Search results for: learning quality

Authors: Fakhrullah Sarwari, Hiroko Ono

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Kabul city has suffered a lot in 40 years of conflict of civil war and “The war on terror”. After the invasion of Afghanistan by the United States of America and its allies in 2001, the Taliban was removed from operational power, but The Taliban and other terrorist groups remained in remote areas of the country, they started suicide attacks and bombings. Hence to protect from these attacks officials surrounded their office buildings and houses with concrete blast walls. It gives a bad landscape to the city and creates traffic congestions. Our research contains; questionnaire, reviewing Kabul Municipality documents and literature review. Questionnaires were distributed to Kabul citizens to find out how people feel by seeing the T-Walls on Kabul streets? And what problems they face with T-Walls. “The T-Walls pull down commission” of Kabul Municipality documents were reviewed to find out what caused the failure of this commission. A literature review has been done to compare Kabul with Washington D.C on how they designed the city against terrorism threat without turning the cities into lock down. Bogota city of Columbia urban happiness movement is reviewed and compared with Kabul. The finding of research revealed that citizens of Kabul want security but not at the expense of public realm and creating the architecture of fear. It also indicates that increasing the T-walls do not give secure feeling but instead; it increases terror, hatred and affect people’s optimism. At the end, a series of recommendation is suggested on the issue.

Keywords: Anti-terror design, Kabul, T-Walls, urban happiness.

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Authors: Ahmed Barakat, Nourhan A. Saad, Mahmoud Hammad

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Tracking and monitoring agricultural products, cold chain activities, and transportation in real-time can effectively ensure both the quality and safety of agricultural products, as well as reduce overall logistics costs. Effective supply chain practices are one of the main requirements for enhancing agricultural business in Egypt. Cold chain is among the best practices for the storage and transportation of perishable goods and has potential within the agricultural sector in Egypt. This practice has the scope of reducing the wastage of food and increasing the profitability with a reduction in costs. Even though it has several implementation challenges for the farmers, traders, and people involved in the entire supply chain, it has highlighted better benefits for all and for the export of goods for the economic progression for Egypt. The aim of this paper is to explore cold supply chain practices for the agriculture sector in Egypt, to enhance the export performance of fresh goods. In this context, this study attempts to explore those aspects of the performance of cold supply chain practices that can enhance the functioning of the agriculture sector in Egypt from the perspective of export companies (traders) and farmers. Based on the empirical results obtained by data collection from the farmers and traders, the study argues that there is a significant association between cold supply chain practices and enhancement of the agriculture value chain. The paper thus highlights the contribution of the study with final conclusions and limitations with scope for future research.

Keywords: Agriculture sector, cold chain management, export companies, non-traded goods, supply chain management.

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Authors: Danielle Shackley, Yetunde Folajimi

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As more people turn to the internet seeking health related information, there is more risk of finding false, inaccurate, or dangerous information. Sentiment analysis is a natural language processing technique that assigns polarity scores of text, ranging from positive, neutral and negative. In this research, we evaluate the weight of a sentiment analysis feature added to fake health news classification models. The dataset consists of existing reliably labeled health article headlines that were supplemented with health information collected about COVID-19 from social media sources. We started with data preprocessing, tested out various vectorization methods such as Count and TFIDF vectorization. We implemented 3 Naive Bayes classifier models, including Bernoulli, Multinomial and Complement. To test the weight of the sentiment analysis feature on the dataset, we created benchmark Naive Bayes classification models without sentiment analysis, and those same models were reproduced and the feature was added. We evaluated using the precision and accuracy scores. The Bernoulli initial model performed with 90% precision and 75.2% accuracy, while the model supplemented with sentiment labels performed with 90.4% precision and stayed constant at 75.2% accuracy. Our results show that the addition of sentiment analysis did not improve model precision by a wide margin; while there was no evidence of improvement in accuracy, we had a 1.9% improvement margin of the precision score with the Complement model. Future expansion of this work could include replicating the experiment process, and substituting the Naive Bayes for a deep learning neural network model.

Keywords: Sentiment analysis, Naive Bayes model, natural language processing, topic analysis, fake health news classification model.

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Authors: Adel M. Sharaf, Foad H. Gandoman

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Nowadays, Photovoltaic-PV Farms/ Parks and large PV-Smart Grid Interface Schemes are emerging and commonly utilized in Renewable Energy distributed generation. However, PVhybrid- Dc-Ac Schemes using interface power electronic converters usually has negative impact on power quality and stabilization of modern electrical network under load excursions and network fault conditions in smart grid. Consequently, robust FACTS based interface schemes are required to ensure efficient energy utilization and stabilization of bus voltages as well as limiting switching/fault onrush current condition. FACTS devices are also used in smart grid- Battery Interface and Storage Schemes with PV-Battery Storage hybrid systems as an elegant alternative to renewable energy utilization with backup battery storage for electric utility energy and demand side management to provide needed energy and power capacity under heavy load conditions. The paper presents a robust interface PV-Li-Ion Battery Storage Interface Scheme for Distribution/Utilization Low Voltage Interface using FACTS stabilization enhancement and dynamic maximum PV power tracking controllers. Digital simulation and validation of the proposed scheme is done using MATLAB/Simulink software environment for Low Voltage- Distribution/Utilization system feeding a hybrid Linear-Motorized inrush and nonlinear type loads from a DC-AC Interface VSC-6- pulse Inverter Fed from the PV Park/Farm with a back-up Li-Ion Storage Battery.

