drawbacks, the new modified nonlinear conjugate gradient method is presented. The noticeable features of our work are that the new search direction possesses the sufficient descent property independent of any line search and it belongs to a trust region. Under mild assumptions and standard Wolfe line search technique, the global convergence property of the proposed algorithm is established. Furthermore, to test the practical computational performance of our new algorithm, numerical experiments are provided and implemented on the set of some large dimensional unconstrained problems. The numerical results show that the proposed algorithm is an efficient and robust compared with other similar algorithms.

Keywords: conjugate gradient method, global convergence, large scale optimization, sufficient descent property

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Authors: Azfar Adib

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Like many other countries of the world, mobile internet has been playing a key role in the growth of internet subscriber base in Bangladesh. This study has attempted to identify particular behavioral or usage patterns of 2G mobile internet subscribers who were using the service of the topmost internet service provider (as well as the top mobile operator) of Bangladesh prior to the launching of 3G services (when 2G was fully dominant). It contains some comprehensive analysis carried on different info regarding 2G mobile internet subscribers, obtained from the operator’s own network insights.This is accompanied by the results of a survey conducted among 40 high-frequency users of this service.

Keywords: mobile internet, Symbian, Android, iPhone

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Authors: Souâad Boudebza, Omar Nouali, Faiçal Azouaou

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Social networks have recently gained a growing interest on the web. Traditional formalisms for representing social networks are static and suffer from the lack of semantics. In this paper, we will show how semantic web technologies can be used to model social data. The SemTemp ontology aligns and extends existing ontologies such as FOAF, SIOC, SKOS and OWL-Time to provide a temporal and semantically rich description of social data. We also present a modeling scenario to illustrate how our ontology can be used to model social networks.

Keywords: ontology, semantic web, social network, temporal modeling

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Authors: Eric A. Morris, Xia Liu, Yee Ka Wong, Greg J. Evans, Jeff R. Brook

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Air quality monitoring stations tend to be widely distributed and are often located far from major roadways, thus, determining where, when, and which traffic-related air pollutants (TRAPs) have the greatest impact on public health becomes a matter of extrapolation. Compact, multipollutant sensor systems are an effective solution as they enable several TRAPs to be monitored in a geospatially dense network, thus filling in the gaps between conventional monitoring stations. This work describes two applications of one such system named AirSENCE for gathering actionable air quality data relevant to smart city infrastructures. In the first application, four AirSENCE devices were co-located with traffic monitors around the perimeter of a city block in Oshawa, Ontario. This study, which coincided with the COVID-19 outbreak of 2020 and subsequent lockdown measures, demonstrated a direct relationship between decreased traffic volumes and TRAP concentrations. Conversely, road construction was observed to cause elevated TRAP levels while reducing traffic volumes, illustrating that conventional smart city sensors such as traffic counters provide inadequate data for inferring air quality conditions. The second application used two AirSENCE sensors on opposite sides of a major 2-way commuter road in Toronto. Clear correlations of TRAP concentrations with wind direction were observed, which shows that impacted areas are not necessarily static and may exhibit high day-to-day variability in air quality conditions despite consistent traffic volumes. Both of these applications provide compelling evidence favouring the inclusion of air quality sensors in current and future smart city infrastructure planning. Such sensors provide direct measurements that are useful for public health alerting as well as decision-making for projects involving traffic mitigation, heavy construction, and urban renewal efforts.

Keywords: distributed sensor network, continuous ambient air quality monitoring, Smart city sensors, Internet of Things, traffic-related air pollutants

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Authors: Samira Kalantary, Zohre Saatzade

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Wireless Mesh Networks (WMNs) are low-cost access networks built on cooperative routing over a backbone composed of stationary wireless routers. WMNs must deal with the highly unstable wireless medium. Thus, routing metrics and protocols are evolving by designing algorithms that consider link quality to choose the best routes. In this work, we analyse the state of the art in WMN metrics and propose taxonomy for WMN routing protocols. Performance measurements of a wireless mesh network deployed using various routing metrics are presented and corroborate our analysis.

