Search results for: network resources

Authors: Ted Gournelos

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Marketing approaches in practice and academic literature usually foreground the importance of product and brand awareness in strategy. Decisions emphasize justifications and promotions of existing projects, which has the unintended consequence of pushing marketing, public relations, and other communications to secondary strategies and tactics rather than as inherent pieces of organizational development. In other words, marketers implement what others have already decided. This is a challenge not only for the communications field, but also for the organizations themselves, since integrated communications employees are often the primary, if not the only, touchpoints for client/customer/user research and interaction. Organizations thus become increasingly out of touch, raising the risk of public or human resources crisis and decreasing the focus on opportunities for development and growth. This paper will discuss the potential for social entrepreneurship to refocus marketing and communications professionals on primary strategy, and suggest best practices for developing initiatives not only to impact marketing efforts themselves, but also the guiding organizational approaches to project management, human resources, corporate social responsibility, and research. It will provide a comparative analysis of social media marketing efforts conducted by food security non-governmental organizations from several countries, pointing out both flaws and areas of opportunity for integration with for-profit organizational strategy, and discuss the implications of descriptive, proactive, and interactive messaging.

Keywords: social enterprise, strategy, innovation, social media

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Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

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In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange

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Authors: Xiping Wang，Shuran Yao, Liqin Dai

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Many studies report the winter is getting warmer and the minimum air temperature is obviously rising as the important climate warming evidences. The exacerbated air temperature fluctuation tending to bring more severe weather variation is another important consequence of recent climate change which induced more disasters to crop growth in quite a certain regions. Hebei Province is an important winter wheat growing province in North of China that recently endures more winter freezing injury influencing the local winter wheat crop management. A winter wheat freezing injury assessment Bayesian Network framework was established for the objectives of estimating, assessing and predicting winter wheat freezing disasters in Hebei Province. In this framework, the freezing disasters was classified as three severity degrees (SI) among all the three types of freezing, i.e., freezing caused by severe cold in anytime in the winter, long extremely cold duration in the winter and freeze-after-thaw in early season after winter. The factors influencing winter wheat freezing SI include time of freezing occurrence, growth status of seedlings, soil moisture, winter wheat variety, the longitude of target region and, the most variable climate factors. The climate factors included in this framework are daily mean and range of air temperature, extreme minimum temperature and number of days during a severe cold weather process, the number of days with the temperature lower than the critical temperature values, accumulated negative temperature in a potential freezing event. The Bayesian Network model was evaluated using actual weather data and crop records at selected sites in Hebei Province using real data. With the multi-stage influences from the various factors, the forecast and assessment of the event-based target variables, freezing injury occurrence and its damage to winter wheat production, were shown better scoped by Bayesian Network model.

Keywords: bayesian networks, climatic change, freezing Injury, winter wheat

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Authors: T. Lydon, A. McNabola, P. Coughlan

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Energy consumption in the water distribution network (WDN) is a well established problem equating to the industry contributing heavily to carbon emissions, with 0.9 kg CO2 emitted per m3 of water supplied. It is indicated that 85% of energy wasted in the WDN can be recovered by installing turbines. Existing potential in networks is present at small capacity sites (5-10 kW), numerous and dispersed across networks. However, traditional turbine technology cannot be scaled down to this size in an economically viable fashion, thus alternative approaches are needed. This research aims to enable energy recovery potential within the WDN by exploring the potential of pumps-as-turbines (PATs), to realise this potential. PATs are estimated to be ten times cheaper than traditional micro-hydro turbines, presenting potential to contribute to an economically viable solution. However, a number of technical constraints currently prohibit their widespread use, including the inability of a PAT to control pressure, difficulty in the selection of PATs due to lack of performance data and a lack of understanding on how PATs can cater for fluctuations as extreme as +/- 50% of the average daily flow, characteristic of the WDN. A PAT prototype is undergoing testing in order to identify the capabilities of the technology. Results of preliminary testing, which involved testing the efficiency and power potential of the PAT for varying flow and pressure conditions, in order to develop characteristic and efficiency curves for the PAT and a baseline understanding of the technologies capabilities, are presented here: •The limitations of existing selection methods which convert BEP from pump operation to BEP in turbine operation was highlighted by the failure of such methods to reflect the conditions of maximum efficiency of the PAT. A generalised selection method for the WDN may need to be informed by an understanding of impact of flow variations and pressure control on system power potential capital cost, maintenance costs, payback period. •A clear relationship between flow and efficiency rate of the PAT has been established. The rate of efficiency reductions for flows +/- 50% BEP is significant and more extreme for deviations in flow above the BEP than below, but not dissimilar to the reaction of efficiency of other turbines. •PAT alone is not sufficient to regulate pressure, yet the relationship of pressure across the PAT is foundational in exploring ways which PAT energy recovery systems can maintain required pressure level within the WDN. Efficiencies of systems of PAT energy recovery systems operating conditions of pressure regulation, which have been conceptualise in current literature, need to be established. Initial results guide the focus of forthcoming testing and exploration of PAT technology towards how PATs can form part of an efficiency energy recovery system.

