Search results for: graph convolutional networks (GCNs)

Authors: Abrar Al-Hasan

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Web 2.0 has significantly increased the amount of information available to users not only about firms and their offerings, but also about the activities of other individuals in their networks and markets. It is widely acknowledged that this increased availability of ‘social’ information, particularly about other individuals, is likely to influence a user’s behavior and choices. However, there are very few systematic studies of how such increased information transparency on the behavior of other users in a focal users’ network influences a focal users’ behavior in the emerging marketplace of online language learning. This study seeks to examine the value and impact of ‘social activities’ – wherein, a user sees and interacts with the learning activities of her peers – on her language learning efficiency. An online experiment in a peer-to-peer language marketplace was conducted to compare the learning efficiency of users with ‘social’ information versus users with no ‘social’ information. The results of this study highlight the impact and importance of ‘social’ information within the language learning context. The study concludes by exploring how these insights may inspire new developments in online education.

Keywords: e-Learning, language learning marketplace, peer-to-peer, social network

Procedia PDF Downloads 385

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarms, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Sam Solaimani, Jack A. A. van der Veen, Mehdi Latifi

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Considering the increasingly VUCA (Volatile, Uncertain, Complex, Ambiguous) business market, innovation is the name of the game in contemporary business. Innovation is not solely created within the organization itself; its 'network environment' appears to be equally important for innovation. There are, at least, two streams of literature that emphasize the idea of using the extended organization to foster innovation capability, namely, Supply Chain Collaboration (SCC) (also rooted in the Lean philosophy) and Open Innovation (OI). Remarkably, these two concepts are still considered as being totally different in the sense that these appear in different streams of literature and applying different concepts in pursuing the same purposes. This paper explores the commonalities between the two concepts in order to conceptually further our understanding of how OI can effectively be applied in Supply Chain networks. Drawing on available literature in OI, SCC and Lean, the paper concludes with five principles that help firms to contextualize the implementation of OI to the peculiar setting of SC. Theoretically, the present paper aims at contributing to the relatively under-researched theme of Supply Chain Innovation. More in practical terms, the paper provides OI and SCC communities with a workable know-how to seize on and sustain OI initiatives.

Keywords: lean philosophy, open innovation, supply chain collaboration, supply chain management

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Authors: Priya Arora, Ashutosh Mishra

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Gene identification, towards the pursuit of mutated genes, leading to Parkinson’s disease, puts forward a challenge towards proactive cure of the disorder itself. Computational analysis is an effective technique for exploring genes in the form of protein sequences, as the theoretical and manual analysis is infeasible. The limitations and effectiveness of a particular computational method are entirely dependent on the previous data that is available for disease identification. The article presents a sequence-based classification method for the identification of genes responsible for Parkinson’s disease. During the initiation phase, the physicochemical properties of amino acids transform protein sequences into a feature vector. The second phase of the method employs Jaccard distances to select negative genes from the candidate population. The third phase involves artificial neural networks for making final predictions. The proposed approach is compared with the state of art methods on the basis of F-measure. The results confirm and estimate the efficiency of the method.

Keywords: disease gene identification, Parkinson’s disease, physicochemical properties of amino acid, protein sequences

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Authors: Jiri F. Urbanek, Jiri Barta, Oldrich Svoboda, Jiri J. Urbanek

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The organizations of European and Czech critical infrastructure have specific position, mission, characteristics and behaviour in European Union and Czech state/ business environments, regarding specific requirements for regional and global security environments. They must respect policy of national security and global rules, requirements and standards in all their inherent and outer processes of supply-customer chains and networks. A controlling is generalized capability to have control over situational policy. This paper aims and purposes are to introduce the controlling as quite new necessary process attribute providing for critical infrastructure is environment the capability and profit to achieve its commitment regarding to the effectiveness of the quality management system in meeting customer/ user requirements and also the continual improvement of critical infrastructure organization’s processes overall performance and efficiency, as well as its societal security via continual planning improvement via DYVELOP modelling.

