Search results for: smart decisions

Authors: Amna Ali Al-Saadi, Riken Homma, Kazuhisa Iki

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Despite the fact that many places have successes in achieving some aspects of sustainable urban development, there are no scientific facts to convince decision makers. Also, each of them was developed to fulfill the need of specific city only. Therefore, objective method to generate the solutions from a successful case is the aim of this research. The questions were: how to learn the lesson from each case study; how to distinguish the potential criteria and negative one; snd how to quantify their effects in the future development. Walkability has been selected as a goal. This is because it has been found as a solution to achieve healthy life style as well as social, environmental and economic sustainability. Moreover, it has complication as every aspect of sustainable development. This research is stand on quantitative- comparative methodology in order to assess pedestrian oriented development. Three analyzed area (AAs) were selected. One site is located in Oman in which hypotheses as motorized oriented development, while two sites are in Japan where the development is pedestrian friendly. The study used Multi- criteria evaluation method (MCEM). Initially, MCEM stands on analytic hierarchy process (AHP). The later was structured into main goal (walkability), objectives (functions and layout) and attributes (the urban form criteria). Secondly, the GIS were used to evaluate the attributes in multi-criteria maps. Since each criterion has different scale of measurement, all results were standardized by z-score and used to measure the co-relations among criteria. As results, different scenario was generated from each AA. MCEM (AHP-OWA)-GIS measured the walkability score and determined the priority of criteria development in the non-walker friendly environment. The comparison criteria for z-score presented a measurable distinguished orientation of development. This result has been used to prove that Oman is motorized environment while Japan is walkable. Also, it defined the powerful criteria and week criteria regardless to the AA. This result has been used to generalize the priority for walkable development. In conclusion, the method was found successful in generate scientific base for policy decisions.

Keywords: walkability, policy decisions, sustainable development, GIS

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Authors: Anita Lazurko, Laszlo Pinter, Jeremy Richardson

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Uncertain climate projections, multiple possible development futures, and a financing gap create challenges for water infrastructure decision making. In contrast to conventional predict-plan-act methods, an emerging decision paradigm that enables social-ecological resilience supports decisions that are appropriate for uncertainty and leverage social, ecological, and economic multifunctionality. Concurrently, water infrastructure project finance plays a powerful role in sustainable infrastructure development but remains disconnected from discourse in socio-ecological resilience. At the time of research, a project to transfer water from Lesotho to Botswana through South Africa in the Orange-Senqu River Basin was at the pre-feasibility stage. This case was analysed through documents and interviews to investigate how uncertainty and multifunctionality are conceptualised and considered in decisions for the resilience of water infrastructure and to explore bridging concepts that might allow project finance to better enable socio-ecological resilience. Interviewees conceptualised uncertainty as risk, ambiguity and ignorance, and multifunctionality as politically-motivated shared benefits. Numerous efforts to adopt emerging decision methods that consider these terms were in use but required compromises to accommodate the persistent, conventional decision paradigm, though a range of future opportunities was identified. Bridging these findings to finance revealed opportunities to consider a more comprehensive scope of risk, to leverage risk mitigation measures, to diffuse risks and benefits over space, time and to diverse actor groups, and to clarify roles to achieve multiple objectives for resilience. In addition to insights into how multiple decision paradigms interact in real-world decision contexts, the research highlights untapped potential at the juncture between socio-ecological resilience and project finance.

Keywords: socio-ecological resilience, finance, multifunctionality, uncertainty

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Authors: Behzad Hezarkhani, Greys Sosic

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Collaborative purchasing and replenishment have proven to be beneficial in supply chain management. This talk addresses the situation where buyers, potentially in possession of private procurement channels, carry out cooperative purchasing by submitting their bids to a coordinator. The collaborative organization is faced with two basic decisions: (1) who will be allocated with the products, and (2) how much each party should pay. We discuss mechanisms that could achieve desirable outcomes in this settings with special attention to the strategic behavior of the buyers.

Keywords: supply chain management, group purchasing organizations, game theory, mechanism design

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Authors: Aishi Kundu, Elhan Raza

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"Necessity is the mother of invention" - Rapid increase in the global human population has directed the agricultural domain toward machine learning. The basic need of human beings is considered to be food which can be satisfied through farming. Farming is one of the major revenue generators for the Indian economy. Agriculture is not only considered a source of employment but also fulfils humans’ basic needs. So, agriculture is considered to be the source of employment and a pillar of the economy in developing countries like India. This paper provides a brief review of the progress made in implementing Machine Learning in the agricultural sector. Accurate predictions are necessary at the right time to boost production and to aid the timely and systematic distribution of agricultural commodities to make their availability in the market faster and more effective. This paper includes a thorough analysis of various machine learning algorithms applied in different aspects of agriculture (crop management, soil management, water management, yield tracking, livestock management, etc.).Due to climate changes, crop production is affected. Machine learning can analyse the changing patterns and come up with a suitable approach to minimize loss and maximize yield. Machine Learning algorithms/ models (regression, support vector machines, bayesian models, artificial neural networks, decision trees, etc.) are used in smart agriculture to analyze and predict specific outcomes which can be vital in increasing the productivity of the Agricultural Food Industry. It is to demonstrate vividly agricultural works under machine learning to sensor data. Machine Learning is the ongoing technology benefitting farmers to improve gains in agriculture and minimize losses. This paper discusses how the irrigation and farming management systems evolve in real-time efficiently. Artificial Intelligence (AI) enabled programs to emerge with rich apprehension for the support of farmers with an immense examination of data.