Keywords: energy recovery, pump-as-turbine, water distribution network, water distribution network

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Authors: Shawna M. Margesson

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This research study seeks to explore the lived experience of peer support workers (PSWs) in a peer-led non-governmental organization in Denver, Colorado, USA. The Colorado Mental Wellness Network offers supportive wellness recovery services such as wellness recovery action plans (WRAP), advocacy trainings for anti-stigma campaigns, and PSWs to work with and for consumers in the community. This study suggests that a peer-run environment is a unique community setting for PSWs to work given all employees are living in mental wellness recovery. Little has been documented about PSWs' personal accounts of working within a recovery-oriented organization and their first-person accounts to working with consumers. The importance of this study is to provide an ethnographic account of both subjects; the lived experiences of PSWs of both organizational and consumer-driven recovery. This study seeks to add to the literature and the social work profession the personal accounts of PSWs as they provide services to others like themselves. It also will provide an additional lens to view the peer-driven movement in mental health and wellness recovery.

Keywords: peer to peer movement, mental health, ethnography, peer support workers

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Authors: Haoyang Liang, Dandong Ge

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With the rapid development of Chinese cities, traffic congestion has become more and more serious. At the same time, there are many closed old residential area in Chinese cities, which seriously affect the connectivity of urban roads and reduce the density of urban road networks. After reopening the restricted old residential area, the internal roads in the original residential area were transformed into urban roads, which was of great help to alleviate traffic congestion. This paper uses the spatial syntactic theory to analyze the urban road network and compares the roads with the integration and connectivity degree to evaluate whether the opening of the roads in the residential areas can improve the urban traffic. Based on the road network system within the first loop road in Kunming, the Space Syntax evaluation model is established for status analysis. And comparative analysis method will be used to compare the change of the model before and after the road openness of the old urban residential district within the first-ring road in Kunming. Then it will pick out the areas which indicate a significant difference for the small dimensions model analysis. According to the analyzed results and traffic situation, the evaluation of road openness in the old urban residential district will be proposed to improve the urban residential districts.

Keywords: Space Syntax, Kunming, urban renovation, traffic jam

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Authors: Atom Mkhitaryan, Astghik Avetisyan

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We analyze the developments of doctoral education in Armenia since 1990 and the management process. Education and training of highly qualified personnel are increasingly seen as a fundamental platform that ensures the development of the state. Reforming the national institute for doctoral studies (aspirantura) is aimed at improving the quality of human resources in science, optimizing research topics in accordance with the priority areas of development of science and technology, increasing publication and innovative activities, bringing national science and research closer to the world level and achieving international recognition. We present a number of defended dissertations in Armenia during the last 30 years, the dynamics and the main trends of the development of the academic degree awarding system. We discuss the possible impact of reforming the system of training and certification of highly qualified personnel on the organization of third–level doctoral education (doctoral schools) and specialized / dissertation councils in Armenia. The results of the SWOT analysis of doctoral education and academic degree awarding processes in Armenia are shown. The article presents the main activities and projects aimed at using the advantages and strong points of the National Academy network in order to improve the quality of doctoral education and training. The paper explores the mechanisms of organizational, methodological and infrastructural support for research and innovation activities of doctoral students and young scientists. There are also suggested approaches to the organization of strong networking between research institutes and foreign universities for training and certification of highly qualified personnel. The authors define the role of ISEC in the management of doctoral studies and the establishment of a competitive third-level education for the sphere of research and development in Armenia.

