Search results for: temporal graph network

Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.

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In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means

Procedia PDF Downloads 542

Authors: Georgios Boustras, Cleo Varianou Mikellidou, Christos Argyropoulos

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Summer 2021 was marked by a number of prolific fires in the EU (Greece, Cyprus, France) as well as outside the EU (USA, Turkey, Israel). This series of dramatic events have stretched national civil protection systems and first responders in particular. Despite the introduction of National, Regional and International frameworks (e.g. rescEU), a number of challenges have arisen, not only related to climate change. RESPOND-A (funded by the European Commission by Horizon 2020, Contract Number 883371) introduces a unique five-tier project architectural structure for best associating modern telecommunications technology with novel practices for First Responders of saving lives, while safeguarding themselves, more effectively and efficiently. The introduced architecture includes Perception, Network, Processing, Comprehension, and User Interface layers, which can be flexibly elaborated to support multiple levels and types of customization, so, the intended technologies and practices can adapt to any European Environment Agency (EEA)-type disaster scenario. During the preparation of the RESPOND-A proposal, some of our First Responder Partners expressed the need for an information management system that could boost existing emergency response tools, while some others envisioned a complete end-to-end network management system that would offer high Situational Awareness, Early Warning and Risk Mitigation capabilities. The intuition behind these needs and visions sits on the long-term experience of these Responders, as well, their smoldering worry that the evolving threat of climate change and the consequences of industrial accidents will become more frequent and severe. Three large-scale pilot studies are planned in order to illustrate the capabilities of the RESPOND-A system. The first pilot study will focus on the deployment and operation of all available technologies for continuous communications, enhanced Situational Awareness and improved health and safety conditions for First Responders, according to a big fire scenario in a Wildland Urban Interface zone (WUI). An important issue will be examined during the second pilot study. Unobstructed communication in the form of the flow of information is severely affected during a crisis; the flow of information between the wider public, from the first responders to the public and vice versa. Call centers are flooded with requests and communication is compromised or it breaks down on many occasions, which affects in turn – the effort to build a common operations picture for all firstr esponders. At the same time the information that reaches from the public to the operational centers is scarce, especially in the aftermath of an incident. Understandably traffic if disrupted leaves no other way to observe but only via aerial means, in order to perform rapid area surveys. Results and work in progress will be presented in detail and challenges in relation to civil protection will be discussed.

Keywords: first responders, safety, civil protection, new technologies

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Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

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Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

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Authors: Laura M. F. Bertens

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There is a long tradition of visually representing the art historical canon, in schematic overviews and diagrams. This is indicative of the desire for scientific, ‘objective’ knowledge of the kind (seemingly) produced in the natural sciences. These diagrams will, however, always retain an element of subjectivity and the modelling methods colour our perception of the represented information. In recent decades visualisations of art historical data, such as hand-drawn diagrams in textbooks, have been extended to include digital, computational tools. These tools significantly increase modelling strength and functionality. As such, they might be used to deconstruct and amend the very problem caused by traditional visualisations of the canon. In this paper, the use of digital tools for modelling the art historical canon is studied, in order to draw attention to the artificial nature of the static models that art historians are presented with in textbooks and lectures, as well as to explore the potential of digital, dynamic tools in creating new models. To study the way diagrams of the canon mediate the represented information, two modelling methods have been used on two case studies of existing diagrams. The tree diagram Stammbaum der neudeutschen Kunst (1823) by Ferdinand Olivier has been translated to a social network using the program Visone, and the famous flow chart Cubism and Abstract Art (1936) by Alfred Barr has been translated to an ontological model using Protégé Ontology Editor. The implications of the modelling decisions have been analysed in an art historical context. The aim of this project has been twofold. On the one hand the translation process makes explicit the design choices in the original diagrams, which reflect hidden assumptions about the Western canon. Ways of organizing data (for instance ordering art according to artist) have come to feel natural and neutral and implicit biases and the historically uneven distribution of power have resulted in underrepresentation of groups of artists. Over the last decades, scholars from fields such as Feminist Studies, Postcolonial Studies and Gender Studies have considered this problem and tried to remedy it. The translation presented here adds to this deconstruction by defamiliarizing the traditional models and analysing the process of reconstructing new models, step by step, taking into account theoretical critiques of the canon, such as the feminist perspective discussed by Griselda Pollock, amongst others. On the other hand, the project has served as a pilot study for the use of digital modelling tools in creating dynamic visualisations of the canon for education and museum purposes. Dynamic computer models introduce functionalities that allow new ways of ordering and visualising the artworks in the canon. As such, they could form a powerful tool in the training of new art historians, introducing a broader and more diverse view on the traditional canon. Although modelling will always imply a simplification and therefore a distortion of reality, new modelling techniques can help us get a better sense of the limitations of earlier models and can provide new perspectives on already established knowledge.