Keywords: AC FACTS, Smart grid, Stabilization, PV-Battery Storage, Switched Filter-Compensation (SFC).

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Authors: Mahmood Reza Shakarami, Reza Sedaghati

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Electricity market activities and a growing demand for electricity have led to heavily stressed power systems. This requires operation of the networks closer to their stability limits. Power system operation is affected by stability related problems, leading to unpredictable system behavior. Voltage stability refers to the ability of a power system to sustain appropriate voltage levels through large and small disturbances. Steady-state voltage stability is concerned with limits on the existence of steady-state operating points for the network. FACTS devices can be utilized to increase the transmission capacity, the stability margin and dynamic behavior or serve to ensure improved power quality. Their main capabilities are reactive power compensation, voltage control and power flow control. Among the FACTS controllers, Static Var Compensator (SVC) provides fast acting dynamic reactive compensation for voltage support during contingency events. In this paper, voltage stability assessment with appropriate representations of tap-changer transformers and SVC is investigated. Integrating both of these devices is the main topic of this paper. Effect of the presence of tap-changing transformers on static VAR compensator controller parameters and ratings necessary to stabilize load voltages at certain values are highlighted. The interrelation between transformer off nominal tap ratios and the SVC controller gains and droop slopes and the SVC rating are found. P-V curves are constructed to calculate loadability margins.

Keywords: SVC, voltage stability, P-V curve, reactive power, tap changing transformer.

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Authors: Do Thi Ha, Khanitta Nuntaboot

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Background: Competency of nurses is vital to safe nursing practice as well as essential component to drive quality of nursing services. There exists little up to date information concerning actual competency among Vietnamese nurses. Purposes: The purpose of this study is to identify the actual nursing competency among nurses in clinical settings in Vietnam. Methods: A qualitative study, ethnographic method, comprised of the participant-observation, in-depth interview, and focus group discussion with multidisciplinary groups of nurses employing in Cho Ray hospital, Vietnam, managers/administrators, nurse teachers, medical doctors, other health care providers, patients and family members which derived from purposeful sampling technique. Content analysis was used for data analysis. Results: Five essential themes of nursing competencies among nurses were identified include (1) knowledge, (2) skills, (3) attitude and value-based nursing practice, (4) legal and ethical competencies, and (5) transcultural competencies. Basic and advanced knowledge were identified as further two dimensions of knowledge. There were five sub themes identified as further dimensions of skills include technical skills, communication skills, organizing and management skills, teamwork and interrelationship, and critical thinking skills. Conclusions: The findings from this study provide valuable information and understanding of the actual competency among nurses in clinical settings in Vietnam. It is expected that this understanding would assist in developing a guide to nursing education and training, nursing practice and relevant policy regulation used for promoting nursing competency among nurses.

Keywords: Nursing competency, qualitative design, ethnographic method, Vietnam.

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Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian

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Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.

Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.

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Authors: Mohsen Soori, Fooad Karimi Ghaleh Jough

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The integration of Artificial Intelligence (AI) techniques in the optimization of steel moment frame structures represents a transformative approach to enhance the design, analysis, and performance of these critical engineering systems. The review encompasses a wide spectrum of AI methods, including machine learning algorithms, evolutionary algorithms, neural networks, and optimization techniques, applied to address various challenges in the field. The synthesis of research findings highlights the interdisciplinary nature of AI applications in structural engineering, emphasizing the synergy between domain expertise and advanced computational methodologies. This synthesis aims to serve as a valuable resource for researchers, practitioners, and policymakers seeking a comprehensive understanding of the state-of-the-art in AI-driven optimization for steel moment frame structures. The paper commences with an overview of the fundamental principles governing steel moment frame structures and identifies the key optimization objectives, such as efficiency of structures. Subsequently, it delves into the application of AI in the conceptual design phase, where algorithms aid in generating innovative structural configurations and optimizing material utilization. The review also explores the use of AI for real-time structural health monitoring and predictive maintenance, contributing to the long-term sustainability and reliability of steel moment frame structures. Furthermore, the paper investigates how AI-driven algorithms facilitate the calibration of structural models, enabling accurate prediction of dynamic responses and seismic performance. Thus, by reviewing and analyzing the recent achievements in applications artificial intelligent in optimization of steel moment frame structures, the process of designing, analysis, and performance of the structures can be analyzed and modified.

Keywords: Artificial Intelligent, optimization process, steel moment frame, structural engineering.