Keywords: doctoral studies, academic degree, PhD, certification, highly qualified personnel, dissertation, research and development, innovation, networking, management of doctoral school

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Authors: Samuel Nii Tackie, Oyebade K. Oyedotun, Ebenezer O. Olaniyi, Adnan Khashman

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Artificial neural networks have been used in different fields of artificial intelligence, and more specifically in machine learning. Although, other machine learning options are feasible in most situations, but the ease with which neural networks lend themselves to different problems which include pattern recognition, image compression, classification, computer vision, regression etc. has earned it a remarkable place in the machine learning field. This research exploits neural networks as a data mining tool in predicting the number of times a student repeats a course, considering some attributes relating to the course itself, the teacher, and the particular student. Neural networks were used in this work to map the relationship between some attributes related to students’ course assessment and the number of times a student will possibly repeat a course before he passes. It is the hope that the possibility to predict students’ performance from such complex relationships can help facilitate the fine-tuning of academic systems and policies implemented in learning environments. To validate the power of neural networks in data mining, Turkish students’ performance database has been used; feedforward and radial basis function networks were trained for this task; and the performances obtained from these networks evaluated in consideration of achieved recognition rates and training time.

Keywords: artificial neural network, data mining, classification, students’ evaluation

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Authors: Endalew Jibat, Feyera Senbeta, Tesfaye Zeleke, Fitsum Hagos

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Institutions can play a key role in coordinating how natural resources are effectively used without over-exploitation. Institutions are the laws, policies, and organizational arrangements that permit, forbid or regulate human action. The aim of this study was to look into the roles of formal and informal institutions, as well as their interactions, in water resource governance in Ethiopia's Central Rift Valley (CRV), where water scarcity is a concern. Key informant interviews, group discussions, in depth-interview, and secondary data sources were used to generate relevant data. The study revealed that formal and informal institutions were involved in water resource governance in the study area. However, the influence of informal institutions on formal institutions or vice versa is trivial to change the action of water users. Lack of clear roles and responsibilities of actors, weak capacity and lack of meaningful decentralization and participation of key actors in policy development, lack of synergy and incongruence between formal and informal institutions, and absence of enforcement mechanisms including incentives are attributed to inefficient use of water resources in the CRV. Enhancing the interplay of formal and informal institutions in the water resource policy development and meaningful decentralization and key stakeholders' engagement is recommended for sustainable water use.

Keywords: institutions, governance, institutional interplay, water users

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Authors: Luís Pina

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The conservation of marine biodiversity keeps ecosystems in balance and ensures the sustainable use of resources. In this context, technological resources have been used for monitoring marine species to allow biologists to obtain data in real-time. There are different mobile applications developed for data collection for monitoring purposes, but these systems are designed to be utilized only on third-generation (3G) phones or smartphones with Internet access and in rural parts of the developing countries, Internet services and smartphones are scarce. Thus, the objective of this work is to develop a system to monitor marine turtles using Unstructured Supplementary Service Data (USSD), which users can access through basic mobile phones. The system aims to improve the data collection mechanism and enhance the effectiveness of current systems in monitoring sea turtles using any type of mobile device without Internet access. The system will be able to report information related to the biological activities of marine turtles. Also, it will be used as a platform to assist marine conservation entities to receive reports of illegal sales of sea turtles. The system can also be utilized as an educational tool for communities, providing knowledge and allowing the inclusion of communities in the process of monitoring marine turtles. Therefore, this work may contribute with information to decision-making and implementation of contingency plans for marine conservation programs.

Keywords: GSM, marine biology, marine turtles, unstructured supplementary service data (USSD)

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Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

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Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

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Authors: Esra Ece Var

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Beekeeping plays essential role both in terms of agricultural yields and agricultural economy; they produce honey, wax, royal jelly, apitoxin, pollen, and propolis. Nowadays, these natural products become more importantly suitable and preferable for nutrition, food supplement, medicine, and industry. However, to produce organic honey, majority of the apiaries are located in remote or distant rural areas where utilities such as electricity and Internet network are not available. Additionally, due to colony failures, world honey production decreases year by year despite the increase in the number of beehives. The objective of this paper is to develop a smart beehive monitoring system for apiaries including those that do not have access to Internet network. In this context, temperature and humidity inside the beehive, and ambient temperature were measured with RFID sensors. Control center, where all sensor data was sent and stored at, has a GSM module used to warn the beekeeper via SMS when an anomaly is detected. Simultaneously, using the collected data, an unsupervised machine learning algorithm is used for detecting anomalies and calibrating the warning system. The results show that the smart beehive monitoring system can detect fatal anomalies up to 4 weeks prior to colony loss.