Keywords: wireless mesh networks, routing protocols, routing metrics, bioinformatics

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Authors: Tami Peterson

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Hyperbaric oxygen therapy (HBOT) has been hypothesized as an effective treatment for increasing verbal language skills in individuals on the autism spectrum. A child’s ability to effectively communicate with peers, parents, and caregivers impacts their level of independence and quality of personal relationships. This retrospective study will compare the speech development of participants aged 2-17 years that received 40 sessions of HBOT at 2.0 ATA to those who had not. Both groups will have a verbal assessment every six months. There were 31 subjects in the HBO group and 32 subjects in the non-HBO group. The statistical analysis will focus on whether hyperbaric oxygen therapy made a significant difference in Verbal Behavior Milestones Assessment and Placement Program (VB-MAPP) or Assessment of Basic Language and Learning Skills (ABLLS) results. The evidence demonstrates a strong correlation between HBOT and an increased change from baseline verbal scores compared to the control group, even in difficult to grasp areas such as spontaneous vocalization. We suggest this is due to the anti-inflammatory effects of hyperbaric oxygen therapy. Neuroinflammation causes hypoperfusion of critical central nervous system areas responsible for the symptoms described within the autism spectrum, such as problems with thought processing, memory, and speech. Decreasing the inflammation allows the brain to function properly, which results in improved verbal scores for the participants that underwent HBOT.

Keywords: assessment of basic language and learning skills, autism spectrum disorder, hyperbaric oxygen therapy, verbal behavior milestones assessment and placement program

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Authors: Mohamed H. Khalil

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Water is one of the most crucial elements which influence human lives and development. Noteworthy, over the last few years, GIS plays a significant role in optimizing water management systems, especially after exponential developing in this sector. In this context, the Egyptian government initiated an advanced ‘GIS-Web Based System’. This system is efficiently designed to tangibly assist and optimize the complement and integration of data between departments of Call Center, Operation and Maintenance, and laboratory. The core of this system is a unified ‘Data Model’ for all the spatial and tabular data of the corresponding departments. The system is professionally built to provide advanced functionalities such as interactive data collection, dynamic monitoring, multi-user editing capabilities, enhancing data retrieval, integrated work-flow, different access levels, and correlative information record/track. Noteworthy, this cost-effective system contributes significantly not only in the completeness of the base-map (93%), the water network (87%) in high level of details GIS format, enhancement of the performance of the customer service, but also in reducing the operating costs/day-to-day operations (~ 5-10 %). In addition, the proposed system facilitates data exchange between different departments (Call Center, Operation and Maintenance, and laboratory), which allowed a better understanding/analyzing of complex situations. Furthermore, this system reflected tangibly on: (i) dynamic environmental monitor/water quality indicators (ammonia, turbidity, TDS, sulfate, iron, pH, etc.), (ii) improved effectiveness of the different water departments, (iii) efficient deep advanced analysis, (iv) advanced web-reporting tools (daily, weekly, monthly, quarterly, and annually), (v) tangible planning synthesizing spatial and tabular data; and finally, (vi) scalable decision support system. It is worth to highlight that the proposed future plan (second phase) of this system encompasses scalability will extend to include integration with departments of Billing and SCADA. This scalability will comprise advanced functionalities in association with the existing one to allow further sustainable contributions.

