Search results for: learning processes

Authors: Gökçen A. Çiftçioğlu, M. A. Neşet Kadırgan, Figen Kadırgan

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Solar energy, since it is available every day, is seen as one of the most valuable renewable energy resources. Thus, the energy of sun should be efficiently used in various applications. The most known applications that use solar energy are heating water and spaces. High efficiency solar collectors need appropriate selective surfaces to absorb the heat. Selective surfaces (Selektif-Sera) used in this study are applied to flat collectors, which are produced by a roll to roll cost effective coating of nano nickel layers, developed in Selektif Teknoloji Co. Inc. Efficiency of flat collectors using Selektif-Sera absorbers are calculated in collaboration with Institute for Solar Technik Rapperswil, Switzerland. The main cause of high energy consumption in industry is mostly caused from low temperature level processes. There is considerable effort in research to minimize the energy use by renewable energy sources such as solar energy. A feasibility study will be presented to obtain the potential of solar thermal energy utilization in the textile industry using these solar collectors. For the feasibility calculations presented in this study, textile dyeing and finishing factory located at Kahramanmaras is selected since the geographic location was an important factor. Kahramanmaras is located in the south east part of Turkey thus has a great potential to have solar illumination much longer. It was observed that, the collector area is limited by the available area in the factory, thus a hybrid heating generating system (lignite/solar thermal) was preferred in the calculations of this study to be more realistic. During the feasibility work, the calculations took into account the preheating process, where well waters heated from 15 °C to 30-40 °C by using the hot waters in heat exchangers. Then the preheated water was heated again by high efficiency solar collectors. Economic comparison between the lignite use and solar thermal collector use was provided to determine the optimal system that can be used efficiently. The optimum design of solar thermal systems was studied depending on the optimum collector area. It was found that the solar thermal system is more economic and efficient than the merely lignite use. Return on investment time is calculated as 5.15 years.

Keywords: Solar energy, heating, solar heating.

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Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, G. Corkery, E. Broderick, J. Walsh

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Farm management and operations will drastically change due to access to real-time data, real-time forecasting and tracking of physical items in combination with Internet of Things (IoT) developments to further automate farm operations. Dairy farms have embraced technological innovations and procured vast amounts of permanent data streams during the past decade; however, the integration of this information to improve the whole farm decision-making process does not exist. It is now imperative to develop a system that can collect, integrate, manage, and analyze on-farm and off-farm data in real-time for practical and relevant environmental and economic actions. The developed systems, based on machine learning and artificial intelligence, need to be connected for useful output, a better understanding of the whole farming issue and environmental impact. Evolutionary Computing (EC) can be very effective in finding the optimal combination of sets of some objects and finally, in strategy determination. The system of the future should be able to manage the dairy farm as well as an experienced dairy farm manager with a team of the best agricultural advisors. All these changes should bring resilience and sustainability to dairy farming as well as improving and maintaining good animal welfare and the quality of dairy products. This review aims to provide an insight into the state-of-the-art of big data applications and EC in relation to smart dairy farming and identify the most important research and development challenges to be addressed in the future. Smart dairy farming influences every area of management and its uptake has become a continuing trend.

Keywords: Big data, evolutionary computing, cloud, precision technologies

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Authors: Kazunori Nomura, Hiromichi Ogi, Masaumi Nakahara, Sou Watanabe, Atsuhiro Shibata

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Chemical Processing Facility of Japan Atomic Energy Agency is a basic research field for advanced back-end technology developments with using actual high-level radioactive materials such as irradiated fuels from the fast reactor, high-level liquid waste from reprocessing plant. In the nature of a research facility, various kinds of chemical reagents have been offered for fundamental tests. Most of them were treated properly and stored in the liquid waste vessel equipped in the facility, but some were not treated and remained at the experimental space as a kind of legacy waste. It is required to treat the waste in safety. On the other hand, we formulated the Medium- and Long-Term Management Plan of Japan Atomic Energy Agency Facilities. This comprehensive plan considers Chemical Processing Facility as one of the facilities to be decommissioned. Even if the plan is executed, treatment of the “legacy” waste beforehand must be a necessary step for decommissioning operation. Under this circumstance, we launched a collaborative research project called the STRAD project, which stands for Systematic Treatment of Radioactive liquid waste for Decommissioning, in order to develop the treatment processes for wastes of the nuclear research facility. In this project, decomposition methods of chemicals causing a troublesome phenomenon such as corrosion and explosion have been developed and there is a prospect of their decomposition in the facility by simple method. And solidification of aqueous or organic liquid wastes after the decomposition has been studied by adding cement or coagulants. Furthermore, we treated experimental tools of various materials with making an effort to stabilize and to compact them before the package into the waste container. It is expected to decrease the number of transportation of the solid waste and widen the operation space. Some achievements of these studies will be shown in this paper. The project is expected to contribute beneficial waste management outcome that can be shared world widely.

Keywords: Chemical Processing Facility, medium- and long-term management plan of JAEA Facilities, STRAD project, treatment of radioactive waste.