Keywords: machine Learning, artificial intelligence, crop management, precision farming, smart farming, pre-harvesting, harvesting, post-harvesting

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Authors: Nuno Biga

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Artificial Intelligence (AI) allows machines to interpret information and learn from context analysis, giving them the ability to make predictions adjusted to each specific situation. In addition to learning by performing deterministic and probabilistic calculations, the 'artificial brain' also learns through information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) that provides users with useful suggestions, namely to pursue the following operations: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time the bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed in a pilot project. Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of this information is materialised in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" that players can use during the Game. Each participant in the Virtual Assisted-BIGAMES permanently asks himself about the decisions he should make during the game in order to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, and as the participants gain a better understanding of the game, they will more easily dispense with the VA's recommendations and rely more on their own experience, capability, and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator (Serious Game Controller) is responsible for supporting the players with further analysis and the recommended action may be (or not) aligned with the previous recommendations of the VA. All the information should be jointly analysed and assessed by each player, who are expected to add “Emotional Intelligence”, a component absent from the machine learning process.

Keywords: artificial intelligence (AI), gamification, key performance indicators (KPI), machine learning, management simulators, serious games, virtual assistant

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Authors: Gábor Kocsmárik

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The topic of this is coercive measures against assets in which the factor of the procedure contains a foreign element. We speak of cross-border enforcement if the debtor or the property requesting enforcement or subject to enforcement is not located in the bordering country. Given that the jurisdiction of a country cannot extend beyond its borders, the cooperation of nations and the mutual recognition of their decisions are necessary to eliminate this. In addition, it is essential to create framework rules that are binding and enforceable for each country participating in the convention. During the study, some conventions between countries that are still in force will be presented, which can serve as a starting point for dealing with existing problems.

Keywords: law, execution, civil procedure law, international

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Authors: Md Rezaul Karim, Farha Taznin

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The purpose of this study was to assess and describe the individual and household characteristics of farmers, to measure the attitude of farmers towards climate adaptation farming practices and to explore the individual and household factors contributing in predicting their attitude towards climate adaptation farming practices. Data were collected through personal interviews using a pre-tested interview schedule. The data collection was done at Biral Upazila under Dinajpur district in Bangladesh from 1st November to 15 December 2018. Besides descriptive statistical parameters, Pearson’s Product Moment Correlation Coefficient (r), multiple regression and step-wise multiple regression analysis were used for the statistical analysis. Findings indicated that the highest proportion (77.6 percent) of the farmers had moderately favorable attitudes, followed by only 11.2 percent with highly favorable attitudes and 11.2 percent with slightly favorable attitudes towards climate adaptation farming practices. According to the computed correlation coefficients (r), among the 10 selected factors, five of them, such as education of household head, farm size, annual household income, organizational participation, and information access by extension services, had a significant relationship with the attitude of farmers towards climate-smart practices. The step-wise multiple regression results showed that two characteristics as education of household head and information access by extension services, contributed 26.2% and 5.1%, respectively, in predicting farmers' attitudes towards climate adaptation farming practices. In addition, more than two-thirds of farmers cited their opinion to the problems in response to ‘price of vermi species is high and it is not easily available’ as 1st ranked problem, followed by ‘lack of information for innovative climate-smart technologies’. This study suggests that policy implications are necessary to promote extension education and information services and overcome the obstacles to climate adaptation farming practices. It further recommends that research study should be conducted in diverse contexts of nationally or globally.

Keywords: factors, attitude, climate adaptation, farming practices, Bangladesh

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Authors: Elizabeth Howarth, Dawn Green, Sean Connolly, Geena Vabulas, Sara Smolley

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Through the EU Horizon 2020 Nuvoic Project, the project team recruited 70 individuals in the UK and Ireland to test the Voiceitt speech recognition app and provide user feedback to developers. The app is designed for people with dysarthric speech, to support communication with unfamiliar people and access to speech-driven technologies such as smart home equipment and smart assistants. Participants with atypical speech, due to a range of conditions such as cerebral palsy, acquired brain injury, Down syndrome, stroke and hearing impairment, were recruited, primarily through organisations supporting disabled people. Most had physical or learning disabilities in addition to dysarthric speech. The project team worked with individuals, their families and local support teams, to provide access to the app, including through additional assistive technologies where needed. Testing was user-led, with participants asked to identify and test use cases most relevant to their daily lives over a period of three months or more. Ongoing technical support and training were provided remotely and in-person throughout the testing period. Structured interviews were used to collect feedback on users' experiences, with delivery adapted to individuals' needs and preferences. Informal feedback was collected through ongoing contact between participants, their families and support teams and the project team. Focus groups were held to collect feedback on specific design proposals. User feedback shared with developers has led to improvements to the user interface and functionality, including faster voice training, simplified navigation, the introduction of gamification elements and of switch access as an alternative to touchscreen access, with other feature requests from users still in development. This work offers a case-study in successful and inclusive co-design with the disabled community.