Keywords: GIS Web-Based, base-map, water network, decision support system

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Authors: Sun-Hee Lee, Amanda Kraley

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The “MeToo” movement is a social movement against sexual abuse and harassment. Though the hashtag went viral in 2017 following different cultural flashpoints in different countries, the initial response was quiet in South Korea. This radically changed in January 2018, when a high-ranking senior prosecutor, Seo Ji-hyun, gave a televised interview discussing being sexually assaulted by a colleague. Acknowledging public anger, particularly among women, on the long-existing problems of sexual harassment and abuse, the South Korean media have focused on several high-profile cases. Analyzing the media representation of these cases is a window into the evolving South Korean discourse around “MeToo.” This study presents a linguistic analysis of “MeToo” discourse in South Korea by utilizing a corpus-based approach. The term corpus (pl. corpora) is used to refer to electronic language data, that is, any collection of recorded instances of spoken or written language. A “MeToo” corpus has been collected by extracting newspaper articles containing the keyword “MeToo” from BIGKinds, big data analysis, and service and Nexis Uni, an online academic database search engine, to conduct this language analysis. The corpus analysis explores how Korean media represent accusers and the accused, victims and perpetrators. The extracted data includes 5,885 articles from four broadsheet newspapers (Chosun, JoongAng, Hangyore, and Kyunghyang) and 88 articles from two Korea-based English newspapers (Korea Times and Korea Herald) between January 2017 and November 2020. The information includes basic data analysis with respect to keyword frequency and network analysis and adds refined examinations of select corpus samples through naming strategies, semantic relations, and pragmatic properties. Along with the exponential increase of the number of articles containing the keyword “MeToo” from 104 articles in 2017 to 3,546 articles in 2018, the network and keyword analysis highlights ‘US,’ ‘Harvey Weinstein’, and ‘Hollywood,’ as keywords for 2017, with articles in 2018 highlighting ‘Seo Ji-Hyun, ‘politics,’ ‘President Moon,’ ‘An Ui-Jeong, ‘Lee Yoon-taek’ (the names of perpetrators), and ‘(Korean) society.’ This outcome demonstrates the shift of media focus from international affairs to domestic cases. Another crucial finding is that word ‘defamation’ is widely distributed in the “MeToo” corpus. This relates to the South Korean legal system, in which a person who defames another by publicly alleging information detrimental to their reputation—factual or fabricated—is punishable by law (Article 307 of the Criminal Act of Korea). If the defamation occurs on the internet, it is subject to aggravated punishment under the Act on Promotion of Information and Communications Network Utilization and Information Protection. These laws, in particular, have been used against accusers who have publicly come forward in the wake of “MeToo” in South Korea, adding an extra dimension of risk. This corpus analysis of “MeToo” newspaper articles contributes to the analysis of the media representation of the “MeToo” movement and sheds light on the shifting landscape of gender relations in the public sphere in South Korea.

Keywords: corpus linguistics, MeToo, newspapers, South Korea

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Authors: Zi-Yan Liao, Shan-Yu Zhang, Ya-Xian Lin, Ya-Lun Lee, Shih-Chuan Huang, Hong-Ru Lin

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Traditional wound dressings, such as gauze, bandages, etc., are easy to adhere to the tissue fluid exuded from the wound, causing secondary damage to the wound during removal. This study takes this as the idea to develop a hydrogel dressing, to explore that the dressing will not cause secondary damage to the wound when it is torn off, and at the same time, create an environment conducive to wound healing. First, the temperature-sensitive material N-isopropylacrylamide (NIPAAm) was used as the substrate. Due to its low mechanical properties, the hydrogel would break due to pulling during human activities. Polyvinyl alcohol (PVA) interpenetrates into it to enhance the mechanical properties, and a semi-interpenetration (semi-IPN) composed of poly(N-isopropylacrylamide) (PNIPAAm) and polyvinyl alcohol (PVA) was prepared by free radical polymerization. PNIPAAm was cross-linked with N,N'-methylenebisacrylamide (NMBA) in an ice bath in the presence of linear PVA, and tetramethylhexamethylenediamine (TEMED) was added as a promoter to speed up the gel formation. The polymerization stage was carried out at 16°C for 17 hours and washed with distilled water for three days after gel formation, and the water was changed several times in the middle to complete the preparation of semi-IPN hydrogel. Finally, various tests were used to analyze the effects of different ratios of PNIPAAm and PVA on semi-IPN hydrogels. In the swelling test, it was found that the maximum swelling ratio can reach about 50% under the environment of 21°C, and the higher the ratio of PVA, the more water can be absorbed. The saturated moisture content test results show that when more PVA is added, the higher saturated water content. The water vapor transmission rate test results show that the value of the semi-IPN hydrogel is about 57 g/m²/24hr, which is not much related to the proportion of PVA. It is found in the LCST test compared with the PNIPAAm hydrogel; the semi-IPN hydrogel possesses the same critical solution temperature (30-35°C). The semi-IPN hydrogel prepared in this study has a good effect on temperature response and has the characteristics of thermal sensitivity. It is expected that after improvement, it can be used in the treatment of surface wounds, replacing the traditional dressing shortcoming.