Keywords: added value, DYVELOP, controlling, environments, process approach

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Authors: Stefanie Siebenhütter

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Male and female speakers use language differently and with varying confidence levels. This paper contrasts gendered differences in language use with socioeconomic status and age factors. It specifically examines how Kui minority language use and competence are conditioned by the variable of gender and discusses potential reasons for this variation by examining gendered language awareness and sociolinguistic attitudes. Moreover, it discusses whether women in Kui society function as 'leaders of linguistic change', as represented in Labov’s sociolinguistic model. It discusses whether societal role expectations in collectivistic cultures influence the model of linguistic change. The findings reveal current Kui speaking preferences and give predictions on the prospective language use, which is a stable situation of multilingualism because the current Kui speakers will socialize and teach the prospective Kui speakers in the near future. It further confirms that Lao is losing importance in Kui speaker’s (female’s) daily life.

Keywords: gender, identity construction, language change, minority language, multilingualism, sociolinguistics, social Networks

Procedia PDF Downloads 177

Authors: Teodorica G. Ani

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Economic activity requires an encouraging regulatory environment and effective rules that are transparent and accessible to all. The World Bank has been publishing the annual Doing Business reports since 2004 to investigate the scope and manner of regulations that enhance business activity and those that constrain it. A streamlined business environment supporting the development of competitive small and medium enterprises (SMEs) may expand employment opportunities and improve the living conditions of low income households. Asia has emerged as one of the most attractive markets in the world. Economies in East Asia and the Pacific were among the most active in making it easier for local firms to do business. The study aimed to describe the ease of doing business and its effect to economic growth among selected economies in Asia for the year 2014. The study covered 29 economies in East Asia, Southeast Asia, South Asia and Middle Asia. Ease of doing business is measured by the Doing Business indicators (DBI) of the World Bank. The indicators cover ten aspects of the ease of doing business such as starting a business, dealing with construction permits, getting electricity, registering property, getting credit, protecting investors, paying taxes, trading across borders, enforcing contracts and resolving insolvency. In the study, Gross Domestic Product (GDP) was used as the proxy variable for economic growth. Descriptive research was the research design used. Graphical analysis was used to describe the income and doing business among selected economies. In addition, multiple regression was used to determine the effect of doing business to economic growth. The study presented the income among selected economies. The graph showed China has the highest income while Maldives produces the lowest and that observation were supported by gathered literatures. The study also presented the status of the ten indicators of doing business among selected economies. The graphs showed varying trends on how easy to start a business, deal with construction permits and to register property. Starting a business is easiest in Singapore followed by Hong Kong. The study found out that the variations in ease of doing business is explained by starting a business, dealing with construction permits and registering property. Moreover, an explanation of the regression result implies that a day increase in the average number of days it takes to complete a procedure will decrease the value of GDP in general. The research proposed inputs to policy which may increase the awareness of local government units of different economies on the simplification of the policies of the different components used in measuring doing business.

Keywords: doing business, economic growth, gross domestic product, Asia

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Authors: Sadaf Zahra Usman

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Business Incubation has become a pervasive phenomenon in numerous parts of the world and is seen as a tool for creating a startup ecosystem. The reason for greatest barriers to the advancement of business incubation centers is the need for an entrepreneurial ecosystem and underdeveloped financial assistance and angel investor networks for startup firms. Business incubation helps in creating successful startup ventures by providing administrative support services and assistance in creating their ventures. We identify incubators into three categories: University incubation centers (UICs), Private incubators (PICs), and Government incubator centers (GICs) to measure the influence of different types of business incubation practices and their performance by using a survey questionnaire from incubation managers across Pakistan. The analysis is conducted on eight Business incubators. Results suggest that the quality of incubation centers is extremely important in this regard. The research anticipated helping policymakers, government officials, and incubation management to utilize business incubation more effectively to “hatch” innovation-based entrepreneurial development.