Keywords: co-design, assistive technology, dysarthria, inclusive speech recognition

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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: Jonghyuk Yoon, Hyoungwoon Song

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Recently, there are lots of increasing interest in a smart farming that represents application of modern Information and Communication Technologies (ICT) into agriculture since it provides a methodology to optimize production efficiencies by managing growing conditions of crops automatically. In order to obtain high performance and stability for smart greenhouse, it is important to identify the effect of various working parameters such as capacity of ventilation fan, vent opening area and etc. In the present study, a 3-dimensional CFD (Computational Fluid Dynamics) simulation for single-span greenhouse was conducted using the commercial program, Ansys CFX 18.0. The numerical simulation for single-span greenhouse was implemented to figure out the internal thermal and flow characteristics. In order to numerically model solar radiation that spread over a wide range of wavelengths, the multiband model that discretizes the spectrum into finite bands of wavelength based on Wien’s law is applied to the simulation. In addition, absorption coefficient of vinyl varied with the wavelength bands is also applied based on Beer-Lambert Law. To validate the numerical method applied herein, the numerical results of the temperature at specific monitoring points were compared with the experimental data. The average error rates (12.2~14.2%) between them was shown and numerical results of temperature distribution are in good agreement with the experimental data. The results of the present study can be useful information for the design of various greenhouses. This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Advanced Production Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA)(315093-03).

Keywords: single-span greenhouse, CFD (computational fluid dynamics), solar radiation, multiband model, absorption coefficient

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Authors: Ali Abbas

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Industrial Engineering is a broad multidisciplinary field with intersections and applications in numerous areas. In out current environment, the path from a phenomenon to value involves numerous people with expertise in various areas including domain knowledge of a field and the ability to make decisions within an operating environment that lead to value creation. We propose some skills that industrial engineering programs should focus on, and argue that an industrial engineer is a decision maker instead of a problem solver.

Keywords: decision analysis, problem-solving, value creation, industrial engineering

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Authors: Antonia Syn

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Politicians’ outlooks on the nature of energy futures and an ‘Energy Transition’ have evolved considerably alongside a steady movement towards renewable energies, buttressed by lower technology costs, rising environmental concerns, and favourable national policy decisions. This paper seeks to examine the degree to which an energy transition has become an incontrovertible ‘status quo’ in parliament, and whether politicians share similar understandings of energy futures or narrate different stories under the same label. Parliamentarians construct different understandings of the same reality, in the form of co-existing and competing discourses, shaping and restricting how policy problems and solutions are understood and tackled. Approaching energy policymaking from a parliamentary discourse perspective draws directly from actors’ concrete statements, offering an alternative to policy literature debates revolving around inductive policy theories. This paper uses computer-assisted discourse analysis to describe fundamental discursive changes in British parliamentary debates around energy futures. By applying correspondence cluster analyses to Hansard transcripts from 1986 to 2010, we empirically measure the policy positions of Labour and Conservative politicians’ parliamentary speeches during legislatively salient moments preceding significant energy transition-related policy decisions. Results show the concept of a technology-based, market-driven transition towards fossil-free and nuclear-free renewables integration converged across Labour and the Conservatives within three decades. Specific storylines underwent significant change, particularly in relation to international outlooks, environmental framings, treatments of risk, and increases in rhetoric. This study contributes to a better understanding of the role politics plays in the energy transition, highlighting how politicians’ values and beliefs inevitably determine and delimit creative policymaking.

Keywords: quantitative discourse analysis, energy transition, renewable energy, British parliament, public policy

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Authors: Sarthak Kumar Jena, Chandra Sekhar Mishra, Prabina Rajib

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Purpose: This paper aims to derive undervaluation signal from the insiders trading of Indian companies where the ownership is complex and concentrated, investors protection is weak, and the insider rules and regulations are not stringent like developed country. This study examines the relationship between insider trading with short term and long term abnormal return. The study also examines the relationship between insider trading and the actual share repurchase by the firm. Methodology: A sample of 78 companies over the period 2008-2013 are analyzed in the study due to not availability of insider data in Indian context. For preliminary analysis T-test and Wilcoxon rank sum test is used to find the difference between the insider trading before and after the share repurchase announcement. Tobit model is used to find out whether insider trading influence shares repurchase decisions or not. Return on the basis of market model and buy hold are calculated in the previous year and the following year of share repurchase announcement. Findings: The paper finds that insider trading around share repurchase is more than control firms and there is positive and significant difference in insider buying between the previous year of share buyback announcement and the following year of buyback announcement. Insider buying before share repurchase announcement has a positive influence on share repurchase decisions. We find insider buying has a positive and significant relationship with announcement return, whereas insider selling has a negative significant relationship with announcement return. Actual share repurchase and program completion also depend on insider trading before share repurchase. Research limitation: The study is constrained by the small sample size, so the results should be viewed by keeping this limitation in mind. Originality: The paper is to our best knowledge the first study based on Indian context to extend the insider trading literature to share repurchase event and examine insider trading to find out undervaluation signal associated with insider buying.