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Authors: Ml. López-Moreno, Le. Lugo Avilés, Fr. Román, J. Lugo Rosas, Ja. Hernández-Viezcas, Jr. Peralta-Videa, Jl. Gardea-Torresdey

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Degradation of agricultural soils has increased rapidly during the last 20 years due to the indiscriminate use of pesticides and other anthropogenic activities. Currently, there is an urgent need of soil restoration to increase agricultural production. Utilization of sewage sludge or municipal solid waste is an important way to recycle nutrient elements and improve soil quality. With these amendments, nutrient availability in the aqueous phase might be increased and production of healthier crops can be accomplished. This research project aimed to achieve sustainable management of tropical agricultural soils, specifically in Puerto Rico, through the amendment of water treatment plant sludge’s. This practice avoids landfill disposal of sewage sludge and at the same time results costeffective practice for recycling solid waste residues. Coriander sativum was cultivated in a compost-soil-sludge mixture at different proportions. Results showed that Coriander grown in a mixture of 25% compost+50% Voladora soi+25% sludge had the best growth and development. High chlorophyll content (33.01 ± 0.8) was observed in Coriander plants cultivated in 25% compost+62.5% Coloso soil+ 12.5% sludge compared to plants grown with no sludge (32.59 ± 0.7). ICP-OES analysis showed variations in mineral element contents (macro and micronutrients) in coriander plant grown I soil amended with sludge and compost.

Keywords: Compost, Coriandrum sativum, nutrients, waste sludge.

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Authors: Michaela Skulinova, Wanping Zheng, Yan-Ru Hu, Yvan Soucy

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Space exploration is a highly visible endeavour of humankind to seek profound answers to questions about the origins of our solar system, whether life exists beyond Earth, and how we could live on other worlds. Different platforms have been utilized in planetary exploration missions, such as orbiters, landers, rovers, and penetrators. Having low mass, good mechanical contact with the surface, ability to acquire high quality scientific subsurface data, and ability to be deployed in areas that may not be conducive to landers or rovers, Penetrators provide an alternative and complimentary solution that makes possible scientific exploration of hardly accessible sites (icy areas, gully sites, highlands etc.). The Canadian Space Agency (CSA) has put space exploration as one of the pillars of its space program, and established ExCo program to prepare Canada for future international planetary exploration. ExCo sets surface mobility as its focus and priority, and invests mainly in the development of rovers because of Canada's niche space robotics technology. Meanwhile, CSA is also investigating how micro-penetrators can help Canada to fulfill its scientific objectives for planetary exploration. This paper presents a review of the micro-penetrator technologies, past missions, and lessons learned. It gives a detailed analysis of the technical challenges of micro-penetrators, such as high impact survivability, high precision guidance navigation and control, thermal protection, communications, and etc. Then, a Canadian perspective of a possible micro-penetrator mission is given, including Canadian scientific objectives and priorities, potential instruments, and flight opportunities.

Keywords: micro-penetrator, CSA, planetary exploration

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Authors: E. Soboleva, E. Sergachyova, S. G. Davydenko, T. V. Meledina

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Problem of food preservation is extremely important for mankind. Viscous damage ("illness") of bread results from development of Bacillus spp. bacteria. High temperature resistant spores of this microorganism are steady against 120°C) and remain in bread during pastries, potentially causing spoilage of the final product. Scientists are interested in further characterization of bread spoiling Bacillus spp. species. Our aim was to find weather yeast Saccharomyces cerevisiae strains that are able to produce natural antimicrobial killer factor can preserve bread illness. By diffusion method, we showed yeast antagonistic activity against spore-forming bacteria. Experimental technological parameters were the same as for bakers' yeasts production on the industrial scale. Risograph test during dough fermentation demonstrated gas production. The major finding of the study was a clear indication of the presence of killer yeast strain antagonistic activity against rope in bread causing bacteria. After demonstrating antagonistic effect of S. cerevisiae on bacteria using solid nutrient medium, we tested baked bread under provocative conditions. We also measured formation of carbon dioxide in the dough, dough-making duration and quality of the final products, when using different strains of S. cerevisiae. It is determined that the use of yeast S. cerevisiae RCAM 01730 killer strain inhibits appearance of rope in bread. Thus, natural yeast antimicrobial killer toxin, produced by some S. cerevisiae strains is an anti-rope in bread protector.

Keywords: Bakers' yeasts, rope in bread, Saccharomyces cerevisiae.

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Authors: Jindřiška Šedová

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In the past 20 years the economy of the Czech Republic has experienced substantial changes. In the 1990s the development was affected by the transformation which sought to establish the right conditions for privatization and creation of elementary market relations. In the last decade the characteristic elements such as private ownership and corresponding institutional framework have been strengthened. This development was marked by the accession of the Czech Republic to the EU. The Czech Republic is striving to reduce the difference between its level of economic development and the quality of institutional framework in comparison with other developed countries. The process of finding the adequate solutions has been hampered by the negative impact of the world financial crisis on the Czech Republic and the standard of living of its inhabitants. This contribution seeks to address the question of whether and to which extent the economic development of the transitive Czech economy is affected by the change in behaviour of households and their tendency to consumption, i.e. in the sense of reduction or increase in demand for goods and services. It aims to verify whether the increasing trend of household indebtedness and decreasing trend of saving pose a significant risk in the Czech Republic. At a general level the analysis aims to contribute to finding an answer to the question of whether the debt increase of Czech households is connected to the risk of "eating through" the borrowed money and whether Czech households risk falling into a debt trap. In addition to household indebtedness risks in the Czech Republic the analysis will focus on identification of specifics of the transformation phase of the Czech economy in comparison with the EU countries, or selected OECD countries.