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Authors: Chi-Fang Huang, Yun-Shiow Chen, Yun-Kung Chung

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In the past decade, artificial neural networks (ANNs) have been regarded as an instrument for problem-solving and decision-making; indeed, they have already done with a substantial efficiency and effectiveness improvement in industries and businesses. In this paper, the Back-Propagation neural Networks (BPNs) will be modulated to demonstrate the performance of the collaborative forecasting (CF) function of a Collaborative Planning, Forecasting and Replenishment (CPFR®) system. CPFR functions the balance between the sufficient product supply and the necessary customer demand in a Supply and Demand Chain (SDC). Several classical standard BPN will be grouped, collaborated and exploited for the easy implementation of the proposed modular ANN framework based on the topology of a SDC. Each individual BPN is applied as a modular tool to perform the task of forecasting SKUs (Stock-Keeping Units) levels that are managed and supervised at a POS (point of sale), a wholesaler, and a manufacturer in an SDC. The proposed modular BPN-based CF system will be exemplified and experimentally verified using lots of datasets of the simulated SDC. The experimental results showed that a complex CF problem can be divided into a group of simpler sub-problems based on the single independent trading partners distributed over SDC, and its SKU forecasting accuracy was satisfied when the system forecasted values compared to the original simulated SDC data. The primary task of implementing an autonomous CF involves the study of supervised ANN learning methodology which aims at making “knowledgeable" decision for the best SKU sales plan and stocks management.

Keywords: CPFR, artificial neural networks, global logistics, supply and demand chain.

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Authors: Gysele Lima Ricci, Jose Miguel Rodriguez Anton

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Companies in the tourism sector need to achieve competitive advantages for their survival in the market. In this way, the models based on association, cooperation, complementarity, distribution, exchange and mutual assistance arise as a possibility of organizational development, taking as reference the concept of networks. Many companies seek to partner in local networks as clusters to act together and associate. The main objective of the present research is to identify the specificities of management and the practices of cooperation in the tourist destination of São Paulo - Brazil, and to propose a new management model with possible cluster of tourism. The empirical analysis was carried out in three phases. As a first phase, a research was made by the companies, associations and tourism organizations existing in São Paulo, analyzing the characteristics of their business. In the second phase, the management specificities and cooperation practice used in the tourist destination. And in the third phase, identifying the possible strengths and weaknesses that potential or potential tourist cluster could have, proposing the development of the management model of the same adapted to the needs of the companies, associations and organizations. As a main result, it has been identified that companies, associations and organizations could be looking for synergies with each other and collaborate through a Hiperred organizational structure, in which they share their knowledge, try to make the most of the collaboration and to benefit from three concepts: flexibility, learning and collaboration. Finally, it is concluded that, the proposed tourism cluster management model is viable for the development of tourism destinations because it makes it possible to strategically address agents which are responsible for public policies, as well as public and private companies and organizations in their strategies competitiveness and cooperation.

Keywords: Cluster, management model, networks, tourism sector.

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Authors: Živa Ravnikar, Alfonso Bahillo Martinez, Barbara Goličnik Marušić

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Climate change mitigation has been formally adopted and announced by countries over the globe, where cities are targeting carbon neutrality through various more or less successful, systematic, and fragmentary actions. The article is based on the fact that environmental conditions affect human comfort and the usage of space. Urban planning can, with its sustainable solutions, not only support climate mitigation in terms of a planet reduction of global warming but as well enabling natural processes that in the immediate vicinity produce environmental conditions that encourage people to walk or cycle. However, the article draws attention to the importance of integrating climate consideration into urban planning, where detailed environmental data play a key role, enabling urban planners to improve or monitor environmental conditions on cycle paths. In a practical aspect, this paper tests a particular ICT tool, a prototype used for environmental data. Data gathering was performed along the cycling lanes in Ljubljana (Slovenia), where the main objective was to assess the tool's data applicable value within the planning of comfortable cycling lanes. The results suggest that such transportable devices for in-situ measurements can help a researcher interpret detailed environmental information, characterized by fine granularity and precise data spatial and temporal resolution. Data can be interpreted within human comfort zones, where graphical representation is in the form of a map, enabling the link of the environmental conditions with a spatial context. The paper also provides preliminary results in terms of the potential of such tools for identifying the correlations between environmental conditions and different spatial settings, which can help urban planners to prioritize interventions in places. The paper contributes to multidisciplinary approaches as it demonstrates the usefulness of such fine-grained data for better consideration of microclimatology in urban planning, which is a prerequisite for creating climate-comfortable cycling lanes promoting active mobility.

Keywords: Information and communication technology tools, urban planning, human comfort, microclimate, cycling lanes.

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Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: Data mining, ensemble, radial basis function, support vector machine, accuracy.

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores, Valentin Soloiu

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This work describes a system that uses electromyography (EMG) signals obtained from muscle sensors and an Artificial Neural Network (ANN) for signal classification and pattern recognition that is used to control a small unmanned aerial vehicle using specific arm movements. The main objective of this endeavor is the development of an intelligent interface that allows the user to control the flight of a drone beyond direct manual control. The sensor used were the MyoWare Muscle sensor which contains two EMG electrodes used to collect signals from the posterior (extensor) and anterior (flexor) forearm, and the bicep. The collection of the raw signals from each sensor was performed using an Arduino Uno. Data processing algorithms were developed with the purpose of classifying the signals generated by the arm’s muscles when performing specific movements, namely: flexing, resting, and motion of the arm. With these arm motions roll control of the drone was achieved. MATLAB software was utilized to condition the signals and prepare them for the classification. To generate the input vector for the ANN and perform the classification, the root mean square and the standard deviation were processed for the signals from each electrode. The neuromuscular information was trained using an ANN with a single 10 neurons hidden layer to categorize the four targets. The result of the classification shows that an accuracy of 97.5% was obtained. Afterwards, classification results are used to generate the appropriate control signals from the computer to the drone through a Wi-Fi network connection. These procedures were successfully tested, where the drone responded successfully in real time to the commanded inputs.

Keywords: Biosensors, electromyography, Artificial Neural Network, Arduino, drone flight control, machine learning.