Keywords: canon, ontological modelling, Protege Ontology Editor, social network modelling, Visone

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Authors: E. O. Clarke, O. J. Aderinola, O. A. Adeboyejo, M. A. Anetekhai

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Aims: The study is aimed at establishing the influence of some physical and chemical parameters on the abundance, distribution pattern and seasonal variations of the planktonic crustacean populations. Place and Duration of Study: A premier investigation into the dynamics of planktonic crustacean populations in Ologe lagoon was carried out from January 2011 to December 2012. Study Design: The study covered identification, temporal abundance, spatial distribution and diversity of the planktonic crustacea. Methodology: Standard techniques were used to collect samples from eleven stations covering five proximal satellite towns (Idoluwo, Oto, Ibiye, Obele, and Gbanko) bordering the lagoon. Data obtained were statistically analyzed using linear regression and hierarchical clustering. Results:Thirteen (13) planktonic crustacean populations were identified. Total percentage abundance was highest for Bosmina species (20%) and lowest for Polyphemus species (0.8%). The Pearson’s correlation coefficient (“r” values) between total planktonic crustacean population and some physical and chemical parameters showed that positive correlations having low level of significance occurred with salinity (r = 0.042) (sig = 0.184) and with surface water dissolved oxygen (r = 0.299) (sig = 0.155). Linear regression plots indicated that, the total population of planktonic crustacea were mainly influenced and only increased with an increase in value of surface water temperature (Rsq = 0.791) and conductivity (Rsq = 0.589). The total population of planktonic crustacea had a near neutral (zero correlation) with the surface water dissolved oxygen and thus, does not significantly change with the level of the surface water dissolved oxygen. The correlations were positive with NO3-N (midstream) at Ibiye (Rsq =0.022) and (downstream) Gbanko (Rsq =0.013), PO4-P at Ibiye (Rsq =0.258), K at Idoluwo (Rsq =0.295) and SO4-S at Oto (Rsq = 0.094) and Gbanko (Rsq = 0.457). The Berger-Parker Dominance Index (BPDI) showed that the most dominant species was Bosmina species (BPDI = 1.000), followed by Calanus species (BPDI = 1.254). Clusters by squared Euclidan distances using average linkage between groups showed proximities, transcending the borders of genera. Conclusion: The results revealed that planktonic crustacean population in Ologe lagoon undergo seasonal perturbations, were highly influenced by nutrient, metal and organic matter inputs from river Owoh, Agbara industrial estate and surrounding farmlands and were patchy in spatial distribution.

Keywords: diversity, dominance, perturbations, richness, crustacea, lagoon

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Authors: M. S. Gaafar, S. Y. Marzouk, I. S. Mahmoud, S. Al-Zobaidi

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Makishima and Mackenzie model was used to simulation of acoustic properties (longitudinal and shear ultrasonic wave velocities, elastic moduli theoretically for many tellurite and borate glasses. The model was proposed mainly depending on the values of the experimentally measured density, which are obtained before. In this search work, we are trying to obtain the values of densities of amorphous glasses (as the density depends on the geometry of the network structure of these glasses). In addition, the problem of simulating the slope of linear regression between the experimentally determined bulk modulus and the product of packing density and experimental Young's modulus, were solved in this search work. The results showed good agreement between the experimentally measured values of densities and both ultrasonic wave velocities, and those theoretically determined.

Keywords: glasses, ultrasonic wave velocities, elastic modulus, Makishima & Mackenzie Model

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Authors: Ferinar Moaidi, Mahdi Moaidi

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Environmental issues and the ever-increasing in demand of electrical energy make it necessary to have distributed generation (DG) resources in the power system. In this research, in order to realize the goals of reducing losses and improving the voltage profile in a microgrid, the allocation and sizing of DGs have been used. The proposed Genetic Algorithm (GA) is described from the array of artificial intelligence methods for solving the problem. The algorithm is implemented on the IEEE 33 buses network. This study is presented in two scenarios, primarily to illustrate the effect of location and determination of DGs has been done to reduce losses and improve the voltage profile. On the other hand, decisions made with the one-level assumptions of load are not universally accepted for all levels of load. Therefore, in this study, load modelling is performed and the results are presented for multi-levels load state.

Keywords: distributed generation, genetic algorithm, microgrid, load modelling, loss reduction, voltage improvement

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Authors: Osk Dagsdottir

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Background—Gait classifying allows clinicians to differentiate gait patterns into clinically important categories that help in clinical decision making. Reliable comparison of gait data between normal and patients requires knowledge of the gait parameters of normal children's specific age group. However, there is still a lack of the gait database for normal children of different ages. Objectives—This study aims to investigate the kinematics of the lower limb joints during gait for normal children in different age groups. Methods—Fifty-three normal children (34 boys, 19 girls) were recruited in this study. All the children were aged between 5 to 16 years old. Age groups were defined as three types: young child aged (5-7), child (8-11), and adolescent (12-16). When a participant agreed to take part in the project, their parents signed a consent form. Vicon® motion capture system was used to collect gait data. Participants were asked to walk at their comfortable speed along a 10-meter walkway. Each participant walked up to 20 trials. Three good trials were analyzed using the Vicon Plug-in-Gait model to obtain parameters of the gait, e.g., walking speed, cadence, stride length, and joint parameters, e.g., joint angle, force, moments, etc. Moreover, each gait cycle was divided into 8 phases. The range of motion (ROM) angle of pelvis, hip, knee, and ankle joints in three planes of both limbs were calculated using an in-house program. Results—The temporal-spatial variables of three age groups of normal children were compared between each other; it was found that there was a significant difference (p < 0.05) between the groups. The step length and walking speed were gradually increasing from young child to adolescent, while cadence was gradually decreasing from young child to adolescent group. The mean and standard deviation (SD) of the step length of young child, child and adolescent groups were 0.502 ± 0.067 m, 0.566 ± 0.061 m and 0.672 ± 0.053 m, respectively. The mean and SD of the cadence of the young child, child and adolescent groups were 140.11±15.79 step/min, 129±11.84 step/min, and a 115.96±6.47 step/min, respectively. Moreover, it was observed that there were significant differences in kinematic parameters, either whole gait cycle or each phase. For example, RoM of knee angle in the sagittal plane in the whole cycle of young child group is (65.03±0.52 deg) larger than child group (63.47±0.47 deg). Conclusion—Our result showed that there are significant differences between each age group in the gait phases and thus children walking performance changes with ages. Therefore, it is important for the clinician to consider the age group when analyzing the patients with lower limb disorders before any clinical treatment.