Keywords: household indebtedness, household consumption, credits, financial literacy

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Authors: Javier Romera, Alberto Justo, Ignacio Fidalgo, Javier Araluce, Joshué Pérez

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Nowadays, individuals with mobility needs face a significant challenge when docking vehicles. In many cases, after parking, they encounter insufficient space to exit, leading to two undesired outcomes: either avoiding parking in that spot or settling for improperly placed vehicles. To address this issue, this paper presents a parking control system employing gestural teleoperation. The system comprises three main phases: capturing body markers, interpreting gestures, and transmitting orders to the vehicle. The initial phase is centered around the MediaPipe framework, a versatile tool optimized for real-time gesture recognition. MediaPipe excels at detecting and tracing body markers, with a special emphasis on hand gestures. Hands detection is done by generating 21 reference points for each hand. Subsequently, after data capture, the project employs the MultiPerceptron Layer (MPL) for in-depth gesture classification. This tandem of MediaPipe’s extraction prowess and MPL’s analytical capability ensures that human gestures are translated into actionable commands with high precision. Furthermore, the system has been trained and validated within a built-in dataset. To prove the domain adaptation, a framework based on the Robot Operating System 2 (ROS2), as a communication backbone, alongside CARLA Simulator, is used. Following successful simulations, the system is transitioned to a real-world platform, marking a significant milestone in the project. This real-vehicle implementation verifies the practicality and efficiency of the system beyond theoretical constructs.

Keywords: Gesture detection, MediaPipe, MultiLayer Perceptron Layer, Robot Operating System.

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Authors: Meng Fanchao, Zhan Dechen, Xu Xiaofei

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Software reuse can be considered as the most realistic and promising way to improve software engineering productivity and quality. Automated assistance for software reuse involves the representation, classification, retrieval and adaptation of components. The representation and retrieval of components are important to software reuse in Component-Based on Software Development (CBSD). However, current industrial component models mainly focus on the implement techniques and ignore the semantic information about component, so it is difficult to retrieve the components that satisfy user-s requirements. This paper presents a method of business component retrieval based on specification matching to solve the software reuse of enterprise information system. First, a business component model oriented reuse is proposed. In our model, the business data type is represented as sign data type based on XML, which can express the variable business data type that can describe the variety of business operations. Based on this model, we propose specification match relationships in two levels: business operation level and business component level. In business operation level, we use input business data types, output business data types and the taxonomy of business operations evaluate the similarity between business operations. In the business component level, we propose five specification matches between business components. To retrieval reusable business components, we propose the measure of similarity degrees to calculate the similarities between business components. Finally, a business component retrieval command like SQL is proposed to help user to retrieve approximate business components from component repository.

Keywords: Business component, business operation, business data type, specification matching.

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Authors: A. A. Aiyeloja, A.T. Oladele, O. Tumulo

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Raphia wine is an important forest product with cultural significance besides its use as medicine and food in southern Nigeria. This work aims to evaluate the profitability of Raphia wine production and marketing in Sapele Local Government Area, Nigeria. Four communities (Sapele, Ogiede, Okuoke and Elume) were randomly selected for data collection via questionnaires among producers and marketers. A total of 50 producers and 34 marketers were randomly selected for interview. Data was analyzed using descriptive statistics, profit margin, multiple regression and rate of returns on investment (RORI). Annual average profit was highest in Okuoke (Producers – N90, 000.00, Marketers - N70, 000.00) and least in Sapele (Producers N50, 000.00, Marketers – N45, 000.00). Calculated RORI for marketers were Elume (40.0%), Okuoke (25.0%), Ogiede (33.3%) and Sapele (50.0%). Regression results showed that location has significant effects (0.000, ρ ≤ 0.05) on profit margins. Male (58.8%) and female (41.2%) invest in Raphia wine marketing, while males (100.0%) dominate production. Results showed that Raphia wine has potentials to generate household income, enhance food security and improve quality of life in rural, semi-urban and urban communities. Improved marketing channels, storage facilities and credit facilities via cooperative groups are recommended for producers and marketers by concerned agencies.

Keywords: Raphia wine, Profit margin, RORI, Livelihood, Nigeria.