Keywords: entrepreneurship, unemployment, startups, economy, business incubation practice

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Authors: Julia Baker

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Development plays a major role in stopping biodiversity loss. But the ‘silo species’ protection of legislation (where certain species are protected while many are not) means that development can be ‘legally compliant’ and result in biodiversity loss. ‘Net Gain’ (NG) policies can help overcome this by making it an absolute requirement that development causes no overall loss of biodiversity and brings a benefit. However, offsetting biodiversity losses in one location with gains elsewhere is controversial because people suspect ‘offsetting’ to be an easy way for developers to buy their way out of conservation requirements. Yet the good practice principles (GPP) of offsetting provide several advantages over existing legislation for protecting biodiversity from development. This presentation describes the learning from implementing NG approaches based on GPP. It regards major upgrades of the UK’s transport networks, which involved removing vegetation in order to construct and safely operate new infrastructure. While low-lying habitats were retained, trees and other habitats disrupting the running or safety of transport networks could not. Consequently, achieving NG within the transport corridor was not possible and offsetting was required. The first ‘lessons learnt’ were on obtaining a commitment from business leaders to go beyond legislative requirements and deliver NG, and on the institutional change necessary to embed GPP within daily operations. These issues can only be addressed when the challenges that biodiversity poses for business are overcome. These challenges included: biodiversity cannot be measured easily unlike other sustainability factors like carbon and water that have metrics for target-setting and measuring progress; and, the mindset that biodiversity costs money and does not generate cash in return, which is the opposite of carbon or waste for example, where people can see how ‘sustainability’ actions save money. The challenges were overcome by presenting the GPP of NG as a cost-efficient solution to specific, critical risks facing the business that also boost industry recognition, and by using government-issued NG metrics to develop business-specific toolkits charting their NG progress whilst ensuring that NG decision-making was based on rich ecological data. An institutional change was best achieved by supporting, mentoring and training sustainability/environmental managers for these ‘frontline’ staff to embed GPP within the business. The second learning was from implementing the GPP where business partnered with local governments, wildlife groups and land owners to support their priorities for nature conservation, and where these partners had a say in decisions about where and how best to achieve NG. From this inclusive approach, offsetting contributed towards conservation priorities when all collaborated to manage trade-offs between: -Delivering ecologically equivalent offsets or compensating for losses of one type of biodiversity by providing another. -Achieving NG locally to the development whilst contributing towards national conservation priorities through landscape-level planning. -Not just protecting the extent and condition of existing biodiversity but ‘doing more’. -The multi-sector collaborations identified practical, workable solutions to ‘in perpetuity’. But key was strengthening linkages between biodiversity measures implemented for development and conservation work undertaken by local organizations so that developers support NG initiatives that really count.

Keywords: biodiversity offsetting, development, nature conservation planning, net gain

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Authors: Karim Farahmandfar, Hamidolah Izadi, Mohammadreza Rezaei, Amin Ardali, Ebrahim Goshtasbi Rad, Khosro Jafarpoor

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Statistics illustrates that the higher amount of annual energy consumption is related to surmounting the demand in buildings. Therefore, it is vital to economize the energy consumption and also find the solution with regard to this issue. One of the systems for the sake of heating the building is floor heating. As a matter of fact, floor heating performance is based on convection and radiation. Actually, in addition to creating a favorable heating condition, this method leads to energy saving. It is the goal of this article to outline the constructal theory and introduce the optimization method in branch networks for floor heating. There are several steps in order to gain this purpose. First of all, the pressure drop through the two points of the network is calculated. This pressure drop is as a function of pipes diameter and other parameters. After that, the amount of heat transfer is determined. Consequently, as a result of the combination of these two functions, the final function will be determined. It is necessary to mention that flow is laminar.