Keywords: action research, creative learning, mathematics education, professional development

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Authors: Rajaian Hoonejani Mohammad, Eshraghi Pegah, Zomorodian Zahra Sadat, Tahsildoost Mohammad

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Over the past decade, energy consumption in educational buildings has steadily increased. The purpose of this research is to provide a method to quickly predict the energy consumption of buildings using separate evaluation of zones and decomposing the building to eliminate the complexity of geometry at the early design stage. To produce this framework, machine learning algorithms such as Support vector regression (SVR) and Artificial neural network (ANN) are used to predict energy consumption and thermal comfort metrics in a school as a case. The database consists of more than 55000 samples in three climates of Iran. Cross-validation evaluation and unseen data have been used for validation. In a specific label, cooling energy, it can be said the accuracy of prediction is at least 84% and 89% in SVR and ANN, respectively. The results show that the SVR performed much better than the ANN.

Keywords: early stage of design, energy, thermal comfort, validation, machine learning

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Authors: Ramon Hernán, Maria Teresa Corzo

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This study examines the impact and contribution of the main journals in the discipline of behavioral finance to determine the state of the art of the discipline and the growth lines and concepts studied to date. This is a unique and novel study given that a review of the discipline has not been carried out through the keywords of the articles that allows visualizing through this component of the research, which are the main topics of discussion and the relationships that arise between the concepts discussed. To carry out this study, 3,876 articles have been taken as a reference, which includes 15,859 keywords from the main journals responsible for the growth of the discipline.; Journal of Behavioral Finance, Review of Behavioral Finance, Journal of Behavioral and Experimental Economics, Journal of Behavioral and Experimental Economics and Review of Behavioral Finance. The results indicate which are the topics most covered in the discipline throughout the period from 2000 to 2020, how these concepts have been dealt with on a recurring basis along with others throughout the aforementioned period and how the different concepts have been grouped based on the keywords established by the authors for the classification of their articles with a network diagram to complete the analysis.

Keywords: behavioral finance, keywords, co-words, top journals, data visualization

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Authors: Amal M. Alrayes, Hayat M. Ali

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Since the beginning of distance education with the rapid evolution of technology, the social network plays a vital role in the educational process to enforce the interaction been the learners and teachers. There are many Web 2.0 technologies, services and tools designed for educational purposes. This research aims to investigate instructors’ acceptance towards web-based learning systems in higher educational institutes in Kingdom of Bahrain. Questionnaire is used to investigate the instructors’ usage of Web 2.0 and the factors affecting their acceptance. The results confirm that instructors had high accessibility to such technologies. However, patterns of use were complex. Whilst most expressed interest in using online technologies to support learning activities, learners seemed cautious about other values associated with web-based system, such as the shared construction of knowledge in a public format. The research concludes that there are main factors that affect instructors’ adoption which are security, performance expectation, perceived benefits, subjective norm, and perceived usefulness.

Keywords: Web 2.0, higher education, acceptance, students' perception

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Authors: M. Soubadra Devy, Savitha Swamy, Chethana V. Casiker