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Authors: Tasneem Halawani, Yamen Khateeb

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With customers’ ever-increasing expectations for fast services provisioning for all their business needs, information technology (IT) organizations, as business partners, have to cope with this demanding environment and deliver their services in the most effective and efficient way. The purpose of this paper is to identify optimization and automation opportunities for the top requested IT services in a heterogenic digital environment and widely spread customer base. In collaboration with systems, processes, and subject matter experts (SMEs), the processes in scope were approached by analyzing four-year related historical data, identifying and surveying stakeholders, modeling the as-is processes, and studying systems integration/automation capabilities. This effort resulted in identifying several pain areas, including standardization, unnecessary customer and IT involvement, manual steps, systems integration, and performance measurement. These pain areas were addressed by standardizing the top five requested IT services, eliminating/automating 43 steps, and utilizing a single platform for end-to-end process execution. In conclusion, the optimization of IT service request processes in a heterogenic digital environment and widely spread customer base is challenging, yet achievable without compromising the service quality and customers’ added value. Further studies can focus on measuring the value of the eliminated/automated process steps to quantify the enhancement impact. Moreover, a similar approach can be utilized to optimize other IT service requests, with a focus on business criticality.

Keywords: Automation, customer value, heterogenic, integration, IT services, optimization, processes.

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Authors: Dongseok Cho, Mitchell Driedger, Sera Han, Noman Khan, Mohammed Elmorsy, Mohamad El-Hajj

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Since the approval of the COVID-19 vaccine in late 2020, vaccination rates have varied around the globe. Access to a vaccine supply, mandated vaccination policy, and vaccine hesitancy contribute to these rates. This study used COVID-19 vaccination data from Our World in Data and the Multilateral Leaders Task Force on COVID-19 to create two COVID-19 vaccination indices. The first index is the Vaccine Utilization Index (VUI), which measures how effectively each country has utilized its vaccine supply to doubly vaccinate its population. The second index is the Vaccination Acceleration Index (VAI), which evaluates how efficiently each country vaccinated their populations within their first 150 days. Pearson correlations were created between these indices and country indicators obtained from the World Bank. Results of these correlations identify countries with stronger Health indicators such as lower mortality rates, lower age-dependency ratios, and higher rates of immunization to other diseases display higher VUI and VAI scores than countries with lesser values. VAI scores are also positively correlated to Governance and Economic indicators, such as regulatory quality, control of corruption, and GDP per capita. As represented by the VUI, proper utilization of the COVID-19 vaccine supply by country is observed in countries that display excellence in health practices. A country’s motivation to accelerate its vaccination rates within the first 150 days of vaccinating, as represented by the VAI, was largely a product of the governing body’s effectiveness and economic status, as well as overall excellence in health practises.

Keywords: Data mining, Pearson Correlation, COVID-19, vaccination rates, hesitancy.

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Authors: Gülden Küçükakça, Şefika Dilek Güven, Rahşan Kolutek, Seçil Taylan

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Objective: Nursing students face with stress factors affecting academic performance and quality of life as from first moments of their educational life. Stress causes health problems in students such as physical, psycho-social, and behavioral disorders and might damage formation of professional identity by decreasing efficiency of education. In addition to determination of stress experienced by nursing students during their education, it was aimed to help review theoretical and clinical education settings for bringing stress of nursing students into positive level and to raise awareness of educators concerning their own professional behaviors. Methods: The study was conducted with 315 students studying at nursing department of Semra and Vefa Küçük Health High School, Nevşehir Hacı Bektaş Veli University in the academic year of 2015-2016 and agreed to participate in the study. “Personal Information Form” prepared by the researchers upon the literature review and “Nursing Education Stress Scale (NESS)” were used in this study. Data were assessed with analysis of variance and correlation analysis. Results: Mean NESS Scale score of the nursing students was estimated to be 66.46±16.08 points. Conclusions: As a result of this study, stress level experienced by nursing undergraduate students during their education was determined to be high. In accordance with this result, it can be recommended to determine sources of stress experienced by nursing undergraduate students during their education and to develop approaches to eliminate these stress sources.

Keywords: Stress, nursing education, nursing student, nursing education stress.

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Authors: Bakari M. M. Mwinyiwiwa, Mighanda J. Manyahi, Nicodemu Gregory, Alex L. Kyaruzi

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Microgrids are increasingly being considered to provide electricity for the expanding energy demand in the grid distribution network and grid isolated areas. However, the technical challenges associated with the operation and controls are immense. Management of dynamic power balances, power flow, and network voltage profiles imposes unique challenges in the context of microgrids. Stability of the microgrid during both grid-connected and islanded mode is considered as the major challenge during its operation. Traditional control methods have been employed are based on the assumption of linear loads. For instance the concept of PQ, voltage and frequency control through decoupled PQ are some of very useful when considering linear loads, but they fall short when considering nonlinear loads. The deficiency of traditional control methods of microgrid suggests that more research in the control of microgrids should be done. This research aims at introducing the dq technique concept into decoupled PQ for dynamic load demand control in inverter interfaced DG system operating as isolated LV microgrid. Decoupled PQ in exact mathematical formulation in dq frame is expected to accommodate all variations of the line parameters (resistance and inductance) and to relinquish forced relationship between the DG variables such as power, voltage and frequency in LV microgrids and allow for individual parameter control (frequency and line voltages). This concept is expected to address and achieve accurate control, improve microgrid stability and power quality at all load conditions.

Keywords: Decoupled PQ, microgrid, multisource, renewable energy, dq control.

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Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti

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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.

Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.