Keywords: beekeeping, smart systems, machine learning, anomaly detection, apiculture

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Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

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The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

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Authors: Jyotismita Talukdar

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In this paper, a study has been made on the possibility and accuracy of early prediction of several Heart Disease using Artificial Neural Network. (ANN). The study has been made in both noise free environment and noisy environment. The data collected for this analysis are from five Hospitals. Around 1500 heart patient’s data has been collected and studied. The data is analysed and the results have been compared with the Doctor’s diagnosis. It is found that, in noise free environment, the accuracy varies from 74% to 92%and in noisy environment (2dB), the results of accuracy varies from 62% to 82%. In the present study, four basic attributes considered are Blood Pressure (BP), Fasting Blood Sugar (FBS), Thalach (THAL) and Cholesterol (CHOL.). It has been found that highest accuracy(93%), has been achieved in case of PPI( Post-Permanent-Pacemaker Implementation ), around 79% in case of CAD(Coronary Artery disease), 87% in DCM (Dilated Cardiomyopathy), 89% in case of RHD&MS(Rheumatic heart disease with Mitral Stenosis), 75 % in case of RBBB +LAFB (Right Bundle Branch Block + Left Anterior Fascicular Block), 72% for CHB(Complete Heart Block) etc. The lowest accuracy has been obtained in case of ICMP (Ischemic Cardiomyopathy), about 38% and AF( Atrial Fibrillation), about 60 to 62%.

Keywords: coronary heart disease, chronic stable angina, sick sinus syndrome, cardiovascular disease, cholesterol, Thalach

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Authors: K. Durairaj, I. N. Umar

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The asynchronous discussion forum is one of the most widely used activities in learning management system environment. Online forum allows participants to interact, construct knowledge, and can be used to complement face to face sessions in blended learning courses. However, to what extent do the students perceive the benefits or advantages of forum remain to be seen. Through content and social network analyses, instructors will be able to gauge the students’ engagement and knowledge construction level. Thus, this study aims to analyze the students’ level of knowledge construction and their participation level that occur through online discussion. It also attempts to investigate the relationship between the level of knowledge construction and their social interaction patterns. The sample involves 23 students undertaking a master course in one public university in Malaysia. The asynchronous discussion forum was conducted for three weeks as part of the course requirement. The finding indicates that the level of knowledge construction is quite low. Also, the density value of 0.11 indicating that the overall communication among the participants in the forum is low. This study reveals that strong and significant correlations between SNA measures (in-degree centrality, out-degree centrality) and level of knowledge construction. Thus, allocating these active students in a different groups aids the interactive discussion takes place. Finally, based upon the findings, some recommendations to increase students’ level of knowledge construction and also for further research are proposed.

Keywords: asynchronous discussion forums, content analysis, knowledge construction, social network analysis

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Authors: Michela C. Batista Matos, Madelaine Venzon, Elem F. Martins, Erickson C. Freitas, Adenir V. Teodoro, Maira C. M. Fonseca, Angelo Pallini

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Aromatic plant species are capable of producing and releasing volatile organic compounds spontaneously, which can repel or attract beneficial insects such as generalist predators of herbivores. Attractive plants could be used as crop companion plants to promote biological control of pests. In order to select such plants for future use in horticulture fields, we assessed the attractiveness of the aromatic plants Ocimum basilicum L. (basil), Mentha piperita L. (peppermint), Melissa officinalis L. (lemon balm) and Cordia verbenacea DC (black sage) to adults of the generalist lacewing predator Ceraeochrysa cubana Hagen (Neuroptera: Chrysopidae). This predator is commonly found in agroecosystems in Brazil and it feeds on aphids, mites, small caterpillars, insect eggs and scales. We further tested the effect of these plant species on the survival, development and oviposition of C. cubana. Finally, we evaluated the survival of larvae and adults of C. cubana when only flowers of basil were offered. Females of C. cubana were attracted to basil but not to the remaining aromatic plants. Larvae survival was higher when individuals had access only to basil leaf than when they had access to peppermint, lemon balm, black sage or water. Adult survival on leaf treatments and on water was no longer than three days. Flowers of basil enhanced predator larvae survival, yet they did not reach adulthood. Adults fed on basil flowers lived longer compared with water, but they did not reproduce. Basil is a promising aromatic plant species to be considered for conservation biological control programs. Besides being attractive to adults of the generalist predator, it benefits larvae and adults by providing nutritional resources when prey or other resources are absent. Financial support: CNPq, FAPEMIG and CAPES (Brazil).