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Authors: Teresa Caswell

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Throughout the United States and within a myriad of demographic contexts, students of color experience the results of systemic inequities as an academic outcome. These disparities continue despite the increased resources provided to students and ongoing instruction-focused professional learning received by teachers. We postulated that lower levels of educator cultural competency are an underlying factor of why resource and instructional interventions are less effective than desired. Before implementing any type of intervention, however, cultural competency needed to be confirmed as a factor in schools demonstrating academic disparities between racial subgroups. A needs assessment was designed to measure levels of individual beliefs, including cultural competency, in both principals and teachers at three neighboring schools verified to have academic disparities. The resulting mixed method study utilized the Optimal Theory Applied to Identity Development (OTAID) model to measure cultural competency quantitatively, through self-identity inventory survey items, with teachers and qualitatively, through one-on-one interviews, with each school’s principal. A joint display was utilized to see combined data within and across school contexts. Each school was confirmed to have misalignments between principal and teacher levels of cultural competency beliefs while also indicating that a number of participants in the self-identity inventory survey may have intentionally skipped items referencing the term oppression. Additional use of the OTAID model and self-identity inventory in future research and across contexts is needed to determine transferability and dependability as cultural competency measures.

Keywords: Cultural competency, identity development, mixed method analysis, needs assessment.

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

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

Keywords: Multi-objective decision support, analysis, data validation, freight delivery, multi-modal transportation, genetic programming methods.

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Authors: Prakash Singh

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Many schools throughout the world are facing constant pressure to cope with the violence and drug abuse of learners who show little or no respect for acceptable and desirable social norms. These delinquent learners tend to harbour feelings of being beyond reproach because they strongly believe that it is well within their rights to engage in violent and destructive behaviour. Knives, guns, and other weapons appear to be more readily used by them on the school premises than before. It is known that learners smoke, drink alcohol, and use drugs during school hours, hence, their ability to concentrate, work, and learn, is affected. They become violent and display disruptive behaviour in their classrooms as well as on the school premises, and this atrocious behaviour makes it possible for drug dealers and gangsters to gain access onto the school premises. The primary purpose of this exploratory quantitative study was therefore to establish how tobephobia (TBP), caused by school violence and drug abuse, affects teaching and learning in schools. The findings of this study affirmed that poor discipline resulted in producing poor quality education. Most of the teachers in this study agreed that educating learners who consumed alcohol and other drugs on the school premises resulted in them suffering from TBP. These learners are frequently abusive and disrespectful, and resort to violence to seek attention. As a result, teachers feel extremely demotivated and suffer from high levels of anxiety and stress. The word TBP will surely be regarded as a blessing by many teachers throughout the world because finally, there is a word that will make people sit up and listen to their problems that cause real fear and anxiety in schools.

Keywords: Aims and objectives of quality education, Debilitating effects of tobephobia, Fear of failure associated with education, learners’ violent behaviour and drug abuse.

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Authors: Muhammad Aqil, Ichiro Kita, Moses Macalinao

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Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.

Keywords: Neural Network, Fuzzy, River, Forecasting

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Authors: Ç. Gökçek-Saraç, Ş. Özen, N. Derin

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The N-methyl-D-aspartate (NMDA)-dependent pathway is the major intracellular signaling pathway implemented in both short- and long-term memory formation in the hippocampus which is the most studied brain structure because of its well documented role in learning and memory. However, little is known about the effects of RF-EMR exposure on NMDA receptor signaling pathway including activation of protein kinases, notably Ca²⁺/calmodulin-dependent protein kinase II alpha (CaMKIIα). The aim of the present study was to investigate the effects of acute and chronic 900 MHz RF-EMR exposure on both passive avoidance behaviour and hippocampal levels of CaMKIIα and its phosphorylated form (pCaMKIIα). Rats were divided into the following groups: Sham rats, and rats exposed to 900 MHz RF-EMR for 2 h/day for 1 week (acute group) or 10 weeks (chronic group), respectively. Passive avoidance task was used as a behavioural method. The hippocampal levels of selected kinases were measured using Western Blotting technique. The results of passive avoidance task showed that both acute and chronic exposure to 900 MHz RF-EMR can impair passive avoidance behaviour with minor effects on chronic group of rats. The analysis of western blot data of selected protein kinases demonstrated that hippocampal levels of CaMKIIα and pCaMKIIα were significantly higher in chronic group of rats as compared to acute groups. Taken together, these findings demonstrated that different duration times (1 week vs 10 weeks) of 900 MHz RF-EMR exposure have different effects on both passive avoidance behaviour of rats and hippocampal levels of selected protein kinases.

Keywords: Hippocampus, protein kinase, rat, RF-EMR.

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Authors: Md Rabiul Islam, Ben Wadham

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This paper describes how indigenous students face challenges with various school activities due to inadequate equity and diversity principles in mainstream primary schools in Bangladesh. This study focuses on indigenous students’ interactions with mainstream class teachers and students through teaching-learning activities at public primary schools. Ethnographic research methods guided data collection under a case study methodology in Chittagong Hill Tracts (CHTs) region where maximum indigenous peoples’ inhabitants. The participants (class teachers) shared information through in-depth interviews about their experiences in the four selecting schools. The authors also observed the effects of school activities by use of equity and diversity lens for indigenous students’ situations in those schools. The authors argue that the socio-economic situations of indigenous families are not supportive of the educational development of their children. Similarly, the Bangladesh government does not have enough initiative programs based on equity and diversity principles for fundamental education of indigenous children at rural schools level. Besides this, the conventional teaching system cannot improve the diversification among the students in classrooms. The principles of equity and diversity are not well embedded in professional development of teachers, and using teaching materials in classrooms. The findings suggest that implementing equitable education; there are needed to arrange teachers’ education with equitable knowledge and introducing diversified teaching materials, and implementing teaching through students centered activities that promote the diversification among the multicultural students.