Keywords: constructal theory, optimization, floor heating system, turbulent flow

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Authors: Nasrine Olson

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With over 70,000 scholarly publications on the topic of biosensors, an overview of the field has become a challenge. To facilitate, there are currently over 700 expert-reviews of publications on biosensors and related topics. This study focuses on these review papers in order to provide a Meta-Review of the area. This paper provides a statistical analysis and overview of biosensor-related review papers. Comprehensive searches are conducted in the Web of Science, and PubMed databases and the resulting empirical material are analyzed using bibliometric methods and tools. The study finds that the biosensor-related review papers can be categorized in five related subgroups, broadly denoted by (i) properties of materials and particles, (ii) analysis and indicators, (iii) diagnostics, (iv) pollutant and analytical devices, and (v) treatment/ application. For an easy and clear access to the findings visualization of clusters and networks of connections are presented. The study includes a temporal dimension and identifies the trends over the years with an emphasis on the most recent developments. This paper provides useful insights for those who wish to form a better understanding of the research trends in the area of biosensors.

Keywords: bibliometrics, biosensors, meta-review, statistical analysis, trends visualization

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Authors: Javad Abdi, Azam Famil Khalili

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Modeling emotions have attracted much attention in recent years, both in cognitive psychology and design of artificial systems. However, it is a negative factor in decision-making; emotions have shown to be a strong faculty for making fast satisfying decisions. In this paper, we have adapted a computational model based on the limbic system in the mammalian brain for control engineering applications. Learning in this model based on Temporal Difference (TD) Learning, we applied the proposed controller (termed BELBIC) for a simple model of a submarine. The model was supposed to reach the desired depth underwater. Our results demonstrate excellent control action, disturbance handling, and system parameter robustness for TDBELBIC. The proposal method, regarding the present conditions, the system action in the part and the controlling aims, can control the system in a way that these objectives are attained in the least amount of time and the best way.

Keywords: artificial neural networks, temporal difference, brain emotional learning based intelligent controller, heating- ventilating and air conditioning

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Authors: Sheela Tiwari, R. Naresh, R. Jha

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The paper presents an investigation into the effect of neural network predictive control of UPFC on the transient stability performance of a multi-machine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers and an improved damping of the power oscillations as compared to the conventional PI controller.

Keywords: identification, neural networks, predictive control, transient stability, UPFC

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Authors: Sanaz Moayer, Fang Huang, Scott Gardner

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In the highly leveraged business world of today, an organisation’s success depends on how it can manage and organize its traditional and intangible assets. In the knowledge-based economy, knowledge as a valuable asset gives enduring capability to firms competing in rapidly shifting global markets. It can be argued that ability to create unique knowledge assets by configuring ICT and human capabilities, will be a defining factor for international competitive advantage in the mid-21st century. The concept of KM is recognized in the strategy literature, and increasingly by senior decision-makers (particularly in large firms which can achieve scalable benefits), as an important vehicle for stimulating innovation and organisational performance in the knowledge economy. This thinking has been evident in professional services and other knowledge intensive industries for over a decade. It highlights the importance of social capital and the value of the intellectual capital embedded in social and professional networks, complementing the traditional focus on creation of intellectual property assets. Despite the growing interest in KM within professional services there has been limited discussion in relation to multinational resource based industries such as mining and petroleum where the focus has been principally on global portfolio optimization with economies of scale, process efficiencies and cost reduction. The Australian minerals and metals mining industry, although traditionally viewed as capital intensive, employs a significant number of knowledge workers notably- engineers, geologists, highly skilled technicians, legal, finance, accounting, ICT and contracts specialists working in projects or functions, representing potential knowledge silos within the organisation. This silo effect arguably inhibits knowledge sharing and retention by disaggregating corporate memory, with increased operational and project continuity risk. It also may limit the potential for process, product, and service innovation. In this paper the strategic application of knowledge management incorporating contemporary ICT platforms and data mining practices is explored as an important enabler for knowledge discovery, reduction of risk, and retention of corporate knowledge in resource based industries. With reference to the relevant strategy, management, and information systems literature, this paper highlights possible connections (currently undergoing empirical testing), between an Strategic Knowledge Management (SKM) framework incorporating supportive Data Mining (DM) practices and competitive advantage for multinational firms operating within the Australian resource sector. We also propose based on a review of the relevant literature that more effective management of soft and hard systems knowledge is crucial for major Australian firms in all sectors seeking to improve organisational performance through the human and technological capability captured in organisational networks.