Keywords: basil, chrysopidae, conservation biological control, companion plants

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Authors: Dina Ahmed Alkhodary

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Human Resources are the individual skills, knowledge, attitude, capabilities and experience collected to produce wealth to the company. Human Resource disclosure is the process of involving, reporting, and sharing the Investments made in the Human Resources of an Organization that such as organizations short goals and objectives, employees creation value, training and development plan are presently not accounted for in the conventional accounting practices which is importance nowadays to reduce the employee`s turnover. For the purpose of the study 3 telecommunications companies in Jordan have been selected. Telecommunication industry has been chosen for this study since it is a successful sector in Jordan and Human resource disclosure practices were adopted in all the selected companies and companies was aware to the HR practices. The objective of the study is to find out the HR disclosures practices of the telecommunication Companies in Jordan and to find the relationship between the HR Disclosures practices and employees’ turnover which has been measured by leaver proficiencies, remaining member proficiencies and the new comers proficiencies. The researcher has used the questioner to collect data for the research purpose. Results reveal that There are human resource disclosure practices in telecommunication companies in Jordan but in some areas only and has found There that there is a significant relationship between the human resource disclosure practices of the telecommunication companies in Jordan and Employees turnover. It is important to the companies to disclose more information and it’s important to the researchers to study the HR disclosure in the other industries in Jordan to increase the awareness about it.

Keywords: HR, disclosure, employee, turnover

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Authors: K. W. A. M. Kokila, Matsui Kenichi

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Sri Lanka’s disaster management policy aims to protect lives and developments in disaster affected areas by effectively using resources for disaster risk reduction, emergency management, and community awareness. However, funding for these action programs has posed a serious challenge to the country’s economy. This paper examines the extent to which private-public partnerships (PPPs) can facilitate and expedite disaster management works. In particular, it discusses the results of the questionnaire survey among policymakers, government administrators, NGOs, and private businesses. This questionnaire was conducted in 2017. All respondents were selected based on their experience in PPP projects in the past. The survey focused on clarifying the effectiveness of past PPP projects as well as their efficiency and transparency. The respondents also provided their own opinions and suggestions to improve the future PPP projects in Sri Lanka. The questionnaire was distributed to fifteen persons. The results show that almost all respondents think that PPP projects are beneficial and important for future disaster risk management in Sri Lanka. The respondents, however, showed some reservation about effectiveness and transparency of the PPP process. This paper also discusses the results on the respondents’ perceptions about their capacity regarding human resources and management. This paper, overall, sheds light on technological, financial and human resource management practices in developed countries as well as policy and legislation provisions regarding PPP projects.

Keywords: disaster management, policy, private public partnership, projects

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Authors: Constant Akama, Frank Kulor, Frederick Agyemang

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All over the world, due to increasing population, electric power distribution companies are looking for more efficient ways of reading electricity meters. In Ghana, the prepaid metering system was introduced in 2007 to replace the manual system of reading which was fraught with inefficiencies. However, the prepaid system in Ghana is not capable of integration with online systems such as e-commerce platforms and remote monitoring systems. In this paper, we present a design framework for an automatic metering system that can be integrated with e-commerce platforms and remote monitoring systems. The meter was designed using ADE 7755 which reads the energy consumption and the reading is processed by a microcontroller connected to Sim900 General Packet Radio Service module containing a GSM chip provisioned with an Access Point Name. The system also has a billing server and a management server located at the premises of the utility company which communicate with the meter over a Virtual Private Network and GPRS. With this system, customers can buy credit online and the credit will be transferred securely to the meter. Also, when a fault is reported, the utility company can log into the meter remotely through the management server to troubleshoot the problem.

Keywords: access point name, general packet radio service, GSM, virtual private network

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Authors: Ebtissem Sassi, Abdellatif Benabdelhafid, Sami Hammami

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Congestion, pollution and space misuse are the major risks in the hinterland. Management of these risks is a major issue for all the actors intervening in territory management. A good mastery of these risks is based on the consideration of environmental and physical constraints since the implementation of a policy integrates simultaneously an efficient use, territorial resources, and financial resources which become increasingly rare. Yet, this balance can be difficult to establish simultaneously by all the actors. Indeed, every actor has often the tendency to favor these objectives in detriment to others. In this framework, we have fixed the objective of designing and achieving a model which will centralize multidisciplinary data and serve the analysis tool as well as a decision support tool. In this article, we will elaborate some methodological axes allowing the good management of the territory system through (i) determination of the structural factors of the decision support system, (ii) integration of methods tools favoring the territorial decisional process. Logistics territory geographic information system is a model dealing with this issue. The objective of this model is to facilitate the exchanges between the actors around a common question which was the research subject of human sciences researchers (geography, economy), nature sciences (ecology) as well as finding an optimal solution for simultaneous responses to all these objectives.