Keywords: insider trading, buyback, open market share repurchase, signalling

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Authors: Amirreza Fazely Hamedani, Muzzamil Aziz, Philipp Wieder, Ramin Yahyapour

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Software-defined networking in recent years came into the sight of so many network designers as a successor to the traditional networking. Unlike traditional networks where control and data planes engage together within a single device in the network infrastructure such as switches and routers, the two planes are kept separated in software-defined networks (SDNs). All critical decisions about packet routing are made on the network controller, and the data level devices forward the packets based on these decisions. This type of network is vulnerable to DDoS attacks, degrading the overall functioning and performance of the network by continuously injecting the fake flows into it. This increases substantial burden on the controller side, and the result ultimately leads to the inaccessibility of the controller and the lack of network service to the legitimate users. Thus, the protection of this novel network architecture against denial of service attacks is essential. In the world of cybersecurity, attacks and new threats emerge every day. It is essential to have tools capable of managing and analyzing all this new information to detect possible attacks in real-time. These tools should provide a comprehensive solution to automatically detect, predict and prevent abnormalities in the network. Big data encompasses a wide range of studies, but it mainly refers to the massive amounts of structured and unstructured data that organizations deal with on a regular basis. On the other hand, it regards not only the volume of the data; but also that how data-driven information can be used to enhance decision-making processes, security, and the overall efficiency of a business. This paper presents an intelligent big data framework as a solution to handle illegitimate traffic burden on the SDN network created by the numerous DDoS attacks. The framework entails an efficient defence and monitoring mechanism against DDoS attacks by employing the state of the art machine learning techniques.

Keywords: apache spark, apache kafka, big data, DDoS attack, machine learning, SDN network

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Authors: Yasamin Rahimi, Ali Kamandi, Abbas Hoseini, Hesam Haddad

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Online/offline chat is a convenient approach in the electronic markets of second-hand products in which potential customers would like to have more information about the products to fill the information gap between buyers and sellers. Online peer in peer market is trying to create artificial intelligence-based systems that help customers ask more informative questions in an easier way. In this article, we introduce a method for the question/answer system that we have developed for the top-ranked electronic market in Iran called Divar. When it comes to secondhand products, incomplete product information in a purchase will result in loss to the buyer. One way to balance buyer and seller information of a product is to help the buyer ask more informative questions when purchasing. Also, the short time to start and achieve the desired result of the conversation was one of our main goals, which was achieved according to A/B tests results. In this paper, we propose and evaluate a method for suggesting questions and answers in the messaging platform of the e-commerce website Divar. Creating such systems is to help users gather knowledge about the product easier and faster, All from the Divar database. We collected a dataset of around 2 million messages in Persian colloquial language, and for each category of product, we gathered 500K messages, of which only 2K were Tagged, and semi-supervised methods were used. In order to publish the proposed model to production, it is required to be fast enough to process 10 million messages daily on CPU processors. In order to reach that speed, in many subtasks, faster and simplistic models are preferred over deep neural models. The proposed method, which requires only a small amount of labeled data, is currently used in Divar production on CPU processors, and 15% of buyers and seller’s messages in conversations is directly chosen from our model output, and more than 27% of buyers have used this model suggestions in at least one daily conversation.

Keywords: smart reply, spell checker, information retrieval, intent detection, question answering

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Authors: António J. Gano, Carmen Rangel

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Currently, electric energy storage systems for stationary applications have known an increasing interest, namely with the integration of local renewable energy power sources into energy communities. Li-ion batteries are considered the leading electric storage devices to achieve this integration, and Battery Management Systems (BMS) are decisive for their control and optimum performance. In this work, the advancement of a smart BMS (sBMS) prototype with a modular distributed topology is described. The system, still under development, has a distributed architecture with modular characteristics to operate with different battery pack topologies and charge capacities, integrating adaptive algorithms for functional state real-time monitoring and management of multicellular Li-ion batteries, and is intended for application in the context of a local energy community fed by renewable energy sources. This sBMS system includes different developed hardware units: (1) Cell monitoring units (CMUs) for interfacing with each individual cell or module monitoring within the battery pack; (2) Battery monitoring and switching unit (BMU) for global battery pack monitoring, thermal control and functional operating state switching; (3) Main management and local control unit (MCU) for local sBMS’s management and control, also serving as a communications gateway to external systems and devices. This architecture is fully expandable to battery packs with a large number of cells, or modules, interconnected in series, as the several units have local data acquisition and processing capabilities, communicating over a standard CAN bus and will be able to operate almost autonomously. The CMU units are intended to be used with Li-ion cells but can be used with other cell chemistries, with output voltages within the 2.5 to 5 V range. The different unit’s characteristics and specifications are described, including the different implemented hardware solutions. The developed hardware supports both passive and active methods for charge equalization, considered fundamental functionalities for optimizing the performance and the useful lifetime of a Li-ion battery package. The functional characteristics of the different units of this sBMS system, including different process variables data acquisition using a flexible set of sensors, can support the development of custom algorithms for estimating the parameters defining the functional states of the battery pack (State-of-Charge, State-of-Health, etc.) as well as different charge equalizing strategies and algorithms. This sBMS system is intended to interface with other systems and devices using standard communication protocols, like those used by the Internet of Things. In the future, this sBMS architecture can evolve to a fully decentralized topology, with all the units using Wi-Fi protocols and integrating a mesh network, making unnecessary the MCU unit. The status of the work in progress is reported, leading to conclusions on the system already executed, considering the implemented hardware solution, not only as fully functional advanced and configurable battery management system but also as a platform for developing custom algorithms and optimizing strategies to achieve better performance of electric energy stationary storage devices.