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Sustainable smart cities are emerging as an important concept in response to the exponential rise in the world’s urbanizing population. While earlier, only technical, economic and governance based solutions were considered, more and more layers are being added in recent times. With the prefix of 'sustainability', solutions which help in judicious use of resources without negatively impacting the environment have become critical. We present a case study of Bangalore city which has transformed from being a garden city and pensioners' paradise to being an IT city with a huge, young population from different regions and diverse cultural backgrounds. This has had a big impact on the green spaces in the city and the biodiversity that they support, as well as on farming/gardening practices. Edible landscapes comprising farms lands, home gardens and neighbourhood parks (NPs henceforth) were examined. The land prices of areas having NPs were higher than those that did not indicate an appreciation of their aesthetic value. NPs were part of old and new residential areas largely managed by the municipality. They comprised manicured gardens which were similar in vegetation structure and composition. Results showed that NPs that occurred in higher density supported reasonable levels of biodiversity. In situations where NPs occurred in lower density, the presence of a larger green space such as a heritage park or botanical garden enhanced the biodiversity of these parks. In contrast, farm lands and home gardens which were common within the city are being lost at an unprecedented scale to developmental projects. However, there is also the emergence of a 'neo-culture' of home-gardening that promotes 'locovory' or consumption of locally grown food as a means to a sustainable living and reduced carbon footprint. This movement overcomes the space constraint by using vertical and terrace gardening techniques. Food that is grown within cities comprises of vegetables and fruits which are largely pollinator dependent. This goes hand in hand with our landscape-level study that has shown that cities support pollinator diversity. Maintaining and improving these man-made ecosystems requires analysing the functioning and characteristics of the existing structures of governance. Social network analysis tool was applied to NPs to examine relationships, between actors and ties. The management structures around NPs, gaps, and means to strengthen the networks from the current state to a near-ideal state were identified for enhanced services. Learnings from NPs were used to build a hypothetical governance structure and functioning of integrated governance of NPs and edible landscapes to enhance ecosystem services such as biodiversity support, food production, and aesthetic value. They also contribute to the sustainability axis of smart cities.

Keywords: biodiversity support, ecosystem services, edible green spaces, neighbourhood parks, sustainable smart city

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Authors: Samira Khalil, Adib Saad, Malek Ali

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The aim of this research is to determine fish species belonging to the order Pleuronectiforme fish found in Syrian marine water confirm or deny the continuity of the previously registered species, and record the unregistered species that appeared during this research for the first time. The research was carried out in the Laboratory of Marine Sciences, Faculty of Agriculture (Tishreen University); fish samples were collected periodically (bi-monthly) from fishermen in landing areas along the Syrian coast caught from depths (3m to 700m), using various mediums. An appropriate hand is available to fishermen on the Syrian coast (cliff bottom, fixed nets, enclosure nets, shelf nest, and manual disposal network; 451 individuals were captured and studied during the research period. During this study, it was found that the Syrian water includes 15 species, including one species recorded for the first time. On the eastern coast of the Mediterranean, it is Pegusa impar.

Keywords: pleuronectiformes, Syrian coast, flatfish, mediterranean

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Authors: Adriano Araujo Carvalho, Arturo Alatrista Corrales

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This paper intends to show how electrical energy consumption and production data analysis were used to find opportunities to save energy at Taboada wastewater treatment plant in Callao, Peru. In order to access the data, it was used independent data networks for both electrical and process instruments, which were taken to analyze under an ISO 50001 energy audit, which considered, thus, Energy Performance Indexes for each process and a step-by-step guide presented in this text. Due to the use of aforementioned methodology and data mining techniques applied on information gathered through electronic multimeters (conveniently placed on substation switchboards connected to a cloud network), it was possible to identify thoroughly the performance of each process and thus, evidence saving opportunities which were previously hidden before. The data analysis brought both costs and energy reduction, allowing the plant to save significant resources and to be certified under ISO 50001.

Keywords: energy and production data analysis, energy management, ISO 50001, wastewater treatment plant energy analysis

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Authors: Debora P. Arce, Flavia J. Krsticevic, Marco R. Bertolaccini, Joaquín Ezpeleta, Estela M. Valle, Sergio D. Ponce, Elizabeth Tapia

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Small Heat Shock Proteins (sHSPs) are low molecular weight chaperones that play an important role during stress response and development in all living organisms. Fruit maturation and oxidative stress can induce sHSP synthesis both in Arabidopsis and tomato plants. RNA-Seq technology is becoming widely used in various transcriptomics studies; however, analyzing and interpreting the RNA-Seq data face serious challenges. In the present work, we de novo assembled the Solanum lycopersicum transcriptome for three different maturation stages (mature green, breaker and red ripe). Differential gene expression analysis was carried out during tomato fruit development. We identified 12 sHSPs differentially expressed that might be involved in breaker and red ripe fruit maturation. Interestingly, these sHSPs have different subcellular localization and suggest a complex regulation of the fruit maturation network process.

Keywords: sHSPs, maturation, tomato, RNA-Seq, assembly

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Authors: Hadis Hosseinzadehnaseri

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The red tide is a kind of algae blooming, caused different problems at different sizes for the human life and the environment, so it has become one of the serious global concerns in the field of Oceanography in few recent decades. This phenomenon has affected on Iran's water, especially the Persian Gulf's since last few years. Collecting data associated with this phenomenon and comparison in different parts of the world is significant as a practical way to study this phenomenon and controlling it. Effective factors to occur this phenomenon lead to the increase of the required nutrients of the algae or provide a good environment for blooming. In this study, we examined the probability of relation between the earthquake and the harmful algae blooming in the Persian Gulf's water through comparing the earthquake data and the recorded Red tides. On the one hand, earthquakes can cause changes in seawater temperature that is effective in creating a suitable environment and the other hand, it increases the possibility of water nutrients, and its transportation in the seabed, so it can play a principal role in the development of red tide occurrence. Comparing the distribution spatial-temporal maps of the earthquakes and deadly red tides in the Persian Gulf and Oman Sea, confirms the hypothesis, why there is a meaningful relation between these two distributions. Comparing the number of earthquakes around the world as well as the number of the red tides in many parts of the world indicates the correlation between these two issues. This subject due to numerous earthquakes, especially in recent years and in the southern part of the country should be considered as a warning to the possibility of re-occurrence of a critical state of red tide in a large scale, why in the year 2008, the number of recorded earthquakes have been more than near years. In this year, the distribution value of the red tide phenomenon in the Persian Gulf got measured about 140,000 square kilometers and entire Oman Sea, with 10 months Survival in the area, which is considered as a record among the occurred algae blooming in the world. In this paper, we could obtain a logical and reasonable relation between the earthquake frequency and this phenomenon occurrence, through compilation of statistics relating to the earthquakes in the southern Iran, from 2000 to the end of the first half of 2013 and also collecting statistics on the occurrence of red tide in the region as well as examination of similar data in different parts of the world. As shown in Figure 1, according to a survey conducted on the earthquake data, the most earthquakes in the southern Iran ranks first in the fourth Gregorian calendar month In April, coincided with Ordibehesht and Khordad in Persian calendar and then in the tenth Gregorian calendar month In October, coincided in Aban and Azar in Persian calendar.