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Authors: Jagadish H. Pujar, Pallavi S. Gurjal, Shambhavi D. S, Kiran S. Kunnur

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Medical image segmentation based on image smoothing followed by edge detection assumes a great degree of importance in the field of Image Processing. In this regard, this paper proposes a novel algorithm for medical image segmentation based on vigorous smoothening by identifying the type of noise and edge diction ideology which seems to be a boom in medical image diagnosis. The main objective of this algorithm is to consider a particular medical image as input and make the preprocessing to remove the noise content by employing suitable filter after identifying the type of noise and finally carrying out edge detection for image segmentation. The algorithm consists of three parts. First, identifying the type of noise present in the medical image as additive, multiplicative or impulsive by analysis of local histograms and denoising it by employing Median, Gaussian or Frost filter. Second, edge detection of the filtered medical image is carried out using Canny edge detection technique. And third part is about the segmentation of edge detected medical image by the method of Normalized Cut Eigen Vectors. The method is validated through experiments on real images. The proposed algorithm has been simulated on MATLAB platform. The results obtained by the simulation shows that the proposed algorithm is very effective which can deal with low quality or marginal vague images which has high spatial redundancy, low contrast and biggish noise, and has a potential of certain practical use of medical image diagnosis.

Keywords: Image Segmentation, Image smoothing, Edge Detection, Impulsive noise, Gaussian noise, Median filter, Canny edge, Eigen values, Eigen vector.

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Authors: M. C. Pardo-Ferreira, J. C. Rubio-Romero, M. Martínez-Rojas

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Resilience Engineering is a new paradigm of safety management that proposes to change the way of managing the safety to focus on the things that go well instead of the things that go wrong. Many complex and high-risk sectors such as air traffic control, health care, nuclear power plants, railways or emergencies, have applied this new vision of safety and have obtained very positive results. In the construction sector, safety management continues to be a problem as indicated by the statistics of occupational injuries worldwide. Therefore, it is important to improve safety management in this sector. For this reason, it is proposed to apply Resilience Engineering to the construction sector. The Construction Phase Health and Safety Plan emerges as a key element for the planning of safety management. One of the key tools of Resilience Engineering is the Resilience Assessment Grid that allows measuring the four essential abilities (respond, monitor, learn and anticipate) for resilient performance. The purpose of this paper is to develop a questionnaire based on the Resilience Assessment Grid, specifically on the ability to learn, to assess whether a Construction Phase Health and Safety Plans helps companies in a construction site to implement this ability. The research process was divided into four stages: (i) initial design of a questionnaire, (ii) validation of the content of the questionnaire, (iii) redesign of the questionnaire and (iii) application of the Delphi method. The questionnaire obtained could be used as a tool to help construction companies to evolve from Safety-I to Safety-II. In this way, companies could begin to develop the ability to learn, which will serve as a basis for the development of the other abilities necessary for resilient performance. The following steps in this research are intended to develop other questions that allow evaluating the rest of abilities for resilient performance such as monitoring, learning and anticipating.

Keywords: Resilience engineering, construction sector, resilience assessment grid, construction phase health and safety plan.

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Authors: Bahram Khan, Anderson Rocha Ramos, Rui R. Paulo, Fernando J. Velez

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With the growing demand for a new blend of applications, the users dependency on the internet is increasing day by day. Mobile internet users are giving more attention to their own experiences, especially in terms of communication reliability, high data rates and service stability on move. This increase in the demand is causing saturation of existing radio frequency bands. To address these challenges, researchers are investigating the best approaches, Carrier Aggregation (CA) is one of the newest innovations, which seems to fulfill the demands of the future spectrum, also CA is one the most important feature for Long Term Evolution - Advanced (LTE-Advanced). For this purpose to get the upcoming International Mobile Telecommunication Advanced (IMT-Advanced) mobile requirements (1 Gb/s peak data rate), the CA scheme is presented by 3GPP, which would sustain a high data rate using widespread frequency bandwidth up to 100 MHz. Technical issues such as aggregation structure, its implementations, deployment scenarios, control signal techniques, and challenges for CA technique in LTE-Advanced, with consideration of backward compatibility, are highlighted in this paper. Also, performance evaluation in macro-cellular scenarios through a simulation approach is presented, which shows the benefits of applying CA, low-complexity multi-band schedulers in service quality, system capacity enhancement and concluded that enhanced multi-band scheduler is less complex than the general multi-band scheduler, which performs better for a cell radius longer than 1800 m (and a PLR threshold of 2%).

Keywords: Component carrier, carrier aggregation, LTE-Advanced, scheduling, spectrum management.