Keywords: Li-ion battery, smart BMS, stationary electric storage, distributed BMS

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Authors: Preeti Tiwari, Jay Wood, Duncan Babbage

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Family planning plays a role in saving lives across the globe by preventing unwanted pregnancies. The purpose of this multidisciplinary research was to determine the impact of mHealth tools have on psychosocial determinants of behaviour for family planning. The present study examines a topic that is very relevant in times where human-technology interaction is at its peak. It is probably one of the first studies that have investigated the impact of mobile phone technology on the underlying mechanisms of behaviour change for family planning using primary data. To examine the association between exposure to mHealth tools and predictors of behaviour, data was collected from mHealth intervention areas in India. A post-intervention quasi-experimental study with a 2x2 factorial design was conducted among 831 men and women from the state of Bihar. The quantitative data analysis evaluated the extent of influence that predictors of behaviour (beliefs, social norms, perceived behaviour control, and outcome behaviour) have on a woman’s decisions about family planning. The results indicated an association between exposure to mHealth tools and improved communication about family planning among various family members after receiving health information from a health worker (H1). A relationship between exposure to mHealth tools and increased support women received from their husbands and extended family (mothers-in-law specifically) and peers (H2) was also found. A further result showed that knowledge about family planning was greater among users of family planning (H4). mHealth tools empower women to communicate with family members. This has important implications for developing mobile phone-based tools, as they can be used as a crucial communication channel that can be an effective method of increasing communication among family members about contraceptives. Thus, it can be implied that where women feel nervous talking about contraception, the successful application of mHealth tools can strengthen the interactivity of the health communication and could increase the likelihood of using contraception. However, while it may improve health communication that can inform health decisions, it may be insufficient on its own to cause behaviour change.

Keywords: contraceptive, e-health, psycho-social, women

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Authors: Mikel Alonso López

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In order to begin the process of studying the task of making consumer decisions, the main decision models must be analyzed. The objective of this task is to see if there is a presence of emotions in those models, and analyze how authors that have created them consider their impact in consumer choices. In this paper, the most important models of consumer behavior are analysed. This review is useful to consider an unproblematic background knowledge in the literature. The order that has been established for this study is chronological.

Keywords: consumer behaviour, emotions, decision making, consumer psychology

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Authors: M. Miljkovic, A. Urakpo, M. Simic-Koumoutsaris

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Benefit-risk assessment (BRA) is a valuable tool that takes place in multiple stages during a medicine's lifecycle, and this assessment can be conducted in a variety of ways. The aim was to summarize current BRA methods used during approval decisions and in post-approval settings and to see possible future directions. Relevant reviews, recommendations, and guidelines published in medical literature and through regulatory agencies over the past five years have been examined. BRA implies the review of two dimensions: the dimension of benefits (determined mainly by the therapeutic efficacy) and the dimension of risks (comprises the safety profile of a drug). Regulators, industry, and academia have developed various approaches, ranging from descriptive textual (qualitative) to decision-analytic (quantitative) models, to facilitate the BRA of medicines during the product lifecycle (from Phase I trials, to authorization procedure, post-marketing surveillance and health technology assessment for inclusion in public formularies). These approaches can be classified into the following categories: stepwise structured approaches (frameworks); measures for benefits and risks that are usually endpoint specific (metrics), simulation techniques and meta-analysis (estimation techniques), and utility survey techniques to elicit stakeholders’ preferences (utilities). All these approaches share the following two common goals: to assist this analysis and to improve the communication of decisions, but each is subject to its own specific strengths and limitations. Before using any method, its utility, complexity, the extent to which it is established, and the ease of results interpretation should be considered. Despite widespread and long-time use, BRA is subject to debate, suffers from a number of limitations, and currently is still under development. The use of formal, systematic structured approaches to BRA for regulatory decision-making and quantitative methods to support BRA during the product lifecycle is a standard practice in medicine that is subject to continuous improvement and modernization, not only in methodology but also in cooperation between organizations.