Keywords: competitive advantage, data mining, mining organisation, strategic knowledge management

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Authors: Virender Ranga, Mayank Dave, Anil Kumar Verma

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Recently wireless sensor networks (WSNs) are used in many real life applications like environmental monitoring, habitat monitoring, health monitoring etc. Due to power constraint cheaper devices used in these applications, the energy consumption of each device should be kept as low as possible such that network operates for longer period of time. One of the techniques to prolong the network lifetime is an intelligent grouping of sensor nodes such that they can perform their operation in cooperative and energy efficient manner. With this motivation, we propose a novel approach by organize the sensor nodes in cooperative multihop mini-groups so that the total global energy consumption of the network can be reduced and network lifetime can be improved. Our proposed approach also reduces the number of transmitted messages inside the WSNs, which further minimizes the energy consumption of the whole network. The experimental simulations show that our proposed approach outperforms over the state-of-the-art approach in terms of stability period and aggregated data.

Keywords: clustering, cluster-head, mini-group, stability period

Procedia PDF Downloads 357

Authors: Getaneh Berie Tarekegn, Li-Chia Tai

Abstract:

With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

Procedia PDF Downloads 47

Authors: Nadjat Zerf Boudjettou, Fahima Nader, Rachid Chalal

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Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system.

Keywords: data warehouse, data mining, knowledge discovery in database, KDD, medical knowledge management, Bayesian networks

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Authors: W. Rowan, Y. O’Connor, L. Lynch, C. Heavin

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Situation Awareness can offer the potential for conscious dynamic reflection. In an era of online health data sharing, it is becoming increasingly important that users of health social networks (HSNs) have the information necessary to make informed decisions as part of the registration process and in the provision of eConsent. This research aims to leverage an adapted Situation Awareness (SA) model to explore users’ decision making processes in the provision of eConsent. A HSN platform was used to investigate these behaviours. A mixed methods approach was taken. This involved the observation of registration behaviours followed by a questionnaire and focus group/s. Early results suggest that users are apt to automatically accept eConsent, and only later consider the long-term implications of sharing their personal health information. Further steps are required to continue developing knowledge and understanding of this important eConsent process. The next step in this research will be to develop a set of guidelines for the improved presentation of eConsent on the HSN platform.

Keywords: eConsent, health social network, mixed methods, situation awareness

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Authors: Magdaléna Náplavová, Tomáš Ludík, Petr Hrůza, František Božek

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The use of IT equipment has become a part of every day. However, each device that is part of cyberspace should be secured against unauthorized use. It is very important to know the basics of these security devices, but also the basics of safe conduct their owners. This information should be part of every curriculum computer science education in primary and secondary schools. Therefore, the work focuses on the education of pupils in primary and secondary schools on the Internet. Analysis of the current state describes approaches to the education of pupils in security issues on the Internet. The paper presents a questionnaire-based survey which was carried out in the Czech Republic, whose task was to ascertain the level of opinion pupils in primary and secondary schools on the issue of communication in social networks. The research showed that awareness of socio-pathological phenomena on the Internet environment is very low. Based on the results it was proposed appropriate ways of teaching to this issue and its inclusion a proposal of curriculum for primary and secondary schools.