Keywords: complexity, territory, logistics, territory planning, conceptual model, GIS, MCA

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Authors: Dimitrios Ntardas, Alexandros Tzanetos, Georgios Dounias

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High Voltage Substations (HVS) are the intermediate step between production of power and successfully transmitting it to clients, making them one of the most important checkpoints in power grids. Nowadays - renewable resources and consequently distributed generation are growing fast, the construction of HVS is of high importance both in terms of quality and time completion so that new energy producers can quickly and safely intergrade in power grids. The resources needed, such as machines and workers, should be carefully allocated so that the construction of a HVS is completed on time, with the lowest possible cost (e.g. not spending additional cost that were not taken into consideration, because of project delays), but in the highest quality. In addition, there are milestones and several checkpoints to be precisely achieved during construction to ensure the cost and timeline control and to ensure that the percentage of governmental funding will be granted. The management of such a demanding project is a NP-hard problem that consists of prerequisite constraints and resource limits for each task of the project. In this work, a hybrid meta-heuristic method is implemented to solve this problem. Meta-heuristics have been proven to be quite useful when dealing with high-dimensional constraint optimization problems. Hybridization of them results in boost of their performance.

Keywords: hybrid meta-heuristic methods, substation construction, resource allocation, time-cost efficiency

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Authors: Katawut Kaewbanjong

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We analyzed a volume of data and found significant user satisfaction in software project factors. A statistical significance analysis (logistic regression) and collinearity analysis determined the significance factors from a group of 71 pre-defined factors from 191 software projects in ISBSG Release 12. The eight prediction models used for testing the prediction potential of these factors were Neural network, k-NN, Naïve Bayes, Random forest, Decision tree, Gradient boosted tree, linear regression and logistic regression prediction model. Fifteen pre-defined factors were truly significant in predicting user satisfaction, and they provided 82.71% prediction accuracy when used with a neural network prediction model. These factors were client-server, personnel changes, total defects delivered, project inactive time, industry sector, application type, development type, how methodology was acquired, development techniques, decision making process, intended market, size estimate approach, size estimate method, cost recording method, and effort estimate method. These findings may benefit software development managers considerably.

Keywords: prediction model, statistical analysis, software project, user satisfaction factor

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Authors: Moharram Sharifi

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The purpose of this study was to show how expert and novice writers take positions and stances in Research Articles and Master of Art theses Introductions, so Engagement resources were investigated in 30 Research Articles and 30 Master of Art theses written by Iranian non-native speakers. Through paired samples t-test analysis, we found out that the mean occurrences of heteroglossic items in both RA and Master thesis Introductions were larger than those of monoglossic items, indicating the awareness of both groups of writers to ‘engage’ alternative positions in Introduction sections. The results also revealed that expansive choices were preferred over contractive options in both corpora, implying both groups of writers respect alternative voices cautiously by welcoming rather than closing down the possibility of different perspectives and stances. Furthermore, unlike novice academic writers who used more Attribute features than Entertainment ones in their MATs introduction sections, expert academic writers employed a balanced number of Entertainment and Attribute in their RA introduction sections. The balanced deployment of entertaining and Attribute features in RA Introductions by expert writers might be characteristics of the writers’ demonstration of politeness, which is commonly accepted as an essential feature in academic writing discourse. Finally, through qualitative analysis, it was demonstrated that MAT writers, as novice academic writers, suffered from lacking appropriate evaluative stances and authorial voices toward propositions.

Keywords: novice, expert, engagement, RA Introductions, MA Thesis

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Authors: Amer Rghei

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The Sahara region potentially is one of the most attractive heritage areas in the world. Yet presently, the heritage of the Sahara is currently facing serious planning challenges of underdeveloped and neglected economic and physical potentials. Deterioration of heritage resources has been observed by the author during his several field tours for historic sites has discovered special heritage values such as in Ghadames which combines historic oasis, natural environment along with its exceptional urban fabric and architectural character. Despite the richness of Ghadames with historic significance, it is found that at the present time, Ghadames city, the UNESCO World Heritage site, is facing serious challenges including the abandonment by its tenants and inclusive negligence by its officials. The author believes that Ghadames can illustrate an excellent heritage example in North Africa with cultural pride and socio-economic opportunities that can contribute to overall economic development in the Sahara region. However, the paper deals with the case of Ghadames ‘The World Heritage Site’ in Libya and discusses the current challenges and possible planning for its heritage conservation strategy. The momentous resources in Ghadames with their historical, environmental, economic, social, cultural, and aesthetic values would benefit from a careful heritage planning and management program for its significant values. In this paper an attempt is made to investigate this issue seriously towards building a model of a strategy for heritage conservation planning for Ghadames is proposed.