Keywords: Case study research, equity and diversity, Indigenous children.

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Authors: Denise Levy

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Nuclear technology is part of our everyday life and its beneficial applications help to improve the quality of our lives. Nevertheless, in Brazil, most often the media and social networks tend to associate radiation to nuclear weapons and major accidents, and there is still great misunderstanding about the peaceful applications of nuclear science. The Educational Portal Radioatividades (Radioactivities) is a corporate social responsibility initiative that takes advantage of the growing impact of Internet to offer high quality scientific information for teachers and students throughout Brazil. This web-based initiative focusses on the positive applications of nuclear technology, presenting the several contributions of ionizing radiation in different contexts, such as nuclear medicine, agriculture techniques, food safety and electric power generation, proving nuclear technology as part of modern life and a must to improve the quality of our lifestyle. This educational project aims to contribute for democratization of scientific education and social inclusion, approaching society to scientific knowledge, promoting critical thinking and inspiring further reflections. The website offers a wide variety of ludic activities such as curiosities, interactive exercises and short courses. Moreover, teachers are offered free web-based material with full instructions to be developed in class. Since year 2013, the project has been developed and improved according to a comprehensive study about the realistic scenario of ICTs infrastructure in Brazilian schools and in full compliance with the best e-learning national and international recommendations.

Keywords: Information and communication technologies, nuclear technology, science communication, society and education.

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Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as physiological vital signs, images and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful to influence the judgement of clinical sentiment in ICU clinical notes. This paper presents two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of a clinical transformer model that can reliably predict clinical sentiment for notes of COVID patients in ICU. We train the model on clinical notes for COVID-19 patients, ones not previously seen by Bio_ClinicalBERT or Bio_Discharge_Summary_BERT. The model which was based on Bio_ClinicalBERT achieves higher predictive accuracy than the one based on Bio_Discharge_Summary_BERT (Acc 93.33%, AUC 0.98, and Precision 0.96). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and Precision 0.92).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation.

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Authors: Aparajita Santra

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In the context of the government's vision of turning Delhi into a green, privatized and slum free city, giving it a world-class image at par with the global cities of the world, this paper investigates into the various processes and politics of things that went behind defining spaces in the city and attributing an aesthetic image to it. The paper will explore two cases that were forged primarily through the forces of one particular type of power relation. One would be to look at the modernist movement adopted by the Nehruvian government post-independence and the next case will look at special periods like Emergency and Commonwealth games. The study of these cases will help understand the ambivalence embedded in the different rationales of the Government and different powerful agencies adopted in order to build world-classness. Through the study, it will be easier to discern how city spaces were reconfigured in the name of 'good governance'. In this process, it also became important to analyze the double nature of law, both as a protector of people’s rights and as a threat to people. What was interesting to note through the study was that in the process of nation building and creating an image for the city, the government’s policies and programs were mostly aimed at the richer sections of the society and the poorer sections and people from lower income groups kept getting marginalized, subdued, and pushed further away (These marginalized people were pushed away even geographically!). The reconfiguration of city space and attributing an aesthetic character to it, led to an alteration not only in the way in which citizens perceived and engaged with these spaces, but also brought about changes in the way they envisioned their place in the city. Ironically, it was found that every attempt to build any kind of facility for the city’s elite in turn led to an inevitable removal of the marginalized sections of the society as a necessary step to achieve a clean, green and world-class city. The paper questions the claim made by the government for creating a just, equitable city and granting rights to all. An argument is put forth that in the politics of redistribution of space, the city that has been designed is meant for the aspirational middle-class and elite only, who are ideally primed to live in world-class cities. Thus, the aim is to study city spaces, urban form, the associated politics and power plays involved within and understand whether segmented cities are being built in the name of creating sensible, inclusive cities.

Keywords: Aesthetics, ambivalence, governmentality, power, world-class.

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Authors: J. Ritonja

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The biochemical technology has been developing extremely fast since the middle of the last century. The main reason for such development represents a requirement for large production of high-quality biologically manufactured products such as pharmaceuticals, foods, and beverages. The impact of the biochemical industry on the world economy is enormous. The great importance of this industry also results in intensive development in scientific disciplines relevant to the development of biochemical technology. In addition to developments in the fields of biology and chemistry, which enable to understand complex biochemical processes, development in the field of control theory and applications is also very important. In the paper, the control for the biochemical reactor for the milk fermentation was studied. During the fermentation process, the biophysical quantities must be precisely controlled to obtain the high-quality product. To control these quantities, the bioreactor’s stirring drive and/or heating system can be used. Available commercial biochemical reactors are equipped with open loop or conventional linear closed loop control system. Due to the outstanding parameters variations and the partial nonlinearity of the biochemical process, the results obtained with these control systems are not satisfactory. To improve the fermentation process, the self-tuning adaptive control system was proposed. The use of the self-tuning adaptive control is suggested because the parameters’ variations of the studied biochemical process are very slow in most cases. To determine the linearized mathematical model of the fermentation process, the recursive least square identification method was used. Based on the obtained mathematical model the linear quadratic regulator was tuned. The parameters’ identification and the controller’s synthesis are executed on-line and adapt the controller’s parameters to the fermentation process’ dynamics during the operation. The use of the proposed combination represents the original solution for the control of the milk fermentation process. The purpose of the paper is to contribute to the progress of the control systems for the biochemical reactors. The proposed adaptive control system was tested thoroughly. From the obtained results it is obvious that the proposed adaptive control system assures much better following of the reference signal as a conventional linear control system with fixed control parameters.