Keywords: information security, cyber space, general awareness, questionnaire, socio-pathological phenomena, educational system

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Authors: Lilla Dorina Habsz, Marta Rado

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Popularity is affected by a variety of factors in the primary school such as academic achievement and ethnicity. The main goal of our study was to analyse whether acting white exists in Hungarian elementary schools. In other words, we observed whether Roma students penalize those in-group members who obtain the high academic achievement. Furthermore, to show how popularity is influenced by changes in academic achievement in inter-ethnic relations. The empirical basis of our research was the 'competition and negative networks' longitudinal dataset, which was collected by the MTA TK 'Lendület' RECENS research group. This research followed 11 and 12-year old students for a two-year period. The survey was analysed using fixed and random effect models. Overall, we found a positive correlation between grades and popularity, but no evidence for the acting white effect. However, better grades were more positively evaluated within the majority group than within the minority group, which may further increase inequalities.

Keywords: academic achievement, elementary school, ethnicity, popularity

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Authors: Miria Gambardella

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The influence of solidarity demonstrations towards the Zapatista National Liberation Army has been constantly present over the years, both locally and internationally, guaranteeing visibility to the cause, shaping the movement’s choices, and influencing its hopes of impact worldwide. Most of the coffee produced by the autonomous cooperatives from Chiapas is exported, therefore making coffee trade the main income from international solidarity networks. The question arises about the implications of the relations established between the communities in resistance in Southeastern Mexico and international solidarity movements, specifically on the strategies adopted to conciliate army's demands for autonomy and economic asymmetries between Zapatista cooperatives producing coffee and European collectives who hold purchasing power. In order to deepen the inquiry on those topics, a year-long multi-site investigation was carried out. The first six months of fieldwork were based in Barcelona, where Zapatista coffee was first traded in Spain and where one of the historical and most important European solidarity groups can be found. The last six months of fieldwork were carried out directly in Chiapas, in contact with coffee producers, Zapatista political authorities, international activists as well as vendors, and the rest of the network implicated in coffee production, roasting, and sale. The investigation was based on qualitative research methods, including participatory observation, focus groups, and semi-structured interviews. The analysis did not only focus on retracing the steps of the market chain as if it could be considered a linear and unilateral process, but it rather aimed at exploring actors’ reciprocal perceptions, roles, and dynamics of power. Demonstrations of solidarity and the money circulation they imply aim at changing the system in place and building alternatives, among other things, on the economic level. This work analyzes the formulation of discourse and the organization of solidarity activities that aim at building opportunities for action within a highly politicized economic sphere to which access must be regularly legitimized. The meaning conveyed by coffee is constructed on a symbolic level by the attribution of moral criteria to transactions. The latter participate in the construction of imaginaries that circulate through solidarity movements with the Zapatista rebellion. Commercial exchanges linked to solidarity networks turned out to represent much more than monetary transactions. The social, cultural, and political spheres are invested by ethics, which penetrates all aspects of militant action. It is at this level that the boundaries of different collective actors connect, contaminating each other: merely following the money flow would have been limiting in order to account for a reality within which imaginary is one of the main currencies. The notions of “trust”, “dignity” and “reciprocity” are repeatedly mobilized to negotiate discontinuous and multidirectional flows in the attempt to balance and justify commercial relations in a politicized context that characterizes its own identity through demonizing “market economy” and its dehumanizing powers.

Keywords: coffee trade, economic anthropology, international cooperation, Zapatista National Liberation Army

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Authors: Neeta Kumari, Gopal Pathak

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Artificial neural network has been proved to be an efficient tool for non-parametric modeling of data in various applications where output is non-linearly associated with input. It is a preferred tool for many predictive data mining applications because of its power , flexibility, and ease of use. A standard feed forward networks (FFN) is used to predict the groundwater fluoride content. The ANN model is trained using back propagated algorithm, Tansig and Logsig activation function having varying number of neurons. The models are evaluated on the basis of statistical performance criteria like Root Mean Squarred Error (RMSE) and Regression coefficient (R2), bias (mean error), Coefficient of variation (CV), Nash-Sutcliffe efficiency (NSE), and the index of agreement (IOA). The results of the study indicate that Artificial neural network (ANN) can be used for groundwater fluoride prediction in the limited data situation in the hard rock region like western parts of Jharkhand with sufficiently good accuracy.