Keywords: benefit-risk assessment, benefit-risk profile, product lifecycle, quantitative methods, structured approaches

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Authors: Shuyi Xie

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As the vital city in south China since the ancient time, Guangzhou has been losing its leading role among the rising neighboring cities, especially, Hong Kong and Shenzhen, since the late 1980s, with the overloaded infrastructure and deteriorating urban environment in its old inner city. Fortunately, with the new expansion of its administrative area in 2000, the local municipality considered it as a great opportunity to solve a series of alarming urban problems. Thus, for the first time, strategic planning was introduced to China for providing more convincing and scientific basis towards better urban future. Differed from traditional Chinese planning practices, which rigidly and dogmatically focused on future blueprints, the strategic planning of Guangzhou proceeded from analyzing practical challenges and opportunities towards establishing reasonable developing objectives and proposing corresponding strategies. Moreover, it was pioneering that the municipality invited five planning institutions for proposals, among which, the paper focuses on the one proposed by China Academy of Urban Planning & Design from its theoretical basis to problems’ defining and analyzing the process, as well as planning results. Since it was closer to the following municipal decisions and had a more far-reaching influence for other Chinese cities' following practices. In particular, it demonstrated an innovative exploration on the role played by urban developing rate on deciding urban growth patterns (‘Spillover-reverberation’ or ‘Leapfrog’). That ultimately established an unprecedented paradigm on deciding an appropriate urban spatial structure in future, including its specific location, function and scale. Besides the proposal itself, this article highlights the role of interactions, among actors, as well as proposals, subsequent discussions, summaries and municipal decisions, especially the establishment of the rolling dynamic evaluation system for periodical reviews on implementation situations, as the first attempt in China. Undoubtedly, strategic planning of Guangzhou has brought out considerable benefits, especially opening the strategic mind for plentiful Chinese cities in the following years through establishing a flexible and dynamic planning mechanism highlighted the interactions among multiple actors with innovative and effective tools, methodologies and perspectives on regional, objective-approach and comparative analysis. However, compared with some developed countries, the strategic planning in China just started and has been greatly relied on empirical studies rather than scientific analysis. Moreover, it still faced a bit of controversy, for instance, the certain gap among institutional proposals, final municipal decisions and implemented results, due to the lacking legal constraint. Also, how to improve the public involvement in China with an absolute up-down administrative system is another urgent task. In future, despite of irresistible and irretrievable weakness, some experiences and lessons from previous international practices, with the combination of specific Chinese situations and domestic practices, would enable to promote the further advance on strategic planning in China.

Keywords: evaluation system, global perspective, Guangzhou, interactions, strategic planning, urban growth patterns

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Authors: Mehdi Naserian, Mohammad Jooshaki, Mahmud Fotuhi-Firuzabad, Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee

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In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: communication infrastructure, smart meters, power systems, HVAC system, residential HVAC systems

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Authors: Yanting Cao, Kazumitsu Nawata

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As smartphones upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described as more refined, complex, and detailed. In this context, we analyzed a set of experimental data obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model becomes extremely challenging. After a series of feature selection and parameters adjustment, a well-performed SVM classifier has been trained.

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: Frederico Fialho Teixeira, Islam Mashaly, Maryam Shafiei, Jurij Karlovsek

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The ubiquity of data gathering and smart technologies, advancements in virtual technologies, and the development of the internet of things (IoT) have created urgent demands for the development of frameworks and efficient workflows for data collection, visualisation, and analysis. Digital twin, in different scales of the city into the building, allows for bringing together data from different sources to generate fundamental and illuminating insights for the management of current facilities and the lifecycle of amenities as well as improvement of the performance of current and future designs. Over the past two decades, there has been growing interest in the topic of digital twin and their applications in city and building scales. Most such studies look at the urban environment through a homogeneous or generalist lens and lack specificity in particular characteristics or identities, which define an urban university campus. Bridging this knowledge gap, this paper offers a framework for developing a digital twin for a university campus that, with some modifications, could provide insights for any large-scale digital twin settings like towns and cities. It showcases how currently unused data could be purposefully combined, interpolated and visualised for producing analysis-ready data (such as flood or energy simulations or functional and occupancy maps), highlighting the potential applications of such a framework for campus planning and policymaking. The research integrates campus-level data layers into one spatial information repository and casts light on critical data clusters for the digital twin at the campus level. The paper also seeks to raise insightful and directive questions on how digital twin for campus can be extrapolated to city-scale digital twin. The outcomes of the paper, thus, inform future projects for the development of large-scale digital twin as well as urban and architectural researchers on potential applications of digital twin in future design, management, and sustainable planning, to predict problems, calculate risks, decrease management costs, and improve performance.