Keywords: red tide, earth quake, persian gulf, harmful algae bloom

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Authors: Adekunle K. O, Adeniyi A. E, Kolawole E

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One of the most dramatic trends in the communications market in recent years has been the growth of prepaid services. Today, prepaid no longer constitutes the low-revenue, basic-service segment. It is driven by a high margin, value-add service customers who view it as a convenient way of retaining control over their usage and communication spending while expecting high service levels. To service providers, prepaid services offer the advantage of reducing bad accounts while allowing them to predict usage and plan network resources. Yet, the real-time demands of prepaid services require a scalable, real-time platform to manage customers through their entire life cycle. It delivers integrated real-time rating, voucher management, recharge management, customer care and service provisioning for the generation of new prepaid services. It carries high scalability that can handle millions of prepaid customers in real-time through their entire life cycle.

Keywords: prepaid billing, voucher management, customers, automated, security

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Authors: Vangelis Papadimitropoulos

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This paper is part of the research program “Techno-Social Innovation in the Collaborative Economy”, funded by the Hellenic Foundation for Research and Innovation (H.F.R.I.) for the years 2022-2024. The paper showcases the Open Food Network (OFN) as an open-sourced digital platform supporting short food supply chains in local agricultural production and consumption. The paper outlines the research hypothesis, the theoretical framework, and the methodology of research as well as the findings and conclusions. Research hypothesis: The model of open cooperativism as a vehicle for systemic change in the agricultural sector. Theoretical framework: The research reviews the OFN as an illustrative case study of the three-zoned model of open cooperativism. The OFN is considered a paradigmatic case of the model of open cooperativism inasmuch as it produces commons, it consists of multiple stakeholders including ethical market entities, and it is variously supported by local authorities across the globe, the latter prefiguring the mini role of a partner state. Methodology: Research employs Ernesto Laclau and Chantal Mouffe’s discourse analysis -elements, floating signifiers, nodal points, discourses, logics of equivalence and difference- to analyse the breadth of empirical data gathered through literature review, digital ethnography, a survey, and in-depth interviews with core OFN members. Discourse analysis classifies OFN floating signifiers, nodal points, and discourses into four themes: value proposition, governance, economic policy, and legal policy. Findings: OFN floating signifiers align around the following nodal points and discourses: “digital commons”, “short food supply chains”, “sustainability”, “local”, “the elimination of intermediaries” and “systemic change”. The current research identifies a lack of common ground of what the discourse of “systemic change” signifies on the premises of the OFN’s value proposition. The lack of a common mission may be detrimental to the formation of a common strategy that would be perhaps deemed necessary to bring about systemic change in agriculture. Conclusions: Drawing on Laclau and Mouffe’s discourse theory of hegemony, research introduces a chain of equivalence by aligning discourses such as “agro-ecology”, “commons-based peer production”, “partner state” and “ethical market entities” under the model of open cooperativism, juxtaposed against the current hegemony of neoliberalism, which articulates discourses such as “market fundamentalism”, “privatization”, “green growth” and “the capitalist state” to promote corporatism and entrepreneurship. Research makes the case that for OFN to further agroecology and challenge the current hegemony of industrial agriculture, it is vital that it opens up its supply chains into equivalent sectors of the economy, civil society, and politics to form a chain of equivalence linking together ethical market entities, the commons and a partner state around the model of open cooperativism.

Keywords: sustainability, the digital commons, open cooperativism, innovation

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Authors: Mahdi Bazarganigilani

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Aortic enlargement, also known as an aortic aneurysm, can occur when the walls of the aorta become weak. This disease can become deadly if overlooked and undiagnosed. In this paper, a computer-aided diagnosis (CAD) system was introduced to accurately diagnose aortic enlargement from chest x-ray images. An enhanced convolutional neural network (CNN) was employed and then trained by transfer learning by using three different main areas from the original images. The areas included the left lung, heart, and right lung. The accuracy of the system was then evaluated on 1001 samples by using 4-fold cross-validation. A promising accuracy of 90% was achieved in terms of the F-measure indicator. The results showed using different areas from the original image in the training phase of CNN could increase the accuracy of predictions. This encouraged the author to evaluate this method on a larger dataset and even on different CAD systems for further enhancement of this methodology.