Keywords: Artificial neural network (ANN), FFN (Feed-forward network), backpropagation algorithm, Levenberg-Marquardt algorithm, groundwater fluoride contamination

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Authors: Norbert Csizmadia

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The 21st Century's main power centers are the cities. More than 52% of the world’s population lives in cities, in particular in the megacities which have a population over 10 million people and is still growing. According to various research and forecasts, the main economic concentration will be in 40 megacities and global centers. Based on various competitiveness analyzes and indices, global city centers, and city networks are outlined, but if we look at other aspects of urban development like complexity, connectivity, creativity, technological development, viability, green cities, pedestrian and child friendly cities, creative and cultural centers, cultural spaces and knowledge centers, we get a city competitiveness index with quite new complex indicators. The research shows this result. In addition to the megacities and the global centers, with the investigation of functionality, we got 64 so-called ‘fusiononopolis’ (i.e., fusion-polis) which stand for the most decisive economic power centers of the 21st century. In this city competition Asian centers considerably rise, as the world's functional city competitiveness index is being formed.

Keywords: economic geography, human geography, technological development, urbanism

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Authors: Saurabh Parkhedkar, Rajanikant Tenguria

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The paper proposes revamping the public transportation system in Mumbai with the use of Radio Frequency Identification (RFID) technology in order to provide better integration and compatibility across various modes of transport. In Mumbai, mass transport system suffers from poor inter-compatible ticketing system, subpar money collection techniques, and lack of planning for optimum utilization of resources. Development of suburbs and growth in population will result in growing demand for mass transportation networks. Hence, the growing demand for the already overburdened public transportation system is only going to worsen the scenario. Thus, a superior system is essential in order to regulate, manage and supervise future transportation needs. The proposed RFID based system integrates Mumbai Suburban Railway, BEST (Brihanmumbai Electric Supply and Transport Undertaking transport wing) Bus, Mumbai Monorail and Mumbai Metro systems into a Unified Public Transportation System (UPTS). The UTPS takes into account various drawbacks of the present day system and offers solution, suitable for the modern age Mumbai.

Keywords: urbanization, transportation, RFID, Mumbai, public transportation, smart city.

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Authors: Sumbal Riaz, Sardar-un-Nisa, Mehreen Sirshar

Abstract:

5G - The 5th generation of mobile phone and data communication standards is the next edge of innovation for whole mobile industry. 5G is Real Wireless World System and it will provide a totally wireless communication system all over the world without limitations. 5G uses many 4g technologies and it will hit the market in 2020. This research is the comprehensive survey on the quality parameters of 5G technology.5G provide High performance, Interoperability, easy roaming, fully converged services, friendly interface and scalability at low cost. To meet the traffic demands in future fifth generation wireless communications systems will include i) higher densification of heterogeneous networks with massive deployment of small base stations supporting various Radio Access Technologies (RATs), ii) use of massive Multiple Input Multiple Output (MIMO) arrays, iii) use of millimetre Wave spectrum where larger wider frequency bands are available, iv) direct device to device (D2D) communication, v) simultaneous transmission and reception, vi) cognitive radio technology.

Keywords: 5G, 5th generation, innovation, standard, wireless communication

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Authors: Fariba Ebrahimi, Mehdi Ghorbani

Abstract:

Achieving to integrated Water management fundamentally needs to effective relation, coordination, collaboration and synergy among various actors who have common but different responsibilities. In this sense, the foundation of comprehensive and integrated management is not compatible with centralization and top-down strategies. The aim of this paper is analysis institutional network of water relevant stakeholders and water policy monitoring in Shemiranat. In this study collaboration networks between informal and formal institutions co-management process have been investigated. Stakeholder network analysis as a quantitative method has been implicated in this research. The results of this study indicate that institutional cohesion is medium; sustainability of institutional network is about 40 percent (medium). Additionally the core-periphery index has measured in this study according to reciprocity index. Institutional capacities for integrated natural resource management in regional level are measured in this study. Furthermore, the necessity of centrality reduction and promote stakeholders relations and cohesion are emphasized to establish a collaborative natural resource governance.