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Authors: Ek-Uma Imkome, Jintana Yunibhand, Waraporn Chaiyawat

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Background: Persons with schizophrenia patient and misusing methamphetamines suffering from social dysfunction that impact on their quality of life. Knowledge of factors related to social dysfunction will guide the effective intervention. Objectives: To determine the direct effect, indirect effect and total effect of an acerbate Psychotics’ Symptoms, Social Support, Stressful life events, Medication use self-efficacy impact on social dysfunction in Thai schizophrenic patient and methamphetamine misuse. Methods: Data were collected from schizophrenic and methamphetamine misuse patient by self report. A linear structural relationship was used to test the hypothesized path model. Results: The hypothesized model was found to fit the empirical data and explained 54% of the variance of the psychotic symptoms (X² = 114.35, df = 92, p-value = 0.05, X² /df = 1.24, GFI = 0.96, AGFI = 0.92, CFI = 1.00, NFI = 0.99, NNFI = 0.99, RMSEA = 0.02). The highest total effect on social dysfunction was psychotic symptoms (0.67, p<0.05). Medication use self-efficacy had a direct effect on psychotic symptoms (-0.25, p<0.01), and social support had direct effect on medication use self efficacy (0.36, p <0.01). Conclusions: Psychotic symptoms and stressful life events were the significance factors that influenced direct on social dysfunctioning. Therefore, interventions that are designed to manage these factors are crucial in order to enhance social functioning in this population.

Keywords: Psychotic symptoms, methamphetamine, schizophrenia, stressful life events, social dysfunction, social support, medication use self-efficacy.

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Authors: G. Tamanza, A. Bossoni

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84 deaf students (from primary school to college) and their families participated in this inclusion project in cooperation with numerous institutions in northern Italy (Brescia-Lombardy). Participants were either congenitally deaf or their deafness was related to other pathologies. This research promoted the integration of deaf students as they pass from primary school to high school to college. Learning methods and processes were studied that focused on encour­aging individual autonomy and socialization. The research team and its collaborators included school teachers, speech ther­apists, psychologists and home tutors, as well as teaching assistants, child neuropsychiatrists and other external authorities involved with deaf persons social inclusion programs. Deaf children and their families were supported, in terms of inclusion, and were made aware of the research team that focused on the Bisogni Educativi Speciali (BES or Special Educational Needs) (L.170/2010 - DM 5669/2011). This project included a diagnostic and evaluative phase as well as an operational one. Results demonstrated that deaf children were highly satisfied and confident; academic performance improved and collaboration in school increased. Deaf children felt that they had access to high school and college. Empowerment for the families of deaf children in terms of networking among local services that deal with the deaf also improved while family satisfaction also improved. We found that teachers and those who gave support to deaf children increased their professional skills. Achieving autonomy, instrumental, communicative and relational abilities were also found to be crucial. Project success was determined by temporal continuity, clear theoretical methodology, strong alliance for the project direction and a resilient team response.

Keywords: Autonomy, inclusion, skills, well-being.

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Authors: Citlali Aguilera Lira, David Lynch Steinicke, Andrea León Garcia

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One of the challenges that higher education faces is to find how to approach the sustainability in an inclusive way to the student within all the different academic areas, how to move the sustainable development from the abstract field to the operational field. This research comes from the ecoliteracy and the pedagogical praxis as tools for rebuilding the teaching processes inside of universities. The purpose is to determine and describe which are the factors involved in the process of learning particularly in the Greenhouse-School Siembra UV. In the Greenhouse-School Siembra UV, of the University of Veracruz, are cultivated vegetables, medicinal plants and small cornfields under the usage of eco-technologies such as hydroponics, Wickingbed and Hugelkultur, which main purpose is the saving of space, labor and natural resources, as well as function as agricultural production alternatives in the urban and periurban zones. The sample was formed with students from different academic areas and who are actively involved in the greenhouse, as well as institutes from the University of Veracruz and governmental and nongovernmental departments. This project comes from a pedagogic praxis approach, from filling the needs that the different professional profiles of the university students have. All this with the purpose of generate a pragmatic dialogue with the sustainability. It also comes from the necessity to understand the factors that intervene in the students’ praxis. In this manner is how the students are the fundamental unit in the sphere of sustainability. As a result, it is observed that those University of Veracruz students who are involved in the Greenhouse-school, Siembra UV, have enriched in different levels the sense of urban and periurban agriculture because of the diverse academic approaches they have and the interaction between them. It is concluded that the ecotechnologies act as fundamental tools for ecoliteracy in society, where it is strengthen the nutritional and food security from a sustainable development approach.

Keywords: Farming eco-technologies, food security, multidisciplinary, pedagogical praxis.

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Authors: Wardoyo, Humairoh

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In global competition nowadays, the world economy heavily depends upon high technology and capital intensive industries that are mainly owned by well-established economic and developed countries, such as United States of America, United Kingdom, Japan, and South Korea. Indonesia as a developing country is building its economic activities towards industrial country as well, although a slightly different approach was implemented. For example, similar to the concept of one village one product (OVOP) implemented in Japan, Indonesia also adopted this concept by promoting local traditional products to improve incomes of village people and to enhance local economic activities. Analysis on how OVOP program increase local people’s income and influence customer satisfaction were the objective of this paper. Behavioral intention to purchase and re-purchase, customer satisfaction and promotion are key factors for local products to play significant roles in improving local income and economy of the region. The concepts of OVOP and key factors that influence economic activities of local people and the region will be described and explained in the paper. Results of research, in a case study based on 300 respondents, customers of a local restaurant at Tangerang City, Banten Province of Indonesia, indicated that local product, service quality and behavioral intention individually have significant influence to customer satisfaction; whereas simultaneous tests to the variables indicated positive and significant influence to the behavioral intention through customer satisfaction as the intervening variable.