Keywords: digital twin, smart campus, framework, data collection, point cloud

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Authors: Semire Yekta

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Many online retailers set up manual review teams to overcome the limitations of automated online fraud detection systems. This study critically examines the strategies they adapt in their decision-making process to set apart fraudulent individuals from non-fraudulent online shoppers. The study uses a mix method research approach. 32 in-depth interviews have been conducted alongside with participant observation and auto-ethnography. The study found out that all steps of the decision-making process are significantly affected by a level of subjectivity, personal understandings of online fraud, preferences and judgments and not necessarily by objectively identifiable facts. Rather clearly knowing who the fraudulent individuals are, the team members have to predict whether they think the customer might be a fraudster. Common strategies used are relying on the classification and fraud scorings in the automated fraud detection systems, weighing up arguments for and against the customer and making a decision, using cancellation to test customers’ reaction and making use of personal experiences and “the sixth sense”. The interaction in the team also plays a significant role given that some decisions turn into a group discussion. While customer data represent the basis for the decision-making, fraud management teams frequently make use of Google search and Google Maps to find out additional information about the customer and verify whether the customer is the person they claim to be. While this, on the one hand, raises ethical concerns, on the other hand, Google Street View on the address and area of the customer puts customers living in less privileged housing and areas at a higher risk of being classified as fraudsters. Phone validation is used as a final measurement to make decisions for or against the customer when previous strategies and Google Search do not suffice. However, phone validation is also characterized by individuals’ subjectivity, personal views and judgment on customer’s reaction on the phone that results in a final classification as genuine or fraudulent.

Keywords: online fraud, data mining, manual review, social construction

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Authors: Shatakshi Garg

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As the world continues to grapple with the COVID-19 pandemic, India, one of the most populous democratic federal developing nation, continues to report the highest active cases and deaths, as well as struggle to let its health infrastructure not succumb to the exponentially growing requirements of hospital beds, ventilators, oxygen to save thousands of lives daily at risk. In this context, the paper outlines the handling of the COVID-19 pandemic since it first hit India in January 2020 – the policy decisions taken by the Union and the State governments from the larger perspective of its federal structure. The Constitution of India adopted in 1950 enshrined the federal relations between the Union and the State governments by way of the constitutional division of revenue-raising and expenditure responsibilities. By way of the 72nd and 73rd Amendments in the Constitution, powers and functions were devolved further to the third tier, namely the local governments, with the intention of further strengthening the federal structure of the country. However, with time, several constitutional amendments have shifted the scales in favour of the union government. The paper briefly traces some of these major amendments as well as some policy decisions which made the federal relations asymmetrical. As a result, data on key fiscal parameters helps establish how the union government gained upper hand at the expense of weak state governments, reducing the local governments to mere constitutional bodies without adequate funds and fiscal autonomy to carry out the assigned functions. This quasi-federal structure of India with the union government amassing the majority of power in terms of ‘funds, functions and functionaries’ exposed the perils of weakening sub-national governments post COVID-19 pandemic. With a complex quasi-federal structure and a heterogeneous population of over 1.3 billion, the announcement of a sudden nationwide lockdown by the union government was followed by a plight of migrants struggling to reach homes safely in the absence of adequate arrangements for travel and safety-net made by the union government. With limited autonomy enjoyed by the states, they were mostly dictated by the union government on most aspects of handling the pandemic, including protocols for lockdown, re-opening post lockdown, and vaccination drive. The paper suggests that certain policy decisions like demonetization, the introduction of GST, etc., taken by the incumbent government since 2014 when they first came to power, have further weakened the states and local governments, which have amounted to catastrophic losses, both economic and human. The role of the executive, legislature and judiciary are explored to establish how all these three arms of the government have worked simultaneously to further weaken and expose the fault-lines of the federal structure of India, which has lent the nation incapacitated to handle this pandemic. The paper then suggests the urgency of re-looking at the federal structure of the country and undertaking measures that strengthen the sub-national governments and restore the federal spirit as was enshrined in the constitution to avoid mammoth human and economic losses from a pandemic of this sort.

Keywords: COVID-19 pandemic, India, federal structure, economic losses

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Authors: J. A. López, J. E. Olguín, C. W. Camargo, G. A. Quijano, R. Martínez

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This paper presents an anthropometric study conducted to 300 employees in a maquiladora industry that belongs to the cluster of medical products as part of a research project to pretend simulate workplace conditions under which operators conduct their activities. This project is relevant because traditionally performed a study to design ergonomic workspaces according to anthropometric profile of users, however, this paper demonstrates the importance of making decisions when the infrastructure cannot be adapted for economic whichever put emphasis on user activity.

Keywords: anthropometry, biomechanics, design, ergonomics, productivity

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Authors: Hande Sezgin, Senem Kursun Bahadır, Yakup Erhan Boke, Fatma Kalaoğlu

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Electronic textiles (e-textiles) are fabrics that contain electronics and interconnections with them. In this study, two types of base yarns (cotton and acrylic) and three conductive steel yarns with different linear resistance values (14Ω/m, 30Ω/m, 70Ω/m) were used to investigate the effect of base yarn type and linear resistance of conductive yarns on thermal behavior of e-textile structures. Thermal behavior of samples were examined by thermal camera.