Keywords: computer-aided diagnosis systems, aortic enlargement, chest X-ray, image processing, convolutional neural networks

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Authors: Toushik Maiti, Saibal Chatterjee, Kamaljyoti Gogoi, Arijit Basuray

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Eastern Regional(ER) Grid and North Eastern Regional (NER) Grid are two major grids of Eastern Part of India. Both of the grid consists of voltage level 765kV, 400 kV, 220 kV and numerous buses at lower voltage range. Eastern Regional Grid and North Eastern Regional Grid are not only connected among themselves but are also connected to various other grids of India. ER and NER Grid having various HVDC lines or back to back systems which form the total network. The studied system comprises of 340 buses of different voltage levels and transmission lines running over a length of 32089 km. The validation of load flow has been done using IEEE STANDARD 30 bus system. The power flow simulation analysis has been performed after synchronizing both the Eastern Grid and North-Eastern Regional Grid of India using Power System Simulators for Engineering (PSS®E) Important inferences has been drawn from the study.

Keywords: HVDC, load flow, PSS®E, unsymmetrical and symmetrical faults

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Authors: Paul E. Jose

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A new self-report measure named the General Emotion Regulation Measure (GERM) assesses four key goals for experiencing broad valenced groups of emotions: 1) trying to experience positive emotions (e.g., joy, pride, liking a person); 2) trying to avoid experiencing positive emotions; 3) trying to experience negative emotions (e.g., anger, anxiety, contempt); and 4) trying to avoid experiencing negative emotions. Although individual differences in GERM motives have been identified, evidence of validity with common mood outcomes is lacking. In the present study, whether GERM motives predict self-reported subjective happiness and depressive symptoms (CES-D) was tested with a community sample of 833 young adults. It was predicted that the GERM motive of trying to experience positive emotions would positively predict subjective happiness, and analogously trying to experience negative emotions would predict depressive symptoms. An initial path model was constructed in which the four GERM motives predicted both subjective happiness and depressive symptoms. The fully saturated model included three non-significant paths, which were subsequently pruned, and a good fitting model was obtained (CFI = 1.00; RMR = .007). Two GERM motives significantly predicted subjective happiness: 1) trying to experience positive emotions ( = .38, p < .001) and 2) trying to avoid experiencing positive emotions ( = -.48, p <.001). Thus, individuals who reported high levels of trying to experience positive emotions reported high levels of happiness, and individuals who reported low levels of trying to avoid experiencing positive emotions also reported high levels of happiness. Three GERM motives significantly predicted depressive symptoms: 1) trying to avoid experiencing positive emotions ( = .20, p <.001); 2) trying to experience negative emotions ( = .15, p <.001); and 3) trying to experience positive emotions (= -.07, p <.001). In agreement with predictions, trying to experience positive emotions was positively associated with subjective happiness and trying to experience negative emotions was positively associated with depressive symptoms. In essence, these two valenced mood states seem to be sustained by trying to experience similarly valenced emotions. However, the three other significant paths in the model indicated that emotional motives play a complicated role in supporting both positive and negative mood states. For subjective happiness, the GERM motive of not trying to avoid positive emotions, i.e., not avoiding happiness, was also a strong predictor of happiness. Thus, people who report being the happiest are those individuals who not only strive to experience positive emotions but also are not ambivalent about them. The pattern for depressive symptoms was more nuanced. Individuals who reported higher depressive symptoms also reported higher levels of avoiding positive emotions and trying to experience negative emotions. The strongest predictor for depressed mood was avoiding positive emotions, which would suggest that happiness aversion or fear of happiness is an important motive for dysphoric people. Future work should determine whether these patterns of association are similar among clinically depressed people, and longitudinal data are needed to determine temporal relationships between motives and mood states.

Keywords: emotions motives, depression, subjective happiness, path model

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Authors: Iris Vogeler, Rogerio Cichota, Armin Werner

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Dairy farms are under pressure to increase productivity while reducing environmental impacts. Effective fertiliser management practices are critical to achieve this. Determination of optimum nitrogen (N) fertilisation rates which maximise pasture growth and minimise N losses is challenging due to variability in plant requirements and likely near-future supply of N by the soil. Remote sensing can be used for mapping N nutrition status of plants and to rapidly assess the spatial variability within a field. An algorithm is, however, lacking which relates the N status of the plants to the expected yield response to additions of N. The aim of this simulation study was to develop a multi-variate model for determining N fertilisation rate for a target percentage of the maximum achievable yield based on the pasture N concentration (ii) use of an algorithm for guiding fertilisation rates, and (iii) evaluation of the model regarding pasture yield and N losses, including N leaching, denitrification and volatilisation. A simulation study was carried out using the Agricultural Production Systems Simulator (APSIM). The simulations were done for an irrigated ryegrass pasture in the Canterbury region of New Zealand. A multi-variate model was developed and used to determine monthly required N fertilisation rates based on pasture N content prior to fertilisation and targets of 50, 75, 90 and 100% of the potential monthly yield. These monthly optimised fertilisation rules were evaluated by running APSIM for a ten-year period to provide yield and N loss estimates from both nonurine and urine affected areas. Comparison with typical fertilisation rates of 150 and 400 kg N/ha/year was also done. Assessment of pasture yield and leaching from fertiliser and urine patches indicated a large reduction in N losses when N fertilisation rates were controlled by the multi-variate model. However, the reduction in leaching losses was much smaller when taking into account the effects of urine patches. The proposed approach based on biophysical modelling to develop a multi-variate model for determining optimum N fertilisation rates dependent on pasture N content is very promising. Further analysis, under different environmental conditions and validation is required before the approach can be used to help adjust fertiliser management practices to temporal and spatial N demand based on the nitrogen status of the pasture.