Keywords: Ghadames, Oasis architecture, Sahara region, heritage environment

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

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Authors: Yue Yang, Qiang Wu, Xingyu Gao

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"Organized research units" have always been an important part of academia. According to the type of organization, there are public research units, university research units, and corporate research units. Existing research has explored the research unit in some depth from several perspectives. However, there is a research gap on the closer interaction between the three from a network perspective and the impact of this interaction on their performance as well as originality. Cliques are a special kind of structure under the concept of cohesive subgroups in the field of social networks, representing particularly tightly knit teams in a network. This study develops the concepts of the diversity of clique types and the diversity of clique geography based on cliques, starting from the diversity of collaborative activities characterized by them. Taking research units as subjects and assigning values to their power in cliques based on occupational age, we explore the impact of clique diversity and clique power on their performance as well as originality and the moderating role of clique relationship strength and structural holes in them. By collecting 9094 articles published in the field of quantum communication at WoSCC over the 15 years 2007-2021, we processed them to construct annual collaborative networks between a total of 533 research units and measured the network characteristic variables using Ucinet. It was found that the type and geographic diversity of cliques promoted the performance and originality of the research units, and the strength of clique relationships positively moderated the positive effect of the diversity of clique types on performance and negatively affected the promotional relationship between the geographic diversity of cliques and performance. It also negatively affected the positive effects of clique-type diversity and clique-geography diversity on originality. Structural holes positively moderated the facilitating effect of both types of factional diversity on performance and originality. Clique power promoted the performance of the research unit, but unfavorably affected its performance on novelty. Faction relationship strength facilitated the relationship between faction rights and performance and showed negative insignificance for clique power and originality. Structural holes positively moderated the effect of clique power on performance and originality.

Keywords: research unit, social networks, clique structure, clique power, diversity

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Authors: Palak Sadhwani, Susie Pryor

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This paper investigates interprofessional collaboration (IPC) in the context of entrepreneurship education. Collaboration has been found to enhance problem solving, leverage expertise, improve resource allocation, and create organizational efficiencies. However, research suggests that successful collaboration is hampered by individual and organizational characteristics. IPC occurs when two or more professionals work together to solve a problem or achieve a common objective. The necessity for this form of collaboration is particularly prevalent in cross-disciplinary fields. In this study, we utilize social exchange theory (SET) to examine IPC in the context of an entrepreneurship living learning community (LLC) at a large university in the Western United States. Specifically, we explore these research questions: How are rules or norms established that govern the collaboration process? How are resources valued and distributed? How are relationships developed and managed among and between parties? LLCs are defined as groups of students who live together in on-campus housing and share similar academic or special interests. In 2007, the Association of American Colleges and Universities named living communities a high impact practice (HIP) because of their capacity to enhance and give coherence to undergraduate education. The entrepreneurship LLC in this study was designed to offer first year college students the opportunity to live and learn with like-minded students from diverse backgrounds. While the university offers other LLC environments, the target residents for this LLC are less easily identified and are less apparently homogenous than residents of other LLCs on campus (e.g., Black Scholars, LatinX, Women in Science and Education), creating unique challenges. The LLC is a collaboration between the university’s College of Business & Public Administration and the Department of Housing and Residential Education (DHRE). Both parties are contributing staff, technology, living and learning spaces, and other student resources. This paper reports the results an ethnographic case study which chronicles the start-up challenges associated with the co-creation of the LLC. SET provides a general framework for examining how resources are valued and exchanged. In this study, SET offers insights into the processes through which parties negotiate tensions resulting from approaching this shared project from very different perspectives and cultures in a novel project environment. These tensions occur due to a variety of factors, including team formation and management, allocation of resources, and differing output expectations. The results are useful to both scholars and practitioners of entrepreneurship education and organizational management. They suggest probably points of conflict and potential paths towards reconciliation.

Keywords: case study, ethnography, interprofessional collaboration, social exchange theory

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Authors: Manasi Roy, Raju Mondal

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During last two decades the synthesis and design of MOFs or novel coordination polymers (CPs) has flourished as an emerging area of research due to their role as functional materials. Accordingly, ten new cobalt-based MOFs have been synthesized using a simple bispyrazole ligand, 4,4′-methylene-bispyrazole (H2MBP), and isophthalic acid (H2IPA) and its four 5-substituted derivatives R-H2IPA (R = COOH, OH, tBu, NH2). The major aim of this study was to validate the mutual influence of temperature and substitutions on the final structural self-assembly. Five different isophthalic acid derivatives were used to study the influence of substituents while each reaction was carried out at two different temperatures to assess the temperature effect. A clear correlation was observed between the reaction temperature and the coordination number of the cobalt atoms which consequently changes the self assembly pattern. Another fact that the periodical change in coordination number did bring about some systematic changes in the structural network via secondary building unit selectivity. With the presence of a tunable cavity inside the network, and unsaturated metal centers, MOFs show highly encouraging photocatalytic degradation of toxic dye with a potential application in waste water purification. Another fascinating aspect of this work is the construction of magnetic coordination polymers with the occurrence of a not-so-common MCE behavior of cobalt-based MOF.