Keywords: Adaptive control, biochemical reactor, linear quadratic regulator, recursive least square identification.

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Authors: R. B. Ibrahim, M. S. Argungu, I. M. Mungadi

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It is obvious in this present time, internet has become an indispensable part of human life since its inception. The Internet has provided diverse opportunities to make life so easy for human beings, through the adoption of various channels. Among these channels are email, internet banking, video conferencing, and the like. Email is one of the easiest means of communication hugely accepted among individuals and organizations globally. But over decades the security integrity of this platform has been challenged with malicious activities like Phishing. Email phishing is designed by phishers to fool the recipient into handing over sensitive personal information such as passwords, credit card numbers, account credentials, social security numbers, etc. This activity has caused a lot of financial damage to email users globally which has resulted in bankruptcy, sudden death of victims, and other health-related sicknesses. Although many methods have been proposed to detect email phishing, in this research, the results of multiple machine-learning methods for predicting email phishing have been compared with the use of filter-wrapper feature selection. It is worth noting that all three models performed substantially but one outperformed the other. The dataset used for these models is obtained from Kaggle online data repository, while three classifiers: decision tree, Naïve Bayes, and Logistic regression are ensemble (Bagging) respectively. Results from the study show that the Decision Tree (CART) bagging ensemble recorded the highest accuracy of 98.13% using PEF (Phishing Essential Features). This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, hybrid, filter-wrapper, phishing.

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Authors: C. Farinea, A. Conserva, F. Demeur

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Nature has often been something humans have fought against. However, with the changing climate and urban challenges such as air pollution and food shortages, to name but a few, it has never been more crucial to work with nature to find solutions that can help us to adapt to the current planetary situation and mitigate the challenges that we will continue to face in the future. Nature-based solutions (NBS) have been gaining ground as one strategy that can help to create more sustainable solutions for our planet and simultaneously, provide several ecosystem services. As designers, there are a lot of insights that can be extracted and gained from nature. However, nature is a complex and sometimes difficult to predict system and its implementation in cities requires a multidisciplinary knowledge. To keep up with the solutions and prepare the future generations of architects and designers with the skills to be able to implement NBS, educational systems also have to adapt with the times. Architecture is no longer solely about drawing buildings with beautiful forms. It is no longer discipline bound. With the input from different disciplines, the implementation of NBS can be significantly more successful. Transdisciplinary strategies can encourage architects and designers to think beyond their discipline, and ensure the success and realization of the NBS. The paper will demonstrate how transdisciplinary teaching methodologies, including also taking part in participatory processes with experts intended as gathering local knowledge, can be implemented with architectural master students to achieve implementable NBS. Through two projects co-funded by the European Union, strategies such as participatory co-design and transdisciplinary start-ups were implemented into seminars that focused on the development of NBS with a transdisciplinary approach. Within the “Design with Living Systems” seminar, students took part in participatory co-design strategies with experts to design solutions that will be implemented in Porto as part of a healthy corridor, and that respond to the needs of the users and site. On the other hand, within the “Design for Living Systems” seminar, the transdisciplinary start-up approach created start-ups with students of architecture, business and biology focusing on identifying a problem and designing a NBS as a product. Both seminars proved to be successful in achieving implementable NBS through strategies of transdisciplinary education and gave the students the skill sets to be able to work with nature in their future careers.

Keywords: Architectural higher education, digital fabrication, nature-based solutions, transdisciplinary approaches.

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Authors: L. Nekoozad, M. Salehi Barough, B. Salmasian

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Introduction: Some parameters should be considered to investigate the chronic effects of radiation absorption in radiation workers. Trace elements are parameters which small changes in them can cause significant effects on live systems. The role of trace element concentration in human health is significant. These elements play an important role in the developing and functioning of the immune system, cellular respiration, and oxidation processes. Considering the importance and necessity of this issue and few studies, measurements of concentration changes of these elements due to the absorbed dose are important. Purpose: This study aimed to determine the biological effects of occupational dose absorption on plasma and erythrocyte concentration of Zn and Cu in the radiology staff of Tehran Oil Hospital. Material and methods: In this analytical-comparative study, 72 people have entered. 36 people (18 males and 18 females) were selected as radiology staff in the diagnostic and therapeutic departments of Tehran Oil Hospital. And 36 people (18 males and 18 females) were selected as general section staff in the same hospital as a control group. Radiology and control groups’ age and sex were matched. 10 ml of venous blood was taken from all people.  An atomic absorption spectrometer was used to obtain zinc and copper plasma concentrations. Levine test was used to compare these results validity. Results: The mean concentrations of copper and zinc were measured as 0.951 and 0.754 mg/L in the plasma phase and 3.2  and 0.401 mg/L in the RBC phase for the radiology group.  Copper and zinc average concentrations, respectively 0.976 and 0.813 mg/L in the plasma phase and 2.906 and 0.476 mg/L in the RBC phase, were measured for the control group. These elements Concentrations in the plasma phase were significantly different from that of the control group, but the concentrations in the red blood cell phase did not show a significant difference compared to the control group. In comparison, a separate comparison between men and women in the experimental and control groups showed a significant difference in the values of the elements mentioned. With a significant increase in samples, a better justification than the available statistical results can be extracted. Conclusions: Within this study results, chronic occupational probabilistic absorption destructive effects (even within the permitted range) on blood trace element concentration have been confirmed.