Keywords: APSIM modelling, optimum N fertilization rate, pasture N content, ryegrass pasture, three dimensional surface response function.

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Authors: Mohamed R. Mhereeg

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The paper discusses the design of a .NET Windows Service based agent system called MACS (Multi-Agent Classification System). MACS is a system aims to accurately classify spread-sheet developers competency over a network. It is designed to automatically and autonomously monitor spread-sheet users and gather their development activities based on the utilization of the software Multi-Agent Technology (MAS). This is accomplished in such a way that makes management capable to efficiently allow for precise tailor training activities for future spread-sheet development. The monitoring agents of MACS are intended to be distributed over the WWW in order to satisfy the monitoring and classification of the multiple developer aspect. The Prometheus methodology is used for the design of the agents of MACS. Prometheus has been used to undertake this phase of the system design because it is developed specifically for specifying and designing agent-oriented systems. Additionally, Prometheus specifies also the communication needed between the agents in order to coordinate to achieve their delegated tasks.

Keywords: classification, design, MACS, MAS, prometheus

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Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

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Authors: Anamika Paul, Sudipto Sarkar

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The flow behaviour of non-Newtonian fluid is quite complicated, although both the pseudoplastic (n < 1, n being the power index) and dilatant (n > 1) fluids under this category are used immensely in chemical and process industries. A limited research work is carried out for flow over a bluff body in non-Newtonian flow environment. In the present numerical simulation we control the vortices of a square cylinder by placing an upstream vertical splitter plate for pseudoplastic (n=0.8), Newtonian (n=1) and dilatant (n=1.2) fluids. The position of the upstream plate is also varied to calculate the critical distance between the plate and cylinder, below which the cylinder vortex shedding suppresses. Here the Reynolds number is considered as Re = 150 (Re = U∞a/ν, where U∞ is the free-stream velocity of the flow, a is the side of the cylinder and ν is the maximum value of kinematic viscosity of the fluid), which comes under laminar periodic vortex shedding regime. The vertical plate is having a dimension of 0.5a × 0.05a and it is placed at the cylinder centre-line. Gambit 2.2.30 is used to construct the flow domain and to impose the boundary conditions. In detail, we imposed velocity inlet (u = U∞), pressure outlet (Neumann condition), symmetry (free-slip boundary condition) at upper and lower domain. Wall boundary condition (u = v = 0) is considered both on the cylinder and the splitter plate surfaces. The unsteady 2-D Navier Stokes equations in fully conservative form are then discretized in second-order spatial and first-order temporal form. These discretized equations are then solved by Ansys Fluent 14.5 implementing SIMPLE algorithm written in finite volume method. Here, fine meshing is used surrounding the plate and cylinder. Away from the cylinder, the grids are slowly stretched out in all directions. To get an account of mesh quality, a total of 297 × 208 grid points are used for G/a = 3 (G being the gap between the plate and cylinder) in the streamwise and flow-normal directions respectively after a grid independent study. The computed mean flow quantities obtained from Newtonian flow are agreed well with the available literatures. The results are depicted with the help of instantaneous and time-averaged flow fields. Qualitative and quantitative noteworthy differences are obtained in the flow field with the changes in rheology of fluid. Also, aerodynamic forces and vortex shedding frequencies differ with the gap-ratio and power index of the fluid. We can conclude from the present simulation that fluent is capable to capture the vortex dynamics of unsteady laminar flow regime even in the non-Newtonian flow environment.

Keywords: CFD, critical gap-ratio, splitter plate, wake-wake interactions, dilatant, pseudoplastic

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Authors: Kun Xue, Lvlan Miu, Jiarui Li

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Jetting structures are widely found in particle rings or shells dispersed by the central explosion. In contrast, some explosive dispersal of particles only results in a dispersed cloud without distinctive structures. Employing the coupling method of the compressible computational fluid mechanics and discrete element method (CCFD-DEM), we reveal the underlying physics governing the formation of the jetting structure, which is related to the competition between the shock compaction and gas infiltration, two major processes during the shock interaction with the granular media. If the shock compaction exceeds the gas infiltration, the discernable jetting structures are expected, precipitated by the agglomerates of fast-moving particles induced by the heterogenous network of force chains. Otherwise, particles are uniformly accelerated by the interstitial flows, and no distinguishable jetting structures are formed. We proceed to devise the phase map of the jetting formation in the space defined by two dimensionless parameters which characterize the timescales of the shock compaction and the gas infiltration, respectively.