Keywords: policy monitoring, water management, social network, stakeholder, shemiranat

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Authors: Sukhbir Singh

Abstract:

This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

Abstract:

Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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Authors: Sombol Mokhles

Abstract:

Tackling climate change requires expanding networking opportunities between a diverse range of cities to accelerate climate actions. Existing climate city networks have limitations in actively engaging “ordinary” cities in networking processes between cities, as they encourage a few powerful cities to be followed by the many “ordinary” cities. To reimagine the networking opportunities between cities beyond global cities, this paper incorporates “cosmopolitan comparison” to expand our knowledge of a diverse range of cities using a data-driven approach. Through a cosmopolitan perspective, a framework is presented on how to utilise large data to expand knowledge of cities beyond global cities to reimagine the existing hierarchical networking practices. The contribution of this framework is beyond urban climate governance but inclusive of different fields which strive for a more inclusive and cosmopolitan comparison attentive to the differences across cities.

Keywords: cosmopolitan city comparison, data-driven approach, climate city networking, urban climate governance

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Authors: Paola Clerici Maestosi

Abstract:

Positive Energy District (PED) is a rather recent concept whose aim is to contribute to the main objectives of the Energy Union strategy. It is based on an integrated multi-sectoral approach in response to Europe's most complex challenges. PED integrates energy efficiency, renewable energy production, and energy flexibility in an integrated, multi-sectoral approach at the city level. The core idea behind Positive Energy Districts (PEDs) is to establish an urban area that can generate more energy than it consumes. Additionally, it should be flexible enough to adapt to changes in the energy market. This is crucial because a PED's goal is not just to achieve an annual surplus of net energy but also to help reduce the impact on the interconnected centralized energy networks. It achieves this by providing options to increase on-site load matching and self-consumption, employing technologies for short- and long-term energy storage, and offering energy flexibility through smart control. Thus, it seems that PEDs can encompass all types of buildings in the city environment. Given this which is the added value of having green buildings being constitutive part of PEDS? The paper will present a systematic literature review identifying the role of green building in Positive Energy District to provide answer to following questions: (RQ1) the state of the art of PEDs implementation; (RQ2) penetration of green building in Positive Energy District selected case studies. Methodological approach is based on a broad holistic study of bibliographic sources according to Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) further data will be analysed, mapped and text mining through VOSviewer. Main contribution of research is a cognitive framework on Positive Energy District in Europe and a selection of case studies where green building supported the transition to PED. The inclusion of green buildings within Positive Energy Districts (PEDs) adds significant value for several reasons. Firstly, green buildings are designed and constructed with a focus on environmental sustainability, incorporating energy-efficient technologies, materials, and design principles. As integral components of PEDs, these structures contribute directly to the district's overall ability to generate more energy than it consumes. Secondly, green buildings typically incorporate renewable energy sources, such as solar panels or wind turbines, further boosting the district's capacity for energy generation. This aligns with the PED objective of achieving a surplus of net energy. Moreover, green buildings often feature advanced systems for on-site energy management, load-matching, and self-consumption. This enhances the PED's capability to respond to variations in the energy market, making the district more agile and flexible in optimizing energy use. Additionally, the environmental considerations embedded in green buildings align with the broader sustainability goals of PEDs. By reducing the ecological footprint of individual structures, PEDs with green buildings contribute to minimizing the overall impact on centralized energy networks and promote a more sustainable urban environment. In summary, the incorporation of green buildings within PEDs not only aligns with the district's energy objectives but also enhances environmental sustainability, energy efficiency, and the overall resilience of the urban environment.

Keywords: positive energy district, renewables energy production, energy flexibility, energy efficiency

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