Keywords: hydrogel, N-isopropylacrylamide, polyvinyl alcohol, hydrogel wound dressing, semi-interpenetrating polymer network

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Authors: Hannah Rosenqvist, Fanny Guay

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Critical infrastructure protection has been an important topic for several years. Programmes such as the European Programme for Critical Infrastructure Protection (EPCIP), Critical Infrastructure Warning Information Network (CIWIN) and the European Reference Network for Critical Infrastructure Protection (ENR-CIP) have been the pillars to the work done since 2006. However, measuring critical infrastructure resilience has not been an easy task. This has to do with the fact that the concept of resilience has several definitions and is applied in different domains such as engineering and social sciences. Since June 2015, the EU project IMPROVER has been focusing on developing a methodology for implementing a combination of societal, organizational and technological resilience concepts, in the hope to increase critical infrastructure resilience. For this paper, we performed research on how to include societal resilience as a form of measurement of the context of critical infrastructure resilience. Because one of the main purposes of critical infrastructure (CI) is to deliver services to the society, we believe that societal resilience is an important factor that should be considered when assessing the overall CI resilience. We found that existing methods for CI resilience assessment focus mainly on technical aspects and therefore that is was necessary to develop a resilience model that take social factors into account. The model developed within the project IMPROVER aims to include the community’s expectations of infrastructure operators as well as information sharing with the public and planning processes. By considering such aspects, the IMPROVER framework not only helps operators to increase the resilience of their infrastructures on the technical or organizational side, but aims to strengthen community resilience as a whole. This will further be achieved by taking interdependencies between critical infrastructures into consideration. The knowledge gained during this project will enrich current European policies and practices for improved disaster risk management. The framework for societal resilience analysis is based on three dimensions for societal resilience; coping capacity, adaptive capacity and transformative capacity which are capacities that have been recognized throughout a widespread literature review in the field. A set of indicators have been defined that describe a community’s maturity within these resilience dimensions. Further, the indicators are categorized into six community assets that need to be accessible and utilized in such a way that they allow responding to changes and unforeseen circumstances. We conclude that the societal resilience model developed within the project IMPROVER can give a good indication of the level of societal resilience to critical infrastructure operators.

Keywords: community resilience, critical infrastructure protection, critical infrastructure resilience, societal resilience

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Authors: Dhruv J. Limaye, Hanga Galfalvy, Cheick A. Sissoko, Yung-yu Huang, Chunanning Tang, Ying Liu, Shu-Chi Hsiung, Andrew J. Dwork, Gorazd B. Rosoklija, Victoria Arango, Lewis Brown, J. John Mann, Maura Boldrini

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Memory and emotion require hippocampal cell viability and connectivity and are disrupted in major depressive disorder (MDD). Applying shotgun proteomics and stereological quantification of neural progenitor cells (NPCs), intermediate neural progenitors (INPs), and mature granule neurons (GNs), to postmortem human hippocampus, identified differentially expressed proteins (DEPs), and fewer NPCs, INPs and GNs, in untreated MDD (uMDD) compared with non-psychiatric controls (CTRL) and antidepressant-treated MDD (MDDT). DEPs lower in uMDD vs. CTRL promote mitosis, differentiation, and prevent apoptosis. DEPs higher in uMDD vs. CTRL inhibit the cell cycle, and regulate cell adhesion, neurite outgrowth, and DNA repair. DEPs lower in MDDT vs. uMDD block cell proliferation. We observe group-specific correlations between numbers of NPCs, INPs, and GNs and an abundance of proteins regulating mitosis, differentiation, and apoptosis. Altered protein expression underlies hippocampus cellular and volume loss in uMDD, supports a trophic effect of antidepressants, and offers new treatment targets.