Keywords: Chronic absorption, atomic absorption spectrometry, radiology staff, trace element concentration.

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Authors: Charbel Geryes Aoun, Loic Lagadec

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A Sensor Network (SN) is considered as an operation of two phases: (1) the observation/measuring, which means the accumulation of the gathered data at each sensor node; (2) transferring the collected data to some processing center (e.g. Fusion Servers) within the SN. Therefore, an underwater sensor network can be defined as a sensor network deployed underwater that monitors underwater activity. The deployed sensors, such as hydrophones, are responsible for registering underwater activity and transferring it to more advanced components. The process of data exchange between the aforementioned components perfectly defines the Marine Observatory (MO) concept which provides information on ocean state, phenomena and processes. The first step towards the implementation of this concept is defining the environmental constraints and the required tools and components (Marine Cables, Smart Sensors, Data Fusion Server, etc). The logical and physical components that are used in these observatories perform some critical functions such as the localization of underwater moving objects. These functions can be orchestrated with other services (e.g. military or civilian reaction). In this paper, we present an extension to our MO meta-model that is used to generate a design tool (ArchiMO). We propose constraints to be taken into consideration at design time. We illustrate our proposal with an example from the MO domain. Additionally, we generate the corresponding simulation code using our self-developed domain-specific model compiler. On the one hand, this illustrates our approach in relying on Enterprise Architecture (EA) framework that respects: multiple-views, perspectives of stakeholders, and domain specificity. On the other hand, it helps reducing both complexity and time spent in design activity, while preventing from design modeling errors during porting this activity in the MO domain. As conclusion, this work aims to demonstrate that we can improve the design activity of complex system based on the use of MDE technologies and a domain-specific modeling language with the associated tooling. The major improvement is to provide an early validation step via models and simulation approach to consolidate the system design.

Keywords: Smart sensors, data fusion, distributed fusion architecture, sensor networks, domain specific modeling language, enterprise architecture, underwater moving object, localization, marine observatory, NS-3, IMS.

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Authors: A. Giani

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The current pedagogical culture recognizes an educational scope within the sports practices. It is widely accepted, in the pedagogical culture, that thanks to the acquisition and development of motor skills, it is also possible to exercise abilities that concern the way of facing and managing the difficulties of everyday life. Sport is a peculiar educational environment: the children have the opportunity to discover the possibilities of their body, to correlate with their peers, and to learn how to manage the rules and the relationship with authorities, such as coaches. Educational aspects of the sport concern both non-formal and formal educational environments. Coaches play a critical role in an agonistic sphere: exactly like the competencies developed by the children, coaches have to work on their skills to properly set up the educational scene. Facing these new educational tasks - which are not new per se, but new because they are brought back to awareness - a few questions arise: does the coach have adequate preparation? Is the training of the coach in this specific area appropriate? This contribution aims to explore the issue in depth by focusing on the reality of the Football School. Starting from a possible sense of pedagogical inadequacy detected during a series of meetings with several football clubs in Piedmont (Italy), there have been highlighted some important educational needs within the professional training of sports coaches. It is indeed necessary for the coach to know the processes underlying the educational relationship in order to better understand the centrality of the assessment during the educational intervention and to be able to manage the asymmetry in the coach-athlete relationship. In order to provide a response to these pedagogical needs, a formative plan has been designed to allow both an in-depth study of educational issues and a correct self-evaluation of certain pedagogical skills’ control levels, led by the coach. This plan has been based on particular practices, the Educational Practices of Pre-test (EPP), a specific version of community practices designed for the extracurricular activities. The above-mentioned practices realized through the use of texts meant as pre-tests, promoted a reflection within the group of coaches: they set up real and plausible sports experiences - in particular football, triggering a reflection about the relationship’s object, spaces, and methods. The characteristic aspect of pre-tests is that it is impossible to anticipate the reflection as it is necessarily connected to the personal experience and sensitivity, requiring a strong interest and involvement by participants: situations must be considered by the coaches as possible settings in which they could be found on the field.

Keywords: Relational needs, responsibility, self-evaluation, values.

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Authors: Siripen Yiamjanya, Kevin Wongleedee

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This research paper aims to identify travel motivation by push and pull factors that affected decision making of international tourists in selecting Thailand as their destination choice. A total of 200 international tourists who traveled to Thailand during January and February, 2014 were used as the sample in this study. A questionnaire was employed as a tool in collecting the data, conducted in Bangkok. The list consisted of 30 attributes representing both psychological factors as “push- based factors” and destination factors as “pull-based factors”. Mean and standard deviation were used in order to find the top ten travel motives that were important determinants in the respondents’ decision making process to select Thailand as their destination choice. The finding revealed the top ten travel motivations influencing international tourists to select Thailand as their destination choice included [i] getting experience in foreign land; [ii] Thai food; [iii] learning new culture; [iv] relaxing in foreign land; [v] wanting to learn new things; [vi] being interested in Thai culture, and traditional markets; [vii] escaping from same daily life; [viii] enjoying activities; [ix] adventure; and [x] good weather. Classification of push- based and pull- based motives suggested that getting experience in foreign land was the most important push motive for international tourists to travel, while Thai food portrayed its highest significance as pull motive. Discussion and suggestions were also made for tourism industry of Thailand.

Keywords: Decision Making, Destination Choice, International Tourist, Pull Factor, Push Factor, Thailand, Travel Motivation.