Keywords: MOFs, temperature effect, MCE, dye degradation

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Authors: Gayani Ranawake

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Effective communication is widely regarded as an important aspect of any discipline. This particular study deals with written communication in science. Writing conventions and linguistic choices play a key role in conveying the message effectively to a target audience. Scientists are responsible for conveying their findings or research results not only to their discourse community but also to the general public. Recognizing appropriate linguistic choices is crucial since they vary depending on the target audience. The majority of scientists can communicate effectively with their discourse community, but public engagement seems more challenging to them. There is a lack of research into the language use of scientists, and in particular how it varies by discipline and audience (genre). A better understanding of the different linguistic conventions used in effective science writing by scientists for scientists and by scientists for the public will help to guide scientists who are familiar with their discourse community norms to write effectively for the public. This study investigates the differences and similarities of linguistic choices in biology articles written by scientists for their discourse community and biology magazine articles written by scientists and science communicators for the general public. This study is a part of a larger project investigating linguistic differences in different genres of science academic writing. The sample for this particular study is composed of 20 research articles from the journal Biological Reviews and 20 magazine articles from the magazine Australian Popular Science. Differences in the linguistic devices were analyzed using Hyland’s metadiscourse model for academic writing proposed in 2005. The frequency of the usage of interactive resources (transitions, frame markers, endophoric markers, evidentials and code glosses) and interactional resources (hedges, boosters, attitude markers, self-mentions and engagement markers) were compared and contrasted using the NVivo textual analysis tool. The results clearly show the differences in the frequency of usage of interactional and interactive resources in the two disciplines under investigation. The findings of this study provide a reference guide for scientists and science writers to understand the differences in the linguistic choices between the two genres. This will be particularly helpful for scientists who are proficient at writing for their discourse community, but not for the public.

Keywords: discourse analysis, linguistic choices, metadiscourse, science writing

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Authors: David Oluigbo, Erik Hemberg, Nathan Shwatal, Wenqi Ding, Yin Yuan, Susanna Mierau

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Introduction: Calcium imaging is an established technique in neuroscience research for detecting activity in neural networks. Bursts of action potentials in neurons lead to transient increases in intracellular calcium visualized with fluorescent indicators. Manual identification of cell bodies and their contours by experts typically takes 10-20 minutes per calcium imaging recording. Our aim, therefore, was to design an automated pipeline to facilitate and optimize calcium imaging data analysis. Our pipeline aims to accelerate cell body and contour identification and production of graphical representations reflecting changes in neuronal calcium-based fluorescence. Methods: We created a Python-based pipeline that uses OpenCV (a computer vision Python package) to accurately (1) detect neuron contours, (2) extract the mean fluorescence within the contour, and (3) identify transient changes in the fluorescence due to neuronal activity. The pipeline consisted of 3 Python scripts that could both be easily accessed through a Python Jupyter notebook. In total, we tested this pipeline on ten separate calcium imaging datasets from murine dissociate cortical cultures. We next compared our automated pipeline outputs with the outputs of manually labeled data for neuronal cell location and corresponding fluorescent times series generated by an expert neuroscientist. Results: Our results show that our automated pipeline efficiently pinpoints neuronal cell body location and neuronal contours and provides a graphical representation of neural network metrics accurately reflecting changes in neuronal calcium-based fluorescence. The pipeline detected the shape, area, and location of most neuronal cell body contours by using binary thresholding and grayscale image conversion to allow computer vision to better distinguish between cells and non-cells. Its results were also comparable to manually analyzed results but with significantly reduced result acquisition times of 2-5 minutes per recording versus 10-20 minutes per recording. Based on these findings, our next step is to precisely measure the specificity and sensitivity of the automated pipeline’s cell body and contour detection to extract more robust neural network metrics and dynamics. Conclusion: Our Python-based pipeline performed automated computer vision-based analysis of calcium image recordings from neuronal cell bodies in neuronal cell cultures. Our new goal is to improve cell body and contour detection to produce more robust, accurate neural network metrics and dynamic graphs.

Keywords: calcium imaging, computer vision, neural activity, neural networks

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