Keywords: proteomics, hippocampus, depression, mitosis, migration, differentiation, mitochondria, apoptosis, antidepressants, human brain

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Authors: Dale Dzemydiene, Aurelija Burinskiene, Arunas Miliauskas, Kristina Ciziuniene

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Data flow and the purpose of reporting the data are different and dependent on business needs. Different parameters are reported and transferred regularly during freight delivery. This business practices form the dataset constructed for each time point and contain all required information for freight moving decisions. As a significant amount of these data is used for various purposes, an integrating methodological approach must be developed to respond to the indicated problem. The proposed methodology contains several steps: (1) collecting context data sets and data validation; (2) multi-objective analysis for optimizing freight transfer services. For data validation, the study involves Grubbs outliers analysis, particularly for data cleaning and the identification of statistical significance of data reporting event cases. The Grubbs test is often used as it measures one external value at a time exceeding the boundaries of standard normal distribution. In the study area, the test was not widely applied by authors, except when the Grubbs test for outlier detection was used to identify outsiders in fuel consumption data. In the study, the authors applied the method with a confidence level of 99%. For the multi-objective analysis, the authors would like to select the forms of construction of the genetic algorithms, which have more possibilities to extract the best solution. For freight delivery management, the schemas of genetic algorithms' structure are used as a more effective technique. Due to that, the adaptable genetic algorithm is applied for the description of choosing process of the effective transportation corridor. In this study, the multi-objective genetic algorithm methods are used to optimize the data evaluation and select the appropriate transport corridor. The authors suggest a methodology for the multi-objective analysis, which evaluates collected context data sets and uses this evaluation to determine a delivery corridor for freight transfer service in the multi-modal transportation network. In the multi-objective analysis, authors include safety components, the number of accidents a year, and freight delivery time in the multi-modal transportation network. The proposed methodology has practical value in the management of multi-modal transportation processes.

Keywords: multi-objective, analysis, data flow, freight delivery, methodology

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan, Adrian Brezulianu

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This paper presents the contributions in designing a mobile system named Tele-ECG implemented for remote monitoring of cardiac patients. For a better flexibility of this application, the authors chose to implement a local memory and multiple communication interfaces. The project described in this presentation is based on the ARM Cortex M0+ microcontroller and the ADAS1000 dedicated chip necessary for the collection and transmission of Electrocardiogram signals (ECG) from the patient to the microcontroller, without altering the performances and the stability of the system. The novelty brought by this paper is the implementation of a remote monitoring system for cardiac patients, having a real-time behavior and multiple interfaces. The microcontroller is responsible for processing digital signals corresponding to ECG and also for the implementation of communication interface with the main server, using GSM/Bluetooth SIMCOM SIM800C module. This paper translates all the characteristics of the Tele-ECG project representing a feasible implementation in the biomedical field. Acknowledgment: This paper was supported by the project 'Development and integration of a mobile tele-electrocardiograph in the GreenCARDIO© system for patients monitoring and diagnosis - m-GreenCARDIO', Contract no. BG58/30.09.2016, PNCDI III, Bridge Grant 2016, using the infrastructure from the project 'Integrated Center for research, development and innovation in Advanced Materials, Nanotechnologies, and Distributed Systems for fabrication and control', Contract No. 671/09.04.2015, Sectoral Operational Program for Increase of the Economic Competitiveness co-funded from the European Regional Development Fund.

Keywords: Tele-ECG, real-time cardiac monitoring, electrocardiogram, microcontroller

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