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Authors: Mustafa M. Donma, Orkide Donma

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A growing list of cancers might be influenced by obesity. Obesity is associated with an increased risk for the occurrence and development of some cancers. Inflammation can lead to cancer. It is one of the characteristic features of cancer and plays a critical role in cancer development. C-reactive protein (CRP) is under evaluation related to the new and simple prognostic factors in patients with metastatic renal cell cancer. Obesity can predict and promote systemic inflammation in healthy adults. BMI is correlated with hs-CRP. In this study, SII index and CRP values were evaluated in children with normal BMI and those within the range of different obesity grades to detect the tendency towards cancer in pediatric obesity. A total of one hundred and ninety-four children; thirty-five children with normal BMI, twenty overweight (OW), forty-seven obese (OB) and ninety-two morbid obese (MO) participated in the study. Age- and sex-matched groups were constituted using BMI-for age percentiles. Informed consent was obtained. Ethical Committee approval was taken. Weight, height, waist circumference (C), hip C, head C and neck C of the children were measured. The complete blood count test was performed. C-reactive protein analysis was performed. Statistical analyses were performed using SPSS. The degree for statistical significance was p≤0.05. SII index values were progressively increasing starting from normal weight (NW) to MO children. There is a statistically significant difference between NW and OB as well as MO children. No significant difference was observed between NW and OW children, however, a correlation was observed between NW and OW children. MO constitutes the only group, which exhibited a statistically significant correlation between SII index and CRP. Obesity-related bladder, kidney, cervical, liver, colorectal, endometrial cancers are still being investigated. Obesity, characterized as a chronic low-grade inflammation, is a crucial risk factor for colon cancer. Elevated childhood BMI values may be indicative of processes leading to cancer, initiated early in life. Prevention of childhood adiposity may decrease the cancer incidence in adults. To authors’ best knowledge, this study is the first to introduce SII index values during obesity of varying degrees of severity. It is suggested that this index seems to affect all stages of obesity with an increasing tendency and may point out the concomitant status of obesity and cancer starting from very early periods of life.

Keywords: Children, c- reactive protein, systemic immune-inflammation index, obesity.

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Authors: Alexandre Boum, Salomon Madinatou

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This paper aims at bringing a scientific contribution to the cardiac arrhythmia biomedical diagnosis systems; more precisely to the study of the amelioration of cardiac arrhythmia classification performance using artificial neural network, adaptive neuro-fuzzy and fuzzy inference systems classifiers. The purpose of this amelioration is to enable cardiologists to make reliable diagnosis through automatic cardiac arrhythmia analyzes and classifications based on high confidence classifiers. In this study, six classes of the most commonly encountered arrhythmias are considered: the Right Bundle Branch Block, the Left Bundle Branch Block, the Ventricular Extrasystole, the Auricular Extrasystole, the Atrial Fibrillation and the Normal Cardiac rate beat. From the electrocardiogram (ECG) extracted parameters, we constructed a matrix (360x360) serving as an input data sample for the classifiers based on neural networks and a matrix (1x6) for the classifier based on fuzzy logic. By varying three parameters (the quality of the neural network learning, the data size and the quality of the input parameters) the automatic classification permitted us to obtain the following performances: in terms of correct classification rate, 83.6% was obtained using the fuzzy logic based classifier, 99.7% using the neural network based classifier and 99.8% for the adaptive neuro-fuzzy based classifier. These results are based on signals containing at least 360 cardiac cycles. Based on the comparative analysis of the aforementioned three arrhythmia classifiers, the classifiers based on neural networks exhibit a better performance.

Keywords: Adaptive neuro-fuzzy, artificial neural network, cardiac arrythmias, fuzzy inference systems.

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Authors: Sharan Badiger, Prema T. Akkasaligar, Patil LS, Manish Patel, Biradar MS

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Human immunodeficiency virus infection and acquired immunodeficiency syndrome is a global pandemic with cases reporting from virtually every country and continues to be a common infection in developing country like India. Microalbuminuria is a manifestation of human immunodeficiency virus associated nephropathy. Therefore, microalbuminuria may be an early marker of human immunodeficiency virus associated nephropathy, and screening for its presence may be beneficial. A strikingly high prevalence of microalbuminuria among human immunodeficiency virus infected patients has been described in various studies. Risk factors for clinically significant proteinuria include African - American race, higher human immunodeficiency virus ribonucleic acid level and lower CD4 lymphocyte count. The cardiovascular risk factors of increased systolic blood pressure and increase fasting blood sugar level are strongly associated with microalbuminuria in human immunodeficiency virus patient. These results suggest that microalbuminuria may be a sign of current endothelial dysfunction and micro-vascular disease and there is substantial risk of future cardiovascular disease events. Positive contributing factors include early kidney disease such as human immunodeficiency virus associated nephropathy, a marker of end organ damage related to co morbidities of diabetes or hypertension, or more diffuse endothelial cells dysfunction. Nevertheless after adjustment for non human immunodeficiency virus factors, human immunodeficiency virus itself is a major risk factor. The presence of human immunodeficiency virus infection is independent risk to develop microalbuminuria in human immunodeficiency virus patient. Cardiovascular risk factors appeared to be stronger predictors of microalbuminuria than markers of human immunodeficiency virus severity person with human immunodeficiency virus infection and microalbuminuria therefore appear to potentially bear the burden of two separate damage related to known vascular end organ damage related to know vascular risk factors, and human immunodeficiency virus specific processes such as the direct viral infection of kidney cells.The higher prevalence of microalbuminuria among the human immunodeficiency virus infected could be harbinger of future increased risks of both kidney and cardiovascular disease. Further study defining the prognostic significance of microalbuminuria among human immunodeficiency virus infected persons will be essential. Microalbuminuria seems to be a predictor of cardiovascular disease in diabetic and non diabetic subjects, hence it can also be used for early detection of micro vascular disease in human immunodeficiency virus positive patients, thus can help to diagnose the disease at the earliest.