Keywords: compressible multiphase flows, DEM, granular jetting, pattern formation

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Authors: Samiah Alammari, Nassim Ammour

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When providing a massive number of tasks successively to a deep learning process, a good performance of the model requires preserving the previous tasks data to retrain the model for each upcoming classification. Otherwise, the model performs poorly due to the catastrophic forgetting phenomenon. To overcome this shortcoming, we developed a successful continual learning deep model for remote sensing hyperspectral image regions classification. The proposed neural network architecture encapsulates two trainable subnetworks. The first module adapts its weights by minimizing the discrimination error between the land-cover classes during the new task learning, and the second module tries to learn how to replicate the data of the previous tasks by discovering the latent data structure of the new task dataset. We conduct experiments on HSI dataset Indian Pines. The results confirm the capability of the proposed method.

Keywords: continual learning, data reconstruction, remote sensing, hyperspectral image segmentation

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Authors: Ourn Vimoil, Kallaya Suntornvongsagul

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Cambodia is considered as one of the most disaster prone countries in South East Asia, and most of natural disasters are related to floods. Cambodia, a developing country, faces significant impacts from floods, such as environmental, social, and economic losses. Using data accessed from focus group discussions and field surveys with villagers in Ba Baong commune, prey Veng province, Cambodia, the research would like to examine roles of social networks in raising community’s coping capacity with floods. The findings indicate that social capital play crucial roles in three stages of floods, namely preparedness, response, and recovery to overcome the crisis. People shared their information and resources, and extent their assistances to one another in order to adapt to floods. The study contribute to policy makers, national and international agencies working on this issue to pay attention on social networks as one factors to accelerate flood coping capacity at community level.

Keywords: social network, community, coping capacity, flood, Cambodia

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Authors: Umesh Kumar Singh, Abhishek Raghuvanshi, Suyash Kumar Singh

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As IoT networks gain popularity, they are more susceptible to security breaches. As a result, it is crucial to analyze the IoT platform as a whole from the standpoint of core security concepts. The Internet of Things relies heavily on wireless networks, which are well-known for being susceptible to a wide variety of attacks. This article provides an analysis of many techniques that may be used to identify vulnerabilities in the software and hardware associated with the Internet of Things (IoT). In the current investigation, an experimental setup is built with the assistance of server computers, client PCs, Internet of Things development boards, sensors, and cloud subscriptions. Through the use of network host scanning methods and vulnerability scanning tools, raw data relating to IoT-based applications and devices may be collected. Shodan is a tool that is used for scanning, and it is also used for effective vulnerability discovery in IoT devices as well as penetration testing. This article presents an efficient mitigation plan for encountering vulnerabilities in the Internet of Things.

Keywords: internet of things, security, privacy, vulnerability identification, mitigation plan

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Authors: Salahud Din, Saima Masood, Hafsa Zaneb, Habib Ur Rehman, Saima Ashraf, Imad Khan, Muqader Shah

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The objective of this study was (1) to study gross morphological, osteometric and clinical important landmarks in the skull of adult Chinkara to obtain baseline data and (2) to study sexual dimorphism in male and female adult Chinkara through osteometry. For this purpose, after performing postmortem examination, the carcass of adult Chinkara of known sex and age was buried in the locality of the Manglot Wildlife Park and Ungulate Breeding Centre, Nizampur, Pakistan; after a specific period of time, the bones were unearthed. Gross morphological features and various osteometric parameters of the skull were studied in the University of Veterinary and Animal Sciences, Lahore, Pakistan. The shape of the Chinkara skull was elongated and had thirty-two bones. The skull was comprised of the cranial and the facial part. The facial region of the skull was formed by maxilla, incisive, palatine, vomar, pterygoid, frontal, parietal, nasal, incisive, turbinates, mandible and hyoid apparatus. The bony region of the cranium of Chinkara was comprised of occipital, ethmoid, sphenoid, interparietal, parietal, temporal, and frontal bone. The foramina identified in the facial region of the skull of Chinkara were infraorbital, supraorbital foramen, lacrimal, sphenopalatine, maxillary and caudal palatine foramina. The foramina of the cranium of the skull of the Chinkara were the internal acoustic meatus, external acoustic meatus, hypoglossal canal, transverse canal, sphenorbital fissure, carotid canal, foramen magnum, stylomastoid foramen, foramen rotundum, foramen ovale and jugular foramen, and the rostral and the caudal foramina that formed the pterygoid canal. The measured craniometric parameters did not show statistically significant differences (p > 0.05) between male and female adult Chinkara except Palatine bone, OI, DO, IOCDE, OCT, ICW, IPCW, and PCPL were significantly higher (p > 0.05) in male than female Chinkara and mean values of the mandibular parameters except b and h were significantly (p < 0.5) higher in male Chinkara than female Chinkara. Sexual dimorphism exists in some of the orbital and foramen magnum parameters, while high levels of sexual dimorphism identified in mandible. In conclusion, morphocraniometric studies of Chinkara skull made it possible to identify species-specific skull and use clinical measurements during practical application.

Keywords: Chinkara, skull, morphology, morphometrics, sexual dimorphism

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