Keywords: Behavioral intention, customer satisfaction, local products, one village one product.

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Authors: Paula A. Cruise, Carvell McLeary

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Employee turnover leads to lowered productivity, decreased morale and work quality, and psychological effects associated with employee separation and replacement. Yet, it remains unknown why talented employees willingly withdraw from organizations. This uncertainty is worsened as studies; a) priorities organizational over individual predictors resulting in restriction in range in turnover measurement; b) focus on actual rather than intended turnover thereby limiting conceptual understanding of the turnover construct and its relationship with other variables and; c) produce inconsistent findings across cultures, contexts and industries despite a clear need for a unified perspective. The current study addressed these gaps by adopting the theory of planned behavior (TPB) framework to examine socio-cognitive factors in organizational trust and individual turnover intentions among bankers and energy employees in Jamaica. In a comparative study of n=369 [n_bank= 264; male=57 (22.73%); n_energy =105; male =45 (42.86)], it was hypothesized that organizational trust was a predictor of employee turnover intention, and the effect of individual, group, cognitive and socio-affective variables varied across industry. Findings from structural equation modelling confirmed the hypothesis, with a model of both cognitive and socio-affective variables being a better fit [CMIN (χ²) = 800.067, df = 364, p ≤ .000; CFI = 0.950; RMSEA = 0.057 with 90% C.I. (0.052 - 0.062); PCLOSE = 0.016; PNFI = 0.818 in predicting turnover intention. The findings are discussed in relation to socio-cognitive components of trust models and predicting negative employee behaviors across cultures and industries.

Keywords: Context-specific organizational trust, cross-cultural psychology, theory of planned behavior, employee turnover intention.

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Authors: Raghavi Janaswamy, Saraswathi K. Vasudev

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Music is ubiquitous in human lives. Ever since the foetus hears the sound inside the mother’s womb and later upon birth the baby experiences alluring sounds, the curiosity of learning emanates and evokes exploration. Music is an education than a mere entertainment. The intricate balance between music, education and entertainment has well been recognized by the scientific community and is being explored as a viable tool to understand and improve the human cognition. There are seven basic swaras (notes) Sa, Ri, Ga, Ma, Pa, Da and Ni in the Carnatic music system that are analogous to C, D, E, F, G, A and B of the western system. The Carnatic music builds on the conscious use of microtones, gamakams (oscillation) and rendering styles that evolved over centuries and established its stance. The complex but erudite raga system has been designed with elaborate experiments on srutis (musical sounds) and human perception abilities. In parallel, ‘rasa’- the emotions evoked by certain srutis and hence the ragas been solidified along with the power of language in combination with the musical sounds. The Carnatic music branches out as Kalpita sangeetam (pre-composed music) and Manodharma sangeetam (improvised music). This article explores the Manodharma sangeetam and its subdivisions such as raga alapana, swara kalpana, neraval and ragam-tanam-pallavi (RTP). The intrinsic mathematical strategies in its practice methods toward improvising the music have been discussed in detail with concert examples. The techniques on swara weaving for swara kalpana rendering and methods on the alapana development are also discussed at length with an emphasis on the impact on the human cognitive abilities. The articulation of the outlined conscious practice methods not only helps to leave a long-lasting melodic impression on the listeners but also onsets cognitive developments.

Keywords: Carnatic, Manodharmam, music cognition, Alapana.

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Authors: Saeid Haghjoo, Ebrahim Reyhani, Fahimeh Kolahdouz

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The present study aimed to evaluate the understanding of the students in Tehran universities (Iran) about the numerical representation of the average rate of change based on the Structure of Observed Learning Outcomes (SOLO). In the present descriptive-survey research, the statistical population included undergraduate students (basic sciences and engineering) in the universities of Tehran. The samples were 604 students selected by random multi-stage clustering. The measurement tool was a task whose face and content validity was confirmed by math and mathematics education professors. Using Cronbach's Alpha criterion, the reliability coefficient of the task was obtained 0.95, which verified its reliability. The collected data were analyzed by descriptive statistics and inferential statistics (chi-squared and independent t-tests) under SPSS-24 software. According to the SOLO model in the prestructural, unistructural, and multistructural levels, basic science students had a higher percentage of understanding than that of engineering students, although the outcome was inverse at the relational level. However, there was no significant difference in the average understanding of both groups. The results indicated that students failed to have a proper understanding of the numerical representation of the average rate of change, in addition to missconceptions when using physics formulas in solving the problem. In addition, multiple solutions were derived along with their dominant methods during the qualitative analysis. The current research proposed to focus on the context problems with approximate calculations and numerical representation, using software and connection common relations between math and physics in the teaching process of teachers and professors.

Keywords: Average rate of change, context problems, derivative, numerical representation, SOLO taxonomy.

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