Keywords: Acquired immunodeficiency syndrome, Human immunodeficiency virus, Microalbuminuria.

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Authors: Sreejith Jayachandran, Mojtaba Ghodsi, Morteza Mohammadzaheri

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The modern busy world is running behind new embedded technologies based on computers and software meanwhile some people are unable to monitor their health condition and regular medical check-ups. Some of them postpone medical check-ups due to a lack of time and convenience while others skip these regular evaluations and medical examinations due to huge medical bills and hospital expenses. In this research, we present a device in the telemonitoring system capable of monitoring, checking, and evaluating the health status of the human body remotely through the internet for the needs of all kinds of people. The remote health monitoring device is a microcontroller-based embedded unit. The various types of sensors in this device are connected to the human body, and with the help of an Arduino UNO board, the required analogue data are collected from the sensors. The microcontroller on the Arduino board processes the analogue data collected in this way into digital data and transfers that information to the cloud and stores it there; the processed digital data are then instantly displayed through the LCD attached to the machine. By accessing the cloud storage with a username and password, the concerned person’s health care teams/doctors, and other health staff can collect these data for the assessment and follow-up of that patient. Besides that, the family members/guardians can use and evaluate these data for awareness of the patient's current health status. Moreover, the system is connected to a GPS module. In emergencies, the concerned team can be positioning the patient or the person with this device. The setup continuously evaluates and transfers the data to the cloud and also the user can prefix a normal value range for the evaluation. For example, the blood pressure normal value is universally prefixed between 80/120 mmHg. Similarly, the Remote Health Monitoring System (RHMS) is also allowed to fix the range of values referred to as normal coefficients. This IoT-based miniature system 11×10×10 cm3 with a low weight of 500 gr only consumes 10 mW. This smart monitoring system is manufactured for 100 GBP (British Pound Sterling), and can facilitate the communication between patients and health systems, but also it can be employed for numerous other uses including communication sectors in the aerospace and transportation systems.

Keywords: Embedded Technology, Telemonitoring system, Microcontroller, Arduino UNO, Cloud storage, GPS, RHMS, Remote Health Monitoring System, Alert system.

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Authors: Tholokuhle T. Ntshakala, Seraphin D. Eyono Obono

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Nations are still finding it quite difficult to win mega sport competitions despite the major contribution of sport to society in terms of social and economic development, personal health, and in education. Even though the world of sports has been transformed into a huge global economy, it is important to note that the first step of sport is usually its introduction to children at school through physical education or PE. In other words, nations who do not win mega sport competitions also suffer from a weak and neglected PE system. This problem of the neglect of PE systems is the main motivation of this research aimed at examining the factors affecting the perceived awareness of physical education teachers on the ICTs that are adoptable for the teaching and learning of physical education. Two types of research objectives will materialize this aim: relevant theories will be identified in relation to the analysis of the perceived ICT awareness of PE teachers and subsequent models will be compiled and designed from existing literature; the empirical testing of such theories and models will also be achieved through the survey of PE teachers from the Camperdown magisterial district of the KwaZulu-Natal province of South Africa. The main hypothesis at the heart of this study is the relationship between the demographics of PE teachers, their behavior both as individuals and as social entities, and their perceived awareness of the ICTs that are adoptable for PE, as postulated by existing literature; except that this study categorizes human behavior under performance expectancy, computer attitude, and social influence. This hypothesis was partially confirmed by the survey conducted by this research in the sense that performance expectancy and teachers’ age, gender, computer usage, and class size were found to be the only factors affecting their awareness of ICTs for physical education.

Keywords: Human Behavior, ICT Awareness, Physical Education, Teachers.

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Authors: Adebisi. Elizabeth, Banjo

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Language and culture are interwoven that they cannot be separated, for the knowledge of a language cannot be complete without having the culture of the language. Indigenous food is a cultural aspect of any language that is expected to be acquired by all the speakers of the language. Indigenous food is known to be vital right from early years, which is also attributed to the healthy living of the ancient people. However it is discovered that the indigenous food is almost being replaced by fast food products such as Indomie noodles, Spaghetti and Macaroni to the extent that majority of the young folks prefer the eating of the fast foods and cannot prepare the indigenous foods which are good for growth and healthy living of people. Therefore, there is need to revitalize and re-educate people on the indigenous food which is an aspect of inter-cultural education of any language to prevent it from being forgotten or neglected.

African foods are many, but this study focused on Nigerian food using some Yoruba dishes as a case study. Examples of Yoruba dishes are pounded yam and melon with vegetable and dried fish soup, beans pudding (moin moin) and pap (eko), water yam pudding with fish and meat (ikokore) and many more. The ingredients needed for the preparation of these indigenous foods contain some basic food nutrients which will be analyzed and their nutritional importance to human bodies will also be discussed.

The process of re- awakening the education of indigenous food to the present and up-coming generation should be via print and electronic media in form of advertisements on posters, billboards, calendars and in rhymes on television programs, radio presentations, video tapes and CD–ROM apart from classroom teaching and learning. Indigenous food is a panacea to healthy living and longevity, a prevention of diseases and a means of accelerated healing of the body through natural foods.

Keywords: Indigenous food, print and electronic media, nutritional values, re-awakening education.

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