Keywords: conductive yarn, e-textiles, smart textiles, thermal analysis

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Authors: Braden M. Li, Inhwan Kim, Jesse S. Jur

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One of the fundamental challenges in the electronic textile (e-textile) industry is the mismatch in compliance between the rigid electronic components integrated onto soft textile platforms. To address these problems, various printing technologies using conductive inks have been explored in an effort to improve the electromechanical performance without sacrificing the innate properties of the printed textile. However, current printing methods deposit densely layered coatings onto textile surfaces with low through-plane wetting resulting in poor electromechanical properties. This work presents an inkjet printing technique in conjunction with unique Kirigami cut designs to address these issues for printed smart textiles. By utilizing particle free reactive silver inks, our inkjet process produces conformal and micron thick silver coatings that surround individual fibers of the printed smart textile. This results in a highly conductive (0.63 Ω sq-1) printed e-textile while also maintaining the innate properties of the textile material including stretchability, flexibility, breathability and fabric hand. Kirigami is the Japanese art of paper cutting. By utilizing periodic cut designs, Kirigami imparts enhanced flexibility and delocalization of stress concentrations. Kirigami cut design parameters (i.e., cut spacing and length) were correlated to both the mechanical and electromechanical properties of the printed textiles. We demonstrate that designs using a higher cut-out ratio exponentially softens the textile substrate. Thus, our designs achieve a 30x improvement in the overall stretchability, 1000x decrease in elastic modulus, and minimal resistance change over strain regimes of 100-200% when compared to uncut designs. We also show minimal resistance change of our Kirigami inspired printed devices after being stretched to 100% for 1000 cycles. Lastly, we demonstrate a Kirigami-inspired electrocardiogram (ECG) monitoring system that improves stretchability without sacrificing signal acquisition performance. Overall this study suggests fundamental parameters affecting the performance of e-textiles and their scalability in the wearable technology industry

Keywords: kirigami, inkjet printing, flexible electronics, reactive silver ink

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Authors: Hasna Elalaoui Elabdallaoui, Abdelaziz Elfazziki, Mohamed Sadgal

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Outlines: The social economy is a moral approach to solidarity applied to the projects’ development. To reconcile economic activity and social equity, crowdfunding is as an alternative means of financing social projects. Several collaborative blockchain platforms exist. It eliminates the need for a central authority or an inconsiderate middleman. Also, the costs for a successful crowdfunding campaign are reduced, since there is no commission to be paid to the intermediary. It improves the transparency of record keeping and delegates authority to authorities who may be prone to corruption. Objectives: The objectives are: to define a software infrastructure for projects’ participatory financing within a social and solidarity economy, allowing transparent, secure, and fair management and to have a financial mechanism that improves financial inclusion. Methodology: The proposed methodology is: crowdfunding platforms literature review, financing mechanisms literature review, requirements analysis and project definition, a business plan, Platform development process and implementation technology, and testing an MVP. Contributions: The solution consists of proposing a new approach to crowdfunding based on Islamic financing, which is the principle of Mousharaka inspired by Islamic financing, which presents a financial innovation that integrates ethics and the social dimension into contemporary banking practices. Conclusion: Crowdfunding platforms need to secure projects and allow only quality projects but also offer a wide range of options to funders. Thus, a framework based on blockchain technology and Islamic financing is proposed to manage this arbitration between quality and quantity of options. The proposed financing system, "Musharaka", is a mode of financing that prohibits interests and uncertainties. The implementation is offered on the secure Ethereum platform as investors sign and initiate transactions for contributions using their digital signature wallet managed by a cryptography algorithm and smart contracts. Our proposal is illustrated by a crop irrigation project in the Marrakech region.

Keywords: social economy, Musharaka, blockchain, smart contract, crowdfunding

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Authors: Iva Buchberger, Vesna Kovač

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Global education policy trends and recommendations underline the importance of (distributive) school leadership as a school effectiveness key factor. In this context, the broader aim of this research (supported by the Croatian Science Foundation) is to identify school leadership characteristics in Croatian schools and to examine the correlation between school leadership and school effectiveness. The aim of the proposed conference paper is to focus on the school leadership characteristics which are additionally explained with school leadership facilitators that contribute to (distributive) school leadership development. The aforementioned school leadership characteristics include the following dimensions: (a) participation in the process of making different types of decisions, (b) influence in the decision making process, (c) social interactions between different stakeholders in the decision making process in schools. Further, the school leadership facilitators are categorized as follows: (a) principal’s activities (such as providing support to different stakeholders and developing mutual trust among them), (b) stakeholders’ characteristics (such as developed stakeholders’ interest and competence to participate in decision-making process), (c) organizational and material resources (such as school material conditions, the necessary information and time as resources for making decisions). The data were collected by a constructed and validated questionnaire for examining the school leadership characteristics and facilitators from teachers’ perspective. The main population in this study consists of all primary schools in Croatia while the sample is comprised of 100 primary schools, selected by random sampling. Furthermore, the sample of teachers was selected by an additional procedure taking into consideration the independent variables of sex, work experience, etc. Data processing was performed by standard statistical methods of descriptive and inferential statistics. Statistical program IBM SPSS 20.0 was used for data processing. The results of this study show that there is a (positive) correlation between school leadership characteristics and school leadership facilitators. Specifically, it is noteworthy to mention that all the dimensions of school leadership characteristics are in positive correlation with the categories of school leadership facilitators. These results are indicative for the education policy creators who should ensure positive and supportive environment for the school leadership development including the development of school leadership characteristics and school leadership facilitators.

Keywords: distributive school leadership, school effectiveness , school leadership characteristics, school leadership facilitators

Procedia PDF Downloads 247